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Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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1

Demand Uncertainty and Price Dispersion.  

E-Print Network (OSTI)

??Demand uncertainty has been recognized as one factor that may cause price dispersion in perfectly competitive markets with costly and perishable capacity. With the persistence… (more)

Li, Suxi

2007-01-01T23:59:59.000Z

2

Essays on pricing under uncertainty  

E-Print Network (OSTI)

This dissertation analyzes pricing under uncertainty focusing on the U.S. airline industry. It sets to test theories of price dispersion driven by uncertainty in the demand by taking advantage of very detailed information about the dynamics of airline prices and inventory levels as the flight date approaches. Such detailed information about inventories at a ticket level to analyze airline pricing has been used previously by the author to show the importance of capacity constraints in airline pricing. This dissertation proposes and implements many new ideas to analyze airline pricing. Among the most important are: (1) It uses information about inventories at a ticket level. (2) It is the first to note that fare changes can be explained by adding dummy variables representing ticket characteristics. Therefore, the load factor at a ticket level will lose its explanatory power on fares if all ticket characteristics are included in a pricing equation. (3) It is the first to propose and implement a measure of Expected Load Factor as a tool to identify which flights are peak and which ones are not. (4) It introduces a novel idea of comparing actual sales with average sales at various points prior departure. Using these deviations of actual sales from sales under average conditions, it presents is the first study to show empirical evidence of peak load pricing in airlines. (5) It controls for potential endogeneity of sales using dynamic panels. The first essay tests the empirical importance of theories that explain price dispersion under costly capacity and demand uncertainty. The essay calculates a measure of an Expected Load Factor, that is used to calibrate the distribution of demand uncertainty and to identify which flights are peak and which ones are off-peak. It shows that different prices can be explained by the different selling probabilities. The second essay is the first study to provide formal evidence of stochastic peak-load pricing in airlines. It shows that airlines learn about the demand and respond to early sales setting higher prices when expected demand is high and more likely to exceed capacity.

Escobari Urday, Diego Alfonso

2008-05-01T23:59:59.000Z

3

Microsoft Word - Price Uncertainty Supplement.doc  

Annual Energy Outlook 2012 (EIA)

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...

4

Natural Gas Price Uncertainty: Establishing Price Floors  

Science Conference Proceedings (OSTI)

This report presents the results of comprehensive calculations of ceiling and floor prices for natural gas. Ceiling prices are set by the price levels at which it is more economic to switch from natural gas to residual fuel oil in steam units and to distillate in combined cycle units. Switching to distillate is very rare, whereas switching to fuel oil is quite common, varying between winter and summer and increasing when natural gas prices are high or oil prices low. Monthly fuel use was examined for 89 ...

2007-01-11T23:59:59.000Z

5

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

Outlook Price Uncertainty-January 2010 Outlook Price Uncertainty-January 2010 1 January 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 January 12, 2010 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged $74.50 per barrel in December 2009, about $3.50 per barrel lower than the prior month's average. The WTI spot price fell from $78 to $70 during the first 2 weeks of December, but colder-than-normal weather and U.S. crude oil and product inventory draws that exceeded the December 5-year averages helped push it back up to $79 per barrel by the end of the month. EIA forecasts that WTI spot prices will weaken over

6

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 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 Chart). Energy price forecasts are highly uncertain, as history has shown (Energy Price Volatility and Forecast Uncertainty). WTI futures for September 2010 delivery for the

7

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 1 June 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 June 8, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged less than $74 per barrel in May 2010, almost $11 per barrel below the prior month's average and $7 per barrel lower than 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, a decrease of about $3 per barrel from the previous Outlook (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown. Prices for near-term futures options contracts suggest that the market attaches

8

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

November 2010 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 barrel by the fourth quarter of next year. Projected WTI prices average $79 per barrel in 2010 and $85 per barrel in 2011. WTI futures for January 2011 delivery (for the 5-day period ending November 4)

9

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

May 2010 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 (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown. Prices for near-term futures options contracts suggest that the market attaches

10

Microsoft Word - Price Uncertainty Supplement .docx  

Gasoline and Diesel Fuel Update (EIA)

1 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 from last monthʹs Outlook to $92 per barrel with a continuing rise to an average $99 per barrel in the fourth quarter of 2012. The projected annual average WTI price is $93 per barrel in 2011 and $98 per barrel in

11

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 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 of reports of a stumbling economic recovery. EIA has lowered its average fourth quarter 2010 WTI spot price forecast to $77 per barrel, compared with $81 in last month's Outlook. WTI spot prices are projected to

12

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

October 2010 October 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 October 13, 2010 Release Crude Oil Prices. WTI oil prices averaged $75 per barrel in September but rose above $80 at the end of the month and into early October. EIA has raised the average fourth- quarter 2010 forecasted WTI spot price to $79 per barrel compared with $77 per barrel in last monthʹs Outlook. WTI spot prices are projected to rise to $85 per barrel by the fourth quarter of next year. As has been the case for most of 2010, WTI futures traded with a notable lack of volatility during the third quarter of 2010 (Figure 1). However, prices did bounce in

13

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

March 2010 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, rising to an average of about $82 per barrel by the end of the year and to $85 per barrel by the end of 2011 (West Texas Intermediate Crude Oil Price Chart).

14

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

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 barrel higher than in the last Outlook. Projected WTI prices average $79 per barrel in 2010 and $86 per barrel in 2011. WTI futures for February 2011 delivery during the 5-day period ending December 2

15

Uncertainty analysis  

SciTech Connect

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

Thomas, R.E.

1982-03-01T23:59:59.000Z

16

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

April 2010 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 Asia and the Middle East, and held near $81 until rising to $85 at the start of April. EIA expects WTI prices to average above $81 per barrel this summer, slightly less that $81 for 2010 as a whole,

17

Uncertainty Representation: Estimating Process Parameters for Forward Price Forecasting  

Science Conference Proceedings (OSTI)

Market prices set the value of electric power assets and contracts, yet forward prices are unavailable for time horizons relevant to most valuations. Price forecasts are inherently uncertain because the drivers of prices are uncertain, but equilibrating market forces also work to reduce the growth of uncertainty over time. Consequently, quantifying the degree of future price uncertainty is difficult, but has tremendous strategic potential for power companies seeking to value real options and invest in fl...

1999-12-10T23:59:59.000Z

18

Sensitivity and Uncertainty Analysis  

Energy.gov (U.S. Department of Energy (DOE))

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

19

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

E-Print Network (OSTI)

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

Hashimoto, Susumu

20

The optimal harvesting problem with price uncertainty  

E-Print Network (OSTI)

Jul 1, 2011 ... tation when timber price is governed by a stochastic process. ... in terms of the parameters of the price process and the discount factor.

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Microsoft Word - Documentation - Price Forecast Uncertainty.doc  

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

October 2009 October 2009 1 October 2009 Short-Term Energy Outlook Supplement: Energy Price Volatility and Forecast Uncertainty 1 Summary It is often noted that energy prices are quite volatile, reflecting market participants' adjustments to new information from physical energy markets and/or markets in energy- related financial derivatives. Price volatility is an indication of the level of uncertainty, or risk, in the market. This paper describes how markets price risk and how the market- clearing process for risk transfer can be used to generate "price bands" around observed futures prices for crude oil, natural gas, and other commodities. These bands provide a quantitative measure of uncertainty regarding the range in which markets expect prices to

22

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

E-Print Network (OSTI)

This study presents an analysis of several recently published methods for quantifying the uncertainty in economic evaluations due to uncertainty in future oil prices. Conventional price forecasting methods used in the industry typically underestimate the range of uncertainty in oil and gas price forecasts. These forecasts traditionally consider pessimistic, most-likely, and optimistic cases in an attempt to quantify economic uncertainty. The recently developed alternative methods have their unique strengths as well as weaknesses that may affect their applicability in particular situations. While stochastic methods can improve the assessment of price uncertainty they can also be tedious to implement. The inverted hockey stick method is found to be an easily applied alternative to the stochastic methods. However, the primary basis for validating this method has been found to be unreliable. In this study, a consistent and reliable validation of uncertainty estimates predicted by the inverted hockey stick method is presented. Verifying the reliability of this model will ensure reliable quantification of economic uncertainty. Although we cannot eliminate uncertainty from investment evaluations, we can better quantify the uncertainty by accurately predicting the volatility in future oil and gas prices. Reliably quantifying economic uncertainty will enable operators to make better decisions and allocate their capital with increased efficiency.

Fariyibi, Festus Lekan

2006-08-01T23:59:59.000Z

23

Volatile coal prices reflect supply, demand uncertainties  

SciTech Connect

Coal mine owners and investors say that supply and demand are now finally in balance. But coal consumers find that both spot tonnage and new contract coal come at a much higher price.

Ryan, M.

2004-12-15T23:59:59.000Z

24

Microsoft Word - feb10-Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

February 2010 February 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 February 12, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $78.33 per barrel in January 2010, almost $4 per barrel higher than the prior month's average and matching the $78-per-barrel forecast in last month's Outlook. The WTI spot price peaked at $83.12 on January 6 and then fell to $72.85 on January 29 as the weather turned warm and concerns about the strength of world economic recovery increased. EIA forecasts that WTI spot prices will remain near current levels over the next few months, averaging $76 per barrel in February and March, before rising to about $82 per barrel in the late

25

Uncertainty and calibration analysis  

SciTech Connect

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

Coutts, D.A.

1991-03-01T23:59:59.000Z

26

Subject: Cost and Price Analysis | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Subject: Cost and Price Analysis Subject: Cost and Price Analysis Subject: Cost and Price Analysis More Documents & Publications Subject: Cost and Price Analysis Policy Flash...

