Sample records for analysis price uncertainty

  1. Uncertainty analysis of an aviation climate model and an aircraft price model for assessment of environmental effects

    E-Print Network [OSTI]

    Jun, Mina

    2007-01-01T23:59:59.000Z

    Estimating, presenting, and assessing uncertainties are important parts in assessment of a complex system. This thesis focuses on the assessment of uncertainty in the price module and the climate module in the Aviation ...

  2. Application of price uncertainty quantification models and their impacts on project evaluations 

    E-Print Network [OSTI]

    Fariyibi, Festus Lekan

    2006-10-30T23:59:59.000Z

    This study presents an analysis of several recently published methods for quantifying the uncertainty in economic evaluations due to uncertainty in future oil prices. Conventional price forecasting methods used in the industry typically...

  3. Application of price uncertainty quantification models and their impacts on project evaluations

    E-Print Network [OSTI]

    Fariyibi, Festus Lekan

    2006-10-30T23:59:59.000Z

    This study presents an analysis of several recently published methods for quantifying the uncertainty in economic evaluations due to uncertainty in future oil prices. Conventional price forecasting methods used in the industry typically...

  4. Uncertainty analysis

    SciTech Connect (OSTI)

    Thomas, R.E.

    1982-03-01T23:59:59.000Z

    An evaluation is made of the suitability of analytical and statistical sampling methods for making uncertainty analyses. The adjoint method is found to be well-suited for obtaining sensitivity coefficients for computer programs involving large numbers of equations and input parameters. For this purpose the Latin Hypercube Sampling method is found to be inferior to conventional experimental designs. The Latin hypercube method can be used to estimate output probability density functions, but requires supplementary rank transformations followed by stepwise regression to obtain uncertainty information on individual input parameters. A simple Cork and Bottle problem is used to illustrate the efficiency of the adjoint method relative to certain statistical sampling methods. For linear models of the form Ax=b it is shown that a complete adjoint sensitivity analysis can be made without formulating and solving the adjoint problem. This can be done either by using a special type of statistical sampling or by reformulating the primal problem and using suitable linear programming software.

  5. Uncertainty Analysis Economic Evaluations

    E-Print Network [OSTI]

    Bhulai, Sandjai

    uncertainties in typical oil and gas projects: 1. The oil price, 2. The investments (capex) and operating expenses (opex) for the project, 3. The number of wells and associated capex to recover the reserves, 4

  6. A REACTIVE APPROACH FOR MINING PROJECT EVALUATION UNDER PRICE UNCERTAINTY

    E-Print Network [OSTI]

    Duffy, Ken

    A REACTIVE APPROACH FOR MINING PROJECT EVALUATION UNDER PRICE UNCERTAINTY Meimei Zhang. This method often undervalues a mining project since it ignores future price uncertainty and does not allow on metal price. This paper also demonstrates that the "reactive" approach can estimate the mine project

  7. Analysis of Strategies of Companies under Carbon Constraint: Relationship between Profit Structure of Companies and Carbon/Fuel Price Uncertainty

    E-Print Network [OSTI]

    Hashimoto, Susumu

    This paper examines the relationship between future carbon prices and the expected profit of companies by case studies with model companies. As the future carbon price will vary significantly in accordance with the political ...

  8. Developments of the Price equation and natural selection under uncertainty

    E-Print Network [OSTI]

    Grafen, Alan

    success, following Darwin (1859). Here, this project is pursued by developing the Price equation, ¢rstDevelopments of the Price equation and natural selection under uncertainty Alan Grafen Department to employ these approaches. Here, a new theore- tical development arising from the Price equation provides

  9. Sandia National Laboratories: Uncertainty Analysis

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Experimental Testing Phenomenological Modeling Risk and Safety Assessment Cyber-Based Vulnerability Assessments Uncertainty Analysis Transportation Safety Fire Science Human...

  10. Uncertainty and calibration analysis

    SciTech Connect (OSTI)

    Coutts, D.A.

    1991-03-01T23:59:59.000Z

    All measurements contain some deviation from the true value which is being measured. In the common vernacular this deviation between the true value and the measured value is called an inaccuracy, an error, or a mistake. Since all measurements contain errors, it is necessary to accept that there is a limit to how accurate a measurement can be. The undertainty interval combined with the confidence level, is one measure of the accuracy for a measurement or value. Without a statement of uncertainty (or a similar parameter) it is not possible to evaluate if the accuracy of the measurement, or data, is appropriate. The preparation of technical reports, calibration evaluations, and design calculations should consider the accuracy of measurements and data being used. There are many methods to accomplish this. This report provides a consistent method for the handling of measurement tolerances, calibration evaluations and uncertainty calculations. The SRS Quality Assurance (QA) Program requires that the uncertainty of technical data and instrument calibrations be acknowledged and estimated. The QA Program makes some specific technical requirements related to the subject but does not provide a philosophy or method on how uncertainty should be estimated. This report was prepared to provide a technical basis to support the calculation of uncertainties and the calibration of measurement and test equipment for any activity within the Experimental Thermal-Hydraulics (ETH) Group. The methods proposed in this report provide a graded approach for estimating the uncertainty of measurements, data, and calibrations. The method is based on the national consensus standard, ANSI/ASME PTC 19.1.

  11. Short-Term Energy Outlook Supplement: Energy Price Volatility and Forecast Uncertainty

    Reports and Publications (EIA)

    2009-01-01T23:59:59.000Z

    It is often noted that energy prices are quite volatile, reflecting market participants' adjustments to new information from physical energy markets and/or markets in energy-related financial derivatives. Price volatility is an indication of the level of uncertainty, or risk, in the market. This paper describes how markets price risk and how the marketclearing process for risk transfer can be used to generate "price bands" around observed futures prices for crude oil, natural gas, and other commodities.

  12. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01T23:59:59.000Z

    capita terms. When crude oil prices are used, these are theprices are driven by oil prices, moreover, and oil isby ‡uctuations in the crude oil price. The overall mean real

  13. Sandia Energy - Uncertainty Analysis

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del Sol Home DistributionTransportation Safety Home Stationary PowerUncertainty

  14. Effects of the Uncertainty about Global Economic Recovery on Energy Transition and CO2 Price

    E-Print Network [OSTI]

    Durand-Lasserve, Olivier

    This paper examines the impact that uncertainty over economic growth may have on global energy transition and CO2 prices. We use a general-equilibrium model derived from MERGE, and define several stochastic scenarios for ...

  15. SSL Pricing and Efficacy Trend Analysis for Utility Program Planning...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Market-Based Programs Technical Information Network SSL Pricing and Efficacy Trend Analysis for Utility Program Planning SSL Pricing and Efficacy Trend Analysis for Utility...

  16. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01T23:59:59.000Z

    World crude oil and natural gas: a demand and supply model.analysis of the demand for oil in the Middle East. EnergyEstimates elasticity of demand for crude oil, not gasoline.

  17. Uncertainty quantification and error analysis

    SciTech Connect (OSTI)

    Higdon, Dave M [Los Alamos National Laboratory; Anderson, Mark C [Los Alamos National Laboratory; Habib, Salman [Los Alamos National Laboratory; Klein, Richard [Los Alamos National Laboratory; Berliner, Mark [OHIO STATE UNIV.; Covey, Curt [LLNL; Ghattas, Omar [UNIV OF TEXAS; Graziani, Carlo [UNIV OF CHICAGO; Seager, Mark [LLNL; Sefcik, Joseph [LLNL; Stark, Philip [UC/BERKELEY; Stewart, James [SNL

    2010-01-01T23:59:59.000Z

    UQ studies all sources of error and uncertainty, including: systematic and stochastic measurement error; ignorance; limitations of theoretical models; limitations of numerical representations of those models; limitations on the accuracy and reliability of computations, approximations, and algorithms; and human error. A more precise definition for UQ is suggested below.

  18. 5, 45074543, 2005 Uncertainty analysis

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    parameterization, the representation of the in-cloud updraft velocity, the relationship between effective radius10 of the study of aerosol effects on the global climate, uncertainty in the estimation of the indirect aerosol the aerosol chemical and physical properties and cloud microphysics. Aerosols influence cloud radiative

  19. Uncertainty analysis of multi-rate kinetics of uranium desorption...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Uncertainty analysis of multi-rate kinetics of uranium desorption from sediments. Uncertainty analysis of multi-rate kinetics of uranium desorption from sediments. Abstract: A...

  20. Uncertainty Analysis for Photovoltaic Degradation Rates (Poster)

    SciTech Connect (OSTI)

    Jordan, D.; Kurtz, S.; Hansen, C.

    2014-04-01T23:59:59.000Z

    Dependable and predictable energy production is the key to the long-term success of the PV industry. PV systems show over the lifetime of their exposure a gradual decline that depends on many different factors such as module technology, module type, mounting configuration, climate etc. When degradation rates are determined from continuous data the statistical uncertainty is easily calculated from the regression coefficients. However, total uncertainty that includes measurement uncertainty and instrumentation drift is far more difficult to determine. A Monte Carlo simulation approach was chosen to investigate a comprehensive uncertainty analysis. The most important effect for degradation rates is to avoid instrumentation that changes over time in the field. For instance, a drifting irradiance sensor, which can be achieved through regular calibration, can lead to a substantially erroneous degradation rates. However, the accuracy of the irradiance sensor has negligible impact on degradation rate uncertainty emphasizing that precision (relative accuracy) is more important than absolute accuracy.

  1. Bayesian Environmetrics: Uncertainty and Sensitivity Analysis

    E-Print Network [OSTI]

    Draper, David

    (joint work with Bruno Mendes) Department of Applied Mathematics and Statistics University of California and analysis of variance tools provide sensitivity analysis insight. -- Model uncertainty audit shows, as an energy source, has been employed in the United States and Europe for more than 50 years, and yet

  2. Extended Forward Sensitivity Analysis for Uncertainty Quantification

    SciTech Connect (OSTI)

    Haihua Zhao; Vincent A. Mousseau

    2011-09-01T23:59:59.000Z

    Verification and validation (V&V) are playing more important roles to quantify uncertainties and realize high fidelity simulations in engineering system analyses, such as transients happened in a complex nuclear reactor system. Traditional V&V in the reactor system analysis focused more on the validation part or did not differentiate verification and validation. The traditional approach to uncertainty quantification is based on a 'black box' approach. The simulation tool is treated as an unknown signal generator, a distribution of inputs according to assumed probability density functions is sent in and the distribution of the outputs is measured and correlated back to the original input distribution. The 'black box' method mixes numerical errors with all other uncertainties. It is also not efficient to perform sensitivity analysis. Contrary to the 'black box' method, a more efficient sensitivity approach can take advantage of intimate knowledge of the simulation code. In these types of approaches equations for the propagation of uncertainty are constructed and the sensitivities are directly solved for as variables in the simulation. This paper presents the forward sensitivity analysis as a method to help uncertainty qualification. By including time step and potentially spatial step as special sensitivity parameters, the forward sensitivity method is extended as one method to quantify numerical errors. Note that by integrating local truncation errors over the whole system through the forward sensitivity analysis process, the generated time step and spatial step sensitivity information reflect global numerical errors. The discretization errors can be systematically compared against uncertainties due to other physical parameters. This extension makes the forward sensitivity method a much more powerful tool to help uncertainty qualification. By knowing the relative sensitivity of time and space steps with other interested physical parameters, the simulation is allowed to run at optimized time and space steps without affecting the confidence of the physical parameter sensitivity results. The time and space steps forward sensitivity analysis method can also replace the traditional time step and grid convergence study with much less computational cost. Several well defined benchmark problems with manufactured solutions are utilized to demonstrate the extended forward sensitivity analysis method. All the physical solutions, parameter sensitivity solutions, even the time step sensitivity in one case, have analytical forms, which allows the verification to be performed in the strictest sense.

  3. The impact of uncertainty and risk measures

    E-Print Network [OSTI]

    Jo, Soojin; Jo, Soojin

    2012-01-01T23:59:59.000Z

    First, it recovers historical oil price uncertainty seriesmore reliable historical oil price uncertainty series as itAs a result, the historical oil price uncertainty series is

  4. Price analysis in electronic marketing of Texas feeder cattle

    E-Print Network [OSTI]

    Mahoney, Kathleen Ann

    1981-01-01T23:59:59.000Z

    PRICE ANALYSIS IN ZLECZRCNIC ~ING OF TEXAS FEEOER ~ A Thesis Submitted to the Graduate College of Texas AsN Bu. varsity in Partial fulfillment of the reguirarents for the degree of De~ 1981 Major Subject: Agricultural Economics PRICE... ANALYSIS IN ELECTRONIC MARKETING OF TEXAS FEEDER CATTLE A Thesis by KATHLEEN ANN MAHONEY Approved as to style and content by: Chairman of Co ttee) ead of De rtment (Me r) ( r) December 1981 1. 11 Price Analysis in Electronic Marketing of Texas...

  5. DOE Publishes Pricing and Efficacy Trend Analysis for Utility...

    Broader source: Energy.gov (indexed) [DOE]

    a new report, SSL Pricing and Efficacy Trend Analysis for Utility Program Planning. The report was created in response to requests from utilities and energy efficiency...

  6. Representation of analysis results involving aleatory and epistemic uncertainty.

    SciTech Connect (OSTI)

    Johnson, Jay Dean (ProStat, Mesa, AZ); Helton, Jon Craig (Arizona State University, Tempe, AZ); Oberkampf, William Louis; Sallaberry, Cedric J.

    2008-08-01T23:59:59.000Z

    Procedures are described for the representation of results in analyses that involve both aleatory uncertainty and epistemic uncertainty, with aleatory uncertainty deriving from an inherent randomness in the behavior of the system under study and epistemic uncertainty deriving from a lack of knowledge about the appropriate values to use for quantities that are assumed to have fixed but poorly known values in the context of a specific study. Aleatory uncertainty is usually represented with probability and leads to cumulative distribution functions (CDFs) or complementary cumulative distribution functions (CCDFs) for analysis results of interest. Several mathematical structures are available for the representation of epistemic uncertainty, including interval analysis, possibility theory, evidence theory and probability theory. In the presence of epistemic uncertainty, there is not a single CDF or CCDF for a given analysis result. Rather, there is a family of CDFs and a corresponding family of CCDFs that derive from epistemic uncertainty and have an uncertainty structure that derives from the particular uncertainty structure (i.e., interval analysis, possibility theory, evidence theory, probability theory) used to represent epistemic uncertainty. Graphical formats for the representation of epistemic uncertainty in families of CDFs and CCDFs are investigated and presented for the indicated characterizations of epistemic uncertainty.

  7. Uncertainty Budget Analysis for Dimensional Inspection Processes (U)

    SciTech Connect (OSTI)

    Valdez, Lucas M. [Los Alamos National Laboratory

    2012-07-26T23:59:59.000Z

    This paper is intended to provide guidance and describe how to prepare an uncertainty analysis of a dimensional inspection process through the utilization of an uncertainty budget analysis. The uncertainty analysis is stated in the same methodology as that of the ISO GUM standard for calibration and testing. There is a specific distinction between how Type A and Type B uncertainty analysis is used in a general and specific process. All theory and applications are utilized to represent both a generalized approach to estimating measurement uncertainty and how to report and present these estimations for dimensional measurements in a dimensional inspection process. The analysis of this uncertainty budget shows that a well-controlled dimensional inspection process produces a conservative process uncertainty, which can be attributed to the necessary assumptions in place for best possible results.

  8. Measurement uncertainty analysis techniques applied to PV performance measurements

    SciTech Connect (OSTI)

    Wells, C.

    1992-10-01T23:59:59.000Z

    The purpose of this presentation is to provide a brief introduction to measurement uncertainty analysis, outline how it is done, and illustrate uncertainty analysis with examples drawn from the PV field, with particular emphasis toward its use in PV performance measurements. The uncertainty information we know and state concerning a PV performance measurement or a module test result determines, to a significant extent, the value and quality of that result. What is measurement uncertainty analysis It is an outgrowth of what has commonly been called error analysis. But uncertainty analysis, a more recent development, gives greater insight into measurement processes and tests, experiments, or calibration results. Uncertainty analysis gives us an estimate of the I interval about a measured value or an experiment's final result within which we believe the true value of that quantity will lie. Why should we take the time to perform an uncertainty analysis A rigorous measurement uncertainty analysis: Increases the credibility and value of research results; allows comparisons of results from different labs; helps improve experiment design and identifies where changes are needed to achieve stated objectives (through use of the pre-test analysis); plays a significant role in validating measurements and experimental results, and in demonstrating (through the post-test analysis) that valid data have been acquired; reduces the risk of making erroneous decisions; demonstrates quality assurance and quality control measures have been accomplished; define Valid Data as data having known and documented paths of: Origin, including theory; measurements; traceability to measurement standards; computations; uncertainty analysis of results.

  9. Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing

    SciTech Connect (OSTI)

    Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila

    2011-08-15T23:59:59.000Z

    Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.

  10. Which Models Matter: Uncertainty and Sensitivity Analysis for

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Models Matter: Uncertainty and Sensitivity Analysis for Photovoltaic Power Systems Clifford W. Hansen and Andrew Pohl Sandia National Laboratories, Albuquerque, NM, 87185-1033, USA...

  11. An econometric analysis of prices for Texas grapefruit

    E-Print Network [OSTI]

    Gutierrez-Villarreal, Jorge

    1967-01-01T23:59:59.000Z

    " Price F. o. b. Price. Prcccssed Grapefruit Price Fouat'on. I". ethod of Statisticei Analysis. Data. . 76 I m f L jo / '-'2 Zquatior G. "-, fruit Texas. "rash Grape ru m J. exes ~ !I Qy F. o. I" orida. "Gn F. o. ~r ce it Pci. ce Ejlu... + . 00370y (. 191) (. 00083) Xf = 6. 441 Means: Xz Where: Xz. q y . 437q + . 00000y 11 3067 X? 9 2067 Xf ? 2 1000 q 9 o333 y 1666 GG G. S. azu:ual average retail pr'ce for orapefruit (cents per pound) U. S. annual averag fam-retail price spread...

  12. Uncertainty in climate change policy analysis

    E-Print Network [OSTI]

    Jacoby, Henry D.; Prinn, Ronald G.

    Achieving agreement about whether and how to control greenhouse gas emissions would be difficult enough even if the consequences were fully known. Unfortunately, choices must be made in the face of great uncertainty, about ...

  13. Measurement uncertainty analysis techniques applied to PV performance measurements

    SciTech Connect (OSTI)

    Wells, C.

    1992-10-01T23:59:59.000Z

    The purpose of this presentation is to provide a brief introduction to measurement uncertainty analysis, outline how it is done, and illustrate uncertainty analysis with examples drawn from the PV field, with particular emphasis toward its use in PV performance measurements. The uncertainty information we know and state concerning a PV performance measurement or a module test result determines, to a significant extent, the value and quality of that result. What is measurement uncertainty analysis? It is an outgrowth of what has commonly been called error analysis. But uncertainty analysis, a more recent development, gives greater insight into measurement processes and tests, experiments, or calibration results. Uncertainty analysis gives us an estimate of the I interval about a measured value or an experiment`s final result within which we believe the true value of that quantity will lie. Why should we take the time to perform an uncertainty analysis? A rigorous measurement uncertainty analysis: Increases the credibility and value of research results; allows comparisons of results from different labs; helps improve experiment design and identifies where changes are needed to achieve stated objectives (through use of the pre-test analysis); plays a significant role in validating measurements and experimental results, and in demonstrating (through the post-test analysis) that valid data have been acquired; reduces the risk of making erroneous decisions; demonstrates quality assurance and quality control measures have been accomplished; define Valid Data as data having known and documented paths of: Origin, including theory; measurements; traceability to measurement standards; computations; uncertainty analysis of results.

  14. An economic and statistical analysis of pecan prices

    E-Print Network [OSTI]

    Hertel, Karlene Sharon

    1979-01-01T23:59:59.000Z

    AN ECONOMIC AND STATISTICAL ANALYSIS OP PECAN PRICES A Thesis by KARLENE SHARON HERTEL Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirement for the degree of NASTER OP SCIENCE August 1979 Maj... or Subject: Agricultural Economics AN ECONOMIC AND STATISTICAL ANALYSIS OF PECAN PRICES A Thesis by KARLENE SHARON HERTEL Approved as to style and content by: ( hairman of Committ ) ead of Depar ment) (Member) (Member) August 1979 ABSTRACT...

  15. A Quantitative Analysis of Pricing Behavior In California's Wholesale Electricity Market During Summer 2000

    E-Print Network [OSTI]

    Joskow, Paul; Kahn, Edward

    2004-06-16T23:59:59.000Z

    A Quantitative Analysis of Pricing Behavior In California's Wholesale Electricity Market During Summer 2000...

  16. Essays on Price Dynamics, Welfare Analysis, Household Food Insecurity in Mexico 

    E-Print Network [OSTI]

    Magana Lemus, David

    2013-09-20T23:59:59.000Z

    Higher and more volatile food prices, as reported in recent years, have consequences on household welfare and potentially on public policy. Analysis of agricultural commodities price dynamics, welfare ...

  17. Consumer Demand under Price Uncertainty: Empirical Evidence from the Market for Cigarettes

    E-Print Network [OSTI]

    Coppejans, Mark; Gilleskie, Donna; Sieg, Holger; Strumpf, Koleman

    2007-08-01T23:59:59.000Z

    We develop a demand model for goods that are subject to habit formation. We show that consumption plans of forward-looking individuals depend on preferences, current period prices, and individual beliefs about the evolution ...

  18. Uncertainty and sensitivity analysis for long-running computer codes : a critical review

    E-Print Network [OSTI]

    Langewisch, Dustin R

    2010-01-01T23:59:59.000Z

    This thesis presents a critical review of existing methods for performing probabilistic uncertainty and sensitivity analysis for complex, computationally expensive simulation models. Uncertainty analysis (UA) methods ...

  19. Analysis of leaded and unleaded gasoline pricing. Final report

    SciTech Connect (OSTI)

    Not Available

    1985-03-15T23:59:59.000Z

    This report summarizes the evaluation of the cost price relation between the two fuels. The original scope of work identified three separate categories of effort: Gather and organize available data on the wholesale and retail prices of gasoline at a national level for the past 5 years. Using the data collected in Subtask 1, develop models of pricing practices that aid in explaining retail markups and price differentials for different types and grades of gasoline at different retail outlets in the current gasoline market. Using the data from Subtask 1 and the analysis framework from Subtask 2, analyze the likely range of future retail markups and price differentials for different grades of leaded and unleaded gasoline. The report is organized in a format that is different than suggested by the subtasks outlined above. The first section provides a characterization of the problem - data available to quantify cost and price of the fuels as well as issues that directly affect this relationship. The second section provides a discussion of issues likely to affect this relation in the future. The third section postulates a model that can be used to quantify the relation between fuels, octane levels, costs and prices.

  20. Bio-energy Logistics Network Design Under Price-based Supply and Yield Uncertainty 

    E-Print Network [OSTI]

    Memisoglu, Gokhan

    2014-12-10T23:59:59.000Z

    network. In the second study, we consider a two-stage stochastic problem to model farm-to-biorefinery biomass logistics while designing a policy that encourages farmers to plant biomass energy crops by offering them a unit wholesale price. In the first...

  1. EIA - Natural Gas Price Data & Analysis

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877Southwest Region About U.S. Natural GasPrices

  2. Uncertainty Analysis Technique for OMEGA Dante Measurements

    SciTech Connect (OSTI)

    May, M J; Widmann, K; Sorce, C; Park, H; Schneider, M

    2010-05-07T23:59:59.000Z

    The Dante is an 18 channel X-ray filtered diode array which records the spectrally and temporally resolved radiation flux from various targets (e.g. hohlraums, etc.) at X-ray energies between 50 eV to 10 keV. It is a main diagnostics installed on the OMEGA laser facility at the Laboratory for Laser Energetics, University of Rochester. The absolute flux is determined from the photometric calibration of the X-ray diodes, filters and mirrors and an unfold algorithm. Understanding the errors on this absolute measurement is critical for understanding hohlraum energetic physics. We present a new method for quantifying the uncertainties on the determined flux using a Monte-Carlo parameter variation technique. This technique combines the uncertainties in both the unfold algorithm and the error from the absolute calibration of each channel into a one sigma Gaussian error function. One thousand test voltage sets are created using these error functions and processed by the unfold algorithm to produce individual spectra and fluxes. Statistical methods are applied to the resultant set of fluxes to estimate error bars on the measurements.

  3. COST AND PRICE ANALYSIS--AN EXPLANATION Some form of price or cost analysis should be performed in connection with every procurement action,

    E-Print Network [OSTI]

    Weston, Ken

    performance should cost. Cost or pricing data, which should be provided by the subcontractor, are the means for conducting cost analysis. Such data provide factual information about the costs that the subcontractor says where price analysis does not yield a fair and reasonable price and where cost data are required

  4. System architecture analysis and selection under uncertainty

    E-Print Network [OSTI]

    Smaling, Rudolf M

    2005-01-01T23:59:59.000Z

    A system architecture analysis and selection methodology is presented that builds on the Multidisciplinary Analysis and Optimization framework. It addresses a need and opportunity to extend the MAO techniques to include a ...

  5. Analysis and Reduction of Complex Networks Under Uncertainty

    SciTech Connect (OSTI)

    Knio, Omar M

    2014-04-09T23:59:59.000Z

    This is a collaborative proposal that aims at developing new methods for the analysis and reduction of complex multiscale networks under uncertainty. The approach is based on combining methods of computational singular perturbation (CSP) and probabilistic uncertainty quantification. In deterministic settings, CSP yields asymptotic approximations of reduced-dimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty raises fundamentally new issues, particularly concerning its impact on the topology of slow manifolds, and means to represent and quantify associated variability. To address these challenges, this project uses polynomial chaos (PC) methods to reformulate uncertain network models, and to analyze them using CSP in probabilistic terms. Specific objectives include (1) developing effective algorithms that can be used to illuminate fundamental and unexplored connections among model reduction, multiscale behavior, and uncertainty, and (2) demonstrating the performance of these algorithms through applications to model problems.

  6. ANALYSIS OF FUTURE PRICES AND MARKETS FOR HIGH TEMPERATURE SUPERCONDUCTORS

    E-Print Network [OSTI]

    1 ANALYSIS OF FUTURE PRICES AND MARKETS FOR HIGH TEMPERATURE SUPERCONDUCTORS BY JOSEPH MULHOLLAND temperature superconductors (HTS) may impact the national electrical system over the next 25 years dollars. However, the savings from superconductivity are offset somewhat by the high cost of manufacturing

  7. Tariff-based analysis of commercial building electricity prices

    E-Print Network [OSTI]

    Coughlin, Katie M.; Bolduc, Chris A.; Rosenquist, Greg J.; Van Buskirk, Robert D.; McMahon, James E.

    2008-01-01T23:59:59.000Z

    4 Calculation of Electricity Prices 4.1 Averageaverage seasonal and annual electricity prices by region inbased annual average electricity price vs. annual energy

  8. Approaches to uncertainty analysis in probabilistic risk assessment

    SciTech Connect (OSTI)

    Bohn, M.P.; Wheeler, T.A.; Parry, G.W.

    1988-01-01T23:59:59.000Z

    An integral part of any probabilistic risk assessment (PRA) is the performance of an uncertainty analysis to quantify the uncertainty in the point estimates of the risk measures considered. While a variety of classical methods of uncertainty analysis exist, application of these methods and developing new techniques consistent with existing PRA data bases and the need for expert (subjective) input has been an area of considerable interest since the pioneering Reactor Safety Study (WASH-1400) in 1975. This report presents the results of a critical review of existing methods for performing uncertainty analyses for PRAs, with special emphasis on identifying data base limitations on the various methods. Both classical and Baysian approaches have been examined. This work was funded by the US Nuclear Regulatory Commission in support of its ongoing full-scope PRA of the LaSalle nuclear power station. Thus in addition to the review, this report contains recommendations for a suitable uncertainty analysis methodology for the LaSalle PRA.

  9. Learning Curve: Analysis of an Agent Pricing Strategy Under Varying Conditions

    E-Print Network [OSTI]

    in employing these real-time agents is understanding the costs and benefits to different agent pricingLearning Curve: Analysis of an Agent Pricing Strategy Under Varying Conditions Joan Morris, Pattie@cs.brown.edu Abstract - By employing dynamic pricing, the act of changing prices over time within a marketplace, sellers

  10. Analysis of Competitive Electricity Markets under a New Model of Real-Time Retail Pricing with

    E-Print Network [OSTI]

    Bhatia, Sangeeta

    Analysis of Competitive Electricity Markets under a New Model of Real-Time Retail Pricing with Ex for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA {mardavij, mdrine loop system. Under this pricing mechanism, electricity is priced at the exant´e price (calculated based

  11. Uncertainty and sensitivity analysis for photovoltaic system modeling.

    SciTech Connect (OSTI)

    Hansen, Clifford W.; Pohl, Andrew Phillip; Jordan, Dirk [National Center for Photovoltaics, National Renewable Energy Laboratory, Golden, CO] [National Center for Photovoltaics, National Renewable Energy Laboratory, Golden, CO

    2013-12-01T23:59:59.000Z

    We report an uncertainty and sensitivity analysis for modeling DC energy from photovoltaic systems. We consider two systems, each comprised of a single module using either crystalline silicon or CdTe cells, and located either at Albuquerque, NM, or Golden, CO. Output from a PV system is predicted by a sequence of models. Uncertainty in the output of each model is quantified by empirical distributions of each model's residuals. We sample these distributions to propagate uncertainty through the sequence of models to obtain an empirical distribution for each PV system's output. We considered models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane-of-array irradiance; (2) estimate effective irradiance from plane-of-array irradiance; (3) predict cell temperature; and (4) estimate DC voltage, current and power. We found that the uncertainty in PV system output to be relatively small, on the order of 1% for daily energy. Four alternative models were considered for the POA irradiance modeling step; we did not find the choice of one of these models to be of great significance. However, we observed that the POA irradiance model introduced a bias of upwards of 5% of daily energy which translates directly to a systematic difference in predicted energy. Sensitivity analyses relate uncertainty in the PV system output to uncertainty arising from each model. We found that the residuals arising from the POA irradiance and the effective irradiance models to be the dominant contributors to residuals for daily energy, for either technology or location considered. This analysis indicates that efforts to reduce the uncertainty in PV system output should focus on improvements to the POA and effective irradiance models.

  12. Analysis of Federal Subsidies: Implied Price of Carbon

    SciTech Connect (OSTI)

    D. Craig Cooper; Thomas Foulke

    2010-10-01T23:59:59.000Z

    For informed climate change policy, it is important for decision makers to be able to assess how the costs and benefits of federal energy subsidies are distributed and to be able to have some measure to compare them. One way to do this is to evaluate the implied price of carbon (IPC) for a federal subsidy, or set of subsidies; where the IPC is the cost of the subsidy to the U.S. Treasury divided by the emissions reductions it generated. Subsidies with lower IPC are more cost effective at reducing greenhouse gas emissions, while subsidies with a negative IPC act to increase emissions. While simple in concept, the IPC is difficult to calculate in practice. Calculation of the IPC requires knowledge of (i) the amount of energy associated with the subsidy, (ii) the amount and type of energy that would have been produced in the absence of the subsidy, and (iii) the greenhouse gas emissions associated with both the subsidized energy and the potential replacement energy. These pieces of information are not consistently available for federal subsidies, and there is considerable uncertainty in cases where the information is available. Thus, exact values for the IPC based upon fully consistent standards cannot be calculated with available data. However, it is possible to estimate a range of potential values sufficient for initial comparisons. This study has employed a range of methods to generate “first order” estimates for the IPC of a range of federal subsidies using static methods that do not account for the dynamics of supply and demand. The study demonstrates that, while the IPC value depends upon how the inquiry is framed and the IPC cannot be calculated in a “one size fits all” manner, IPC calculations can provide a valuable perspective for climate policy analysis. IPC values are most useful when calculated within the perspective of a case study, with the method and parameters of the calculation determined by the case. The IPC of different policy measures can then be quantitatively evaluated within the case. Results can be qualitatively compared across cases, so long as such comparisons are considered to be preliminary and treated with the appropriate level of caution.

  13. Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment, main report

    SciTech Connect (OSTI)

    Harper, F.T.; Young, M.L.; Miller, L.A. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States); Lui, C.H. [Nuclear Regulatory Commission, Washington, DC (United States); Goossens, L.H.J.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Paesler-Sauer, J. [Research Center, Karlsruhe (Germany); Helton, J.C. [and others

    1995-01-01T23:59:59.000Z

    The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the risks presented by nuclear installations based on postulated frequencies and magnitudes of potential accidents. In 1991, the US Nuclear Regulatory Commission (NRC) and the Commission of the European Communities (CEC) began a joint uncertainty analysis of the two codes. The ultimate objective of the joint effort was to develop credible and traceable uncertainty distributions for the input variables of the codes. Expert elicitation was identified as the best technology available for developing a library of uncertainty distributions for the selected consequence parameters. The study was formulated jointly and was limited to the current code models and to physical quantities that could be measured in experiments. Experts developed their distributions independently. To validate the distributions generated for the wet deposition input variables, samples were taken from these distributions and propagated through the wet deposition code model. Resulting distributions closely replicated the aggregated elicited wet deposition distributions. To validate the distributions generated for the dispersion code input variables, samples from the distributions and propagated through the Gaussian plume model (GPM) implemented in the MACCS and COSYMA codes. Project teams from the NRC and CEC cooperated successfully to develop and implement a unified process for the elaboration of uncertainty distributions on consequence code input parameters. Formal expert judgment elicitation proved valuable for synthesizing the best available information. Distributions on measurable atmospheric dispersion and deposition parameters were successfully elicited from experts involved in the many phenomenological areas of consequence analysis. This volume is the first of a three-volume document describing the project.

  14. Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment, appendices A and B

    SciTech Connect (OSTI)

    Harper, F.T.; Young, M.L.; Miller, L.A. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States); Lui, C.H. [Nuclear Regulatory Commission, Washington, DC (United States); Goossens, L.H.J.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Paesler-Sauer, J. [Research Center, Karlsruhe (Germany); Helton, J.C. [and others

    1995-01-01T23:59:59.000Z

    The development of two new probabilistic accident consequence codes, MACCS and COSYMA, completed in 1990, estimate the risks presented by nuclear installations based on postulated frequencies and magnitudes of potential accidents. In 1991, the US Nuclear Regulatory Commission (NRC) and the Commission of the European Communities (CEC) began a joint uncertainty analysis of the two codes. The objective was to develop credible and traceable uncertainty distributions for the input variables of the codes. Expert elicitation, developed independently, was identified as the best technology available for developing a library of uncertainty distributions for the selected consequence parameters. The study was formulated jointly and was limited to the current code models and to physical quantities that could be measured in experiments. To validate the distributions generated for the wet deposition input variables, samples were taken from these distributions and propagated through the wet deposition code model along with the Gaussian plume model (GPM) implemented in the MACCS and COSYMA codes. Resulting distributions closely replicated the aggregated elicited wet deposition distributions. Project teams from the NRC and CEC cooperated successfully to develop and implement a unified process for the elaboration of uncertainty distributions on consequence code input parameters. Formal expert judgment elicitation proved valuable for synthesizing the best available information. Distributions on measurable atmospheric dispersion and deposition parameters were successfully elicited from experts involved in the many phenomenological areas of consequence analysis. This volume is the second of a three-volume document describing the project and contains two appendices describing the rationales for the dispersion and deposition data along with short biographies of the 16 experts who participated in the project.

  15. Probabilistic accident consequence uncertainty analysis -- Early health effects uncertainty assessment. Volume 2: Appendices

    SciTech Connect (OSTI)

    Haskin, F.E. [Univ. of New Mexico, Albuquerque, NM (United States); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Goossens, L.H.J.; Kraan, B.C.P. [Delft Univ. of Technology (Netherlands)

    1997-12-01T23:59:59.000Z

    The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA early health effects models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on early health effects, (4) short biographies of the experts, and (5) the aggregated results of their responses.

  16. Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for internal dosimetry. Volume 2: Appendices

    SciTech Connect (OSTI)

    Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Harrison, J.D. [National Radiological Protection Board (United Kingdom); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

    1998-04-01T23:59:59.000Z

    The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA internal dosimetry models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on internal dosimetry, (4) short biographies of the experts, and (5) the aggregated results of their responses.

  17. Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for deposited material and external doses. Volume 2: Appendices

    SciTech Connect (OSTI)

    Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Boardman, J. [AEA Technology (United Kingdom); Jones, J.A. [National Radiological Protection Board (United Kingdom); Harper, F.T.; Young, M.L. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

    1997-12-01T23:59:59.000Z

    The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA deposited material and external dose models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on deposited material and external doses, (4) short biographies of the experts, and (5) the aggregated results of their responses.

  18. A statistical analysis of the natural gas futures market : the interplay of sentiment, volatility and prices

    E-Print Network [OSTI]

    Fazzio, Thomas J. (Thomas Joseph)

    2010-01-01T23:59:59.000Z

    This paper attempts to understand the price dynamics of the North American natural gas market through a statistical survey that includes an analysis of the variables influencing the price and volatility of this energy ...

  19. A Time Series Analysis of Food Price and Its Input Prices 

    E-Print Network [OSTI]

    Routh, Kari 1988-

    2012-11-27T23:59:59.000Z

    of crude oil, gasoline, corn, and ethanol prices, as well as, the relative foreign exchange rate of the U.S. dollar and producer price indexes for food manufacturing and fuel products on domestic food prices are examined. Because the data series are non...

  20. A Time Series Analysis of Food Price and Its Input Prices

    E-Print Network [OSTI]

    Routh, Kari 1988-

    2012-11-27T23:59:59.000Z

    of crude oil, gasoline, corn, and ethanol prices, as well as, the relative foreign exchange rate of the U.S. dollar and producer price indexes for food manufacturing and fuel products on domestic food prices are examined. Because the data series are non...

  1. Electricity Forward Prices: A High-Frequency Empirical Analysis

    E-Print Network [OSTI]

    Longstaff, Francis; Wang, Ashley

    2002-01-01T23:59:59.000Z

    and Optimal Hedging in Electricity Forward Markets. JournalP. 2002. Modelling Electricity Prices: Interna- tionalPricing and Risk Managing Electricity Derivatives. The U.S.

  2. ELECTRICITY FORWARD PRICES: A High-Frequency Empirical Analysis

    E-Print Network [OSTI]

    Longstaff, Francis A; Wang, Ashley

    2002-01-01T23:59:59.000Z

    and Optimal Hedging in Electricity Forward Markets. JournalP. 2002. Modelling Electricity Prices: Interna- tionalPricing and Risk Managing Electricity Derivatives. The U.S.

  3. Uncertainty analysis of river flooding and dam failure risks using local sensitivity computations.

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Uncertainty analysis of river flooding and dam failure risks using local sensitivity computations) for uncertainty analysis with respect to two major types of risk in river hydrodynamics: flash flood and dam failure. LSA is com- pared to a Global Uncertainty Analysis (GUA) consisting in running Monte Carlo

  4. Abstract--The capability to deal effectively with the uncer-tainty associated with locational marginal prices (LMPs) in con-

    E-Print Network [OSTI]

    , standard market design, locational marginal prices, fixed/firm/financial transmission rights, transmission.S. electricity sector. The proposal uses locational marginal prices (LMPs) to identify congestion situations marginal prices (LMPs) in con- gestion management schemes requires the development of ap- propriate

  5. Systematic Uncertainties in the Analysis of the Reactor Neutrino Anomaly

    E-Print Network [OSTI]

    A. C. Hayes; J. L. Friar; G. T. Garvey; G. Jungman; Guy Jonkmans

    2014-04-05T23:59:59.000Z

    We examine uncertainties in the analysis of the reactor neutrino anomaly, wherein it is suggested that only about 94% of the emitted antineutrino flux was detected in short baseline experiments. We find that the form of the corrections that lead to the anomaly are very uncertain for the 30% of the flux that arises from forbidden decays. This uncertainty was estimated in four ways, is as large as the size of the anomaly, and is unlikely to be reduced without accurate direct measurements of the antineutrino flux. Given the present lack of detailed knowledge of the structure of the forbidden transitions, it is not possible to convert the measured aggregate fission beta spectra to antineutrino spectra to the accuracy needed to infer an anomaly. Neutrino physics conclusions based on the original anomaly need to be revisited, as do oscillation analyses that assumed that the antineutrino flux is known to better than approximately 4%.

