National Library of Energy BETA

Sample records for analysis price uncertainty

  1. Market Prices and Uncertainty Report

    Reports and Publications (EIA)

    2016-01-01

    Monthly analysis of crude oil, petroleum products, natural gas, and propane prices is released as a regular supplement to the Short-Term Energy Outlook.

  2. Microsoft Word - Price Uncertainty Supplement.doc

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

    November 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 November 9, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged almost $82 per barrel in October, about $7 per barrel higher than the September average, as expectations of higher oil demand pushed up prices. EIA has raised the average fourth quarter 2010 WTI spot price forecast to about $83 per barrel compared with $79 per barrel in last monthʹs Outlook. WTI spot prices rise to $87 per

  3. Microsoft Word - Price Uncertainty Supplement .docx

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

    1 1 January 2011 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 January 11, 2011 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged over $89 per barrel in December, about $5 per barrel higher than the November average. Expectations of higher oil demand, combined with unusually cold weather in both Europe and the U.S. Northeast, contributed to prices. EIA has raised the first quarter 2011 WTI spot price forecast by $8 per barrel

  4. Microsoft Word - Price Uncertainty Supplement.doc

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

    0 1 August 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 August 10, 2010 Release WTI crude oil spot prices averaged $76.32 per barrel in July 2010 or about $1 per barrel above the prior month's average, and close to the $77 per barrel projected in last month's Outlook. EIA projects WTI prices will average about $80 per barrel over the second half of this year and rise to $85 by the end of next year (West Texas Intermediate Crude Oil Price Chart). Energy price

  5. Microsoft Word - Price Uncertainty Supplement.doc

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

    December 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 December 7, 2010 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged over $84 per barrel in November, more than $2 per barrel higher than the October average. EIA has raised the average winter 2010-2011 period WTI spot price forecast by $1 per barrel from the last monthʹs Outlook to $84 per barrel. WTI spot prices rise to $89 per barrel by the end of next year, $2 per

  6. Microsoft Word - Price Uncertainty Supplement.doc

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

    0 1 July 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 July 7, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $75.34 per barrel in June 2010 ($1.60 per barrel above the prior month's average), close to the $76 per barrel projected in the forecast in last month's Outlook. EIA projects WTI prices will average about $79 per barrel over the second half of this year and rise to $84 by the end of next year (West Texas Intermediate Crude Oil Price

  7. Microsoft Word - Price Uncertainty Supplement.doc

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

    March 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 March 9, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $76.39 per barrel in February 2010, almost $2 per barrel lower than the prior month's average and very near the $76 per barrel forecast in last month's Outlook. Last month, the WTI spot price reached a low of $71.15 on February 5 and peaked at $80.04 on February 22. EIA expects WTI prices to average above $80 per barrel this spring,

  8. Microsoft Word - Price Uncertainty Supplement.doc

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

    April 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 April 6, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $81 per barrel in March 2010, almost $5 per barrel above the prior month's average and $3 per barrel higher than forecast in last month's Outlook. Oil prices rose from a low this year of $71.15 per barrel on February 5 to $80 per barrel by the end of February, generally on news of robust economic and energy demand growth in non-OECD

  9. Microsoft Word - Price Uncertainty Supplement.doc

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

    May 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 May 11, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $84 per barrel in April 2010, about $3 per barrel above the prior month's average and $2 per barrel higher than forecast in last month's Outlook. EIA projects WTI prices will average about $84 per barrel over the second half of this year and rise to $87 by the end of next year, an increase of about $2 per barrel from the previous Outlook

  10. Microsoft Word - Price Uncertainty Supplement.doc

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

    0 1 September 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 September 8, 2010 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged about $77 per barrel in August 2010, very close to the July average, but $3 per barrel lower than projected in last month's Outlook. WTI spot prices averaged almost $82 per barrel over the first 10 days of August but then fell by $9 per barrel over the next 2 weeks as the market reacted to a series

  11. Uncertainty Analysis

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

    Analysis - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion ...

  12. Uncertainty Analysis

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

    Analysis - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel Cycle Defense Waste Management Programs Advanced Nuclear Energy

  13. Sensitivity and Uncertainty Analysis

    Broader source: Energy.gov [DOE]

    Summary Notes from 15 November 2007 Generic Technical Issue Discussion on Sensitivity and Uncertainty Analysis and Model Support

  14. Microsoft Word - Price Uncertainty Supplement.doc

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

    an unusually severe hurricane outlook, financial-market uncertainty in Europe and China, ... Mid-way into the month, energy futures, commodities and securities were sold, as financial...

  15. Uncertainty Analysis Technique for OMEGA Dante Measurements ...

    Office of Scientific and Technical Information (OSTI)

    Uncertainty Analysis Technique for OMEGA Dante Measurements Citation Details In-Document Search Title: Uncertainty Analysis Technique for OMEGA Dante Measurements You are...

  16. ENHANCED UNCERTAINTY ANALYSIS FOR SRS COMPOSITE ANALYSIS

    SciTech Connect (OSTI)

    Smith, F.; Phifer, M.

    2011-06-30

    The Composite Analysis (CA) performed for the Savannah River Site (SRS) in 2009 (SRS CA 2009) included a simplified uncertainty analysis. The uncertainty analysis in the CA (Smith et al. 2009b) was limited to considering at most five sources in a separate uncertainty calculation performed for each POA. To perform the uncertainty calculations in a reasonable amount of time, the analysis was limited to using 400 realizations, 2,000 years of simulated transport time, and the time steps used for the uncertainty analysis were increased from what was used in the CA base case analysis. As part of the CA maintenance plan, the Savannah River National Laboratory (SRNL) committed to improving the CA uncertainty/sensitivity analysis. The previous uncertainty analysis was constrained by the standard GoldSim licensing which limits the user to running at most four Monte Carlo uncertainty calculations (also called realizations) simultaneously. Some of the limitations on the number of realizations that could be practically run and the simulation time steps were removed by building a cluster of three HP Proliant windows servers with a total of 36 64-bit processors and by licensing the GoldSim DP-Plus distributed processing software. This allowed running as many as 35 realizations simultaneously (one processor is reserved as a master process that controls running the realizations). These enhancements to SRNL computing capabilities made uncertainty analysis: using 1000 realizations, using the time steps employed in the base case CA calculations, with more sources, and simulating radionuclide transport for 10,000 years feasible. In addition, an importance screening analysis was performed to identify the class of stochastic variables that have the most significant impact on model uncertainty. This analysis ran the uncertainty model separately testing the response to variations in the following five sets of model parameters: (a) K{sub d} values (72 parameters for the 36 CA elements in sand and clay), (b) Dose Parameters (34 parameters), (c) Material Properties (20 parameters), (d) Surface Water Flows (6 parameters), and (e) Vadose and Aquifer Flow (4 parameters). Results provided an assessment of which group of parameters is most significant in the dose uncertainty. It was found that K{sub d} and the vadose/aquifer flow parameters, both of which impact transport timing, had the greatest impact on dose uncertainty. Dose parameters had an intermediate level of impact while material properties and surface water flows had little impact on dose uncertainty. Results of the importance analysis are discussed further in Section 7 of this report. The objectives of this work were to address comments received during the CA review on the uncertainty analysis and to demonstrate an improved methodology for CA uncertainty calculations as part of CA maintenance. This report partially addresses the LFRG Review Team issue of producing an enhanced CA sensitivity and uncertainty analysis. This is described in Table 1-1 which provides specific responses to pertinent CA maintenance items extracted from Section 11 of the SRS CA (2009). As noted above, the original uncertainty analysis looked at each POA separately and only included the effects from at most five sources giving the highest peak doses at each POA. Only 17 of the 152 CA sources were used in the original uncertainty analysis and the simulation time was reduced from 10,000 to 2,000 years. A major constraint on the original uncertainty analysis was the limitation of only being able to use at most four distributed processes. This work expanded the analysis to 10,000 years using 39 of the CA sources, included cumulative dose effects at downstream POAs, with more realizations (1,000) and finer time steps. This was accomplished by using the GoldSim DP-Plus module and the 36 processors available on a new windows cluster. The last part of the work looked at the contribution to overall uncertainty from the main categories of uncertainty variables: K{sub d}s, dose parameters, flow parameters, and material propertie

  17. Sensitivity and Uncertainty Analysis Shell

    Energy Science and Technology Software Center (OSTI)

    1999-04-20

    SUNS (Sensitivity and Uncertainty Analysis Shell) is a 32-bit application that runs under Windows 95/98 and Windows NT. It is designed to aid in statistical analyses for a broad range of applications. The class of problems for which SUNS is suitable is generally defined by two requirements: 1. A computer code is developed or acquired that models some processes for which input is uncertain and the user is interested in statistical analysis of the outputmoreof that code. 2. The statistical analysis of interest can be accomplished using the Monte Carlo analysis. The implementation then requires that the user identify which input to the process model is to be manipulated for statistical analysis. With this information, the changes required to loosely couple SUNS with the process model can be completed. SUNS is then used to generate the required statistical sample and the user-supplied process model analyses the sample. The SUNS post processor displays statistical results from any existing file that contains sampled input and output values.less

  18. Cost Analysis: Technology, Competitiveness, Market Uncertainty | Department

    Office of Environmental Management (EM)

    of Energy Technology to Market » Cost Analysis: Technology, Competitiveness, Market Uncertainty Cost Analysis: Technology, Competitiveness, Market Uncertainty As a basis for strategic planning, competitiveness analysis, funding metrics and targets, SunShot supports analysis teams at national laboratories to assess technology costs, location-specific competitive advantages, policy impacts on system financing, and to perform detailed levelized cost of energy (LCOE) analyses. This shows the

  19. Subject: Cost and Price Analysis | Department of Energy

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

    Subject: Cost and Price Analysis Subject: Cost and Price Analysis PDF icon Subject: Cost and Price Analysis More Documents & Publications Subject: Cost and Price Analysis Policy Flash 2013-78 Acquisition Guide Chapter 7.3 Acquisition Planning in the M&O Environment Policy Flash 2013-30 Acquisition Letter on Acquisition Planning Considerations for Management and Operating Contracts

  20. Uncertainty Analysis for Photovoltaic Degradation Rates (Poster)

    SciTech Connect (OSTI)

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

    2014-04-01

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

    Office of Environmental Management (EM)

    Analysis and Decision-Making Under Uncertainty: A Strategy and its Applications Risk Analysis and Decision-Making Under Uncertainty: A Strategy and its Applications Ming Ye...

  2. October 16, 2014 Webinar - Decisional Analysis under Uncertainty |

    Energy Savers [EERE]

    Department of Energy 6, 2014 Webinar - Decisional Analysis under Uncertainty October 16, 2014 Webinar - Decisional Analysis under Uncertainty Webinar - October 16, 2014, 11 am - 12:40 pm EDT: Dr. Paul Black (Neptune, Inc), Decisional Analysis under Uncertainty PDF icon Agenda - October 16, 2014 - P&RA CoP Webinar PDF icon Presentation - Decision Making under Uncertainty: Introduction to Structured Decision Analysis for Performance Assessments More Documents & Publications Status

  3. Analysis of Price Volatility in Natural Gas Markets

    Reports and Publications (EIA)

    2007-01-01

    This article presents an analysis of price volatility in the spot natural gas market, with particular emphasis on the Henry Hub in Louisiana.

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

    SciTech Connect (OSTI)

    Johnson, Jay Dean; Helton, Jon Craig; Oberkampf, William Louis; Sallaberry, Cedric J.

    2008-08-01

    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.

  5. Measurement uncertainty analysis techniques applied to PV performance measurements

    SciTech Connect (OSTI)

    Wells, C.

    1992-10-01

    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.

  6. PMU Uncertainty Quantification in Voltage Stability Analysis | Argonne

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

    National Laboratory PMU Uncertainty Quantification in Voltage Stability Analysis Title PMU Uncertainty Quantification in Voltage Stability Analysis Publication Type Journal Article Year of Publication 2015 Authors Chen, C, Wang, J, Li, Z, Sun, H, Wang, Z Journal IEEE Transactions on Power Systems Volume 30 Start Page 2196 Issue 4 Pagination 2 Date Published 06162015 Keywords phasor measurement unit, recursive least square, uncertainty, voltage stability Abstract This letter presents an

  7. 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 Abstract - Predicting power for a photovoltaic system from measured irradiance requires a sequence of models, e.g.: translation of measured irradiance to the plane-of-array; estimation of cell temperature; and calculation of module electrical output. Uncertainty in predicted power arises from the aggregate uncertainty

  8. Measurement uncertainty analysis techniques applied to PV performance measurements

    SciTech Connect (OSTI)

    Wells, C.

    1992-10-01

    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. Uncertainty Analysis Technique for OMEGA Dante Measurements (Conference) |

    Office of Scientific and Technical Information (OSTI)

    SciTech Connect Conference: Uncertainty Analysis Technique for OMEGA Dante Measurements Citation Details In-Document Search Title: Uncertainty Analysis Technique for OMEGA Dante Measurements 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

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

    SciTech Connect (OSTI)

    Harper, F.T.; Young, M.L.; Miller, L.A.; Hora, S.C.; Lui, C.H.; Goossens, L.H.J.; Cooke, R.M.; Paesler-Sauer, J.; Helton, J.C.

    1995-01-01

    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.

  11. 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.; Hora, S.C.; Lui, C.H.; Goossens, L.H.J.; Cooke, R.M.; Paesler-Sauer, J.; Helton, J.C.

    1995-01-01

    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.

  12. Uncertainty and sensitivity analysis for photovoltaic system modeling.

    SciTech Connect (OSTI)

    Hansen, Clifford W.; Pohl, Andrew Phillip; Jordan, Dirk

    2013-12-01

    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.

  13. 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.; Harrison, J.D.; Harper, F.T.; Hora, S.C.

    1998-04-01

    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.

  14. Analysis of Federal Subsidies: Implied Price of Carbon

    SciTech Connect (OSTI)

    D. Craig Cooper; Thomas Foulke

    2010-10-01

    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.

  15. The Uncertainty in the Local Seismic Response Analysis

    SciTech Connect (OSTI)

    Pasculli, A.; Pugliese, A.; Romeo, R. W.; Sano, T.

    2008-07-08

    In the present paper is shown the influence on the local seismic response analysis exerted by considering dispersion and uncertainty in the seismic input as well as in the dynamic properties of soils. In a first attempt a 1D numerical model is developed accounting for both the aleatory nature of the input motion and the stochastic variability of the dynamic properties of soils. The seismic input is introduced in a non-conventional way through a power spectral density, for which an elastic response spectrum, derived--for instance--by a conventional seismic hazard analysis, is required with an appropriate level of reliability. The uncertainty in the geotechnical properties of soils are instead investigated through a well known simulation technique (Monte Carlo method) for the construction of statistical ensembles. The result of a conventional local seismic response analysis given by a deterministic elastic response spectrum is replaced, in our approach, by a set of statistical elastic response spectra, each one characterized by an appropriate level of probability to be reached or exceeded. The analyses have been carried out for a well documented real case-study. Lastly, we anticipate a 2D numerical analysis to investigate also the spatial variability of soil's properties.

  16. Microsoft Word - Price Probabilities Supplement.doc

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

    0 1 April 2010 Short-Term Energy Outlook Supplement: Probabilities of Possible Future Prices 1 EIA introduced a monthly analysis of energy price volatility and forecast uncertainty in the October 2009 Short-Term Energy Outlook (STEO). Included in the analysis were charts portraying confidence intervals around the New York Mercantile Exchange (NYMEX) futures prices of West Texas Intermediate (equivalent to light sweet crude oil) and Henry Hub natural gas contracts. The March 2010 STEO added

  17. Uncertainty Quantification

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

    ... Uncertainty Quantification in Electric Grids The analysis and reduction of electric grid models under uncertainty is important to developing robust and reliable smart-grid ...

  18. Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 1: Main report

    SciTech Connect (OSTI)

    Brown, J.; Goossens, L.H.J.; Kraan, B.C.P.

    1997-06-01

    This volume is the first of a two-volume document that summarizes a joint project conducted by the US Nuclear Regulatory Commission and the European Commission 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 document reports on an ongoing project to assess uncertainty in the MACCS and COSYMA calculations for the offsite consequences of radionuclide releases by hypothetical nuclear power plant accidents. A panel of sixteen experts was formed to compile credible and traceable uncertainty distributions for food chain variables that affect calculations of offsite consequences. The expert judgment elicitation procedure and its outcomes are described in these volumes. Other panels were formed to consider uncertainty in other aspects of the codes. Their results are described in companion reports. Volume 1 contains background information and a complete description of the joint consequence uncertainty study. Volume 2 contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures for both panels, (3) the rationales and results for the panels on soil and plant transfer and animal transfer, (4) short biographies of the experts, and (5) the aggregated results of their responses.

  19. 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)

    1997-08-01

    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.

  20. 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.

    2000-11-01

    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.

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

    Office of Environmental Management (EM)

    Applications | Department of Energy Analysis and Decision-Making Under Uncertainty: A Strategy and its Applications Risk Analysis and Decision-Making Under Uncertainty: A Strategy and its Applications Ming Ye (mye@fsu.edu) Florida State University Mary Hill (mchill@ku.edu) University of Kansas This research is supported by DOE Early Career Award: DE-SC0008272 Acknowledge the efforts of ISCMEM Working Group 2- Federal Scientists Working for Coordinated Uncertainty Analysis and Parameter

  2. Fukushima Daiichi unit 1 uncertainty analysis--Preliminary selection of uncertain parameters and analysis methodology

    SciTech Connect (OSTI)

    Cardoni, Jeffrey N.; Kalinich, Donald A.

    2014-02-01

    Sandia National Laboratories (SNL) plans to conduct uncertainty analyses (UA) on the Fukushima Daiichi unit (1F1) plant with the MELCOR code. The model to be used was developed for a previous accident reconstruction investigation jointly sponsored by the US Department of Energy (DOE) and Nuclear Regulatory Commission (NRC). However, that study only examined a handful of various model inputs and boundary conditions, and the predictions yielded only fair agreement with plant data and current release estimates. The goal of this uncertainty study is to perform a focused evaluation of uncertainty in core melt progression behavior and its effect on key figures-of-merit (e.g., hydrogen production, vessel lower head failure, etc.). In preparation for the SNL Fukushima UA work, a scoping study has been completed to identify important core melt progression parameters for the uncertainty analysis. The study also lays out a preliminary UA methodology.

  3. Techno-economic and uncertainty analysis of in situ and ex situ fast pyrolysis for biofuel production

    SciTech Connect (OSTI)

    Li, Boyan; Ou, Longwen; Dang, Qi; Meyer, Pimphan A.; Jones, Susanne B.; Brown, Robert C.; Wright, Mark

    2015-11-01

    This study evaluates the techno-economic uncertainty in cost estimates for two emerging biorefinery technologies for biofuel production: in situ and ex situ catalytic pyrolysis. Stochastic simulations based on process and economic parameter distributions are applied to calculate biorefinery performance and production costs. The probability distributions for the minimum fuel-selling price (MFSP) indicate that in situ catalytic pyrolysis has an expected MFSP of $4.20 per gallon with a standard deviation of 1.15, while the ex situ catalytic pyrolysis has a similar MFSP with a smaller deviation ($4.27 per gallon and 0.79 respectively). These results suggest that a biorefinery based on ex situ catalytic pyrolysis could have a lower techno-economic risk than in situ pyrolysis despite a slightly higher MFSP cost estimate. Analysis of how each parameter affects the NPV indicates that internal rate of return, feedstock price, total project investment, electricity price, biochar yield and bio-oil yield are significant parameters which have substantial impact on the MFSP for both in situ and ex situ catalytic pyrolysis.

  4. Uncertainty Analysis of RELAP5-3D

    SciTech Connect (OSTI)

    Alexandra E Gertman; Dr. George L Mesina

    2012-07-01

    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 INLs massively parallel cluster system. Data from the studies was collected and analyzed with SAS. A summary of the results of our studies are presented.

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

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

    2015 | Department of Energy Price Indices and Discount Factors for 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 NBS Special Publication 709. PDF icon ashb15.pdf More Documents & Publications Guidance on Life-Cycle Cost Analysis Required by Executive Order 13123 Vehicle Technologies Office Merit Review 2015: Fuel-Neutral Studies of Particulate Matter

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

    SciTech Connect (OSTI)

    Wells, C.V.

    1992-11-01

    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.

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

    SciTech Connect (OSTI)

    Wells, C.V.

    1992-11-01

    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. 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

    2014-02-01

    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 Commissions 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).

  9. 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.

    1995-01-01

    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.

  10. 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.

    2012-06-01

    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.

  11. An Analysis of Residential PV System Price Differences between the United

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

    States and Germany | Department of Energy An Analysis of Residential PV System Price Differences between the United States and Germany An Analysis of Residential PV System Price Differences between the United States and Germany 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

  12. 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.

    2006-06-01

    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.

  13. 2007 Wholesale Power Rate Case Final Proposal : Market Price Forecast Study.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    2006-07-01

    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.

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

    SciTech Connect (OSTI)

    Tuenge, Jason R.

    2013-10-01

    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.

  15. PROBABILISTIC SENSITIVITY AND UNCERTAINTY ANALYSIS WORKSHOP SUMMARY REPORT

    SciTech Connect (OSTI)

    Seitz, R

    2008-06-25

    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.

  16. Analysis and Reduction of Complex Networks Under Uncertainty.

    SciTech Connect (OSTI)

    Ghanem, Roger G

    2014-07-31

    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.

  17. Uncertainty analysis of multi-rate kinetics of uranium desorption from

    Office of Scientific and Technical Information (OSTI)

    sediments (Journal Article) | SciTech Connect SciTech Connect Search Results Journal Article: Uncertainty analysis of multi-rate kinetics of uranium desorption from sediments Citation Details In-Document Search Title: Uncertainty analysis of multi-rate kinetics of uranium desorption from sediments 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

  18. The IAEA Coordinated Research Program on HTGR Uncertainty Analysis: Phase I Status and Initial Results

    SciTech Connect (OSTI)

    Strydom, Gerhard; Bostelmann, Friederike; Ivanov, Kostadin

    2014-10-01

    The continued development of High Temperature Gas Cooled Reactors (HTGRs) requires verification of HTGR design and safety features with reliable high fidelity physics models and robust, efficient, and accurate codes. One way to address the uncertainties in the HTGR analysis tools is to assess the sensitivity of critical parameters (such as the calculated maximum fuel temperature during loss of coolant accidents) to a few important input uncertainties. The input parameters were identified by engineering judgement in the past but are today typically based on a Phenomena Identification Ranking Table (PIRT) process. The input parameters can also be derived from sensitivity studies and are then varied in the analysis to find a spread in the parameter of importance. However, there is often no easy way to compensate for these uncertainties. In engineering system design, a common approach for addressing performance uncertainties is to add compensating margins to the system, but with passive properties credited it is not so clear how to apply it in the case of modular HTGR heat removal path. Other more sophisticated uncertainty modelling approaches, including Monte Carlo analysis, have also been proposed and applied. Ideally one wishes 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. Therefore some safety analysis calculations may use a mixture of these approaches for different parameters depending upon the particular requirements of the analysis problem involved. Sensitivity analysis can for example be used to provide information as part of an uncertainty analysis to determine best estimate plus uncertainty results to the required confidence level. In order to address uncertainty propagation in analysis and methods in the HTGR community the IAEA initiated a Coordinated Research Project (CRP) on the HTGR Uncertainty Analysis in Modelling (UAM) that officially started in 2013. Although this project focuses specifically on the peculiarities of HTGR designs and its simulation requirements, many lessons can be learned from the LWR community and the significant progress already made towards a consistent methodology uncertainty analysis. In the case of LWRs the NRC has already in 1988 amended 10 CFR 50.46 to allow best-estimate (plus uncertainties) calculations of emergency core cooling system performance. The Nuclear Energy Agency (NEA) of the Organization for Economic Co-operation and Development (OECD) also established an Expert Group on "Uncertainty Analysis in Modelling" which finally led to the definition of the "Benchmark for Uncertainty Analysis in Modelling (UAM) for Design, Operation and Safety Analysis of LWRs". The CRP on HTGR UAM will follow as far as possible the on-going OECD Light Water Reactor UAM benchmark activity.