27

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

global gasoline and diesel price and income elasticities.shift in the short-run price elasticity of gasoline demand.Habits and Uncertain Relative Prices: Simulating Petrol Con-

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

28

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

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

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

29

Bayesian calibration Uncertainty Sensitivity analysis  

E-Print Network (OSTI)

available at www.sciencedirect.com journal homepage: www.elsevier.com/locate/ecolmodel Sensitivity and uncertainty analysis from a coupled 3-PG and soil organic matter decomposition model

Monte Carlo; Markov Chain

2008-01-01T23:59:59.000Z

30

Oil price analysis  

Science Conference Proceedings (OSTI)

The transport has been in the whole history of mankind the basic and determining mover of the human society shape. It determined not only the position of towns, but also their inner design and it was also last but not least the basic element of the economic ... Keywords: GDP, deposit, fuels, history, market equilibrium, oil, oil reserves, price

Zdenek Riha; Viktorie Jirova; Marek Honcu

2011-12-01T23:59:59.000Z

31

Congestion Pricing under Operational, Supply-Side Uncertainty  

E-Print Network (OSTI)

of public-private partner- ships. To support the process of determining appropriate prices, a large amount

Kockelman, Kara M.

32

EIA - Analysis of Natural Gas Prices  

U.S. Energy Information Administration (EIA)

The analysis focuses on natural gas end-use consumption trends, natural gas prices, ... during the year. Categories: Prices ... of 20 percent in the WTI leads to ...

33

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

E-Print Network (OSTI)

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

Durand-Lasserve, Olivier

34

Oil Price Uncertainty and Industrial Production Karl Pinnoy  

E-Print Network (OSTI)

improvements in GDP per unit of energy use. However, for those series, where oil price volatility is signi one would expect, based on trend improvements in GDP per unit of energy use. However, for those series, P. and L. Kilian (2009). "How Sensitive Are Consumer Expenditures to Retail Energy Prices

Maurer, Frank

35

A Large US Retailer Selects Transportation Carriers Under Diesel Price Uncertainty  

Science Conference Proceedings (OSTI)

A large US retailer that procures transportation services from third-party carriers experienced an unexpected jump in fuel surcharges as the price of diesel fuel skyrocketed in the summer of 2008. As a result, it sought to limit its future exposure to ... Keywords: price uncertainty, risk aversion, service contract, transportation

John Turner; Ben Peterson; Soo-Haeng Cho; Sunder Kekre; Alan Scheller-Wolf

2012-07-01T23:59:59.000Z

36

Summary Short?Term Energy Outlook Supplement: Energy Price Volatility and Forecast Uncertainty 1  

E-Print Network (OSTI)

It is often noted that energy prices are quite volatile, reflecting market participants’ adjustments to new information from physical energy markets and/or markets in energyrelated financial derivatives. Price volatility is an indication of the level of uncertainty, or risk, in the market. This paper describes how markets price risk and how the marketclearing process for risk transfer can be used to generate “price bands ” around observed futures prices for crude oil, natural gas, and other commodities. These bands provide a quantitative measure of uncertainty regarding the range in which markets expect prices to trade. The Energy Information Administration’s (EIA) monthly Short-Term Energy Outlook (STEO) publishes “base case ” projections for a variety of energy prices that go out 12 to 24 months (every January the STEO forecast is extended through December of the following year). EIA has recognized that all price forecasts are highly uncertain and has described the uncertainty by identifying the market factors that may significantly move prices away from their expected paths, such as economic growth, Organization of Petroleum Exporting Countries (OPEC) behavior, geo-political events, and hurricanes.

unknown authors

2009-01-01T23:59:59.000Z

37

Subject: Cost and Price Analysis | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Subject: Cost and Price Analysis Subject: Cost and Price Analysis Subject: Cost and Price Analysis More Documents & Publications Acquisition Letter 2009-03 Acquisition...

38

EIA - Natural Gas Price Data & Analysis  

Gasoline and Diesel Fuel Update (EIA)

Prices Prices Prices U.S. and State prices for wellhead, imports, exports, citygate, and end-use sectors. Percentages of total volume delivered by sector. (monthly, annual). Residential and Commercial Prices by Local Distributors and Marketers Average price of natural gas delivered to residential and commercial consumers by local distribution companies and marketers, and the percent sold by local distribution companies in selected states and DC (annual). Spot and Futures Prices Henry Hub natural gas spot price and New York Mercantile Exchange futures contract prices for natural gas based on delivery at the Henry Hub in Louisiana (daily, weekly, monthly, annual). Natural Gas Weekly Update Analysis of current price, supply, and storage data; and a weather snapshot.

39

Design Feasibility Analysis and Optimization under Uncertainty...  

NLE Websites -- All DOE Office Websites (Extended Search)

Feasibility Analysis and Optimization under Uncertainty - A Bayesian Optimal Decision Framework Speaker(s): Jose M. Ortega Date: October 7, 2003 - 12:00pm Location: Bldg. 90...

40

Analysis of seasonality in energy prices  

Science Conference Proceedings (OSTI)

The identification of normal seasonal trends in energy prices is of considerable importance to budget planners and households. The purpose of this paper is to examine several key energy price series for the existence of these seasonal patterns, and to determine whether these patterns have changed over time. The prices examined are motor gasoline, heating oil, retail residual fuel oil, and residential electricity. The principal users of this analysis are energy analysts and budget planners in private industry and government.

Not Available

1986-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Estimating Marginal Residential Energy Prices in the Analysis...  

NLE Websites -- All DOE Office Websites (Extended Search)

Marginal Residential Energy Prices in the Analysis of Proposed Appliance Energy Efficiency Standards Title Estimating Marginal Residential Energy Prices in the Analysis of Proposed...

42

Effects of the uncertainty about global economic recovery on energy transition and CO2 price  

E-Print Network (OSTI)

This paper examines the impact that uncertainty over economic growth may have on global energy transition and CO 2 prices. We use a general-equilibrium model derived from MERGE, and define several stochastic scenarios for economic growth. Each scenario is characterized by the likelihood of a rapid global economic recovery. More precisely, during each decade, global economy may- with a given probability- shift from the EIA's (2010) loweconomic-growth path to the EIA's (2010) high-economic-growth path. The climate policy considered corresponds in the medium term to the commitments announced after the Copenhagen conference, and in the long term to a reduction of 25 % in global energy-related CO 2 emissions (with respect to 2005). For the prices of CO 2 and electricity, as well as for the implementation of CCS, the branches of the resulting stochastic trajectories appear to be heavily influenced by agents ’ initial expectations of future economic growth and by the economic growth actually realized. Thus, in 2040, the global price of CO 2 may range from $21 (when an initiallyanticipated economic recovery never occurs) to $128 (in case of non-anticipated rapid economic recovery). In addition, we show that within each region, the model internalizes the constraints limiting the expansion of each power-generation technology through the price paid by the power utility for the acquisition of new production capacity. As a result, in China, the curves of endogenous investment costs for onshore and offshore wind are all

Co Price; Olivier Dur; Axel Pierru; Yves Smeers; Olivier Durand-lasserve; Axel Pierru; Yves Smeers

2011-01-01T23:59:59.000Z

43

Valuing modularity Choice of nuclear power investments under price uncertainty: Valuing modularity  

E-Print Network (OSTI)

Abstract: We consider the choice problem faced by a firm in the electricity sector which holds two investment projects. The first project is an irreversible investment in a large nuclear power plant. The second project consists in building a flexible sequence of smaller, modular, nuclear power plants on the same site. In other words, we compare the benefit of the large power plant project coming from increasing returns to scale, to the benefit of the modular project due to its reduced risk (flexibility). We use the theory of real options to measure the value of the option to invest in the successive modules, under price uncertainty. From this theory, it is well-known that risk-neutral entrepreneurs will decide to invest only if the market price of electricity exceeds the cost of electricity by a positive margin which is an increasing function of the market risk. In particular, this margin is larger for the irreversible investment than for the modular project. This is because the investment process in the modular project can be interrupted at any time when the market conditions deteriorate, thereby limiting the potential loss of the investor. We consider in particular an environment where the discount rate is 8 % and volatility of the market price of electricity equals 20 % per year. The modular project consists in four units of 300 MWe each, and in which 40 % of the total overnight cost is borne by the first module. We show that the benefit of modularity is equivalent in terms of profitability to a reduction of the cost of electricity by one-thousand of a euro per kWh.- 2-Valuing modularity

Christian Gollier; David Proult; Françoise Thais; Gilles Walgenwitz

2004-01-01T23:59:59.000Z

44

Uncertainty analysis of well test data  

E-Print Network (OSTI)

During a well test a transient pressure response is created by a temporary change in production rate. The well response is usually monitored during a relatively short period of time, depending upon the test objectives. Reservoir properties are determined from well test data via an inverse problem approach. Uncertainty is inherent in any nonlinear inverse problem. Unfortunately, well test interpretation suffers particularly from a variety of uncertainties that, when combined, reduce the confidence that can be associated with the estimated reservoir properties. The specific factors that have been analyzed in this work are: 1. Pressure noise (random noise) 2. Pressure drift (systematic variation) 3. Rate history effects Our work is based on the analysis of the effects of random pressure noise, the drift error, and the rate history on the estimation of typical reservoir parameters for two common reservoir models: A vertical well with a constant wellbore storage and skin in a homogeneous reservoir. A vertical well with a finite conductivity vertical fracture including wellbore effects in a homogeneous reservoir. This work represents a sensitivity study of the impact of pressure and rate uncertainty on parameter estimation and the confidence intervals associated with these results. In this work we statistically analyze the calculated reservoir parameters to quantify the impact of pressure and rate uncertainty on them.