  6. OIL PRICE IMPACT ON FINANCIAL MARKETS: CO-SPECTRAL ANALYSIS FOR EXPORTING VERSUS IMPORTING COUNTRIES

    E-Print Network [OSTI]

    Boyer, Edmond

    relationship between oil and stock markets, which parallels the one between high oil prices and macroeconomicOIL PRICE IMPACT ON FINANCIAL MARKETS: CO-SPECTRAL ANALYSIS FOR EXPORTING VERSUS IMPORTING://www.economie.polytechnique.edu/ mailto:chantal.poujouly@polytechnique.edu hal-00822070,version1-14May2013 #12;1 Oil price impact

  7. Efficiency with Linear Prices? A Theoretical and Experimental Analysis of the Combinatorial Clock

    E-Print Network [OSTI]

    Cengarle, María Victoria

    Efficiency with Linear Prices? A Theoretical and Experimental Analysis of the Combinatorial Clock with complementarities among goods as they can be found in procurement, energy markets, transportation, and the sale simplicity and for its highly usable price discovery, derived by the use of linear prices. Unfor- tunately

  8. The level crossing analysis of German stock market index (DAX) and daily oil price time series

    E-Print Network [OSTI]

    Shayeganfar, F; Peinke, J; Tabar, M Reza Rahimi

    2010-01-01T23:59:59.000Z

    The level crossing analysis of DAX and oil price time series are given. We determine the average frequency of positive-slope crossings, $\

  9. An Analysis of Residential PV System Price Differences Between the United States and Germany

    E-Print Network [OSTI]

    Seel, Joachim

    2014-01-01T23:59:59.000Z

    A levelized cost of electricity (LCoE) analysis based on thePV system prices could reduce LCoE assumptions: 25-year life

  10. Utility Green Pricing Programs: A Statistical Analysis of Program Effectiveness

    SciTech Connect (OSTI)

    Wiser, R.; Olson, S.; Bird, L.; Swezey, B.

    2004-02-01T23:59:59.000Z

    This report analyzes actual utility green pricing program data to provide further insight into which program features might help maximize both customer participation in green pricing programs and the amount of renewable energy purchased by customers in those programs.

  11. Convex Hull Pricing in Electricity Markets: Formulation, Analysis ...

    E-Print Network [OSTI]

    Dane Schiro

    2015-05-01T23:59:59.000Z

    May 1, 2015 ... Consequently, each Independent System Operator (ISO) uses ... Mathematically, the ISO pricing methods differ in sometimes subtle but ...

  12. The impact of uncertainty and risk measures

    E-Print Network [OSTI]

    Jo, Soojin; Jo, Soojin

    2012-01-01T23:59:59.000Z

    historical uncertainty series by incorporating a realized volatility series from daily oil price data

  13. Electricity prices in a competitive environment: Marginal cost pricing of generation services and financial status of electric utilities. A preliminary analysis through 2015

    SciTech Connect (OSTI)

    NONE

    1997-08-01T23:59:59.000Z

    The emergence of competitive markets for electricity generation services is changing the way that electricity is and will be priced in the United States. This report presents the results of an analysis that focuses on two questions: (1) How are prices for competitive generation services likely to differ from regulated prices if competitive prices are based on marginal costs rather than regulated {open_quotes}cost-of-service{close_quotes} pricing? (2) What impacts will the competitive pricing of generation services (based on marginal costs) have on electricity consumption patterns, production costs, and the financial integrity patterns, production costs, and the financial integrity of electricity suppliers? This study is not intended to be a cost-benefit analysis of wholesale or retail competition, nor does this report include an analysis of the macroeconomic impacts of competitive electricity prices.

  14. The impact of uncertainty and risk measures

    E-Print Network [OSTI]

    Jo, Soojin; Jo, Soojin

    2012-01-01T23:59:59.000Z

    xi Chapter 1 The Effects of Oil Price Uncertainty on theLIST OF FIGURES Figure Figure Figure Figure Figure Oil priceOil price uncertainty with and without realized

  15. Uncertainty analysis of climate change and policy response

    E-Print Network [OSTI]

    Webster, Mort David.; Forest, Chris Eliot.; Reilly, John M.; Babiker, Mustafa H.M.; Kicklighter, David W.; Mayer, Monika.; Prinn, Ronald G.; Sarofim, Marcus C.; Sokolov, Andrei P.; Stone, Peter H.; Wang, Chien.

    To aid climate policy decisions, accurate quantitative descriptions of the uncertainty in climate outcomes under various possible policies are needed. Here, we apply an earth systems model to describe the uncertainty in ...

  16. Cassini Spacecraft Uncertainty Analysis Data and Methodology Review and Update/Volume 1: Updated Parameter Uncertainty Models for the Consequence Analysis

    SciTech Connect (OSTI)

    WHEELER, TIMOTHY A.; WYSS, GREGORY D.; HARPER, FREDERICK T.

    2000-11-01T23:59:59.000Z

    Uncertainty distributions for specific parameters of the Cassini General Purpose Heat Source Radioisotope Thermoelectric Generator (GPHS-RTG) Final Safety Analysis Report consequence risk analysis were revised and updated. The revisions and updates were done for all consequence parameters for which relevant information exists from the joint project on Probabilistic Accident Consequence Uncertainty Analysis by the United States Nuclear Regulatory Commission and the Commission of European Communities.

  17. Computational Methods for Sensitivity and Uncertainty Analysis in Criticality Safety

    SciTech Connect (OSTI)

    Broadhead, B.L.; Childs, R.L.; Rearden, B.T.

    1999-09-20T23:59:59.000Z

    Interest in the sensitivity methods that were developed and widely used in the 1970s (the FORSS methodology at ORNL among others) has increased recently as a result of potential use in the area of criticality safety data validation procedures to define computational bias, uncertainties and area(s) of applicability. Functional forms of the resulting sensitivity coefficients can be used as formal parameters in the determination of applicability of benchmark experiments to their corresponding industrial application areas. In order for these techniques to be generally useful to the criticality safety practitioner, the procedures governing their use had to be updated and simplified. This paper will describe the resulting sensitivity analysis tools that have been generated for potential use by the criticality safety community.

  18. Essays on Price Dynamics, Welfare Analysis, Household Food Insecurity in Mexico

    E-Print Network [OSTI]

    Magana Lemus, David

    2013-09-20T23:59:59.000Z

    of freedom. 24 Table 2.3. Augmented Dickey-Fuller (D-F) t-tests and Ljung-Box Q- statistics*. Price Series D-F t-test (k) Q-statistic (p-value) Natural logarithm of levels Yellow Corn MX -0.77 (0) 35.74 (0.48) White Corn MX -0.44 (0) 53... on Trade and Price Analysis ......... 8 II.3. Price Data ........................................................................................... 15 II.4. Modeling Considerations...

  19. Carbon Permit Prices in the European Emissions Trading System: A Stochastic Analysis

    E-Print Network [OSTI]

    Carbon Permit Prices in the European Emissions Trading System: A Stochastic Analysis By Wee Chiang, Technology and Policy Program 1 #12;Carbon Permit Prices in the European Emissions Trading System Abstract The Emission Trading Scheme (ETS) is a cornerstone for European efforts to reduce greenhouse gas

  20. Application of Uncertainty and Sensitivity Analysis to a Kinetic Model for Enzymatic Biodiesel Production

    E-Print Network [OSTI]

    Mosegaard, Klaus

    Application of Uncertainty and Sensitivity Analysis to a Kinetic Model for Enzymatic Biodiesel benefits of using uncertainty and sensitivity analysis in the kinetics of enzymatic biodiesel production, Monte-Carlo Simulations, Enzymatic Biodiesel 1. INTRODUCTION In order to determine the optimal

  1. 2007 Wholesale Power Rate Case Final Proposal : Market Price Forecast Study.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    2006-07-01T23:59:59.000Z

    This study presents BPA's market price forecasts for the Final Proposal, which are based on AURORA modeling. AURORA calculates the variable cost of the marginal resource in a competitively priced energy market. In competitive market pricing, the marginal cost of production is equivalent to the market-clearing price. Market-clearing prices are important factors for informing BPA's power rates. AURORA was used as the primary tool for (a) estimating the forward price for the IOU REP Settlement benefits calculation for fiscal years (FY) 2008 and 2009, (b) estimating the uncertainty surrounding DSI payments and IOU REP Settlements benefits, (c) informing the secondary revenue forecast and (d) providing a price input used for the risk analysis. For information about the calculation of the secondary revenues, uncertainty regarding the IOU REP Settlement benefits and DSI payment uncertainty, and the risk run, see Risk Analysis Study WP-07-FS-BPA-04.

  2. Determination of uncertainty in reserves estimate from analysis of production decline data

    E-Print Network [OSTI]

    Wang, Yuhong

    2007-09-17T23:59:59.000Z

    Analysts increasingly have used probabilistic approaches to evaluate the uncertainty in reserves estimates based on a decline curve analysis. This is because the results represent statistical analysis of historical data that usually possess...

  3. Quantitative Analysis of Variability and Uncertainty in Environmental Data and Models

    E-Print Network [OSTI]

    Frey, H. Christopher

    Quantitative Analysis of Variability and Uncertainty in Environmental Data and Models Volume 1 ........................................6 1.3 Is A Probabilistic Analysis Necessary? ................................................................8 1.4 Previous Work in Probabilistic Risk Assessment

  4. Tariff-based analysis of commercial building electricity prices

    E-Print Network [OSTI]

    Coughlin, Katie M.; Bolduc, Chris A.; Rosenquist, Greg J.; Van Buskirk, Robert D.; McMahon, James E.

    2008-01-01T23:59:59.000Z

    is higher than the average cost per-kWh, the question of howcost recovery adders are neglected unless they are speci?ed as a price per kWh

  5. Analysis on various pricing scenarios in a deregulated electricity market 

    E-Print Network [OSTI]

    Afanador Delgado, Catalina

    2006-10-30T23:59:59.000Z

    The electricity pricing structure in Texas has changed after deregulation (January 2002). The Energy Systems Laboratory has served as a technical consultant on electricity purchases to several universities in the Texas A&M University System since...

  6. Analysis on various pricing scenarios in a deregulated electricity market

    E-Print Network [OSTI]

    Afanador Delgado, Catalina

    2006-10-30T23:59:59.000Z

    The electricity pricing structure in Texas has changed after deregulation (January 2002). The Energy Systems Laboratory has served as a technical consultant on electricity purchases to several universities in the Texas A&M University System since...

  7. Principles and applications of measurement and uncertainty analysis in research and calibration

    SciTech Connect (OSTI)

    Wells, C.V.

    1992-11-01T23:59:59.000Z

    Interest in Measurement Uncertainty Analysis has grown in the past several years as it has spread to new fields of application, and research and development of uncertainty methodologies have continued. This paper discusses the subject from the perspectives of both research and calibration environments. It presents a history of the development and an overview of the principles of uncertainty analysis embodied in the United States National Standard, ANSI/ASME PTC 19.1-1985, Measurement Uncertainty. Examples are presented in which uncertainty analysis was utilized or is needed to gain further knowledge of a particular measurement process and to characterize final results. Measurement uncertainty analysis provides a quantitative estimate of the interval about a measured value or an experiment result within which the true value of that quantity is expected to lie. Years ago, Harry Ku of the United States National Bureau of Standards stated that The informational content of the statement of uncertainty determines, to a large extent, the worth of the calibrated value.'' Today, that statement is just as true about calibration or research results as it was in 1968. Why is that true What kind of information should we include in a statement of uncertainty accompanying a calibrated value How and where do we get the information to include in an uncertainty statement How should we interpret and use measurement uncertainty information This discussion will provide answers to these and other questions about uncertainty in research and in calibration. The methodology to be described has been developed by national and international groups over the past nearly thirty years, and individuals were publishing information even earlier. Yet the work is largely unknown in many science and engineering arenas. I will illustrate various aspects of uncertainty analysis with some examples drawn from the radiometry measurement and calibration discipline from research activities.

  8. Principles and applications of measurement and uncertainty analysis in research and calibration

    SciTech Connect (OSTI)

    Wells, C.V.

    1992-11-01T23:59:59.000Z

    Interest in Measurement Uncertainty Analysis has grown in the past several years as it has spread to new fields of application, and research and development of uncertainty methodologies have continued. This paper discusses the subject from the perspectives of both research and calibration environments. It presents a history of the development and an overview of the principles of uncertainty analysis embodied in the United States National Standard, ANSI/ASME PTC 19.1-1985, Measurement Uncertainty. Examples are presented in which uncertainty analysis was utilized or is needed to gain further knowledge of a particular measurement process and to characterize final results. Measurement uncertainty analysis provides a quantitative estimate of the interval about a measured value or an experiment result within which the true value of that quantity is expected to lie. Years ago, Harry Ku of the United States National Bureau of Standards stated that ``The informational content of the statement of uncertainty determines, to a large extent, the worth of the calibrated value.`` Today, that statement is just as true about calibration or research results as it was in 1968. Why is that true? What kind of information should we include in a statement of uncertainty accompanying a calibrated value? How and where do we get the information to include in an uncertainty statement? How should we interpret and use measurement uncertainty information? This discussion will provide answers to these and other questions about uncertainty in research and in calibration. The methodology to be described has been developed by national and international groups over the past nearly thirty years, and individuals were publishing information even earlier. Yet the work is largely unknown in many science and engineering arenas. I will illustrate various aspects of uncertainty analysis with some examples drawn from the radiometry measurement and calibration discipline from research activities.

  9. An intraseasonal price analysis for Texas fresh grapefruit

    E-Print Network [OSTI]

    Smith, E. G

    1975-01-01T23:59:59.000Z

    determining those factors which had the greatest influence on weekly and monthly Texas fresh F. O. B. shipping point grapefruit price. This equation was then used in developing a conditional allocative system for intraseasonal shipments which would maximize... shipments seemed to have more effect in determining Texas price than did shipments from any other producing region even though Texas produces only 16 percent of the grapefruit produced in the U. S. Similar equations run for Florida fresh grapefruit...

  10. Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 2: Appendices

    SciTech Connect (OSTI)

    Brown, J. [National Radiological Protection Board (United Kingdom); Goossens, L.H.J.; Kraan, B.C.P. [Delft Univ. of Technology (Netherlands)] [and others

    1997-06-01T23:59:59.000Z

    This volume is the second of a two-volume document that summarizes a joint project by the US Nuclear Regulatory and the Commission of European Communities to assess uncertainties in the MACCS and COSYMA probabilistic accident consequence codes. These codes were developed primarily for estimating the risks presented by nuclear reactors based on postulated frequencies and magnitudes of potential accidents. This two-volume report, which examines mechanisms and uncertainties of transfer through the food chain, is the first in a series of five such reports. A panel of sixteen experts was formed to compile credible and traceable uncertainty distributions for food chain transfer that affect calculations of offsite radiological consequences. Seven of the experts reported on transfer into the food chain through soil and plants, nine reported on transfer via food products from animals, and two reported on both. The expert judgment elicitation procedure and its outcomes are described in these volumes. This volume contains seven appendices. Appendix A presents a brief discussion of the MAACS and COSYMA model codes. Appendix B is the structure document and elicitation questionnaire for the expert panel on soils and plants. Appendix C presents the rationales and responses of each of the members of the soils and plants expert panel. Appendix D is the structure document and elicitation questionnaire for the expert panel on animal transfer. The rationales and responses of each of the experts on animal transfer are given in Appendix E. Brief biographies of the food chain expert panel members are provided in Appendix F. Aggregated results of expert responses are presented in graph format in Appendix G.

  11. Thorough approach to measurement uncertainty analysis applied to immersed heat exchanger testing

    SciTech Connect (OSTI)

    Farrington, R.B.; Wells, C.V.

    1986-04-01T23:59:59.000Z

    This paper discusses the value of an uncertainty analysis, discusses how to determine measurement uncertainty, and then details the sources of error in instrument calibration, data acquisition, and data reduction for a particular experiment. Methods are discussed to determine both the systematic (or bias) error in an experiment as well as to determine the random (or precision) error in the experiment. The detailed analysis is applied to two sets of conditions in measuring the effectiveness of an immersed coil heat exchanger. It shows the value of such analysis as well as an approach to reduce overall measurement uncertainty and to improve the experiment. This paper outlines how to perform an uncertainty analysis and then provides a detailed example of how to apply the methods discussed in the paper. The authors hope this paper will encourage researchers and others to become more concerned with their measurement processes and to report measurement uncertainty with all of their test results.

  12. Building-Integrated Photovoltaics (BIPV) in the Residential Section: An Analysis of Installed Rooftop Prices (Presentation)

    SciTech Connect (OSTI)

    James, T.; Goodrich, A.; Woodhouse, M.; Margolis, R.; Ong, S.

    2012-06-01T23:59:59.000Z

    This powerpoint presentation to be presented at the World Renewable Energy Forum on May 17, 2012, in Denver, CO, discusses building-integrated photovoltaics (BIPV) in the residential section and includes an analysis of installed rooftop prices.

  13. Modeling aviation's global emissions, uncertainty analysis, and applications to policy

    E-Print Network [OSTI]

    Lee, Joosung Joseph, 1974-

    2005-01-01T23:59:59.000Z

    (cont.) fuel burn results below 3000 ft. For emissions, the emissions indices were the most influential uncertainties for the variance in model outputs. By employing the model, this thesis examined three policy options for ...

  14. Survey of sampling-based methods for uncertainty and sensitivity analysis.

    SciTech Connect (OSTI)

    Johnson, Jay Dean; Helton, Jon Craig; Sallaberry, Cedric J. PhD. (.; .); Storlie, Curt B. (Colorado State University, Fort Collins, CO)

    2006-06-01T23:59:59.000Z

    Sampling-based methods for uncertainty and sensitivity analysis are reviewed. The following topics are considered: (1) Definition of probability distributions to characterize epistemic uncertainty in analysis inputs, (2) Generation of samples from uncertain analysis inputs, (3) Propagation of sampled inputs through an analysis, (4) Presentation of uncertainty analysis results, and (5) Determination of sensitivity analysis results. Special attention is given to the determination of sensitivity analysis results, with brief descriptions and illustrations given for the following procedures/techniques: examination of scatterplots, correlation analysis, regression analysis, partial correlation analysis, rank transformations, statistical tests for patterns based on gridding, entropy tests for patterns based on gridding, nonparametric regression analysis, squared rank differences/rank correlation coefficient test, two dimensional Kolmogorov-Smirnov test, tests for patterns based on distance measures, top down coefficient of concordance, and variance decomposition.

  15. Uncertainty Analysis of RELAP5-3D

    SciTech Connect (OSTI)

    Alexandra E Gertman; Dr. George L Mesina

    2012-07-01T23:59:59.000Z

    As world-wide energy consumption continues to increase, so does the demand for the use of alternative energy sources, such as Nuclear Energy. Nuclear Power Plants currently supply over 370 gigawatts of electricity, and more than 60 new nuclear reactors have been commissioned by 15 different countries. The primary concern for Nuclear Power Plant operation and lisencing has been safety. The safety of the operation of Nuclear Power Plants is no simple matter- it involves the training of operators, design of the reactor, as well as equipment and design upgrades throughout the lifetime of the reactor, etc. To safely design, operate, and understand nuclear power plants, industry and government alike have relied upon the use of best-estimate simulation codes, which allow for an accurate model of any given plant to be created with well-defined margins of safety. The most widely used of these best-estimate simulation codes in the Nuclear Power industry is RELAP5-3D. Our project focused on improving the modeling capabilities of RELAP5-3D by developing uncertainty estimates for its calculations. This work involved analyzing high, medium, and low ranked phenomena from an INL PIRT on a small break Loss-Of-Coolant Accident as wall as an analysis of a large break Loss-Of- Coolant Accident. Statistical analyses were performed using correlation coefficients. To perform the studies, computer programs were written that modify a template RELAP5 input deck to produce one deck for each combination of key input parameters. Python scripting enabled the running of the generated input files with RELAP5-3D on INL’s massively parallel cluster system. Data from the studies was collected and analyzed with SAS. A summary of the results of our studies are presented.

  16. SOARCA Peach Bottom Atomic Power Station Long-Term Station Blackout Uncertainty Analysis: Convergence of the Uncertainty Results

    SciTech Connect (OSTI)

    Bixler, Nathan E.; Osborn, Douglas M.; Sallaberry, Cedric Jean-Marie; Eckert-Gallup, Aubrey Celia; Mattie, Patrick D.; Ghosh, S. Tina

    2014-02-01T23:59:59.000Z

    This paper describes the convergence of MELCOR Accident Consequence Code System, Version 2 (MACCS2) probabilistic results of offsite consequences for the uncertainty analysis of the State-of-the-Art Reactor Consequence Analyses (SOARCA) unmitigated long-term station blackout scenario at the Peach Bottom Atomic Power Station. The consequence metrics evaluated are individual latent-cancer fatality (LCF) risk and individual early fatality risk. Consequence results are presented as conditional risk (i.e., assuming the accident occurs, risk per event) to individuals of the public as a result of the accident. In order to verify convergence for this uncertainty analysis, as recommended by the Nuclear Regulatory Commission’s Advisory Committee on Reactor Safeguards, a ‘high’ source term from the original population of Monte Carlo runs has been selected to be used for: (1) a study of the distribution of consequence results stemming solely from epistemic uncertainty in the MACCS2 parameters (i.e., separating the effect from the source term uncertainty), and (2) a comparison between Simple Random Sampling (SRS) and Latin Hypercube Sampling (LHS) in order to validate the original results obtained with LHS. Three replicates (each using a different random seed) of size 1,000 each using LHS and another set of three replicates of size 1,000 using SRS are analyzed. The results show that the LCF risk results are well converged with either LHS or SRS sampling. The early fatality risk results are less well converged at radial distances beyond 2 miles, and this is expected due to the sparse data (predominance of “zero” results).

  17. Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment. Volume 3, Appendices C, D, E, F, and G

    SciTech Connect (OSTI)

    Harper, F.T.; Young, M.L.; Miller, L.A. [Sandia National Labs., Albuquerque, NM (United States)] [and others

    1995-01-01T23:59:59.000Z

    The development of two new probabilistic accident consequence codes, MACCS and COSYMA, completed in 1990, estimate the risks presented by nuclear installations based on postulated frequencies and magnitudes of potential accidents. In 1991, the US Nuclear Regulatory Commission (NRC) and the Commission of the European Communities (CEC) began a joint uncertainty analysis of the two codes. The objective was to develop credible and traceable uncertainty distributions for the input variables of the codes. Expert elicitation, developed independently, was identified as the best technology available for developing a library of uncertainty distributions for the selected consequence parameters. The study was formulated jointly and was limited to the current code models and to physical quantities that could be measured in experiments. To validate the distributions generated for the wet deposition input variables, samples were taken from these distributions and propagated through the wet deposition code model along with the Gaussian plume model (GPM) implemented in the MACCS and COSYMA codes. Resulting distributions closely replicated the aggregated elicited wet deposition distributions. Project teams from the NRC and CEC cooperated successfully to develop and implement a unified process for the elaboration of uncertainty distributions on consequence code input parameters. Formal expert judgment elicitation proved valuable for synthesizing the best available information. Distributions on measurable atmospheric dispersion and deposition parameters were successfully elicited from experts involved in the many phenomenological areas of consequence analysis. This volume is the third of a three-volume document describing the project and contains descriptions of the probability assessment principles; the expert identification and selection process; the weighting methods used; the inverse modeling methods; case structures; and summaries of the consequence codes.

  18. An Analysis of Price Determination and Markups in the Air-Conditioning and Heating Equipment Industry

    SciTech Connect (OSTI)

    Dale, Larry; Millstein, Dev; Coughlin, Katie; Van Buskirk, Robert; Rosenquist, Gregory; Lekov, Alex; Bhuyan, Sanjib

    2004-01-30T23:59:59.000Z

    In this report we calculate the change in final consumer prices due to minimum efficiency standards, focusing on a standard economic model of the air-conditioning and heating equipment (ACHE) wholesale industry. The model examines the relationship between the marginal cost to distribute and sell equipment and the final consumer price in this industry. The model predicts that the impact of a standard on the final consumer price is conditioned by its impact on marginal distribution costs. For example, if a standard raises the marginal cost to distribute and sell equipment a small amount, the model predicts that the standard will raise the final consumer price a small amount as well. Statistical analysis suggest that standards do not increase the amount of labor needed to distribute equipment the same employees needed to sell lower efficiency equipment can sell high efficiency equipment. Labor is a large component of the total marginal cost to distribute and sell air-conditioning and heating equipment. We infer from this that standards have a relatively small impact on ACHE marginal distribution and sale costs. Thus, our model predicts that a standard will have a relatively small impact on final ACHE consumer prices. Our statistical analysis of U.S. Census Bureau wholesale revenue tends to confirm this model prediction. Generalizing, we find that the ratio of manufacturer price to final consumer price prior to a standard tends to exceed the ratio of the change in manufacturer price to the change in final consumer price resulting from a standard. The appendix expands our analysis through a typical distribution chain for commercial and residential air-conditioning and heating equipment.

  19. Oil Prices, Stock Markets and Portfolio Investment: Evidence from Sector Analysis in Europe over the Last Decade

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    the dynamic relationship between oil price variations and stock markets. The pioneering paper by Jones model with GARCH effects to American monthly data and shows a significant relationship between oil priceOil Prices, Stock Markets and Portfolio Investment: Evidence from Sector Analysis in Europe over

  20. Uncertainties analysis of fission fraction for reactor antineutrino experiments

    E-Print Network [OSTI]

    X. B. Ma; F. Lu; L. Z. Wang; Y. X. Chen; W. L. Zhong; F. P. An

    2015-03-17T23:59:59.000Z

    Reactor antineutrino experiment are used to study neutrino oscillation, search for signatures of nonstandard neutrino interaction, and monitor reactor operation for safeguard application. Reactor simulation is an important source of uncertainties for a reactor neutrino experiment. Commercial code is used for reactor simulation to evaluate fission fraction in Daya Bay neutrino experiment, but the source code doesn't open to our researcher results from commercial secret. In this study, The open source code DRAGON was improved to calculate the fission rates of the four most important isotopes in fissions, $^{235}$U,$^{238}$U,$^{239}$Pu and $^{241}$Pu, and then was validated for PWRs using the Takahama-3 benchmark. The fission fraction results are consistent with those of MIT's results. Then, fission fraction of Daya Bay reactor core was calculated by using improved DRAGON code, and the fission fraction calculated by DRAGON agreed well with these calculated by SCIENCE. The average deviation less than 5\\% for all the four isotopes. The correlation coefficient matrix between $^{235}$U,$^{238}$U,$^{239}$Pu and $^{241}$Pu were also studied using DRAGON, and then the uncertainty of the antineutrino flux by the fission fraction was calculated by using the correlation coefficient matrix. The uncertainty of the antineutrino flux by the fission fraction simulation is 0.6\\% per core for Daya Bay antineutrino experiment. The uncertainties source of fission fraction calculation need further to be studied in the future.

  1. Application of the probabilistic collocation method for an uncertainty analysis of a simple ocean model

    E-Print Network [OSTI]

    Webster, Mort David.; Tatang, Menner A.; McRae, Gregory J.

    This paper presents the probabilistic collocation method as a computationally efficient method for performing uncertainty analysis on large complex models such as those used in global climate change research. The collocation ...

  2. SSL Pricing and Efficacy Trend Analysis for Utility Program Planning

    SciTech Connect (OSTI)

    Tuenge, Jason R.

    2013-10-01T23:59:59.000Z

    An LED lamp or luminaire can generally be found that matches or exceeds the efficacy of benchmark technologies in a given product category, and LED products continue to expand into ever-higher lumen output niches. However, the price premium for LED continues to pose a barrier to adoption in many applications, in spite of expected savings from reduced energy use and maintenance. Other factors—such as dimmability and quality of light—can also present challenges. The appropriate type, timing, and magnitude of energy efficiency activities will vary from organization to organization based on local variables and the method of evaluation. A number of factors merit consideration when prioritizing activities for development. Category-specific projections for pricing and efficacy are provided herein to assist in efficiency program planning efforts.

  3. A QUALITATIVE APPROACH TO UNCERTAINTY ANALYSIS FOR THE PWR ROD EJECTION ACCIDENT

    SciTech Connect (OSTI)

    DIAMOND,D.J.; ARONSON,A.; YANG,C.

    2000-06-19T23:59:59.000Z

    In order to understand best-estimate calculations of the peak local fuel enthalpy during a rod ejection accident, an assessment of the uncertainty has been completed. The analysis took into account point kinetics parameters which would be available from a three-dimensional core model and engineering judgment as to the uncertainty in those parameters. Sensitivity studies to those parameters were carried out using the best-estimate code PARCS. The results showed that the uncertainty (corresponding to one standard deviation) in local fuel enthalpy would be determined primarily by the uncertainty in ejected rod worth and delayed neutron fraction. For an uncertainty in the former of 8% and the latter of 5%, the uncertainty in fuel enthalpy varied from 51% to 69% for control rod worth varying from $1.2 to $1.0. Also considered in the uncertainty were the errors introduced by uncertainties in the Doppler reactivity coefficient, the fuel pellet specific heat, and assembly and fuel pin peaking factors.

  4. PROBABILISTIC SENSITIVITY AND UNCERTAINTY ANALYSIS WORKSHOP SUMMARY REPORT

    SciTech Connect (OSTI)

    Seitz, R

    2008-06-25T23:59:59.000Z

    Stochastic or probabilistic modeling approaches are being applied more frequently in the United States and globally to quantify uncertainty and enhance understanding of model response in performance assessments for disposal of radioactive waste. This increased use has resulted in global interest in sharing results of research and applied studies that have been completed to date. This technical report reflects the results of a workshop that was held to share results of research and applied work related to performance assessments conducted at United States Department of Energy sites. Key findings of this research and applied work are discussed and recommendations for future activities are provided.

  5. Uncertainty Analysis Framework - Hanford Site-Wide Groundwater Flow and Transport Model

    SciTech Connect (OSTI)

    Cole, Charles R.; Bergeron, Marcel P.; Murray, Christopher J.; Thorne, Paul D.; Wurstner, Signe K.; Rogers, Phillip M.

    2001-11-09T23:59:59.000Z

    Pacific Northwest National Laboratory (PNNL) embarked on a new initiative to strengthen the technical defensibility of the predictions being made with a site-wide groundwater flow and transport model at the U.S. Department of Energy Hanford Site in southeastern Washington State. In FY 2000, the focus of the initiative was on the characterization of major uncertainties in the current conceptual model that would affect model predictions. The long-term goals of the initiative are the development and implementation of an uncertainty estimation methodology in future assessments and analyses using the site-wide model. This report focuses on the development and implementation of an uncertainty analysis framework.

  6. Analysis and Reduction of Complex Networks Under Uncertainty.

    SciTech Connect (OSTI)

    Ghanem, Roger G [University of Southern California

    2014-07-31T23:59:59.000Z

    This effort was a collaboration with Youssef Marzouk of MIT, Omar Knio of Duke University (at the time at Johns Hopkins University) and Habib Najm of Sandia National Laboratories. The objective of this effort was to develop the mathematical and algorithmic capacity to analyze complex networks under uncertainty. Of interest were chemical reaction networks and smart grid networks. The statements of work for USC focused on the development of stochastic reduced models for uncertain networks. The USC team was led by Professor Roger Ghanem and consisted of one graduate student and a postdoc. The contributions completed by the USC team consisted of 1) methodology and algorithms to address the eigenvalue problem, a problem of significance in the stability of networks under stochastic perturbations, 2) methodology and algorithms to characterize probability measures on graph structures with random flows. This is an important problem in characterizing random demand (encountered in smart grid) and random degradation (encountered in infrastructure systems), as well as modeling errors in Markov Chains (with ubiquitous relevance !). 3) methodology and algorithms for treating inequalities in uncertain systems. This is an important problem in the context of models for material failure and network flows under uncertainty where conditions of failure or flow are described in the form of inequalities between the state variables.

  7. 1997-2001 by M. Kostic Ch.5: Uncertainty/Error Analysis

    E-Print Network [OSTI]

    Kostic, Milivoje M.

    1 ©1997-2001 by M. Kostic Ch.5: Uncertainty/Error Analysis · Introduction · Bias and Precision Summation/Propagation (Expanded Combined Uncertainty) · Problem 5-30 ©1997-2001 by M. Kostic Ch.5) at corresponding Probability (%P) Remember: u = d%P = t,%PS (@ %P); z=t=d/S #12;2 ©1997-2001 by M. Kostic Bias

  8. Determining Price Reasonableness in Federal ESPCs

    SciTech Connect (OSTI)

    Shonder, J.A.

    2005-03-08T23:59:59.000Z

    This document reports the findings and implementation recommendations of the Price Reasonableness Working Group to the Federal ESPC Steering Committee. The working group was formed to address concerns of agencies and oversight organizations related to pricing and fair and reasonable price determination in federal energy savings performance contracts (ESPCs). This report comprises the working group's recommendations and is the proposed draft of a training curriculum on fair and reasonable price determination for users of federal ESPCs. The report includes: (1) A review of federal regulations applicable to determining price reasonableness of federal ESPCs (section 2), (2) Brief descriptions of the techniques described in Federal Acquisition Regulations (FAR) 15.404-1 and their applicability to ESPCs (section 3), and (3) Recommended strategies and procedures for cost-effectively completing price reasonableness determinations (sections 4). Agencies have struggled with fair and reasonable price determinations in their ESPCs primarily because this alternative financing vehicle is relatively new and relatively rare in the federal sector. The methods of determining price reasonableness most familiar to federal contracting officers (price competition based on the government's design and specifications, in particular) are generally not applicable to ESPCs. The regulatory requirements for determining price reasonableness in federal ESPCs have also been misunderstood, as federal procurement professionals who are inexperienced with ESPCs are further confused by multiple directives, including Executive Order 13123, which stresses life-cycle cost-effectiveness. Uncertainty about applicable regulations and inconsistent practice and documentation among agencies have fueled claims that price reasonableness determinations have not been sufficiently rigorous in federal ESPCs or that the prices paid in ESPCs are generally higher than the prices paid for similar goods and services obtained through conventional procurements. While claims of excessive prices are largely unsubstantiated and based on anecdotal evidence, the perception that there is a problem is shared by many in the ESPC community and has been noted by auditors and oversight organizations. The Price Reasonableness Working Group determined that a more formal emphasis on FAR 15.404-1 in the ESPC process could remove much of the doubt about price reasonableness determinations. The working group's recommended consensus policy on price reasonableness stresses the price analysis techniques described in the FAR that are applicable to ESPCs and includes guidance for agencies use of these techniques in determining price reasonableness for their ESPC delivery orders. The recommended policy and guidance, if communicated to federal ESPC stakeholders, can ensure that agencies will comply with the FAR in awarding ESPCs, obtain fair and reasonable prices and best value for the government, and follow procedures that provide auditable documentation of due diligence in price reasonableness determinations.

  9. Pricing with uncertain customer valuations

    E-Print Network [OSTI]

    2007-10-16T23:59:59.000Z

    Building Room 329, 200 W Packer Ave, Bethlehem, PA 18015, ... of uncertainty motivates the introduction of non-linearities in the demand as a function of price ... of price-response functions, parametrized by a risk sensitivity coefficient, which

  10. Uncertainty analysis for probabilistic pipe fracture evaluations in LBB applications

    SciTech Connect (OSTI)

    Rahman, S.; Ghadiali, N.; Wilkowski, G.

    1997-04-01T23:59:59.000Z

    During the NRC`s Short Cracks in Piping and Piping Welds Program at Battelle, a probabilistic methodology was developed to conduct fracture evaluations of circumferentially cracked pipes for application to leak-rate detection. Later, in the IPIRG-2 program, several parameters that may affect leak-before-break and other pipe flaw evaluations were identified. This paper presents new results from several uncertainty analyses to evaluate the effects of normal operating stresses, normal plus safe-shutdown earthquake stresses, off-centered cracks, restraint of pressure-induced bending, and dynamic and cyclic loading rates on the conditional failure probability of pipes. systems in BWR and PWR. For each parameter, the sensitivity to conditional probability of failure and hence, its importance on probabilistic leak-before-break evaluations were determined.

  11. analysis uncertainty: Topics by E-print Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Theses and Dissertations Summary: ??Hypersonic vehicles face a challenging flight environment. The aerothermoelastic analysis of its components requires numerous simplifying...

  12. Uncertainty analysis of multi-rate kinetics of uranium desorption from sediments

    SciTech Connect (OSTI)

    Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.; Zhang, Guannan

    2014-01-01T23:59:59.000Z

    A multi-rate expression for uranyl [U(VI)] surface complexation reactions has been proposed to describe diffusion-limited U(VI) sorption/desorption in heterogeneous subsurface sediments. An important assumption in the rate expression is that its rate constants follow a certain type probability distribution. In this paper, a Bayes-based, Differential Evolution Markov Chain method was used to assess the distribution assumption and to analyze parameter and model structure uncertainties. U(VI) desorption from a contaminated sediment at the US Hanford 300 Area, Washington was used as an example for detail analysis. The results indicated that: 1) the rate constants in the multi-rate expression contain uneven uncertainties with slower rate constants having relative larger uncertainties; 2) the lognormal distribution is an effective assumption for the rate constants in the multi-rate model to simualte U(VI) desorption; 3) however, long-term prediction and its uncertainty may be significantly biased by the lognormal assumption for the smaller rate constants; and 4) both parameter and model structure uncertainties can affect the extrapolation of the multi-rate model with a larger uncertainty from the model structure. The results provide important insights into the factors contributing to the uncertainties of the multi-rate expression commonly used to describe the diffusion or mixing-limited sorption/desorption of both organic and inorganic contaminants in subsurface sediments.

  13. MMIII* by M. Kosticwww.kostic.niu.edu Error or Uncertainty Analysis

    E-Print Network [OSTI]

    Kostic, Milivoje M.

    Gas Analysis SO2 , NO, NO2 , CO, CO2 , THC, O2Sample Tanks Particle Probe Gas Probe Exhaust DMA1 © MMIII* by M. Kosticwww.kostic.niu.edu Unleashing Error or Uncertainty Analysis of Measurement - Differential Mobility Analyzer CNC ­ Condensation Nuclei Counter HPLPC ­ High Pressure Large Particle Counter

  14. Two-dimensional cross-section and SED uncertainty analysis for the Fusion Engineering Device (FED)

    SciTech Connect (OSTI)

    Embrechts, M.J.; Urban, W.T.; Dudziak, D.J.