  19. Use of SUSA in Uncertainty and Sensitivity Analysis for INL VHTR Coupled Codes

    SciTech Connect (OSTI)

    Gerhard Strydom

    2010-06-01

    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 fr 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 interim milestone report provides an overview of the current status of the implementation and testing of SUSA at the INL VHTR Project Office.

  20. 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.

    2001-11-09

    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.

  1. Large-Scale Transport Model Uncertainty and Sensitivity Analysis: Distributed Sources in Complex Hydrogeologic Systems

    SciTech Connect (OSTI)

    Sig Drellack, Lance Prothro

    2007-12-01

    The Underground Test Area (UGTA) Project of the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office is in the process of assessing and developing regulatory decision options based on modeling predictions of contaminant transport from underground testing of nuclear weapons at the Nevada Test Site (NTS). The UGTA Project is attempting to develop an effective modeling strategy that addresses and quantifies multiple components of uncertainty including natural variability, parameter uncertainty, conceptual/model uncertainty, and decision uncertainty in translating model results into regulatory requirements. The modeling task presents multiple unique challenges to the hydrological sciences as a result of the complex fractured and faulted hydrostratigraphy, the distributed locations of sources, the suite of reactive and non-reactive radionuclides, and uncertainty in conceptual models. Characterization of the hydrogeologic system is difficult and expensive because of deep groundwater in the arid desert setting and the large spatial setting of the NTS. Therefore, conceptual model uncertainty is partially addressed through the development of multiple alternative conceptual models of the hydrostratigraphic framework and multiple alternative models of recharge and discharge. Uncertainty in boundary conditions is assessed through development of alternative groundwater fluxes through multiple simulations using the regional groundwater flow model. Calibration of alternative models to heads and measured or inferred fluxes has not proven to provide clear measures of model quality. Therefore, model screening by comparison to independently-derived natural geochemical mixing targets through cluster analysis has also been invoked to evaluate differences between alternative conceptual models. Advancing multiple alternative flow models, sensitivity of transport predictions to parameter uncertainty is assessed through Monte Carlo simulations. The simulations are challenged by the distributed sources in each of the Corrective Action Units, by complex mass transfer processes, and by the size and complexity of the field-scale flow models. An efficient methodology utilizing particle tracking results and convolution integrals provides in situ concentrations appropriate for Monte Carlo analysis. Uncertainty in source releases and transport parameters including effective porosity, fracture apertures and spacing, matrix diffusion coefficients, sorption coefficients, and colloid load and mobility are considered. With the distributions of input uncertainties and output plume volumes, global analysis methods including stepwise regression, contingency table analysis, and classification tree analysis are used to develop sensitivity rankings of parameter uncertainties for each model considered, thus assisting a variety of decisions.

  2. Determining Price Reasonableness in Federal ESPCs

    SciTech Connect (OSTI)

    Shonder, J.A.

    2005-03-08

    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.

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

    SciTech Connect (OSTI)

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

    2012-11-01

    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.

  4. 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

    2014-02-01

    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)

  5. Probabilities of Possible Future Prices (Released in the STEO April 2010)

    Reports and Publications (EIA)

    2010-01-01

    The Energy Information Administration introduced a monthly analysis of energy price volatility and forecast uncertainty in the October 2009 Short-Term Energy Outlook (STEO). Included in the analysis were charts portraying confidence intervals around the New York Mercantile Exchange (NYMEX) futures prices of West Texas Intermediate (equivalent to light sweet crude oil) and Henry Hub natural gas contracts.

  6. Implementation of a Bayesian Engine for Uncertainty Analysis

    SciTech Connect (OSTI)

    Leng Vang; Curtis Smith; Steven Prescott

    2014-08-01

    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.

  7. Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2015

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

    NISTIR 85-3273-30 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2015 Annual Supplement to NIST Handbook 135 Priya D. Lavappa Joshua D. Kneifel This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.IR.85-3273-30 U.S. DEPARTMENT OF COMMERCE Technology Administration National Institute of Standards and Technology Prepared for United States Department of Energy Federal Energy Management Program April 2005 NISTIR 85-3273-30 Energy Price Indices

  8. An Analysis of Residential PV System Price Differences between...

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

    Date March 2014 Topic Financing, Incentives and Market Analysis; Planning, Zoning, Permitting & Interconnection Subprogram Soft Costs Author Lawrence Berkeley National Laboratory ...

  9. Effect of soil property uncertainties on permafrost thaw projections: A calibration-constrained analysis

    SciTech Connect (OSTI)

    Harp, D. R.; Atchley, A. L.; Painter, S. L.; Coon, E. T.; Wilson, C. J.; Romanovsky, V. E.; Rowland, J. C.

    2015-06-29

    The effect of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The Null-Space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of intra-annual uncertainty due to soil properties and the inter-annual variability due to year to year differences in CESM climate forcings. After calibrating to borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant intra-annual uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Intra-annual uncertainties in projected soil moisture content and Stefan number are small. A volume and time integrated Stefan number decreases significantly in the future climate, indicating that latent heat of phase change becomes more important than heat conduction in future climates. Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.

  10. Effect of soil property uncertainties on permafrost thaw projections: A calibration-constrained analysis

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Harp, D. R.; Atchley, A. L.; Painter, S. L.; Coon, E. T.; Wilson, C. J.; Romanovsky, V. E.; Rowland, J. C.

    2015-06-29

    The effect of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The Null-Space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows formore » the evaluation of intra-annual uncertainty due to soil properties and the inter-annual variability due to year to year differences in CESM climate forcings. After calibrating to borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant intra-annual uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Intra-annual uncertainties in projected soil moisture content and Stefan number are small. A volume and time integrated Stefan number decreases significantly in the future climate, indicating that latent heat of phase change becomes more important than heat conduction in future climates. Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.« less

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

    SciTech Connect (OSTI)

    Tuenge, J. R.

    2013-10-01

    Report to help utilities and energy efficiency organizations forecast the order in which important SSL applications will become cost-effective and estimate when each "tipping point" will be reached. Includes performance trend analysis from DOE's LED Lighting Facts® and CALiPER programs plus cost analysis from various sources.

  12. 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

    2014-10-01

    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.

  13. Regional price targets appropriate for advanced coal extraction. [Forecasting to 1985 and 2000; USA; Regional analysis

    SciTech Connect (OSTI)

    Terasawa, K.L.; Whipple, D.W.

    1980-12-01

    The object of the study is to provide a methodology for predicting coal prices in regional markets for the target time frames 1985 and 2000 that could subsequently be used to guide the development of an advanced coal extraction system. The model constructed for the study is a supply and demand model that focuses on underground mining, since the advanced technology is expected to be developed for these reserves by the target years. The supply side of the model is based on coal reserve data generated by Energy and Environmental Analysis, Inc. (EEA). Given this data and the cost of operating a mine (data from US Department of Energy and Bureau of Mines), the Minimum Acceptable Selling Price (MASP) is obtained. The MASP is defined as the smallest price that would induce the producer to bring the mine into production, and is sensitive to the current technology and to assumptions concerning miner productivity. Based on this information, market supply curves can then be generated. On the demand side of the model, demand by region is calculated based on an EEA methodology that emphasizes demand by electric utilities and demand by industry. The demand and supply curves are then used to obtain the price targets. This last step is accomplished by allocating the demands among the suppliers so that the combined cost of producing and transporting coal is minimized.

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

    SciTech Connect (OSTI)

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

    2008-01-25

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

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Pastore, Giovanni; Swiler, L. P.; Hales, Jason D.; Novascone, Stephen R.; Perez, Danielle M.; Spencer, Benjamin W.; Luzzi, Lelio; Uffelen, Paul Van; Williamson, Richard L.

    2014-10-12

    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 uncertaintymore » 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.« less

  16. Quantification of margins and uncertainty for risk-informed decision analysis.

    SciTech Connect (OSTI)

    Alvin, Kenneth Fredrick

    2010-09-01

    QMU stands for 'Quantification of Margins and Uncertainties'. QMU is a basic framework for consistency in integrating simulation, data, and/or subject matter expertise to provide input into a risk-informed decision-making process. QMU is being applied to a wide range of NNSA stockpile issues, from performance to safety. The implementation of QMU varies with lab and application focus. The Advanced Simulation and Computing (ASC) Program develops validated computational simulation tools to be applied in the context of QMU. QMU provides input into a risk-informed decision making process. The completeness aspect of QMU can benefit from the structured methodology and discipline of quantitative risk assessment (QRA)/probabilistic risk assessment (PRA). In characterizing uncertainties it is important to pay attention to the distinction between those arising from incomplete knowledge ('epistemic' or systematic), and those arising from device-to-device variation ('aleatory' or random). The national security labs should investigate the utility of a probability of frequency (PoF) approach in presenting uncertainties in the stockpile. A QMU methodology is connected if the interactions between failure modes are included. The design labs should continue to focus attention on quantifying uncertainties that arise from epistemic uncertainties such as poorly-modeled phenomena, numerical errors, coding errors, and systematic uncertainties in experiment. The NNSA and design labs should ensure that the certification plan for any RRW is supported by strong, timely peer review and by an ongoing, transparent QMU-based documentation and analysis in order to permit a confidence level necessary for eventual certification.

  17. 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.

    1995-02-01

    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.

  18. 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.

    2014-02-01

    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.

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

    SciTech Connect (OSTI)

    Helton, J.C.; Johnson, J.D.; McKay, M.D.; Shiver, A.W.; Sprung, J.L.

    1995-01-01

    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.

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

    SciTech Connect (OSTI)

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

    2005-05-11

    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. Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis: Modeling Archive

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

    E.T. Coon; C.J. Wilson; S.L. Painter; V.E. Romanovsky; D.R. Harp; A.L. Atchley; J.C. Rowland

    2016-02-02

    This dataset contains an ensemble of thermal-hydro soil parameters including porosity, thermal conductivity, thermal conductivity shape parameters, and residual saturation of peat and mineral soil. The ensemble was generated using a Null-Space Monte Carlo analysis of parameter uncertainty based on a calibration to soil temperatures collected at the Barrow Environmental Observatory site by the NGEE team. The micro-topography of ice wedge polygons present at the site is included in the analysis using three 1D column models to represent polygon center, rim and trough features. The Arctic Terrestrial Simulator (ATS) was used in the calibration to model multiphase thermal and hydrological processes in the subsurface.

  2. Idealization, uncertainty and heterogeneity : game frameworks defined with formal concept analysis.

    SciTech Connect (OSTI)

    Racovitan, M. T.; Sallach, D. L.; Decision and Information Sciences; Northern Illinois Univ.

    2006-01-01

    The present study begins with Formal Concept Analysis, and undertakes to demonstrate how a succession of game frameworks may, by design, address increasingly complex and interesting social phenomena. We develop a series of multi-agent exchange games, each of which incorporates an additional dimension of complexity. All games are based on coalition patterns in exchanges where diverse cultural markers provide a basis for trust and reciprocity. The first game is characterized by an idealized concept of trust. A second game framework introduces uncertainty regarding the reciprocity of prospective transactions. A third game framework retains idealized trust and uncertainty, and adds additional agent heterogeneity. Cultural markers are not equally salient in conferring or withholding trust, and the result is a richer transactional process.

  3. Uncertainty Studies of Real Anode Surface Area in Computational Analysis for Molten Salt Electrorefining

    SciTech Connect (OSTI)

    Sungyeol Choi; Jaeyeong Park; Robert O. Hoover; Supathorn Phongikaroon; Michael F. Simpson; Kwang-Rag Kim; Il Soon Hwang

    2011-09-01

    This study examines how much cell potential changes with five differently assumed real anode surface area cases. Determining real anode surface area is a significant issue to be resolved for precisely modeling molten salt electrorefining. Based on a three-dimensional electrorefining model, calculated cell potentials compare with an experimental cell potential variation over 80 hours of operation of the Mark-IV electrorefiner with driver fuel from the Experimental Breeder Reactor II. We succeeded to achieve a good agreement with an overall trend of the experimental data with appropriate selection of a mode for real anode surface area, but there are still local inconsistencies between theoretical calculation and experimental observation. In addition, the results were validated and compared with two-dimensional results to identify possible uncertainty factors that had to be further considered in a computational electrorefining analysis. These uncertainty factors include material properties, heterogeneous material distribution, surface roughness, and current efficiency. Zirconium's abundance and complex behavior have more impact on uncertainty towards the latter period of electrorefining at given batch of fuel. The benchmark results found that anode materials would be dissolved from both axial and radial directions at least for low burn-up metallic fuels after active liquid sodium bonding was dissolved.

  4. SWEPP PAN assay system uncertainty analysis: Passive mode measurements of graphite waste

    SciTech Connect (OSTI)

    Blackwood, L.G.; Harker, Y.D.; Meachum, T.R.; Yoon, Woo Y.

    1997-07-01

    The Idaho National Engineering and Environmental Laboratory is being used as a temporary storage facility for transuranic waste generated by the U.S. Nuclear Weapons program at the Rocky Flats Plant (RFP) in Golden, Colorado. Currently, there is a large effort in progress to prepare to ship this waste to the Waste Isolation Pilot Plant (WIPP) in Carlsbad, New Mexico. In order to meet the TRU Waste Characterization Quality Assurance Program Plan nondestructive assay compliance requirements and quality assurance objectives, it is necessary to determine the total uncertainty of the radioassay results produced by the Stored Waste Examination Pilot Plant (SWEPP) Passive Active Neutron (PAN) radioassay system. To this end a modified statistical sampling and verification approach has been developed to determine the total uncertainty of a PAN measurement. In this approach the total performance of the PAN nondestructive assay system is simulated using computer models of the assay system and the resultant output is compared with the known input to assess the total uncertainty. This paper is one of a series of reports quantifying the results of the uncertainty analysis of the PAN system measurements for specific waste types and measurement modes. In particular this report covers passive mode measurements of weapons grade plutonium-contaminated graphite molds contained in 208 liter drums (waste code 300). The validity of the simulation approach is verified by comparing simulated output against results from measurements using known plutonium sources and a surrogate graphite waste form drum. For actual graphite waste form conditions, a set of 50 cases covering a statistical sampling of the conditions exhibited in graphite wastes was compiled using a Latin hypercube statistical sampling approach.

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

    SciTech Connect (OSTI)

    Helton, J.C.; Johnson, J.D.; Rollstin, J.A.; Shiver, A.W.; Sprung, J.L.

    1995-01-01

    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.

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

    SciTech Connect (OSTI)

    Helton, J.C.; Johnson, J.D.; Rollstin, J.A.; Shiver, A.W.; Sprung, J.L.

    1995-01-01

    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.

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

    SciTech Connect (OSTI)

    Perk, Zoltn Gilli, Luca Lathouwers, Danny Kloosterman, Jan Leen

    2014-03-01

    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 (1520), 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.

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

    SciTech Connect (OSTI)

    Oladosu, Gbadebo A

    2009-01-01

    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.

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

    SciTech Connect (OSTI)

    James, T.

    2014-03-01

    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.

  10. Quantitative Analysis of Variability and Uncertainty in Environmental Data and Models. Volume 1. Theory and Methodology Based Upon Bootstrap Simulation

    SciTech Connect (OSTI)

    Frey, H. Christopher; Rhodes, David S.

    1999-04-30

    This is Volume 1 of a two-volume set of reports describing work conducted at North Carolina State University sponsored by Grant Number DE-FG05-95ER30250 by the U.S. Department of Energy. The title of the project is Quantitative Analysis of Variability and Uncertainty in Acid Rain Assessments. The work conducted under sponsorship of this grant pertains primarily to two main topics: (1) development of new methods for quantitative analysis of variability and uncertainty applicable to any type of model; and (2) analysis of variability and uncertainty in the performance, emissions, and cost of electric power plant combustion-based NOx control technologies. These two main topics are reported separately in Volumes 1 and 2.

  11. Electricity Prices in a Competitive Environment: Marginal Cost Pricing

    Reports and Publications (EIA)

    1997-01-01

    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 cost-of-service 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 of electricity suppliers?

  12. 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; Hough, Patricia Diane; Eddy, John P.

    2011-12-01

    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.

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

    SciTech Connect (OSTI)

    Kempe, M.

    2014-03-01

    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.

  14. Users manual for the FORSS sensitivity and uncertainty analysis code system

    SciTech Connect (OSTI)

    Lucius, J.L.; Weisbin, C.R.; Marable, J.H.; Drischler, J.D.; Wright, R.Q.; White, J.E.

    1981-01-01

    FORSS is a code system used to study relationships between nuclear reaction cross sections, integral experiments, reactor performance parameter predictions and associated uncertainties. This report describes the computing environment and the modules currently used to implement FORSS Sensitivity and Uncertainty Methodology.

  15. Gamma-Ray Library and Uncertainty Analysis: Passively Emitted Gamma Rays Used in Safeguards Technology

    SciTech Connect (OSTI)

    Parker, W

    2009-09-18

    Non-destructive gamma-ray analysis is a fundamental part of nuclear safeguards, including nuclear energy safeguards technology. Developing safeguards capabilities for nuclear energy will certainly benefit from the advanced use of gamma-ray spectroscopy as well as the ability to model various reactor scenarios. There is currently a wide variety of nuclear data that could be used in computer modeling and gamma-ray spectroscopy analysis. The data can be discrepant (with varying uncertainties), and it may difficult for a modeler or software developer to determine the best nuclear data set for a particular situation. To use gamma-ray spectroscopy to determine the relative isotopic composition of nuclear materials, the gamma-ray energies and the branching ratios or intensities of the gamma-rays emitted from the nuclides in the material must be well known. A variety of computer simulation codes will be used during the development of the nuclear energy safeguards, and, to compare the results of various codes, it will be essential to have all the {gamma}-ray libraries agree. Assessing our nuclear data needs allows us to create a prioritized list of desired measurements, and provides uncertainties for energies and especially for branching intensities. Of interest are actinides, fission products, and activation products, and most particularly mixtures of all of these radioactive isotopes, including mixtures of actinides and other products. Recent work includes the development of new detectors with increased energy resolution, and studies of gamma-rays and their lines used in simulation codes. Because new detectors are being developed, there is an increased need for well known nuclear data for radioactive isotopes of some elements. Safeguards technology should take advantage of all types of gamma-ray detectors, including new super cooled detectors, germanium detectors and cadmium zinc telluride detectors. Mixed isotopes, particularly mixed actinides found in nuclear reactor streams can be especially challenging to identify. The super cooled detectors have a marked improvement in energy resolution, allowing the possibility of deconvolution of mixtures of gamma rays that was unavailable with high purity germanium detectors. Isotopic analysis codes require libraries of gamma rays. In certain situations, isotope identification can be made in the field, sometimes with a short turnaround time, depending on the choice of detector and software analysis package. Sodium iodide and high purity germanium detectors have been successfully used in field scenarios. The newer super cooled detectors offer dramatically increased resolution, but they have lower efficiency and so can require longer collection times. The different peak shapes require software development for the specific detector type and field application. Libraries can be tailored to specific scenarios; by eliminating isotopes that are certainly not present, the analysis time may be shortened and the accuracy may be increased. The intent of this project was to create one accurate library of gamma rays emitted from isotopes of interest to be used as a reliable reference in safeguards work. All simulation and spectroscopy analysis codes can draw upon this best library to improve accuracy and cross-code consistency. Modeling codes may include MCNP and COG. Gamma-ray spectroscopy analysis codes may include MGA, MGAU, U235 and FRAM. The intent is to give developers and users the tools to use in nuclear energy safeguards work. In this project, the library created was limited to a selection of actinide isotopes of immediate interest to reactor technology. These isotopes included {sup 234-238}U, {sup 237}Np, {sup 238-242}Pu, {sup 241,243}Am and {sup 244}Cm. These isotopes were examined, and the best of gamma-ray data, including line energies and relative strengths were selected.

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

    Reports and Publications (EIA)

    1998-01-01

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

  17. A joint analysis of Planck and BICEP2 B modes including dust polarization uncertainty

    SciTech Connect (OSTI)

    Mortonson, Michael J.; Seljak, Uro E-mail: useljak@berkeley.edu

    2014-10-01

    We analyze BICEP2 and Planck data using a model that includes CMB lensing, gravity waves, and polarized dust. Recently published Planck dust polarization maps have highlighted the difficulty of estimating the amount of dust polarization in low intensity regions, suggesting that the polarization fractions have considerable uncertainties and may be significantly higher than previous predictions. In this paper, we start by assuming nothing about the dust polarization except for the power spectrum shape, which we take to be C{sub l}{sup BB,dust}?l{sup -2.42}. The resulting joint BICEP2+Planck analysis favors solutions without gravity waves, and the upper limit on the tensor-to-scalar ratio is r<0.11, a slight improvement relative to the Planck analysis alone which gives r<0.13 (95% c.l.). The estimated amplitude of the dust polarization power spectrum agrees with expectations for this field based on both HI column density and Planck polarization measurements at 353 GHz in the BICEP2 field. Including the latter constraint on the dust spectrum amplitude in our analysis improves the limit further to r<0.09, placing strong constraints on theories of inflation (e.g., models with r>0.14 are excluded with 99.5% confidence). We address the cross-correlation analysis of BICEP2 at 150 GHz with BICEP1 at 100 GHz as a test of foreground contamination. We find that the null hypothesis of dust and lensing with 0r= gives ??{sup 2}<2 relative to the hypothesis of no dust, so the frequency analysis does not strongly favor either model over the other. We also discuss how more accurate dust polarization maps may improve our constraints. If the dust polarization is measured perfectly, the limit can reach r<0.05 (or the corresponding detection significance if the observed dust signal plus the expected lensing signal is below the BICEP2 observations), but this degrades quickly to almost no improvement if the dust calibration error is 20% or larger or if the dust maps are not processed through the BICEP2 pipeline, inducing sampling variance noise.

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

    SciTech Connect (OSTI)

    1997-04-01

    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.

  19. Uncertainty in soil-structure interaction analysis of a nuclear power plant due to different analytical techniques

    SciTech Connect (OSTI)

    Chen, J.C.; Chun, R.C.; Goudreau, G.L.; Maslenikov, O.R.; Johnson, J.J.

    1984-01-01

    This paper summarizes the results of the dynamic response analysis of the Zion reactor containment building using three different soil-structure interaction (SSI) analytical procedures which are: the substructure method, CLASSI; the equivalent linear finite element approach, ALUSH; and the nonlinear finite element procedure, DYNA3D. Uncertainties in analyzing a soil-structure system due to SSI analysis procedures were investigated. Responses at selected locations in the structure were compared through peak accelerations and response spectra.