Merad, Mohamed Belgacem

2002-01-01T23:59:59.000Z

45

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

shift in the short-run price elasticity of gasoline demand.A meta-analysis of the price elasticity of gasoline demand.2007. Consumer demand un- der price uncertainty: Empirical

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

46

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

Science Conference Proceedings (OSTI)

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

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

2011-08-15T23:59:59.000Z

47

Estimating Marginal Residential Energy Prices in the Analysis of Proposed  

NLE Websites -- All DOE Office Websites (Extended Search)

Marginal Residential Energy Prices in the Analysis of Proposed Marginal Residential Energy Prices in the Analysis of Proposed Appliance Energy Efficiency Standards Title Estimating Marginal Residential Energy Prices in the Analysis of Proposed Appliance Energy Efficiency Standards Publication Type Report LBNL Report Number LBNL-44230 Year of Publication 2000 Authors Chaitkin, Stuart, James E. McMahon, Camilla Dunham Whitehead, Robert D. Van Buskirk, and James D. Lutz Document Number LBNL-44230 Date Published March 1 Publisher Lawrence Berkeley National Laboratory City Berkeley Abstract Use of marginal energy prices, instead of average energy prices, represents a theoretically valuable and challenging refinement to the usual life-cycle cost analysis conducted for proposed appliance energy efficiency standards. LBNL developed a method to estimate marginal residential energy prices using a regression analysis based on a nationally representative sample of actual consumer energy bills. Based on the 1997 Residential Energy Consumption Survey (RECS), national mean marginal electricity prices were estimated to be 2.5% less than average electricity prices in the summer and 10.0% less than average prices in the non-summer months. For natural gas, marginal prices were 4.4% less than average prices in the winter and 15.3% less than average prices in the non-winter months.

48

Lumpy Price Adjustments: A Microeconometric Analysis  

E-Print Network (OSTI)

change in response to a given shock. This model is very close in spirit to the econometric model proposed by Rosett (1959) for the analysis of frictions in yield changes. However, we depart from Rosett?s model in that, in our model, the adjustment... , in the sequel, use anymore the index j for products since we estimate this model for each product separately. 4 best modelled as a stochastic process. Another argument for adopting such an approach lies in the synchronization of price changes within stores...

Dhyne, Emmanuel; Fuss, Catherine; Pesaran, M Hashem; Sevestre, Patrick

49

Uncertainty Budget Analysis for Dimensional Inspection Processes (U)  

SciTech Connect

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

Valdez, Lucas M. [Los Alamos National Laboratory

2012-07-26T23:59:59.000Z

50

Measurement uncertainty analysis techniques applied to PV performance measurements  

DOE Green Energy (OSTI)

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.

Wells, C.

1992-10-01T23:59:59.000Z

51

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

NLE Websites -- All DOE Office Websites (Extended Search)

NRELTP-620-35609 ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY NATIONAL RENEWABLE ENERGY LABORATORY Utility Green Pricing Programs: A Statistical Analysis of Program...

52

Analysis of Price Volatility in Natural Gas Markets  

Reports and Publications (EIA)

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

Erin Mastrangelo

2007-08-17T23:59:59.000Z

53

Strategic power plant investment planning under fuel and carbon price uncertainty.  

E-Print Network (OSTI)

??The profitability of power plant investments depends strongly on uncertain fuel and carbon prices. In this doctoral thesis, we combine fundamental electricity market models with… (more)

Geiger, Ansgar

2011-01-01T23:59:59.000Z

54

Statistical Uncertainty Analysis Applied to Criticality Calculation  

Science Conference Proceedings (OSTI)

In this paper, we present an uncertainty methodology based on a statistical approach, for assessing uncertainties in criticality prediction using monte carlo method due to uncertainties in the isotopic composition of the fuel. The methodology has been applied to criticality calculations with MCNP5 with additional stochastic input of the isotopic fuel composition. The stochastic input were generated using the latin hypercube sampling method based one the probability density function of each nuclide composition. The automatic passing of the stochastic input to the MCNP and the repeated criticality calculation is made possible by using a python script to link the MCNP and our latin hypercube sampling code.

Hartini, Entin; Andiwijayakusuma, Dinan; Susmikanti, Mike; Nursinta, A. W. [Centre for Nuclear Informatics Development, National Nuclear Energy Agency of Indonesia (Indonesia)

2010-06-22T23:59:59.000Z

55

Uncertainty in climate change policy analysis  

E-Print Network (OSTI)

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

Jacoby, Henry D.; Prinn, Ronald G.

56

Maximizing Gross Margin of a Pumped Storage Hydroelectric Facility Under Uncertainty in Price and Water Inflow.  

E-Print Network (OSTI)

??The operation of a pumped storage hydroelectric facility is subject to uncertainty. This is especially true in today’s energy markets. Published models to achieve optimal… (more)

Ikudo, Akina

2009-01-01T23:59:59.000Z

57

Analysis of alternative-fuel price trajectories  

Science Conference Proceedings (OSTI)

Findings are presented from a study to (1) acquire, analyze, and report alternative published price projections including both oil- and coal-price trajectories, and to (2) apply the fixed-annuity formula to the updated primary source projections (Energy Information Administration; Data Resources, Inc.; and Wharton Econometric Forecasting Associates, Inc.) and to the newly acquired price projections. This report also encompasses: comparisons of key assumptions underlying the price projections, and a discussion of the applicability of the fixed-annuity formula as used in the alternative-cost calculation. Section II contains graphic presentations of all updated and newly acquired coal and oil price forecasts and the corresponding calculated annuity equivalents, tabulated presentations and discussions of each forecast and underlying assumptions, and a description of how each forecast price series was transformed into input for the present-value formulas. Section III presents the fixed-annuity formula employed and discusses its appropriateness for this application. Section IV discusses the applicability of the net present value approach for comparing alternate-fuel price trajectories. Appendix A contains a listing of contacts as potential sources of price forecasts. Appendix B contains the raw forecast data from each forecast source and the coal and oil price series derived from the raw data which were actually input into the cost calculation procedure. Appendix C contains a description and listing of the computer program developed to implement the cost calculation procedure. Finally, Appendix D contains tabulations and discussions of other alternative world crude price forecasts that were identified, but for which no corresponding coal-price projections were available. (MCW)

Not Available

1980-12-31T23:59:59.000Z

58

An analysis of nine-ending pricing  

E-Print Network (OSTI)

Prices ending in 9 are ubiquitous. In this paper I first develop a theoretical model of the effect of such prices on sales and review the empirical literature on the topic. Then I use a data set from an online experiment ...

Wu, Wei, 1973-

2004-01-01T23:59:59.000Z

59

EIA - Analysis of Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

Prices Prices 2010 Peaks, Plans and (Persnickety) Prices This presentation provides information about EIA's estimates of working gas peak storage capacity, and the development of the natural gas storage industry. Natural gas shale and the need for high deliverability storage are identified as key drivers in natural gas storage capacity development. The presentation also provides estimates of planned storage facilities through 2012. Categories: Prices, Storage (Released, 10/28/2010, ppt format) Natural Gas Year-In-Review 2009 This is a special report that provides an overview of the natural gas industry and markets in 2009 with special focus on the first complete set of supply and disposition data for 2009 from the Energy Information Administration. Topics discussed include natural gas end-use consumption trends, offshore and onshore production, imports and exports of pipeline and liquefied natural gas, and above-average storage inventories. Categories: Prices, Production, Consumption, Imports/Exports & Pipelines, Storage (Released, 7/9/2010, Html format)

60

Prices  

Gasoline and Diesel Fuel Update (EIA)

Information AdministrationPetroleum Marketing Annual 1998 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) -...

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Prices  

Gasoline and Diesel Fuel Update (EIA)

Information AdministrationPetroleum Marketing Annual 2001 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) -...

62

Prices  

Annual Energy Outlook 2012 (EIA)

Information AdministrationPetroleum Marketing Annual 1999 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) -...

63

Measurement uncertainty analysis techniques applied to PV performance measurements  

DOE Green Energy (OSTI)

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.

Wells, C.

1992-10-01T23:59:59.000Z

64

Cost estimation and analysis for government contract pricing in china  

Science Conference Proceedings (OSTI)

Software cost estimation methods and their applications in government contract pricing have been developed and practiced for years. However, in China, the government contract process has been questioned in some aspects. It is largely based on analogy ... Keywords: cost analysis., cost estimation, government contract pricing

Mei He; Ye Yang; Qing Wang; Mingshu Li

2007-05-01T23:59:59.000Z

65

Multi-fractal Analysis of World Crude Oil Prices  

Science Conference Proceedings (OSTI)

In order to reveal the stylized facts of world crude oil prices, R/S (Rescaled Range Analysis) method is introduced in this paper. For illustration, WTI (West Texas Intermediate) and Brent daily crude oil prices are used in this paper. The calculated ...

Xiucheng Dong; Junchen Li; Jian Gao

2009-04-01T23:59:59.000Z

66

Efficient Algorithms for Heavy-Tail Analysis under Interval Uncertainty  

E-Print Network (OSTI)

Efficient Algorithms for Heavy-Tail Analysis under Interval Uncertainty Vladik Kreinovich1 heavy-tailed distri- butions, i.e., distributions in which (x) decreases as (x) x- . To properly take for computing these ranges. Keywords: heavy-tailed distributions, interval uncertainty, efficient algorithms

Kreinovich, Vladik

67

Analysis of the effect of packing capacity on pork prices  

E-Print Network (OSTI)

In 1998, pork prices fell to an all time low. Across the industry, concern was expressed for research as to what led to this price crash. Capacity constraints at the packer level have been a key area of concern. This study is an analysis of the effect of capacity constraints on pork prices. Ordinary least squares (OLS) models were run for both live and cutout prices. Capacity constraints were measured three ways: using a binary variable (0,1 dummy) and two continuous variables. One continuous variable was for the number of head slaughtered on the weekend, and the second continuous variable was found by using a ratio of slaughter during the weekends to slaughter during the 5-day workweek ("over-flow" ratio). The continuous variables used to measure capacity constraints were statistically significant explanatory factors in the regressions for hog and pork prices. The capacity constraints were estimated to have a different relationship with the prices at the farm level as compared with packer prices. Increasing capacity constraints is associated with a negative relationship to farm prices, and a positive relationship to packer prices. The measurement used for over-flow ratio, the ratio of weekend slaughter to slaughter during the 5-day workweek, did not generate different results than the continuous variable of weekend slaughter. The estimated coefficients for both continuous variables were more statistically significant than a dummy variable approach for the capacity constraint.