    1982-01-01T23:59:59.000Z

    The theory of two-dimensional cross-section and secondary-energy-distribution (SED) sensitivity was implemented by developing a two-dimensional sensitivity and uncertainty analysis code, SENSIT-2D. Analyses of the Fusion Engineering Design (FED) conceptual inboard shield indicate that, although the calculated uncertainties in the 2-D model are of the same order of magnitude as those resulting from the 1-D model, there might be severe differences. The more complex the geometry, the more compulsory a 2-D analysis becomes. Specific results show that the uncertainty for the integral heating of the toroidal field (TF) coil for the FED is 114.6%. The main contributors to the cross-section uncertainty are chromium and iron. Contributions to the total uncertainty were smaller for nickel, copper, hydrogen and carbon. All analyses were performed with the Los Alamos 42-group cross-section library generated from ENDF/B-V data, and the COVFILS covariance matrix library. The large uncertainties due to chromium result mainly from large convariances for the chromium total and elastic scattering cross sections.

  15. IAEA CRP on HTGR Uncertainty Analysis: Benchmark Definition and Test Cases

    SciTech Connect (OSTI)

    Gerhard Strydom; Frederik Reitsma; Hans Gougar; Bismark Tyobeka; Kostadin Ivanov

    2012-11-01T23:59:59.000Z

    Uncertainty and sensitivity studies are essential elements of the reactor simulation code verification and validation process. Although several international uncertainty quantification activities have been launched in recent years in the LWR, BWR and VVER domains (e.g. the OECD/NEA BEMUSE program [1], from which the current OECD/NEA LWR Uncertainty Analysis in Modelling (UAM) benchmark [2] effort was derived), the systematic propagation of uncertainties in cross-section, manufacturing and model parameters for High Temperature Reactor (HTGR) designs has not been attempted yet. This paper summarises the scope, objectives and exercise definitions of the IAEA Coordinated Research Project (CRP) on HTGR UAM [3]. Note that no results will be included here, as the HTGR UAM benchmark was only launched formally in April 2012, and the specification is currently still under development.

  16. SOARCA Peach Bottom Atomic Power Station Long-Term Station Blackout Uncertainty Analysis: Knowledge Advancement.

    SciTech Connect (OSTI)

    Gauntt, Randall O.; Mattie, Patrick D.; Bixler, Nathan E.; Ross, Kyle; Cardoni, Jeffrey N; Kalinich, Donald A.; Osborn, Douglas M.; Sallaberry, Cedric Jean-Marie; Ghosh, S. Tina

    2014-02-01T23:59:59.000Z

    This paper describes the knowledge advancements from the uncertainty analysis for the State-of- the-Art Reactor Consequence Analyses (SOARCA) unmitigated long-term station blackout accident scenario at the Peach Bottom Atomic Power Station. This work assessed key MELCOR and MELCOR Accident Consequence Code System, Version 2 (MACCS2) modeling uncertainties in an integrated fashion to quantify the relative importance of each uncertain input on potential accident progression, radiological releases, and off-site consequences. This quantitative uncertainty analysis provides measures of the effects on consequences, of each of the selected uncertain parameters both individually and in interaction with other parameters. The results measure the model response (e.g., variance in the output) to uncertainty in the selected input. Investigation into the important uncertain parameters in turn yields insights into important phenomena for accident progression and off-site consequences. This uncertainty analysis confirmed the known importance of some parameters, such as failure rate of the Safety Relief Valve in accident progression modeling and the dry deposition velocity in off-site consequence modeling. The analysis also revealed some new insights, such as dependent effect of cesium chemical form for different accident progressions. (auth)

  17. Uncertainty in soil-structure interaction analysis arising from differences in analytical techniques

    SciTech Connect (OSTI)

    Maslenikov, O. R.; Chen, J. C.; Johnson, J. J.

    1982-07-01T23:59:59.000Z

    This study addresses uncertainties arising from variations in different modeling approaches to soil-structure interaction of massive structures at a nuclear power plant. To perform a comprehensive systems analysis, it is necessary to quantify, for each phase of the traditional analysis procedure, both the realistic seismic response and the uncertainties associated with them. In this study two linear soil-structure interaction techniques were used to analyze the Zion, Illinois nuclear power plant: a direct method using the FLUSH computer program and a substructure approach using the CLASSI family of computer programs. In-structure response from two earthquakes, one real and one synthetic, was compared. Structure configurations from relatively simple to complicated multi-structure cases were analyzed. The resulting variations help quantify uncertainty in structure response due to analysis procedures.

  18. The impact of uncertainty and risk measures

    E-Print Network [OSTI]

    Jo, Soojin; Jo, Soojin

    2012-01-01T23:59:59.000Z

    uncertainty on investment: Evidence from TEXAS oil drilling.investment decisions to changes in uncertainty using Texas oiloil price uncertainty deters var- ious types of real economic activities, such as output production, investment,

  19. Great price spike of '93: An analysis of lumber and stumpage prices in the pacific northwest. Forest Service research paper

    SciTech Connect (OSTI)

    Sohngen, B.L.; Haynes, R.W.

    1994-08-01T23:59:59.000Z

    The report includes prices for red alder hardwood logs which are published and analyzed for reliability consistency, and robustness. Timberland managers can use these prices to make decisions regarding land management. They show that values for red alder logs have been increasing steadily for the past 11 years.

  20. Analysis of uncertainties in CRAC2 calculations: the inhalation pathway

    SciTech Connect (OSTI)

    Killough, G.G.; Dunning, D.E. Jr.

    1984-01-01T23:59:59.000Z

    CRAC2 is a computer code for estimating the health effects and economic costs that might result from a release of radioactivity from a nuclear reactor to the environment. This paper describes tests of sensitivity of the predicted health effects to uncertainties in parameters associated with inhalation of the released radionuclides. These parameters are the particle size of the carrier aerosol and, for each element in the release, the clearance parameters for the lung model on which the code's dose conversion factors for inhalation are based. CRAC2 uses hourly meteorological data and a straight-line Gaussian plume model to predict the transport of airborne radioactivity; it includes models for plume depletion and population evacuation, and data for the distributions of population and land use. The code can compute results for single weather sequences, or it can perform random sampling of weather sequences from the meteorological data file and compute results for each weather sequence in the sample. For the work described in this paper, we concentrated on three fixed weather sequences that represent a range of conditions. For each fixed weather sequence, we applied random sampling to joint distributions of the inhalation parameters in order to estimate the sensitivity of the predicted health effects. All sampling runs produced coefficients of variation that were less than 50%, but some differences of means between weather sequences were substantial, as were some differences between means and the corresponding CRAC2 results without random sampling. Early injuries showed differences of as much as 1 to 2 orders of magnitude, while the differences in early fatalities were less than a factor of 2. Latent cancer fatalities varied by less than 10%. 19 references, 6 figures, 3 tables.

  1. Uncertainty Analysis for a Virtual Flow Meter Using an Air-Handling Unit Chilled Water Valve

    SciTech Connect (OSTI)

    Song, Li; Wang, Gang; Brambley, Michael R.

    2013-04-28T23:59:59.000Z

    A virtual water flow meter is developed that uses the chilled water control valve on an air-handling unit as a measurement device. The flow rate of water through the valve is calculated using the differential pressure across the valve and its associated coil, the valve command, and an empirically determined valve characteristic curve. Thus, the probability of error in the measurements is significantly greater than for conventionally manufactured flow meters. In this paper, mathematical models are developed and used to conduct uncertainty analysis for the virtual flow meter, and the results from the virtual meter are compared to measurements made with an ultrasonic flow meter. Theoretical uncertainty analysis shows that the total uncertainty in flow rates from the virtual flow meter is 1.46% with 95% confidence; comparison of virtual flow meter results with measurements from an ultrasonic flow meter yielded anuncertainty of 1.46% with 99% confidence. The comparable results from the theoretical uncertainty analysis and empirical comparison with the ultrasonic flow meter corroborate each other, and tend to validate the approach to computationally estimating uncertainty for virtual sensors introduced in this study.

  2. Risk Analysis and Decision-Making Under Uncertainty: A Strategy...

    Office of Environmental Management (EM)

    Estimation Since 2002 To view all the P&RA CoP 2014 Technical Exchange Meeting videos click here. Video Presentation - Part 1 Video Presentation - Part 2 Risk Analysis and...

  3. Incorporating uncertainty in the Life Cycle Cost Analysis of pavements

    E-Print Network [OSTI]

    Swei, Omar Abdullah

    2012-01-01T23:59:59.000Z

    Life Cycle Cost Analysis (LCCA) is an important tool to evaluate the economic performance of alternative investments for a given project. It considers the total cost to construct, maintain, and operate a pavement over its ...

  4. Tariff-based analysis of commercial building electricity prices

    E-Print Network [OSTI]

    Coughlin, Katie M.; Bolduc, Chris A.; Rosenquist, Greg J.; Van Buskirk, Robert D.; McMahon, James E.

    2008-01-01T23:59:59.000Z

    this analysis. For the energy consumption data, within eachenergy consumption, for January and July, for the CBECS data. . . . . . . . . . . . . . . . . . . . . . . . . . . . .4]. The billing data include energy consumption, demand and

  5. Use of Forward Sensitivity Analysis Method to Improve Code Scaling, Applicability, and Uncertainty (CSAU) Methodology

    SciTech Connect (OSTI)

    Haihua Zhao; Vincent A. Mousseau; Nam T. Dinh

    2010-10-01T23:59:59.000Z

    Code Scaling, Applicability, and Uncertainty (CSAU) methodology was developed in late 1980s by US NRC to systematically quantify reactor simulation uncertainty. Basing on CSAU methodology, Best Estimate Plus Uncertainty (BEPU) methods have been developed and widely used for new reactor designs and existing LWRs power uprate. In spite of these successes, several aspects of CSAU have been criticized for further improvement: i.e., (1) subjective judgement in PIRT process; (2) high cost due to heavily relying large experimental database, needing many experts man-years work, and very high computational overhead; (3) mixing numerical errors with other uncertainties; (4) grid dependence and same numerical grids for both scaled experiments and real plants applications; (5) user effects; Although large amount of efforts have been used to improve CSAU methodology, the above issues still exist. With the effort to develop next generation safety analysis codes, new opportunities appear to take advantage of new numerical methods, better physical models, and modern uncertainty qualification methods. Forward sensitivity analysis (FSA) directly solves the PDEs for parameter sensitivities (defined as the differential of physical solution with respective to any constant parameter). When the parameter sensitivities are available in a new advanced system analysis code, CSAU could be significantly improved: (1) Quantifying numerical errors: New codes which are totally implicit and with higher order accuracy can run much faster with numerical errors quantified by FSA. (2) Quantitative PIRT (Q-PIRT) to reduce subjective judgement and improving efficiency: treat numerical errors as special sensitivities against other physical uncertainties; only parameters having large uncertainty effects on design criterions are considered. (3) Greatly reducing computational costs for uncertainty qualification by (a) choosing optimized time steps and spatial sizes; (b) using gradient information (sensitivity result) to reduce sampling number. (4) Allowing grid independence for scaled integral effect test (IET) simulation and real plant applications: (a) eliminate numerical uncertainty on scaling; (b) reduce experimental cost by allowing smaller scaled IET; (c) eliminate user effects. This paper will review the issues related to the current CSAU, introduce FSA, discuss a potential Q-PIRT process, and show simple examples to perform FSA. Finally, the general research direction and requirements to use FSA in a system analysis code will be discussed.

  6. An Analysis of the Effects of Residential Photovoltaic Energy Systems on Home Sales Prices in California

    E-Print Network [OSTI]

    Hoen, Ben

    2011-01-01T23:59:59.000Z

    Residential Photovoltaic Energy Systems on Home Sales PricesResidential Photovoltaic Energy Systems on Home Sales Prices

  7. Robust Efficient Frontier Analysis with a Separable Uncertainty Model

    E-Print Network [OSTI]

    2007-11-29T23:59:59.000Z

    We consider MV analysis with n risky assets held over a period of time. ..... since it is the pointwise infimum of a family of linear functions. ...... for Circuit & System Solutions award 2003-CT-888, by JPL award I291856, by the Precourt. Institute ...

  8. Performance evaluation of passive cooling in office buildings based on uncertainty and sensitivity analysis

    SciTech Connect (OSTI)

    Breesch, H. [Building Physics, Construction and Services, Department of Architecture and Urban Planning, Ghent University, J. Plateaustraat 22, B-9000 Ghent (Belgium); Sustainable Building Research Group, Department of Construction, Catholic University College Ghent, Gebroeders Desmetstraat 1, B-9000 Ghent (Belgium); Janssens, A. [Building Physics, Construction and Services, Department of Architecture and Urban Planning, Ghent University, J. Plateaustraat 22, B-9000 Ghent (Belgium)

    2010-08-15T23:59:59.000Z

    Natural night ventilation is an interesting passive cooling method in moderate climates. Driven by wind and stack generated pressures, it cools down the exposed building structure at night, in which the heat of the previous day is accumulated. The performance of natural night ventilation highly depends on the external weather conditions and especially on the outdoor temperature. An increase of this outdoor temperature is noticed over the last century and the IPCC predicts an additional rise to the end of this century. A methodology is needed to evaluate the reliable operation of the indoor climate of buildings in case of warmer and uncertain summer conditions. The uncertainty on the climate and on other design data can be very important in the decision process of a building project. The aim of this research is to develop a methodology to predict the performance of natural night ventilation using building energy simulation taking into account the uncertainties in the input. The performance evaluation of natural night ventilation is based on uncertainty and sensitivity analysis. The results of the uncertainty analysis showed that thermal comfort in a single office cooled with single-sided night ventilation had the largest uncertainty. The uncertainties on thermal comfort in case of passive stack and cross ventilation were substantially smaller. However, since wind, as the main driving force for cross ventilation, is highly variable, the cross ventilation strategy required larger louvre areas than the stack ventilation strategy to achieve a similar performance. The differences in uncertainty between the orientations were small. Sensitivity analysis was used to determine the most dominant set of input parameters causing the uncertainty on thermal comfort. The internal heat gains, solar heat gain coefficient of the sunblinds, internal convective heat transfer coefficient, thermophysical properties related to thermal mass, set-point temperatures controlling the natural night ventilation, the discharge coefficient C{sub d} of the night ventilation opening and the wind pressure coefficients C{sub p} were identified to have the largest impact on the uncertainty of thermal comfort. The impact of the warming climate on the uncertainty of thermal comfort was determined. The uncertainty on thermal comfort appeared to increase significantly when a weather data set with recurrence time of 10 years (warm weather) was applied in the transient simulations in stead of a standard weather data set. Natural night ventilation, designed for normal weather conditions, was clearly not able to ensure a high probability of good thermal comfort in warm weather. To ensure a high probability of good thermal comfort and to reduce the performance uncertainty in a warming climate, natural night ventilation has to be combined with additional measures. Different measures were analysed, based on the results of the sensitivity analysis. All the measures were shown to significantly decrease the uncertainty of thermal comfort in warm weather. The study showed the importance to carry out simulations with a warm weather data set together with the analysis under typical conditions. This approach allows to gain a better understanding of the performance of a natural night ventilation design, and to optimize the design to a robust solution. (author)

  9. Uncertainty and sensitivity analysis of fission gas behavior in engineering-scale fuel modeling

    SciTech Connect (OSTI)

    G. Pastore; L.P. Swiler; J.D. Hales; S.R. Novascone; D.M. Perez; B.W. Spencer; L. Luzzi; P. Van Uffelen; R.L. Williamson

    2014-10-01T23:59:59.000Z

    The role of uncertainties in fission gas behavior calculations as part of engineering-scale nuclear fuel modeling is investigated using the BISON fuel performance code and a recently implemented physics-based model for the coupled fission gas release and swelling. Through the integration of BISON with the DAKOTA software, a sensitivity analysis of the results to selected model parameters is carried out based on UO2 single-pellet simulations covering different power regimes. The parameters are varied within ranges representative of the relative uncertainties and consistent with the information from the open literature. The study leads to an initial quantitative assessment of the uncertainty in fission gas behavior modeling with the parameter characterization presently available. Also, the relative importance of the single parameters is evaluated. Moreover, a sensitivity analysis is carried out based on simulations of a fuel rod irradiation experiment, pointing out a significant impact of the considered uncertainties on the calculated fission gas release and cladding diametral strain. The results of the study indicate that the commonly accepted deviation between calculated and measured fission gas release by a factor of 2 approximately corresponds to the inherent modeling uncertainty at high fission gas release. Nevertheless, higher deviations may be expected for values around 10% and lower. Implications are discussed in terms of directions of research for the improved modeling of fission gas behavior for engineering purposes.

  10. Implementation of a Bayesian Engine for Uncertainty Analysis

    SciTech Connect (OSTI)

    Leng Vang; Curtis Smith; Steven Prescott

    2014-08-01T23:59:59.000Z

    In probabilistic risk assessment, it is important to have an environment where analysts have access to a shared and secured high performance computing and a statistical analysis tool package. As part of the advanced small modular reactor probabilistic risk analysis framework implementation, we have identified the need for advanced Bayesian computations. However, in order to make this technology available to non-specialists, there is also a need of a simplified tool that allows users to author models and evaluate them within this framework. As a proof-of-concept, we have implemented an advanced open source Bayesian inference tool, OpenBUGS, within the browser-based cloud risk analysis framework that is under development at the Idaho National Laboratory. This development, the “OpenBUGS Scripter” has been implemented as a client side, visual web-based and integrated development environment for creating OpenBUGS language scripts. It depends on the shared server environment to execute the generated scripts and to transmit results back to the user. The visual models are in the form of linked diagrams, from which we automatically create the applicable OpenBUGS script that matches the diagram. These diagrams can be saved locally or stored on the server environment to be shared with other users.

  11. A stochastic framework for uncertainty analysis in electric power transmission systems with wind generation

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    of generating units, the transfer of electric power over networks of transmission lines and, finally1 A stochastic framework for uncertainty analysis in electric power transmission systems with wind an electric transmission network with wind power generation and their impact on its reliability. A stochastic

  12. Reservoir Simulation and Uncertainty Analysis of Enhanced CBM Production Using Artificial Neural Networks

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    SPE 125959 Reservoir Simulation and Uncertainty Analysis of Enhanced CBM Production Using, Society of Petroleum Engineers This paper was prepared for presentation at the 2009 SPE Eastern Regional by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers

  13. Quantitative uncertainty and sensitivity analysis of a PWR control rod ejection accident

    SciTech Connect (OSTI)

    Pasichnyk, I.; Perin, Y.; Velkov, K. [Gesellschaft flier Anlagen- und Reaktorsicherheit - GRS mbH, Boltzmannstasse 14, 85748 Garching bei Muenchen (Germany)

    2013-07-01T23:59:59.000Z

    The paper describes the results of the quantitative Uncertainty and Sensitivity (U/S) Analysis of a Rod Ejection Accident (REA) which is simulated by the coupled system code ATHLET-QUABOX/CUBBOX applying the GRS tool for U/S analysis SUSA/XSUSA. For the present study, a UOX/MOX mixed core loading based on a generic PWR is modeled. A control rod ejection is calculated for two reactor states: Hot Zero Power (HZP) and 30% of nominal power. The worst cases for the rod ejection are determined by steady-state neutronic simulations taking into account the maximum reactivity insertion in the system and the power peaking factor. For the U/S analysis 378 uncertain parameters are identified and quantified (thermal-hydraulic initial and boundary conditions, input parameters and variations of the two-group cross sections). Results for uncertainty and sensitivity analysis are presented for safety important global and local parameters. (authors)

  14. An Analysis of the Price Elasticity of Demand for Household Appliances

    SciTech Connect (OSTI)

    Fujita, Kimberly; Dale, Larry; Fujita, K. Sydny

    2008-01-25T23:59:59.000Z

    This report summarizes our study of the price elasticity of demand for home appliances, including refrigerators, clothes washers, and dishwashers. In the context of increasingly stringent appliance standards, we are interested in what kind of impact the increased manufacturing costs caused by higher efficiency requirements will have on appliance sales. We begin with a review of existing economics literature describing the impact of economic variables on the sale of durable goods.We then describe the market for home appliances and changes in this market over the past 20 years, performing regression analysis on the shipments of home appliances and relevant economic variables including changes to operating cost and household income. Based on our analysis, we conclude that the demand for home appliances is price inelastic.

  15. The price of electricity from private power producers: Stage 2, Expansion of sample and preliminary statistical analysis

    SciTech Connect (OSTI)

    Comnes, G.A.; Belden, T.N.; Kahn, E.P.

    1995-02-01T23:59:59.000Z

    The market for long-term bulk power is becoming increasingly competitive and mature. Given that many privately developed power projects have been or are being developed in the US, it is possible to begin to evaluate the performance of the market by analyzing its revealed prices. Using a consistent method, this paper presents levelized contract prices for a sample of privately developed US generation properties. The sample includes 26 projects with a total capacity of 6,354 MW. Contracts are described in terms of their choice of technology, choice of fuel, treatment of fuel price risk, geographic location, dispatchability, expected dispatch niche, and size. The contract price analysis shows that gas technologies clearly stand out as the most attractive. At an 80% capacity factor, coal projects have an average 20-year levelized price of $0.092/kWh, whereas natural gas combined cycle and/or cogeneration projects have an average price of $0.069/kWh. Within each technology type subsample, however, there is considerable variation. Prices for natural gas combustion turbines and one wind project are also presented. A preliminary statistical analysis is conducted to understand the relationship between price and four categories of explanatory factors including product heterogeneity, geographic heterogeneity, economic and technological change, and other buyer attributes (including avoided costs). Because of residual price variation, we are unable to accept the hypothesis that electricity is a homogeneous product. Instead, the analysis indicates that buyer value still plays an important role in the determination of price for competitively-acquired electricity.

  16. Implementation and Validation of Uncertainty Analysis of Available Energy and Available Power

    SciTech Connect (OSTI)

    Jon P. Christophersen; John L. Morrison; B. J. Schubert; Shawn Allred

    2007-04-01T23:59:59.000Z

    The Idaho National Laboratory does extensive testing and evaluation of state-of-the-art batteries and ultracapacitors for hybrid-electric vehicle applications as part of the FreedomCAR and Vehicle Technologies Program. Significant parameters of interest include Available Energy and Available Power. Documenting the uncertainty analysis of these derived parameters is a very complex problem. The error is an unknown combination of both linearity and offset; the analysis presented in this paper computes the uncertainty both ways and then the most conservative method is assumed (which is the worst case scenario). Each method requires the use of over 134 equations, some of which are derived and some are measured values. This includes the measurement device error (calibration error) and bit resolution and analog noise error (standard deviation error). The implementation of these equations to acquire a closed form answer was done using Matlab (an array based programming language) and validated using Monte Carlo simulations.

  17. AEP Ohio gridSMART Demonstration Project Real-Time Pricing Demonstration Analysis

    SciTech Connect (OSTI)

    Widergren, Steven E.; Subbarao, Krishnappa; Fuller, Jason C.; Chassin, David P.; Somani, Abhishek; Marinovici, Maria C.; Hammerstrom, Janelle L.

    2014-02-01T23:59:59.000Z

    This report contributes initial findings from an analysis of significant aspects of the gridSMART® Real-Time Pricing (RTP) – Double Auction demonstration project. Over the course of four years, Pacific Northwest National Laboratory (PNNL) worked with American Electric Power (AEP), Ohio and Battelle Memorial Institute to design, build, and operate an innovative system to engage residential consumers and their end-use resources in a participatory approach to electric system operations, an incentive-based approach that has the promise of providing greater efficiency under normal operating conditions and greater flexibility to react under situations of system stress. The material contained in this report supplements the findings documented by AEP Ohio in the main body of the gridSMART report. It delves into three main areas: impacts on system operations, impacts on households, and observations about the sensitivity of load to price changes.

  18. Uncertainty and sensitivity analysis of early exposure results with the MACCS Reactor Accident Consequence Model

    SciTech Connect (OSTI)

    Helton, J.C. [Arizona State Univ., Tempe, AZ (United States); Johnson, J.D. [GRAM, Inc., Albuquerque, NM (United States); McKay, M.D. [Los Alamos National Lab., NM (United States); Shiver, A.W.; Sprung, J.L. [Sandia National Labs., Albuquerque, NM (United States)

    1995-01-01T23:59:59.000Z

    Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis are used in an investigation with the MACCS model of the early health effects associated with a severe accident at a nuclear power station. The primary purpose of this study is to provide guidance on the variables to be considered in future review work to reduce the uncertainty in the important variables used in the calculation of reactor accident consequences. The effects of 34 imprecisely known input variables on the following reactor accident consequences are studied: number of early fatalities, number of cases of prodromal vomiting, population dose within 10 mi of the reactor, population dose within 1000 mi of the reactor, individual early fatality probability within 1 mi of the reactor, and maximum early fatality distance. When the predicted variables are considered collectively, the following input variables were found to be the dominant contributors to uncertainty: scaling factor for horizontal dispersion, dry deposition velocity, inhalation protection factor for nonevacuees, groundshine shielding factor for nonevacuees, early fatality hazard function alpha value for bone marrow exposure, and scaling factor for vertical dispersion.

  19. Uncertainty analysis on reactivity and discharged inventory for a pressurized water reactor fuel assembly due to {sup 235,238}U nuclear data uncertainties

    SciTech Connect (OSTI)

    Da Cruz, D. F.; Rochman, D.; Koning, A. J. [Nuclear Research and Consultancy Group NRG, Westerduinweg 3, 1755 ZG Petten (Netherlands)

    2012-07-01T23:59:59.000Z

    This paper discusses the uncertainty analysis on reactivity and inventory for a typical PWR fuel element as a result of uncertainties in {sup 235,238}U nuclear data. A typical Westinghouse 3-loop fuel assembly fuelled with UO{sub 2} fuel with 4.8% enrichment has been selected. The Total Monte-Carlo method has been applied using the deterministic transport code DRAGON. This code allows the generation of the few-groups nuclear data libraries by directly using data contained in the nuclear data evaluation files. The nuclear data used in this study is from the JEFF3.1 evaluation, and the nuclear data files for {sup 238}U and {sup 235}U (randomized for the generation of the various DRAGON libraries) are taken from the nuclear data library TENDL. The total uncertainty (obtained by randomizing all {sup 238}U and {sup 235}U nuclear data in the ENDF files) on the reactor parameters has been split into different components (different nuclear reaction channels). Results show that the TMC method in combination with a deterministic transport code constitutes a powerful tool for performing uncertainty and sensitivity analysis of reactor physics parameters. (authors)

  20. Use of Quantitative Uncertainty Analysis to Support M&VDecisions in ESPCs

    SciTech Connect (OSTI)

    Mathew, Paul A.; Koehling, Erick; Kumar, Satish

    2005-05-11T23:59:59.000Z

    Measurement and Verification (M&V) is a critical elementof an Energy Savings Performance Contract (ESPC) - without M&V, thereisno way to confirm that the projected savings in an ESPC are in factbeing realized. For any given energy conservation measure in an ESPC,there are usually several M&V choices, which will vary in terms ofmeasurement uncertainty, cost, and technical feasibility. Typically,M&V decisions are made almost solely based on engineering judgmentand experience, with little, if any, quantitative uncertainty analysis(QUA). This paper describes the results of a pilot project initiated bythe Department of Energy s Federal Energy Management Program to explorethe use of Monte-Carlo simulation to assess savings uncertainty andthereby augment the M&V decision-making process in ESPCs. The intentwas to use QUA selectively in combination with heuristic knowledge, inorder to obtain quantitative estimates of the savings uncertainty withoutthe burden of a comprehensive "bottoms-up" QUA. This approach was used toanalyze the savings uncertainty in an ESPC for a large federal agency.The QUA was seamlessly integrated into the ESPC development process andthe incremental effort was relatively small with user-friendly tools thatare commercially available. As the case study illustrates, in some casesthe QUA simply confirms intuitive or qualitative information, while inother cases, it provides insight that suggests revisiting the M&Vplan. The case study also showed that M&V decisions should beinformed by the portfolio risk diversification. By providing quantitativeuncertainty information, QUA can effectively augment the M&Vdecision-making process as well as the overall ESPC financialanalysis.

  1. Genetic algorithm evolved agent-based equity trading using Technical Analysis and the Capital Asset Pricing Model

    E-Print Network [OSTI]

    Aickelin, Uwe

    Genetic algorithm evolved agent-based equity trading using Technical Analysis and the Capital Asset data using technical analysis, the capital asset pricing model and a hybrid model of the two approaches. Results indicated that the technical analysis based approach performed better than the capital asset

  2. Automouse: An improvement to the mouse computerized uncertainty analysis system operational manual

    SciTech Connect (OSTI)

    Klee, A.J.

    1992-08-01T23:59:59.000Z

    Under a mandate of national environmental laws, the agency strives to formulate and implement actions leading to a compatible balance between human activities and the ability of natural systems to support and nurture life. The Risk Reduction Engineering Laboratory is responsible for planning, implementing, and managing research development, and demonstration programs to provide an authoritative, defensible engineering basis in support of the policies, programs, and regulations of the EPA with respect to drinking water, wastewater, pesticides, toxic substances, solid and hazardous wastes, and Superfund-related activities. The publication is one of the products of that research and provides a vital communication link between the researcher and the user community. The manual describes a system, called MOUSE (for Modular Oriented Uncertainty SystEm), for dealing with the computational problems of uncertainty, specifically in models that consist of a set of one or more equations. Since such models are frequently encountered in the fields of environmental science, risk analysis, economics, and engineering, the system has broad application throughout these fields. An important part of the MOUSE system is AutoMOUSE which actually writes the computer programs required for the uncertainty analysis computations. Thus, no prior programming knowledge is needed to learn or use MOUSE and, because of its transportability and compactness, the system can be run on a wide variety of personal computers available to the U.S. Environmental Protection Agency and/or its contractors and grantees.

  3. Uncertainty Analysis for a De-pressurised Loss of Forced Cooling Event of the PBMR Reactor

    SciTech Connect (OSTI)

    Jansen van Rensburg, Pieter A.; Sage, Martin G. [PBMR, 1279 Mike Crawford Avenue, Centurion 0046 (South Africa)

    2006-07-01T23:59:59.000Z

    This paper presents an uncertainty analysis for a De-pressurised Loss of Forced Cooling (DLOFC) event that was performed with the systems CFD (Computational Fluid Dynamics) code Flownex for the PBMR reactor. An uncertainty analysis was performed to determine the variation in maximum fuel, core barrel and reactor pressure vessel (RPV) temperature due to variations in model input parameters. Some of the input parameters that were varied are: thermo-physical properties of helium and the various solid materials, decay heat, neutron and gamma heating, pebble bed pressure loss, pebble bed Nusselt number and pebble bed bypass flows. The Flownex model of the PBMR reactor is a 2-dimensional axisymmetrical model. It is simplified in terms of geometry and some other input values. However, it is believed that the model adequately indicates the effect of changes in certain input parameters on the fuel temperature and other components during a DLOFC event. Firstly, a sensitivity study was performed where input variables were varied individually according to predefined uncertainty ranges and the results were sorted according to the effect on maximum fuel temperature. In the sensitivity study, only seven variables had a significant effect on the maximum fuel temperature (greater that 5 deg. C). The most significant are power distribution profile, decay heat, reflector properties and effective pebble bed conductivity. Secondly, Monte Carlo analyses were performed in which twenty variables were varied simultaneously within predefined uncertainty ranges. For a one-tailed 95% confidence level, the conservatism that should be added to the best estimate calculation of the maximum fuel temperature for a DLOFC was determined as 53 deg. C. This value will probably increase after some model refinements in the future. Flownex was found to be a valuable tool for uncertainly analyses, facilitating both sensitivity studies and Monte Carlo analyses. (authors)

  4. The impact of uncertainty and risk measures

    E-Print Network [OSTI]

    Jo, Soojin; Jo, Soojin

    2012-01-01T23:59:59.000Z

    peak, and finds that this nonlinear transformation of the oiland oil price growth rates. As seen in the above illustration, uncertainty is at its peak

  5. 2007 Wholesale Power Rate Case Initial Proposal : Market Price Forecast Study.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    2005-11-01T23:59:59.000Z

    This chapter presents BPA's market price forecasts, which are based on AURORA modeling. AURORA calculates the variable cost of the marginal resource in a competitively priced energy market. In competitive market pricing, the marginal cost of production is equivalent to the market-clearing price. Market-clearing prices are important factors for informing BPA's rates. AURORA is used as the primary tool for (a) calculation of the demand rate, (b) shaping the PF rate, (c) estimating the forward price for the IOU REP settlement benefits calculation for fiscal years 2008 and 2009, (d) estimating the uncertainty surrounding DSI payments, (e) informing the secondary revenue forecast and (f) providing a price input used for the risk analysis.

  6. Single-Product Pricing via Robust Optimization

    E-Print Network [OSTI]

    2006-01-30T23:59:59.000Z

    manufacturing to fashion retail. Applying probabilistic ... In Section 2, we develop the robust pricing model in the presence of additive uncertainty. We analyze.

  7. Uncertainty and sensitivity analysis of food pathway results with the MACCS Reactor Accident Consequence Model

    SciTech Connect (OSTI)

    Helton, J.C. [Arizona State Univ., Tempe, AZ (United States); Johnson, J.D.; Rollstin, J.A. [GRAM, Inc., Albuquerque, NM (United States); Shiver, A.W.; Sprung, J.L. [Sandia National Labs., Albuquerque, NM (United States)

    1995-01-01T23:59:59.000Z

    Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis are used in an investigation with the MACCS model of the food pathways associated with a severe accident at a nuclear power station. The primary purpose of this study is to provide guidance on the variables to be considered in future review work to reduce the uncertainty in the important variables used in the calculation of reactor accident consequences. The effects of 87 imprecisely-known input variables on the following reactor accident consequences are studied: crop growing season dose, crop long-term dose, milk growing season dose, total food pathways dose, total ingestion pathways dose, total long-term pathways dose, area dependent cost, crop disposal cost, milk disposal cost, condemnation area, crop disposal area and milk disposal area. When the predicted variables are considered collectively, the following input variables were found to be the dominant contributors to uncertainty: fraction of cesium deposition on grain fields that is retained on plant surfaces and transferred directly to grain, maximum allowable ground concentrations of Cs-137 and Sr-90 for production of crops, ground concentrations of Cs-134, Cs-137 and I-131 at which the disposal of milk will be initiated due to accidents that occur during the growing season, ground concentrations of Cs-134, I-131 and Sr-90 at which the disposal of crops will be initiated due to accidents that occur during the growing season, rate of depletion of Cs-137 and Sr-90 from the root zone, transfer of Sr-90 from soil to legumes, transfer of Cs-137 from soil to pasture, transfer of cesium from animal feed to meat, and the transfer of cesium, iodine and strontium from animal feed to milk.

  8. Uncertainty and sensitivity analysis of chronic exposure results with the MACCS reactor accident consequence model

    SciTech Connect (OSTI)

    Helton, J.C. [Arizona State Univ., Tempe, AZ (United States); Johnson, J.D.; Rollstin, J.A. [Gram, Inc., Albuquerque, NM (United States); Shiver, A.W.; Sprung, J.L. [Sandia National Labs., Albuquerque, NM (United States)

    1995-01-01T23:59:59.000Z

    Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis are used in an investigation with the MACCS model of the chronic exposure pathways associated with a severe accident at a nuclear power station. The primary purpose of this study is to provide guidance on the variables to be considered in future review work to reduce the uncertainty in the important variables used in the calculation of reactor accident consequences. The effects of 75 imprecisely known input variables on the following reactor accident consequences are studied: crop growing season dose, crop long-term dose, water ingestion dose, milk growing season dose, long-term groundshine dose, long-term inhalation dose, total food pathways dose, total ingestion pathways dose, total long-term pathways dose, total latent cancer fatalities, area-dependent cost, crop disposal cost, milk disposal cost, population-dependent cost, total economic cost, condemnation area, condemnation population, crop disposal area and milk disposal area. When the predicted variables are considered collectively, the following input variables were found to be the dominant contributors to uncertainty: dry deposition velocity, transfer of cesium from animal feed to milk, transfer of cesium from animal feed to meat, ground concentration of Cs-134 at which the disposal of milk products will be initiated, transfer of Sr-90 from soil to legumes, maximum allowable ground concentration of Sr-90 for production of crops, fraction of cesium entering surface water that is consumed in drinking water, groundshine shielding factor, scale factor defining resuspension, dose reduction associated with decontamination, and ground concentration of 1-131 at which disposal of crops will be initiated due to accidents that occur during the growing season.

  9. Energy prices and energy intensity in China : a structural decomposition analysis and econometrics study

    E-Print Network [OSTI]

    Shi, Xiaoyu

    2006-01-01T23:59:59.000Z

    Since the start of its economic reforms in 1978, China's energy prices relative to other prices have increased. At the same time, its energy intensity, i.e., energy consumption per unit of Gross Domestic Product (GDP), has ...

  10. Price discrimination and limits to arbitrage: An analysis of global LNG markets

    E-Print Network [OSTI]

    Ritz, Robert A.

    2014-07-31T23:59:59.000Z

    Gas prices around the world vary widely despite being connected by international trade of liquefied natural gas (LNG). Some industry observers argue that major exporters have acted irrationally by not arbitraging prices. This is also difficult...

  11. Energy prices and energy intensity in China : a structural decomposition analysis and econometric study

    E-Print Network [OSTI]

    Shi, Xiaoyu, M.C.P. Massachusetts Institute of Technology

    2005-01-01T23:59:59.000Z

    Since the start of its economic reforms in 1978, China's energy prices relative to other prices have increased. At the same time, its energy intensity, i.e., physical energy consumption per unit of Gross Domestic Product ...

  12. Luxury condos : an analysis of sales price and hotel amenities in Manhattan

    E-Print Network [OSTI]

    Dolan, Amelia Jane

    2011-01-01T23:59:59.000Z

    The purpose of this research project is to examine the market pricing behavior of condos with hotel amenities in the Manhattan condo market. To do this, data was compiled from multiple sources to track variations in price ...

  13. Uncertainty, investment, and industry evolution

    E-Print Network [OSTI]

    Caballero, Ricardo J.

    1992-01-01T23:59:59.000Z

    We study the effects of aggregate and idiosyncratic uncertainty on the entry of firms, total investment, and prices in a competitive industry with irreversible investment. We first use standard dynamic programming methods ...

  14. Development code for sensitivity and uncertainty analysis of input on the MCNPX for neutronic calculation in PWR core

    SciTech Connect (OSTI)

    Hartini, Entin, E-mail: entin@batan.go.id; Andiwijayakusuma, Dinan, E-mail: entin@batan.go.id [Center for Development of Nuclear Informatics - National Nuclear Energy Agency, PUSPIPTEK, Serpong, Tangerang, Banten (Indonesia)

    2014-09-30T23:59:59.000Z

    This research was carried out on the development of code for uncertainty analysis is based on a statistical approach for assessing the uncertainty input parameters. In the butn-up calculation of fuel, uncertainty analysis performed for input parameters fuel density, coolant density and fuel temperature. This calculation is performed during irradiation using Monte Carlo N-Particle Transport. The Uncertainty method based on the probabilities density function. Development code is made in python script to do coupling with MCNPX for criticality and burn-up calculations. Simulation is done by modeling the geometry of PWR terrace, with MCNPX on the power 54 MW with fuel type UO2 pellets. The calculation is done by using the data library continuous energy cross-sections ENDF / B-VI. MCNPX requires nuclear data in ACE format. Development of interfaces for obtaining nuclear data in the form of ACE format of ENDF through special process NJOY calculation to temperature changes in a certain range.