  20. A simplified analysis of uncertainty propagation in inherently controlled ATWS events

    SciTech Connect (OSTI)

    Wade, D.C.

    1987-01-01

    The quasi static approach can be used to provide useful insight concerning the propagation of uncertainties in the inherent response to ATWS events. At issue is how uncertainties in the reactivity coefficients and in the thermal-hydraulics and materials properties propagate to yield uncertainties in the asymptotic temperatures attained upon inherent shutdown. The basic notion to be quantified is that many of the same physical phenomena contribute to both the reactivity increase of power reduction and the reactivity decrease of core temperature rise. Since these reactivities cancel by definition, a good deal of uncertainty cancellation must also occur of necessity. For example, if the Doppler coefficient is overpredicted, too large a positive reactivity insertion is predicted upon power reduction and collapse of the ..delta..T across the fuel pin. However, too large a negative reactivity is also predicted upon the compensating increase in the isothermal core average temperature - which includes the fuel Doppler effect.

  1. 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.

    2010-11-01

    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.

  2. Response model and activity analysis of the revenue reconciliation problem in the marginal cost pricing of electricity

    SciTech Connect (OSTI)

    Hassig, N.L.

    1980-01-01

    The objective of the research was to determine if feasible reconciliation procedures exist that meet the multiple (and sometimes competing) goals of the electricity pricing problem while staying within the constraints of the problem. The answer was that such procedures do exist. Selection among the alternative, feasible procedures depends on the weighting factors placed on the goals. One procedure did not universally satisfy all the goals; the various procedures satisfied the alternative goals to varying degrees. The selection process was sensitive to the initial conditions of the model and to the band width of the constraint boundary conditions. Discriminate analysis was used to identify the variables that contribute the most to the optimal selection process. The results of the research indicated that the variables that are the most effective in selecting among the various procedures were the following: the ratio of peak to off-peak prices, the amount of revenue adjustment required, the constraint on equity, the constraint on peak price stability, and the constraint on meeting the revenue requirement. The poicy recommendations that can be derived from this research are very relevant in light of today's energy problems. Time-of-use pricing of electricity is needed in order to signal to the consumer the true cost of electricity by season and by time of day. Marginal costs capture such costs and rates should be based on such costs. Revenue reconciliation procedures make marginal cost-based rates feasible from a regulatory requirement perspective. This research showed that such procedures are available and selection among alternative procedures depends on the preference rankings placed on the multiple, and sometimes competing goals of electricity pricing.

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

    SciTech Connect (OSTI)

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

    2013-05-01

    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.

  4. Fukushima Daiichi Unit 1 Uncertainty Analysis-Exploration of Core Melt Progression Uncertain Parameters-Volume II.

    SciTech Connect (OSTI)

    Denman, Matthew R.; Brooks, Dusty Marie

    2015-08-01

    Sandia National Laboratories (SNL) has conducted an uncertainty analysi s (UA) on the Fukushima Daiichi unit (1F1) accident progression wit h the MELCOR code. Volume I of the 1F1 UA discusses the physical modeling details and time history results of the UA. Volume II of the 1F1 UA discusses the statistical viewpoint. The model used was developed for a previous accident reconstruction investigation jointly sponsored by the US Department of Energy (DOE) and Nuclear Regulatory Commission (NRC). The goal of this work was to perform a focused evaluation of uncertainty in core damage progression behavior and its effect on key figures - of - merit (e.g., hydrogen production, fraction of intact fuel, vessel lower head failure) and in doing so assess the applicability of traditional sensitivity analysis techniques .

  5. Microsoft Word - Price Uncertainty Supplement.doc

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

    ... This can be seen in the spread between the green (July 1 forwards) and black curves ... Source: U.S. EIA, CME Group Energy Information AdministrationShort-Term Energy Outlook ...

  6. Microsoft Word - Price Uncertainty Supplement.doc

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

    ... In Figure 3, the then-prompt February 2009 futures contract (green dashed curve in Figure ... Figure 4 shows the comparable 2007 period and the same effect. U.S. Energy Information ...

  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.

    2013-10-01

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

    SciTech Connect (OSTI)

    None,

    1980-05-01

    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.

  9. Characterization, propagation and analysis of aleatory and epistemic uncertainty in the 2008 performance assessment for the proposed repository for radioactive waste at Yucca Mountain, Nevada.

    SciTech Connect (OSTI)

    Helton, Jon Craig; Sallaberry, Cedric M.; Hansen, Clifford W.

    2010-10-01

    The 2008 performance assessment (PA) for the proposed repository for high-level radioactive waste at Yucca Mountain (YM), Nevada, illustrates the conceptual structure of risk assessments for complex systems. The 2008 YM PA is based on the following three conceptual entities: a probability space that characterizes aleatory uncertainty; a function that predicts consequences for individual elements of the sample space for aleatory uncertainty; and a probability space that characterizes epistemic uncertainty. These entities and their use in the characterization, propagation and analysis of aleatory and epistemic uncertainty are described and illustrated with results from the 2008 YM PA.

  10. 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. Fisher, R. K.; Van Zeeland, M. A.; Pipes, R.

    2014-11-15

    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.

  11. Fuel cycle cost uncertainty from nuclear fuel cycle comparison

    SciTech Connect (OSTI)

    Li, J.; McNelis, D.; Yim, M.S.

    2013-07-01

    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.

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

    SciTech Connect (OSTI)

    Michael Pernice

    2012-10-01

    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.

  13. Measuring and Explaining Electricity Price Changes in Restructured States

    SciTech Connect (OSTI)

    Fagan, Mark L.

    2006-06-15

    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)

  14. 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.

    2013-10-01

    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.

  15. 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

    2012-10-01

    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.

  16. Fukushima Daiichi Unit 1 Accident Progression Uncertainty Analysis and Implications for Decommissioning of Fukushima Reactors - Volume I.

    SciTech Connect (OSTI)

    Gauntt, Randall O.; Mattie, Patrick D.

    2016-01-01

    Sandia National Laboratories (SNL) has conducted an uncertainty analysis (UA) on the Fukushima Daiichi unit (1F1) accident progression with the MELCOR code. The model used was developed for a previous accident reconstruction investigation jointly sponsored by the US Department of Energy (DOE) and Nuclear Regulatory Commission (NRC). That study focused on reconstructing the accident progressions, as postulated by the limited plant data. This work was focused evaluation of uncertainty in core damage progression behavior and its effect on key figures-of-merit (e.g., hydrogen production, reactor damage state, fraction of intact fuel, vessel lower head failure). The primary intent of this study was to characterize the range of predicted damage states in the 1F1 reactor considering state of knowledge uncertainties associated with MELCOR modeling of core damage progression and to generate information that may be useful in informing the decommissioning activities that will be employed to defuel the damaged reactors at the Fukushima Daiichi Nuclear Power Plant. Additionally, core damage progression variability inherent in MELCOR modeling numerics is investigated.

  17. 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

    2014-05-01

    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.

  18. nCTEQ15 - Global analysis of nuclear parton distributions with uncertainties

    SciTech Connect (OSTI)

    Kusina, A.; Jezo, T.; Clark, D. B.; Keppel, Cynthia; Lyonnet, F.; Morfin, Jorge; Olness, F. I.; Owens, Jeff; Schienbein, I.

    2015-09-01

    We present the first official release of the nCTEQ nuclear parton distribution functions with errors. The main addition to the previous nCTEQ PDFs is the introduction of PDF uncertainties based on the Hessian method. Another important addition is the inclusion of pion production data from RHIC that give us a handle on constraining the gluon PDF. This contribution summarizes our results from arXiv:1509.00792 and concentrates on the comparison with other groups providing nuclear parton distributions.

  19. Analysis of sampling plan options for tank 16H from the perspective of statistical uncertainty

    SciTech Connect (OSTI)

    Shine, E. P.

    2013-02-28

    This report develops a concentration variability model for Tank 16H in order to compare candidate sampling plans for assessing the concentrations of analytes in the residual material in the annulus and on the floor of the primary vessel. A concentration variability model is used to compare candidate sampling plans based on the expected upper 95% confidence limit (UCL95) for the mean. The result is expressed as a rank order of candidate sampling plans from lowest to highest expected UCL95, with the lowest being the most desirable from an uncertainty perspective.

  20. Systematic uncertainties associated with the cosmological analysis of the first Pan-STARRS1 type Ia supernova sample

    SciTech Connect (OSTI)

    Scolnic, D.; Riess, A.; Brout, D.; Rodney, S. [Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States); Rest, A. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Huber, M. E.; Tonry, J. L. [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Foley, R. J.; Chornock, R.; Berger, E.; Soderberg, A. M.; Stubbs, C. W.; Kirshner, R. P.; Challis, P.; Czekala, I.; Drout, M. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Narayan, G. [Department of Physics, Harvard University, 17 Oxford Street, Cambridge, MA 02138 (United States); Smartt, S. J.; Botticella, M. T. [Astrophysics Research Centre, School of Mathematics and Physics, Queens University Belfast, Belfast BT7 1NN (United Kingdom); Schlafly, E. [Max Planck Institute for Astronomy, Konigstuhl 17, D-69117 Heidelberg (Germany); and others

    2014-11-01

    We probe the systematic uncertainties from the 113 Type Ia supernovae (SN Ia) in the Pan-STARRS1 (PS1) sample along with 197 SN Ia from a combination of low-redshift surveys. The companion paper by Rest et al. describes the photometric measurements and cosmological inferences from the PS1 sample. The largest systematic uncertainty stems from the photometric calibration of the PS1 and low-z samples. We increase the sample of observed Calspec standards from 7 to 10 used to define the PS1 calibration system. The PS1 and SDSS-II calibration systems are compared and discrepancies up to ?0.02 mag are recovered. We find uncertainties in the proper way to treat intrinsic colors and reddening produce differences in the recovered value of w up to 3%. We estimate masses of host galaxies of PS1 supernovae and detect an insignificant difference in distance residuals of the full sample of 0.037 0.031 mag for host galaxies with high and low masses. Assuming flatness and including systematic uncertainties in our analysis of only SNe measurements, we find w =?1.120{sub ?0.206}{sup +0.360}(Stat){sub ?0.291}{sup +0.269}(Sys). With additional constraints from Baryon acoustic oscillation, cosmic microwave background (CMB) (Planck) and H {sub 0} measurements, we find w=?1.166{sub ?0.069}{sup +0.072} and ?{sub m}=0.280{sub ?0.012}{sup +0.013} (statistical and systematic errors added in quadrature). The significance of the inconsistency with w = 1 depends on whether we use Planck or Wilkinson Microwave Anisotropy Probe measurements of the CMB: w{sub BAO+H0+SN+WMAP}=?1.124{sub ?0.065}{sup +0.083}.

  1. 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

    2011-04-19

    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.

  2. Electromagnetic form factors of the nucleon: New fit and analysis of uncertainties

    SciTech Connect (OSTI)

    Alberico, W. M.; Giunti, C.; Bilenky, S. M.; Graczyk, K. M.

    2009-06-15

    Electromagnetic form factors of proton and neutron, obtained from a new fit of data, are presented. The proton form factors are obtained from a simultaneous fit to the ratio {mu}{sub p}G{sub Ep}/G{sub Mp} determined from polarization transfer measurements and to ep elastic cross section data. Phenomenological two-photon exchange corrections are taken into account. The present fit for protons was performed in the kinematical region Q{sup 2} is an element of (0,6) GeV{sup 2}. For both protons and neutrons we use the latest available data. For all form factors, the uncertainties and correlations of form factor parameters are investigated with the {chi}{sup 2} method.

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

    SciTech Connect (OSTI)

    Langton, C.; Kosson, D.

    2009-11-30

    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.

  4. Signal discovery, limits, and uncertainties with sparse on/off measurements: an objective bayesian analysis

    SciTech Connect (OSTI)

    Knoetig, Max L., E-mail: mknoetig@phys.ethz.ch [Institute for Particle Physics, ETH Zurich, 8093 Zurich (Switzerland)

    2014-08-01

    For decades researchers have studied the On/Off counting problem where a measured rate consists of two parts. One part is due to a signal process and the other is due to a background process, the magnitudes for both of which are unknown. While most frequentist methods are adequate for large number counts, 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 counts only being due to background 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. This approach is valid without restrictions for any number count, including zero, and may be widely applied in particle physics, cosmic-ray physics, and high-energy astrophysics. In order to demonstrate the performance of this approach, I apply the method to gamma-ray burst data.

  5. Natural Gas Wellhead Price

    Gasoline and Diesel Fuel Update (EIA)

    Pipeline and Distribution Use Price City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Vehicle Fuel Price Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010

  6. Utility-Scale Solar 2014. An Empirical Analysis of Project Cost, Performance, and Pricing Trends in the United States

    SciTech Connect (OSTI)

    Bolinger, Mark; Seel, Joachim

    2015-09-01

    Other than the nine Solar Energy Generation Systems (“SEGS”) parabolic trough projects built in the 1980s, virtually no large-scale or “utility-scale” solar projects – defined here to include any groundmounted photovoltaic (“PV”), concentrating photovoltaic (“CPV”), or concentrating solar thermal power (“CSP”) project larger than 5 MWAC – existed in the United States prior to 2007. By 2012 – just five years later – utility-scale had become the largest sector of the overall PV market in the United States, a distinction that was repeated in both 2013 and 2014 and that is expected to continue for at least the next few years. Over this same short period, CSP also experienced a bit of a renaissance in the United States, with a number of large new parabolic trough and power tower systems – some including thermal storage – achieving commercial operation. With this critical mass of new utility-scale projects now online and in some cases having operated for a number of years (generating not only electricity, but also empirical data that can be mined), the rapidly growing utility-scale sector is ripe for analysis. This report, the third edition in an ongoing annual series, meets this need through in-depth, annually updated, data-driven analysis of not just installed project costs or prices – i.e., the traditional realm of solar economics analyses – but also operating costs, capacity factors, and power purchase agreement (“PPA”) prices from a large sample of utility-scale solar projects in the United States. Given its current dominance in the market, utility-scale PV also dominates much of this report, though data from CPV and CSP projects are presented where appropriate.

  7. Sandia Energy - Price Premiums for Solar Home Sales

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

    Price Premiums for Solar Home Sales Home Renewable Energy Energy Partnership News News & Events Photovoltaic Solar Systems Analysis Price Premiums for Solar Home Sales Previous...

  8. 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.

    1990-05-01

    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.

  9. 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.

    2010-09-01

    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.

  10. CASL L1 Milestone report : CASL.P4.01, sensitivity and uncertainty analysis for CIPS with VIPRE-W and BOA.

    SciTech Connect (OSTI)

    Sung, Yixing; Adams, Brian M.; Secker, Jeffrey R.

    2011-12-01

    The CASL Level 1 Milestone CASL.P4.01, successfully completed in December 2011, aimed to 'conduct, using methodologies integrated into VERA, a detailed sensitivity analysis and uncertainty quantification of a crud-relevant problem with baseline VERA capabilities (ANC/VIPRE-W/BOA).' The VUQ focus area led this effort, in partnership with AMA, and with support from VRI. DAKOTA was coupled to existing VIPRE-W thermal-hydraulics and BOA crud/boron deposit simulations representing a pressurized water reactor (PWR) that previously experienced crud-induced power shift (CIPS). This work supports understanding of CIPS by exploring the sensitivity and uncertainty in BOA outputs with respect to uncertain operating and model parameters. This report summarizes work coupling the software tools, characterizing uncertainties, and analyzing the results of iterative sensitivity and uncertainty studies. These studies focused on sensitivity and uncertainty of CIPS indicators calculated by the current version of the BOA code used in the industry. Challenges with this kind of analysis are identified to inform follow-on research goals and VERA development targeting crud-related challenge problems.

  11. FERC's acceptance of market-based pricing: An antitrust analysis. [Federal Energy Regulatory Commission

    SciTech Connect (OSTI)

    Harris, B.C.; Frankena, M.W. )

    1992-06-01

    In large part, FERC's determination of market power is based on an analysis that focuses on the ability of power suppliers to foreclose' other potential power suppliers by withholding transmission access to the buyer. The authors believe that this analysis is flawed because the conditions it considers are neither necessary nor sufficient for the existence of market power. That is, it is possible that market-based rates can be subject to market power even if no transmission supplier has the ability to foreclose some power suppliers; conversely, it is possible that no market power exists despite the ability to foreclose other suppliers. This paper provides a critical analysis of FERC's market-power determinations. The concept of market power is defined and its relationship to competition is discussed in Section 1, while a framework for evaluating the existence of market power is presented in Section 2. In Section 3, FERC's recent order in Terra Comfort is examined using this framework. A brief preview of FERC's order in TECO Power Services comprises Section 4. Overall conclusions are presented in Section 5.

  12. 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

    2013-12-01

    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.

  13. Understanding the Impact of Higher Corn Prices on Consumer Food Prices

    SciTech Connect (OSTI)

    None

    2007-04-18

    In an effort to assess the true effects of higher corn prices, the National Corn Growers Association (NCGA) commissioned an analysis on the impact of increased corn prices on retail food prices. This paper summarizes key results of the study and offers additional analysis based on information from a variety of other sources.

  14. 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.; Watson, Jean-Paul; Kolda, Tamara Gibson; Adams, Brian M.; Swiler, Laura Painton; Williams, Pamela J.; Hough, Patricia Diane; Gay, David M.; Dunlavy, Daniel M.; Eddy, John P.; Hart, William Eugene; Guinta, Anthony A.; Brown, Shannon L.

    2006-10-01

    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.

  15. 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.

  16. Natural Gas Citygate Price

    Gasoline and Diesel Fuel Update (EIA)

    Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From

  17. Average Commercial Price

    Gasoline and Diesel Fuel Update (EIA)

    Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From

  18. Average Residential Price

    Gasoline and Diesel Fuel Update (EIA)

    Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From

  19. Price controls and international petroleum product prices

    SciTech Connect (OSTI)

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

    1980-02-01

    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.

  20. What Drives U.S. Gasoline Prices?

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

    ... Past EIA research and analysis 1 has shown that changes in wholesale gasoline ... price. 3 http:www.eia.govpetroleumgasdieselpumpmethodology.cfm 4 This Week In Petroleum ...

  1. 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

    2005-08-01

    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)?

  2. Analysis of changes in OPEC's crude oil prices, current account, and surplus investments, with emphasis upon oil-revenue purchasing power - 1973 through 1980

    SciTech Connect (OSTI)

    Tadayon, S.

    1984-01-01

    The study sought to provide a comprehensive investigation of changes in the Organisation of Petroleum Exporting Countries (OPEC) crude oil prices, current-account balance, and current-account surplus investments abroad. The study emphasized analysis and, to some extent, quantification of the real value, or purchasing power, of OPEC oil revenues. The research approach was descriptive-elemental to expand upon characteristics of variables identified for the study. Research questions were answered by direct findings for each question. The method utilized for the study included document research and statistical analyses of data derived. The aim was to obtain complete and accurate information. The study compiled documented data regarding OPEC's crude oil prices, current-account balance, and current-account surplus investments abroad and analyzed the purchasing power of oil revenues as time passed and events occurred over the eight years from 1973 through 1980.

  3. Diesel prices decrease

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

    Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.82 a gallon on Monday. That's down 2.1 cents from a week ago, based on the weekly price...

  4. Diesel prices flat nationally

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

    Diesel prices flat nationally The U.S. average retail price for on-highway diesel fuel remained the same from a week ago at 3.98 a gallon on Monday, based on the weekly price...

  5. Diesel prices decrease

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

    Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.88 a gallon on Monday. That's down a penny from a week ago, based on the weekly price...

  6. Diesel prices increase

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

    Diesel prices increase The U.S. average retail price for on-highway diesel fuel rose to 3.90 a gallon on Monday. That's up 3 cents from a week ago, based on the weekly price...

  7. Diesel prices decrease

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

    Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.85 a gallon on Monday. That's down 2 cents from a week ago, based on the weekly price...

  8. Diesel prices decrease

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

    Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 4.05 a gallon on Monday. That's down 4.1 cents from a week ago, based on the weekly price...

  9. Diesel prices decrease

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

    Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.87 a gallon on Monday. That's down 1.6 cents from a week ago, based on the weekly price...

  10. Diesel prices flat

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

    Diesel prices flat The U.S. average retail price for on-highway diesel fuel saw no movement from last week. Prices remained flat at 3.89 a gallon on Monday, based on the weekly...

  11. Diesel prices increase

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

    Diesel prices increase The U.S. average retail price for on-highway diesel fuel rose to 3.84 a gallon on Monday. That's up 2.2 cents from a week ago, based on the weekly price...

  12. Diesel prices decrease

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

    Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.88 a gallon on Monday. That's down 0.4 cents from a week ago, based on the weekly price...

  13. 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.

    2012-06-19

    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.

  14. The Role of Uncertainty Quantification for Reactor Physics

    SciTech Connect (OSTI)

    Salvatores, Massimo; Palmiotti, Giuseppe; Aliberti, G.

    2015-01-01

    The quantification of uncertainties is a crucial step in design. The comparison of a-priori uncertainties with the target accuracies, allows to define needs and priorities for uncertainty reduction. In view of their impact, the uncertainty analysis requires a reliability assessment of the uncertainty data used. The choice of the appropriate approach and the consistency of different approaches are discussed.

  15. Domestic petroleum-product prices around the world. Survey: free market or government price controls

    SciTech Connect (OSTI)

    Not Available

    1983-01-27

    In this issue, Energy Detente draws from their regular Western and Eastern Hemisphere Fuel Price/Tax Series, each produced monthly, and adds other survey data and analysis for a broad view of 48 countries around the world. They find that seven Latin American nations, including OPEC members Venezuela and Ecuador, are among the ten countries with lowest gasoline prices. In this Fourth Special Price Report, Energy Detente provides a first-time presentation of which prices are government-controlled, and which are free to respond to market forces. South Korea, with fixed prices since 1964, has the highest premium-grade gasoline price in our survey, US $5.38 per gallon. Paraguay, with prices fixed by PETROPAR, the national oil company, has the second highest premium gasoline price, US $4.21 per gallon. Nicaragua, also with government price controls, ranks third highest in the survey, with US $3.38 per gallon for premium gasoline. Kuwait shows the lowest price at US $0.55 per gallon. Several price changes from the previous survey reflect changes in currency exchange as all prices are converted to US dollars. The Energy Detente fuel price/tax series is presented for Western Hemisphere countries.

  16. Appendix C: Price case comparisons

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

    High oil price Low oil price Reference High oil price Low oil price Reference High oil price Production Crude oil and lease condensate ... 13.87 19.06 20.36...

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

    SciTech Connect (OSTI)

    Alonso, Juan J.; Iaccarino, Gianluca

    2013-08-25

    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.

  18. World Crude Oil Prices

    Gasoline and Diesel Fuel Update (EIA)

    World Crude Oil Prices (Dollars per Barrel) The data on this page are no longer available.