Spivey, Sarah Elizabeth

2000-01-01T23:59:59.000Z

68

Design Feasibility Analysis and Optimization under Uncertainty - A Bayesian  

NLE Websites -- All DOE Office Websites (Extended Search)

Design Feasibility Analysis and Optimization under Uncertainty - A Bayesian Design Feasibility Analysis and Optimization under Uncertainty - A Bayesian Optimal Decision Framework Speaker(s): Jose M. Ortega Date: October 7, 2003 - 12:00pm Location: Bldg. 90 Seminar Host/Point of Contact: Michael Sohn A new approach to the problem of identifying design feasibility and optimality under uncertainty is introduced. Based on the Bayesian concepts of predictive probability and expected utility, the method can quantify the feasibility of a process design and identify the optimal operation conditions when there are uncertainties in the process parameters. The use of Bayesian statistics enables the treatment of a very wide class of parameter uncertainties, including simple bounds, analytic probability density functions, correlation structures and empirical distributions.

69

Impacts of PSC Elements on Contract Economics under Oil Price Uncertainty  

Science Conference Proceedings (OSTI)

Production sharing contract (PSC) is one of the most common types of cooperation modes in international petroleum contracts. The elements that affect PSC economics mainly include royalty, cost oil, profit oil as well as income tax. Assuming that oil ... Keywords: Production Sharing, Oil Price, Oil Contract, International Petroleum Cooperation

Wang Zhen; Zhao Lin; Liu Mingming

2010-05-01T23:59:59.000Z

70

Including uncertainty in hazard analysis through fuzzy measures  

Science Conference Proceedings (OSTI)

This paper presents a method for capturing the uncertainty expressed by an Hazard Analysis (HA) expert team when estimating the frequencies and consequences of accident sequences and provides a sound mathematical framework for propagating this uncertainty to the risk estimates for these accident sequences. The uncertainty is readily expressed as distributions that can visually aid the analyst in determining the extent and source of risk uncertainty in HA accident sequences. The results also can be expressed as single statistics of the distribution in a manner analogous to expressing a probabilistic distribution as a point-value statistic such as a mean or median. The study discussed here used data collected during the elicitation portion of an HA on a high-level waste transfer process to demonstrate the techniques for capturing uncertainty. These data came from observations of the uncertainty that HA team members expressed in assigning frequencies and consequences to accident sequences during an actual HA. This uncertainty was captured and manipulated using ideas from possibility theory. The result of this study is a practical method for displaying and assessing the uncertainty in the HA team estimates of the frequency and consequences for accident sequences. This uncertainty provides potentially valuable information about accident sequences that typically is lost in the HA process.

Bott, T.F.; Eisenhawer, S.W.

1997-12-01T23:59:59.000Z

71

Analysis of price diffusion in financial markets using PUCK model  

E-Print Network (OSTI)

Based on the new type of random walk process called the Potentials of Unbalanced Complex Kinetics (PUCK) model, we theoretically show that the price diffusion in large scales is amplified 2/(2 + b) times, where b is the coefficient of quadratic term of the potential. In short time scales the price diffusion depends on the size M of the super moving average. Both numerical simulations and real data analysis of Yen-Dollar rates are consistent with theoretical analysis.

Mizuno, T; Takayasu, M; Mizuno, Takayuki; Takayasu, Hideki; Takayasu, Misako

2006-01-01T23:59:59.000Z

72

Analysis of automated highway system risks and uncertainties. Volume 5  

SciTech Connect

This volume describes a risk analysis performed to help identify important Automated Highway System (AHS) deployment uncertainties and quantify their effect on costs and benefits for a range of AHS deployment scenarios. The analysis identified a suite of key factors affecting vehicle and roadway costs, capacities and market penetrations for alternative AHS deployment scenarios. A systematic protocol was utilized for obtaining expert judgments of key factor uncertainties in the form of subjective probability percentile assessments. Based on these assessments, probability distributions on vehicle and roadway costs, capacity and market penetration were developed for the different scenarios. The cost/benefit risk methodology and analysis provide insights by showing how uncertainties in key factors translate into uncertainties in summary cost/benefit indices.

Sicherman, A.

1994-10-01T23:59:59.000Z

73

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

E-Print Network (OSTI)

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

Langewisch, Dustin R

2010-01-01T23:59:59.000Z

74

Tariff-based analysis of commercial building electricity prices  

E-Print Network (OSTI)

4.2 E?ective Marginal Prices . . . . . . . . . . . . . . . .Demand Prices . . . . . . . . . . . . . . . . . . . . . .4 Calculation of Electricity Prices 4.1 Average

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

2008-01-01T23:59:59.000Z

75

An Analysis of Price Volatility in Natural Gas Markets  

U.S. Energy Information Administration (EIA)

Market prices respond to shifts in supply and demand, and the degree of price response relates to the price elasticity of both. Natural gas prices have been particularly

76

Tariff-based analysis of commercial building electricity prices  

E-Print Network (OSTI)

Energy and Demand Prices . . . . . . . . . . . . . . . . . . . . . .US DOE 1999. Marginal Energy Prices Report U.S. Departmentmarginal price Marginal energy price in cper kwh Marginal

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

2008-01-01T23:59:59.000Z

77

System architecture analysis and selection under uncertainty  

E-Print Network (OSTI)

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

Smaling, Rudolf M

2005-01-01T23:59:59.000Z

78

Price Realism Analysis| An Examination of an Area Ripe for Reform.  

E-Print Network (OSTI)

?? The purpose of this thesis is to explore the confusion and misapplication of price realism analysis in evaluations of firm-fixed price contracts and to… (more)

Bernstein, Alexis J.

2012-01-01T23:59:59.000Z

79

Analysis of leaded and unleaded gasoline pricing. Final report  

SciTech Connect

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

1985-03-15T23:59:59.000Z

80

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

E-Print Network (OSTI)

4 Customer Price as a function of Marginal Cost with upwardB.1 Relationship between Customer Price and Marginal Coston final ACHE consumer prices. Our statistical analysis of

2004-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

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

SciTech Connect

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.

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

1995-01-01T23:59:59.000Z

82

Visual Scanning Hartmann Optical Tester (VSHOT) Uncertainty Analysis (Milestone Report)  

DOE Green Energy (OSTI)

In 1997, an uncertainty analysis was conducted of the Video Scanning Hartmann Optical Tester (VSHOT). In 2010, we have completed a new analysis, based primarily on the geometric optics of the system, and it shows sensitivities to various design and operational parameters. We discuss sources of error with measuring devices, instrument calibrations, and operator measurements for a parabolic trough mirror panel test. These help to guide the operator in proper setup, and help end-users to understand the data they are provided. We include both the systematic (bias) and random (precision) errors for VSHOT testing and their contributions to the uncertainty. The contributing factors we considered in this study are: target tilt; target face to laser output distance; instrument vertical offset; laser output angle; distance between the tool and the test piece; camera calibration; and laser scanner. These contributing factors were applied to the calculated slope error, focal length, and test article tilt that are generated by the VSHOT data processing. Results show the estimated 2-sigma uncertainty in slope error for a parabolic trough line scan test to be +/-0.2 milliradians; uncertainty in the focal length is +/- 0.1 mm, and the uncertainty in test article tilt is +/- 0.04 milliradians.

Gray, A.; Lewandowski, A.; Wendelin, T.

2010-10-01T23:59:59.000Z

83

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

Science Conference Proceedings (OSTI)

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

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

1997-12-01T23:59:59.000Z

84

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

SciTech Connect

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

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

1997-12-01T23:59:59.000Z

85

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

Science Conference Proceedings (OSTI)

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.

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

1998-04-01T23:59:59.000Z

86

Strategic Price Competition and Price Disperion in the Airline Industry: A Conceptual Framework and Empirical Analysis.  

E-Print Network (OSTI)

??It is a generally accepted belief in marketing literature that variation in prices, i.e. price dispersion, is a critical, strategic factor that influences product demand,… (more)

Gailey, Edward D.

2009-01-01T23:59:59.000Z

87

Analysis on various pricing scenarios in a deregulated electricity market  

E-Print Network (OSTI)

The electricity pricing structure in Texas has changed after deregulation (January 2002). The Energy Systems Laboratory has served as a technical consultant on electricity purchases to several universities in the Texas A&M University System since 2001. In the fiscal year of 2006 Stephen F. Austin State University joined with the TAMU campuses and agencies, and there are now 183 accounts in the Electric Reliability Council of Texas (ERCOT) North, Northeast, South, West, and Houston areas of Texas. From the 183 accounts, 9 Interval Data Recorder (IDR) accounts consume 92% of the total load. The objective of this research is to find the most economic price structure to purchase electricity for the Texas A&M System and Stephen F. Austin University by analyzing various pricing scenarios: the spot market, forward contracts, take or pay contracts and on/off season (tiered) contracts. The analysis was based on the 9 IDR accounts. The prices for the spot market were given by ERCOT and the other prices by Sempra. The energy charges were calculated every 15 minute using the real historical consumption of each facility and the aggregated load of all facilities. The result for the analysis was given for each institution separately, as well as for the aggregated load of all facilities. The results of the analysis showed that the tiered price was the most economical structure to purchase electricity for each individual university and for the total aggregated load of all 9 IDR accounts. From March 1, 2005 to February 28, 2006, purchasing electricity on the tiered price would have cost $13,810,560. The forward contract, that is, purchasing electricity on a fixed rate, was the next cheapest with an energy cost of $14,266,870 from March 1, 2005 to February 28, 2006, 3% higher than purchasing electricity at the tiered price. The most expensive method to purchase electricity would have been the spot market. Its energy costs would have been approximately $18,171,610, 36% and 31% higher, respectively, than purchasing electricity at the tiered price and the fixed rate.