  15. Identifying the Oil Price-Macroeconomy Relationship: An Empirical Mode Decomposition Analysis of U.S. Data

    SciTech Connect (OSTI)

    Oladosu, Gbadebo A [ORNL

    2009-01-01T23:59:59.000Z

    This work applies the empirical mode decomposition (EMD) method to data on real quarterly oil price (West Texas Intermediate - WTI) and U.S. gross domestic product (GDP). This relatively new method is adaptive and capable of handling non-linear and non-stationary data. Correlation analysis of the decomposition results was performed and examined for insights into the oil-macroeconomy relationship. Several components of this relationship were identified. However, the principal one is that the medium-run cyclical component of the oil price exerts a negative and exogenous influence on the main cyclical component of the GDP. This can be interpreted as the supply-driven or supply-shock component of the oil price-GDP relationship. In addition, weak correlations suggesting a lagging demand-driven, an expectations-driven, and a long-run supply-driven component of the relationship were also identified. Comparisons of these findings with significant oil supply disruption and recession dates were supportive. The study identified a number of lessons applicable to recent oil market events, including the eventuality of persistent economic and price declines following a long oil price run-up. In addition, it was found that oil-market related exogenous events are associated with short- to medium-run price implications regardless of whether they lead to actual supply disruptions.

  16. An Analysis of the Effects of Photovoltaic Energy Systems on Residential Selling Prices in California.

    SciTech Connect (OSTI)

    Cappers, Peter; Wiser, Ryan; Thayer, Mark; Hoen, Ben

    2011-04-12T23:59:59.000Z

    An increasing number of homes with existing photovoltaic (PV) energy systems have sold in the U.S., yet relatively little research exists that estimates the marginal impacts of those PV systems on the sales price. A clearer understanding of these effects might influence the decisions of homeowners, home buyers and PV home builders. This research analyzes a large dataset of California homes that sold from 2000 through mid-2009 with PV installed. Across a large number of hedonic and repeat sales model specifications and robustness tests, the analysis finds strong evidence that homes with PV systems sold for a premium over comparable homes without. The effects range, on average, from approximately $3.9 to $6.4 per installed watt (DC), with most models coalescing near $5.5/watt, which corresponds to a premium of approximately $17,000 for a 3,100 watt system. The research also shows that, as PV systems age, the premium enjoyed at the time of home sale decreases. Additionally, existing homes with PV systems are found to have commanded a larger sales price premium than new homes with similarly sized PV systems. Reasons for this discrepancy are suggested, yet further research is warranted in this area as well as a number of other areas that are highlighted.

  17. Grid and basis adaptive polynomial chaos techniques for sensitivity and uncertainty analysis

    SciTech Connect (OSTI)

    Perkó, Zoltán, E-mail: Z.Perko@tudelft.nl; Gilli, Luca, E-mail: Gilli@nrg.eu; Lathouwers, Danny, E-mail: D.Lathouwers@tudelft.nl; Kloosterman, Jan Leen, E-mail: J.L.Kloosterman@tudelft.nl

    2014-03-01T23:59:59.000Z

    The demand for accurate and computationally affordable sensitivity and uncertainty techniques is constantly on the rise and has become especially pressing in the nuclear field with the shift to Best Estimate Plus Uncertainty methodologies in the licensing of nuclear installations. Besides traditional, already well developed methods – such as first order perturbation theory or Monte Carlo sampling – Polynomial Chaos Expansion (PCE) has been given a growing emphasis in recent years due to its simple application and good performance. This paper presents new developments of the research done at TU Delft on such Polynomial Chaos (PC) techniques. Our work is focused on the Non-Intrusive Spectral Projection (NISP) approach and adaptive methods for building the PCE of responses of interest. Recent efforts resulted in a new adaptive sparse grid algorithm designed for estimating the PC coefficients. The algorithm is based on Gerstner's procedure for calculating multi-dimensional integrals but proves to be computationally significantly cheaper, while at the same it retains a similar accuracy as the original method. More importantly the issue of basis adaptivity has been investigated and two techniques have been implemented for constructing the sparse PCE of quantities of interest. Not using the traditional full PC basis set leads to further reduction in computational time since the high order grids necessary for accurately estimating the near zero expansion coefficients of polynomial basis vectors not needed in the PCE can be excluded from the calculation. Moreover the sparse PC representation of the response is easier to handle when used for sensitivity analysis or uncertainty propagation due to the smaller number of basis vectors. The developed grid and basis adaptive methods have been implemented in Matlab as the Fully Adaptive Non-Intrusive Spectral Projection (FANISP) algorithm and were tested on four analytical problems. These show consistent good performance both in terms of the accuracy of the resulting PC representation of quantities and the computational costs associated with constructing the sparse PCE. Basis adaptivity also seems to make the employment of PC techniques possible for problems with a higher number of input parameters (15–20), alleviating a well known limitation of the traditional approach. The prospect of larger scale applicability and the simplicity of implementation makes such adaptive PC algorithms particularly appealing for the sensitivity and uncertainty analysis of complex systems and legacy codes.

  18. BWR transient analysis using neutronic / thermal hydraulic coupled codes including uncertainty quantification

    SciTech Connect (OSTI)

    Hartmann, C.; Sanchez, V. [Karlsruhe Inst. of Technology (KIT), Inst. for Neutron Physics and Reactor Technology INR, Hermann-vom-Helmholtz-Platz-1, D-76344 Eggenstein-Leopoldshafen (Germany); Tietsch, W. [Westinghouse Electric Germany GmbH, Mannheim (Germany); Stieglitz, R. [Karlsruhe Inst. of Technology (KIT), Inst. for Neutron Physics and Reactor Technology INR, Hermann-vom-Helmholtz-Platz-1, D-76344 Eggenstein-Leopoldshafen (Germany)

    2012-07-01T23:59:59.000Z

    The KIT is involved in the development and qualification of best estimate methodologies for BWR transient analysis in cooperation with industrial partners. The goal is to establish the most advanced thermal hydraulic system codes coupled with 3D reactor dynamic codes to be able to perform a more realistic evaluation of the BWR behavior under accidental conditions. For this purpose a computational chain based on the lattice code (SCALE6/GenPMAXS), the coupled neutronic/thermal hydraulic code (TRACE/PARCS) as well as a Monte Carlo based uncertainty and sensitivity package (SUSA) has been established and applied to different kind of transients of a Boiling Water Reactor (BWR). This paper will describe the multidimensional models of the plant elaborated for TRACE and PARCS to perform the investigations mentioned before. For the uncertainty quantification of the coupled code TRACE/PARCS and specifically to take into account the influence of the kinetics parameters in such studies, the PARCS code has been extended to facilitate the change of model parameters in such a way that the SUSA package can be used in connection with TRACE/PARCS for the U and S studies. This approach will be presented in detail. The results obtained for a rod drop transient with TRACE/PARCS using the SUSA-methodology showed clearly the importance of some kinetic parameters on the transient progression demonstrating that the coupling of a best-estimate coupled codes with uncertainty and sensitivity tools is very promising and of great importance for the safety assessment of nuclear reactors. (authors)

  19. The best-estimate analysis of LB LOCA with uncertainty evaluation

    SciTech Connect (OSTI)

    Stritar, A.; Mavko, B.; Prosek, A.

    1992-01-01T23:59:59.000Z

    The large-break loss-of-coolant accident (LB LOCA) has been analyzed with a conservative computer code and methodology. One of the conclusions of that analysis was the need for the uncertainty analysis of the final result with the number of input parameters as independent variables. In this paper, the analysis of the LB LOCA with the best-estimate code, RELAP5/MOD2, is described. The analysis has been performed for the Krsko nuclear power plant in Slovenia. It is a Westinghouse two-loop 664-MW (electric) pressurized water reactor. The cold-leg break between the pump and the reactor vessel has been selected for the analysis. The input model that was used with the RELAP5/MOD2 code was the modified standard input for that plant, which had been used for transient analyses for several years. The changes to the model were introduced mainly to achieve better efficiency of the extensive computational task. The number of heat slabs on the secondary side of the steam generators has been reduced to gain computing speed. The number of axial heat slabs in the core has been increased to achieve a better power profile. There were two hot rods modeled in the average hydraulic core. With two hot rods, the number of necessary calculations has been halved. In each hot rod, a model of another input parameter has been applied.

  20. Uncertainty and Sensitivity Analysis Results Obtained in the 1996 Performance Assessment for the Waste Isolation Pilot Plant

    SciTech Connect (OSTI)

    Bean, J.E.; Berglund, J.W.; Davis, F.J.; Economy, K.; Garner, J.W.; Helton, J.C.; Johnson, J.D.; MacKinnon, R.J.; Miller, J.; O'Brien, D.G.; Ramsey, J.L.; Schreiber, J.D.; Shinta, A.; Smith, L.N.; Stockman, C.; Stoelzel, D.M.; Vaughn, P.

    1998-09-01T23:59:59.000Z

    The Waste Isolation Pilot Plant (WPP) is located in southeastern New Mexico and is being developed by the U.S. Department of Energy (DOE) for the geologic (deep underground) disposal of transuranic (TRU) waste. A detailed performance assessment (PA) for the WIPP was carried out in 1996 and supports an application by the DOE to the U.S. Environmental Protection Agency (EPA) for the certification of the WIPP for the disposal of TRU waste. The 1996 WIPP PA uses a computational structure that maintains a separation between stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty, with stochastic uncertainty arising from the many possible disruptions that could occur over the 10,000 yr regulatory period that applies to the WIPP and subjective uncertainty arising from the imprecision with which many of the quantities required in the PA are known. Important parts of this structure are (1) the use of Latin hypercube sampling to incorporate the effects of subjective uncertainty, (2) the use of Monte Carlo (i.e., random) sampling to incorporate the effects of stochastic uncertainty, and (3) the efficient use of the necessarily limited number of mechanistic calculations that can be performed to support the analysis. The use of Latin hypercube sampling generates a mapping from imprecisely known analysis inputs to analysis outcomes of interest that provides both a display of the uncertainty in analysis outcomes (i.e., uncertainty analysis) and a basis for investigating the effects of individual inputs on these outcomes (i.e., sensitivity analysis). The sensitivity analysis procedures used in the PA include examination of scatterplots, stepwise regression analysis, and partial correlation analysis. Uncertainty and sensitivity analysis results obtained as part of the 1996 WIPP PA are presented and discussed. Specific topics considered include two phase flow in the vicinity of the repository, radionuclide release from the repository, fluid flow and radionuclide transport in formations overlying the repository, and complementary cumulative distribution functions used in comparisons with regulatory standards (i.e., 40 CFR 191, Subpart B).

  1. TRITIUM UNCERTAINTY ANALYSIS FOR SURFACE WATER SAMPLES AT THE SAVANNAH RIVER SITE

    SciTech Connect (OSTI)

    Atkinson, R.

    2012-07-31T23:59:59.000Z

    Radiochemical analyses of surface water samples, in the framework of Environmental Monitoring, have associated uncertainties for the radioisotopic results reported. These uncertainty analyses pertain to the tritium results from surface water samples collected at five locations on the Savannah River near the U.S. Department of Energy's Savannah River Site (SRS). Uncertainties can result from the field-sampling routine, can be incurred during transport due to the physical properties of the sample, from equipment limitations, and from the measurement instrumentation used. The uncertainty reported by the SRS in their Annual Site Environmental Report currently considers only the counting uncertainty in the measurements, which is the standard reporting protocol for radioanalytical chemistry results. The focus of this work is to provide an overview of all uncertainty components associated with SRS tritium measurements, estimate the total uncertainty according to ISO 17025, and to propose additional experiments to verify some of the estimated uncertainties. The main uncertainty components discovered and investigated in this paper are tritium absorption or desorption in the sample container, HTO/H{sub 2}O isotopic effect during distillation, pipette volume, and tritium standard uncertainty. The goal is to quantify these uncertainties and to establish a combined uncertainty in order to increase the scientific depth of the SRS Annual Site Environmental Report.

  2. An Analysis of Price Volatility in Different Spot Markets for Electricity in the U.S.A.

    E-Print Network [OSTI]

    An Analysis of Price Volatility in Different Spot Markets for Electricity in the U.S.A. by Tim for electricity in the USA vary in fundamental ways. In particular, markets in the East, such as New England, New in the new auction markets for electricity can be described by a stochastic regime-switching model

  3. Preliminary Investigations on Uncertainty Analysis of Wind-Wave Predictions in Lake Michigan

    E-Print Network [OSTI]

    Nekouee, Navid

    2015-01-01T23:59:59.000Z

    With all the improvement in wave and hydrodynamics numerical models, the question rises in our mind that how the accuracy of the forcing functions and their input can affect the results. In this paper, a commonly used numerical third generation wave model, SWAN is applied to predict waves in Lake Michigan. Wind data were analyzed to determine wind variation frequency over Lake Michigan. Wave predictions uncertainty due to wind local effects were compared during a period where wind had a fairly constant speed and direction over the northern and southern basins. The study shows that despite model calibration in Lake Michigan area, the model deficiency arises from ignoring wind effects in small scales. Wave prediction also emphasizes that small scale turbulence in meteorological forces can increase error in predictions up to 35%. Wave frequency and coherence analysis showed that both models are able to reveal the time scale of the wave variation with same accuracy. Insufficient number of meteorological stations ...

  4. Uncertainty Analysis on the Design of Thermal Conductivity Measurement by a Guarded Cut-Bar Technique

    SciTech Connect (OSTI)

    Jeff Phillips; Changhu Xing; Colby Jensen; Heng Ban1

    2011-07-01T23:59:59.000Z

    A technique adapted from the guarded-comparative-longitudinal heat flow method was selected for the measurement of the thermal conductivity of a nuclear fuel compact over a temperature range characteristic of its usage. This technique fulfills the requirement for non-destructive measurement of the composite compact. Although numerous measurement systems have been created based on the guarded comparative method, comprehensive systematic (bias) and measurement (precision) uncertainty associated with this technique have not been fully analyzed. In addition to the geometric effect in the bias error, which has been analyzed previously, this paper studies the working condition which is another potential error source. Using finite element analysis, this study showed the effect of these two types of error sources in the thermal conductivity measurement process and the limitations in the design selection of various parameters by considering their effect on the precision error. The results and conclusions provide valuable reference for designing and operating an experimental measurement system using this technique.

  5. Why Do Motor Gasoline Prices Vary Regionally? California Case Study

    Reports and Publications (EIA)

    1998-01-01T23:59:59.000Z

    Analysis of the difference between the retail gasoline prices in California and the average U.S. retail prices.

  6. DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis.

    SciTech Connect (OSTI)

    Eldred, Michael Scott; Vigil, Dena M.; Dalbey, Keith R.; Bohnhoff, William J.; Adams, Brian M.; Swiler, Laura Painton; Lefantzi, Sophia (Sandia National Laboratories, Livermore, CA); Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Eddy, John P.

    2011-12-01T23:59:59.000Z

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the DAKOTA software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of DAKOTA-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of DAKOTA's iterative analysis capabilities.

  7. Reliable algorithms for power system analysis in the presence of data uncertainties

    SciTech Connect (OSTI)

    Dimitrovski, Aleksandar D [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK); Vaccaro, Alfredo [University of Sannio

    2011-01-01T23:59:59.000Z

    A robust and reliable power flow analysis represents an essential requirement for many power systems applications as far as network optimization, voltage control, state estimation, and service restoration are concerned. The most common power flow approach, referred to here as a deterministic power flow (PLF), requires precise or 'crisp' values chosen by the analyst for each input variable. The solution provides precise network voltages and flows through each line. The specified values rest upon assumptions about the operating condition derived from historical measurements or predictions about future conditions and thus, cannot be considered accurate. Even in the case where the inputs are based on measurements, inaccuracies arise from time-skew problems, three-phase unbalance, static modeling approximations of dynamic components (e.g., transformer tap changers), variations in line parameters, and so on. The advent of deregulation and competitive power markets will only exacerbate this problem as well-known generation patterns change, loading becomes less predictable and the transmission paths grow more diverse. Conventional methodologies proposed in literature address tolerance analysis of power flow solution by means of detailed probabilistic methods, accounting for the variability and stochastic nature of the input data, and sampling based approaches. In particular uncertainty propagation using sampling based methods, such as the Monte Carlo, requires several model runs that sample various combinations of input values. Since the number of model runs can sometimes be very large, the required computer resources can sometimes be prohibitively expensive resulting in substantial computational demands. As far as probabilistic methods are concerned, they represent a useful tool, especially for planning studies, but, as evidenced by the many discussions reported in literature, they could reveal some shortcomings principally arising from: (1) the non-normal distribution and the statistical dependence of the input data; and (2) the difficulty arising in accurately identifying probability distributions for some input data, such as the power generated by wind or photovoltaic generators. All these could result in time consuming computations with several limitations in practical applications especially in power flow analysis of complex power networks. In order to try and overcome some of these limitations, obtaining thereby comprehensive power flow solution tolerance analysis at adequate computational costs, self validated computation could play a crucial role. Armed with such a vision, this chapter will analyze two advanced techniques for power flow analysis in the presence of data uncertainty namely the boundary power flow and the affine arithmetic power flow.

  8. Japan's Solar Photovoltaic (PV) Market: An Analysis of Residential System Prices (Presentation)

    SciTech Connect (OSTI)

    James, T.

    2014-03-01T23:59:59.000Z

    This presentation summarizes market and policy factors influencing residential solar photovoltaic system prices in Japan, and compares these factors to related developments in the United States.

  9. An Analysis of Residential PV System Price Differences Between the United States and Germany

    E-Print Network [OSTI]

    Seel, Joachim

    2014-01-01T23:59:59.000Z

    inverter costs. Figure 4: Median installed price of non-appraised PV systemsPV system prices could reduce LCoE assumptions: 25-year life span, nominal discount rate of 4.5%, O&M $100/year, one inverter

  10. Uncertainty and sensitivity analysis methods for improving design robustness and reliability

    E-Print Network [OSTI]

    He, Qinxian, Ph. D. Massachusetts Institute of Technology

    2014-01-01T23:59:59.000Z

    Engineering systems of the modern day are increasingly complex, often involving numerous components, countless mathematical models, and large, globally-distributed design teams. These features all contribute uncertainty ...

  11. Uncertainty Analysis of Certified Photovoltaic Measurements at the National Renewable Energy Laboratory

    SciTech Connect (OSTI)

    Emery, K.

    2009-08-01T23:59:59.000Z

    Discusses NREL Photovoltaic Cell and Module Performance Characterization Group's procedures to achieve lowest practical uncertainty in measuring PV performance with respect to reference conditions.

  12. LED Price Tracking Form

    Broader source: Energy.gov [DOE]

    DOE intends to update the SSL Pricing and Efficacy Trend Analysis for Utility Program Planning report on an annual basis, but doing so requires that we have sufficient product and purchase data including acquisition date, purchase price, product category, and rated initial lumens. Those interested in helping collect this data are asked to use the LED Price Tracking FormMicrosoft Excel and follow the instructions for submitting data.

  13. PEBBED Uncertainty and Sensitivity Analysis of the CRP-5 PBMR DLOFC Transient Benchmark with the SUSA Code

    SciTech Connect (OSTI)

    Gerhard Strydom

    2011-01-01T23:59:59.000Z

    The need for a defendable and systematic uncertainty and sensitivity approach that conforms to the Code Scaling, Applicability, and Uncertainty (CSAU) process, and that could be used for a wide variety of software codes, was defined in 2008. The GRS (Gesellschaft für Anlagen und Reaktorsicherheit) company of Germany has developed one type of CSAU approach that is particularly well suited for legacy coupled core analysis codes, and a trial version of their commercial software product SUSA (Software for Uncertainty and Sensitivity Analyses) was acquired on May 12, 2010. This report summarized the results of the initial investigations performed with SUSA, utilizing a typical High Temperature Reactor benchmark (the IAEA CRP-5 PBMR 400MW Exercise 2) and the PEBBED-THERMIX suite of codes. The following steps were performed as part of the uncertainty and sensitivity analysis: 1. Eight PEBBED-THERMIX model input parameters were selected for inclusion in the uncertainty study: the total reactor power, inlet gas temperature, decay heat, and the specific heat capability and thermal conductivity of the fuel, pebble bed and reflector graphite. 2. The input parameters variations and probability density functions were specified, and a total of 800 PEBBED-THERMIX model calculations were performed, divided into 4 sets of 100 and 2 sets of 200 Steady State and Depressurized Loss of Forced Cooling (DLOFC) transient calculations each. 3. The steady state and DLOFC maximum fuel temperature, as well as the daily pebble fuel load rate data, were supplied to SUSA as model output parameters of interest. The 6 data sets were statistically analyzed to determine the 5% and 95% percentile values for each of the 3 output parameters with a 95% confidence level, and typical statistical indictors were also generated (e.g. Kendall, Pearson and Spearman coefficients). 4. A SUSA sensitivity study was performed to obtain correlation data between the input and output parameters, and to identify the primary contributors to the output data uncertainties. It was found that the uncertainties in the decay heat, pebble bed and reflector thermal conductivities were responsible for the bulk of the propagated uncertainty in the DLOFC maximum fuel temperature. It was also determined that the two standard deviation (2s) uncertainty on the maximum fuel temperature was between ±58oC (3.6%) and ±76oC (4.7%) on a mean value of 1604 oC. These values mostly depended on the selection of the distributions types, and not on the number of model calculations above the required Wilks criteria (a (95%,95%) statement would usually require 93 model runs).

  14. Using Uncertainty Analysis to Guide the Development of Accelerated Stress Tests (Presentation)

    SciTech Connect (OSTI)

    Kempe, M.

    2014-03-01T23:59:59.000Z

    Extrapolation of accelerated testing to the long-term results expected in the field has uncertainty associated with the acceleration factors and the range of possible stresses in the field. When multiple stresses (such as temperature and humidity) can be used to increase the acceleration, the uncertainty may be reduced according to which stress factors are used to accelerate the degradation.

  15. Uncertainty analysis of steady state incident heat flux measurements in hydrocarbon fuel fires.

    SciTech Connect (OSTI)

    Nakos, James Thomas

    2005-12-01T23:59:59.000Z

    The objective of this report is to develop uncertainty estimates for three heat flux measurement techniques used for the measurement of incident heat flux in a combined radiative and convective environment. This is related to the measurement of heat flux to objects placed inside hydrocarbon fuel (diesel, JP-8 jet fuel) fires, which is very difficult to make accurately (e.g., less than 10%). Three methods will be discussed: a Schmidt-Boelter heat flux gage; a calorimeter and inverse heat conduction method; and a thin plate and energy balance method. Steady state uncertainties were estimated for two types of fires (i.e., calm wind and high winds) at three times (early in the fire, late in the fire, and at an intermediate time). Results showed a large uncertainty for all three methods. Typical uncertainties for a Schmidt-Boelter gage ranged from {+-}23% for high wind fires to {+-}39% for low wind fires. For the calorimeter/inverse method the uncertainties were {+-}25% to {+-}40%. The thin plate/energy balance method the uncertainties ranged from {+-}21% to {+-}42%. The 23-39% uncertainties for the Schmidt-Boelter gage are much larger than the quoted uncertainty for a radiative only environment (i.e ., {+-}3%). This large difference is due to the convective contribution and because the gage sensitivities to radiative and convective environments are not equal. All these values are larger than desired, which suggests the need for improvements in heat flux measurements in fires.

  16. Quasiparticle random phase approximation uncertainties and their correlations in the analysis of neutrinoless double beta decay

    E-Print Network [OSTI]

    Amand Faessler; G. L. Fogli; E. Lisi; V. Rodin; A. M. Rotunno; F. Simkovic

    2009-03-06T23:59:59.000Z

    The variances and covariances associated to the nuclear matrix elements (NME) of neutrinoless double beta decay are estimated within the quasiparticle random phase approximation (QRPA). It is shown that correlated NME uncertainties play an important role in the comparison of neutrinoless double beta decay rates for different nuclei, and that they are degenerate with the uncertainty in the reconstructed Majorana neutrino mass.

  17. Assessment of uncertainty in cloud radiative effects and heating rates through retrieval algorithm differences: Analysis using

    E-Print Network [OSTI]

    Protat, Alain

    Assessment of uncertainty in cloud radiative effects and heating rates through retrieval algorithm. The effect of uncertainty in retrieved quantities on the cloud radiative effect and radiative heating rates translates into sometimes large differences in cloud shortwave radiative effect (CRE) though the majority

  18. 2009 Technical Risk and Uncertainty Analysis of the U.S. Department of Energy's Solar Energy Technologies Program Concentrating Solar Power and Photovoltaics R&D

    SciTech Connect (OSTI)

    McVeigh, J.; Lausten, M.; Eugeni, E.; Soni, A.

    2010-11-01T23:59:59.000Z

    The U.S. Department of Energy (DOE) Solar Energy Technologies Program (SETP) conducted a 2009 Technical Risk and Uncertainty Analysis to better assess its cost goals for concentrating solar power (CSP) and photovoltaic (PV) systems, and to potentially rebalance its R&D portfolio. This report details the methodology, schedule, and results of this technical risk and uncertainty analysis.

  19. An Example Uncertainty and Sensitivity Analysis for Reactive Transport at the Horonobe Site for Performance Assessment Calculations.

    SciTech Connect (OSTI)

    James, Scott; Cohan, Alexander [Sandia National Laboratories, Albuquerque, NM] [Sandia National Laboratories, Albuquerque, NM

    2005-08-01T23:59:59.000Z

    Given pre-existing Groundwater Modeling System (GMS) models of the Horonobe Underground Research Laboratory (URL) at both the regional and site scales, this work performs an example uncertainty analysis for performance assessment (PA) applications. After a general overview of uncertainty and sensitivity analysis techniques, the existing GMS site-scale model is converted to a PA model of the steady-state conditions expected after URL closure. This is done to examine the impact of uncertainty in site-specific data in conjunction with conceptual model uncertainty regarding the location of the Oomagari Fault. A heterogeneous stochastic model is developed and corresponding flow fields and particle tracks are calculated. In addition, a quantitative analysis of the ratio of dispersive to advective forces, the F-ratio, is performed for stochastic realizations of each conceptual model. Finally, a one-dimensional transport abstraction is modeled based on the particle path lengths and the materials through which each particle passes to yield breakthrough curves at the model boundary. All analyses indicate that accurate characterization of the Oomagari Fault with respect to both location and hydraulic conductivity is critical to PA calculations. This work defines and outlines typical uncertainty and sensitivity analysis procedures and demonstrates them with example PA calculations relevant to the Horonobe URL. Acknowledgement: This project was funded by Japan Nuclear Cycle Development Institute (JNC). This work was conducted jointly between Sandia National Laboratories (SNL) and JNC under a joint JNC/U.S. Department of Energy (DOE) work agreement. Performance assessment calculations were conducted and analyzed at SNL based on a preliminary model by Kashima, Quintessa, and JNC and include significant input from JNC to make sure the results are relevant for the Japanese nuclear waste program.

  20. Introduction to Macroeconomic Dynamics Special Issue on Oil Price Shocks

    E-Print Network [OSTI]

    Garousi, Vahid

    shocks, Oil price uncertainty, Nonlinearity in the Oil Price- Output Relationship. 2 #12;Table Production: Is the Relationship Linear?" John Elder and Apostolos Serletis, "Volatility in Oil Prices-Term Oil Price Forecasts: A New Perspective on Oil and the Macroeconomy." 3 #12;1 Overview The relationship

  1. Empirical Analysis of the Spot Market Implications of Price-Responsive Demand

    E-Print Network [OSTI]

    Siddiqui, Afzal S.; Bartholomew, Emily S.; Marnay, Chris

    2008-01-01T23:59:59.000Z

    and Demand Response in Electricity Markets,” CSEM Working Paper CSEM-WP-105, University of California Energy Institute, Berkeley, CA, USA.USA. Siddiqui, AS (2004), “Price-Elastic Demand in Deregulated Electricity

  2. Multi-criteria analysis : an alternative approach for the evaluation of road pricing strategies

    E-Print Network [OSTI]

    Ensor, Jeffrey D. (Jeffrey Douglas)

    2005-01-01T23:59:59.000Z

    Interest in road pricing among political leaders, transportation analysts, academics, and government agencies has increased in recent years. There are myriad reasons for this newfound consideration, but the deployment of ...

  3. Empirical Analysis of the Spot Market Implications ofPrice-Responsive Demand

    SciTech Connect (OSTI)

    Siddiqui, Afzal S.; Bartholomew, Emily S.; Marnay, Chris

    2005-08-01T23:59:59.000Z

    Regardless of the form of restructuring, deregulatedelectricity industries share one common feature: the absence of anysignificant, rapid demand-side response to the wholesale (or, spotmarket) price. For a variety of reasons, most electricity consumers stillpay an average cost based regulated retail tariff held over from the eraof vertical integration, even as the retailers themselves are oftenforced to purchase electricity at volatile wholesale prices set in openmarkets. This results in considerable price risk for retailers, who aresometimes additionally forbidden by regulators from signing hedgingcontracts. More importantly, because end-users do not perceive real-time(or even hourly or daily) fluctuations in the wholesale price ofelectricity, they have no incentive to adjust their consumptionaccordingly. Consequently, demand for electricity is highly inelastic,which together with the non storability of electricity that requiresmarket clearing over very short time steps spawn many other problemsassociated with electricity markets, such as exercise of market power andprice volatility. Indeed, electricity generation resources can bestretched to the point where system adequacy is threatened. Economictheory suggests that even modest price responsiveness can relieve thestress on generation resources and decrease spot prices. To quantify thiseffect, actual generator bid data from the New York control area is usedto construct supply stacks and intersect them with demand curves ofvarious slopes to approximate the effect of different levels of demandresponse. The potential impact of real-time pricing (RTP) on theequilibrium spot price and quantity is then estimated. These resultsindicate the immediate benefits that could be derived from a moreprice-responsive demand providing policymakers with a measure of howprices can be potentially reduced and consumption maintained within thecapability of generation assets.

  4. Recommendations for probabilistic seismic hazard analysis: Guidance on uncertainty and use of experts

    SciTech Connect (OSTI)

    Budnitz, R.J.; Apostolakis, G.; Boore, D.M. [and others

    1997-04-01T23:59:59.000Z

    Probabilistic Seismic Hazard Analysis (PSHA) is a methodology that estimates the likelihood that various levels of earthquake-caused ground motion will be exceeded at a given location in a given future time period. Due to large uncertainties in all the geosciences data and in their modeling, multiple model interpretations are often possible. This leads to disagreement among experts, which in the past has led to disagreement on the selection of ground motion for design at a given site. In order to review the present state-of-the-art and improve on the overall stability of the PSHA process, the U.S. Nuclear Regulatory Commission (NRC), the U.S. Department of Energy (DOE), and the Electric Power Research Institute (EPRI) co-sponsored a project to provide methodological guidance on how to perform a PSHA. The project has been carried out by a seven-member Senior Seismic Hazard Analysis Committee (SSHAC) supported by a large number other experts. The SSHAC reviewed past studies, including the Lawrence Livermore National Laboratory and the EPRI landmark PSHA studies of the 1980`s and examined ways to improve on the present state-of-the-art. The Committee`s most important conclusion is that differences in PSHA results are due to procedural rather than technical differences. Thus, in addition to providing a detailed documentation on state-of-the-art elements of a PSHA, this report provides a series of procedural recommendations. The role of experts is analyzed in detail. Two entities are formally defined-the Technical Integrator (TI) and the Technical Facilitator Integrator (TFI)--to account for the various levels of complexity in the technical issues and different levels of efforts needed in a given study.

  5. accident consequence uncertainty: Topics by E-print Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    uncertainties in typical oil and gas projects: 1. The oil price, 2. The investments (capex) and operating. The oil and gas reserves and production profiles, 5. The production...

  6. analytical uncertainty propagation: Topics by E-print Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    uncertainties in typical oil and gas projects: 1. The oil price, 2. The investments (capex) and operating. The oil and gas reserves and production profiles, 5. The production...

  7. assessing spatial uncertainty: Topics by E-print Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    uncertainties in typical oil and gas projects: 1. The oil price, 2. The investments (capex) and operating. The oil and gas reserves and production profiles, 5. The production...

  8. Electricity generation and emissions reduction decisions under uncertainty : a general equilibrium analysis

    E-Print Network [OSTI]

    Morris, Jennifer F. (Jennifer Faye)

    2013-01-01T23:59:59.000Z

    The electric power sector, which accounts for approximately 40% of U.S. carbon dioxide emissions, will be a critical component of any policy the U.S. government pursues to confront climate change. In the context of uncertainty ...

  9. Electricity Generation and Emissions Reduction Decisions under Policy Uncertainty: A General Equilibrium Analysis

    E-Print Network [OSTI]

    Morris, J.

    The electric power sector, which accounts for approximately 40% of U.S. carbon dioxide emissions, will be a critical component of any policy the U.S. government pursues to confront climate change. In the context of uncertainty ...

  10. Climate Change Impacts on Extreme Events in the United States: An Uncertainty Analysis

    E-Print Network [OSTI]

    Monier, Erwan

    Extreme weather and climate events, such as heat waves, droughts and severe precipitation events, have substantial impacts on ecosystems and the economy. However, future climate simulations display large uncertainty in ...

  11. Uncertainty Analysis in Upscaling Well Log data By Markov Chain Monte Carlo Method

    E-Print Network [OSTI]

    Hwang, Kyubum

    2010-01-16T23:59:59.000Z

    the uncertainties, a Bayesian framework could be a useful tool for providing the posterior information to give a better estimate for a chosen model with a conditional probability. In addition, the likelihood of a Bayesian framework plays an important role...

  12. Essays on Price Dynamics

    E-Print Network [OSTI]

    Hong, Gee Hee

    2012-01-01T23:59:59.000Z

    2.3 Wholesale Price vs. Retailof Adjustment - Regular Price, Sales Price and Wholesaleand Vertical Structure -Wholesale price (Weeks)100 Price

  13. Fuel cycle cost uncertainty from nuclear fuel cycle comparison

    SciTech Connect (OSTI)

    Li, J.; McNelis, D. [Institute for the Environment, University of North Carolina, Chapel Hill (United States); Yim, M.S. [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology (Korea, Republic of)

    2013-07-01T23:59:59.000Z

    This paper examined the uncertainty in fuel cycle cost (FCC) calculation by considering both model and parameter uncertainty. Four different fuel cycle options were compared in the analysis including the once-through cycle (OT), the DUPIC cycle, the MOX cycle and a closed fuel cycle with fast reactors (FR). The model uncertainty was addressed by using three different FCC modeling approaches with and without the time value of money consideration. The relative ratios of FCC in comparison to OT did not change much by using different modeling approaches. This observation was consistent with the results of the sensitivity study for the discount rate. Two different sets of data with uncertainty range of unit costs were used to address the parameter uncertainty of the FCC calculation. The sensitivity study showed that the dominating contributor to the total variance of FCC is the uranium price. In general, the FCC of OT was found to be the lowest followed by FR, MOX, and DUPIC. But depending on the uranium price, the FR cycle was found to have lower FCC over OT. The reprocessing cost was also found to have a major impact on FCC.

  14. Cheese Prices

    E-Print Network [OSTI]

    Schwart Jr., Robert B.; Anderson, David P.; Knutson, Ronald D.

    2003-08-25T23:59:59.000Z

    Cheese prices are derived from the USDA Agricultural Marketing Service Market News, the National Agricultural Statistics Service, and the Chicago Mercantile Exchange. This publication explains the process of cheese pricing. It includes information...

  15. Incorporating uncertainty into electric utility projections and decisions

    SciTech Connect (OSTI)

    Hanson, D.A.

    1992-01-01T23:59:59.000Z

    This paper focuses on how electric utility companies can respond in their decision making to uncertain variables. Here we take a mean- variance type of approach. The mean'' value is an expected cost, on a discounted value basis. We assume that management has risk preferences incorporating a tradeoff between the mean and variance in the utility's net income. Decisions that utilities are faced with can be classified into two types: ex ante and ex post. The ex ante decisions need to be made prior to the uncertainty being revealed and the ex post decision can be postponed until after the uncertainty is revealed. Intuitively, we can say that the ex ante decisions provide a hedge against the uncertainties and the ex post decisions allow the negative outcomes of uncertain variables to be partially mitigated, dampening the losses. An example of an ex post decision is how the system is operated i.e., unit dispatch, and in some cases switching among types of fuels, say with different sulfur contents. For example, if gas prices go up, natural gas combined cycle units are likely to be dispatched at lower capacity factors. If SO{sub 2} emission allowance prices go up, a utility may seek to switch into a lower sulfur coal. Here we assume that regulated electric utilities do have some incentive to lower revenue requirements and hence an incentive to lower the electric rates needed for the utility to break even, thereby earning a fair return on invested capital. This paper presents the general approach first, including applications to capacity expansion and system dispatch. Then a case study is presented focusing on the 1990 Clean Air Act Amendments including SO{sub 2} emissions abatement and banking of allowances under uncertainty. It is concluded that the emission banking decisions should not be made in isolation but rather all the uncertainties in demand, fuel prices, technology performance etc., should be included in the uncertainty analysis affecting emission banking.

  16. Incorporating uncertainty into electric utility projections and decisions

    SciTech Connect (OSTI)

    Hanson, D.A.

    1992-07-01T23:59:59.000Z

    This paper focuses on how electric utility companies can respond in their decision making to uncertain variables. Here we take a mean- variance type of approach. The ``mean`` value is an expected cost, on a discounted value basis. We assume that management has risk preferences incorporating a tradeoff between the mean and variance in the utility`s net income. Decisions that utilities are faced with can be classified into two types: ex ante and ex post. The ex ante decisions need to be made prior to the uncertainty being revealed and the ex post decision can be postponed until after the uncertainty is revealed. Intuitively, we can say that the ex ante decisions provide a hedge against the uncertainties and the ex post decisions allow the negative outcomes of uncertain variables to be partially mitigated, dampening the losses. An example of an ex post decision is how the system is operated i.e., unit dispatch, and in some cases switching among types of fuels, say with different sulfur contents. For example, if gas prices go up, natural gas combined cycle units are likely to be dispatched at lower capacity factors. If SO{sub 2} emission allowance prices go up, a utility may seek to switch into a lower sulfur coal. Here we assume that regulated electric utilities do have some incentive to lower revenue requirements and hence an incentive to lower the electric rates needed for the utility to break even, thereby earning a fair return on invested capital. This paper presents the general approach first, including applications to capacity expansion and system dispatch. Then a case study is presented focusing on the 1990 Clean Air Act Amendments including SO{sub 2} emissions abatement and banking of allowances under uncertainty. It is concluded that the emission banking decisions should not be made in isolation but rather all the uncertainties in demand, fuel prices, technology performance etc., should be included in the uncertainty analysis affecting emission banking.

  17. The IAEA Coordinated Research Program on HTGR Reactor Physics, Thermal-hydraulics and Depletion Uncertainty Analysis: Description of the Benchmark Test Cases and Phases

    SciTech Connect (OSTI)

    Frederik Reitsma; Gerhard Strydom; Bismark Tyobeka; Kostadin Ivanov

    2012-10-01T23:59:59.000Z

    The continued development of High Temperature Gas Cooled Reactors (HTGRs) requires verification of design and safety features with reliable high fidelity physics models and robust, efficient, and accurate codes. The uncertainties in the HTR analysis tools are today typically assessed with sensitivity analysis and then a few important input uncertainties (typically based on a PIRT process) are varied in the analysis to find a spread in the parameter of importance. However, one wish to apply a more fundamental approach to determine the predictive capability and accuracies of coupled neutronics/thermal-hydraulics and depletion simulations used for reactor design and safety assessment. Today there is a broader acceptance of the use of uncertainty analysis even in safety studies and it has been accepted by regulators in some cases to replace the traditional conservative analysis. Finally, there is also a renewed focus in supplying reliable covariance data (nuclear data uncertainties) that can then be used in uncertainty methods. Uncertainty and sensitivity studies are therefore becoming an essential component of any significant effort in data and simulation improvement. In order to address uncertainty in analysis and methods in the HTGR community the IAEA launched a Coordinated Research Project (CRP) on the HTGR Uncertainty Analysis in Modelling early in 2012. The project is built on the experience of the OECD/NEA Light Water Reactor (LWR) Uncertainty Analysis in Best-Estimate Modelling (UAM) benchmark activity, but focuses specifically on the peculiarities of HTGR designs and its simulation requirements. Two benchmark problems were defined with the prismatic type design represented by the MHTGR-350 design from General Atomics (GA) while a 250 MW modular pebble bed design, similar to the INET (China) and indirect-cycle PBMR (South Africa) designs are also included. In the paper more detail on the benchmark cases, the different specific phases and tasks and the latest status and plans are presented.