  19. Calculating Impacts of Energy Standards on Energy Demand in U.S. Buildings with Uncertainty in an Integrated Assessment Model

    SciTech Connect (OSTI)

    Scott, Michael J.; Daly, Don S.; Hathaway, John E.; Lansing, Carina S.; Liu, Ying; McJeon, Haewon C.; Moss, Richard H.; Patel, Pralit L.; Peterson, Marty J.; Rice, Jennie S.; Zhou, Yuyu

    2015-10-01

    In this paper, an integrated assessment model (IAM) uses a newly-developed Monte Carlo analysis capability to analyze the impacts of more aggressive U.S. residential and commercial building-energy codes and equipment standards on energy consumption and energy service costs at the state level, explicitly recognizing uncertainty in technology effectiveness and cost, socioeconomics, presence or absence of carbon prices, and climate impacts on energy demand. The paper finds that aggressive building-energy codes and equipment standards are an effective, cost-saving way to reduce energy consumption in buildings and greenhouse gas emissions in U.S. states. This conclusion is robust to significant uncertainties in population, economic activity, climate, carbon prices, and technology performance and costs.

  20. Natural Gas Citygate Price

    Gasoline and Diesel Fuel Update (EIA)

    Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground

  1. Natural Gas Industrial Price

    Gasoline and Diesel Fuel Update (EIA)

    Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground

  2. Average Commercial Price

    Gasoline and Diesel Fuel Update (EIA)

    Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground

  3. Average Residential Price

    Gasoline and Diesel Fuel Update (EIA)

    Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground

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

    2006-10-01

    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.

  5. 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; Gay, David M.; Eddy, John P.; Haskell, Karen H.

    2010-05-01

    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.

  6. 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; Gay, David M.; Eddy, John P.; Haskell, Karen H.

    2010-05-01

    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.

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

    2006-10-01

    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.

  8. State energy price and expenditure report 1993

    SciTech Connect (OSTI)

    1995-12-01

    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.

  9. Techno-Economic Analysis of the Deacetylation and Disk Refining Process. Characterizing the Effect of Refining Energy and Enzyme Usage on Minimum Sugar Selling Price and Minimum Ethanol Selling Price

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Chen, Xiaowen; Shekiro, Joseph; Pschorn, Thomas; Sabourin, Marc; Tucker, Melvin P.; Tao, Ling

    2015-10-29

    A novel, highly efficient deacetylation and disk refining (DDR) process to liberate fermentable sugars from biomass was recently developed at the National Renewable Energy Laboratory (NREL). The DDR process consists of a mild, dilute alkaline deacetylation step followed by low-energy-consumption disk refining. The DDR corn stover substrates achieved high process sugar conversion yields, at low to modest enzyme loadings, and also produced high sugar concentration syrups at high initial insoluble solid loadings. The sugar syrups derived from corn stover are highly fermentable due to low concentrations of fermentation inhibitors. The objective of this work is to evaluate the economic feasibilitymore » of the DDR process through a techno-economic analysis (TEA). A large array of experiments designed using a response surface methodology was carried out to investigate the two major cost-driven operational parameters of the novel DDR process: refining energy and enzyme loadings. The boundary conditions for refining energy (128–468 kWh/ODMT), cellulase (Novozyme’s CTec3) loading (11.6–28.4 mg total protein/g of cellulose), and hemicellulase (Novozyme’s HTec3) loading (0–5 mg total protein/g of cellulose) were chosen to cover the most commercially practical operating conditions. The sugar and ethanol yields were modeled with good adequacy, showing a positive linear correlation between those yields and refining energy and enzyme loadings. The ethanol yields ranged from 77 to 89 gallons/ODMT of corn stover. The minimum sugar selling price (MSSP) ranged from $0.191 to $0.212 per lb of 50 % concentrated monomeric sugars, while the minimum ethanol selling price (MESP) ranged from $2.24 to $2.54 per gallon of ethanol. The DDR process concept is evaluated for economic feasibility through TEA. The MSSP and MESP of the DDR process falls within a range similar to that found with the deacetylation/dilute acid pretreatment process modeled in NREL’s 2011 design report. The DDR process is a much simpler process that requires less capital and maintenance costs when compared to conventional chemical pretreatments with pressure vessels. As a result, we feel the DDR process should be considered as an option for future biorefineries with great potential to be more cost-effective.« less

  10. Techno-Economic Analysis of the Deacetylation and Disk Refining Process. Characterizing the Effect of Refining Energy and Enzyme Usage on Minimum Sugar Selling Price and Minimum Ethanol Selling Price

    SciTech Connect (OSTI)

    Chen, Xiaowen; Shekiro, Joseph; Pschorn, Thomas; Sabourin, Marc; Tucker, Melvin P.; Tao, Ling

    2015-10-29

    A novel, highly efficient deacetylation and disk refining (DDR) process to liberate fermentable sugars from biomass was recently developed at the National Renewable Energy Laboratory (NREL). The DDR process consists of a mild, dilute alkaline deacetylation step followed by low-energy-consumption disk refining. The DDR corn stover substrates achieved high process sugar conversion yields, at low to modest enzyme loadings, and also produced high sugar concentration syrups at high initial insoluble solid loadings. The sugar syrups derived from corn stover are highly fermentable due to low concentrations of fermentation inhibitors. The objective of this work is to evaluate the economic feasibility of the DDR process through a techno-economic analysis (TEA). A large array of experiments designed using a response surface methodology was carried out to investigate the two major cost-driven operational parameters of the novel DDR process: refining energy and enzyme loadings. The boundary conditions for refining energy (128468 kWh/ODMT), cellulase (Novozymes CTec3) loading (11.628.4 mg total protein/g of cellulose), and hemicellulase (Novozymes HTec3) loading (05 mg total protein/g of cellulose) were chosen to cover the most commercially practical operating conditions. The sugar and ethanol yields were modeled with good adequacy, showing a positive linear correlation between those yields and refining energy and enzyme loadings. The ethanol yields ranged from 77 to 89 gallons/ODMT of corn stover. The minimum sugar selling price (MSSP) ranged from $0.191 to $0.212 per lb of 50 % concentrated monomeric sugars, while the minimum ethanol selling price (MESP) ranged from $2.24 to $2.54 per gallon of ethanol. The DDR process concept is evaluated for economic feasibility through TEA. The MSSP and MESP of the DDR process falls within a range similar to that found with the deacetylation/dilute acid pretreatment process modeled in NRELs 2011 design report. The DDR process is a much simpler process that requires less capital and maintenance costs when compared to conventional chemical pretreatments with pressure vessels. As a result, we feel the DDR process should be considered as an option for future biorefineries with great potential to be more cost-effective.

  11. Analysis of road pricing, metering and the priority treatment of high occupancy vehicles using system dynamics. Master's thesis

    SciTech Connect (OSTI)

    Castillo, W.

    1992-01-01

    Transportation Systems Management (TSM) employs various techniques such as road pricing, metering and the priority treatment of high occupancy vehicles (HOVs) in an effort to make more efficient use of existing transportation facilities. Efficiency is improved in terms of moving more people through the facility while simultaneously reducing the number of vehicles using the facility. This report uses a hypothetical toll facility and examines four computer modeling approaches to determine which of the approaches are valid in terms of predicting the behavior of trip makers seeking to use the facility in response to various combinations of TSM techniques. Once an approach has been determined to be valid, seven different combination of TSM techniques, or strategies, are compared to a base strategy to determine what strategy or strategies are most affective in achieving the goals of TSM.

  12. Massachusetts Natural Gas Prices

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

    Imports Price 4.86 4.77 3.69 5.49 8.00 1989-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.74 7.04 6.03 6.20 6.96 NA 1984-2015 Residential Price 14.53 13.81 13.22 13.49 14.50 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 85.4 89.3 87.8 99.6 99.5 NA 1989-2015 Commercial Price 12.00 11.68 10.68 11.25 12.48 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices 52.1 50.0 48.6 39.4 42.3 NA 1990-2015 Industrial Price 10.41 10.14

  13. Michigan Natural Gas Prices

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

    Wellhead Price 3.79 1967-2010 Imports Price 4.73 4.38 2.88 4.02 8.34 1989-2014 Exports Price 4.85 4.44 3.12 4.07 6.26 1989-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.07 6.18 5.50 4.91 5.54 4.22 1984-2015 Residential Price 11.32 10.47 9.95 9.09 9.33 8.78 1967-2015 Percentage of Total Residential Deliveries included in Prices 91.9 92.1 91.6 91.6 92.2 92.7 1989-2015 Commercial Price 8.95 9.14 8.35 7.82 8.28 7.49 1967-2015 Percentage of Total Commercial Deliveries included

  14. Minnesota Natural Gas Prices

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

    Imports Price 4.49 4.15 2.87 3.87 5.60 1989-2014 Exports Price -- 3.90 3.46 3.83 11.05 1999-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.48 5.04 4.26 4.58 6.56 4.40 1984-2015 Residential Price 8.76 8.85 7.99 8.19 9.89 8.84 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 7.60 7.46 6.36 6.86 8.66 7.30 1967-2015 Percentage of Total Commercial Deliveries included in Prices 93.1 89.8 91.1

  15. Mississippi Natural Gas Prices

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

    4.17 1967-2010 Imports Price -- 12.93 -- -- -- 2007-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.73 5.29 3.97 4.44 5.29 NA 1984-2015 Residential Price 10.19 9.47 9.60 9.00 9.49 9.71 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 99.5 99.5 99.5 100.0 NA 1989-2015 Commercial Price 8.75 7.99 7.37 7.61 8.36 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices 90.6 89.8 89.0 89.1 87.5 NA 1990-2015 Industrial Price 6.19 5.83

  16. Montana Natural Gas Prices

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

    3.64 1967-2010 Imports Price 4.13 3.75 2.45 3.23 4.39 1989-2014 Exports Price 4.05 3.82 2.40 3.43 5.38 1989-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.17 5.11 4.23 4.21 5.03 3.71 1984-2015 Residential Price 8.64 8.80 8.05 8.19 9.11 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 99.8 99.8 99.8 99.9 99.8 NA 1989-2015 Commercial Price 8.54 8.66 7.98 8.09 8.77 7.82 1967-2015 Percentage of Total Commercial Deliveries included in Prices 54.6 53.3

  17. Texas Natural Gas Prices

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

    70 1967-2010 Imports Price 6.72 6.78 10.09 12.94 11.79 1993-2014 Exports Price 4.68 4.44 3.14 3.94 4.67 1989-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.89 5.39 4.30 4.89 5.77 4.20 1984-2015 Residential Price 10.82 10.21 10.55 10.50 11.16 10.65 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 99.7 99.7 99.7 99.8 99.9 1989-2015 Commercial Price 7.90 7.07 6.63 7.25 8.26 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices

  18. California Natural Gas Prices

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

    87 1967-2010 Imports Price 4.76 3.57 -- 3.59 -- 2007-2014 Exports Price 4.51 4.18 2.90 3.89 4.56 1997-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 4.86 4.47 3.46 4.18 4.88 3.27 1984-2015 Residential Price 9.92 9.93 9.14 9.92 11.51 11.38 1967-2015 Percentage of Total Residential Deliveries included in Prices 98.5 98.3 97.5 96.1 94.8 94.9 1989-2015 Commercial Price 8.30 8.29 7.05 7.81 9.05 7.98 1967-2015 Percentage of Total Commercial Deliveries included in Prices 54.1 54.3

  19. Florida Natural Gas Prices

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

    Wellhead Price NA 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.49 5.07 3.93 4.44 5.05 NA 1984-2015 Residential Price 17.89 18.16 18.34 18.46 19.02 19.29 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 98.0 97.7 97.8 97.8 97.8 1989-2015 Commercial Price 10.60 11.14 10.41 10.87 11.38 10.74 1967-2015 Percentage of Total Commercial Deliveries included in Prices 100.0 38.5 37.0 33.3 32.3 NA 1990-2015 Industrial Price 8.33 8.07 6.96 6.77 6.89

  20. Idaho Natural Gas Prices

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

    Imports Price 4.19 3.90 2.59 3.34 4.14 1989-2014 Exports Price 5.85 4.74 -- 3.27 -- 1999-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 4.82 4.65 4.07 3.93 4.29 NA 1984-2015 Residential Price 8.95 8.80 8.26 8.12 8.54 8.62 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 8.21 8.09 7.35 7.29 7.70 7.61 1967-2015 Percentage of Total Commercial Deliveries included in Prices 82.0 80.8 77.0 77.4

  1. Louisiana Natural Gas Prices

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

    23 1967-2010 Imports Price 4.84 7.57 7.98 14.40 14.59 1989-2014 Exports Price 7.07 9.63 11.80 -- -- 2007-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.43 5.67 3.48 4.12 4.90 3.32 1984-2015 Residential Price 11.73 11.37 11.54 10.80 10.89 10.71 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 9.88 9.36 8.44 8.59 9.01 7.93 1967-2015 Percentage of Total Commercial Deliveries included in Prices

  2. Maine Natural Gas Prices

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

    Imports Price 4.94 4.40 3.45 4.86 9.71 1999-2014 Exports Price 4.53 4.46 4.30 8.43 6.68 2007-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.19 8.14 7.73 7.35 10.33 NA 1984-2015 Residential Price 14.14 14.20 15.94 15.21 16.90 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 99.9 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 11.71 11.69 12.22 12.79 15.13 14.40 1967-2015 Percentage of Total Commercial Deliveries included in Prices 45.0 45.8

  3. Maryland Natural Gas Prices

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

    Wellhead Price NA 1967-2010 Imports Price 5.37 5.30 13.82 15.29 8.34 1999-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.49 6.26 5.67 5.37 6.36 4.99 1984-2015 Residential Price 12.44 12.10 12.17 11.67 12.21 12.05 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 79.3 77.0 74.3 72.8 73.1 1989-2015 Commercial Price 9.87 10.29 10.00 10.06 10.52 10.00 1967-2015 Percentage of Total Commercial Deliveries included in Prices 100.0 27.3 24.7 26.2 27.3 27.4

  4. Diesel prices slightly increase

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

    Diesel prices slightly increase The U.S. average retail price for on-highway diesel fuel rose slightly to 3.87 a gallon on Monday. That's up 2-tenths of a penny from a week ago,...

  5. Residential heating oil price

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

    heating oil price decreases The average retail price for home heating oil fell 3.6 cents from a week ago to 3.04 per gallon. That's down 99.4 cents from a year ago, based on the...

  6. Residential heating oil price

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

    heating oil price decreases The average retail price for home heating oil fell 6.3 cents from a week ago to 2.91 per gallon. That's down 1.10 from a year ago, based on the...

  7. Diesel prices rise slightly

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

    Diesel prices rise slightly The U.S. average retail price for on-highway diesel fuel rose slightly to 4.16 a gallon on Monday. That's up 2-tenths of a penny from a week ago, based...

  8. Residential heating oil price

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

    heating oil price decreases The average retail price for home heating oil fell 7.5 cents from a week ago to 2.84 per gallon. That's down 1.22 from a year ago, based on the...

  9. Residential heating oil price

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

    heating oil price decreases The average retail price for home heating oil fell 7.6 cents from a week ago to 2.97 per gallon. That's down 1.05 from a year ago, based on the...

  10. Diesel prices decrease slightly

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

    Diesel prices decrease slightly The U.S. average retail price for on-highway diesel fuel fell slightly to 3.84 a gallon on Monday. That's down 3-tenths of a penny from a week ago,...

  11. Diesel prices slightly decrease

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

    Diesel prices slightly decrease The U.S. average retail price for on-highway diesel fuel fell slightly to 3.84 a gallon on Monday. That's down 8-tenths of a penny from a week ago,...

  12. Diesel prices slightly decrease

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

    Diesel prices slightly decrease The U.S. average retail price for on-highway diesel fuel fell to 3.87 a gallon on Monday. That's down 1.1 cents from a week ago, based on the...

  13. Residential heating oil price

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

    heating oil price decreases The average retail price for home heating oil fell 4.1 cents from a week ago to 2.89 per gallon, based on the residential heating fuel survey by the...

  14. Diesel prices increase nationally

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

    Diesel prices increase nationally The U.S. average retail price for on-highway diesel fuel rose to 3.91 a gallon on Monday. That's up 1.3 cents from a week ago, based on the...

  15. Supernova relic neutrinos and the supernova rate problem: Analysis of uncertainties and detectability of ONeMg and failed supernovae

    SciTech Connect (OSTI)

    Mathews, Grant J. [Center for Astrophysics, Department of Physics, University of Notre Dame, Notre Dame, IN 46556 (United States); Hidaka, Jun; Kajino, Toshitaka; Suzuki, Jyutaro [National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588 (Japan)

    2014-08-01

    Direct measurements of the core collapse supernova rate (R{sub SN}) in the redshift range 0 ? z ? 1 appear to be about a factor of two smaller than the rate inferred from the measured cosmic massive star formation rate (SFR). This discrepancy would imply that about one-half of the massive stars that have been born in the local observed comoving volume did not explode as luminous supernovae. In this work, we explore the possibility that one could clarify the source of this 'supernova rate problem' by detecting the energy spectrum of supernova relic neutrinos with a next generation 10{sup 6} ton water ?erenkov detector like Hyper-Kamiokande. First, we re-examine the supernova rate problem. We make a conservative alternative compilation of the measured SFR data over the redshift range 0 ?z ? 7. We show that by only including published SFR data for which the dust obscuration has been directly determined, the ratio of the observed massive SFR to the observed supernova rate R{sub SN} has large uncertainties ?1.8{sub ?0.6}{sup +1.6} and is statistically consistent with no supernova rate problem. If we further consider that a significant fraction of massive stars will end their lives as faint ONeMg SNe or as failed SNe leading to a black hole remnant, then the ratio reduces to ?1.1{sub ?0.4}{sup +1.0} and the rate problem is essentially solved. We next examine the prospects for detecting this solution to the supernova rate problem. We first study the sources of uncertainty involved in the theoretical estimates of the neutrino detection rate and analyze whether the spectrum of relic neutrinos can be used to independently identify the existence of a supernova rate problem and its source. We consider an ensemble of published and unpublished core collapse supernova simulation models to estimate the uncertainties in the anticipated neutrino luminosities and temperatures. We illustrate how the spectrum of detector events might be used to establish the average neutrino temperature and constrain SN models. We also consider supernova ?-process nucleosynthesis to deduce constraints on the temperature of the various neutrino flavors. We study the effects of neutrino oscillations on the detected neutrino energy spectrum and also show that one might distinguish the equation of state (EoS) as well as the cause of the possible missing luminous supernovae from the detection of supernova relic neutrinos. We also analyze a possible enhanced contribution from failed supernovae leading to a black hole remnant as a solution to the supernova rate problem. We conclude that indeed it might be possible (though difficult) to measure the neutrino temperature, neutrino oscillations, and the EoS and confirm this source of missing luminous supernovae by the detection of the spectrum of relic neutrinos.

  16. Uncertainty and sensitivity analysis in the 2008 performance assessment for the proposed repository for high-level radioactive waste at Yucca Mountain, Nevada.

    SciTech Connect (OSTI)

    Helton, Jon Craig; Sallaberry, Cedric M.; Hansen, Clifford W.

    2010-05-01

    Extensive work has been carried out by the U.S. Department of Energy (DOE) in the development of a proposed geologic repository at Yucca Mountain (YM), Nevada, for the disposal of high-level radioactive waste. As part of this development, an extensive performance assessment (PA) for the YM repository was completed in 2008 [1] and supported a license application by the DOE to the U.S. Nuclear Regulatory Commission (NRC) for the construction of the YM repository [2]. This presentation provides an overview of the conceptual and computational structure of the indicated PA (hereafter referred to as the 2008 YM PA) and the roles that uncertainty analysis and sensitivity analysis play in this structure.

  17. Residential propane price

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases The average retail price for propane is $2.36 per gallon, down 1 cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.92 per gallon, down 8-tenths of a cent from last week, and down 44.4 cents

  18. Residential propane price

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $2.29 per gallon, down 3.1 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.80 per gallon, down 2.4 cents from last week

  19. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases The average retail price for propane is $2.32 per gallon, down 2 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.82 per gallon, down 2.4 cents from last week. This is Marcela Rourk,

  20. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $2.01 per gallon, up 1.2 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.47 per gallon, up 9-tenths of a cent from last week, and down 44.8

  1. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $2.02 per gallon, up 4-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.48 per gallon, down 1-tenth of a cent from last week, and down 43

  2. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $2.03 per gallon, up 1 cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.48 per gallon, up 9-tenths of a cent from last week, and down 40.7

  3. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $1.96 per gallon, up 7-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.43 per gallon, up 1.3 cents from last week, and down 51.7

  4. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $1.97 per gallon, up 6-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.44 per gallon, up 7-tenths of a cent from last week, and down 50.

  5. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $1.98 per gallon, up 1.1 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.44 per gallon, up 4-tenths of a cent from last week, and down 49.7

  6. Residential propane prices available

    Gasoline and Diesel Fuel Update (EIA)

    propane prices available The average retail price for propane is $1.94 per gallon, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.40 per gallon. This is Marcela Rourk, with EIA, in Washington.

  7. Residential propane prices available

    Gasoline and Diesel Fuel Update (EIA)

    8, 2015 Residential propane price increases The average retail price for propane is $1.91 per gallon, up 1.4 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.39 per gallon, up 1 cent from last week, and down 55.3

  8. Mineral dissolution and precipitation during CO2 injection at the Frio-I Brine Pilot: Geochemical modeling and uncertainty analysis

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Ilgen, A. G.; Cygan, R. T.

    2015-12-07

    During the Frio-I Brine Pilot CO2 injection experiment in 2004, distinct geochemical changes in response to the injection of 1600 tons of CO2 were recorded in samples collected from the monitoring well. Previous geochemical modeling studies have considered dissolution of calcite and iron oxyhydroxides, or release of adsorbed iron, as the most likely sources of the increased ion concentrations. We explore in this modeling study possible alternative sources of the increasing calcium and iron, based on the data from the detailed petrographic characterization of the Upper Frio Formation “C”. Particularly, we evaluate whether dissolution of pyrite and oligoclase (anorthitemore » component) can account for the observed geochemical changes. Due to kinetic limitations, dissolution of pyrite and anorthite cannot account for the increased iron and calcium concentrations on the time scale of the field test (10 days). However, dissolution of these minerals is contributing to carbonate and clay mineral precipitation on the longer time scales (1000 years). The one-dimensional reactive transport model predicts carbonate minerals, dolomite and ankerite, as well as clay minerals kaolinite, nontronite and montmorillonite, will precipitate in the Frio Formation “C” sandstone as the system progresses towards chemical equilibrium during a 1000-year period. Cumulative uncertainties associated with using different thermodynamic databases, activity correction models (Pitzer vs. B-dot), and extrapolating to reservoir temperature, are manifested in the difference in the predicted mineral phases. Furthermore, these models are consistent with regards to the total volume of mineral precipitation and porosity values which are predicted to within 0.002%.« less

  9. Residential propane prices available

    Gasoline and Diesel Fuel Update (EIA)

    propane prices available The average retail price for propane is $2.30 per gallon, based on the U.S. Energy Information Administration's weekly residential heating fuel survey. Propane prices in the Midwest region, which has the most households that use propane, averaged $1.89 a gallon. This is Marcela Rourk, with EIA, in Washington. The EIA has expanded its propane price survey to include 14 more states located mostly in the South and the West. The survey now looks at propane prices in 38

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

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

    monthly supplement to the EIA Short-Term Energy Outlook. (http:www.eia.doe.govemeu... in mid-January, as is seen in the green curve in Figure 1, going to a level of ...