Afanador Delgado, Catalina

2006-08-01T23:59:59.000Z

88

Tariff-based analysis of commercial building electricity prices  

E-Print Network (OSTI)

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

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

2008-01-01T23:59:59.000Z

89

Electricity Forward Prices: A High-Frequency Empirical Analysis  

E-Print Network (OSTI)

P. 2002. Modelling Electricity Prices: Interna- tionalSchwartz, E. 2002. Electricity Prices and Power Derivatives:spot and forward electricity prices in more detail than in

Longstaff, Francis; Wang, Ashley

2002-01-01T23:59:59.000Z

90

Tariff-based analysis of commercial building electricity prices  

E-Print Network (OSTI)

4 Calculation of Electricity Prices 4.1 Averageseasonal and annual electricity prices by region in c/kWh.based annual average electricity price vs. annual energy

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

2008-01-01T23:59:59.000Z

91

ELECTRICITY FORWARD PRICES: A High-Frequency Empirical Analysis  

E-Print Network (OSTI)

P. 2002. Modelling Electricity Prices: Interna- tionalSchwartz, E. 2002. Electricity Prices and Power Derivatives:spot and forward electricity prices in more detail than in

Longstaff, Francis A; Wang, Ashley

2002-01-01T23:59:59.000Z

92

Statistical uncertainty analysis of radon transport in nonisothermal, unsaturated soils  

Science Conference Proceedings (OSTI)

To accurately predict radon fluxes soils to the atmosphere, we must know more than the radium content of the soil. Radon flux from soil is affected not only by soil properties, but also by meteorological factors such as air pressure and temperature changes at the soil surface, as well as the infiltration of rainwater. Natural variations in meteorological factors and soil properties contribute to uncertainty in subsurface model predictions of radon flux, which, when coupled with a building transport model, will also add uncertainty to predictions of radon concentrations in homes. A statistical uncertainty analysis using our Rn3D finite-element numerical model was conducted to assess the relative importance of these meteorological factors and the soil properties affecting radon transport. 10 refs., 10 figs., 3 tabs.

Holford, D.J.; Owczarski, P.C.; Gee, G.W.; Freeman, H.D.

1990-10-01T23:59:59.000Z

93

Customer Response to Electricity Prices: Information to Support Wholesale Price Forecasting and Market Analysis  

Science Conference Proceedings (OSTI)

Understanding customer response to electricity price changes is critical to profitably managing a retail business, designing efficient wholesale power markets, and forecasting power prices for valuation of long-lived generating assets. This report packages the collective results of dozens of price response studies for use by forward price forecasters and power market analysts in forecasting loads, revenues, and the benefits of time-varying prices more accurately. In specific, the report describes key mea...

2001-11-30T23:59:59.000Z

94

Analysis of Federal Subsidies: Implied Price of Carbon  

Science Conference Proceedings (OSTI)

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.

D. Craig Cooper; Thomas Foulke

2010-10-01T23:59:59.000Z

95

A Time Series Analysis of Food Price and Its Input Prices  

E-Print Network (OSTI)

Rapid increases in consumer food price beginning in 2007 generated interest in identifying the main factors influencing these increases. In subsequent years, food prices have fluctuated, but generally have continued their ascent. The effects of crude oil, gasoline, corn, and ethanol prices, as well as, the relative foreign exchange rate of the U.S. dollar and producer price indexes for food manufacturing and fuel products on domestic food prices are examined. Because the data series are non-stationary and cointegrated, a vector error correction model is estimated. Weak exogeneity and exclusion tests in the cointegration space are performed. Directed acyclical graphs are used to specify contemporaneous causal relationships. Dynamic interactions among the series are given by impulse response functions and forecast error variance decompositions. Weak exogeneity tests indicate all eight series work to bring the system back into equilibrium following a shock to the system. Further, exclusion tests suggest crude oil, gasoline, food CPI, ethanol, and food PPI variables are not in the long-run relationships. Dynamic analyses suggest the following relationships. Ethanol price is not a major factor in domestic food prices, suggesting that food prices are largely unaffected by the recent increased use of corn-based ethanol for fuel. Crude oil prices, corn prices, and the relative foreign exchange rate of the U.S. dollar, however, do influence domestic food prices with corn price contributing the most to food price variability. Innovation accounting inferences are robust to potential different contemporaneous causal specifications.

Routh, Kari 1988-

2012-12-01T23:59:59.000Z

96

Documentation - Price Forecast Uncertainty  

U.S. Energy Information Administration (EIA)

Energy Information Administration/Short-Term Energy Outlook Supplement — October 2009 2 example, if a confidence level of 95 percent is specified, then a range of ...

97

Markets & Finance - Analysis - U.S. Energy Information Administration...  

Annual Energy Outlook 2012 (EIA)

Glossary FAQS Overview Data Market Prices and Uncertainty Charts Archive Analysis & Projections Most Requested Electricity Financial Markets Financial Reporting System...

98

Utility green pricing programs: A statistical analysis of program effectiveness  

E-Print Network (OSTI)

Consumer Demand for ‘Green Power’ and Energy Efficiency. ”of renewable energy supported by green pricing programs (renewable energy purchases through green pricing programs (

Wiser, Ryan; Olson, Scott; Bird, Lori; Swezey, Blair

2004-01-01T23:59:59.000Z

99

ELECTRICITY FORWARD PRICES: A High-Frequency Empirical Analysis  

E-Print Network (OSTI)

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

Longstaff, Francis A; Wang, Ashley

2002-01-01T23:59:59.000Z

100

Electricity Forward Prices: A High-Frequency Empirical Analysis  

E-Print Network (OSTI)

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

Longstaff, Francis; Wang, Ashley

2002-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Tariff-based analysis of commercial building electricity prices  

E-Print Network (OSTI)

price vs. annual peak demand. . . . . Tari?-based annuala function of annual peak demand. . . Probability that theelectricity price vs. annual peak demand; each point is one

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

2008-01-01T23:59:59.000Z

102

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

E-Print Network (OSTI)

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

Fazzio, Thomas J. (Thomas Joseph)

2010-01-01T23:59:59.000Z

103

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

E-Print Network (OSTI)

OIL PRICE IMPACT ON FINANCIAL MARKETS: CO-SPECTRAL ANALYSIS FOR EXPORTING VERSUS IMPORTING://www.economie.polytechnique.edu/ mailto:chantal.poujouly@polytechnique.edu hal-00822070,version1-14May2013 #12;1 Oil price impact Khaled Guesmi3 Abstract The aim of this paper is to study the degree of interdependence between oil price

Paris-Sud XI, Université de

104

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

Science Conference Proceedings (OSTI)

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.

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

1997-06-01T23:59:59.000Z

105

Utility Green Pricing Programs: A Statistical Analysis of Program Effectiveness  

DOE Green Energy (OSTI)

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

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

2004-02-01T23:59:59.000Z

106

ELECTRICITY FORWARD PRICES: A High-Frequency Empirical Analysis  

E-Print Network (OSTI)

electricity prices reported by PJM. Prices are reported inNew Jersey, Maryland (PJM) electricity market for the periodusing the high-frequency PJM data set and documenting risk-

Longstaff, Francis A; Wang, Ashley

2002-01-01T23:59:59.000Z

107

Electricity Forward Prices: A High-Frequency Empirical Analysis  

E-Print Network (OSTI)

electricity prices reported by PJM. Prices are reported inNew Jersey, Maryland (PJM) electricity market for the periodusing the high-frequency PJM data set and documenting risk-

Longstaff, Francis; Wang, Ashley

2002-01-01T23:59:59.000Z

108

Tariff-based analysis of commercial building electricity prices  

E-Print Network (OSTI)

electricity prices developed for residential AC were criticized by a number of stakeholders, who argued that retail rates

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

2008-01-01T23:59:59.000Z

109

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

E-Print Network (OSTI)

??This paper attempts to understand the price dynamics of the North American natural gas market through a statistical survey that includes an analysis of the… (more)

Fazzio, Thomas J. (Thomas Joseph)

2010-01-01T23:59:59.000Z

110

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

DOE Green Energy (OSTI)

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.

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

2000-11-01T23:59:59.000Z

111

Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for deposited material and external doses. Volume 1: Main report  

SciTech Connect

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA deposited material and external dose models.

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

1997-12-01T23:59:59.000Z

112

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

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.

1997-08-01T23:59:59.000Z

113

Hogged Wood Fuel Supply and Price Analysis : Final Report.  

SciTech Connect

This study discusses the factors that determine the supply and demand for hogged wood in the Pacific Northwest, with particular emphasis on the role of the regional pulp and paper industry and lumber industry. Because hogged wood is often a substitute for conventional fuels, the consumption and price of natural gas, electricity, fuel oil and coal are also addressed. A detailed and comprehensive examination of the indicies relating to the hogged wood market is provided, including analysis and graphing of all time series variables. A spreadsheet- based forecasting model is developed and presented with an emphasis on explaining the process used to arrive at the final model. 42 refs., 46 figs., 14 tabs. (MHB)

Biederman, Richard T.; Blazek, Christopher F.

1991-05-01T23:59:59.000Z

114

Sensitivity analysis of world oil prices. Analysis report AR/IA/79-47  

SciTech Connect

An analysis of the impact of the political disruption in Iran on the world oil market is presented. During the first quarter of 1979, this disruption caused a loss of approximately 5 million barrels per day (MMBD) of oil production available for export from Iran to the rest of the world. This loss of production and the political climate in Iran have caused much speculation concerning future Iranian oil production and total Organization of Petroleum Exporting Countries (OPEC) oil production in the nearterm and midterm. The analysis describes these issues in terms of two critical factors: the world oil price and the level of OPEC oil production in the nearterm and midterm. A detailed comparison of the Central Intelligence Agency (CIA) and Energy Information Agency (EIA) forecasting models of world oil prices is presented. This comparison consists of examining reasons for differences in the price forecasts of the CIA model by using CIA assumptions within the EIA model. The CIA and EIA model structures and major parameters are also compared. It is important to note that this analysis is not all encompassing. In particular, the analysis does not provide data on crude oil prices in the spot market, but does provide information on the average crude oil price; and does not permit rationing of oil, since the market is forced to clear only through changes in oil prices. Throughout this paper, world oil prices are defined in terms of real 1978 dollars per barrel of crude oil delivered to the East Coast of the United States net of any import fees.