  18. Uncertainty Analysis of Spectral Irradiance Reference Standards Used for NREL Calibrations

    SciTech Connect (OSTI)

    Habte, A.; Andreas, A.; Reda, I.; Campanelli, M.; Stoffel, T.

    2013-05-01T23:59:59.000Z

    Spectral irradiance produced by lamp standards such as the National Institute of Standards and Technology (NIST) FEL-type tungsten halogen lamps are used to calibrate spectroradiometers at the National Renewable Energy Laboratory. Spectroradiometers are often used to characterize spectral irradiance of solar simulators, which in turn are used to characterize photovoltaic device performance, e.g., power output and spectral response. Therefore, quantifying the calibration uncertainty of spectroradiometers is critical to understanding photovoltaic system performance. In this study, we attempted to reproduce the NIST-reported input variables, including the calibration uncertainty in spectral irradiance for a standard NIST lamp, and quantify uncertainty for measurement setup at the Optical Metrology Laboratory at the National Renewable Energy Laboratory.

  19. Measuring and Explaining Electricity Price Changes in Restructured States

    SciTech Connect (OSTI)

    Fagan, Mark L.

    2006-06-15T23:59:59.000Z

    An effort to determine the effect of restructuring on prices finds that, on average, prices for industrial customers in restructured states were lower, relative to predicted prices, than prices for industrial customers in non-restructured states. This preliminary analysis also finds that these price changes are explained primarily by high pre-restructuring prices, not whether or not a state restructured. (author)

  20. A note on competitive investment under uncertainty

    E-Print Network [OSTI]

    Pindyck, Robert S.

    1991-01-01T23:59:59.000Z

    This paper clarifies how uncertainty affects irreversible investment in a competitive market equilibrium. With free entry, irreversibility affects the distribution of future prices, and thereby creates an opportunity cost ...

  1. CO? price impact on Dell's supply chain : a framework for carbon footprint economic analysis

    E-Print Network [OSTI]

    Colón-Jiménez, Ely X

    2010-01-01T23:59:59.000Z

    The principal scope of this project is to design, analyze and report a case study of how to effectively account for the highly likely scenario of a CO2 price policy (cap-and-trade or tax) with regard to Dell's product and ...

  2. Draft regulatory analysis: Notice of proposed rulemaking for the allocation and pricing of gasohol

    SciTech Connect (OSTI)

    None,

    1980-05-01T23:59:59.000Z

    The three principal problem areas addressed are: how to price unleaded blend stock and gasohol; how blenders are to obtain unleaded blend stock to blend with ethanol to produce gasohol; and how gasohol suppliers may distribute gasohol to purchasers. The proposed pricing and allocation rules, if adopted as final rules, would be in effect for about a year, because the statutory authority for gasoline price and allocation controls has an expiration date of September 30, 1981. The principal issues addressed are: what volume of ethanol and gasohol production can be expected between now and the end of 1981; what prices these products are likely to reach, independent of the rule and its alternative; what effect the rule and its alternative may have on the price and distribution of ethanol and gasohol; and what effect the rule and its alternative may have on motor vehicle misfueling and competition in the motor gasoline industry. On supply issues, it is concluded that by December, 1981, ethanol and gasohol production should increase by a factor of 3 or 4 above present levels, enough to meet the President's goals, without requiring additional corn acreage or adversely affecting food production. Ethanol production should increase from its present level of about 92 million gallons per year (6062 B/D) to the 3, 4, and 7 hundred million gallons per year levels (20,000, 30,000, and 45,000 B/D) necessaryto produce gasohol at year-end rates of 200,000 B/D in 1980, 300,000 B/D in 1981 and 450,000 B/D in 1982. In 1980 gasohol will represent about 3.2 percent of the total gasoline market, and 7.9 percent of the total unleaded market. Gasohol should help extend, rather than adversely affect, unleaded supplies. 30 references, 8 tables.

  3. Development of the two-dimensional cross-section sensitivity and uncertainty analysis code SENSIT-2D with applications to the FED

    SciTech Connect (OSTI)

    Embrechts, M.J.; Dudziak, D.J.; Urban, W.T.

    1983-01-01T23:59:59.000Z

    Sensitivity and uncertainty analyses implement the information obtained from a transport code by providing a reasonable estimate for the uncertainty of a particular design parameter and a better understanding of the nucleonics involved. The toroidal geometry of many fusion devices motivates a two-dimensional calculation capability. A two-dimensional cross-section and secondary energy distribution (SED) sensitivity and uncertainty analysis code, SENSIT-2D, has been developed that allows modeling of a toroidal geometry. Two-dimensional and one-dimensional sensitivity analyses for the heating and the copper d.p.a. of the TF coil for a conceptual FED blanket/shield design were performed. The uncertainties from the two-dimensional analysis are of the same order of magnitude as those obtained from the one-dimensional study. The largest uncertainties were caused by the cross-section covariances for chromium.

  4. Evaluating and developing parameter optimization and uncertainty analysis methods for a computationally intensive distributed hydrological model 

    E-Print Network [OSTI]

    Zhang, Xuesong

    2009-05-15T23:59:59.000Z

    ? weights for river stage prediction (Chau, 2006). Other evolutionary algorithms, such as Differential Evaluation (DE) (Storn and Price, 1997) and Artificial Immune Systems (AIS) (de Castro and Von Zuben, 2002a; de Castro and Von Zuben, 2002b), although... is to structure the hydrologic model as a probability model, then the confidence interval of model output can be computed (Montanari et al., 1997). Representative methods of this category include Markov Chain Monte Carlo (MCMC) and a Generalized Likelihood...

  5. Mapping and uncertainty analysis of energy and pitch angle phase space in the DIII-D fast ion loss detector

    SciTech Connect (OSTI)

    Pace, D. C., E-mail: pacedc@fusion.gat.com; Fisher, R. K.; Van Zeeland, M. A. [General Atomics, PO Box 85608, San Diego, California 92186-5608 (United States); Pipes, R. [Department of Physics, University of Hawaii, Hilo, Hawaii 96720-4091 (United States)

    2014-11-15T23:59:59.000Z

    New phase space mapping and uncertainty analysis of energetic ion loss data in the DIII-D tokamak provides experimental results that serve as valuable constraints in first-principles simulations of energetic ion transport. Beam ion losses are measured by the fast ion loss detector (FILD) diagnostic system consisting of two magnetic spectrometers placed independently along the outer wall. Monte Carlo simulations of mono-energetic and single-pitch ions reaching the FILDs are used to determine the expected uncertainty in the measurements. Modeling shows that the variation in gyrophase of 80 keV beam ions at the FILD aperture can produce an apparent measured energy signature spanning across 50-140 keV. These calculations compare favorably with experiments in which neutral beam prompt loss provides a well known energy and pitch distribution.

  6. Coalescing Executions for Fast Uncertainty Analysis William N. Sumner Tao Bao Xiangyu Zhang Sunil Prabhakar

    E-Print Network [OSTI]

    Zhang, Xiangyu

    of the output. In this paper, we propose a technique to improve the cost-effectiveness of MC methods. Assuming.3 [Programming Languages]: Language Con- structs and Features General Terms Languages, Experimentation, Performance Keywords uncertainty, sensitivity, monte carlo, coalescing 1. INTRODUCTION Uncertain data

  7. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison (Presentation)

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B.; Miettinen, J.; Holttinen, H.; Gomez-Lozaro, E.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Lovholm, A.; Berge, E.; Dobschinski, J.

    2013-10-01T23:59:59.000Z

    This presentation summarizes the work to investigate the uncertainty in wind forecasting at different times of year and compare wind forecast errors in different power systems using large-scale wind power prediction data from six countries: the United States, Finland, Spain, Denmark, Norway, and Germany.

  8. A regional analysis of U.S. utility slaughter cows prices

    E-Print Network [OSTI]

    Rogers, Toby Gale

    1996-01-01T23:59:59.000Z

    impacts on prices within each region justifies the use of the SUR. 3t Table 4. Coefficients for Monthly Dummy Variables, Base Month = October' Re JAN FEB MAR APR MAY JUN JUL AUG SEP NOV DEC 0. 03 (1. 9) 0. 01 (0. 8) 0. 02 (1. 4) 0. 03 (2. 5) 0... are in parenthesis. Table 5. Percentage Change in Monthly Cow Prices Relative to October Re JAN FEB MAR APR MAY JUN JUL AUG SEP NOV DEC 2 74 (1 9) 0. 90 (0. 8) 1. 92 (1 4) 3. 98 3. 87 2. 94 4. 60 2. 22 -1. 69 0. 50 -1. 19 1. 11 1. 41 (2. 8) (2. 7) (2. 1) (3...

  9. Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis :

    SciTech Connect (OSTI)

    Adams, Brian M.; Ebeida, Mohamed Salah; Eldred, Michael S.; Jakeman, John Davis; Swiler, Laura Painton; Stephens, John Adam; Vigil, Dena M.; Wildey, Timothy Michael; Bohnhoff, William J.; Eddy, John P.; Hu, Kenneth T.; Dalbey, Keith R.; Bauman, Lara E; Hough, Patricia Diane

    2014-05-01T23:59:59.000Z

    The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

  10. Uncertainties analysis of fission fraction for reactor antineutrino experiments using DRAGON

    E-Print Network [OSTI]

    X. B. Ma; L. Z. Wang; Y. X. Chen; W. L. Zhong; F. P. An

    2014-05-27T23:59:59.000Z

    Rising interest in nuclear reactors as a source of antineutrinos for experiments motivates validated, fast, and accessible simulation to predict reactor rates. First, DRAGON was developed to calculate the fission rates of the four most important isotopes in fissions,235U,238U,239Pu and141Pu, and it was validated for PWRs using the Takahama benchmark. The fission fraction calculation function was validated through comparing our calculation results with MIT's results. we calculate the fission fraction of the Daya Bay reactor core, and compare its with those calculated by the commercial reactor simulation program SCIENCE, which is used by the Daya Bay nuclear power plant, and the results was consist with each other. The uncertainty of the antineutrino flux by the fission fraction was studied, and the uncertainty of the antineutrino flux by the fission fraction simulation is 0.6% per core for Daya Bay antineutrino experiment.

  11. Addendum to: QRPA uncertainties and their correlations in the analysis of neutrinoless double beta decay

    E-Print Network [OSTI]

    Amand Faessler; G. L. Fogli; E. Lisi; V. Rodin; A. M. Rotunno; F. Simkovic

    2013-01-07T23:59:59.000Z

    In a previous article [Phys. Rev. D 79, 053001 (2009)] we estimated the correlated uncertainties associated to the nuclear matrix elements (NME) of neutrinoless double beta decay (0 nu beta beta) within the quasiparticle random phase approximation (QRPA). Such estimates encompass recent independent calculations of NMEs, and can thus still provide a fair representation of the nuclear model uncertainties. In this context, we compare the claim of 0 nu beta beta decay in Ge-76 with recent negative results in Xe-136 and in other nuclei, and we infer the lifetime ranges allowed or excluded at 90% C.L. We also highlight some issues that should be addressed in order to properly compare and combine results coming from different 0 nu beta beta decay candidate nuclei.

  12. The optimal harvesting problem with price uncertainty

    E-Print Network [OSTI]

    2011-07-01T23:59:59.000Z

    Jul 1, 2011 ... Abstract. In this paper we study the exploitation of a one species forest plan- ...... Optimal harvesting models in forest management – a survey.

  13. Microsoft Word - Price Uncertainty Supplement .docx

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115 10 11 1

  14. Microsoft Word - Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115 10 11

  15. Microsoft Word - Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115 10 110 1

  16. Microsoft Word - Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115 10 110 1

  17. Microsoft Word - Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115 10 110

  18. Microsoft Word - Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115 10 1100

  19. Microsoft Word - Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115 10 11000

  20. Microsoft Word - Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115 10

  1. Microsoft Word - Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115 10May

  2. Microsoft Word - Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115

  3. Microsoft Word - Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115October

  4. Microsoft Word - Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter Fuels8 115October0

  5. Considerations for sensitivity analysis, uncertainty quantification, and data assimilation for grid-to-rod fretting

    SciTech Connect (OSTI)

    Michael Pernice

    2012-10-01T23:59:59.000Z

    Grid-to-rod fretting is the leading cause of fuel failures in pressurized water reactors, and is one of the challenge problems being addressed by the Consortium for Advanced Simulation of Light Water Reactors to guide its efforts to develop a virtual reactor environment. Prior and current efforts in modeling and simulation of grid-to-rod fretting are discussed. Sources of uncertainty in grid-to-rod fretting are also described.

  6. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.; Gomez-Lazaro, E.; Lovholm, A. L.; Berge, E.; Miettinen, J.; Holttinen, H.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Dobschinski, J.

    2013-10-01T23:59:59.000Z

    One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

  7. A Tool for the Analysis of Real Options in Sustainability Improvement Projects 

    E-Print Network [OSTI]

    Boonchanta, Napon

    2012-10-19T23:59:59.000Z

    .................................................................................................... 27 6.3 Simulation model of uncertainty scenarios .......................................................... 29 6.3.1 Uncertainty in electricity price ........................................................ 30 6.3.2 Uncertainty in photovoltaic.... The model considered only uncertainties in the price of energy, Photovoltaic technology efficiency and price volatility in Photovoltaic technology. Future retail energy price was modeled using the Binomial Lattice model while Photovoltaic price...

  8. An Analysis of the Effects of Residential Photovoltaic Energy Systems on Home Sales Prices in California

    SciTech Connect (OSTI)

    Hoen, Ben; Cappers, Peter; Wiser, Ryan; Thayer, Mark

    2011-04-19T23:59:59.000Z

    An increasing number of homes in the U.S. have sold with photovoltaic (PV) energy systems installed at the time of sale, yet relatively little research exists that estimates the marginal impacts of those PV systems on home sale prices. A clearer understanding of these possible impacts might influence the decisions of homeowners considering the installation of a PV system, homebuyers considering the purchase of a home with PV already installed, and new home builders considering including PV as an optional or standard product on their homes. This research analyzes a large dataset of California homes that sold from 2000 through mid-2009 with PV installed. It finds strong evidence that homes with PV systems sold for a premium over comparable homes without PV systems during this time frame. Estimates for this premium expressed in dollars per watt of installed PV range, on average, from roughly $4 to $5.5/watt across a large number of hedonic and repeat sales model specifications and robustness tests. When expressed as a ratio of the sales price premium of PV to estimated annual energy cost savings associated with PV, an average ratio of 14:1 to 19:1 can be calculated; these results are consistent with those of the more-extensive existing literature on the impact of energy efficiency on sales prices. When the data are split among new and existing homes, however, PV system premiums are markedly affected. New homes with PV show premiums of $2.3-2.6/watt, while existing homes with PV show premiums of more than $6/watt. Reasons for this discrepancy are suggested, yet further research is warranted. A number of other areas where future research would be useful are also highlighted.

  9. What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis

    E-Print Network [OSTI]

    Kristoufek, Ladislav

    2014-01-01T23:59:59.000Z

    Bitcoin has emerged as a fascinating phenomenon of the financial markets. Without any central authority issuing the currency, it has been associated with controversy ever since its popularity and public interest reached high levels. Here, we contribute to the discussion by examining potential drivers of Bitcoin prices ranging from fundamental to speculative and technical sources as well as a potential influence of the Chinese market. The evolution of the relationships is examined in both time and frequency domains utilizing the continuous wavelets framework so that we comment on development of the interconnections in time but we can also distinguish between short-term and long-term connections.

  10. Proposal for the utilization of the total cross section covariances and its correlations with channel reactions for sensitivity and uncertainty analysis

    SciTech Connect (OSTI)

    Sabouri, P.; Bidaud, A. [Labratoire de Physique Subatomique et de Cosmologie, CNRS-IN2P3/UJF/INPG, Grenoble (France); Dabiran, S.; Buijs, A. [Dept. of Engineering Physics, McMaster Univ., Hamilton, ON (Canada)

    2012-07-01T23:59:59.000Z

    An alternate method for the estimation of the global uncertainty on criticality, using the total cross section and its covariances, is proposed. Application of the method with currently available covariance data leads to an unrealistically large prediction of the global uncertainty on criticality. New covariances for total cross section and individual reactions are proposed. Analysis with the proposed covariance matrices is found to result in a global uncertainty for criticality consistent with the traditional method. Recommendations are made to evaluators for providing total cross section covariances. (authors)

  11. Analysis of uncertainties in CRAC2 calculations: wet deposition and plume rise

    SciTech Connect (OSTI)

    Ward, R.C.; Kocher, D.C.; Hicks, B.B.; Hosker, R.P. Jr.; Ku, J.Y.; Rao, K.S.

    1984-01-01T23:59:59.000Z

    We have studied the sensitivity of results from the CRAC2 computer code, which predicts health impacts from a reactor-accident scenario, to uncertainties in selected meteorological models and parameters. The sources of uncertainty examined include the models for plume rise and wet deposition and the meteorological bin-sampling procedure. An alternative plume-rise model usually had little effect on predicted health impacts. In an alternative wet-deposition model, the scavenging rate depends only on storm type, rather than on rainfall rate and atmospheric stability class as in the CRAC2 model. Use of the alternative wet-deposition model in meteorological bin-sampling runs decreased predicted mean early injuries by as much as a factor of 2 to 3 and, for large release heights and sensible heat rates, decreased mean early fatalities by nearly an order of magnitude. The bin-sampling procedure in CRAC2 was expanded by dividing each rain bin into four bins that depend on rainfall rate. Use of the modified bin structure in conjunction with the CRAC2 wet-deposition model changed all predicted health impacts by less than a factor of 2. 9 references.

  12. REVIEW OF MECHANISTIC UNDERSTANDING AND MODELING AND UNCERTAINTY ANALYSIS METHODS FOR PREDICTING CEMENTITIOUS BARRIER PERFORMANCE

    SciTech Connect (OSTI)

    Langton, C.; Kosson, D.

    2009-11-30T23:59:59.000Z

    Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various chapters contain both a description of the mechanism or and a discussion of the current approaches to modeling the phenomena.

  13. Structural model uncertainty in stochastic simulation

    SciTech Connect (OSTI)

    McKay, M.D.; Morrison, J.D. [Los Alamos National Lab., NM (United States). Technology and Safety Assessment Div.

    1997-09-01T23:59:59.000Z

    Prediction uncertainty in stochastic simulation models can be described by a hierarchy of components: stochastic variability at the lowest level, input and parameter uncertainty at a higher level, and structural model uncertainty at the top. It is argued that a usual paradigm for analysis of input uncertainty is not suitable for application to structural model uncertainty. An approach more likely to produce an acceptable methodology for analyzing structural model uncertainty is one that uses characteristics specific to the particular family of models.

  14. Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model

    E-Print Network [OSTI]

    Jiang, Yueyang

    This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares ...

  15. Risk-Informed Safety Margin Characterization (RISMC): Integrated Treatment of Aleatory and Epistemic Uncertainty in Safety Analysis

    SciTech Connect (OSTI)

    R. W. Youngblood

    2010-10-01T23:59:59.000Z

    The concept of “margin” has a long history in nuclear licensing and in the codification of good engineering practices. However, some traditional applications of “margin” have been carried out for surrogate scenarios (such as design basis scenarios), without regard to the actual frequencies of those scenarios, and have been carried out with in a systematically conservative fashion. This means that the effectiveness of the application of the margin concept is determined in part by the original choice of surrogates, and is limited in any case by the degree of conservatism imposed on the evaluation. In the RISMC project, which is part of the Department of Energy’s “Light Water Reactor Sustainability Program” (LWRSP), we are developing a risk-informed characterization of safety margin. Beginning with the traditional discussion of “margin” in terms of a “load” (a physical challenge to system or component function) and a “capacity” (the capability of that system or component to accommodate the challenge), we are developing the capability to characterize probabilistic load and capacity spectra, reflecting both aleatory and epistemic uncertainty in system response. For example, the probabilistic load spectrum will reflect the frequency of challenges of a particular severity. Such a characterization is required if decision-making is to be informed optimally. However, in order to enable the quantification of probabilistic load spectra, existing analysis capability needs to be extended. Accordingly, the INL is working on a next-generation safety analysis capability whose design will allow for much more efficient parameter uncertainty analysis, and will enable a much better integration of reliability-related and phenomenology-related aspects of margin.

  16. Price regulation for waste hauling franchises in California: an examination of how regulators regulate pricing and the effects of competition on regulated markets

    E-Print Network [OSTI]

    Seltzer, Steven A.

    2011-01-01T23:59:59.000Z

    Thomadakis, Stavros. “Price Regulation Under Uncertainty inin the Theory of Regulation. ” Handbook of IndustrialMark and David Sappington. “Regulation, Competition and

  17. The Impact of City-level Permitting Processes on Residential Photovoltaic Installation Prices and Development Times: An Empirical Analysis of Solar Systems in California Cities

    E-Print Network [OSTI]

    Wiser, Ryan

    2014-01-01T23:59:59.000Z

    and Utility-Scale Photovoltaic System Prices in the UnitedResidential Photovoltaic Installation Prices and DevelopmentResidential Photovoltaic Installation Prices and Development

  18. Signal discovery, limits, and uncertainties with sparse On/Off measurements: an objective Bayesian analysis

    E-Print Network [OSTI]

    Max L. Knoetig

    2014-06-11T23:59:59.000Z

    For decades researchers have studied the On/Off counting problem, where a measured rate consists of two parts. One due to a signal process and another due to a background process, of which both magnitudes are unknown. While most frequentist methods are adequate for large count numbers, they cannot be applied to sparse data. Here I want to present a new objective Bayesian solution that only depends on three parameters: the number of events in the signal region, the number of events in the background region, and the ratio of the exposure for both regions. First, the probability of the hypothesis that the counts are due to background only is derived analytically. Second, the marginalized posterior for the signal parameter is also derived analytically. With this two-step approach it is easy to calculate the signal's significance, strength, uncertainty, or upper limit in a unified way. The approach is valid without restrictions for any count number including zero and may be widely applied in particle physics, cosmic-ray physics and high-energy astrophysics. In order to demonstrate its performance I apply the method to gamma-ray burst data.

  19. Assessor Training Measurement Uncertainty

    E-Print Network [OSTI]

    NVLAP Assessor Training Measurement Uncertainty #12;Assessor Training 2009: Measurement Uncertainty Training 2009: Measurement Uncertainty 3 Measurement Uncertainty ·Calibration and testing labs performing Training 2009: Measurement Uncertainty 4 Measurement Uncertainty ·When the nature of the test precludes

  20. Columbia University flow instability experimental program: Volume 2. Single tube uniformly heated tests -- Part 2: Uncertainty analysis and data

    SciTech Connect (OSTI)

    Dougherty, T.; Maciuca, C.; McAssey, E.V. Jr.; Reddy, D.G.; Yang, B.W.

    1990-05-01T23:59:59.000Z

    In June 1988, Savannah River Laboratory requested that the Heat Transfer Research Facility modify the flow excursion program, which had been in progress since November 1987, to include testing of single tubes in vertical down-flow over a range of length to diameter (L/D) ratios of 100 to 500. The impetus for the request was the desire to obtain experimental data as quickly as possible for code development work. In July 1988, HTRF submitted a proposal to SRL indicating that by modifying a facility already under construction the data could be obtained within three to four months. In January 1990, HTFR issued report CU-HTRF-T4, part 1. This report contained the technical discussion of the results from the single tube uniformly heated tests. The present report is part 2 of CU-HTRF-T4 which contains further discussion of the uncertainty analysis and the complete set of data.

  1. An Analysis of Residential PV System Price Differences between the United States and Germany

    Broader source: Energy.gov [DOE]

    Residential photovoltaic (PV) systems were twice as expensive in the United States as in Germany (median of $5.29/W vs. $2.59/W) in 2012. This price discrepancy stems primarily from differences in non-hardware or "soft" costs between the two countries, which can only be explained in part by differences in cumulative market size and associated learning. A survey of German PV installers was deployed to collect rough data on PV soft costs in Germany to compare to results of a similar survey of U.S. PV installers. Non-module hardware costs and all analyzed soft costs are lower in Germany, especially for customer acquisition, installation labor, and profit/overhead costs, but also for expenses related to permitting, interconnection, and inspection procedures. Additional costs occur in the United States due to state and local sales taxes, smaller average system sizes, and longer project development times. To reduce the identified additional costs of residential PV systems, the United States could introduce policies that enable a robust and lasting market while minimizing market fragmentation.

  2. The Effect of Changing Input and Product Prices on the Demand for Irrigation Water in Texas

    E-Print Network [OSTI]

    Lacewell, R. D.; Condra, G. D.

    uncertainties which often have not disturbed the policy-maker in evaluating alternatives. Product prices have risen and fallen at an unprecedented rate while input prices have steadily risen at rates which preclude realistic budgeting. For example, during...

  3. A new approach and computational algorithm for sensitivity/uncertainty analysis for SED and SAD with applications to beryllium integral experiments

    SciTech Connect (OSTI)

    Song, P.M.; Youssef, M.Z.; Abdou, M.A. (Univ. of California, Los Angeles (United States))

    1993-04-01T23:59:59.000Z

    A new approach for treating the sensitivity and uncertainty in the secondary energy distribution (SED) and the secondary angular distribution (SAD) has been developed, and the existing two-dimensional sensitivity/uncertainty analysis code, FORSS, was expanded to incorporate the new approach. The calculational algorithm was applied to the [sup 9]Be(n,2n) cross section to study the effect of the current uncertainties in the SED and SAD of neutrons emitted from this reaction on the prediction accuracy of the tritium production rate from [sup 6]Li(T[sub 6]) and [sup 7]Li(T[sub 7]) in an engineering-oriented fusion integral experiment of the US Department of Energy/Japan Atomic Energy Research Institute Collaborative Program on Fusion Neutronics in which beryllium was used as a neutron multiplier. In addition, the analysis was extended to include the uncertainties in the integrated smooth cross sections of beryllium and other materials that constituted the test assembly used in the experiment. This comprehensive two-dimensional cross-section sensitivity/uncertainty analysis aimed at identifying the sources of discrepancies between calculated and measured values for T[sub 6] and T[sub 7].

  4. Use of Quantitative Uncertainty Analysis to Support M&V Decisions in Super ESPCs

    E-Print Network [OSTI]

    Kumar, Satish; Mathew, Paul

    2005-01-01T23:59:59.000Z

    the financial analysis of the ESPC, in that it providesis a critical element of an ESPC—without it, there is no wayrealized. Every FEMP Super ESPC is required to have an M&V

  5. as-run neutronics uncertainty: Topics by E-print Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    uncertainties in typical oil and gas projects: 1. The oil price, 2. The investments (capex) and operating. The oil and gas reserves and production profiles, 5. The production...

  6. Algal Biomass Constituent Analysis: Method Uncertainties and Investigation of the Underlying Measuring Chemistries

    SciTech Connect (OSTI)

    Laurens, L. M. L.; Dempster, T. A.; Jones, H. D. T.; Wolfrum, E. J.; Van Wychen, S.; McAllister, J. S. P.; Rencenberger, M.; Parchert, K. J.; Gloe, L. M.

    2012-02-21T23:59:59.000Z

    Algal biomass compositional analysis data form the basis of a large number of techno-economic process analysis models that are used to investigate and compare different processes in algal biofuels production. However, the analytical methods used to generate these data are far from standardized. This work investigated the applicability of common methods for rapid chemical analysis of biomass samples with respect to accuracy and precision. This study measured lipids, protein, carbohydrates, ash, and moisture of a single algal biomass sample at 3 institutions by 8 independent researchers over 12 separate workdays. Results show statistically significant differences in the results from a given analytical method among laboratories but not between analysts at individual laboratories, suggesting consistent training is a critical issue for empirical analytical methods. Significantly different results from multiple lipid and protein measurements were found to be due to different measurement chemistries. We identified a set of compositional analysis procedures that are in best agreement with data obtained by more advanced analytical procedures. The methods described here and used for the round robin experiment do not require specialized instrumentation, and with detailed analytical documentation, the differences between laboratories can be markedly reduced.

  7. ResGrid: A Grid-Aware Toolkit for Reservoir Uncertainty Analysis

    E-Print Network [OSTI]

    Allen, Gabrielle

    ,000 oil producing wells, around 4K offshore. Reservoir Studies · Assessments and predictions of oil/gas oil, water or gas. · Many geological parameters cannot be measured or modeled and are unknowns. · We ­ Drilling performance analysis with high-rate data "UCOMS" #12;Oil Industry in Louisiana · Major oil

  8. Why are allowance prices so low? : an analysis of the SO2 emissions trading program

    E-Print Network [OSTI]

    Ellerman, A. Denny

    1996-01-01T23:59:59.000Z

    This paper presents an analysis of the reduction in SO2 emissions by electric utilities between 1985 and 1993. We find that emissions have been reduced for reasons largely unrelated to the emission reduction mandate ...

  9. Uncertainty Analysis of a Giant Oil Field in the Middle East Using Surrogate Reservoir Model Shahab D. Mohaghegh, West Virginia University

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    management. The underlying static models are the result of integrated efforts that usually includesUncertainty Analysis of a Giant Oil Field in the Middle East Using Surrogate Reservoir Model Shahab, and Maher Kenawy, ADCO ABSTRACT Simulation models are routinely used as a powerful tool for reservoir

  10. Effects of breach formation parameter uncertainty on inundation risk area and consequence analysis

    SciTech Connect (OSTI)

    Skousen, Benjamin Don [Los Alamos National Laboratory; David, Judi [Los Alamos National Laboratory; Mc Pherson, Timothy [Los Alamos National Laboratory; Burian, Steve [UNIV OF UTAH

    2010-01-01T23:59:59.000Z

    According to the national inventory of dams (NID), there are approximately 79,500 dams in the United States, with 11,800 of these dams being classified as high-hazard. It has been recommended that each high-hazard dam in the United States have an emergency action plan (EAP), but it has been found that only about 60% of the high-hazard dams have a complete EAP. A major aspect of these plans is inundation risk area identification and associated impacts in the event of dam failure. In order to determine the inundation risk area an estimation of breach discharge must be completed. Most methods used to determine breach discharge, including the NWS-DAMBRK model, require modelers to select size, shape, and time of breach formation. Federal agencies (e.g. Bureau of Reclamation, Federal Energy Regulatory Commission) with oversight of U.S. dams have recommended ranges of values for each of these parameters based on dam type. However, variations in these parameters even within the recommended range have the potential to impose significant transformation on the discharge hydrograph relative to both timing and magnitude of the peak discharge. Therefore, it has also been recommended that sensitivity of these parameters be investigated when performing breach inundation analyses. This paper presents a sensitivity analysis of three breach parameters (average breach width, side slope, and time to failure) on a case study dam located in the United States. The sensitivity analysis employed was based on the 3{sup 3} factorial design, in which three levels (e.g. low, medium, and high) were selected for each of the three parameters, resulting in twenty-seven combinations. The three levels remained within the recommended range of values for each parameter type. With each combination of input parameters, a discharge hydrograph was generated and used as a source condition for inundation analysis using a two-dimensional shallow water equation model. The resulting simulations were compared to determine the sensitivity of flood inundation area, flood arrival time, peak flood depths, and socio-economic impacts (e.g. population at risk, direct and indirect economic loss) to changes in individual parameters and parameter interactions. Results and discussion from this sensitivity analysis will be presented in detail in the paper.

  11. Analysis of Future Prices and Markets for High Temperature Superconductors ENERGY SAVINGS IN HTS DEVICES

    E-Print Network [OSTI]

    of each device. The incremental capital cost is the cost over and above that of cryogenics and HTS wire SAVINGS IN HTS DEVICES This Appendix collects and explains several of the key assumptions a sequence of changes to the economic analysis of the individual HTS devices. Table 1-1 displays certain

  12. DAKOTA, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis:version 4.0 reference manual

    SciTech Connect (OSTI)

    Griffin, Joshua D. (Sandai National Labs, Livermore, CA); Eldred, Michael Scott; Martinez-Canales, Monica L. (Sandai National Labs, Livermore, CA); Watson, Jean-Paul; Kolda, Tamara Gibson (Sandai National Labs, Livermore, CA); Adams, Brian M.; Swiler, Laura Painton; Williams, Pamela J. (Sandai National Labs, Livermore, CA); Hough, Patricia Diane (Sandai National Labs, Livermore, CA); Gay, David M.; Dunlavy, Daniel M.; Eddy, John P.; Hart, William Eugene; Guinta, Anthony A.; Brown, Shannon L.

    2006-10-01T23:59:59.000Z

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a reference manual for the commands specification for the DAKOTA software, providing input overviews, option descriptions, and example specifications.

  13. DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's reference manual.

    SciTech Connect (OSTI)

    Eldred, Michael Scott; Dalbey, Keith R.; Bohnhoff, William J.; Adams, Brian M.; Swiler, Laura Painton; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gay, David M.; Eddy, John P.; Haskell, Karen H.

    2010-05-01T23:59:59.000Z

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a reference manual for the commands specification for the DAKOTA software, providing input overviews, option descriptions, and example specifications.

  14. Understanding Crude Oil Prices

    E-Print Network [OSTI]

    Hamilton, James Douglas

    2008-01-01T23:59:59.000Z

    2004. “OPEC’s Optimal Crude Oil Price,” Energy Policy 32(2),percent change in real oil price. Figure 3. Price of crudein predicting quarterly real oil price change. variable real

  15. Understanding Crude Oil Prices

    E-Print Network [OSTI]

    Hamilton, James Douglas

    2008-01-01T23:59:59.000Z

    2004. “OPEC’s Optimal Crude Oil Price,” Energy Policy 32(2),percent change in real oil price. Figure 3. Price of crude023 Understanding Crude Oil Prices James D. Hamilton June

  16. Neutron activation analysis of the 30Si content of highly enriched 28Si: proof of concept and estimation of the achievable uncertainty

    E-Print Network [OSTI]

    D'Agostino, Giancarlo; Oddone, Massimo; Prata, Michele; Bergamaschi, Luigi; Giordani, Laura

    2014-01-01T23:59:59.000Z

    We investigated the use of neutron activation to estimate the 30Si mole fraction of the ultra-pure silicon material highly enriched in 28Si for the measurement of the Avogadro constant. Specifically, we developed a relative method based on Instrumental Neutron Activation Analysis and using a natural-Si sample as a standard. To evaluate the achievable uncertainty, we irradiated a 6 g sample of a natural-Si material and modeled experimentally the signal that would be produced by a sample of the 28Si-enriched material of similar mass and subjected to the same measurement conditions. The extrapolation of the expected uncertainty from the experimental data indicates that a measurement of the 30Si mole fraction of the 28Si-enriched material might reach a 4% relative combined standard uncertainty.

  17. Predicting System Performance with Uncertainty

    E-Print Network [OSTI]

    Yan, B.; Malkawi, A.

    2012-01-01T23:59:59.000Z

    on uncertainty in input values for predictions. The input values associated with predictions can come from estimations or measurements corrupted with noise. Therefore, it is more reasonable to assign probability distributions over their domains of plausible... increases, the number of simulations required increases significantly. The time cost limits the extension of uncertainty analysis. Current studies have not covered uncertainty related to system controls in operations. Measurements in system operations...

  18. Development, sensitivity analysis, and uncertainty quantification of high-fidelity arctic sea ice models.

    SciTech Connect (OSTI)

    Peterson, Kara J.; Bochev, Pavel Blagoveston; Paskaleva, Biliana S.

    2010-09-01T23:59:59.000Z

    Arctic sea ice is an important component of the global climate system and due to feedback effects the Arctic ice cover is changing rapidly. Predictive mathematical models are of paramount importance for accurate estimates of the future ice trajectory. However, the sea ice components of Global Climate Models (GCMs) vary significantly in their prediction of the future state of Arctic sea ice and have generally underestimated the rate of decline in minimum sea ice extent seen over the past thirty years. One of the contributing factors to this variability is the sensitivity of the sea ice to model physical parameters. A new sea ice model that has the potential to improve sea ice predictions incorporates an anisotropic elastic-decohesive rheology and dynamics solved using the material-point method (MPM), which combines Lagrangian particles for advection with a background grid for gradient computations. We evaluate the variability of the Los Alamos National Laboratory CICE code and the MPM sea ice code for a single year simulation of the Arctic basin using consistent ocean and atmospheric forcing. Sensitivities of ice volume, ice area, ice extent, root mean square (RMS) ice speed, central Arctic ice thickness, and central Arctic ice speed with respect to ten different dynamic and thermodynamic parameters are evaluated both individually and in combination using the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA). We find similar responses for the two codes and some interesting seasonal variability in the strength of the parameters on the solution.

  19. International market integration for natural gas? : a cointegration analysis of priced in Europe, North America and Japan

    E-Print Network [OSTI]

    L'Hegaret, Guillaume

    2004-01-01T23:59:59.000Z

    We examine the degree of natural gas market integration in Europe, North America and Japan, between the mid 1990?s and 2002. Our hypothesis is that there was a certain split of prices between Europe and North America. The ...

  20. Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model – Evidence from MOPEX Basins

    SciTech Connect (OSTI)

    Huang, Maoyi; Hou, Zhangshuan; Leung, Lai-Yung R.; Ke, Yinghai; Liu, Ying; Fang, Zhufeng; Sun, Yu

    2013-12-01T23:59:59.000Z

    With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning a wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.

  1. Optimization Under Generalized Uncertainty

    E-Print Network [OSTI]

    Lodwick, Weldon

    11 Optimization Under Generalized Uncertainty Optimization Modeling Math 4794/5794: Spring 2013 Weldon A. Lodwick Weldon.Lodwick@ucdenver.edu 2/14/2013 Optimization Modeling - Spring 2013 #12 in the context of optimization problems. The theoretical frame-work for these notes is interval analysis. From

  2. Price Risk Management in the Midst of a Credit Crisis

    E-Print Network [OSTI]

    Welch, Mark; Amosson, Stephen H.; Robinson, John; Falconer, Lawrence

    2009-03-26T23:59:59.000Z

    Agricultural producers today face volatile markets, tight credit, economic uncertainty and escalating input costs. Understanding and using risk management tools in this environment can reduce much of the price risk and may improve financial returns....

  3. Selling Into the Sun: Price Premium Analysis of a Multi-State Dataset of Solar Homes

    Broader source: Energy.gov [DOE]

    Homes with solar photovoltaic (PV) systems have multiplied in the United States recently, reaching more than half a million in 2014, in part due to plummeting PV costs and innovative financing options. As PV systems become an increasingly common feature of U.S. homes, the ability to assess the value of these homes appropriately will become increasingly important. At the same time, capturing the value of PV to homes will be important for facilitating a robust residential PV market. Appraisers and real estate agents have made strides toward valuing PV homes, and several limited studies have suggested the presence of PV home premiums; however, gaps remain in understanding these premiums for housing markets nationwide. To fill these gaps, researchers from Lawrence Berkeley National Laboratory (LBNL) and their collaborators from other institutions conducted the most comprehensive PV home premium analysis to date. The study more than doubles the number of PV home sales previously analyzed, examines transactions in eight states, and spans the years 2002–2013. The results impart confidence that PV consistently adds value across a variety of states, housing and PV markets, and home types.