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

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

    growth, Organization of Petroleum ... Journal of Environmental Economics and Management, Vol. 46 (2003) pp. 52 - 71. Ogawa, ... volatility, John Wiley & Sons Ltd. (2005). ...

  12. Alabama Natural Gas Prices

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

    4.46 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.46 5.80 5.18 4.65 4.93 NA 1984-2015 Residential Price 15.79 15.08 16.20 15.47 14.59 13.95 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 99.0 1989-2015 Commercial Price 13.34 12.36 12.56 12.35 11.92 11.03 1967-2015 Percentage of Total Commercial Deliveries included in Prices 79.3 78.9 76.2 76.6 78.4 77.6 1990-2015 Industrial Price 6.64 5.57 4.35 4.98 5.49 3.94

  13. Alaska Natural Gas Prices

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

    3.17 1967-2010 Exports Price 12.19 12.88 15.71 -- 15.74 1989-2014 Pipeline and Distribution Use Price 1970-2005 Citygate Price 6.67 6.53 6.14 6.02 6.34 6.57 1988-2015 Residential Price 8.89 8.77 8.47 8.85 9.11 9.68 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 8.78 8.09 8.09 8.34 8.30 7.80 1967-2015 Percentage of Total Commercial Deliveries included in Prices 87.7 88.6 94.9 94.5 94.5 98.2 1990-2015

  14. Arizona Natural Gas Prices

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

    11 1967-2010 Exports Price 4.57 4.28 3.07 4.17 5.15 1989-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.59 5.91 4.68 4.73 5.20 NA 1984-2015 Residential Price 15.87 15.04 15.75 13.92 17.20 17.04 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 10.72 9.99 9.35 8.76 10.34 10.53 1967-2015 Percentage of Total Commercial Deliveries included in Prices 88.7 87.8 86.6 85.5 84.4 83.8 1990-2015

  15. Arkansas Natural Gas Prices

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

    3.84 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.76 6.27 5.36 4.99 5.84 4.76 1984-2015 Residential Price 11.53 11.46 11.82 10.46 10.39 11.20 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 8.89 8.90 7.99 7.68 7.88 8.08 1967-2015 Percentage of Total Commercial Deliveries included in Prices 55.6 51.5 40.2 43.7 45.5 42.5 1990-2015 Industrial Price 7.28 7.44 6.38 6.74 6.99 6.97

  16. Missouri Natural Gas Prices

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

    1967-1997 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.17 5.85 5.27 4.99 5.76 4.65 1984-2015 Residential Price 11.66 12.02 12.25 10.88 10.83 11.59 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 10.28 9.99 9.54 9.00 8.96 9.10 1967-2015 Percentage of Total Commercial Deliveries included in Prices 76.5 73.1 69.2 72.3 70.5 71.1 1990-2015 Industrial Price 8.70 8.54 7.85 8.19 8.00 7.75 1997-2015

  17. Nebraska Natural Gas Prices

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

    8 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.62 5.11 4.31 4.61 5.58 NA 1984-2015 Residential Price 8.95 8.84 8.68 8.39 8.77 8.94 1967-2015 Percentage of Total Residential Deliveries included in Prices 87.4 87.3 85.8 87.5 87.8 87.2 1989-2015 Commercial Price 7.08 6.69 6.19 6.49 7.27 6.54 1967-2015 Percentage of Total Commercial Deliveries included in Prices 60.6 60.6 55.8 57.3 56.4 56.1 1990-2015 Industrial Price 5.85 5.61 4.34 4.72 5.69 4.61 1997-2015 Percentage of

  18. Nevada Natural Gas Prices

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

    NA 2006-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.19 6.77 5.13 5.16 5.90 4.06 1984-2015 Residential Price 12.25 10.66 10.14 9.42 11.44 11.82 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 9.77 8.07 7.43 6.61 8.21 8.66 1967-2015 Percentage of Total Commercial Deliveries included in Prices 65.4 64.3 61.4 60.1 58.4 57.9 1990-2015 Industrial Price 10.53 8.99 7.34 6.66 7.83 NA 1997-2015

  19. Ohio Natural Gas Prices

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

    3 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.87 5.51 4.47 4.51 4.91 4.49 1984-2015 Residential Price 11.13 10.78 9.91 9.46 10.16 9.49 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 9.25 8.55 7.11 6.21 7.82 6.62 1967-2015 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1990-2015 Industrial Price 7.40 6.77 5.48 6.03 7.06 NA 1997-2015

  20. Oklahoma Natural Gas Prices

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

    71 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.18 5.67 5.00 4.75 5.35 4.59 1984-2015 Residential Price 11.12 10.32 11.10 9.71 10.10 10.26 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 9.77 8.94 8.95 8.05 8.26 8.22 1967-2015 Percentage of Total Commercial Deliveries included in Prices 47.5 46.3 41.1 44.6 45.3 43.7 1990-2015 Industrial Price 8.23 7.37 7.65 7.16 8.27 NA 1997-2015

  1. Oregon Natural Gas Prices

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

    92 1979-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.78 5.84 5.21 4.82 5.40 4.65 1984-2015 Residential Price 12.49 11.76 11.22 10.84 11.72 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 10.10 9.60 8.91 8.60 9.44 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices 97.4 97.4 96.9 96.6 96.0 NA 1990-2015 Industrial Price 7.05 6.84 5.87 5.79 6.20 6.38 1997-2015

  2. Pennsylvania Natural Gas Prices

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

    NA 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.04 6.28 5.52 5.26 5.59 NA 1984-2015 Residential Price 12.90 12.46 11.99 11.63 11.77 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 91.2 88.6 87.3 86.2 NA 1989-2015 Commercial Price 10.47 10.42 10.24 10.11 10.13 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices 100.0 48.5 42.1 40.2 41.4 NA 1990-2015 Industrial Price 8.23 9.86 9.58 9.13 9.95 NA 1997-2015 Percentage

  3. Tennessee Natural Gas Prices

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

    35 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.78 5.23 4.35 4.73 5.37 4.06 1984-2015 Residential Price 10.46 10.21 9.95 9.44 10.13 9.69 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 9.39 9.04 8.36 8.41 9.30 8.46 1967-2015 Percentage of Total Commercial Deliveries included in Prices 90.8 89.9 88.8 90.0 90.7 88.6 1990-2015 Industrial Price 6.64 6.15 4.98 5.62 6.31 4.89 1997-2015

  4. Utah Natural Gas Prices

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

    23 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.53 5.68 5.50 5.70 5.74 5.70 1984-2015 Residential Price 8.22 8.44 8.70 8.55 9.48 9.72 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 6.83 7.05 7.00 7.13 7.71 7.97 1967-2015 Percentage of Total Commercial Deliveries included in Prices 86.2 86.7 83.9 81.8 78.3 77.0 1990-2015 Industrial Price 5.57 5.50 4.69 5.22 5.83 5.89 1997-2015

  5. Vermont Natural Gas Prices

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

    6.54 5.81 4.90 5.72 6.61 1989-2014 Pipeline and Distribution Use Price 1982-2005 Citygate Price 8.29 7.98 6.63 6.16 7.08 NA 1984-2015 Residential Price 16.14 16.17 16.73 15.87 14.68 14.56 1980-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 11.82 11.90 12.09 7.57 9.13 NA 1980-2015 Percentage of Total Commercial Deliveries included in Prices 100 100 100 100 100 NA 1990-2015 Industrial Price 6.57 6.09 4.89 8.59 6.63

  6. Virginia Natural Gas Prices

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

    NA 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.88 6.64 5.64 5.54 5.98 NA 1984-2015 Residential Price 12.73 12.72 12.42 11.68 12.07 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 90.1 89.5 89.9 90.1 NA 1989-2015 Commercial Price 9.55 9.69 8.77 8.83 9.17 8.11 1967-2015 Percentage of Total Commercial Deliveries included in Prices 100.0 54.1 52.1 54.6 55.8 54.2 1990-2015 Industrial Price 6.68 6.44 5.29 6.02 6.43 NA 1997-2015 Percentage

  7. Colorado Natural Gas Prices

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

    3.96 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.26 4.94 4.26 4.76 5.42 3.96 1984-2015 Residential Price 8.13 8.25 8.28 7.85 8.89 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 NA 1989-2015 Commercial Price 7.58 7.84 7.58 7.26 8.15 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices 94.6 93.8 92.2 94.7 94.5 NA 1990-2015 Industrial Price 5.84 6.42 5.79 5.90 6.84 NA 1997-2015 Percentage of

  8. Georgia Natural Gas Prices

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

    Imports Price 4.39 4.20 2.78 3.36 4.33 1999-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.93 5.19 4.35 4.66 5.19 3.82 1984-2015 Residential Price 15.17 15.72 16.23 14.60 14.45 15.06 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 10.95 10.51 9.75 9.38 9.86 8.49 1967-2015 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1990-2015 Industrial

  9. Illinois Natural Gas Prices

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

    NA 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.52 5.09 4.11 4.43 6.28 3.82 1984-2015 Residential Price 9.39 8.78 8.26 8.20 9.59 7.95 1967-2015 Percentage of Total Residential Deliveries included in Prices 88.0 88.0 87.9 87.7 87.3 86.3 1989-2015 Commercial Price 8.76 8.27 7.78 7.57 8.86 7.26 1967-2015 Percentage of Total Commercial Deliveries included in Prices 42.3 38.1 36.8 38.4 38.5 NA 1990-2015 Industrial Price 7.13 6.84 5.63 6.00 7.75 5.36 1997-2015 Percentage of

  10. Indiana Natural Gas Prices

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

    4.13 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.52 4.97 4.23 4.38 5.63 NA 1984-2015 Residential Price 8.63 9.46 8.94 8.43 9.02 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 94.1 94.6 94.5 95.0 95.3 NA 1989-2015 Commercial Price 7.55 8.04 7.69 7.59 8.19 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices 72.5 70.2 67.4 68.2 67.6 NA 1990-2015 Industrial Price 5.65 6.53 6.19 6.54 7.45 NA 1997-2015 Percentage of Total

  11. Iowa Natural Gas Prices

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

    Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.69 5.27 4.84 4.95 6.24 NA 1984-2015 Residential Price 9.57 9.54 9.46 8.99 10.02 8.49 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 7.81 7.55 7.13 6.97 8.15 6.49 1967-2015 Percentage of Total Commercial Deliveries included in Prices 72.0 72.1 72.2 72.5 74.4 NA 1990-2015 Industrial Price 6.10 5.78 4.70 5.43 7.40 NA 1997-2015 Percentage of Total

  12. Kansas Natural Gas Prices

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

    23 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.08 5.53 4.74 4.98 6.10 NA 1984-2015 Residential Price 10.61 9.93 10.12 10.19 10.59 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 NA 1989-2015 Commercial Price 9.65 8.89 8.82 9.07 9.53 8.83 1967-2015 Percentage of Total Commercial Deliveries included in Prices 66.0 62.6 59.8 61.4 59.3 NA 1990-2015 Industrial Price 5.49 5.28 3.87 4.86 5.70 4.37 1997-2015 Percentage

  13. Kentucky Natural Gas Prices

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

    47 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.69 5.18 4.17 4.47 5.16 NA 1984-2015 Residential Price 10.02 10.44 10.19 9.80 10.62 10.94 1967-2015 Percentage of Total Residential Deliveries included in Prices 95.7 95.5 95.9 96.2 96.3 96.3 1989-2015 Commercial Price 8.61 8.79 8.28 8.32 9.04 8.80 1967-2015 Percentage of Total Commercial Deliveries included in Prices 80.5 79.2 77.4 78.8 80.5 79.2 1990-2015 Industrial Price 5.57 5.16 3.96 4.84 5.80 4.36 1997-2015

  14. Wisconsin Natural Gas Prices

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

    Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.14 5.65 4.88 4.88 6.96 4.71 1984-2015 Residential Price 10.34 9.77 9.27 8.65 10.52 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 8.53 8.03 7.34 6.94 8.74 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices 76.2 76.4 74.4 77.7 77.0 NA 1990-2015 Industrial Price 7.56 7.05 5.81 6.02 8.08 NA 1997-2015 Percentage of Total

  15. Wyoming Natural Gas Prices

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

    4.30 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.04 4.65 4.03 4.51 5.27 4.36 1984-2015 Residential Price 8.58 8.72 8.42 8.27 9.34 9.19 1967-2015 Percentage of Total Residential Deliveries included in Prices 75.4 75.6 75.3 73.8 72.9 73.3 1989-2015 Commercial Price 7.13 7.29 6.72 6.81 7.69 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices 65.3 64.0 62.6 62.9 60.8 NA 1990-2015 Industrial Price 4.91 5.57 4.87 4.62 5.89 NA 1997-2015 Percentage of

  16. Direct Aerosol Forcing Uncertainty

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

    Mccomiskey, Allison

    2008-01-15

    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.

  17. Achieving Robustness to Uncertainty for Financial Decision-making

    SciTech Connect (OSTI)

    Barnum, George M.; Van Buren, Kendra L.; Hemez, Francois M.; Song, Peter

    2014-01-10

    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.

  18. 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

    2013-09-01

    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.

  19. Statistics, Uncertainty, and Transmitted Variation

    SciTech Connect (OSTI)

    Wendelberger, Joanne Roth

    2014-11-05

    The field of Statistics provides methods for modeling and understanding data and making decisions in the presence of uncertainty. When examining response functions, variation present in the input variables will be transmitted via the response function to the output variables. This phenomenon can potentially have significant impacts on the uncertainty associated with results from subsequent analysis. This presentation will examine the concept of transmitted variation, its impact on designed experiments, and a method for identifying and estimating sources of transmitted variation in certain settings.

  20. Quantitative Analysis of Variability and Uncertainty in Environmental Data and Models. Volume 2. Performance, Emissions, and Cost of Combustion-Based NOx Controls for Wall and Tangential Furnace Coal-Fired Power Plants

    SciTech Connect (OSTI)

    Frey, H. Christopher; Tran, Loan K.

    1999-04-30

    This is Volume 2 of a two-volume set of reports describing work conducted at North Carolina State University sponsored by Grant Number DE-FG05-95ER30250 by the U.S. Department of Energy. The title of the project is Quantitative Analysis of Variability and Uncertainty in Acid Rain Assessments. The work conducted under sponsorship of this grant pertains primarily to two main topics: (1) development of new methods for quantitative analysis of variability and uncertainty applicable to any type of model; and (2) analysis of variability and uncertainty in the performance, emissions, and cost of electric power plant combustion-based NOx control technologies. These two main topics are reported separately in Volumes 1 and 2.

  1. Mississippi Natural Gas Prices

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

    3.81 3.82 3.64 3.68 NA 4.29 1989-2015 Residential Price 14.87 15.82 15.39 13.96 12.13 9.71 1989-2015 Percentage of Total Residential Deliveries included in Prices 99.3 100.0 100.0 100.0 NA 100.0 2002-2015 Commercial Price 7.79 NA NA 7.81 7.98 8.06 1989-2015 Percentage of Total Commercial Deliveries included in Prices 81.0 NA NA 82.3 NA 86.1 1989-2015 Industrial Price 4.49 3.95 4.46 4.21 4.26 4.12 2001-2015 Percentage of Total Industrial Deliveries included in Prices 8.7 9.3 9.6 8.8 8.5 8.4

  2. Connecticut Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    4.58 4.45 4.59 3.58 3.36 3.80 1989-2015 Residential Price 18.22 19.33 NA 15.30 12.50 11.82 1989-2015 Percentage of Total Residential Deliveries included in Prices 95.8 94.3 NA 94.6 95.9 96.4 2002-2015 Commercial Price 9.29 9.52 NA 9.53 8.48 8.18 1989-2015 Percentage of Total Commercial Deliveries included in Prices 71.9 67.6 NA 73.5 75.4 78.4 1989-2015 Industrial Price 5.88 5.66 6.59 5.76 5.87 6.60 2001-2015 Percentage of Total Industrial Deliveries included in Prices 43.9 45.3 44.5 47.8 49.8

  3. Delaware Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    10.56 10.03 10.35 6.54 5.14 4.98 1989-2015 Residential Price 21.80 23.75 23.22 NA 14.03 11.09 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 13.35 13.86 13.93 12.54 10.82 9.15 1989-2015 Percentage of Total Commercial Deliveries included in Prices 35.8 33.4 29.9 31.6 31.6 38.9 1989-2015 Industrial Price 8.82 11.38 11.40 11.15 9.62 8.32 2001-2015 Percentage of Total Industrial Deliveries included in Prices 0.2

  4. Georgia Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    16 4.16 4.14 3.80 3.37 3.51 1989-2015 Residential Price 25.45 24.78 25.75 20.43 15.20 14.41 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 9.08 9.07 9.38 8.65 9.72 7.80 1989-2015 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Industrial Price 4.06 4.25 4.15 4.02 3.65 3.74 2001-2015 Percentage of Total Industrial Deliveries included in Prices 20.0

  5. Hawaii Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    22.97 17.72 15.38 14.59 14.92 14.81 1989-2015 Residential Price 45.12 37.43 36.33 37.38 38.46 38.20 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 36.02 30.45 28.60 27.06 28.13 28.72 1989-2015 Percentage of Total Commercial Deliveries included in Prices 100 100 100 100 100 100 1989-2015 Industrial Price 21.32 19.06 18.87 17.77 17.47 14.88 2001-2015 Percentage of Total Industrial Deliveries included in Prices

  6. Idaho Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    65 4.50 NA 3.75 3.52 3.34 1989-2015 Residential Price 10.72 10.96 9.56 8.93 7.74 7.89 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 8.41 8.12 8.00 7.65 6.93 7.12 1989-2015 Percentage of Total Commercial Deliveries included in Prices 52.9 58.6 64.4 67.0 79.0 83.5 1989-2015 Industrial Price 6.09 6.08 5.93 5.77 NA 5.39 2001-2015 Percentage of Total Industrial Deliveries included in Prices 2.2 NA 1.9 NA NA 2.4

  7. Illinois Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Citygate Price 5.12 4.75 4.91 3.61 3.17 3.43 1989-2015 Residential Price 15.10 15.87 15.35 9.68 7.11 6.28 1989-2015 Percentage of Total Residential Deliveries included in Prices 85.2 85.3 86.3 87.1 88.2 86.8 2002-2015 Commercial Price 11.48 12.68 11.81 8.21 6.63 6.02 1989-2015 Percentage of Total Commercial Deliveries included in Prices 25.2 21.9 22.8 30.4 NA 37.1 1989-2015 Industrial Price 6.32 5.82 6.00 5.24 4.48 4.54 2001-2015 Percentage

  8. Indiana Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Citygate Price 4.57 4.82 4.58 NA 3.62 3.52 1989-2015 Residential Price 17.18 17.31 15.21 9.26 7.32 6.91 1989-2015 Percentage of Total Residential Deliveries included in Prices 95.1 95.5 95.9 95.4 95.9 96.0 2002-2015 Commercial Price 10.56 10.62 8.02 NA 6.05 6.16 1989-2015 Percentage of Total Commercial Deliveries included in Prices 56.8 53.9 57.5 NA 65.5 67.8 1989-2015 Industrial Price 6.22 5.79 5.15 4.23 4.36 4.74 2001-2015 Percentage of

  9. Iowa Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    54 4.61 4.62 3.58 3.81 3.79 1989-2015 Residential Price 15.67 17.34 16.40 13.15 8.41 7.29 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 8.45 8.95 8.14 5.99 6.39 5.72 1989-2015 Percentage of Total Commercial Deliveries included in Prices 59.1 55.5 59.3 70.3 NA 75.2 1989-2015 Industrial Price 5.32 5.00 NA 4.46 5.14 4.50 2001-2015 Percentage of Total Industrial Deliveries included in Prices 2.4 1.9 NA 5.2 6.3

  10. Kansas Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Citygate Price 5.39 NA NA 5.53 3.94 3.55 1989-2015 Residential Price 19.38 20.79 19.68 14.37 NA 7.81 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 NA 100.0 2002-2015 Commercial Price 12.42 11.98 12.47 9.39 7.25 7.08 1989-2015 Percentage of Total Commercial Deliveries included in Prices 31.1 NA 35.8 40.1 53.1 59.0 1989-2015 Industrial Price 4.12 4.07 4.02 4.31 4.76 5.79 2001-2015 Percentage of

  11. Alabama Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Citygate Price 3.80 4.04 3.81 3.83 3.61 3.27 1989-2015 Residential Price 20.35 20.60 20.38 19.12 17.67 14.30 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 68.8 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 11.89 11.93 11.75 11.40 11.47 10.73 1989-2015 Percentage of Total Commercial Deliveries included in Prices 70.5 69.7 69.7 68.6 69.9 76.2 1989-2015 Industrial Price 3.82 3.91 3.68 3.48 3.33 3.48

  12. Arizona Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Citygate Price 4.55 4.53 4.48 4.25 4.42 NA 1989-2015 Residential Price 23.59 24.01 23.01 20.77 14.57 12.75 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 10.67 10.52 10.40 10.14 9.36 9.17 1989-2015 Percentage of Total Commercial Deliveries included in Prices 80.7 79.4 80.1 80.2 83.3 85.5 1989-2015 Industrial Price 6.80 NA 6.62 6.36 6.35 6.43 2001-2015

  13. Tennessee Natural Gas Prices

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

    2 4.00 4.03 3.80 3.49 3.45 1989-2015 Residential Price 17.72 19.78 17.47 14.51 11.82 9.28 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 9.34 9.86 9.37 8.92 8.72 8.33 1989-2015 Percentage of Total Commercial Deliveries included in Prices 79.8 76.7 79.7 81.9 85.5 88.4 1989-2015 Industrial Price 4.66 4.65 4.49 4.32 4.34 4.45 2001-2015 Percentage of Total Industrial Deliveries included in Prices 27.8 29.5 29.3

  14. Ohio Natural Gas Prices

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

    3.24 3.04 2.34 3.02 3.45 3.75 1989-2015 Residential Price 23.83 25.46 24.31 15.36 9.68 7.40 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 8.14 8.02 7.99 6.79 6.03 5.53 1989-2015 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Industrial Price 6.43 7.26 NA 6.68 5.64 5.55 2001-2015 Percentage of Total Industrial Deliveries included in Prices 1.4 1.0 NA

  15. Oklahoma Natural Gas Prices

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

    5.17 5.43 5.45 5.28 4.22 3.86 1989-2015 Residential Price 23.13 26.66 25.23 23.39 14.41 7.35 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 13.62 15.18 14.85 14.21 10.78 6.14 1989-2015 Percentage of Total Commercial Deliveries included in Prices 30.4 28.6 29.4 30.1 30.8 47.6 1989-2015 Industrial Price NA 8.56 NA 9.67 7.72 6.04 2001-2015 Percentage of Total Industrial Deliveries included in Prices NA 0.4 NA

  16. Oregon Natural Gas Prices

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

    6.30 5.84 5.19 5.15 3.92 3.72 1989-2015 Residential Price 16.60 17.52 14.81 13.88 10.10 NA 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 10.76 11.12 10.13 10.18 8.39 9.09 1989-2015 Percentage of Total Commercial Deliveries included in Prices 94.3 94.0 94.2 94.7 95.1 95.3 1989-2015 Industrial Price 6.39 6.49 6.47 6.51 5.67 5.59 2001-2015 Percentage of Total Industrial Deliveries included in Prices 15.3 15.4

  17. Vermont Natural Gas Prices

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

    6.39 6.34 5.96 4.59 5.08 5.93 1989-2015 Residential Price 21.69 23.04 23.16 18.41 14.89 13.84 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 6.10 NA 6.97 6.20 6.65 7.37 1989-2015 Percentage of Total Commercial Deliveries included in Prices 100 100 100 100 100 100 1989-2015 Industrial Price 5.90 4.53 4.65 5.58 5.42 5.81 2001-2015 Percentage of Total Industrial Deliveries included in Prices 100.0 100.0 100.0

  18. Wisconsin Natural Gas Prices

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

    68 5.95 5.61 4.25 4.21 3.96 1989-2015 Residential Price 13.27 14.05 12.80 8.42 7.89 7.38 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 6.42 6.44 6.18 5.37 6.34 6.12 1989-2015 Percentage of Total Commercial Deliveries included in Prices 54.8 57.2 58.1 69.4 75.1 77.7 1989-2015 Industrial Price 4.54 4.91 4.56 4.69 5.37 5.43 2001-2015 Percentage of Total Industrial Deliveries included in Prices 11.5 11.1 12.6

  19. Residential propane price

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases The average retail price for propane is $2.35 per gallon, down 1.1 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.92 per gallon, down 3-tenths of a cent from last week, and down 47.9 cents

  20. Residential propane price

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $2.39 per gallon, up 3.9 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.91 per gallon, down 8-tenths of a cent from last week, and down 63.1 cents

  1. Residential propane price

    Gasoline and Diesel Fuel Update (EIA)

    propane price decrease The average retail price for propane is $2.37 per gallon, down 1.3 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.93 per gallon, down 3-tenths of a cent from last week, and down 39.6 cents

  2. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases The average retail price for propane is $2.38 per gallon, down 1.1 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.91 per gallon, down 4-tenths of a cent from last week, and down $2.29 cents

  3. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases The average retail price for propane is $2.37 per gallon, down 9-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.89 per gallon, down 1.4 cents from last week, and down $1.93 cents

  4. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases The average retail price for propane is $2.36 per gallon, down 6-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.89 per gallon, down 4-tenths of a cent from last week, and down $1.67 cents from a year ago. This is Marcela Rourk, with EIA, in Washington.