Rodekohr, M.; Cato, D.

1979-09-01T23:59:59.000Z

115

An Empirical Analysis of Analysts' Target Prices: Short Term . . .  

E-Print Network (OSTI)

Using a large database of analysts' target prices, we examine short-term market reactions to target price announcements and long-term co-movement of target and stock prices. We find a significant market reaction to the information contained in analysts' target prices, both unconditional and conditional on contemporaneously issued stock recommendations and earnings forecast revisions. For example, the spread in average announcement day abnormal returns between positive and negative target price revisions is as high as 7 percent. We also find that stock recommendations and earnings forecast revisions are informative controlling for the information in target prices. Using a cointegration approach, we explore the long-term behavior of market and target prices and estimate the system's long-term equilibrium. In this equilibrium a typical firm's one-year ahead target price is 22 percent higher than its current market price. Finally, while market prices react to the information conveyed in analysts' reports, we show that any subsequent corrections towards the long-term equilibrium are, in effect, done by analysts alone.

Alon Brav; Reuven Lehavy

2001-01-01T23:59:59.000Z

116

Uncertainty Analysis for Broadband Solar Radiometric Instrumentation Calibrations and Measurements: An Update; Preprint  

DOE Green Energy (OSTI)

The measurement of broadband solar radiation has grown in importance since the advent of solar renewable energy technologies in the 1970's, and the concern about the Earth's radiation balance related to climate change in the 1990's. In parallel, standardized methods of uncertainty analysis and reporting have been developed. Historical and updated uncertainties are based on the current international standardized uncertainty analysis method. Despite the fact that new and sometimes overlooked sources of uncertainty have been identified over the period 1988 to 2004, uncertainty in broadband solar radiometric instrumentation remains at 3% to 5% for pyranometers, and 2% to 3% for pyrheliometers. Improvements in characterizing correction functions for radiometer data may reduce total uncertainty. We analyze the theoretical standardized uncertainty sensitivity coefficients for the instrumentation calibration measurement equation and highlight the single parameter (thermal offset voltages), which contributes the most to the observed calibration responsivities.

Myers, D. R.; Reda, I. M.; Wilcox, S. M.; Stoffel, T. L.

2004-04-01T23:59:59.000Z

117

CASMO5/TSUNAMI-3D spent nuclear fuel reactivity uncertainty analysis  

Science Conference Proceedings (OSTI)

The CASMO5 lattice physics code is used in conjunction with the TSUNAMI-3D sequence in ORNL's SCALE 6 code system to estimate the uncertainties in hot-to-cold reactivity changes due to cross-section uncertainty for PWR assemblies at various burnup points. The goal of the analysis is to establish the multiplication factor uncertainty similarity between various fuel assemblies at different conditions in a quantifiable manner and to obtain a bound on the hot-to-cold reactivity uncertainty over the various assembly types and burnup attributed to fundamental cross-section data uncertainty. (authors)

Ferrer, R.; Rhodes, J. [Studsvik Scandpower, Inc., 504 Shoup Ave., Idaho Falls, ID 83402 (United States); Smith, K. [Dept. of Nuclear Science and Engineering, Massachusetts Inst. of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 (United States)

2012-07-01T23:59:59.000Z

118

Microsoft Word - Price Probabilities Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 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 another set of charts listing the probability of the future realized price exceeding or falling below given price levels (see Figures 1A and 1B for West Texas Intermediate crude oil price probabilities). These charts are also available as spreadsheets allowing users to input their own prices to

119

Utility green pricing programs: A statistical analysis of program effectiveness  

E-Print Network (OSTI)

Size Participation Rate (%) Utility Size (# customers) Non-Size Participation Rate (%) Utility Size (# customers)non-residential participation rates in utility green pricing

Wiser, Ryan; Olson, Scott; Bird, Lori; Swezey, Blair

2004-01-01T23:59:59.000Z

120

Forecast Prices  

Gasoline and Diesel Fuel Update (EIA)

Notes: Notes: Prices have already recovered from the spike, but are expected to remain elevated over year-ago levels because of the higher crude oil prices. There is a lot of uncertainty in the market as to where crude oil prices will be next winter, but our current forecast has them declining about $2.50 per barrel (6 cents per gallon) from today's levels by next October. U.S. average residential heating oil prices peaked at almost $1.50 as a result of the problems in the Northeast this past winter. The current forecast has them peaking at $1.08 next winter, but we will be revisiting the outlook in more detail next fall and presenting our findings at the annual Winter Fuels Conference. Similarly, diesel prices are also expected to fall. The current outlook projects retail diesel prices dropping about 14 cents per gallon

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

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

E-Print Network (OSTI)

Thomadakis, Stavros. “Price Regulation Under Uncertainty in698. Bös, Dieter. Pricing and Price Regulation. Elsevier.Optimal Structure of Public Prices. ” The American Economic

Seltzer, Steven A.

2011-01-01T23:59:59.000Z

122

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

E-Print Network (OSTI)

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

Lee, Joosung Joseph, 1974-

2005-01-01T23:59:59.000Z

123

Analysis and reduction of chemical models under uncertainty.  

SciTech Connect

While models of combustion processes have been successful in developing engines with improved fuel economy, more costly simulations are required to accurately model pollution chemistry. These simulations will also involve significant parametric uncertainties. Computational singular perturbation (CSP) and polynomial chaos-uncertainty quantification (PC-UQ) can be used to mitigate the additional computational cost of modeling combustion with uncertain parameters. PC-UQ was used to interrogate and analyze the Davis-Skodje model, where the deterministic parameter in the model was replaced with an uncertain parameter. In addition, PC-UQ was combined with CSP to explore how model reduction could be combined with uncertainty quantification to understand how reduced models are affected by parametric uncertainty.

Oxberry, Geoff; Debusschere, Bert J.; Najm, Habib N.

2008-08-01T23:59:59.000Z

124

A POTENTIAL APPLICATION OF UNCERTAINTY ANALYSIS TO DOE-STD-3009-94 ACCIDENT ANALYSIS  

Science Conference Proceedings (OSTI)

The objective of this paper is to assess proposed transuranic waste accident analysis guidance and recent software improvements in a Windows-OS version of MACCS2 that allows the inputting of parameter uncertainty. With this guidance and code capability, there is the potential to perform a quantitative uncertainty assessment of unmitigated accident releases with respect to the 25 rem Evaluation Guideline (EG) of DOE-STD-3009-94 CN3 (STD-3009). Historically, the classification of safety systems in a U.S. Department of Energy (DOE) nuclear facility's safety basis has involved how subject matter experts qualitatively view uncertainty in the STD-3009 Appendix A accident analysis methodology. Specifically, whether consequence uncertainty could be larger than previously evaluated so the site-specific accident consequences may challenge the EG. This paper assesses whether a potential uncertainty capability for MACCS2 could provide a stronger technical basis as to when the consequences from a design basis accident (DBA) truly challenges the 25 rem EG.

Palmrose, D E; Yang, J M

2007-05-10T23:59:59.000Z

125

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

SciTech Connect

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.

Wells, C.V.

1992-11-01T23:59:59.000Z

126

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

Science Conference Proceedings (OSTI)

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.

Wells, C.V.

1992-11-01T23:59:59.000Z

127

Sensitivity and uncertainty analysis applied to the JHR reactivity prediction  

SciTech Connect

The on-going AMMON program in EOLE reactor at CEA Cadarache (France) provides experimental results to qualify the HORUS-3D/N neutronics calculation scheme used for the design and safety studies of the new Material Testing Jules Horowitz Reactor (JHR). This paper presents the determination of technological and nuclear data uncertainties on the core reactivity and the propagation of the latter from the AMMON experiment to JHR. The technological uncertainty propagation was performed with a direct perturbation methodology using the 3D French stochastic code TRIPOLI4 and a statistical methodology using the 2D French deterministic code APOLLO2-MOC which leads to a value of 289 pcm (1{sigma}). The Nuclear Data uncertainty propagation relies on a sensitivity study on the main isotopes and the use of a retroactive marginalization method applied to the JEFF 3.1.1 {sup 27}Al evaluation in order to obtain a realistic multi-group covariance matrix associated with the considered evaluation. This nuclear data uncertainty propagation leads to a K{sub eff} uncertainty of 624 pcm for the JHR core and 684 pcm for the AMMON reference configuration core. Finally, transposition and reduction of the prior uncertainty were made using the Representativity method which demonstrates the similarity of the AMMON experiment with JHR (the representativity factor is 0.95). The final impact of JEFF 3.1.1 nuclear data on the Begin Of Life (BOL) JHR reactivity calculated by the HORUS-3D/N V4.0 is a bias of +216 pcm with an associated posterior uncertainty of 304 pcm (1{sigma}). (authors)

Leray, O.; Vaglio-Gaudard, C.; Hudelot, J. P.; Santamarina, A.; Noguere, G. [CEA, DER, SPRC, F-13108 St Paul-Lez-Durance (France); Di-Salvo, J. [CEA, DER, SPEx, F-13108 St Paul-Lez-Durance (France)

2012-07-01T23:59:59.000Z

128

Fuzzy-algebra uncertainty analysis for abnormal-environment safety assessment  

Science Conference Proceedings (OSTI)

Many safety (risk) analyses depend on uncertain inputs and on mathematical models chosen from various alternatives, but give fixed results (implying no uncertainty). Conventional uncertainty analyses help, but are also based on assumptions and models, the accuracy of which may be difficult to assure. Some of the models and assumptions that on cursory examination seem reasonable can be misleading. As a result, quantitative assessments, even those accompanied by uncertainty measures, can give unwarranted impressions of accuracy. Since analysis results can be a major contributor to a safety-measure decision process, risk management depends on relating uncertainty to only the information available. The uncertainties due to abnormal environments are even more challenging than those in normal-environment safety assessments, and therefore require an even more cautious approach. A fuzzy algebra analysis is proposed in this report that has the potential to appropriately reflect the information available and portray uncertainties well, especially for abnormal environments.