  4. Treatment of Uncertainty in Long-Term Planning 1 Introduction

    E-Print Network [OSTI]

    McCalley, James D.

    attribute to lie. For example, we could specify the price of natural gas in one of the following ways: #12 with time. #12;3 Figure 2: Specification of uncertainty in natural gas price Aside: We may also apply (maturation rate) Fuel costs forecast Demand forecast Plant retirement dates and salvage value Policy

  5. Managing Wind Power Forecast Uncertainty in Electric Brandon Keith Mauch

    E-Print Network [OSTI]

    i Managing Wind Power Forecast Uncertainty in Electric Grids Brandon Keith Mauch Co for the modeled wind- CAES system would not cover annualized capital costs. We also estimate market prices-ahead market is roughly $100, with large variability due to electric power prices. Wind power forecast errors

  6. Quasiparticle random phase approximation uncertainties and their correlations in the analysis of 0{nu}{beta}{beta} decay

    SciTech Connect (OSTI)

    Faessler, Amand; Rodin, V. [Institute of Theoretical Physics, University of Tuebingen, 72076 Tuebingen (Germany); Fogli, G. L.; Rotunno, A. M. [Dipartimento Interateneo di Fisica 'Michelangelo Merlin', Via Amendola 173, 70126 Bari (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Via Orabona 4, 70126 Bari (Italy); Lisi, E. [Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Via Orabona 4, 70126 Bari (Italy); Simkovic, F. [Institute of Theoretical Physics, University of Tuebingen, 72076 Tuebingen (Germany); Bogoliubov Laboratory of Theoretical Physics, JINR, 141980 Dubna (Russian Federation); Department of Nuclear Physics, Comenius University, Mlynska dolina F1, SK-842 15 Bratislava (Slovakia)

    2009-03-01T23:59:59.000Z

    The variances and covariances associated to the nuclear matrix elements of neutrinoless double beta decay (0{nu}{beta}{beta}) are estimated within the quasiparticle random phase approximation. It is shown that correlated nuclear matrix elements uncertainties play an important role in the comparison of 0{nu}{beta}{beta} decay rates for different nuclei, and that they are degenerate with the uncertainty in the reconstructed Majorana neutrino mass.

  7. INCORPORATING UNCERTAINTY INTO DAM SAFETY RISK Sanjay S. Chauhan1

    E-Print Network [OSTI]

    Chauhan, Sanjay S.

    on the topic of uncertainty in quantitative risk and policy analysis the reader is referred to Morgan to incorporating input uncertainties into risk analysis model. Input uncertainties are captured by using for uncertainty analysis in dam safety risk assessment, and demonstrates some useful formats for presenting

  8. Assessment of Uncertainty in Cloud Radiative Effects and Heating Rates through Retrieval Algorithm Differences: Analysis using 3-years of ARM data at Darwin, Australia

    SciTech Connect (OSTI)

    Comstock, Jennifer M.; Protat, Alain; McFarlane, Sally A.; Delanoe, Julien; Deng, Min

    2013-05-22T23:59:59.000Z

    Ground-based radar and lidar observations obtained at the Department of Energy’s Atmospheric Radiation Measurement Program’s Tropical Western Pacific site located in Darwin, Australia are used to retrieve ice cloud properties in anvil and cirrus clouds. Cloud microphysical properties derived from four different retrieval algorithms (two radar-lidar and two radar only algorithms) are compared by examining mean profiles and probability density functions of effective radius (Re), ice water content (IWC), extinction, ice number concentration, ice crystal fall speed, and vertical air velocity. Retrieval algorithm uncertainty is quantified using radiative flux closure exercises. The effect of uncertainty in retrieved quantities on the cloud radiative effect and radiative heating rates are presented. Our analysis shows that IWC compares well among algorithms, but Re shows significant discrepancies, which is attributed primarily to assumptions of particle shape. Uncertainty in Re and IWC translates into sometimes-large differences in cloud radiative effect (CRE) though the majority of cases have a CRE difference of roughly 10 W m-2 on average. These differences, which we believe are primarily driven by the uncertainty in Re, can cause up to 2 K/day difference in the radiative heating rates between algorithms.

  9. Real Time Pricing as a Default or Optional Service for C&ICustomers: A Comparative Analysis of Eight Case Studies

    SciTech Connect (OSTI)

    Barbose, Galen; Goldman, Charles; Bharvirkar, Ranjit; Hopper,Nicole; Ting, Michael; Neenan, Bernie

    2005-08-01T23:59:59.000Z

    Demand response (DR) has been broadly recognized to be an integral component of well-functioning electricity markets, although currently underdeveloped in most regions. Among the various initiatives undertaken to remedy this deficiency, public utility commissions (PUC) and utilities have considered implementing dynamic pricing tariffs, such as real-time pricing (RTP), and other retail pricing mechanisms that communicate an incentive for electricity consumers to reduce their usage during periods of high generation supply costs or system reliability contingencies. Efforts to introduce DR into retail electricity markets confront a range of basic policy issues. First, a fundamental issue in any market context is how to organize the process for developing and implementing DR mechanisms in a manner that facilitates productive participation by affected stakeholder groups. Second, in regions with retail choice, policymakers and stakeholders face the threshold question of whether it is appropriate for utilities to offer a range of dynamic pricing tariffs and DR programs, or just ''plain vanilla'' default service. Although positions on this issue may be based primarily on principle, two empirical questions may have some bearing--namely, what level of price response can be expected through the competitive retail market, and whether establishing RTP as the default service is likely to result in an appreciable level of DR? Third, if utilities are to have a direct role in developing DR, what types of retail pricing mechanisms are most appropriate and likely to have the desired policy impact (e.g., RTP, other dynamic pricing options, DR programs, or some combination)? Given a decision to develop utility RTP tariffs, three basic implementation issues require attention. First, should it be a default or optional tariff, and for which customer classes? Second, what types of tariff design is most appropriate, given prevailing policy objectives, wholesale market structure, ratemaking practices and standards, and customer preferences? Third, if a primary goal for RTP implementation is to induce DR, what types of supplemental activities are warranted to support customer participation and price response (e.g., interval metering deployment, customer education, and technical assistance)?

  10. MCNP6 Results for the Phase III Sensitivity Benchmark of the OCED/NEA Expert Group on Uncertainty Analysis for Criticality Safety Assessment

    SciTech Connect (OSTI)

    Kiedrowski, Brian C. [Los Alamos National Laboratory

    2012-06-19T23:59:59.000Z

    Within the last decade, there has been increasing interest in the calculation of cross section sensitivity coefficients of k{sub eff} for integral experiment design and uncertainty analysis. The OECD/NEA has an Expert Group devoted to Sensitivity and Uncertainty Analysis within the Working Party for Nuclear Criticality Safety. This expert group has developed benchmarks to assess code capabilities and performance for doing sensitivity and uncertainty analysis. Phase III of a set of sensitivity benchmarks evaluates capabilities for computing sensitivity coefficients. MCNP6 has the capability to compute cross section sensitivities for k{sub eff} using continuous-energy physics. To help verify this capability, results for the Phase III benchmark cases are generated and submitted to the Expert Group for comparison. The Phase III benchmark has three cases: III.1, an array of MOX fuel pins, III.2, a series of infinite lattices of MOX fuel pins with varying pitches, and III.3 two spheres with homogeneous mixtures of UF{sub 4} and polyethylene with different enrichments.

  11. Price controls and international petroleum product prices

    SciTech Connect (OSTI)

    Deacon, R.T.; Mead, W.J.; Agarwal, V.B.

    1980-02-01T23:59:59.000Z

    The effects of Federal refined-product price controls upon the price of motor gasoline in the United States through 1977 are examined. A comparison of domestic and foreign gasoline prices is made, based on the prices of products actually moving in international trade. There is also an effort to ascribe US/foreign market price differentials to identifiable cost factors. Primary emphasis is on price comparisons at the wholesale level, although some retail comparisons are presented. The study also examines the extent to which product price controls are binding, and attempts to estimate what the price of motor gasoline would have been in the absence of controls. The time period under consideration is from 1969 through 1977, with primary focus on price relationships in 1970-1971 (just before US controls) and 1976-1977. The foreign-domestic comparisons are made with respect to four major US cities, namely, Boston, New York, New Orleans, and Los Angeles. 20 figures, 14 tables.

  12. Uncertainty Measurement for Trace Element Analysis of Uranium and Plutonium Samples by Inductively Coupled Plasma-Atomic Emission Spectrometry (ICP-AES) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS)

    SciTech Connect (OSTI)

    Gallimore, David L. [Los Alamos National Laboratory

    2012-06-13T23:59:59.000Z

    The measurement uncertainty estimatino associated with trace element analysis of impurities in U and Pu was evaluated using the Guide to the Expression of Uncertainty Measurement (GUM). I this evalution the uncertainty sources were identified and standard uncertainties for the components were categorized as either Type A or B. The combined standard uncertainty was calculated and a coverage factor k = 2 was applied to obtain the expanded uncertainty, U. The ICP-AES and ICP-MS methods used were deveoped for the multi-element analysis of U and Pu samples. A typical analytical run consists of standards, process blanks, samples, matrix spiked samples, post digestion spiked samples and independent calibration verification standards. The uncertainty estimation was performed on U and Pu samples that have been analyzed previously as part of the U and Pu Sample Exchange Programs. Control chart results and data from the U and Pu metal exchange programs were combined with the GUM into a concentration dependent estimate of the expanded uncertainty. Comparison of trace element uncertainties obtained using this model was compared to those obtained for trace element results as part of the Exchange programs. This process was completed for all trace elements that were determined to be above the detection limit for the U and Pu samples.

  13. Analysis of ISO NE Balancing Requirements: Uncertainty-based Secure Ranges for ISO New England Dynamic Inerchange Adjustments

    SciTech Connect (OSTI)

    Etingov, Pavel V.; Makarov, Yuri V.; Wu, Di; Hou, Zhangshuan; Sun, Yannan; Maslennikov, S.; Luo, X.; Zheng, T.; George, S.; Knowland, T.; Litvinov, E.; Weaver, S.; Sanchez, E.

    2013-01-31T23:59:59.000Z

    The document describes detailed uncertainty quantification (UQ) methodology developed by PNNL to estimate secure ranges of potential dynamic intra-hour interchange adjustments in the ISO-NE system and provides description of the dynamic interchange adjustment (DINA) tool developed under the same contract. The overall system ramping up and down capability, spinning reserve requirements, interchange schedules, load variations and uncertainties from various sources that are relevant to the ISO-NE system are incorporated into the methodology and the tool. The DINA tool has been tested by PNNL and ISO-NE staff engineers using ISO-NE data.

  14. Energy Price Indices and Discount Factors for Life-Cycle Cost...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    0 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2010 Report describes the 2010 edition of energy price indices and discount factors for performing...

  15. DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, developers manual.

    SciTech Connect (OSTI)

    Eldred, Michael Scott; Dalbey, Keith R.; Bohnhoff, William J.; Adams, Brian M.; Swiler, Laura Painton; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gay, David M.; Eddy, John P.; Haskell, Karen H.

    2010-05-01T23:59:59.000Z

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a developers manual for the DAKOTA software and describes the DAKOTA class hierarchies and their interrelationships. It derives directly from annotation of the actual source code and provides detailed class documentation, including all member functions and attributes.

  16. DAKOTA, a multilevel parellel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis:version 4.0 uers's manual.

    SciTech Connect (OSTI)

    Griffin, Joshua D. (Sandai National Labs, Livermore, CA); Eldred, Michael Scott; Martinez-Canales, Monica L. (Sandai National Labs, Livermore, CA); Watson, Jean-Paul; Kolda, Tamara Gibson (Sandai National Labs, Livermore, CA); Giunta, Anthony Andrew; Adams, Brian M.; Swiler, Laura Painton; Williams, Pamela J. (Sandai National Labs, Livermore, CA); Hough, Patricia Diane (Sandai National Labs, Livermore, CA); Gay, David M.; Dunlavy, Daniel M.; Eddy, John P.; Hart, William Eugene; Brown, Shannon L.

    2006-10-01T23:59:59.000Z

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the DAKOTA software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

  17. Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis:version 4.0 developers manual.

    SciTech Connect (OSTI)

    Griffin, Joshua D. (Sandia National lababoratory, Livermore, CA); Eldred, Michael Scott; Martinez-Canales, Monica L. (Sandia National lababoratory, Livermore, CA); Watson, Jean-Paul; Kolda, Tamara Gibson (Sandia National lababoratory, Livermore, CA); Giunta, Anthony Andrew; Adams, Brian M.; Swiler, Laura Painton; Williams, Pamela J. (Sandia National lababoratory, Livermore, CA); Hough, Patricia Diane (Sandia National lababoratory, Livermore, CA); Gay, David M.; Dunlavy, Daniel M.; Eddy, John P.; Hart, William Eugene; Brown, Shannon L.

    2006-10-01T23:59:59.000Z

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a developers manual for the DAKOTA software and describes the DAKOTA class hierarchies and their interrelationships. It derives directly from annotation of the actual source code and provides detailed class documentation, including all member functions and attributes.

  18. DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual.

    SciTech Connect (OSTI)

    Eldred, Michael Scott; Dalbey, Keith R.; Bohnhoff, William J.; Adams, Brian M.; Swiler, Laura Painton; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gay, David M.; Eddy, John P.; Haskell, Karen H.

    2010-05-01T23:59:59.000Z

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the DAKOTA software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

  19. State energy price and expenditure report 1993

    SciTech Connect (OSTI)

    NONE

    1995-12-01T23:59:59.000Z

    The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 states and the District of Columbia and in aggregate for the US. The five economic sectors used in SEPER correspond to those used in SEDR and are residential, commercial, industrial, transportation, and electric utility. Documentation in appendices describe how the price estimates are developed, provide conversion factors for measures used in the energy analysis, and include a glossary. 65 tabs.

  20. Enhance accuracy in Software cost and schedule estimation by using "Uncertainty Analysis and Assessment" in the system modeling process

    E-Print Network [OSTI]

    Vasantrao, Kardile Vilas

    2011-01-01T23:59:59.000Z

    Accurate software cost and schedule estimation are essential for software project success. Often it referred to as the "black art" because of its complexity and uncertainty, software estimation is not as difficult or puzzling as people think. In fact, generating accurate estimates is straightforward-once you understand the intensity of uncertainty and framework for the modeling process. The mystery to successful software estimation-distilling academic information and real-world experience into a practical guide for working software professionals. Instead of arcane treatises and rigid modeling techniques, this will guide highlights a proven set of procedures, understandable formulas, and heuristics that individuals and development teams can apply to their projects to help achieve estimation proficiency with choose appropriate development approaches In the early stage of software life cycle project manager are inefficient to estimate the effort, schedule, cost estimation and its development approach .This in tu...

  1. Volatility of Power Grids Under Real-Time Pricing

    E-Print Network [OSTI]

    Roozbehani, Mardavij

    The paper proposes a framework for modeling and analysis of the dynamics of supply, demand, and clearing prices in power systems with real-time retail pricing and information asymmetry. Characterized by passing on the ...

  2. Quantifying uncertainty in LCA-modelling of waste management systems

    SciTech Connect (OSTI)

    Clavreul, Julie, E-mail: julc@env.dtu.dk [Department of Environmental Engineering, Technical University of Denmark, Miljoevej, Building 113, DK-2800 Kongens Lyngby (Denmark); Guyonnet, Dominique [BRGM, ENAG BRGM-School, BP 6009, 3 Avenue C. Guillemin, 45060 Orleans Cedex (France); Christensen, Thomas H. [Department of Environmental Engineering, Technical University of Denmark, Miljoevej, Building 113, DK-2800 Kongens Lyngby (Denmark)

    2012-12-15T23:59:59.000Z

    Highlights: Black-Right-Pointing-Pointer Uncertainty in LCA-modelling of waste management is significant. Black-Right-Pointing-Pointer Model, scenario and parameter uncertainties contribute. Black-Right-Pointing-Pointer Sequential procedure for quantifying uncertainty is proposed. Black-Right-Pointing-Pointer Application of procedure is illustrated by a case-study. - Abstract: Uncertainty analysis in LCA studies has been subject to major progress over the last years. In the context of waste management, various methods have been implemented but a systematic method for uncertainty analysis of waste-LCA studies is lacking. The objective of this paper is (1) to present the sources of uncertainty specifically inherent to waste-LCA studies, (2) to select and apply several methods for uncertainty analysis and (3) to develop a general framework for quantitative uncertainty assessment of LCA of waste management systems. The suggested method is a sequence of four steps combining the selected methods: (Step 1) a sensitivity analysis evaluating the sensitivities of the results with respect to the input uncertainties, (Step 2) an uncertainty propagation providing appropriate tools for representing uncertainties and calculating the overall uncertainty of the model results, (Step 3) an uncertainty contribution analysis quantifying the contribution of each parameter uncertainty to the final uncertainty and (Step 4) as a new approach, a combined sensitivity analysis providing a visualisation of the shift in the ranking of different options due to variations of selected key parameters. This tiered approach optimises the resources available to LCA practitioners by only propagating the most influential uncertainties.

  3. Understanding Crude Oil Prices

    E-Print Network [OSTI]

    Hamilton, James Douglas

    2008-01-01T23:59:59.000Z

    EIA, World Petroleum Consumption) times the average price of West Texas Intermediate (from the FRED database

  4. Understanding Crude Oil Prices

    E-Print Network [OSTI]

    Hamilton, James Douglas

    2008-01-01T23:59:59.000Z

    consumption would be reduced and incentives for production increased whenever the price of crude oil

  5. Fuel Price Forecasts INTRODUCTION

    E-Print Network [OSTI]

    Fuel Price Forecasts INTRODUCTION Fuel prices affect electricity planning in two primary ways and water heating, and other end-uses as well. Fuel prices also influence electricity supply and price because oil, coal, and natural gas are potential fuels for electricity generation. Natural gas

  6. Large-Scale Uncertainty and Error Analysis for Time-dependent Fluid/Structure Interactions in Wind Turbine Applications

    SciTech Connect (OSTI)

    Alonso, Juan J. [Stanford University; Iaccarino, Gianluca [Stanford University

    2013-08-25T23:59:59.000Z

    The following is the final report covering the entire period of this aforementioned grant, June 1, 2011 - May 31, 2013 for the portion of the effort corresponding to Stanford University (SU). SU has partnered with Sandia National Laboratories (PI: Mike S. Eldred) and Purdue University (PI: Dongbin Xiu) to complete this research project and this final report includes those contributions made by the members of the team at Stanford. Dr. Eldred is continuing his contributions to this project under a no-cost extension and his contributions to the overall effort will be detailed at a later time (once his effort has concluded) on a separate project submitted by Sandia National Laboratories. At Stanford, the team is made up of Profs. Alonso, Iaccarino, and Duraisamy, post-doctoral researcher Vinod Lakshminarayan, and graduate student Santiago Padron. At Sandia National Laboratories, the team includes Michael Eldred, Matt Barone, John Jakeman, and Stefan Domino, and at Purdue University, we have Prof. Dongbin Xiu as our main collaborator. The overall objective of this project was to develop a novel, comprehensive methodology for uncertainty quantification by combining stochastic expansions (nonintrusive polynomial chaos and stochastic collocation), the adjoint approach, and fusion with experimental data to account for aleatory and epistemic uncertainties from random variable, random field, and model form sources. The expected outcomes of this activity were detailed in the proposal and are repeated here to set the stage for the results that we have generated during the time period of execution of this project: 1. The rigorous determination of an error budget comprising numerical errors in physical space and statistical errors in stochastic space and its use for optimal allocation of resources; 2. A considerable increase in efficiency when performing uncertainty quantification with a large number of uncertain variables in complex non-linear multi-physics problems; 3. A solution to the long-time integration problem of spectral chaos approaches; 4. A rigorous methodology to account for aleatory and epistemic uncertainties, to emphasize the most important variables via dimension reduction and dimension-adaptive refinement, and to support fusion with experimental data using Bayesian inference; 5. The application of novel methodologies to time-dependent reliability studies in wind turbine applications including a number of efforts relating to the uncertainty quantification in vertical-axis wind turbine applications. In this report, we summarize all accomplishments in the project (during the time period specified) focusing on advances in UQ algorithms and deployment efforts to the wind turbine application area. Detailed publications in each of these areas have also been completed and are available from the respective conference proceedings and journals as detailed in a later section.

  7. The Growing Price Gap between More and Less Healthy Foods: Analysis of a Novel Longitudinal UK Dataset

    E-Print Network [OSTI]

    Jones, Nicholas R. V.; Conklin, Annalijn I.; Suhrcke, Marc; Monsivais, Pablo

    2014-10-08T23:59:59.000Z

    in the rate of change in the price of food groups. [14] We further excluded an additional four items in the basket as they contained no nutrients meaningful to the research questions (Instant Coffee, Filter Coffee, Tea Bags, Bottled Mineral Water), leaving a... by the DH to define a healthy diet. [3] The five groups analysed were: (i) bread, rice potatoes and pasta; (ii) fruit and vegetables; (iii) milk and dairy foods; (iv) meat, fish, eggs, beans and other sources of protein; and (v) food and drinks high in fat...

  8. Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-01-01T23:59:59.000Z

    Associates, citing NYMEX natural gas bid-offer spreadAnalysis of the Market for Natural Gas Futures. ” The Energyas a Physical Hedge Against Natural Gas Price Movements. ”

  9. Edgeworth Price Cycles, Cost-based Pricing and Sticky Pricing in Retail Gasoline Markets

    E-Print Network [OSTI]

    Noel, Michael

    2004-01-01T23:59:59.000Z

    Johnson. “Gas Wars: Retail Gasoline Price Fluctua- tions”,were collected on retail gasoline prices, wholesale (rack)ancillary information. Retail gasoline prices, RET AIL mt ,

  10. COORDINATING ON LOWER PRICES: PHARMACEUTICAL PRICING

    E-Print Network [OSTI]

    Sadoulet, Elisabeth

    of political activity on pharmaceutical prices, focusing on the health care reform period. We characterize health care reform discussions in 1993, large-scale efforts to curb drug prices were debated and seemed everywhere from the Catastrophic Health Insurance Bill to proposals for Medicare coverage of drugs. During

  11. Achieving Robustness to Uncertainty for Financial Decision-making

    SciTech Connect (OSTI)

    Barnum, George M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Van Buren, Kendra L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hemez, Francois M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Song, Peter [Univ. of Pennsylvania, Philadelphia, PA (United States)

    2014-01-10T23:59:59.000Z

    This report investigates the concept of robustness analysis to support financial decision-making. Financial models, that forecast future stock returns or market conditions, depend on assumptions that might be unwarranted and variables that might exhibit large fluctuations from their last-known values. The analysis of robustness explores these sources of uncertainty, and recommends model settings such that the forecasts used for decision-making are as insensitive as possible to the uncertainty. A proof-of-concept is presented with the Capital Asset Pricing Model. The robustness of model predictions is assessed using info-gap decision theory. Info-gaps are models of uncertainty that express the “distance,” or gap of information, between what is known and what needs to be known in order to support the decision. The analysis yields a description of worst-case stock returns as a function of increasing gaps in our knowledge. The analyst can then decide on the best course of action by trading-off worst-case performance with “risk”, which is how much uncertainty they think needs to be accommodated in the future. The report also discusses the Graphical User Interface, developed using the MATLAB® programming environment, such that the user can control the analysis through an easy-to-navigate interface. Three directions of future work are identified to enhance the present software. First, the code should be re-written using the Python scientific programming software. This change will achieve greater cross-platform compatibility, better portability, allow for a more professional appearance, and render it independent from a commercial license, which MATLAB® requires. Second, a capability should be developed to allow users to quickly implement and analyze their own models. This will facilitate application of the software to the evaluation of proprietary financial models. The third enhancement proposed is to add the ability to evaluate multiple models simultaneously. When two models reflect past data with similar accuracy, the more robust of the two is preferable for decision-making because its predictions are, by definition, less sensitive to the uncertainty.

  12. Utility spot pricing study : Wisconsin

    E-Print Network [OSTI]

    Caramanis, Michael C.

    1982-01-01T23:59:59.000Z

    Spot pricing covers a range of electric utility pricing structures which relate the marginal costs of electric generation to the prices seen by utility customers. At the shortest time frames prices change every five ...

  13. Grid Pricing of Fed Cattle

    E-Print Network [OSTI]

    Schroeder, Ted C.; Hogan, Robert J.; Anderson, David P.

    2009-03-02T23:59:59.000Z

    There are several value-based fed cattle pricing systems, including formula pricing, price grids and alliances. This publication describes the different cattle pricing methods and helps you decide which is best for you....

  14. STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES 2005 TO 2018 Mignon Marks Principal Author Mignon Marks Project Manager David Ashuckian Manager ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY DIVISION B.B. Blevins Executive Director

  15. Contractual form, retail price and asset characteristics

    E-Print Network [OSTI]

    Shepard, Andrea

    1991-01-01T23:59:59.000Z

    Predictions derived from a principal-agent analysis of the manufacturer-retailer relationship are derived and tested using microdata on contractual form, outlet characteristics and retail prices for gasoline stations in ...

  16. CANNED FISH RETAIL PRICES

    E-Print Network [OSTI]

    RETAIL PRICES CONTENTS Page Tuna, Canned White Meat Tuna. (Albacore), Solid Pack, In Oil All BrandsCANNED FISH RETAIL PRICES UNITED STATES DEPARTMENT OF THE INTERIOR FISH AND WILDLIFE SERVICE BUREAU PRICES APRIL 1959 Prepared in the Bureau of Commercial Fisheries Branch of Market Development FISHERY

  17. CANNED FISH RETAIL PRICES

    E-Print Network [OSTI]

    PRICES CONTENTS Page Tuna, Canned White Meat Tuna (Albacore), Solid Pack, In Oil All Brands ExceptCANNED FISH RETAIL PRICES JUNE ll959 UNITED STATES DEPARTMENT OF THE INTERIOR FISH AND WILDUFE, Commissioner CANNED FISH RETAIL PRICES JUNE 1959 Prepared in the Bureau of Commercial Fisheries Branch

  18. Uncertainty and Sensitivity Analyses Plan

    SciTech Connect (OSTI)

    Simpson, J.C.; Ramsdell, J.V. Jr.

    1993-04-01T23:59:59.000Z

    Hanford Environmental Dose Reconstruction (HEDR) Project staff are developing mathematical models to be used to estimate the radiation dose that individuals may have received as a result of emissions since 1944 from the US Department of Energy's (DOE) Hanford Site near Richland, Washington. An uncertainty and sensitivity analyses plan is essential to understand and interpret the predictions from these mathematical models. This is especially true in the case of the HEDR models where the values of many parameters are unknown. This plan gives a thorough documentation of the uncertainty and hierarchical sensitivity analysis methods recommended for use on all HEDR mathematical models. The documentation includes both technical definitions and examples. In addition, an extensive demonstration of the uncertainty and sensitivity analysis process is provided using actual results from the Hanford Environmental Dose Reconstruction Integrated Codes (HEDRIC). This demonstration shows how the approaches used in the recommended plan can be adapted for all dose predictions in the HEDR Project.

  19. Strategic investment in power generation under uncertainty : Electric Reliability Council of Texas

    E-Print Network [OSTI]

    Chiyangwa, Diana Kudakwashe

    2010-01-01T23:59:59.000Z

    The purpose of this study is to develop a strategy for investment in power generation technologies in the future given the uncertainties in climate policy and fuel prices. First, such studies are commonly conducted using ...

  20. SIMULATION MODEL ANALYSIS OF THE MOST PROMISING GEOLOGIC SEQUESTRATION FORMATION CANDIDATES IN THE ROCKY MOUNTAIN REGION, USA, WITH FOCUS ON UNCERTAINTY ASSESSMENT

    SciTech Connect (OSTI)

    Lee, Si-Yong; Zaluski, Wade; Will, Robert; Eisinger, Chris; Matthews, Vince; McPherson, Brian

    2013-09-01T23:59:59.000Z

    The purpose of this report is to report results of reservoir model simulation analyses for forecasting subsurface CO2 storage capacity estimation for the most promising formations in the Rocky Mountain region of the USA. A particular emphasis of this project was to assess uncertainty of the simulation-based forecasts. Results illustrate how local-scale data, including well information, number of wells, and location of wells, affect storage capacity estimates and what degree of well density (number of wells over a fixed area) may be required to estimate capacity within a specified degree of confidence. A major outcome of this work was development of a new workflow of simulation analysis, accommodating the addition of “random pseudo wells” to represent virtual characterization wells.

  1. Programmatic methods for addressing contaminated volume uncertainties.

    SciTech Connect (OSTI)

    DURHAM, L.A.; JOHNSON, R.L.; RIEMAN, C.R.; SPECTOR, H.L.; Environmental Science Division; U.S. ARMY CORPS OF ENGINEERS BUFFALO DISTRICT

    2007-01-01T23:59:59.000Z

    Accurate estimates of the volumes of contaminated soils or sediments are critical to effective program planning and to successfully designing and implementing remedial actions. Unfortunately, data available to support the preremedial design are often sparse and insufficient for accurately estimating contaminated soil volumes, resulting in significant uncertainty associated with these volume estimates. The uncertainty in the soil volume estimates significantly contributes to the uncertainty in the overall project cost estimates, especially since excavation and off-site disposal are the primary cost items in soil remedial action projects. The Army Corps of Engineers Buffalo District's experience has been that historical contaminated soil volume estimates developed under the Formerly Utilized Sites Remedial Action Program (FUSRAP) often underestimated the actual volume of subsurface contaminated soils requiring excavation during the course of a remedial activity. In response, the Buffalo District has adopted a variety of programmatic methods for addressing contaminated volume uncertainties. These include developing final status survey protocols prior to remedial design, explicitly estimating the uncertainty associated with volume estimates, investing in predesign data collection to reduce volume uncertainties, and incorporating dynamic work strategies and real-time analytics in predesign characterization and remediation activities. This paper describes some of these experiences in greater detail, drawing from the knowledge gained at Ashland1, Ashland2, Linde, and Rattlesnake Creek. In the case of Rattlesnake Creek, these approaches provided the Buffalo District with an accurate predesign contaminated volume estimate and resulted in one of the first successful FUSRAP fixed-price remediation contracts for the Buffalo District.

  2. Price Discovery in the Natural Gas Markets of the United States and Canada

    E-Print Network [OSTI]

    Olsen, Kyle

    2011-02-22T23:59:59.000Z

    .S. Midwest and Northeast, but little to markets in the west. The uncertainty of a markets’ price depends primarily on markets located in nearby regions. Policy makers may use information on market integration for important policy matters in efforts...

  3. The Appraisal Journal, Price Effects of High Voltage Transmission...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    data was sufficient to derive precise market price equations via multiple linear regression analysis for both Portland and Seattle. In addition, due to where the rights of way...

  4. Residential implementation of critical-peak pricing of electricity

    E-Print Network [OSTI]

    Herter, Karen

    2006-01-01T23:59:59.000Z

    L.R. Modeling alternative residential peak-load electricitydemand response to residential critical peak pricing (CPP)analysis of California residential customer response to

  5. Optimization Online - Convex Hull Pricing in Electricity Markets ...

    E-Print Network [OSTI]

    Dane Schiro

    2015-03-19T23:59:59.000Z

    Mar 19, 2015 ... Convex Hull Pricing in Electricity Markets: Formulation, Analysis, and Implementation Challenges. Dane Schiro (dschiro ***at*** iso-ne.com)

  6. Planning for future uncertainties in electric power generation : an analysis of transitional strategies for reduction of carbon and sulfur emissions

    E-Print Network [OSTI]

    Tabors, Richard D.

    1991-01-01T23:59:59.000Z

    The object of this paper is to identify strategies for the U.S. electric utility industry for reduction of both acid rain producing and global warming gases. The research used the EPRI Electric Generation Expansion Analysis ...

  7. Flexible design of commercial systems under market uncertainty: framework and application

    E-Print Network [OSTI]

    de Weck, Olivier L.

    Flexible design of commercial systems under market uncertainty: framework and application to respond to changing market conditions. The basic premise is that commercial systems optimization aims price of oil, demand for a particular product, or technological innovations that affect the price

  8. The Effect of Uncertainty on Pollution Abatement Investments: Measuring Hurdle Rates for Swedish Industry

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    ex post data. The method is based on a structural option value model where the future price, oil price uncertainty, abatement investment, sulfur emissions, pulp and paper industry, energy in the measurement of costs, heterogeneity in discount rates or, still, market failures (see for example Hausman

  9. IEEE TRANSACTIONS ON POWER SYSTEMS, CHEN, DENG AND HUO. 1 Electricity Price Curve Modeling by Manifold

    E-Print Network [OSTI]

    markets. Index Terms-- Electricity spot price, locational marginal price, electricity forward curveIEEE TRANSACTIONS ON POWER SYSTEMS, CHEN, DENG AND HUO. 1 Electricity Price Curve Modeling and prediction of electricity price curves by applying the manifold learning methodology. Cluster analysis based

  10. IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 23, NO. 3, AUGUST 2008 877 Electricity Price Curve Modeling

    E-Print Network [OSTI]

    Huo, Xiaoming

    --Electricity forward curve, electricity spot price, forecasting, locational marginal price, manifold learning. IIEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 23, NO. 3, AUGUST 2008 877 Electricity Price Curve approach for the modeling and analysis of electricity price curves by ap- plying the manifold learning

  11. Energy Price Indices and Discount Factors for Life-Cycle Cost...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis-2014 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis-2014 Handbook describes the...

  12. Direct Aerosol Forcing Uncertainty

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Mccomiskey, Allison

    Understanding sources of uncertainty in aerosol direct radiative forcing (DRF), the difference in a given radiative flux component with and without aerosol, is essential to quantifying changes in Earth's radiation budget. We examine the uncertainty in DRF due to measurement uncertainty in the quantities on which it depends: aerosol optical depth, single scattering albedo, asymmetry parameter, solar geometry, and surface albedo. Direct radiative forcing at the top of the atmosphere and at the surface as well as sensitivities, the changes in DRF in response to unit changes in individual aerosol or surface properties, are calculated at three locations representing distinct aerosol types and radiative environments. The uncertainty in DRF associated with a given property is computed as the product of the sensitivity and typical measurement uncertainty in the respective aerosol or surface property. Sensitivity and uncertainty values permit estimation of total uncertainty in calculated DRF and identification of properties that most limit accuracy in estimating forcing. Total uncertainties in modeled local diurnally averaged forcing range from 0.2 to 1.3 W m-2 (42 to 20%) depending on location (from tropical to polar sites), solar zenith angle, surface reflectance, aerosol type, and aerosol optical depth. The largest contributor to total uncertainty in DRF is usually single scattering albedo; however decreasing measurement uncertainties for any property would increase accuracy in DRF. Comparison of two radiative transfer models suggests the contribution of modeling error is small compared to the total uncertainty although comparable to uncertainty arising from some individual properties.

  13. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01T23:59:59.000Z

    of the Global Crude Oil Market and the U.S. Retail Gasolinea¤ect the world crude oil market (though of course this maythe integration of the world oil market rescues the original

  14. Microsoft Word - feb10-Price Uncertainty Supplement.doc

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400,Information Administration2 U.S.and Winter, 19989,3,1,February

  15. Microsoft Word - Documentation - Price Forecast Uncertainty.doc

    U.S. Energy Information Administration (EIA) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14 Jan-15LiquidBG NorthandEnergyConti,09GE

  16. Automobile Prices, Gasoline Prices, and Consumer Demand for Fuel Economy

    E-Print Network [OSTI]

    Sadoulet, Elisabeth

    2008 Abstract The relationship between gasoline prices and the demand for vehicle fuel efficiencyAutomobile Prices, Gasoline Prices, and Consumer Demand for Fuel Economy Ashley Langer University evidence that automobile manufacturers set vehicle prices as if consumers respond to gasoline prices. We

  17. Price changes in the gasoline market: Are Midwestern gasoline prices downward sticky?

    SciTech Connect (OSTI)

    NONE

    1999-03-01T23:59:59.000Z

    This report examines a recurring question about gasoline markets: why, especially in times of high price volatility, do retail gasoline prices seem to rise quickly but fall back more slowly? Do gasoline prices actually rise faster than they fall, or does this just appear to be the case because people tend to pay more attention to prices when they`re rising? This question is more complex than it might appear to be initially, and it has been addressed by numerous analysts in government, academia and industry. The question is very important, because perceived problems with retail gasoline pricing have been used in arguments for government regulation of prices. The phenomenon of prices at different market levels tending to move differently relative to each other depending on direction is known as price asymmetry. This report summarizes the previous work on gasoline price asymmetry and provides a method for testing for asymmetry in a wide variety of situations. The major finding of this paper is that there is some amount of asymmetry and pattern asymmetry, especially at the retail level, in the Midwestern states that are the focus of the analysis. Nevertheless, both the amount asymmetry and pattern asymmetry are relatively small. In addition, much of the pattern asymmetry detected in this and previous studies could be a statistical artifact caused by the time lags between price changes at different points in the gasoline distribution system. In other words, retail gasoline prices do sometimes rise faster than they fall, but this is largely a lagged market response to an upward shock in the underlying wholesale gasoline or crude oil prices, followed by a return toward the previous baseline. After consistent time lags are factored out, most apparent asymmetry disappears.

  18. Evaluation of the Repeatability of the Delta Q Duct Leakage Testing Technique Including Investigation of Robust Analysis Techniques and Estimates of Weather Induced Uncertainty

    E-Print Network [OSTI]

    Dickerhoff, Darryl

    2008-01-01T23:59:59.000Z

    Techniques and Estimates of Weather Induced Uncertaintythe uncertainty due to changing weather during the test (the DeltaQ test are influenced by weather induced pressures.

  19. Uncertainties in Gapped Graphene

    E-Print Network [OSTI]

    Eylee Jung; Kwang S. Kim; DaeKil Park

    2012-03-20T23:59:59.000Z

    Motivated by graphene-based quantum computer we examine the time-dependence of the position-momentum and position-velocity uncertainties in the monolayer gapped graphene. The effect of the energy gap to the uncertainties is shown to appear via the Compton-like wavelength $\\lambda_c$. The uncertainties in the graphene are mainly contributed by two phenomena, spreading and zitterbewegung. While the former determines the uncertainties in the long-range of time, the latter gives the highly oscillation to the uncertainties in the short-range of time. The uncertainties in the graphene are compared with the corresponding values for the usual free Hamiltonian $\\hat{H}_{free} = (p_1^2 + p_2^2) / 2 M$. It is shown that the uncertainties can be under control within the quantum mechanical law if one can choose the gap parameter $\\lambda_c$ freely.

  20. Price-elastic demand in deregulated electricity markets

    SciTech Connect (OSTI)

    Siddiqui, Afzal S.

    2003-05-01T23:59:59.000Z

    The degree to which any deregulated market functions efficiently often depends on the ability of market agents to respond quickly to fluctuating conditions. Many restructured electricity markets, however, experience high prices caused by supply shortages and little demand-side response. We examine the implications for market operations when a risk-averse retailer's end-use consumers are allowed to perceive real-time variations in the electricity spot price. Using a market-equilibrium model, we find that price elasticity both increases the retailers revenue risk exposure and decreases the spot price. Since the latter induces the retailer to reduce forward electricity purchases, while the former has the opposite effect, the overall impact of price responsive demand on the relative magnitudes of its risk exposure and end-user price elasticity. Nevertheless, price elasticity decreases cumulative electricity consumption. By extending the analysis to allow for early settlement of demand, we find that forward stage end-user price responsiveness decreases the electricity forward price relative to the case with price-elastic demand only in real time. Moreover, we find that only if forward stage end-user demand is price elastic will the equilibrium electricity forward price be reduced.