  5. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases The average retail price for propane is $2.36 per gallon, down 7-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.89 per gallon, down 1.1 cents from last week, and down $1.43 cents from a year ago. This is Marcela Rourk, with EIA, in Washington.

  6. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases The average retail price for propane is $2.35 per gallon, down 3-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.88 per gallon, down 3-tenths of a cent from last week, and down $1.18 from a year ago. This is Marcela Rourk, with EIA, in Washington.

  7. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases The average retail price for propane is $2.36 per gallon, down 1.1 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.86 per gallon, down 1.6 cents from last week, and down 72.7 cents from a year ago. This is Marcela Rourk,

  8. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    8, 2015 Residential propane price decreases The average retail price for propane is $2.34 per gallon, down 1.7 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.85 per gallon, down 1.2 cents from last week, and down 63.2

  9. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    6, 2014 Residential propane price decreases The average retail price for propane fell to $3.48 per gallon, down 15.9 cents from a week ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged 3.06 a gallon, down 24.8 cents from last week, but up $1.28 from a year ago. This is Marcela Rourk, with EIA, in Washington.

  10. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    05, 2014 Residential propane price decreases The average retail price for propane fell to $2.40 per gallon, down 1.2 cents from a week ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.95 per gallon, up 8-tenths of a cent from last week, and down 1.9

  11. Residential propane price decreases

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases The average retail price for propane is $2.39 per gallon, down 2.2 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.94 per gallon, down 1.3 cents from last week, and down 17.5 cents from a year ago. This is Marcela Rourk, with EIA, in Washington.

  12. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $2.00 per gallon, up 7-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.46 per gallon, up 4-tenths of a cent from last week, and down 46.2

  13. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $2.02 per gallon, up 5-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.48 per gallon, up 7-tenths of a cent from last week, and down 43.3

  14. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $2.02 per gallon, up 4-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.47 per gallon, down 2-tenths of a cent from last week, and down 41.9

  15. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    Residential propane price virtually unchanged The average retail price for propane is $2.03 per gallon, up 1-tenth of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.48 per gallon, down 1-tenths of a cent from last week, and down 39.8

  16. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    Residential propane price decreases The average retail price for propane is $2.03 per gallon, down 6-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.48 per gallon, down 6-tenths of a cent from last week, and down 40 cents

  17. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    Residential propane price decreases The average retail price for propane is $2.03 per gallon, down 2-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.47 per gallon, down 6-tenths of a cent from last week, and down 41 cents

  18. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    4, 2015 Residential propane price increases The average retail price for propane is $2.36 per gallon, up half of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.88 per gallon, down 1-tenth of a cent from last week, and down 90.5

  19. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    Residential propane price decreases The average retail price for propane is $2.02 per gallon, down 5-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.46 per gallon, down 7-tenths of a cent from last week, and down 40 cents

  20. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $1.96 per gallon, up 1.8 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.42 per gallon, up 6-tenths of a cent from last week, and down 52.9 cents

  1. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $2.41 per gallon, up 6-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.95 per gallon, up 2-tenths of a cent from last week, and down 12.7 cents from a year ago. This is Marcela Rourk, with EIA, in Washington.

  2. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $1.98 per gallon, up 5-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.45 per gallon, up 6-tenths of a cent from last week, and down 48.2

  3. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    propane price increases The average retail price for propane is $1.99 per gallon, up 3-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.45 per gallon, up 2-tenths of a cent from last week, and down 47.6

  4. Residential propane prices available

    Gasoline and Diesel Fuel Update (EIA)

    Residential propane price decreases The average retail price for propane is $1.91 per gallon, down 6.7 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.40 per gallon, down 1.6 cents from last week, and down 49.5 cents from a year ago. This is Marcela Rourk, with EIA, in Washington.

  5. Residential propane prices available

    Gasoline and Diesel Fuel Update (EIA)

    1, 2015 Residential propane price increases The average retail price for propane is $1.90 per gallon, up 2-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.38 per gallon, up 1.1 cents from last week, and down 53 cents from a year ago. This is Marcela Rourk

  6. Residential propane prices available

    Gasoline and Diesel Fuel Update (EIA)

    4, 2015 Residential propane price increases The average retail price for propane is $1.92 per gallon, up 1.4 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.42 per gallon, up 2.6 cents from last week, and down 53.2

  7. Residential propane prices available

    Gasoline and Diesel Fuel Update (EIA)

    Residential propane price decreases The average retail price for propane is $1.92 per gallon, down 6-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.40 per gallon, down 1.2 cents from last week, and down 54.8 cents from a year ago. This is Marcela Rourk, with EIA, in Washington.

  8. Residential propane prices available

    Gasoline and Diesel Fuel Update (EIA)

    8, 2015 Residential propane price increases The average retail price for propane is $1.94 per gallon, up 2 cents from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.42 per gallon, up 1 cent from last week, and down 52.8 cents from a year ago.

  9. Residential propane prices decreases

    Gasoline and Diesel Fuel Update (EIA)

    5, 2014 Residential propane prices decreases The average retail price for propane fell to $3.89 per gallon, that's down 11.9 cents from a week ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged 3.83 a gallon, down 36.8 cents from last week, but up $2.05 from a year ago. This is Amerine Woodyard

  10. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    propane prices increase The average retail price for propane rose 3.9 cents from a week ago to $2.80 per gallon. That's up 53.7 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged 2.32 a gallon, up 3.8 cents from last week, and up 59

  11. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    propane prices increase The average retail price for propane rose 2.5 cents from a week ago to $2.83 per gallon. That's up 56 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged 2.36 a gallon, up 3.9 cents from last week, and up 62.3

  12. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    propane prices increase The average retail price for propane rose to $2.40 per gallon, up 1.1 cents from a week ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.94 a gallon, up 2.9 cents from last week, and up 2.6 cents from a year ago. This is Marcela Rourk, with EIA, in Washington.

  13. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    propane prices increase The average retail price for propane rose 5.5 cents per gallon from last week to $2.62 per gallon; up 37.4 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. The retail price for propane in the Midwest region averaged 2.11 per gallon, up 3.4 cents per gallon from last week, and up 39.6

  14. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    propane prices increase The average retail price for propane rose 9.1 cents from a week ago to $2.71 per gallon. That's up 46.9 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged 2.22 a gallon, up 11 cents from last week, and up 50.8 cents from a year ago

  15. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    propane prices increase The average retail price for propane rose 4.8 cents from a week ago to $2.76 per gallon. That's up 51.2 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged 2.28 a gallon, up 6.3 cents from last week, and up 56.4

  16. Residential propane prices stable

    Gasoline and Diesel Fuel Update (EIA)

    propane prices stable The average retail price for propane is $2.37 per gallon. That's down 4-tenths of a penny from a week ago, based on the U.S. Energy Information Administration's weekly residential heating fuel survey. Propane prices in the Midwest region averaged $1.89 a gallon. Down 2-tenths of a cent from last week. This is Amerine Woodyard, with EIA, in Washington.

  17. Residential propane prices stable

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases The average retail price for propane is $2.40 per gallon, down 9-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.94 per gallon, down 7-tenths of a cent from . last week, and down 8.7 cents from a year ago This is Marcela Rourk, with EIA, in Washington.

  18. Residential propane prices surges

    Gasoline and Diesel Fuel Update (EIA)

    5, 2014 Residential propane price decreases The average retail price for propane fell to $3.30 per gallon, down 17.5 cents from a week ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged 2.78 a gallon, down 27.9 cents from last week, but up 99.3

  19. Residential propane prices surges

    Gasoline and Diesel Fuel Update (EIA)

    2, 2014 Residential propane price decreases The average retail price for propane fell to $3.17 per gallon, down 13.1 cents from a week ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged 2.60 a gallon, down 18.5 cents from last week, but up 88.1

  20. Residential propane prices surges

    Gasoline and Diesel Fuel Update (EIA)

    9, 2014 Residential propane price decreases The average retail price for propane fell to $3.08 per gallon, down 8.6 cents from a week ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged 2.48 a gallon, down 10.7 cents from last week, but up 69.7

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

    Information AdministrationPetroleum Marketing Annual 2001 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

  2. Crude Oil Prices

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

    Information AdministrationPetroleum Marketing Annual 1998 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

  3. Crude Oil Prices

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

    Information AdministrationPetroleum Marketing Annual 1999 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

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    Broader source: Energy.gov [DOE]

    The Price-Anderson Act (PAA) provides a system of indemnification for legal liability resulting from a nuclear incident in connection with contractual activity for DOE.

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    subcontracts. *Act as a consultant and provide advice to Cost Compliance personnel on the pricing of complex contracts andor agreements. *Perform analysis and provide assistance...

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

    2010-06-17

    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.

  8. Price of Motor Gasoline Through Retail Outlets

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

    & Stocks by State (Dollars per Gallon Excluding Taxes) Data Series: Retail Price - Motor Gasoline Retail Price - Regular Gasoline Retail Price - Midgrade Gasoline Retail Price...

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

    SciTech Connect (OSTI)

    1999-03-01

    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.

  10. The principal component analysis method used with polynomial Chaos expansion to propagate uncertainties through critical transport problems

    SciTech Connect (OSTI)

    Rising, M. E.; Prinja, A. K.

    2012-07-01

    A critical neutron transport problem with random material properties is introduced. The total cross section and the average neutron multiplicity are assumed to be uncertain, characterized by the mean and variance with a log-normal distribution. The average neutron multiplicity and the total cross section are assumed to be uncorrected and the material properties for differing materials are also assumed to be uncorrected. The principal component analysis method is used to decompose the covariance matrix into eigenvalues and eigenvectors and then 'realizations' of the material properties can be computed. A simple Monte Carlo brute force sampling of the decomposed covariance matrix is employed to obtain a benchmark result for each test problem. In order to save computational time and to characterize the moments and probability density function of the multiplication factor the polynomial chaos expansion method is employed along with the stochastic collocation method. A Gauss-Hermite quadrature set is convolved into a multidimensional tensor product quadrature set and is successfully used to compute the polynomial chaos expansion coefficients of the multiplication factor. Finally, for a particular critical fuel pin assembly the appropriate number of random variables and polynomial expansion order are investigated. (authors)

  11. Uncertainties in Air Exchange using Continuous-Injection, Long...

    Office of Scientific and Technical Information (OSTI)

    people to minimize experimental costs. In this article we will conduct a first-principles error analysis to estimate the uncertainties and then compare that analysis to CILTS...

  12. Montana Natural Gas Prices

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

    24 3.43 3.36 3.10 3.28 2.87 1989-2015 Residential Price 10.00 11.68 11.78 11.04 9.01 7.34 1989-2015 Percentage of Total Residential Deliveries included in Prices 99.8 99.8 99.8...

  13. Missouri Natural Gas Prices

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

    6.99 7.38 7.28 6.75 5.35 3.86 1989-2015 Residential Price 20.81 23.68 25.19 23.91 20.53 14.08 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0...

  14. Nevada Natural Gas Prices

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

    4.15 4.53 4.64 4.38 4.40 3.57 1989-2015 Residential Price 15.51 16.72 16.41 16.39 16.19 NA 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0...

  15. Maryland Natural Gas Prices

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

    50 7.38 8.78 7.19 4.07 4.26 1989-2015 Residential Price 18.35 18.44 19.08 19.39 13.51 12.72 1989-2015 Percentage of Total Residential Deliveries included in Prices 70.3 70.8 71.7...

  16. Michigan Natural Gas Prices

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

    3.92 3.82 3.82 3.60 3.65 3.81 1989-2015 Residential Price 12.50 13.65 13.52 13.21 8.93 7.84 1989-2015 Percentage of Total Residential Deliveries included in Prices 93.0 92.4 92.6...

  17. Massachusetts Natural Gas Prices

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

    25 7.30 7.15 7.59 4.62 4.42 1989-2015 Residential Price 12.15 13.26 13.78 13.23 NA 11.15 1989-2015 Percentage of Total Residential Deliveries included in Prices 99.3 99.3 99.3 99.2...

  18. Louisiana Natural Gas Prices

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

    22 3.48 3.28 3.08 2.95 2.62 1989-2015 Residential Price 14.71 15.18 16.20 15.57 14.79 13.57 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0...

  19. Maine Natural Gas Prices

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

    7.37 9.76 NA 5.52 4.38 7.52 1989-2015 Residential Price 17.15 20.79 22.87 21.79 NA 13.49 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0...

  20. Connecticut Natural Gas Prices

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

    67-2005 Citygate Price 6.81 6.58 5.92 5.12 5.42 5.61 1984-2014 Residential Price 14.81 14.93 13.83 14.17 13.32 14.13 1967-2014 Percentage of Total Residential Deliveries included...

  1. Delaware Natural Gas Prices

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

    78-2005 Citygate Price 6.54 5.67 9.03 7.19 5.67 5.54 1984-2014 Residential Price 17.79 15.12 15.38 15.24 13.65 13.21 1967-2014 Percentage of Total Residential Deliveries included...

  2. Hawaii Natural Gas Prices

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

    Citygate Price 17.82 22.94 31.58 32.39 28.45 26.94 1984-2014 Residential Price 36.37 44.50 55.28 52.86 49.13 47.51 1980-2014 Percentage of Total Residential Deliveries included in...

  3. Gasoline prices - January 7, 2013

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

    short version) The U.S. average retail price for regular gasoline showed little movement from last week. Prices remained flat at 3.30 a gallon on Monday, based on the weekly price...

  4. Diesel prices continue to increase

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

    Diesel prices continue to increase The U.S. average retail price for on-highway diesel fuel rose to 3.98 a gallon. That's up 2.6 cents from a week ago, based on the weekly price...

  5. Gasoline prices - January 7, 2013

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

    long version) The U.S. average retail price for regular gasoline showed little movement from last week. Prices remained flat at 3.30 a gallon on Monday, based on the weekly price...

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

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

    Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2015 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2015 Handbook describes the annual...

  7. 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.

    2012-06-01

    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.

  8. Physical Uncertainty Bounds (PUB)

    SciTech Connect (OSTI)

    Vaughan, Diane Elizabeth; Preston, Dean L.

    2015-03-19

    This paper introduces and motivates the need for a new methodology for determining upper bounds on the uncertainties in simulations of engineered systems due to limited fidelity in the composite continuum-level physics models needed to simulate the systems. We show that traditional uncertainty quantification methods provide, at best, a lower bound on this uncertainty. We propose to obtain bounds on the simulation uncertainties by first determining bounds on the physical quantities or processes relevant to system performance. By bounding these physics processes, as opposed to carrying out statistical analyses of the parameter sets of specific physics models or simply switching out the available physics models, one can obtain upper bounds on the uncertainties in simulated quantities of interest.

  9. California Gasoline Price Study, 2003

    Reports and Publications (EIA)

    2003-01-01

    This is the final report to Congressman Ose describing the factors driving California's spring 2003 gasoline price spike and the subsequent price increases in June and August.

  10. Accelerated Depletion: Assessing Its Impacts on Domestic Oil and Natural Gas Prices and Production

    Reports and Publications (EIA)

    2000-01-01

    Analysis of the potential impacts of accelerated depletion on domestic oil and natural gas prices and production.

  11. Washington Natural Gas Prices

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

    4.22 3.96 2.72 3.62 4.32 1989-2014 Exports Price 4.81 4.47 3.87 4.02 5.05 1998-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.29 5.55 4.48 4.89 5.82 4.42 1984-2015 Residential Price 12.24 12.30 11.87 11.37 10.59 10.61 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 10.49 10.40 9.82 9.21 9.03 9.14 1967-2015 Percentage of Total Commercial Deliveries included in Prices 87.8 88.4 87.4 86.8

  12. Image registration with uncertainty analysis

    DOE Patents [OSTI]

    Simonson, Katherine M. (Cedar Crest, NM)

    2011-03-22

    In an image registration method, edges are detected in a first image and a second image. A percentage of edge pixels in a subset of the second image that are also edges in the first image shifted by a translation is calculated. A best registration point is calculated based on a maximum percentage of edges matched. In a predefined search region, all registration points other than the best registration point are identified that are not significantly worse than the best registration point according to a predetermined statistical criterion.

  13. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    propane prices increase The average retail price for propane rose 3.2 cents from a week ago to $2.86 per gallon. That's up 59.3 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged 2.40 a gallon, up 3.2 cents from last week, and up 65.8 cents from a year ago. This is Marcela Rourk, with EIA, in Washington.

  14. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    propane prices increase The average retail price for propane rose 10.3 cents from a week ago to $2.96 per gallon. That's up 68.1 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. This is the largest single week increase since the heating season started in October. Propane prices in the Midwest region averaged 2.55 a gallon, up 14.9 cents from last week, and up 79.1 cents from a year ago. This is Marcela Rourk, with EIA, in

  15. Residential propane prices increase

    Gasoline and Diesel Fuel Update (EIA)

    propane prices increase The average retail price for propane rose 2.3 cents per gallon from last week to $2.57 per gallon; up 32.2 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. The retail price for propane in the Midwest region averaged 2.08 per gallon, up 2.4 cents per gallon from last week, and up 36.9 cents from a year earlier. This is Marlana Anderson, with EIA, in Washington.

  16. Residential propane prices surges

    Gasoline and Diesel Fuel Update (EIA)

    propane prices surges The average retail price for propane rose to an all-time high of $4.01 a gallon, that's up $1.05 from a week ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. This is the largest weekly increase since the survey began in 1990. Propane prices in the Midwest region averaged 4.20 a gallon, up $1.66 from last week, and up $2.43 from a

  17. Crude Oil Prices

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

    20.86 20.67 20.47 20.24 20.32 19.57 See footnotes at end of table. 21. Domestic Crude Oil First Purchase Prices Energy Information Administration Petroleum Marketing Annual...

  18. What Is Price Volatility

    Gasoline and Diesel Fuel Update (EIA)

    heating-degree-days than normal. Also relevant was that the prices of fuel oil and other alternative fuels were relatively high during this period. For example, the average...

  19. Residential propane price increases

    Gasoline and Diesel Fuel Update (EIA)

    Residential propane virtually unchanged The average retail price for propane is $2.02 per gallon, up 1-tenth of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.46 per gallon, up 1-tenth of a cent from last week, and down 38.8

  20. Competitive Electricity Prices: An Update

    Reports and Publications (EIA)

    1998-01-01

    Illustrates a third impact of the move to competitive generation pricing -- the narrowing of the range of prices across regions of the country. This feature article updates information in Electricity Prices in a Competitive Environment: Marginal Cost Pricing of Generation Services and Financial Status of Electric Utilities.

  1. Stephanie Price | Department of Energy

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

    Stephanie Price Stephanie Price Stephanie Price - Communicator, National Renewable Energy Laboratory Stephanie Price is a communicator at the National Renewable Energy Laboratory, which assists EERE in providing technical content for many of its websites. Most Recent Updating the Doors and Windows August 23 My Energy Audit, Part 2: Windows July 9 My Energy Audit, Part 1: Heating June 6

  2. Uncertainty with New Technology

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

    an application. By removing uncertainty and hesitation associated with new technology adoption, ES-Select plays a key role in helping to address grid issues by providing the first...