Cooper, J.A.

1994-01-01T23:59:59.000Z

129

Uncertainty Analysis of RELAP5-3D  

SciTech Connect

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

Alexandra E Gertman; Dr. George L Mesina

2012-07-01T23:59:59.000Z

130

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

SciTech Connect

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.

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

1995-01-01T23:59:59.000Z

131

Analysis of the lumped fission-product uncertainty in CRBR  

Science Conference Proceedings (OSTI)

An approximation made in most fast reactor analyses is to utilize a single lumped fission product (FP) cross-section set to represent the total effect of the approximately 800 possible fission product nuclides in a depleted reactor model. Recent investigations have analyzed several aspects of this one-lump approximation (burnup dependence, comparison with a two-lump model, etc.), but little has been done in addressing the quality, or uncertainty, in the basic cross-section data utilized in any such representation. Thus, the purpose of this study is to investigate the uncertainty in the FP reactivity effect due to the data uncertainties inherent in an ENDF/B-V composite FP representation specifically designed for application with the current CRBR heterogeneous core concept.

White, J.R.; Schenter, R.E.

1981-01-01T23:59:59.000Z

132

Modified Phenomena Identification and Ranking Table (PIRT) for Uncertainty Analysis  

SciTech Connect

This paper describes a methodology of characterizing important phenomena, which is also part of a broader research by the authors called 'Modified PIRT'. The methodology provides robust process of phenomena identification and ranking process for more precise quantification of uncertainty. It is a two-step process of identifying and ranking methodology based on thermal-hydraulics (TH) importance as well as uncertainty importance. Analytical Hierarchical Process (AHP) has been used for as a formal approach for TH identification and ranking. Formal uncertainty importance technique is used to estimate the degree of credibility of the TH model(s) used to represent the important phenomena. This part uses subjective justification by evaluating available information and data from experiments, and code predictions. The proposed methodology was demonstrated by developing a PIRT for large break loss of coolant accident LBLOCA for the LOFT integral facility with highest core power (test LB-1). (authors)

Gol-Mohamad, Mohammad P.; Modarres, Mohammad; Mosleh, Ali [University of Maryland, College Park, MD 20742 (United States)

2006-07-01T23:59:59.000Z

133

Gasoline Prices  

NLE Websites -- All DOE Office Websites (Extended Search)

Gasoline Prices Gasoline Price Data Sign showing gasoline prices Local Prices: Find the cheapest gasoline prices in your area. State & Metro Area Prices: Average prices from AAA's...

134

System analysis approach for the identification of factors driving crude oil prices  

Science Conference Proceedings (OSTI)

A system analysis approach is proposed to identify the main factors driving international crude oil prices by integrating a partial least squares model, an vector error correction model and the directed acyclic graph method. The different mechanisms ... Keywords: Crude oil price, DAG, Driving factors, Financial crisis, VECM

Qiang Ji

2012-11-01T23:59:59.000Z

135

Environmental Energy Technologies Division Energy Analysis Department Managing Natural Gas Price  

E-Print Network (OSTI)

-fired generation contracts 2) Reduces Natural Gas Prices: Increased RE reduces natural gas demand, and consequently Quantity Q0 P0 P1 Q1 Original Demand ShiftedDemandq Theory: Increased use of RE will reduce natural gasEnvironmental Energy Technologies Division · Energy Analysis Department Managing Natural Gas Price

136

Tariff-based analysis of commercial building electricity prices  

E-Print Network (OSTI)

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

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

2008-01-01T23:59:59.000Z

137

Utility green pricing programs: A statistical analysis of program effectiveness  

E-Print Network (OSTI)

Bird, L. , Swezey, B. 2003. Green Power Marketing in theR. , Aabakken, J. 2002. Green Power Marketing Abroad: RecentHolt, E. , Holt, M. 2004. Green Pricing Resource Guide.

Wiser, Ryan; Olson, Scott; Bird, Lori; Swezey, Blair

2004-01-01T23:59:59.000Z

138

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

Science Conference Proceedings (OSTI)

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.

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

2006-06-01T23:59:59.000Z

139

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

Science Conference Proceedings (OSTI)

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.

United States. Bonneville Power Administration.

2006-07-01T23:59:59.000Z

140

An Analysis of Price Determination and Markups in the Air-Conditioning...  

NLE Websites -- All DOE Office Websites (Extended Search)

An Analysis of Price Determination and Markups in the Air-Conditioning and Heating Equipment Industry NOTICE Due to the current lapse of federal funding, Berkeley Lab websites are...

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
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141

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

DOE Green Energy (OSTI)

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.

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

2012-06-01T23:59:59.000Z

142

Bayesian Neural Networks for Uncertainty Analysis of Hydrologic Modeling: A Comparison of Two Schemes  

SciTech Connect

Bayesian Neural Networks (BNNs) have been shown as useful tools to analyze modeling uncertainty of Neural Networks (NNs). This research focuses on the comparison of two BNNs. The first BNNs (BNN-I) use statistical methods to describe the characteristics of different uncertainty sources (input, parameter, and model structure) and integrate these uncertainties into a Markov Chain Monte Carlo (MCMC) framework to estimate total uncertainty. The second BNNs (BNN-II) lump all uncertainties into a single error term (i.e. the residual between model prediction and measurement). In this study, we propose a simple BNN-II, which use Genetic Algorithms (GA) and Bayesian Model Averaging (BMA) to calibrate Neural Networks with different structures (number of hidden units) and combine the predictions from different NNs to derive predictions and uncertainty analysis. We tested these two BNNs in two watersheds for daily and monthly hydrologic simulation. The BMA based BNNs developed in this study outperforms BNN-I in the two watersheds in terms of both accurate prediction and uncertainty estimation. These results show that, given incomplete understanding of the characteristics associated with each uncertainty source, the simple lumped error approach may yield better prediction and uncertainty estimation.

Zhang, Xuesong; Zhao, Kaiguang

2012-06-01T23:59:59.000Z

143

Robust Bayesian Uncertainty Analysis of Climate System Properties Using Markov Chain Monte Carlo Methods  

Science Conference Proceedings (OSTI)

A Bayesian uncertainty analysis of 12 parameters of the Bern2.5D climate model is presented. This includes an extensive sensitivity study with respect to the major statistical assumptions. Special attention is given to the parameter representing ...

Lorenzo Tomassini; Peter Reichert; Reto Knutti; Thomas F. Stocker; Mark E. Borsuk

2007-04-01T23:59:59.000Z

144

Direct Aerosol Radiative Forcing Uncertainty Based on a Radiative Perturbation Analysis  

Science Conference Proceedings (OSTI)

To provide a lower bound for the uncertainty in measurement-based clear- and all-sky direct aerosol radiative forcing (DARF), a radiative perturbation analysis is performed for the ideal case in which the perturbations in global mean aerosol ...

Norman G. Loeb; Wenying Su

2010-10-01T23:59:59.000Z

145

The Impact of Technical Analysis on Asset Price Dynamics  

E-Print Network (OSTI)

vectors: 0=gl , where ( ) )1(11 1,,...,, +´-= MMM llll , and 1)1( 1 1 ´+* - ÷ ÷ ÷ ø ö çç ç è æ ¶ ¶-= MQ t t Q qg . Using the normalised price given by (20), the 1´M sub-vector in g becomes *1*1*1*1 )0()()( Qt q t Qt q tq t Qt q t Qt...

Yang, J-H Steffi; Satchell, Stephen E

2004-06-16T23:59:59.000Z

146

PROBABILISTIC SENSITIVITY AND UNCERTAINTY ANALYSIS WORKSHOP SUMMARY REPORT  

SciTech Connect

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.

Seitz, R

2008-06-25T23:59:59.000Z

147

Video Scanning Hartmann Optical Tester (VSHOT) Uncertainty Analysis: Preprint  

DOE Green Energy (OSTI)

This purely analytical work is based primarily on the geometric optics of the system and shows sensitivities to various design and operational parameters. We discuss sources of error with measuring devices, instrument calibrations, and operator measurements for a parabolic trough test. In this paper, we include both the random (precision) and systematic (bias) errors for VSHOT testing and their contributions to the uncertainty. The contributing factors that we considered in this study are target tilt, target face to laser output distance, instrument vertical offset, scanner tilt, distance between the tool and the test piece, camera calibration, and scanner/calibration.

Lewandowski, A.; Gray, A.

2010-10-01T23:59:59.000Z

148

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

Science Conference Proceedings (OSTI)

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.