  1. Crude Oil Prices

    U.S. Energy Information Administration (EIA) Indexed Site

    the acquisition date. See the Explanatory Notes section for additional detail. Sources: Energy Information Administration, Form FEA-F701-M-0, "Transfer Pricing Report," January...

  2. Livestock Seasonal Price Variation

    E-Print Network [OSTI]

    Davis, Ernest E.; Sartwelle III, James D.; Mintert, James R.

    1999-09-21T23:59:59.000Z

    that number by the index of the future month for which the price forecast is being determined. For example, if June Amarillo direct fed cattle prices averaged $64 per hun- dredweight (cwt.), the forecast for October would be $64 divided by 97.12, multiplied... by 99.04 = $65.27 per cwt. Adjusting for the vari- ability suggests that there is a 68 percent proba- bility that the October monthly average price would fall between $70.67 cwt. and $59.87 cwt. Seasonal Price Index for Amarillo Direct Fed Steers...

  3. Understanding Crude Oil Prices

    E-Print Network [OSTI]

    Hamilton, James Douglas

    2008-01-01T23:59:59.000Z

    historical data for claiming to be able to predict oil pricehistorical data. The second is to look at the predictions of economic theory as to how oil prices

  4. RUMINATIONS ON NDA MEASUREMENT UNCERTAINTY COMPARED TO DA UNCERTAINTY

    SciTech Connect (OSTI)

    Salaymeh, S.; Ashley, W.; Jeffcoat, R.

    2010-06-17T23:59:59.000Z

    It is difficult to overestimate the importance that physical measurements performed with nondestructive assay instruments play throughout the nuclear fuel cycle. They underpin decision making in many areas and support: criticality safety, radiation protection, process control, safeguards, facility compliance, and waste measurements. No physical measurement is complete or indeed meaningful, without a defensible and appropriate accompanying statement of uncertainties and how they combine to define the confidence in the results. The uncertainty budget should also be broken down in sufficient detail suitable for subsequent uses to which the nondestructive assay (NDA) results will be applied. Creating an uncertainty budget and estimating the total measurement uncertainty can often be an involved process, especially for non routine situations. This is because data interpretation often involves complex algorithms and logic combined in a highly intertwined way. The methods often call on a multitude of input data subject to human oversight. These characteristics can be confusing and pose a barrier to developing and understanding between experts and data consumers. ASTM subcommittee C26-10 recognized this problem in the context of how to summarize and express precision and bias performance across the range of standards and guides it maintains. In order to create a unified approach consistent with modern practice and embracing the continuous improvement philosophy a consensus arose to prepare a procedure covering the estimation and reporting of uncertainties in non destructive assay of nuclear materials. This paper outlines the needs analysis, objectives and on-going development efforts. In addition to emphasizing some of the unique challenges and opportunities facing the NDA community we hope this article will encourage dialog and sharing of best practice and furthermore motivate developers to revisit the treatment of measurement uncertainty.

  5. Variation and Uncertainty in Evaporation from a Subtropical Estuary: Florida Bay

    E-Print Network [OSTI]

    Miami, University of

    Variation and Uncertainty in Evaporation from a Subtropical Estuary: Florida Bay RENE´ M. PRICE1 both vapor flux and energy budget methods. The results were placed into a long-term context using 33 the overall uncertainty in monthly evaporation, and ranged from 9% to 26%. Over a 33-yr period (1970

  6. Multifidelity methods for multidisciplinary design under uncertainty

    E-Print Network [OSTI]

    Christensen, Daniel Erik

    2012-01-01T23:59:59.000Z

    For computational design and analysis tasks, scientists and engineers often have available many different simulation models. The output of each model has an associated uncertainty that is a result of the modeling process. ...

  7. Pricing to Accelerate Demand Learning in Dynamic Assortment ...

    E-Print Network [OSTI]

    2013-03-16T23:59:59.000Z

    are made. In practice, a substantial amount of uncertainty about the demand process is ... sales. Note that there is full information about price-response function and, as a result, the .... To the best of our knowledge, we are the first to consider ...

  8. Carbon capture retrofits and the cost of regulatory uncertainty

    SciTech Connect (OSTI)

    Reinelt, P.S.; Keith, D.W. [SUNY College of Fredonia, Fredonia, NY (United States). Dept. of Economics

    2007-07-01T23:59:59.000Z

    Power generation firms confront impending replacement of an aging coal-fired fleet in a business environment characterized by volatile natural gas prices and uncertain carbon regulation. We develop a stochastic dynamic programming model of firm investment decisions that minimizes the expected present value of future power generation costs under uncertain natural gas and carbon prices. We explore the implications of regulatory uncertainty on generation technology choice and the optimal timing of investment, and assess the implications of these choices for regulators. We find that interaction of regulatory uncertainty with irreversible investment always raises the social cost of carbon abatement. Further, the social cost of regulatory uncertainty is strongly dependent on the relative competitiveness of IGCC plants, for which the cost of later carbon capture retrofits is comparatively small, and on the firm's ability to use investments in natural gas generation as a transitional strategy to manage carbon regulation uncertainty. Without highly competitive IGCC or low gas prices, regulatory uncertainty can increase the expected social cost of reducing emissions by 40 to 60%.

  9. Techno-Economic Analysis of PEV Battery Second Use: Repurposed-Battery Selling Price and Commercial and Industrial End-User Value

    SciTech Connect (OSTI)

    Neubauer, J.; Pesaran, A.; Williams, B.; Ferry, M.; Eyer, J.

    2012-06-01T23:59:59.000Z

    Accelerated market penetration of plug-in electric vehicles and deployment of grid-connected energy storage are restricted by the high cost of lithium-ion batteries. Research, development, and manufacturing are underway to lower material costs, enhance process efficiencies, and increase production volumes. A fraction of the battery cost may be recovered after vehicular service by reusing the battery where it may have sufficient performance for other energy-storage applications. By extracting post-vehicle additional services and revenue from the battery, the total lifetime value of the battery is increased. The overall cost of energy-storage solutions for both primary (automotive) and secondary (grid) customer could be decreased. This techno-economic analysis of battery second use considers effects of battery degradation in both automotive and grid service, repurposing costs, balance-of-system costs, the value of aggregated energy-storage to commercial and industrial end users, and competitive technology. Batteries from plug-in electric vehicles can economically be used to serve the power quality and reliability needs of commercial and industrial end users. However, the value to the automotive battery owner is small (e.g., $20-$100/kWh) as declining future battery costs and other factors strongly affect salvage value. Repurposed automotive battery prices may range from $38/kWh to $132/kWh.

  10. Scaling analysis of time series of daily prices from stock markets of transitional economies in the Western Balkans

    E-Print Network [OSTI]

    Savran, Darko; Blesic, Suzana; Miljkovic, Vladimir

    2014-01-01T23:59:59.000Z

    In this paper we have analyzed scaling properties of time series of stock market indices (SMIs) of developing economies of Western Balkans, and have compared the results we have obtained with the results from more developed economies. We have used three different techniques of data analysis to obtain and verify our findings: Detrended Fluctuation Analysis (DFA) method, Detrended Moving Average (DMA) method, and Wavelet Transformation (WT) analysis. We have found scaling behavior in all SMI data sets that we have analyzed. The scaling of our SMI series changes from long-range correlated to slightly anti-correlated behavior with the change in growth or maturity of the economy the stock market is embedded in. We also report the presence of effects of potential periodic-like influences on the SMI data that we have analyzed. One such influence is visible in all our SMI series, and appears at a period $T_{p}\\approx 90$ days. We propose that the existence of various periodic-like influences on SMI data may partially...

  11. Revised 1997 Retail Electricity Price Forecast Principal Author: Ben Arikawa

    E-Print Network [OSTI]

    Revised 1997 Retail Electricity Price Forecast March 1998 Principal Author: Ben Arikawa Electricity 1997 FORE08.DOC Page 1 CALIFORNIA ENERGY COMMISSION ELECTRICITY ANALYSIS OFFICE REVISED 1997 RETAIL ELECTRICITY PRICE FORECAST Introduction The Electricity Analysis Office of the California Energy Commission

  12. The Minimum Price Contract

    E-Print Network [OSTI]

    Waller, Mark L.; Amosson, Stephen H.; Welch, Mark; Dhuyvetter, Kevin C.

    2008-10-17T23:59:59.000Z

    , he can Mark Waller, Steve Amosson, Mark Welch, and Kevin Dhuyvetter* 2 lock in a floor price and still have upside poten- tial if the market rallies. Options-based marketing strategies, such as the minimum price contract, work well in times...

  13. Utility spot pricing, California

    E-Print Network [OSTI]

    Schweppe, Fred C.

    1982-01-01T23:59:59.000Z

    The objective of the present spot pricing study carried out for SCE and PG&E is to develop the concepts which wculd lead to an experimental design for spot pricing in the two utilities. The report suggests a set of experiments ...

  14. Energy Prices and California's Economic

    E-Print Network [OSTI]

    Sadoulet, Elisabeth

    1 Energy Prices and California's Economic Security David RolandHolst October, 2009 on Energy Prices, Renewables, Efficiency, and Economic Growth: Scenarios and Forecasts, financial support drivers, the course of fossil fuel energy prices, energy efficiency trends, and renewable energy

  15. Gasoline price data systems

    SciTech Connect (OSTI)

    Not Available

    1980-05-01T23:59:59.000Z

    Timely observation on prices of gasoline at the wholesale and retail level by geographical area can serve several purposes: (1) to facilitate the monitoring of compliance with controls on distributor margins; (2) to indicate changes in the competitive structure of the distribution system; (3) to measure the incidence of changes in crude oil and refiner costs on retail prices by grade of gasoline, by type of retail outlet, and by geographic area; (4) to identify anomalies in the retail pricing structure that may create incentives for misfueling; and (5) to provide detailed time series data for use in evaluating conservation response to price changes. In order to provide the needed data for these purposes, the following detail on gasoline prices and characteristics of the sampling procedure appear to be appropriate: (1) monthly sample observations on wholesale and retail prices by gasoline grade and type of wholesale or retail dealer, together with volume weights; (2) sample size sufficient to provide detail by state and large cities; (3) responses to be tabulated and reports provided within 30 days after date of observation; and (4) a quick response sampling procedure that can provide weekly data, at least at the national level, when needed in time of rapidly changing prices. Price detail by state is suggested due to its significance for administrative purposes and since gasoline consumption data are estimated by state from other sources. Price detail for large cities are suggested in view of their relevancy as problem areas for vehicle emissions, reflecting one of the analytical uses of the data. In this report, current reporting systems and data on gasoline prices are reviewed and evaluated in terms of the needs outlined above. Recommendations are made for ways to fill the gaps in existing data systems to meet these needs.

  16. Price/Cost Proposal Form

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    PREPARATION INSTRUCTIONS PriceCost Proposal: Provide complete, current, and accurate cost or pricing data in accordance with Federal and Department of Energy Acquisition...

  17. The effects of incorporating dynamic data on estimates of uncertainty

    E-Print Network [OSTI]

    Mulla, Shahebaz Hisamuddin

    2004-09-30T23:59:59.000Z

    in production forecasts will help in assessing risk and making good economic decisions. This study investigates the effect of combining dynamic data with the uncertainty in static data to see the effect on estimates of uncertainty in production forecasting... combined with linear uncertainty analysis. The results were compared with the uncertainty predicted using only static data. We also investigated approaches for best selecting a smaller number of models from a larger set of realizations to be history...

  18. Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty

    E-Print Network [OSTI]

    Siddiqui, Afzal

    2010-01-01T23:59:59.000Z

    Tradeo? Between Cost and Risk with Stochastic Energy PricesInvest- ment and Risk Analysis,” The Energy Journal 29(2):also their risk management capability as energy prices are

  19. A Framework for Analysis of the Uncertainty of Socioeconomic Growth and Climate Change on the Risk of Water Stress: a Case Study in Asia

    E-Print Network [OSTI]

    Fant, C.

    The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in how these factors change in the future is the uncertainty of ...

  20. Multi-Factor Energy Price Models Exotic Derivatives Pricing

    E-Print Network [OSTI]

    Jaimungal, Sebastian

    Multi-Factor Energy Price Models and Exotic Derivatives Pricing by Samuel Hikspoors A thesis of Statistics University of Toronto c Copyright by Samuel Hikspoors 2008 #12;Multi-Factor Energy Price Models and practitioners alike recently started to develop the tools of energy derivatives pricing

  1. Linking Oil Prices, Gas Prices, Economy, Transport, and Land Use

    E-Print Network [OSTI]

    Bertini, Robert L.

    Linking Oil Prices, Gas Prices, Economy, Transport, and Land Use A Review of Empirical Findings Hongwei Dong, Ph.D. Candidate John D. Hunt, Professor John Gliebe, Assistant Professor #12;Framework Oil-run Short and Long-run #12;Topics covered by this presentation: Oil price and macro-economy Gas price

  2. DRAFT REPORT HIERARCHY OF METHODS TO CHARACTERIZE UNCERTAINTY

    E-Print Network [OSTI]

    Frey, H. Christopher

    ...................................................................................................... 5 1.2.3 Risk, Cost, Uncertainty and Decisions ........................................................... 20 1.4.3 Other Quantitative Methods.............................................................................................. 24 1.4.5 Sensitivity Analysis

  3. Diesel prices slightly increase

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel pricesDiesel prices slightlyDiesel prices

  4. Programmatic methods for addressing contaminated volume uncertainties

    SciTech Connect (OSTI)

    Rieman, C.R.; Spector, H.L. [U.S. Army Corps of Engineers Buffalo District, Buffalo, NY (United States); Durham, L.A.; Johnson, R.L. [Argonne National Laboratory, Environmental Science Div., IL (United States)

    2007-07-01T23:59:59.000Z

    Accurate estimates of the volumes of contaminated soils or sediments are critical to effective program planning and to successfully designing and implementing remedial actions. Unfortunately, data available to support the pre-remedial design are often sparse and insufficient for accurately estimating contaminated soil volumes, resulting in significant uncertainty associated with these volume estimates. The uncertainty in the soil volume estimates significantly contributes to the uncertainty in the overall project cost estimates, especially since excavation and off-site disposal are the primary cost items in soil remedial action projects. The U.S. Army Corps of Engineers Buffalo District's experience has been that historical contaminated soil volume estimates developed under the Formerly Utilized Sites Remedial Action Program (FUSRAP) often underestimated the actual volume of subsurface contaminated soils requiring excavation during the course of a remedial activity. In response, the Buffalo District has adopted a variety of programmatic methods for addressing contaminated volume uncertainties. These include developing final status survey protocols prior to remedial design, explicitly estimating the uncertainty associated with volume estimates, investing in pre-design data collection to reduce volume uncertainties, and incorporating dynamic work strategies and real-time analytics in pre-design characterization and remediation activities. This paper describes some of these experiences in greater detail, drawing from the knowledge gained at Ashland 1, Ashland 2, Linde, and Rattlesnake Creek. In the case of Rattlesnake Creek, these approaches provided the Buffalo District with an accurate pre-design contaminated volume estimate and resulted in one of the first successful FUSRAP fixed-price remediation contracts for the Buffalo District. (authors)

  5. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX FuturesPrices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06T23:59:59.000Z

    On December 5, 2006, the reference case projections from 'Annual Energy Outlook 2007' (AEO 2007) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past six years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past six years at least, levelized cost comparisons of fixed-price renewable generation with variable-price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are 'biased' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2007. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past six AEO releases (AEO 2001-AEO 2006), we once again find that the AEO 2007 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. Specifically, the NYMEX-AEO 2007 premium is $0.73/MMBtu levelized over five years. In other words, on average, one would have had to pay $0.73/MMBtu more than the AEO 2007 reference case natural gas price forecast in order to lock in natural gas prices over the coming five years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation (or other forms of generation whose costs are not tied to the price of natural gas). Fixed-price generation (like certain forms of renewable generation) obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of five years.

  6. Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX FuturesPrices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19T23:59:59.000Z

    On December 12, 2005, the reference case projections from ''Annual Energy Outlook 2006'' (AEO 2006) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past five AEO releases (AEO 2001-AEO 2005), we once again find that the AEO 2006 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEX-AEO 2006 reference case comparison yields by far the largest premium--$2.3/MMBtu levelized over five years--that we have seen over the last six years. In other words, on average, one would have had to pay $2.3/MMBtu more than the AEO 2006 reference case natural gas price forecast in order to lock in natural gas prices over the coming five years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation (or other forms of generation whose costs are not tied to the price of natural gas). Fixed-price generation (like certain forms of renewable generation) obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of five years.

  7. Pricing an Annuity

    E-Print Network [OSTI]

    (We would certainly charge more to cover administrative costs and to allow for a .... The Price of the Annuity (H12) is the last value in the “Total Present Value to ...

  8. The ethics of dynamic pricing

    SciTech Connect (OSTI)

    Faruqui, Ahmad

    2010-07-15T23:59:59.000Z

    Dynamic pricing has garnered much interest among regulators and utilities, since it has the potential for lowering energy costs for society. But the deployment of dynamic pricing has been remarkably tepid. The underlying premise is that dynamic pricing is unfair. But the presumption of unfairness in dynamic pricing rests on an assumption of fairness in today's tariffs. (author)

  9. Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01T23:59:59.000Z

    Gas Price Forecast W ith natural gas prices significantlyof AEO 2006 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEO

  10. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01T23:59:59.000Z

    Natural Gas Price Forecast Although natural gas prices areof AEO 2007 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEO

  11. Environmental Modeling: Coping with Uncertainty

    E-Print Network [OSTI]

    Politècnica de Catalunya, Universitat

    ­ Statistical heterogeneity ­ Complex correlation structures · Classical models: ­ Additive noise ­ UniEnvironmental Modeling: Coping with Uncertainty Daniel M. Tartakovsky (dmt@lanl.gov) Theoretical of environmental processes 2. Parametric uncertainty 3. Current approaches to uncertainty quantification 4. Random

  12. Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets

    SciTech Connect (OSTI)

    Wong-Parodi, Gabrielle; Lekov, Alex; Dale, Larry

    2005-02-09T23:59:59.000Z

    This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futures price. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futures price provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futures price underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003 and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futures price into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.

  13. Metabolic paths in world economy and crude oil price

    E-Print Network [OSTI]

    Picciolo, Francesco; Ruzzenenti, Franco

    2015-01-01T23:59:59.000Z

    In 1983 Hamilton demonstrated the correlation between the price of oil and gross national product for the U.S. economy. A prolific literature followed exploring the potential correlation of oil prices with other important indices like inflation, industrial production, and food prices, using increasingly refined tools. Our work sheds new light on the role of oil prices in shaping the world economy by investigating the metabolic paths of value across trade between 1960 and 2010, by means of Markov Chain analysis. We show that the interdependence of countries' economies are strictly (anti)correlated to the price of oil. We observed a remarkably high correlation of 0.85, unmatched by any former study addressing the correlation between oil price and major economic indicators.

  14. Trajectories without quantum uncertainties

    E-Print Network [OSTI]

    Eugene S. Polzik; Klemens Hammerer

    2014-05-13T23:59:59.000Z

    A common knowledge suggests that trajectories of particles in quantum mechanics always have quantum uncertainties. These quantum uncertainties set by the Heisenberg uncertainty principle limit precision of measurements of fields and forces, and ultimately give rise to the standard quantum limit in metrology. With the rapid developments of sensitivity of measurements these limits have been approached in various types of measurements including measurements of fields and acceleration. Here we show that a quantum trajectory of one system measured relatively to the other "reference system" with an effective negative mass can be quantum uncertainty--free. The method crucially relies on the generation of an Einstein-Podolsky-Rosen entangled state of two objects, one of which has an effective negative mass. From a practical perspective these ideas open the way towards force and acceleration measurements at new levels of sensitivity far below the standard quantum limit.

  15. Methodology for characterizing modeling and discretization uncertainties in computational simulation

    SciTech Connect (OSTI)

    ALVIN,KENNETH F.; OBERKAMPF,WILLIAM L.; RUTHERFORD,BRIAN M.; DIEGERT,KATHLEEN V.

    2000-03-01T23:59:59.000Z

    This research effort focuses on methodology for quantifying the effects of model uncertainty and discretization error on computational modeling and simulation. The work is directed towards developing methodologies which treat model form assumptions within an overall framework for uncertainty quantification, for the purpose of developing estimates of total prediction uncertainty. The present effort consists of work in three areas: framework development for sources of uncertainty and error in the modeling and simulation process which impact model structure; model uncertainty assessment and propagation through Bayesian inference methods; and discretization error estimation within the context of non-deterministic analysis.

  16. Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect (OSTI)

    Bolinger, Mark A; Bolinger, Mark; Wiser, Ryan

    2008-01-07T23:59:59.000Z

    On December 12, 2007, the reference-case projections from Annual Energy Outlook 2008 (AEO 2008) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof) or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers (though its appeal has diminished somewhat as prices have increased); and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

  17. Numerical uncertainty in computational engineering and physics

    SciTech Connect (OSTI)

    Hemez, Francois M [Los Alamos National Laboratory

    2009-01-01T23:59:59.000Z

    Obtaining a solution that approximates ordinary or partial differential equations on a computational mesh or grid does not necessarily mean that the solution is accurate or even 'correct'. Unfortunately assessing the quality of discrete solutions by questioning the role played by spatial and temporal discretizations generally comes as a distant third to test-analysis comparison and model calibration. This publication is contributed to raise awareness of the fact that discrete solutions introduce numerical uncertainty. This uncertainty may, in some cases, overwhelm in complexity and magnitude other sources of uncertainty that include experimental variability, parametric uncertainty and modeling assumptions. The concepts of consistency, convergence and truncation error are overviewed to explain the articulation between the exact solution of continuous equations, the solution of modified equations and discrete solutions computed by a code. The current state-of-the-practice of code and solution verification activities is discussed. An example in the discipline of hydro-dynamics illustrates the significant effect that meshing can have on the quality of code predictions. A simple method is proposed to derive bounds of solution uncertainty in cases where the exact solution of the continuous equations, or its modified equations, is unknown. It is argued that numerical uncertainty originating from mesh discretization should always be quantified and accounted for in the overall uncertainty 'budget' that supports decision-making for applications in computational physics and engineering.

  18. Uncertainty quantification approaches for advanced reactor analyses.

    SciTech Connect (OSTI)

    Briggs, L. L.; Nuclear Engineering Division

    2009-03-24T23:59:59.000Z

    The original approach to nuclear reactor design or safety analyses was to make very conservative modeling assumptions so as to ensure meeting the required safety margins. Traditional regulation, as established by the U. S. Nuclear Regulatory Commission required conservatisms which have subsequently been shown to be excessive. The commission has therefore moved away from excessively conservative evaluations and has determined best-estimate calculations to be an acceptable alternative to conservative models, provided the best-estimate results are accompanied by an uncertainty evaluation which can demonstrate that, when a set of analysis cases which statistically account for uncertainties of all types are generated, there is a 95% probability that at least 95% of the cases meet the safety margins. To date, nearly all published work addressing uncertainty evaluations of nuclear power plant calculations has focused on light water reactors and on large-break loss-of-coolant accident (LBLOCA) analyses. However, there is nothing in the uncertainty evaluation methodologies that is limited to a specific type of reactor or to specific types of plant scenarios. These same methodologies can be equally well applied to analyses for high-temperature gas-cooled reactors and to liquid metal reactors, and they can be applied to steady-state calculations, operational transients, or severe accident scenarios. This report reviews and compares both statistical and deterministic uncertainty evaluation approaches. Recommendations are given for selection of an uncertainty methodology and for considerations to be factored into the process of evaluating uncertainties for advanced reactor best-estimate analyses.

  19. Comparison of AEO 2005 natural gas price forecast to NYMEX futures prices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13T23:59:59.000Z

    On December 9, the reference case projections from ''Annual Energy Outlook 2005 (AEO 2005)'' were posted on the Energy Information Administration's (EIA) web site. As some of you may be aware, we at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk. As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past four years, forward natural gas contracts (e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past four years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation (presuming that long-term price stability is valued). In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2005. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or, more recently (and briefly), http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past four AEO releases (AEO 2001-AE0 2004), we once again find that the AEO 2005 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEXAEO 2005 reference case comparison yields by far the largest premium--$1.11/MMBtu levelized over six years--that we have seen over the last five years. In other words, on average, one would have to pay $1.11/MMBtu more than the AEO 2005 reference case natural gas price forecast in order to lock in natural gas prices over the coming six years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation. Fixed-price renewables obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of six years.

  20. Fewer Prices than Zones Steven Stoft

    E-Print Network [OSTI]

    California at Berkeley. University of

    of the FERC or of its Office of Economic Policy. Nodal energy spot prices induce a least-cost dispatch are priced explicitly instead of implicitly through nodal energy price differences. Pricing transmission energy spot market. Even including the hub price, there are fewer CP+Hub prices than zonal prices

  1. MTBE, methanol prices rise

    SciTech Connect (OSTI)

    Morris, G.D.L.; Cornitius, T.

    1995-12-20T23:59:59.000Z

    After several months of drifting lower in line with declining autumn gasoline prices, tabs for methyl tert-butyl ether (MTBE) have turned around. There has been no big demand surge, but consumers and traders are beginning to build up inventories in advance of a series of midwinter shutdowns and turnarounds by producers. Spot prices, which dropped as low as 75 cts/gal, have rebounded to 90 cts/gal fob. Eager for a positive glimmer, methanol producers posted a 3-cts/gal increase in contract prices this month. It marks the first upward idea since February. In that time contract prices have dropped 75% from $1.55/gal to 39 cts/gal. A hard winter has hit early in much of the US sending natural gas prices up sharply. At the same time, formaldehyde and acetic acid markets remain firm, and with MTBE rebounding, methanol producers feel entitled to a piece of the action. {open_quotes}I don`t buy into this claim that MTBE demand is up and I don`t think producers can justify even a 3-cts/gal increase,{close_quotes} says one. {open_quotes}There is nothing in the economy to warrant a run-up. Housing starts are weaker, and demand is down at least 80,000 bbl/day with the MTBE shutdown.{close_quotes}

  2. Determining Price Reasonableness in UESC Price Proposals

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny:Revised Finding of No53197E T A * S H I E LGeothermal * AugustDETERMINING PRICE

  3. Ris-R-1344(EN) Assessment of Uncertainties in Risk

    E-Print Network [OSTI]

    Risø-R-1344(EN) Assessment of Uncertainties in Risk Analysis of Chemical Establishments of Uncertainties in Risk Analysis of Chemical Establishments The ASSURANCE project Final summary report Kurt risk analyses for the same chemical facility, an ammonia storage. The EC's Joint Research Centre

  4. A pricing problem under Monge property

    E-Print Network [OSTI]

    buyers have to be served and show that the pricing problem still admits a dynamic programming. algorithm if ... An early reference for an optimization application of this property dates back to 1781 when the ..... Personal communication, 2003. ... Heuristics For Product-Line Design Using Conjoint Analysis, Management.

  5. 15.818 Pricing, Spring 2005

    E-Print Network [OSTI]

    Tucker, Catherine

    This course, primarily discussion based, provides a framework for understanding pricing strategies and tactics. Topics covered include pricing in competitive markets, estimating demand, price discrimination, the role of ...

  6. Real Estate Prices and Economic Cycles

    E-Print Network [OSTI]

    Quigley, John M.

    2002-01-01T23:59:59.000Z

    in construction and price development were synchronized with3 Models of Housing price Development Based on EconomicTable 4 Models of Housing Price Development Based on Lagged

  7. Fairness and dynamic pricing: comments

    SciTech Connect (OSTI)

    Hogan, William W.

    2010-07-15T23:59:59.000Z

    In ''The Ethics of Dynamic Pricing,'' Ahmad Faruqui lays out a case for improved efficiency in using dynamic prices for retail electricity tariffs and addresses various issues about the distributional effects of alternative pricing mechanisms. The principal contrast is between flat or nearly constant energy prices and time-varying prices that reflect more closely the marginal costs of energy and capacity. The related issues of fairness criteria, contracts, risk allocation, cost allocation, means testing, real-time pricing, and ethical policies of electricity market design also must be considered. (author)

  8. Texas Farm Commodity Prices.

    E-Print Network [OSTI]

    Childs, V. C. (Virgil C.); Schlotzhauer, Elbert O.; McNeely, John G.

    1948-01-01T23:59:59.000Z

    the base price of 12.4 cents or 31.12 cents a pound. The parity price for wheat was 2.51 times 88.4 cents or $2.22 per bushel. The parity price of potatoes, however, which is calculated from the base August 1919-July 1929, was 1.66 times $1.12 a bushel....90 1.88 1.86 1.78 1.40 1.08 1.12 1920 0 24 1 36 1 44 1.51 1.62 1.70 1.62 1.42 1.15 .94 .86 1921 80 :86 :88 85 84 82 77 64 51 49 52 1922 .51 .58 .66 .68 .72 .72 .72 .74 .71 .72 .79 1923 .92 .95 1.00 1.04 1.04 1.06 1.03 .98 .98 1.01 1.00 1924 1...

  9. Diesel prices decrease

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continue toDiesel prices decrease

  10. Diesel prices decrease

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continue toDiesel prices

  11. Diesel prices decrease

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continue toDiesel pricesDiesel

  12. Diesel prices flat

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continueU.S.Diesel prices flat The

  13. Diesel prices flat nationally

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continueU.S.Diesel prices flat

  14. Diesel prices increase

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continueU.S.Diesel prices

  15. Diesel prices increase

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continueU.S.Diesel pricesDiesel

  16. Diesel prices increase nationally

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continueU.S.DieselDiesel prices

  17. Diesel prices slightly decrease

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel pricesDiesel prices slightly decrease The

  18. Diesel prices slightly decrease

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel pricesDiesel prices slightly decrease

  19. Residential propane price

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil price decreasesheatingheatingpropane price

  20. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price decreasespropane price

  1. Residential propane prices available

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price05,propane prices

  2. Residential propane prices decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price05,propane prices5, 2014

  3. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price05,propane prices5,

  4. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price05,propanepropane prices

  5. Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28T23:59:59.000Z

    On December 17, 2008, the reference-case projections from Annual Energy Outlook 2009 (AEO 2009) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof), differences in capital costs and O&M expenses, or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired or nuclear generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers; and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal, uranium, and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

  6. Low prices harpoon Canada's mini-boom

    SciTech Connect (OSTI)

    Maciej, H. (Canadian Petroleum Association, Calgary, Alta (CA))

    1989-02-01T23:59:59.000Z

    The authors present an analysis of the year 1988 in the Canadian oil and gas industry. With budgets underpinned by price expectations of $17/bbl to $18/bbl for WTI crude, optimism pervaded industry at the beginning of the year. Budget plans called for total spending of some C$7.6 billion, an increase of 25% over the C$6.1 invested in 1987. Drilling plans would have made 1988 the fourth best year on record with total well completions close to the 9,000-well mark. The year started strongly, as prices performed close to expectations. When prices began to soften and no reversal was apparent, corporate expenditures began to be adjusted in the second half.

  7. Convergence Speed of GARCH Option Price to Diffusion Option Price

    E-Print Network [OSTI]

    Chaudhuri, Sanjay

    Convergence Speed of GARCH Option Price to Diffusion Option Price Jin-Chuan Duan, Yazhen Wang that as the time interval between two consecutive observations shrinks to zero, a properly constructed GARCH model will weakly converge to a bivariate diffusion. Naturally the European option price under the GARCH model

  8. Convergence Speed of GARCH Option Price to Diffusion Option Price

    E-Print Network [OSTI]

    Wang, Yazhen

    Convergence Speed of GARCH Option Price to Diffusion Option Price Jin-Chuan Duan National constructed GARCH model will weakly converge to a bi- variate diffusion. Naturally the European option price under the GARCH model will also converge to its bivariate diffusion counterpart. This paper investigates

  9. An analysis of the uncertainty and bias in DCE-MRI measurements using the spoiled gradient-recalled echo pulse sequence

    SciTech Connect (OSTI)

    Subashi, Ergys [Center for In Vivo Microscopy, Duke University Medical Center, Durham, North Carolina 27710 and Medical Physics Graduate Program, Duke University Medical Center, Durham, North Carolina 27710 (United States)] [Center for In Vivo Microscopy, Duke University Medical Center, Durham, North Carolina 27710 and Medical Physics Graduate Program, Duke University Medical Center, Durham, North Carolina 27710 (United States); Choudhury, Kingshuk R. [Department of Biomedical Engineering, Duke University Medical Center, Durham, North Carolina 27710 (United States)] [Department of Biomedical Engineering, Duke University Medical Center, Durham, North Carolina 27710 (United States); Johnson, G. Allan, E-mail: gjohnson@duke.edu [Center for In Vivo Microscopy, Duke University Medical Center, Durham, North Carolina 27710 (United States); Medical Physics Graduate Program, Duke University Medical Center, Durham, North Carolina 27710 (United States); Department of Biomedical Engineering, Duke University Medical Center, Durham, North Carolina 27710 (United States); Department of Radiology, Duke University Medical Center, Durham, North Carolina 27710 (United States)

    2014-03-15T23:59:59.000Z

    Purpose: The pharmacokinetic parameters derived from dynamic contrast-enhanced (DCE) MRI have been used in more than 100 phase I trials and investigator led studies. A comparison of the absolute values of these quantities requires an estimation of their respective probability distribution function (PDF). The statistical variation of the DCE-MRI measurement is analyzed by considering the fundamental sources of error in the MR signal intensity acquired with the spoiled gradient-echo (SPGR) pulse sequence. Methods: The variance in the SPGR signal intensity arises from quadrature detection and excitation flip angle inconsistency. The noise power was measured in 11 phantoms of contrast agent concentration in the range [0–1] mM (in steps of 0.1 mM) and in onein vivo acquisition of a tumor-bearing mouse. The distribution of the flip angle was determined in a uniform 10 mM CuSO{sub 4} phantom using the spin echo double angle method. The PDF of a wide range of T1 values measured with the varying flip angle (VFA) technique was estimated through numerical simulations of the SPGR equation. The resultant uncertainty in contrast agent concentration was incorporated in the most common model of tracer exchange kinetics and the PDF of the derived pharmacokinetic parameters was studied numerically. Results: The VFA method is an unbiased technique for measuringT1 only in the absence of bias in excitation flip angle. The time-dependent concentration of the contrast agent measured in vivo is within the theoretically predicted uncertainty. The uncertainty in measuring K{sup trans} with SPGR pulse sequences is of the same order, but always higher than, the uncertainty in measuring the pre-injection longitudinal relaxation time (T1{sub 0}). The lowest achievable bias/uncertainty in estimating this parameter is approximately 20%–70% higher than the bias/uncertainty in the measurement of the pre-injection T1 map. The fractional volume parameters derived from the extended Tofts model were found to be extremely sensitive to the variance in signal intensity. The SNR of the pre-injection T1 map indicates the limiting precision with which K{sup trans} can be calculated. Conclusions: Current small-animal imaging systems and pulse sequences robust to motion artifacts have the capacity for reproducible quantitative acquisitions with DCE-MRI. In these circumstances, it is feasible to achieve a level of precision limited only by physiologic variability.

  10. Optimal Uncertainty Quantification

    E-Print Network [OSTI]

    Owhadi, Houman; Sullivan, Timothy John; McKerns, Mike; Ortiz, Michael

    2010-01-01T23:59:59.000Z

    We propose a rigorous framework for Uncertainty Quantification (UQ) in which the UQ objectives and the assumptions/information set are brought to the forefront. This framework, which we call \\emph{Optimal Uncertainty Quantification} (OUQ), is based on the observation that, given a set of assumptions and information about the problem, there exist optimal bounds on uncertainties: these are obtained as extreme values of well-defined optimization problems corresponding to extremizing probabilities of failure, or of deviations, subject to the constraints imposed by the scenarios compatible with the assumptions and information. In particular, this framework does not implicitly impose inappropriate assumptions, nor does it repudiate relevant information. Although OUQ optimization problems are extremely large, we show that under general conditions, they have finite-dimensional reductions. As an application, we develop \\emph{Optimal Concentration Inequalities} (OCI) of Hoeffding and McDiarmid type. Surprisingly, contr...

  11. Best Buys and Unit Pricing

    E-Print Network [OSTI]

    Anding, Jenna

    2000-02-02T23:59:59.000Z

    This guide explains how to determine a unit price--the cost of an item based on a specific unit such as pound or ounce. Unit pricing can be used to identify foods that are the most economical....

  12. Asset Prices and Exchange Rates

    E-Print Network [OSTI]

    Pavlova, Anna

    2004-11-30T23:59:59.000Z

    This paper develops a simple two-country, two-good model, in which the real exchange rate, stock and bond prices are jointly determined. The model predicts that stock market prices are correlated ...

  13. Rethinking Real Time Electricity Pricing

    E-Print Network [OSTI]

    Allcott, Hunt

    Most US consumers are charged a near-constant retail price for electricity, despite substantial hourly variation in the wholesale market price. This paper evaluates the .rst program to expose residential consumers to hourly ...

  14. Carbon pricing, nuclear power and electricity markets

    SciTech Connect (OSTI)

    Cameron, R.; Keppler, J. H. [OECD Nuclear Energy Agency, 12, boulevard des Iles, 92130 Issy-les-Moulineaux (France)

    2012-07-01T23:59:59.000Z

    In 2010, the NEA in conjunction with the International Energy Agency produced an analysis of the Projected Costs of Electricity for almost 200 power plants, covering nuclear, fossil fuel and renewable electricity generation. That analysis used lifetime costs to consider the merits of each technology. However, the lifetime cost analysis is less applicable in liberalised markets and does not look specifically at the viewpoint of the private investor. A follow-up NEA assessment of the competitiveness of nuclear energy against coal- and gas-fired generation under carbon pricing has considered just this question. The economic competition in electricity markets is today between nuclear energy and gas-fired power generation, with coal-fired power generation not being competitive as soon as even modest carbon pricing is introduced. Whether nuclear energy or natural gas comes out ahead in their competition depends on a number of assumptions, which, while all entirely reasonable, yield very different outcomes. The analysis in this study has been developed on the basis of daily data from European power markets over the last five-year period. Three different methodologies, a Profit Analysis looking at historic returns over the past five years, an Investment Analysis projecting the conditions of the past five years over the lifetime of plants and a Carbon Tax Analysis (differentiating the Investment Analysis for different carbon prices) look at the issue of competitiveness from different angles. They show that the competitiveness of nuclear energy depends on a number of variables which in different configurations determine whether electricity produced from nuclear power or from CCGTs generates higher profits for its investors. These are overnight costs, financing costs, gas prices, carbon prices, profit margins (or mark-ups), the amount of coal with carbon capture and electricity prices. This paper will present the outcomes of the analysis in the context of a liberalised electricity market, looking at the impact of the seven key variables and provide conclusions on the portfolio that a utility would be advised to maintain, given the need to limit risks but also to move to low carbon power generation. Such portfolio diversification would not only limit financial investor risk, but also a number of non-financial risks (climate change, security of supply, accidents). (authors)

  15. National Laboratory Dorene Price

    E-Print Network [OSTI]

    : price@bnl.gov ELECTROCHEMICAL ENHANCEMENT OF BIO-ETHANOL AND METABOLITE PRODUCTION Brookhaven National as a manufacturing step in their process to produce bio-ethanol or other commercially used metabolites can implement ApplicationFiled 61/042,867 TECHNOLOGY This method accelerates the production of ethanol and other metabolites

  16. National Laboratory Dorene Price

    E-Print Network [OSTI]

    : price@bnl.gov ACTIVATED ALUMINUM HYDRIDE HYDROGEN STORAGE COMPOSITIONS AND USES THEREOF Brookhaven alanates doped with such metal catalysts. Hydrogen is one part of a balanced, strategic portfolio of energy for the U.S. Department of Energy. An activated aluminum hydride (AlH3 ) composition to control

  17. Technique for estimating jet fuel prices from energy futures market

    SciTech Connect (OSTI)

    Vineyard, T.A.