  3. Minnesota Natural Gas Prices

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

    4.68 4.52 4.49 3.51 4.06 3.65 1989-2015 Residential Price 13.30 13.01 12.75 9.33 7.71 7.16 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 8.17 8.03 7.72 6.43 6.20 6.10 1989-2015 Percentage of Total Commercial Deliveries included in Prices 71.0 74.7 74.2 82.7 82.4 89.0 1989-2015 Industrial Price 4.59 4.76 4.23 4.31 4.20 4.31 2001-2015 Percentage of Total Industrial Deliveries included in Prices 11.4 12.6 12.7

  4. Nebraska Natural Gas Prices

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

    4.11 4.16 4.68 4.04 3.83 3.23 1989-2015 Residential Price 14.88 15.79 15.70 13.92 9.51 6.88 1989-2015 Percentage of Total Residential Deliveries included in Prices 88.9 88.2 88.9 87.2 83.8 86.9 2002-2015 Commercial Price 6.03 6.25 6.43 5.91 5.67 5.34 1989-2015 Percentage of Total Commercial Deliveries included in Prices 47.5 44.6 43.4 52.4 48.8 58.3 1989-2015 Industrial Price 4.31 4.38 4.32 4.15 4.09 4.85 2001-2015 Percentage of Total Industrial Deliveries included in Prices 5.5 5.6 6.4 6.1 6.4

  5. California Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Citygate Price 3.56 3.55 3.42 3.32 3.08 3.02 1989-2015 Residential Price 11.68 11.85 11.91 11.53 10.31 11.37 1989-2015 Percentage of Total Residential Deliveries included in Prices 94.8 94.9 94.6 94.7 96.1 95.6 2002-2015 Commercial Price 7.68 7.87 7.84 7.69 7.20 8.23 1989-2015 Percentage of Total Commercial Deliveries included in Prices 45.0 43.5 43.9 46.6 51.7 54.8 1989-2015 Industrial Price 6.02 6.07 6.09 5.88 5.77 6.92 2001-2015

  6. Colorado Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    5.36 5.61 5.62 4.60 3.24 3.07 1989-2015 Residential Price 14.21 13.61 13.03 9.26 6.88 6.45 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 9.41 9.33 9.19 7.83 6.49 6.18 1989-2015 Percentage of Total Commercial Deliveries included in Prices 90.9 91.0 90.8 93.1 95.7 95.8 1989-2015 Industrial Price 7.28 6.53 6.11 5.95 5.14 4.46 2001-2015 Percentage of Total Industrial Deliveries included in Prices 3.5 4.4 5.8 6.6

  7. Florida Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    87 4.44 4.53 4.17 3.92 4.65 1989-2015 Residential Price 24.58 24.59 24.41 23.37 21.56 19.15 1989-2015 Percentage of Total Residential Deliveries included in Prices 97.8 97.7 97.9 97.7 97.6 97.6 2002-2015 Commercial Price 10.92 10.91 11.15 10.61 10.69 10.89 1989-2015 Percentage of Total Commercial Deliveries included in Prices 28.0 26.9 27.7 27.8 27.6 28.6 1989-2015 Industrial Price 6.69 6.02 6.08 6.29 6.20 NA 2001-2015 Percentage of Total Industrial Deliveries included in Prices 3.3 3.3 3.5 3.0

  8. Kentucky Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Citygate Price 3.44 3.41 3.34 3.41 3.21 3.85 1989-2015 Residential Price 23.26 22.36 21.14 16.21 11.07 9.41 1989-2015 Percentage of Total Residential Deliveries included in Prices 96.9 97.6 97.2 97.6 97.4 96.7 2002-2015 Commercial Price 11.98 11.34 10.55 9.42 8.63 7.72 1989-2015 Percentage of Total Commercial Deliveries included in Prices 66.4 67.6 68.0 72.3 76.0 80.6 1989-2015 Industrial Price 4.24 4.05 3.86 3.78 3.44 3.58 2001-2015

  9. Alaska Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Citygate Price 5.60 5.80 5.90 6.11 6.56 6.53 1989-2015 Residential Price 11.78 11.50 9.86 9.44 8.89 8.79 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 7.74 7.89 7.03 7.67 7.43 7.39 1989-2015 Percentage of Total Commercial Deliveries included in Prices 96.6 97.2 98.3 98.7 99.9 99.7 1989-2015 Industrial Price 7.17 7.17 7.17 7.17 7.17 7.24 2001-2015

  10. Arkansas Natural Gas Prices

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Citygate Price 6.97 6.92 5.58 5.63 4.16 4.00 1989-2015 Residential Price 17.53 19.19 18.15 17.40 13.80 10.34 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 8.09 8.19 8.00 7.71 7.86 7.29 1989-2015 Percentage of Total Commercial Deliveries included in Prices 28.0 25.0 25.7 28.1 28.2 41.8 1989-2015 Industrial Price 6.71 6.62 6.47 6.46 6.02 5.67 2001-2015

  11. Texas Natural Gas Prices

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

    3.94 3.86 3.73 4.17 3.90 4.38 1989-2015 Residential Price 18.32 21.15 20.97 19.25 15.54 9.34 1989-2015 Percentage of Total Residential Deliveries included in Prices 99.7 99.7 100.0 100.0 99.6 99.8 2002-2015 Commercial Price 7.50 7.63 7.71 7.66 7.24 6.52 1989-2015 Percentage of Total Commercial Deliveries included in Prices 65.9 63.0 62.6 64.3 66.1 76.4 1989-2015 Industrial Price 3.08 3.14 2.96 2.78 2.29 2.39 2001-2015 Percentage of Total Industrial Deliveries included in Prices 41.5 39.5 41.3

  12. Pennsylvania Natural Gas Prices

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

    5.83 6.67 6.64 NA 4.31 4.15 1989-2015 Residential Price 17.83 18.62 18.32 NA 10.56 9.85 1989-2015 Percentage of Total Residential Deliveries included in Prices 87.1 87.4 87.3 NA 87.7 86.8 2002-2015 Commercial Price 12.09 11.21 11.10 NA 8.27 8.13 1989-2015 Percentage of Total Commercial Deliveries included in Prices 28.5 28.5 29.5 NA 37.3 38.5 1989-2015 Industrial Price 10.81 11.12 10.34 9.59 9.10 8.18 2001-2015 Percentage of Total Industrial Deliveries included in Prices 0.2 0.2 0.2 0.4 0.7 1.0

  13. Wyoming Natural Gas Prices

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

    3.06 3.50 3.89 4.09 3.88 3.89 1989-2015 Residential Price 15.33 15.71 15.37 13.00 8.57 7.11 1989-2015 Percentage of Total Residential Deliveries included in Prices 75.2 76.0 75.3 76.5 75.4 75.7 2002-2015 Commercial Price 7.74 7.55 7.80 7.36 6.65 6.19 1989-2015 Percentage of Total Commercial Deliveries included in Prices 55.0 58.0 51.1 54.8 46.0 53.2 1989-2015 Industrial Price 4.72 4.85 4.85 4.93 5.06 NA 2001-2015 Percentage of Total Industrial Deliveries included in Prices 2.2 2.9 2.1 1.9 1.4 NA

  14. Utah Natural Gas Prices

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

    4.34 3.96 4.18 5.49 4.84 5.96 1989-2015 Residential Price 10.69 10.85 10.89 10.85 9.22 8.75 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 7.26 7.30 7.29 7.33 7.33 7.53 1989-2015 Percentage of Total Commercial Deliveries included in Prices 66.9 65.1 66.7 67.0 76.1 80.7 1989-2015 Industrial Price 5.17 5.29 5.27 5.21 5.31 5.98 2001-2015 Percentage of Total Industrial Deliveries included in Prices 10.9 8.0 7.6

  15. Virginia Natural Gas Prices

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

    7.00 7.36 5.78 4.75 4.07 4.36 1989-2015 Residential Price 20.25 21.10 19.45 NA 11.72 12.09 1989-2015 Percentage of Total Residential Deliveries included in Prices 87.6 87.8 88.8 NA 90.7 89.5 2002-2015 Commercial Price 8.55 8.58 8.91 8.02 7.57 7.93 1989-2015 Percentage of Total Commercial Deliveries included in Prices 47.0 44.3 40.0 48.0 50.4 53.2 1989-2015 Industrial Price 4.81 5.41 4.86 4.22 3.95 4.49 2001-2015 Percentage of Total Industrial Deliveries included in Prices 7.3 7.7 9.0 10.0 7.5

  16. Washington Natural Gas Prices

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

    29 5.84 5.08 4.25 3.51 3.46 1989-2015 Residential Price 12.37 12.57 11.71 11.24 9.71 9.15 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 9.80 10.04 9.42 9.32 8.35 7.80 1989-2015 Percentage of Total Commercial Deliveries included in Prices 79.6 84.3 80.7 83.1 86.0 87.2 1989-2015 Industrial Price 9.45 8.94 8.87 8.48 7.87 7.27 2001-2015 Percentage of Total Industrial Deliveries included in Prices 4.5 4.1 5.0 5.5

  17. Prices & Trends | Department of Energy

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

    Economy » Prices & Trends Prices & Trends Daily wholesale and retail prices for various energy products, including spot prices and select futures prices at national or regional levels. Prices are updated each weekday (excluding federal holidays), typically between 7:30 and 8:30 a.m | Photo courtesy EIA Daily wholesale and retail prices for various energy products, including spot prices and select futures prices at national or regional levels. Prices are updated each weekday (excluding

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

    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.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

    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.

  20. The Alternative Fuel Price Report

    Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

    December 17, 2001 his is the fifth issue of the Clean Cities Alternative Fuel Price Report, a quarterly newsletter keeping you up to date on the price of alternative fuels in the U.S. and their relation to gasoline and diesel prices. This issue discusses prices that were gathered from Clean Cities coordinators and stakeholders during the weeks of October 15 and October 22, 2001, with comparisons to the prices in the previous Price Report for the week of June 4, 2001. Gasoline and Diesel Prices

  1. Natural Gas Electric Power Price

    Gasoline and Diesel Fuel Update (EIA)

    Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground

  2. Decision Analysis for EGS

    Broader source: Energy.gov [DOE]

    Project objectives: DEVELOPMENT OF ANALYSIS TOOLS TO ASSESS: Uncertainties associated with exploration for EGS; Uncertainties associated with development of EGS; Uncertainties associated with operation of EGS.

  3. An uncertainty analysis of the hydrogen source term for a station blackout accident in Sequoyah using MELCOR 1.8.5

    SciTech Connect (OSTI)

    Gauntt, Randall O.; Bixler, Nathan E.; Wagner, Kenneth Charles

    2014-03-01

    A methodology for using the MELCOR code with the Latin Hypercube Sampling method was developed to estimate uncertainty in various predicted quantities such as hydrogen generation or release of fission products under severe accident conditions. In this case, the emphasis was on estimating the range of hydrogen sources in station blackout conditions in the Sequoyah Ice Condenser plant, taking into account uncertainties in the modeled physics known to affect hydrogen generation. The method uses user-specified likelihood distributions for uncertain model parameters, which may include uncertainties of a stochastic nature, to produce a collection of code calculations, or realizations, characterizing the range of possible outcomes. Forty MELCOR code realizations of Sequoyah were conducted that included 10 uncertain parameters, producing a range of in-vessel hydrogen quantities. The range of total hydrogen produced was approximately 583kg 131kg. Sensitivity analyses revealed expected trends with respected to the parameters of greatest importance, however, considerable scatter in results when plotted against any of the uncertain parameters was observed, with no parameter manifesting dominant effects on hydrogen generation. It is concluded that, with respect to the physics parameters investigated, in order to further reduce predicted hydrogen uncertainty, it would be necessary to reduce all physics parameter uncertainties similarly, bearing in mind that some parameters are inherently uncertain within a range. It is suspected that some residual uncertainty associated with modeling complex, coupled and synergistic phenomena, is an inherent aspect of complex systems and cannot be reduced to point value estimates. The probabilistic analyses such as the one demonstrated in this work are important to properly characterize response of complex systems such as severe accident progression in nuclear power plants.

  4. An Efficient Surrogate Modeling Approach in Bayesian Uncertainty...

    Office of Scientific and Technical Information (OSTI)

    Conference: An Efficient Surrogate Modeling Approach in Bayesian Uncertainty Analysis Citation Details In-Document Search Title: An Efficient Surrogate Modeling Approach in...

  5. Measurement uncertainty relations

    SciTech Connect (OSTI)

    Busch, Paul; Lahti, Pekka; Werner, Reinhard F.

    2014-04-15

    Measurement uncertainty relations are quantitative bounds on the errors in an approximate joint measurement of two observables. They can be seen as a generalization of the error/disturbance tradeoff first discussed heuristically by Heisenberg. Here we prove such relations for the case of two canonically conjugate observables like position and momentum, and establish a close connection with the more familiar preparation uncertainty relations constraining the sharpness of the distributions of the two observables in the same state. Both sets of relations are generalized to means of order ? rather than the usual quadratic means, and we show that the optimal constants are the same for preparation and for measurement uncertainty. The constants are determined numerically and compared with some bounds in the literature. In both cases, the near-saturation of the inequalities entails that the state (resp. observable) is uniformly close to a minimizing one.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

    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.

  7. The carbon component of the UK power price

    SciTech Connect (OSTI)

    Kris Voorspools

    2006-08-01

    CO{sub 2} emissions trading is in full swing in Europe and is already having an impact on the price of power in the UK. If EU allowances (EUAs) trade at euro 20/t-CO{sub 2}, the EUA component in the power price is estimated to be slightly < euro 10/MW.h. In the case of UK power for delivery 1 year ahead, this is {approximately} 10% of the market price of power. The introduction of a carbon components into the UK power prices took place along before the 'official' start of ETS in 2005. Analysis of historical data of the price of power, gas, coal and EUAs shows that the first trace of a CO{sub 2} component in UK power dates back to August 2003, shortly after EUAs first started to trade. In April 2004, CO{sub 2} was fully integrated into the UK power price. 4 refs., 5 figs.

  8. Numerical uncertainty in computational engineering and physics

    SciTech Connect (OSTI)

    Hemez, Francois M

    2009-01-01

    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.

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

    SciTech Connect (OSTI)

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

    2008-01-07

    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.

  10. Fairness and dynamic pricing: comments

    SciTech Connect (OSTI)

    Hogan, William W.

    2010-07-15

    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)

  11. Residential propane prices surges

    Gasoline and Diesel Fuel Update (EIA)

    Midwest and Northeast propane prices much higher this winter than last year Households that heat with propane will pay for that propane at prices averaging 39 percent higher in the Midwest and 14 percent higher in the Northeast this winter compared with last winter.....as much colder temperatures this winter boosts heating fuel demand. Midwest residential propane is expected to average $2.41 per gallon over the winter, while propane in the Northeast will average $3.43 per gallon, according to

  12. Price Liquefied Freeport, TX Natural Gas Exports Price to Japan...

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

    Japan (Dollars per Thousand Cubic Feet) Price Liquefied Freeport, TX Natural Gas Exports Price to Japan (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

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

    SciTech Connect (OSTI)

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

    2005-02-09

    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.

  14. Natural Gas Wellhead Price

    Gasoline and Diesel Fuel Update (EIA)

    Wellhead Price Marketed Production Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History U.S. NA NA NA NA NA NA 1973-2015

  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.

    2000-03-01

    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. New Hampshire Natural Gas Prices

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

    Imports Price 5.48 5.45 4.08 6.63 10.55 1999-2014 Exports Price -- 7.54 2.62 6.65 4.06 2007-2014 Pipeline and Distribution Use Price 1980-2005 Citygate Price 8.83 8.07 7.15 7.60 9.28 NA 1984-2015 Residential Price 14.46 14.67 13.74 13.84 16.27 NA 1980-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 12.72 11.46 11.95 12.13 14.96 13.63 1977-2015 Percentage of Total Commercial Deliveries included in Prices 57.3 55.6

  17. New York Natural Gas Prices

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

    5 1967-2010 Imports Price 5.43 4.96 3.83 5.59 8.60 1989-2014 Exports Price -- 4.69 3.61 4.29 5.56 1999-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.86 6.04 5.35 5.02 5.47 4.14 1984-2015 Residential Price 14.04 13.71 12.97 12.49 12.54 11.20 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 10.88 9.32 7.84 8.00 8.31 6.89 1967-2015 Percentage of Total Commercial Deliveries included in Prices

  18. North Dakota Natural Gas Prices

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

    2 1967-2010 Imports Price 4.41 4.04 2.72 3.59 5.00 1994-2014 Exports Price -- -- -- -- 14.71 1999-2014 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.50 5.06 4.43 4.99 6.37 NA 1984-2015 Residential Price 8.08 8.10 7.43 7.43 8.86 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 7.03 7.00 6.04 6.32 7.74 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices 92.6 92.8 91.9

  19. Residential heating oil price increases

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

    heating oil price increases The average retail price for home heating oil rose 11.2 cents from a week ago to 2.91 per gallon. That's down 1.33 from a year ago, based on the...

  20. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 3.92 a gallon on Monday. That's down 7-tenths of a penny from a week ago, based...

  1. Gasoline prices decrease (short version)

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

    Gasoline prices decrease (short version) The U.S. average retail price for regular gasoline fell to 3.67 a gallon on Monday. That's down 3-tenths of a penny from a week ago, based...

  2. Diesel prices continue to increase

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

    Diesel prices continue to increase The U.S. average retail price for on-highway diesel fuel rose to 3.88 a gallon on Monday. That's up 3.9 cents from a week ago, based on the...

  3. Residential heating oil price decreases

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

    heating oil price increases The average retail price for home heating oil rose 1.8 cents from a week ago to 2.08 per gallon. That's down 72 cents from a year ago, based on the...

  4. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 4.01 a gallon on Monday. That's down 4.1 cents from a week ago, based on the...

  5. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 10.5 cents from a week ago to 2.93 per gallon, based on the residential heating fuel survey by the...

  6. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 3 cents from a week ago to 2.33 per gallon. That's down 89 cents from a year ago, based on the...

  7. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 1.8 cents from a week ago to 2.82 per gallon. That's down 1.36 from a year ago, based on the...

  8. Diesel prices continue to increase

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

    Diesel prices continue to increase The U.S. average retail price for on-highway diesel fuel rose to 3.87 a gallon on Monday. That's up 3.9 cents from a week ago, based on the...

  9. Diesel prices continue to increase

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

    Diesel prices continue to increase The U.S. average retail price for on-highway diesel fuel rose to 3.92 a gallon on Monday. That's up 1.2 cents from a week ago, based on the...

  10. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 1.5 cents from a week ago to 2.36 per gallon. That's down 97 cents from a year ago, based on the...

  11. Residential heating oil prices increase

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

    heating oil prices increase The average retail price for home heating oil rose 12 cents from a week ago to 4.18 per gallon. That's up 13 cents from a year ago, based on the...

  12. Gasoline prices decrease (short version)

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

    short version) The U.S. average retail price for regular gasoline fell to 3.63 a gallon on Monday. That's down 2.9 cents from a week ago, based on the weekly price survey by the...

  13. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 3.83 a gallon on Monday. That's down 2 cents from a week ago, based on the...

  14. Residential heating oil price increases

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

    5, 2015 Residential heating oil price increases The average retail price for home heating oil rose 14.7 cents from a week ago to 3.19 per gallon. That's down 1.06 from a year...

  15. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 17.7 cents from a week ago to 3.03 per gallon. That's down 1.09 from a year ago, based on the...

  16. Residential heating oil prices increase

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

    5, 2014 Residential heating oil prices increase The average retail price for home heating oil rose 6.5 cents from a week ago to 4.24 per gallon. That's up 14.9 cents from a year...

  17. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 4.5 cents from a week ago to 2.21 per gallon. That's down 87 cents from a year ago, based on the...

  18. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 2.3 cents from a week ago to 2.38 per gallon. That's down 99 cents from a year ago, based on the...

  19. Gasoline prices decrease (short version)

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

    Gasoline prices decrease (short version) The U.S. average retail price for regular gasoline fell to 3.68 a gallon on Monday. That's down 2.9 cents from a week ago, based on the...

  20. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 3.82 a gallon on Monday. That's down a penny from a week ago, based on the...

  1. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 3.89 a gallon on Monday. That's down 1.1 cents from a week ago based on the...

  2. Residential heating oil prices decline

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

    heating oil price decreases The average retail price for home heating oil fell 2 cents from a week ago to 3.36 per gallon. That's down 52.5 cents from a year ago, based on the...

  3. Residential heating oil prices increase

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

    heating oil prices increase The average retail price for home heating oil rose 2.9 cents from a week ago to 3.98 per gallon. That's up 6-tenths of a penny from a year ago, based...

  4. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 3.94 a gallon on Monday. That's down 3 12 cents from a week ago, based on the...

  5. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 1.9 cents from a week ago to 2.16 per gallon. That's down 75 cents from a year ago, based on the...

  6. Residential heating oil price increases

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

    9, 2015 Residential heating oil price increases The average retail price for home heating oil rose 11.7 cents from a week ago to 3.03 per gallon. That's down 1.20 from a year...

  7. Residential heating oil price decreases

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

    heating oil price increases The average retail price for home heating oil rose 6-tenths of a cent from a week ago to 2.18 per gallon. That's down 79 cents from a year ago, based...

  8. Diesel prices see slight drop

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

    Diesel prices see slight drop The U.S. average retail price for on-highway diesel fuel fell slightly to 3.91 a gallon on Monday. That's down 6-tenths of a penny from a week ago,...

  9. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 3.90 a gallon on Monday. That's down 1.3 cents from a week ago, based on the...

  10. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 3.98 a gallon on Monday. That's down 1.6 cents from a week ago, based on the...

  11. Diesel prices continue to increase

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

    Diesel prices continue to increase The U.S. average retail price for on-highway diesel fuel rose to 3.98 a gallon on Labor Day Monday. That's up 6.8 cents from a week ago, based...

  12. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 5.1 cents from a week ago to 2.11 per gallon. That's down 72 cents from a year ago, based on the...

  13. Residential heating oil prices available

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

    heating oil prices available The average retail price for home heating oil is 3.52 per gallon. That's down 32.7 cents from a year ago, based on the U.S. Energy Information...

  14. Residential heating oil prices available

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

    heating oil prices available The average retail price for home heating oil is 2.41 per gallon, based on the residential heating fuel survey by the U.S. Energy Information...

  15. Diesel prices slightly decrease nationally

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

    Diesel prices slightly decrease nationally The U.S. average retail price for on-highway diesel fuel fell to 3.97 a gallon on Monday. That's down 7-tenths of a penny from a week...

  16. Gasoline prices increase (short version)

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

    gasoline prices increase (short version) The U.S. average retail price for regular gasoline rose to 3.69 a gallon on Monday. That's up 1.2 cents from a week ago, based on the...

  17. Residential heating oil price decreases

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

    7, 2014 Residential heating oil price decreases The average retail price for home heating oil fell 7.8 cents from a week ago to 3.14 per gallon. That's down 81.1 cents from a year...

  18. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 5 cents from a week ago to 2.06 per gallon. That's down 75 cents from a year ago, based on the...

  19. Residential heating oil price decreases

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

    6, 2014 Residential heating oil price decreases The average retail price for home heating oil rose 1.6 cents from a week ago to 4.24 per gallon. That's up 8.9 cents from a year...

  20. Residential heating oil prices increase

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

    heating oil prices increase The average retail price for home heating oil rose 5.4 cents from a week ago to 4.04 per gallon. That's up 4.9 cents from a year ago, based on the...

  1. Gasoline prices decrease (long version)

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

    long version) The U.S. average retail price for regular gasoline fell to 3.65 a gallon on Monday. That's down 2.8 cents from a week ago, based on the weekly price survey by the...

  2. Residential heating oil prices increase

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

    3, 2014 Residential heating oil prices increase The average retail price for home heating oil rose 4.4 cents from a week ago to 4.06 per gallon. That's up 4.1 cents from a year...

  3. Residential heating oil prices decrease

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

    heating oil prices decrease The average retail price for home heating oil fell 1.7 cents from a week ago to 4.02 per gallon. That's up 1.7 cents from a year ago, based on the...

  4. Diesel prices continue to increase

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

    Diesel prices continue to increase The U.S. average retail price for on-highway diesel fuel rose to 3.90 a gallon on Monday. That's up 3.6 cents from a week ago, based on the...

  5. Diesel prices continue to increase

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

    Diesel prices continue to increase The U.S. average retail price for on-highway diesel fuel rose to 3.89 a gallon on Monday. That's up 2.4 cents from a week ago, based on the...

  6. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 7.6 cents from a week ago to 2.26 per gallon. That's down 89 cents from a year ago, based on the...

  7. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 10.5 cents from a week ago to 3.22 per gallon. That's down 73.6 cents from a year ago, based on the...

  8. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 3.89 a gallon on Monday. That's down 5 12 cents from a week ago, based on the...

  9. Gasoline prices decrease (Short version)

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

    Short version) The U.S. average retail price for regular gasoline fell to 3.65 a gallon on Monday. That's down 2.8 cents from a week ago, based on the weekly price survey by the...

  10. Residential heating oil prices decrease

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

    9, 2014 Residential heating oil price decreases The average retail price for home heating oil fell 2.9 cents from a week ago to 3.45 per gallon. That's down 36.6 cents from a year...

  11. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 8 cents from a week ago to 3.21 per gallon. That's down 98.7 cents from a year ago, based on the...

  12. Residential heating oil price decreases

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

    4 Residential heating oil price decreases The average retail price for home heating oil fell 1.6 cents from a week ago to 3.42 per gallon. That's down 39.5 cents from a year ago,...

  13. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 3.8 cents from a week ago to 3.33 per gallon. That's down 59.1 cents from a year ago, based on the...

  14. Residential heating oil prices decline

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

    9, 2014 Residential heating oil price decreases The average retail price for home heating oil fell 3.3 cents from a week ago to 3.38 per gallon. That's down 43.9 cents from a year...

  15. Gasoline prices decrease (long version)

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

    long version) The U.S. average retail price for regular gasoline fell to 3.63 a gallon on Monday. That's down 2.9 cents from a week ago, based on the weekly price survey by the...

  16. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 3.5 cents from a week ago to 2.18 per gallon. That's down 87 cents from a year ago, based on the...

  17. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 3.86 a gallon on Monday. That's down 1.3 cents from a week ago, based on the...

  18. Diesel prices slightly increase nationally

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

    Diesel prices slightly increase nationally The U.S. average retail price for on-highway diesel fuel rose slightly to 3.90 a gallon on Monday. That's up 4-tenths of a penny from a...

  19. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 3.87 a gallon on Monday. That's down 8-tenths of a penny from a week ago, based...

  20. Gasoline prices decrease (long version)

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

    Gasoline prices decrease (long version) The U.S. average retail price for regular gasoline fell to 3.70 a gallon on Monday. That's down 1.4 cents from a week ago, based on the...

  1. Gasoline prices decrease (long version)

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

    5, 2014 Gasoline prices decrease (long version) The U.S. average retail price for regular gasoline fell to 3.68 a gallon on Monday. That's down 2.9 cents from a week ago, based on...

  2. Residential heating oil prices decrease

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

    5, 2014 Residential heating oil prices decrease The average retail price for home heating oil fell 1.8 cents from a week ago to 4.00 per gallon. That's down 2-tenths of a cent...

  3. Diesel prices remain fairly stable

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

    Diesel prices remain fairly stable The U.S. average retail price for on-highway diesel fuel slightly fell to 3.85 a gallon on Monday. That's down 6-tenths of a penny from a week...

  4. Residential heating oil prices decline

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

    heating oil price decreases The average retail price for home heating oil fell 6.3 cents from a week ago to 3.08 per gallon. That's down 90.3 cents from a year ago, based on the...

  5. Residential heating oil price decreases

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

    5, 2014 Residential heating oil price decreases The average retail price for home heating oil fell 1.9 cents from a week ago to 3.43 per gallon. That's down 39 cents from a year...

  6. Diesel prices continue to increase

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

    Diesel prices continue to increase The U.S. average retail price for on-highway diesel fuel rose to 3.91 a gallon on Monday. That's up 7-tenths of a penny from a week ago, based...

  7. Residential heating oil price decreases

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

    heating oil price decreases The average retail price for home heating oil fell 1.9 cents from a week ago to 2.80 per gallon. That's down 1.44 from a year ago, based on the...

  8. Residential heating oil price increases

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

    heating oil price increases The average retail price for home heating oil rose 10.3 cents from a week ago to 3.29 per gallon. That's down 93.7 cents from a year ago, based on the...

  9. Diesel prices continue to decrease

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

    Diesel prices continue to decrease The U.S. average retail price for on-highway diesel fuel fell to 3.92 a gallon on Monday. That's down 3 cents from a week ago based on the...

  10. Residential heating oil prices decline

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

    2, 2014 Residential heating oil prices decline The average retail price for home heating oil is 3.48 per gallon. That's down 4.5 cents from a week ago, based on the residential...

  11. Residential propane price decreases slightly

    Gasoline and Diesel Fuel Update (EIA)

    propane price decreases slightly The average retail price for propane is $2.38 per gallon, down 3-tenths of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.93 per gallon, down one cent from last week, and down 35.5

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28

    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.

  13. Ethanol's Effect on Grain Supply and Prices

    SciTech Connect (OSTI)

    2008-01-01

    This document provides graphical information about ethanol's effect on grain supply and prices, uses of corn, and grain price trends.

  14. Alternative Fuel Price Report - June 29, 2004

    Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

    ALTERNATIVE FUEL PRICE REPORT Alternative Fuel Prices Across the Nation June 29, 2004 his is the twelfth issue of the Clean Cities Alternative Fuel Price Report, a quarterly newsletter keeping you up to date on the prices of alternative fuels in the U.S. and their relation to gasoline and diesel prices. This issue discusses prices that were gathered from Clean Cities coordinators and stakeholders between June 14 and June 25, 2004, with comparisons to the prices in the previous Price Report,

  15. Photovoltaic System Modeling. Uncertainty and Sensitivity Analyses

    SciTech Connect (OSTI)

    Hansen, Clifford W.; Martin, Curtis E.

    2015-08-01

    We report an uncertainty and sensitivity analysis for modeling AC energy from ph otovoltaic systems . Output from a PV system is predicted by a sequence of models. We quantify u ncertainty i n the output of each model using empirical distribution s of each model's residuals. We propagate uncertainty through the sequence of models by sampli ng these distributions to obtain a n empirical distribution of a PV system's output. We consider models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane - of - array irradiance; (2) estimate effective irradiance; (3) predict cell temperature; (4) estimate DC voltage, current and power ; (5) reduce DC power for losses due to inefficient maximum power point tracking or mismatch among modules; and (6) convert DC to AC power . O ur analysis consider s a notional PV system com prising an array of FirstSolar FS - 387 modules and a 250 kW AC inverter ; we use measured irradiance and weather at Albuquerque, NM. We found the uncertainty in PV syste m output to be relatively small, on the order of 1% for daily energy. We found that unce rtainty in the models for POA irradiance and effective irradiance to be the dominant contributors to uncertainty in predicted daily energy. Our analysis indicates that efforts to reduce the uncertainty in PV system output predictions may yield the greatest improvements by focusing on the POA and effective irradiance models.

  16. Diesel prices continue to increase

    Gasoline and Diesel Fuel Update (EIA)

    Diesel prices continue to increase The U.S. retail price for on-highway diesel fuel rose to its highest average since September at $3.95 a gallon. That's up 4.7 cents from a week ago, based on the weekly price survey by the U.S. Energy Information Administration. Diesel prices were highest in the New England region at 4.31 a gallon, up 13.4 cents from a week ago and marking the highest average this region has seen since last February. Prices were lowest in the Gulf Coast states at 3.78 a gallon,

  17. 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)

    2012-07-01

    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)

  18. New Jersey Natural Gas Prices

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

    Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.41 7.53 6.74 6.21 6.21 NA 1984-2015 Residential Price 12.84 11.78 11.09 10.89 9.69 8.37 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 94.6 92.8 90.1 90.7 93.4 1989-2015 Commercial Price 10.11 9.51 8.50 9.55 10.08 8.52 1967-2015 Percentage of Total Commercial Deliveries included in Prices 36.1 32.6 30.8 35.2 32.0 NA 1990-2015 Industrial Price 9.63 9.23 7.87 8.19 10.45 NA 1997-2015 Percentage of Total

  19. New Mexico Natural Gas Prices

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

    5.32 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 4.84 4.52 3.70 4.08 4.99 NA 1984-2015 Residential Price 9.63 9.14 8.69 8.92 10.13 8.58 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 7.47 6.98 6.31 6.77 7.87 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices 60.7 59.8 57.0 57.0 54.4 NA 1990-2015 Industrial Price 6.17 6.22 4.96 5.58 6.45 4.95 1997-2015

  20. North Carolina Natural Gas Prices

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

    Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.02 5.45 4.00 4.63 5.41 NA 1984-2015 Residential Price 12.50 12.55 12.19 11.83 11.88 NA 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 NA 1989-2015 Commercial Price 10.18 9.64 8.62 8.81 9.12 NA 1967-2015 Percentage of Total Commercial Deliveries included in Prices 84.8 84.4 83.5 84.5 84.9 NA 1990-2015 Industrial Price 8.24 7.70 6.37 6.87 7.55 NA 1997-2015 Percentage of Total

  1. South Dakota Natural Gas Prices

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

    NA 1979-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 5.54 5.21 4.67 4.83 6.14 4.17 1984-2015 Residential Price 8.77 8.59 8.39 8.23 9.27 8.21 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 7.13 6.98 6.45 6.59 7.65 6.11 1967-2015 Percentage of Total Commercial Deliveries included in Prices 80.9 81.7 81.6 81.6 81.6 81.0 1990-2015 Industrial Price 5.92 6.25 5.37 5.67 6.88 4.98 1997-2015

  2. West Virginia Natural Gas Prices

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

    NA 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.31 5.91 4.99 4.65 5.07 4.00 1984-2015 Residential Price 11.39 10.91 10.77 9.98 10.21 10.46 1967-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Commercial Price 10.27 9.65 9.35 8.61 8.92 9.15 1967-2015 Percentage of Total Commercial Deliveries included in Prices 51.0 49.2 48.9 52.9 56.7 53.3 1990-2015 Industrial Price 5.40 4.89 3.60 4.30 5.00 NA 1997-2015

  3. Entropic uncertainty relations and entanglement

    SciTech Connect (OSTI)

    Guehne, Otfried; Lewenstein, Maciej

    2004-08-01

    We discuss the relationship between entropic uncertainty relations and entanglement. We present two methods for deriving separability criteria in terms of entropic uncertainty relations. In particular, we show how any entropic uncertainty relation on one part of the system results in a separability condition on the composite system. We investigate the resulting criteria using the Tsallis entropy for two and three qubits.

  4. Assessment of Summer 1997 motor gasoline price increase

    SciTech Connect (OSTI)

    1998-05-01

    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. Energy and Financial Markets Overview: Crude Oil Price Formation

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

    Richard Newell, Administrator May 5, 2011 Energy and Financial Markets Overview: Crude Oil Price Formation EIA's Energy and Financial Markets Initiative 2 Richard Newell, May 5, 2011 * Collection of critical energy information to improve market transparency - improved petroleum storage capacity data - other improvements to data quality and coverage * Analysis of energy and financial market dynamics to improve understanding of what drives energy prices - internal analysis and sponsorship of

  6. Alternative Fuel Price Report - November 26, 2004

    Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

    THE ALTERNATIVE FUEL PRICE REPORT Alternative Fuel Prices Across the Nation November 26, 2004 his is the thirteenth issue of the Clean Cities Alternative Fuel Price Report, a quarterly newsletter keeping you up to date on the prices of alternative fuels in the U.S. and their relation to gasoline and diesel prices. This issue discusses prices that were gathered from Clean Cities coordinators and stakeholders between November 8 and November 19, 2004, with comparisons to the prices in the previous

  7. New York Natural Gas Prices

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

    7.23 7.28 7.03 4.50 3.49 3.56 1989-2015 Residential Price 17.10 17.33 17.53 14.26 12.27 11.42 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 6.08 5.75 5.99 6.27 6.33 6.82 1989-2015 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2015 Industrial Price 5.95 5.41 5.91 5.66 6.10 6.36 2001-2015 Percentage of Total Industrial Deliveries included in Prices 5.0

  8. North Carolina Natural Gas Prices

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

    4.64 4.68 4.46 3.88 NA 3.10 1989-2015 Residential Price 21.31 NA 21.72 14.57 12.12 12.84 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 NA 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 9.38 NA 9.30 8.01 8.45 NA 1989-2015 Percentage of Total Commercial Deliveries included in Prices 73.6 NA 75.8 79.7 81.3 NA 1989-2015 Industrial Price 5.78 5.70 5.96 5.86 5.57 5.70 2001-2015 Percentage of Total Industrial Deliveries included in Prices 8.7 9.4 9.4 10.0 10.4 11.4

  9. North Dakota Natural Gas Prices

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

    3.56 4.32 5.00 4.58 4.16 3.94 1989-2015 Residential Price 21.07 NA NA 9.60 6.57 5.61 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 8.73 8.86 7.91 NA 5.68 5.23 1989-2015 Percentage of Total Commercial Deliveries included in Prices 85.7 82.9 87.0 NA 93.2 94.3 1989-2015 Industrial Price 3.12 2.96 2.81 2.76 2.58 2.88 2001-2015 Percentage of Total Industrial Deliveries included in Prices 23.9 34.8 41.6 44.0 44.9

  10. Rhode Island Natural Gas Prices

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

    2.52 2.41 2.31 2.24 2.22 2.22 1989-2015 Residential Price 19.72 20.92 20.98 19.02 15.46 13.47 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 16.62 17.00 17.11 15.74 12.87 10.96 1989-2015 Percentage of Total Commercial Deliveries included in Prices 51.5 52.8 53.1 53.9 48.6 54.1 1989-2015 Industrial Price 9.61 10.09 9.79 9.92 9.48 8.22 2001-2015 Percentage of Total Industrial Deliveries included in Prices 4.8

  11. South Carolina Natural Gas Prices

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

    3.97 3.96 4.01 3.56 3.20 3.48 1989-2015 Residential Price 24.86 22.97 24.15 16.51 NA NA 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 8.33 8.04 8.28 7.97 8.35 10.06 1989-2015 Percentage of Total Commercial Deliveries included in Prices 90.1 90.2 88.8 89.7 91.3 NA 1989-2015 Industrial Price 4.22 4.46 4.13 4.03 3.86 4.01 2001-2015 Percentage of Total Industrial Deliveries included in Prices 42.2 41.8 43.2 43.6

  12. West Virginia Natural Gas Prices

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

    37 4.72 4.77 3.60 3.57 3.63 1989-2015 Residential Price 19.80 19.04 17.53 12.20 9.60 8.84 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 2002-2015 Commercial Price 11.49 11.90 11.49 9.96 7.94 7.64 1989-2015 Percentage of Total Commercial Deliveries included in Prices 28.1 32.7 27.5 45.9 49.4 56.0 1989-2015 Industrial Price 4.38 4.39 4.34 4.37 NA 3.51 2001-2015 Percentage of Total Industrial Deliveries included in Prices 11.5 12.1 12.8

  13. Natural Gas Wellhead Price

    Gasoline and Diesel Fuel Update (EIA)

    Quantity of Production Imputed Wellhead Value Wellhead Price Marketed Production Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010 2011 2012 2013 2014 2015 View History U.S. 4.48 3.95 2.66 NA NA NA 1922-2015 Alabama 4.46 1967-2010 Alaska 3.17 1967-2010 Arizona 4.11 1967-2010 Arkansas 3.84 1967-2010 California 4.87 1967-2010 Colorado 3.96 1967-2010 Florida NA 1967-2010

  14. Solar Pricing Trends

    Energy Savers [EERE]

    SB 2 1X Category % of Retail Sales From Eligible Renewable Resources Date by Which Compliance Must Occur Category or Compliance Period 1 20% Dec. 31, 2013 Category or Compliance Period 2 25% Dec. 31, 2016 Category or Compliance Period 3 33% Dec. 31, 2020 2 Solar Pricing Trends 3 U.S. Grid-Connected PV Capacity Additions 4 U.S. Renewable Additions wind, 7537 MW biogas, 91 MW biomass, 330 MW geothermal, 910 MW ocean, 0 MW small hydro, 38 MW solar thermal, 3804 MW solar photovoltaic, 5778 MW CA

  15. Residential heating oil price decreases

    Gasoline and Diesel Fuel Update (EIA)

    heating oil price increases The average retail price for home heating oil rose 1 cent from a week ago to $2.09 per gallon. That's down 82 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Heating oil prices in the New England region are at $2.02 per gallon, up 8-tenths of a cent from last week, and down 85

  16. Residential heating oil price decreases

    Gasoline and Diesel Fuel Update (EIA)

    Residential heating oil price increases The average retail price for home heating oil rose 1.1 cents from a week ago to $2.10 per gallon. That's down 94 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Heating oil prices in the New England region are at $2.04 per gallon, up 2.3 cents from last week, and down 95

  17. Residential heating oil price decreases

    Gasoline and Diesel Fuel Update (EIA)

    Residential heating oil price decreases The average retail price for home heating oil fell 9-tenths of a cent from a week ago to $2.09 per gallon. That's down $1.09 from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Heating oil prices in the New England region are at $2.04 per gallon, down 1-tenth of a cent from last week, and down $1.11

  18. Residential heating oil price decreases

    Gasoline and Diesel Fuel Update (EIA)

    Residential heating oil price decreases The average retail price for home heating oil fell 5-tenths of a cent from a week ago to $2.09 per gallon. That's down $1.20 from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Heating oil prices in the New England region are at $2.03 per gallon, down 9-tenths of a cent from last week, and down $1.22

  19. Residential heating oil price decreases

    Gasoline and Diesel Fuel Update (EIA)

    Residential heating oil price increases The average retail price for home heating oil rose 6-tenths of a cent from a week ago to $2.10 per gallon. That's down $1.11 from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Heating oil prices in the New England region are at $2.04 per gallon, up 5-tenths of a cent from last week, and down $1.14

  20. Residential heating oil price decreases

    Gasoline and Diesel Fuel Update (EIA)

    Residential heating oil price increases The average retail price for home heating oil rose 2.6 cents from a week ago to $2.12 per gallon. That's down 91 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. Heating oil prices in the New England region are at $2.06 per gallon, up 2.1 cents from last week, and down 94

  1. Residential heating oil prices decline

    Gasoline and Diesel Fuel Update (EIA)

    propane price increase slightly The average retail price for propane is $2.41 per gallon, up 1-tenth of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.95 per gallon, up 5-tenths of a cent from last week, and down 10.4

  2. Residential heating oil prices increase

    Gasoline and Diesel Fuel Update (EIA)

    heating oil prices increase The average retail price for home heating oil rose 3.9 cents last week to $3.96 per gallon. That's down 2.6 cents from a year ago, based on the residential heating fuel survey by the U.S. Energy Information Administration. The price for heating oil in the New England region averaged 3.92 per gallon, up 5.2 cents from last week, and 1.7

  3. Residential propane price is unchanged

    Gasoline and Diesel Fuel Update (EIA)

    13, 2014 Residential propane price is unchanged The average retail price for propane is $2.40 per gallon, down one-tenth of a cent from last week, based on the residential heating fuel survey by the U.S. Energy Information Administration. Propane prices in the Midwest region averaged $1.94 per gallon, down 7-tenths of a cent from last week, and down 6

  4. Model development and data uncertainty integration

    SciTech Connect (OSTI)

    Swinhoe, Martyn Thomas

    2015-12-02

    The effect of data uncertainties is discussed, with the epithermal neutron multiplicity counter as an illustrative example. Simulation using MCNP6, cross section perturbations and correlations are addressed, along with the effect of the 240Pu spontaneous fission neutron spectrum, the effect of P(?) for 240Pu spontaneous fission, and the effect of spontaneous fission and (?,n) intensity. The effect of nuclear data is the product of the initial uncertainty and the sensitivity -- both need to be estimated. In conclusion, a multi-parameter variation method has been demonstrated, the most significant parameters are the basic emission rates of spontaneous fission and (?,n) processes, and uncertainties and important data depend on the analysis technique chosen.

  5. All Price Tables.vp

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

    e There are no direct fuel costs for hydroelectric, geothermal, wind, photovoltaic, or solar thermal energy. f Electricity imports are included in these prices but not shown...

  6. All Price Tables.vp

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

    g There are no direct fuel costs for hydroelectric, geothermal, wind, photovoltaic, or solar thermal energy. h Electricity imports are included in these prices but not shown...

  7. STEO November 2012 - gas prices

    Gasoline and Diesel Fuel Update (EIA)

    drivers to pull up to lower prices at the gasoline pump in the fourth quarter U.S. drivers should see lower gasoline prices in the fourth quarter of this year. The national pump price is expected to average $3.56 per gallon during the period said the U.S. Energy Information Administration in its new monthly short-term energy outlook. That's down 4 cents from what the agency projected in last month's forecast. The average price for regular gasoline fell by 31 cents per gallon from the start of

  8. Investment and Upgrade in Distributed Generation under Uncertainty

    SciTech Connect (OSTI)

    Siddiqui, Afzal; Maribu, Karl

    2008-08-18

    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.

  9. Understanding Trends in Wind Turbine Prices Over the Past Decade

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2011-10-26

    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.

  10. Relationship Between Wind Generation and Balancing Energy Market Prices in ERCOT: 2007-2009

    SciTech Connect (OSTI)

    Nicholson, E.; Rogers, J.; Porter, K.

    2010-11-01

    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.

  11. Gas Exploration Software for Reducing Uncertainty in Gas Concentration

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

    Estimates - Energy Innovation Portal Energy Analysis Energy Analysis Find More Like This Return to Search Gas Exploration Software for Reducing Uncertainty in Gas Concentration Estimates Lawrence Berkeley National Laboratory Contact LBL About This Technology Technology Marketing SummaryEstimating reservoir parameters for gas exploration from geophysical data is subject to a large degree of uncertainty. Seismic imaging techniques, such as seismic amplitude versus angle (AVA) analysis, can

  12. New Hampshire Natural Gas Prices

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

    9.74 7.87 7.17 5.90 NA 4.34 1989-2015 Residential Price 16.56 19.32 22.79 23.02 17.97 14.18 1989-2015 Percentage of Total Residential Deliveries included in Prices 100.0 100.0...

  13. Natural Gas Futures Prices (NYMEX)

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

    030116 030216 030316 030416 030716 030816 View History Spot Price Henry Hub 1.57 1.60 1.59 1.49 1.56 1997-2016 Futures Prices Contract 1 1.742 1.678 1.639 1.666 1.690 ...

  14. Natural Gas Futures Prices (NYMEX)

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

    012916 020516 021216 021916 022616 030416 View History Spot Price Henry Hub 2.22 2.11 2.16 1.94 1.82 1.57 1997-2016 Futures Prices Contract 1 2.20 2.05 2.05 1.88 1.78 ...

  15. Natural Gas Futures Prices (NYMEX)

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

    2010 2011 2012 2013 2014 2015 View History Spot Price Henry Hub 4.37 4.0 2.75 3.73 4.37 2.62 1997-2015 NGPL Composite 11.83 15.12 10.98 9.94 9.56 4.97 2007-2015 Futures Prices ...

  16. Natural Gas Futures Prices (NYMEX)

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

    Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 View History Spot Price Henry Hub 2.77 2.66 2.34 2.09 1.93 2.28 1997-2016 NGPL Composite 4.42 4.89 4.95 4.72 4.23 2009-2015 Futures Prices ...

  17. South Carolina Natural Gas Prices

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

    6.17 5.67 4.57 5.11 5.22 1984-2014 Residential Price 14.91 13.01 12.93 13.25 12.61 12.65 1967-2014 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0...

  18. Rhode Island Natural Gas Prices

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

    10.05 8.22 4.11 4.01 4.03 1984-2014 Residential Price 17.06 16.48 15.33 14.29 14.55 15.14 1967-2014 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0...

  19. Natural Gas Futures Prices (NYMEX)

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

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Spot Price Henry Hub 2.84 2.77 2.66 2.34 2.09 1.93 1997-2015 NGPL Composite 4.73 4.42 4.89 4.95 2009-2015 Futures Prices...

  20. Diesel prices continue to rise

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

    Diesel prices continue to rise The U.S. average retail price for on-highway diesel fuel rose to 4.16 a gallon on Monday. That's up 5.3 cents from a week ago, based on the weekly...