    1988-05-01T23:59:59.000Z

    This report presents a statistical analysis of future prices of petroleum products for use in predicting the monthly average retail price of kerosene-type jet fuel. The method of least squares was employed to examine the relationship between kerosene-type jet fuel retail prices and energy futures prices. Regression equations were constructed for four of the petroleum commodities traded on the energy futures market: heating oil No. 2, leaded regular gasoline, crude oil, and unleaded gasoline. Thirty-nine regression equations were estimated by the method of least squares to relate the cash price of kerosene-type jet fuel to the futures prices of the above four petroleum commodities for contract periods of 1 to 12 months. The analysis revealed that 19 of the 39 first-order linear regression equations provided a good fit to the data. Specifically, heating oil No. 2 performed better than the order energy futures in predicting the price of kerosene-type jet fuel. The only information required to use these regression equations are energy futures prices which are available daily from the Wall Street Journal. 5 refs., 4 tabs.

  18. Intraclass Price Elasticity & Electric Rate Design 

    E-Print Network [OSTI]

    Gresham, K. E.

    1987-01-01T23:59:59.000Z

    Electric rate design relies on cost incurrance for pricing and pricing structures. However, as utilities move into a marketing mode, rate design needs to respond more to customer reactions to pricing changes. Intraclass price elasticities aid rate...

  19. Fact #835: August 25, 2014 Average Annual Gasoline Pump Price...

    Broader source: Energy.gov (indexed) [DOE]

    35: Average Annual Gasoline Pump Price, 1929-2013 fotw835web.xlsx More Documents & Publications Offshore Wind Market and Economic Analysis Report 2013 Response to several FOIA...

  20. Fuel Prices and New Vehicle Fuel Economy in Europe

    E-Print Network [OSTI]

    Klier, Thomas

    This paper evaluates the effect of fuel prices on new vehicle fuel economy in the eight largest European markets. The analysis spans the years 2002–2007 and uses detailed vehicle registration and specification data to ...

  1. Modeling intraurban price competition: an example of gasoline pricing

    SciTech Connect (OSTI)

    Haining, R.

    1983-11-01T23:59:59.000Z

    Three interacting market models are considered as models for intraurban retail price variation for a single homogenous good, price-posted gasoline. Modifications include spatial markets instead of interacting economic sectors and supply functions independent of price levels in other markets. The final section discusses the results of fitting one of the models to gasoline data for the city of Sheffield during a period of intensifying price competition in the first quarter of 1982. It is concluded, with respect to gasoline price modeling, both independent and interacting market models exist but at different intraurban scales. 15 references, 1 figure, 1 table.

  2. analysis project evaluating: Topics by E-print Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    uncertainties in typical oil and gas projects: 1. The oil price, 2. The investments (capex) and operating. The oil and gas reserves and production profiles, 5. The production...

  3. Life Cycle Regulation of Transportation Fuels: Uncertainty and its Policy Implications

    E-Print Network [OSTI]

    Plevin, Richard Jay

    2010-01-01T23:59:59.000Z

    tainty in quantitative risk and policy analysis. Cambridge ;quantitative and qualitative measures of uncertainty in model-based environmental as- sessment: The NUSAP system. Risk Analysis

  4. Assessment of Summer 1997 motor gasoline price increase

    SciTech Connect (OSTI)

    NONE

    1998-05-01T23:59:59.000Z

    Gasoline markets in 1996 and 1997 provided several spectacular examples of petroleum market dynamics. The first occurred in spring 1996, when tight markets, following a long winter of high demand, resulted in rising crude oil prices just when gasoline prices exhibit their normal spring rise ahead of the summer driving season. Rising crude oil prices again pushed gasoline prices up at the end of 1996, but a warm winter and growing supplies weakened world crude oil markets, pushing down crude oil and gasoline prices during spring 1997. The 1996 and 1997 spring markets provided good examples of how crude oil prices can move gasoline prices both up and down, regardless of the state of the gasoline market in the United States. Both of these spring events were covered in prior Energy Information Administration (EIA) reports. As the summer of 1997 was coming to a close, consumers experienced yet another surge in gasoline prices. Unlike the previous increase in spring 1996, crude oil was not a factor. The late summer 1997 price increase was brought about by the supply/demand fundamentals in the gasoline markets, rather than the crude oil markets. The nature of the summer 1997 gasoline price increase raised questions regarding production and imports. Given very strong demand in July and August, the seemingly limited supply response required examination. In addition, the price increase that occurred on the West Coast during late summer exhibited behavior different than the increase east of the Rocky Mountains. Thus, the Petroleum Administration for Defense District (PADD) 5 region needed additional analysis (Appendix A). This report is a study of this late summer gasoline market and some of the important issues surrounding that event.

  5. Stochastic Reduced Basis Methods for Uncertainty Quantification

    E-Print Network [OSTI]

    Sóbester, András

    Turbine Blades In general, stochastic analysis (using SRBM) of any physical system involves two main steps the variability in the performance of a turbine blade in the presence of uncertainty. These blades operate variability in material properties and boundary condi- tions. Given a numerical solution of the set of SPDEs

  6. Decision Analysis for EGS | Department of Energy

    Broader source: Energy.gov (indexed) [DOE]

    Decision Analysis for EGS Decision Analysis for EGS Project objectives: DEVELOPMENT OF ANALYSIS TOOLS TO ASSESS: Uncertainties associated with exploration for EGS; Uncertainties...

  7. Relationship Between Wind Generation and Balancing Energy Market Prices in ERCOT: 2007-2009

    SciTech Connect (OSTI)

    Nicholson, E.; Rogers, J.; Porter, K.

    2010-11-01T23:59:59.000Z

    This paper attempts to measure the average marginal effects of wind generation on the balancing-energy market price in ERCOT with the help of econometric analysis.

  8. Uncertainty Management in Optimal Disassembly Planning through Learning-based Strategies

    E-Print Network [OSTI]

    Reveliotis, Spiridon "Spyros"

    literature. Keywords: disassembly planning, product recovery, uncertainty management, reinforce- ment technical area of production system modelling, analysis and control. One particular theme that is emergingUncertainty Management in Optimal Disassembly Planning through Learning-based Strategies Spyros A

  9. RESEARCH ARTICLE Open Access Uncertainty-aware visualization and proximity

    E-Print Network [OSTI]

    Kamat, Vineet R.

    -aware, geospatial-AR system for real time visualization and proximity analysis. Uncertainties are modeled excavation: a geospatial augmented reality approach Xing Su1 , Sanat Talmaki2 , Hubo Cai3* and Vineet R Kamat an uncertainty-aware, geospatial augmented reality (AR) to visualize and monitor the proximity between invisible

  10. Uncertainty Principle Respects Locality

    E-Print Network [OSTI]

    Dongsheng Wang

    2015-04-19T23:59:59.000Z

    The notion of nonlocality implicitly implies there might be some kind of spooky action at a distance in nature, however, the validity of quantum mechanics has been well tested up to now. In this work it is argued that the notion of nonlocality is physically improper, the basic principle of locality in nature is well respected by quantum mechanics, namely, the uncertainty principle. We show that the quantum bound on the Clauser, Horne, Shimony, and Holt (CHSH) inequality can be recovered from the uncertainty relation in a multipartite setting. We further argue that the super-quantum correlation demonstrated by the nonlocal box is not physically comparable with the quantum one. The origin of the quantum structure of nature still remains to be explained, some post-quantum theory which is more complete in some sense than quantum mechanics is possible and might not necessarily be a hidden variable theory.

  11. Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01T23:59:59.000Z

    gas price forecasts with contemporaneous natural gas pricesreference-case natural gas price forecast, and that have notof AEO 2009 Natural Gas Price Forecast to NYMEX Futures

  12. Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    gas price forecasts with contemporaneous natural gas pricesreference-case natural gas price forecast, and that have notof AEO 2008 Natural Gas Price Forecast to NYMEX Futures

  13. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    the base-case natural gas price forecast, but to alsogas price forecasts with contemporaneous natural gas pricesof AEO 2010 Natural Gas Price Forecast to NYMEX Futures

  14. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    range of different plausible price projections, using eitherreference-case fuel price projection from the EIA or someprices and the AEO gas price projections over the past two

  15. Calibration Under Uncertainty.

    SciTech Connect (OSTI)

    Swiler, Laura Painton; Trucano, Timothy Guy

    2005-03-01T23:59:59.000Z

    This report is a white paper summarizing the literature and different approaches to the problem of calibrating computer model parameters in the face of model uncertainty. Model calibration is often formulated as finding the parameters that minimize the squared difference between the model-computed data (the predicted data) and the actual experimental data. This approach does not allow for explicit treatment of uncertainty or error in the model itself: the model is considered the %22true%22 deterministic representation of reality. While this approach does have utility, it is far from an accurate mathematical treatment of the true model calibration problem in which both the computed data and experimental data have error bars. This year, we examined methods to perform calibration accounting for the error in both the computer model and the data, as well as improving our understanding of its meaning for model predictability. We call this approach Calibration under Uncertainty (CUU). This talk presents our current thinking on CUU. We outline some current approaches in the literature, and discuss the Bayesian approach to CUU in detail.

  16. Incorporating uncertainty in RADTRAN 6.0 input files.

    SciTech Connect (OSTI)

    Dennis, Matthew L.; Weiner, Ruth F.; Heames, Terence John (Alion Science and Technology)

    2010-02-01T23:59:59.000Z

    Uncertainty may be introduced into RADTRAN analyses by distributing input parameters. The MELCOR Uncertainty Engine (Gauntt and Erickson, 2004) has been adapted for use in RADTRAN to determine the parameter shape and minimum and maximum of the distribution, to sample on the distribution, and to create an appropriate RADTRAN batch file. Coupling input parameters is not possible in this initial application. It is recommended that the analyst be very familiar with RADTRAN and able to edit or create a RADTRAN input file using a text editor before implementing the RADTRAN Uncertainty Analysis Module. Installation of the MELCOR Uncertainty Engine is required for incorporation of uncertainty into RADTRAN. Gauntt and Erickson (2004) provides installation instructions as well as a description and user guide for the uncertainty engine.

  17. Understanding Trends in Wind Turbine Prices Over the Past Decade

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2011-10-26T23:59:59.000Z

    Taking a bottom-up approach, this report examines seven primary drivers of wind turbine prices in the United States, with the goal of estimating the degree to which each contributed to the doubling in turbine prices from 2002 through 2008, as well as the subsequent decline in prices through 2010 (our analysis does not extend into 2011 because several of these drivers are best gauged on a full-year basis due to seasonality issues). The first four of these drivers can be considered, at least to some degree, endogenous influences – i.e., those that are largely within the control of the wind industry – and include changes in: 1) Labor costs, which have historically risen during times of tight turbine supply; 2) Warranty provisions, which reflect technology performance and reliability, and are most often capitalized in turbine prices; 3) Turbine manufacturer profitability, which can impact turbine prices independently of costs; and 4) Turbine design, which for the purpose of this analysis is principally manifested through increased turbine size. The other three drivers analyzed in this study can be considered exogenous influences, in that they can impact wind turbine costs but fall mostly outside of the direct control of the wind industry. These exogenous drivers include changes in: 5) Raw materials prices, which affect the cost of inputs to the manufacturing process; 6) Energy prices, which impact the cost of manufacturing and transporting turbines; and 7) Foreign exchange rates, which can impact the dollar amount paid for turbines and components imported into the United States.

  18. Electoral Competition, Political Uncertainty and Policy Insulation

    E-Print Network [OSTI]

    de Figueiredo, Rui J. P. Jr.

    2001-01-01T23:59:59.000Z

    Uncertainty and Policy Insulation Horn, Murray. 1995. TheUncertainty and Policy Insulation United States Congress.UNCERTAINTY AND POLICY INSULATION Rui J. P. de Figueiredo,

  19. Impact of price specials on estimates of retail meat prices

    E-Print Network [OSTI]

    Degner, Robert L

    1970-01-01T23:59:59.000Z

    ighting Technique V. V. SUM'JARA' AND CONCLUSIONS. 46 55 o3 69 Ti. me-of-the-Week to Collect Prices. Bias Reduced by Regression. Concluding Statement. REFEBENCES. APPENDIX. 89 90 95 100 115 vill LIST OF TABLES Table Page 1-1. Relative...' or individual items in Dallas and Houston. 101 3-1. Simulated BLS price estimates of 46 meat items based upon different sampling rates and weighted average price, or all data, July 1968. . . . . . . . . . . . 107 "Error" of price estimates; differences...

  20. Uncertainty and sampling issues in tank characterization

    SciTech Connect (OSTI)

    Liebetrau, A.M.; Pulsipher, B.A.; Kashporenko, D.M. [and others

    1997-06-01T23:59:59.000Z

    A defensible characterization strategy must recognize that uncertainties are inherent in any measurement or estimate of interest and must employ statistical methods for quantifying and managing those uncertainties. Estimates of risk and therefore key decisions must incorporate knowledge about uncertainty. This report focuses statistical methods that should be employed to ensure confident decision making and appropriate management of uncertainty. Sampling is a major source of uncertainty that deserves special consideration in the tank characterization strategy. The question of whether sampling will ever provide the reliable information needed to resolve safety issues is explored. The issue of sample representativeness must be resolved before sample information is reliable. Representativeness is a relative term but can be defined in terms of bias and precision. Currently, precision can be quantified and managed through an effective sampling and statistical analysis program. Quantifying bias is more difficult and is not being addressed under the current sampling strategies. Bias could be bounded by (1) employing new sampling methods that can obtain samples from other areas in the tanks, (2) putting in new risers on some worst case tanks and comparing the results from existing risers with new risers, or (3) sampling tanks through risers under which no disturbance or activity has previously occurred. With some bound on bias and estimates of precision, various sampling strategies could be determined and shown to be either cost-effective or infeasible.

  1. Investment and Upgrade in Distributed Generation under Uncertainty

    SciTech Connect (OSTI)

    Siddiqui, Afzal; Maribu, Karl

    2008-08-18T23:59:59.000Z

    The ongoing deregulation of electricity industries worldwide is providing incentives for microgrids to use small-scale distributed generation (DG) and combined heat and power (CHP) applications via heat exchangers (HXs) to meet local energy loads. Although the electric-only efficiency of DG is lower than that of central-station production, relatively high tariff rates and the potential for CHP applications increase the attraction of on-site generation. Nevertheless, a microgrid contemplatingthe installation of gas-fired DG has to be aware of the uncertainty in the natural gas price. Treatment of uncertainty via real options increases the value of the investment opportunity, which then delays the adoption decision as the opportunity cost of exercising the investment option increases as well. In this paper, we take the perspective of a microgrid that can proceed in a sequential manner with DG capacity and HX investment in order to reduce its exposure to risk from natural gas price volatility. In particular, with the availability of the HX, the microgrid faces a tradeoff between reducing its exposure to the natural gas price and maximising its cost savings. By varying the volatility parameter, we find that the microgrid prefers a direct investment strategy for low levels of volatility and a sequential one for higher levels of volatility.

  2. Mississippi Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million CubicCubic Feet) PriceLiquids, Proved2009 2010

  3. Mississippi Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto China (Million CubicCubic Feet) PriceLiquids, Proved2009

  4. Diesel prices decrease

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continue to increaseDiesel

  5. Diesel prices decrease

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continue to increaseDieselDiesel

  6. Diesel prices decrease

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continue to

  7. Diesel prices decrease slightly

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continueU.S. DieselDieselDiesel

  8. Diesel prices rise slightly

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavidDiesel prices continueU.S.DieselDieselDiesel

  9. World Crude Oil Prices

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline prices4 Oil demand Motor444 U.S.Working and

  10. Average Commercial Price

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline prices4 OilU.S.5AreOil andMarket Module8.28

  11. Average Residential Price

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline prices4 OilU.S.5AreOil andMarket

  12. Georgia Natural Gas Prices

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803 Table A1.GasYear JanPriceIndustrial Consumers48 4.95

  13. Residential heating oil price

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782AAdministrationheating oil price

  14. Residential propane price

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil price decreasesheatingheating oil

  15. Residential propane price

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil price decreasesheatingheating oilpropane

  16. Residential propane price

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil price decreasesheatingheating

  17. Residential propane price

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil price decreasesheatingheatingpropane

  18. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil price

  19. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price decreases The average

  20. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price decreases The

  1. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price decreases Thepropane

  2. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price decreases

  3. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price decreasespropane

  4. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price decreasespropanepropane

  5. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price

  6. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price05, 2014 Residential

  7. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price05, 2014

  8. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price05, 2014propane

  9. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price05, 2014propanepropane

  10. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price05,propane

  11. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price05,propanepropane

  12. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropane price05,propanepropanepropane

  13. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane prices increase The

  14. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane prices increase

  15. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane prices increasepropane

  16. Residential propane prices stable

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane prices

  17. Residential propane prices stable

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane pricespropane price

  18. What Is Price Volatility

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion Cubic Feet)YearWellhead Price (Dollars perProvedWesternWhatWhat

  19. Table 1. Crude Oil Prices

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    December 1980; Form EIA-14, "Refiners' Monthly Cost Report," January 1981 to present. 1. Crude Oil Prices 2 Energy Information Administration Petroleum Marketing Annual 1996...

  20. Table 1. Crude Oil Prices

    U.S. Energy Information Administration (EIA) Indexed Site

    December 1980; Form EIA-14, "Refiners' Monthly Cost Report," January 1981 to present. 1. Crude Oil Prices 2 Energy Information Administration Petroleum Marketing Annual 1997...

  1. ,"New Mexico Natural Gas Prices"

    U.S. Energy Information Administration (EIA) Indexed Site

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Prices",8,"Monthly","12015","1151989" ,"Release Date:","331...

  2. Revisiting the Income Effect: Gasoline Prices and Grocery Purchases

    E-Print Network [OSTI]

    Gicheva, Dora; Hastings, Justine; Villas-Boas, Sofia B

    2008-01-01T23:59:59.000Z

    Sold On Sale and Retail Gasoline Prices Log % Purchased Onhigher gasoline prices into retail prices, by investigatingexcluding California average retail gasoline price for all

  3. Comparison of AEO 2005 natural gas price forecast to NYMEX futures prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01T23:59:59.000Z

    Gas Price Forecast With natural gas prices significantlyto the EIA’s natural gas price forecasts in AEO 2004 and AEOon the AEO 2005 natural gas price forecasts will likely once

  4. Economic History Revisited: New Uncertainties

    E-Print Network [OSTI]

    to the southern and midwestern regions of the United States. However, the large run-up in oil prices is increasing shown vacancy rates higher than the historical average, while companies seeking properties for sale are paying ever-increasing prices for fewer available sites. Warehouse sites in the southern portion

  5. Postgraduate Scholarship Pricing temperature derivatives and modelling

    E-Print Network [OSTI]

    Banaji,. Murad

    the volumetric risk of the energy units sold, rather than the price risk of each unit. Weather derivativesPostgraduate Scholarship Pricing temperature derivatives and modelling the market price of risk: Pricing temperature derivatives and modelling the market price of risk. Main Supervisor: A. Alexandridis

  6. Conservation Market Price Adder Wally Gibson

    E-Print Network [OSTI]

    and offer into market, if market price justifies cost of building · Utilities purchase at market price gas units · Provides surplus to sell into market in moderate price periods to help cost recovery 2 Overview · Market price does not equal the cost of avoided resource · Market price is still

  7. Assessment and Propagation of Model Uncertainty

    E-Print Network [OSTI]

    David Draper

    2011-01-01T23:59:59.000Z

    1982). Outlook for World Oil Prices. Washington DC: U. S.run. But, in view of the oil price example, which is worse—Case N-2524-RC, of Oil Prices. Santa Monica, CA: RAND.

  8. Higher Prices from Entry: Pricing of Brand-Name Drugs

    E-Print Network [OSTI]

    Perloff, Jeffrey M.

    Workshop for useful discussions and comments. We especially thank Ernst Berndt for extensive help is price. Using a spatial model, we show that the effect of entry on price depends on how close together products are located in characteristic space. To illustrate this logic, we suppose that a firm enters

  9. Real options approach to capacity planning under uncertainty

    E-Print Network [OSTI]

    Mittal, Geetanjali, 1979-

    2004-01-01T23:59:59.000Z

    This thesis highlights the effectiveness of Real Options Analysis (ROA) in capacity planning decisions for engineering projects subject to uncertainty. This is in contrast to the irreversible decision-making proposed by ...

  10. Uncertainty in Greenhouse Emissions and Costs of Atmospheric Stabilization

    E-Print Network [OSTI]

    Webster, Mort D.

    We explore the uncertainty in projections of emissions, and costs of atmospheric stabilization applying the MIT Emissions Prediction and Policy Analysis model, a computable general equilibrium model of the global economy. ...

  11. Improved Price Indexes for Durable Goods: Measuring the Course of Sweding Housing Prices

    E-Print Network [OSTI]

    Englund, Peter; Quigley, John M.; Redfearn, Christian L.

    1996-01-01T23:59:59.000Z

    2.3. Explanations for the price development may be sought ina similar pattern of price development across regions during

  12. Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    to electricity generators to the same price projections fromPrices Delivered to Electricity Generators, Nominal $/MMBtu Each AEO projection

  13. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01T23:59:59.000Z

    to electricity generators to the same price projections fromPrices Delivered to Electricity Generators, Nominal $/MMBtu Each AEO projection

  14. analysis pre-release evaluation: Topics by E-print Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    uncertainties in typical oil and gas projects: 1. The oil price, 2. The investments (capex) and operating. The oil and gas reserves and production profiles, 5. The production...

  15. Uncertainty relation in Schwarzschild spacetime

    E-Print Network [OSTI]

    Jun Feng; Yao-Zhong Zhang; Mark D. Gould; Heng Fan

    2015-02-27T23:59:59.000Z

    We explore the entropic uncertainty relation in the curved background outside a Schwarzschild black hole, and find that Hawking radiation introduces a nontrivial modification on the uncertainty bound for particular observer, therefore it could be witnessed by proper uncertainty game experimentally. We first investigate an uncertainty game between a free falling observer and his static partner holding a quantum memory initially entangled with the quantum system to be measured. Due to the information loss from Hawking decoherence, we find an inevitable increase of the uncertainty on the outcome of measurements in the view of static observer, which is dependent on the mass of the black hole, the distance of observer from event horizon, and the mode frequency of quantum memory. To illustrate the generality of this paradigm, we relate the entropic uncertainty bound with other uncertainty probe, e.g., time-energy uncertainty. In an alternative game between two static players, we show that quantum information of qubit can be transferred to quantum memory through a bath of fluctuating quantum fields outside the black hole. For a particular choice of initial state, we show that the Hawking decoherence cannot counteract entanglement generation after the dynamical evolution of system, which triggers an effectively reduced uncertainty bound that violates the intrinsic limit $-\\log_2c$. Numerically estimation for a proper choice of initial state shows that our result is comparable with possible real experiments. Finally, a discussion on the black hole firewall paradox in the context of entropic uncertainty relation is given.

  16. The impact of uncertainty and risk measures

    E-Print Network [OSTI]

    Jo, Soojin; Jo, Soojin

    2012-01-01T23:59:59.000Z

    Industrial production, oil production, oil price and oilvariables in the VAR, oil production quantity as well as oilquarterly global crude oil production, crude oil price and

  17. Distributed Generation Investment by a Microgrid under Uncertainty

    SciTech Connect (OSTI)

    Marnay, Chris; Siddiqui, Afzal; Marnay, Chris

    2008-08-11T23:59:59.000Z

    This paper examines a California-based microgrid?s decision to invest in a distributed generation (DG) unit fuelled by natural gas. While the long-term natural gas generation cost is stochastic, we initially assume that the microgrid may purchase electricity at a fixed retail rate from its utility. Using the real options approach, we find a natural gas generation cost threshold that triggers DG investment. Furthermore, the consideration of operational flexibility by the microgrid increases DG investment, while the option to disconnect from the utility is not attractive. By allowing the electricity price to be stochastic, we next determine an investment threshold boundary and find that high electricity price volatility relative to that of natural gas generation cost delays investment while simultaneously increasing the value of the investment. We conclude by using this result to find the implicit option value of the DG unit when two sources of uncertainty exist.

  18. Optimal Portfolio Selection Under Concave Price Impact

    SciTech Connect (OSTI)

    Ma Jin, E-mail: jinma@usc.edu [University of Southern California, Department of Mathematics (United States); Song Qingshuo, E-mail: songe.qingshuo@cityu.edu.hk [City University of Hong Kong, Department of Mathematics (Hong Kong); Xu Jing, E-mail: xujing8023@yahoo.com.cn [Chongqing University, School of Economics and Business Administration (China); Zhang Jianfeng, E-mail: jianfenz@usc.edu [University of Southern California, Department of Mathematics (United States)

    2013-06-15T23:59:59.000Z

    In this paper we study an optimal portfolio selection problem under instantaneous price impact. Based on some empirical analysis in the literature, we model such impact as a concave function of the trading size when the trading size is small. The price impact can be thought of as either a liquidity cost or a transaction cost, but the concavity nature of the cost leads to some fundamental difference from those in the existing literature. We show that the problem can be reduced to an impulse control problem, but without fixed cost, and that the value function is a viscosity solution to a special type of Quasi-Variational Inequality (QVI). We also prove directly (without using the solution to the QVI) that the optimal strategy exists and more importantly, despite the absence of a fixed cost, it is still in a 'piecewise constant' form, reflecting a more practical perspective.

  19. A simplified approach to quantifying predictive and parametric uncertainty in artificial neural network hydrologic models

    E-Print Network [OSTI]

    Chaubey, Indrajeet

    considerable interest in developing methods for uncertainty analysis of artificial neural network (ANN) models and parametric uncertainty in artificial neural network hydrologic models, Water Resour. Res., 43, W10407, doi:10A simplified approach to quantifying predictive and parametric uncertainty in artificial neural

  20. Texas Farm Commodity Prices

    E-Print Network [OSTI]

    Childs, V. C. (Virgil C.); Schlotzhauer, Elbert O.; McNeely, John G.

    1948-01-01T23:59:59.000Z

    1" .I61 .I72 .I64 .I87 .276 .320 .356 .349 .220 .207 .213 .217 .270 ,261 .207 .239 .247 .207 .I38 .I02 108 .I46 .206 Wheat Dollars .99 .94 "93 .87 .90 1.06 1.29 2.18 2.08 2.06 2.04 1.09 1.03 .98 1.14 1.57 1.15... markets on or about the 15th of each month. Since, for most products, sales seldom occur at the farm, the prices which farmers receive usually include the cost of handling and delivery to the local market. Sonic trrick crops, notably carrots...

  1. Utility Maximization under Uncertainty

    E-Print Network [OSTI]

    Li, Jian

    2010-01-01T23:59:59.000Z

    Motivated by several search and optimization problems over uncertain datasets, we study the stochastic versions of a broad class of combinatorial problems where either the existences or the weights of the elements in the input dataset are uncertain. The class of problems that we study includes shortest paths, minimum weight spanning trees, and minimum weight matchings over probabilistic graphs; top-k queries over probabilistic datasets; and other combinatorial problems like knapsack. By noticing that the expected value is inadequate in capturing different types of risk-averse or risk-prone behaviors, we consider a more general objective which is to maximize the expected utility of the solution for some given utility function. For weight uncertainty model, we show that we can obtain a polynomial time approximation algorithm with additive error eps for any eps>0, if there is a pseudopolynomial time algorithm for the exact version of the problem. Our result generalizes several prior works on stochastic shortest ...

  2. Determining Price Reasonableness in Federal ESPCs

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    of effort expected. Prices for performance-period services cover mainly labor hours. Preventive maintenance and R&R prices also include replacement parts. A primary standard...

  3. Nonlinear Pricing in Energy and Environmental Markets

    E-Print Network [OSTI]

    Ito, Koichiro

    2011-01-01T23:59:59.000Z

    of households know their marginal price of electricity, andhouseholds experience substantially different nonlinear electricity pricehouseholds experience substantially different nonlinear electricity price

  4. Guidance on Life-Cycle Cost Analysis Required by Executive Order...

    Energy Savers [EERE]

    Documents & Publications Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2010 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis -...

  5. Cost uncertainty for different levels of technology maturity

    SciTech Connect (OSTI)

    DeMuth, S.F. [Los Alamos National Lab., NM (United States); Franklin, A.L. [Pacific Northwest National Lab., Richland, WA (United States)

    1996-08-07T23:59:59.000Z

    It is difficult at best to apply a single methodology for estimating cost uncertainties related to technologies of differing maturity. While highly mature technologies may have significant performance and manufacturing cost data available, less well developed technologies may be defined in only conceptual terms. Regardless of the degree of technical maturity, often a cost estimate relating to application of the technology may be required to justify continued funding for development. Yet, a cost estimate without its associated uncertainty lacks the information required to assess the economic risk. For this reason, it is important for the developer to provide some type of uncertainty along with a cost estimate. This study demonstrates how different methodologies for estimating uncertainties can be applied to cost estimates for technologies of different maturities. For a less well developed technology an uncertainty analysis of the cost estimate can be based on a sensitivity analysis; whereas, an uncertainty analysis of the cost estimate for a well developed technology can be based on an error propagation technique from classical statistics. It was decided to demonstrate these uncertainty estimation techniques with (1) an investigation of the additional cost of remediation due to beyond baseline, nearly complete, waste heel retrieval from underground storage tanks (USTs) at Hanford; and (2) the cost related to the use of crystalline silico-titanate (CST) rather than the baseline CS100 ion exchange resin for cesium separation from UST waste at Hanford.

  6. Uncertainty estimates for derivatives and intercepts

    SciTech Connect (OSTI)

    Clark, E.L.

    1990-01-01T23:59:59.000Z

    Straight line least squares fits of experimental data are widely used in the analysis of test results to provide derivatives and intercepts. A method for evaluating the uncertainty in these parameters is described. The method utilizes conventional least squares results and is applicable to experiments where the independent variable is controlled, but not necessarily free of error. A Monte Carlo verification of the method is given 7 refs., 2 tabs.

  7. Measurement uncertainty of adsorption testing of desiccant materials

    SciTech Connect (OSTI)

    Bingham, C E; Pesaran, A A

    1988-12-01T23:59:59.000Z

    The technique of measurement uncertainty analysis as described in the current ANSI/ASME standard is applied to the testing of desiccant materials in SERI`s Sorption Test Facility. This paper estimates the elemental precision and systematic errors in these tests and propagates them separately to obtain the resulting uncertainty of the test parameters, including relative humidity ({plus_minus}.03) and sorption capacity ({plus_minus}.002 g/g). Errors generated by instrument calibration, data acquisition, and data reduction are considered. Measurement parameters that would improve the uncertainty of the results are identified. Using the uncertainty in the moisture capacity of a desiccant, the design engineer can estimate the uncertainty in performance of a dehumidifier for desiccant cooling systems with confidence. 6 refs., 2 figs., 8 tabs.

  8. Analyzing reliability of virtual machine instances with dynamic pricing in the public cloud

    SciTech Connect (OSTI)

    Lim, Seung-Hwan [ORNL; Thakur, Gautam [ORNL; Horey, James L [ORNL

    2014-01-01T23:59:59.000Z

    This study presents reliability analysis of virtual machine instances in public cloud environments in the face of dynamic pricing. Different from traditional fixed pricing, dynamic pricing allows price to dynamically fluctuate over arbitrary period of time according to external factors such as supply and demand, excess capacity, etc. This pricing option introduces a new type of fault: virtual machine instances may be unexpectedly terminated due to conflicts in the original bid price and the current offered price. This new class of fault under dynamic pricing may be more dominant than traditional faults in cloud computing environments, where resource availability associated with traditional faults is often above 99.9%. To address and understand this new type of fault, we translated two classic reliability metrics, mean time between failures and availability, to the Amazon Web Services spot market using historical price data. We also validated our findings by submitting actual bids in the spot market. We found that overall, our historical analysis and experimental validation lined up well. Based upon these experimental results, we also provided suggestions and techniques to maximize overall reliability of virtual machine instances under dynamic pricing.

  9. A FRAMEWORK FOR TRANSMISSION CONGESTION MANAGEMENT ANALYSIS MINGHAI LIU

    E-Print Network [OSTI]

    Gross, George

    congestion, the market-based mechanisms using the locational marginal prices (LMPs) have become the most transmission services and compute the pricing for those services. The inherent volatility of electricity markets introduces uncertainty in the LMPs and consequently, in transmission pricing. In order to protect

  10. Uncertainty Quantification of Calculated Temperatures for the AGR-1 Experiment

    SciTech Connect (OSTI)

    Binh T. Pham; Jeffrey J. Einerson; Grant L. Hawkes

    2012-04-01T23:59:59.000Z

    This report documents an effort to quantify the uncertainty of the calculated temperature data for the first Advanced Gas Reactor (AGR-1) fuel irradiation experiment conducted in the INL's Advanced Test Reactor (ATR) in support of the Next Generation Nuclear Plant (NGNP) R&D program. Recognizing uncertainties inherent in physics and thermal simulations of the AGR-1 test, the results of the numerical simulations can be used in combination with the statistical analysis methods to improve qualification of measured data. Additionally, the temperature simulation data for AGR tests can be used for validation of the fuel transport and fuel performance simulation models. The crucial roles of the calculated fuel temperatures in ensuring achievement of the AGR experimental program objectives require accurate determination of the model temperature uncertainties. The report is organized into three chapters. Chapter 1 introduces the AGR Fuel Development and Qualification program and provides overviews of AGR-1 measured data, AGR-1 test configuration and test procedure, and thermal simulation. Chapters 2 describes the uncertainty quantification procedure for temperature simulation data of the AGR-1 experiment, namely, (i) identify and quantify uncertainty sources; (ii) perform sensitivity analysis for several thermal test conditions; (iii) use uncertainty propagation to quantify overall response temperature uncertainty. A set of issues associated with modeling uncertainties resulting from the expert assessments are identified. This also includes the experimental design to estimate the main effects and interactions of the important thermal model parameters. Chapter 3 presents the overall uncertainty results for the six AGR-1 capsules. This includes uncertainties for the daily volume-average and peak fuel temperatures, daily average temperatures at TC locations, and time-average volume-average and time-average peak fuel temperatures.

  11. Energy Price Indices and Discount Factors for Life-Cycle Cost...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Life-Cycle Cost Analysis - 2015 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2015 Handbook describes the annual supplements to the NIST Handbook 135 and...

  12. Energy Price Indices and Discount Factors for Life-Cycle Cost...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    2 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2012 Report provides tables of present-value factors for use in the life-cycle cost analysis of capital...

  13. Applying uncertainty quantification to multiphase flow computational fluid dynamics

    SciTech Connect (OSTI)

    Gel, A.; Garg, R.; Tong, C.; Shahnam, M.; Guenther, C.

    2013-07-01T23:59:59.000Z

    Multiphase computational fluid dynamics plays a major role in design and optimization of fossil fuel based reactors. There is a growing interest in accounting for the influence of uncertainties associated with physical systems to increase the reliability of computational simulation based engineering analysis. The U.S. Department of Energy's National Energy Technology Laboratory (NETL) has recently undertaken an initiative to characterize uncertainties associated with computer simulation of reacting multiphase flows encountered in energy producing systems such as a coal gasifier. The current work presents the preliminary results in applying non-intrusive parametric uncertainty quantification and propagation techniques with NETL's open-source multiphase computational fluid dynamics software MFIX. For this purpose an open-source uncertainty quantification toolkit, PSUADE developed at the Lawrence Livermore National Laboratory (LLNL) has been interfaced with MFIX software. In this study, the sources of uncertainty associated with numerical approximation and model form have been neglected, and only the model input parametric uncertainty with forward propagation has been investigated by constructing a surrogate model based on data-fitted response surface for a multiphase flow demonstration problem. Monte Carlo simulation was employed for forward propagation of the aleatory type input uncertainties. Several insights gained based on the outcome of these simulations are presented such as how inadequate characterization of uncertainties can affect the reliability of the prediction results. Also a global sensitivity study using Sobol' indices was performed to better understand the contribution of input parameters to the variability observed in response variable.

  14. Price determination for breeding bulls

    E-Print Network [OSTI]

    Namken, Jerry Carl

    1987-01-01T23:59:59.000Z

    of Oammittee) Ra A. ietrzch C. J ~) Daru. I (Heai of August l987 Price Detezlainatian for Breeding Bulls. (August 1987) Jerry Carl Namkan, B. S. , Texas A&M University; Chair of Advisory Committee: Dr. Donald E. Ferris A study using two different data... sets was conducted to determine the factors affecting the price of zmg~ Hereford hulls. In the first data set, both ~ and lagged national ~ feeder steer, utility cow, and crude oil prices, and net farm income were analyzed in a regzmsion procedure...

  15. Edgeworth Cycles and Focal Prices: Computational Dynamic Markov Equilibria

    E-Print Network [OSTI]

    Noel, Michael D.

    2004-01-01T23:59:59.000Z

    1993). “Gas Wars: Retail Gasoline Price Fluctuations”,Price Cycles: Firm Interaction in the Toronto Retail GasolinePrice Cycles, Cost-based Pricing and Sticky Pricing in Retail Gasoline

  16. Predictability of price movements in deregulated electricity markets

    E-Print Network [OSTI]

    Uritskaya, Olga Y

    2015-01-01T23:59:59.000Z

    In this paper we investigate predictability of electricity prices in the Canadian provinces of Alberta and Ontario, as well as in the US Mid-C market. Using scale-dependent detrended fluctuation analysis, spectral analysis, and the probability distribution analysis we show that the studied markets exhibit strongly anti-persistent properties suggesting that their dynamics can be predicted based on historic price records across the range of time scales from one hour to one month. For both Canadian markets, the price movements reveal three types of correlated behavior which can be used for forecasting. The discovered scenarios remain the same on different time scales up to one month as well as for on- and off- peak electricity data. These scenarios represent sharp increases of prices and are not present in the Mid-C market due to its lower volatility. We argue that extreme price movements in this market should follow the same tendency as the more volatile Canadian markets. The estimated values of the Pareto indi...

  17. Calibration and Measurement Uncertainty Estimation of Radiometric Data: Preprint

    SciTech Connect (OSTI)

    Habte, A.; Sengupta, M.; Reda, I.; Andreas, A.; Konings, J.

    2014-11-01T23:59:59.000Z

    Evaluating the performance of photovoltaic cells, modules, and arrays that form large solar deployments relies on accurate measurements of the available solar resource. Therefore, determining the accuracy of these solar radiation measurements provides a better understanding of investment risks. This paper provides guidelines and recommended procedures for estimating the uncertainty in calibrations and measurements by radiometers using methods that follow the International Bureau of Weights and Measures Guide to the Expression of Uncertainty (GUM). Standardized analysis based on these procedures ensures that the uncertainty quoted is well documented.

  18. Investors' horizon and stock prices

    E-Print Network [OSTI]

    Parsa, Sahar

    2011-01-01T23:59:59.000Z

    This dissertation consists of three essays on the relation between investors' trading horizon and stock prices. The first chapter explores the theoretical relation between the horizon of traders and the negative externality ...

  19. Table 1. Crude Oil Prices

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    can be the month of loading, the month of landing, or sometime between those events. Prices for crude oil can be determined at a time other than the acquisition date. See the...

  20. Figure 4. World Oil Prices

    U.S. Energy Information Administration (EIA) Indexed Site

    4. World Oil Prices" " (2007 dollars per barrel)" ,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023,2024,2025,2026,2027,2028,2029,2030...