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

2001-11-09T23:59:59.000Z

149

Rising House Prices and Monetary Policy  

E-Print Network (OSTI)

Abstract. It is argued that the recent rise in house prices is the biggest …nancial asset price boom in history. In this note, I look at how house prices are determined and how house price bubbles can occur. I discuss whether the recent increase in house prices is a bubble, whether monetary policy can cause a rise in the price of houses relative to other goods and what central banks should do in response to house price bubbles. Finally, I consider how central banks should take account of house prices in the price index used by central banks to measure in‡ation. According to the Economist, the rise in housing prices in developed countries in the last …ve years is the biggest bubble in history, with the total value of residential properties increasing by more than $30 trillion: an amount roughly equal to to developed countries combined annual GDPs. 1 This compares with the global stockmarket boom of the late 1990s where the …ve-year increase was equal to about 80 percent of annual GDP. 2 1. How are House Prices Determined? Before proceeding with an analysis of the relationship between monetary policy and the house price boom, it is useful to consider how house prices are determined and how a house price bubble might arise. To keep matters simple, I abstract from uncertainty, depreciation and transactions costs. Consider a household deciding whether to rent or to buy a house in period t. If the household rents the house it pays the time-t rent, denoted by Q(t). If it purchases the house it pays the time-t house price, denoted by Ph (t). If it opted to purchase, rather than rent, then at the start of period t + 1 the household owns a house worth Ph (t + 1): The value to the household in period t of an amount Ph (t + 1) received in period t + 1

Anne Sibert

2005-01-01T23:59:59.000Z

150

Uncertainties in Cancer Risk Coefficients for Environmental Exposure to Radionuclides. An Uncertainty Analysis for Risk Coefficients Reported in Federal Guidance Report No. 13  

Science Conference Proceedings (OSTI)

Federal Guidance Report No. 13 (FGR 13) provides risk coefficients for estimation of the risk of cancer due to low-level exposure to each of more than 800 radionuclides. Uncertainties in risk coefficients were quantified in FGR 13 for 33 cases (exposure to each of 11 radionuclides by each of three exposure pathways) on the basis of sensitivity analyses in which various combinations of plausible biokinetic, dosimetric, and radiation risk models were used to generate alternative risk coefficients. The present report updates the uncertainty analysis in FGR 13 for the cases of inhalation and ingestion of radionuclides and expands the analysis to all radionuclides addressed in that report. The analysis indicates that most risk coefficients for inhalation or ingestion of radionuclides are determined within a factor of 5 or less by current information. That is, application of alternate plausible biokinetic and dosimetric models and radiation risk models (based on the linear, no-threshold hypothesis with an adjustment for the dose and dose rate effectiveness factor) is unlikely to change these coefficients by more than a factor of 5. In this analysis the assessed uncertainty in the radiation risk model was found to be the main determinant of the uncertainty category for most risk coefficients, but conclusions concerning the relative contributions of risk and dose models to the total uncertainty in a risk coefficient may depend strongly on the method of assessing uncertainties in the risk model.

Pawel, David [U.S. Environmental Protection Agency; Leggett, Richard Wayne [ORNL; Eckerman, Keith F [ORNL; Nelson, Christopher [U.S. Environmental Protection Agency

2007-01-01T23:59:59.000Z

151

Uncertainty and Intercalibration Analysis of H*Wind  

Science Conference Proceedings (OSTI)

The Hurricane Research Division (HRD) Real-time Hurricane Wind Analysis System (H*Wind) is a software application used by NOAA’s HRD to create a gridded tropical cyclone wind analysis based on a wide range of observations. These analyses are used ...

Steven M. DiNapoli; Mark A. Bourassa; Mark D. Powell

2012-06-01T23:59:59.000Z

152

Lynn Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Lynn Price Lynn Price China Energy Group Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R2002 Berkeley CA 94720 Office Location: 90-2108 (510) 486-6519 LKPrice@lbl.gov Lynn Price is a Staff Scientist and Leader of the China Energy Group of the Energy Analysis and Environmental Impacts Department, Environmental Energy Technologies Division, of Lawrence Berkeley National Laboratory. Ms. Price has a MS in Environmental Science from the University of Wisconsin-Madison and has worked at LBNL since 1990. Ms. Price has been a member of the Intergovernmental Panel on Climate Change, which won the Nobel Peace Prize in 2007, since 1994 and was an author on the industrial sector chapter of IPCC's Fourth Assessment Report on Mitigation of Climate Change. Since 1999, Ms. Price has provided technical assistance to the Energy

153

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

SciTech Connect

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.

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

2012-11-01T23:59:59.000Z

154

Incorporating uncertainty in the Life Cycle Cost Analysis of pavements  

E-Print Network (OSTI)

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

Swei, Omar Abdullah

2012-01-01T23:59:59.000Z

155

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

Reports and Publications (EIA)

EIA introduced a monthly analysis of energy price volatility and forecast uncertainty inthe October 2009 Short-Term Energy Outlook (STEO). Included in the analysis werecharts 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.

Information Center

2010-04-01T23:59:59.000Z

156

Determining Price Reasonableness in Federal ESPCs  

SciTech Connect

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.

Shonder, J.A.

2005-03-08T23:59:59.000Z

157

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

SciTech Connect

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

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

2013-04-28T23:59:59.000Z

158

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

day • EP t : wholesale electricity price during day t (in $/Response under Uncertainty 2006 electricity price Simulatedsample path Electricity price ($/MWh e ) Day Figure 3:

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

159

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

Science Conference Proceedings (OSTI)

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

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

2010-08-15T23:59:59.000Z

160

An Analysis of the Price Elasticity of Demand for Household Appliances  

NLE Websites -- All DOE Office Websites (Extended Search)

the Price Elasticity of Demand for Household Appliances the Price Elasticity of Demand for Household Appliances Title An Analysis of the Price Elasticity of Demand for Household Appliances Publication Type Report LBNL Report Number LBNL-326E Year of Publication 2008 Authors Dale, Larry L., and Sydny K. Fujita Document Number LBNL-326E Pagination 19 Date Published 02/2008 Publisher Lawrence Berkeley National Laboratory City Berkeley Abstract This article summarizes our study of the price elasticity of demand1 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 chose to study this particular set of appliances because data for the elasticity calculation was more readily available for refrigerators, clothes washers, and dishwashers than for other appliances. We begin with a review of the 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 it over the past 20 years. We conclude with summary and interpretation of the results of our regression analysis and present estimates of the price elasticity of demand for the three appliances.

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Empirical analysis of the spot market implications of price-elastic demand  

E-Print Network (OSTI)

are exposed to real-time electricity prices, then they cansustained increases in the electricity price. Greater pricethe market-clearing electricity price. Indeed, the remaining

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

2004-01-01T23:59:59.000Z

162

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

E-Print Network (OSTI)

are exposed to real-time electricity prices, they can adjustCustomers Respond to Electricity Price Variability: A Studyhours lowers the electricity spot price and reduces needed

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

2008-01-01T23:59:59.000Z

163

Integrating fuzzy multicriteria analysis and uncertainty evaluation in life cycle assessment  

Science Conference Proceedings (OSTI)

The interpretation phase of Life Cycle Assessment (LCA) studies is often hampered by the number and the heterogeneity of impact assessment results as well as by the uncertainties arising from data, models and practitioner's choices. While decision-aiding ... Keywords: Electricity, Fuzzy sets, LCA, Life cycle assessment, Multicriteria analysis, NAIADE, Noise

Enrico Benetto; Christiane Dujet; Patrick Rousseaux

2008-12-01T23:59:59.000Z

164

Prices and Price Setting.  

E-Print Network (OSTI)

??This thesis studies price data and tries to unravel the underlying economic processes of why firms have chosen these prices. It focuses on three aspects… (more)

Faber, R.P.

2010-01-01T23:59:59.000Z

165

A Probabilistic Graphical Approach to Computing Electricity Price Duration Curves under Price and Quantity Competition.  

Science Conference Proceedings (OSTI)

The electricity price duration curve (EPDC) represents the probability distribution function of the electricity price considered as a random variable. The price uncertainty comes both from the demand side and the supply side, since the load varies continuously, ...

Pascal Michaillat; Shmuel Oren

2007-01-01T23:59:59.000Z

166

Impact of Eliminating Biofuels Production on US Gasoline Prices: An Equilibrium Analysis  

E-Print Network (OSTI)

Impact of Eliminating Biofuels Production on US Gasoline Prices: An Equilibrium Analysis Joshua to encourage biofuel production. Recent demands for reduced federal spending have increased scrutiny are employed in the US to encourage biofuel production and consumption. The Energy Independence and Security

167

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis- 2012  

Energy.gov (U.S. Department of Energy (DOE))

Report provides tables of present-value factors for use in the life-cycle cost analysis of capital investment projects for federal facilities. It also provides energy price indices based on the U.S. Department of Energy (DOE) forecasts from 2012 to 2042.

168

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

E-Print Network (OSTI)

used to adjust the real-time price perceived by end-useare exposed to real-time electricity prices, they can adjustof real-time pricing (RTP) on the equilibrium spot price and

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

2008-01-01T23:59:59.000Z

169

Empirical analysis of the spot market implications of price-elastic demand  

E-Print Network (OSTI)

used to adjust the real-time price perceived by end-useare exposed to real-time electricity prices, then they canof real-time pricing on the equilibrium spot price and

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

2004-01-01T23:59:59.000Z

170

Reduction of uncertainty using sensitivity analysis methods for infinite random sets of indexable type  

Science Conference Proceedings (OSTI)

In this paper we deal with the question ''which is the best way to spend our resources in order to decrease the width of the interval [Bel(F),Pl(F)] in Dempster-Shafer evidence theory?''. A solution based on sensitivity analysis techniques using the ... Keywords: Dempster--Shafer evidence theory, Hartley-like measure of nonspecificity, Random sets, Reduction of uncertainty, Sensitivity analysis

Diego A. Alvarez

2009-05-01T23:59:59.000Z

171

An Analysis of the Price Elasticity of Demand for Household Appliances  

NLE Websites -- All DOE Office Websites (Extended Search)

Analysis of the Price Elasticity of Demand for Analysis of the Price Elasticity of Demand for Household Appliances Larry Dale and K. Sydny Fujita February 2008 Energy Analysis Department Environmental Energy Technologies Division Lawrence Berkeley National Laboratory University of California Berkeley, CA 94720 DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not

172

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2010  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

5 5 (Rev. 5/10) Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2010 Annual Supplement to Amy S. Rushing NIST Handbook 135 and Joshua D. Kneifel NBS Special Publication 709 Barbara C. Lippiatt 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 May 2010 ENERGY PRICE INDICES AND DISCOUNT FACTORS FOR LIFE-CYCLE COST ANALYSIS Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 April 1, 2010 to March 31, 2011 Data for the Federal Methodology for Life-Cycle Cost Analysis, Title 10, CFR, Part 436, Subpart A; and for the Energy Conservation Mandatory Performance Standards for New Federal Residential Buildings,

173

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2011  

NLE Websites -- All DOE Office Websites (Extended Search)

April 2005 April 2005 NISTIR 85-3273-26 (Rev. 9/11) Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2011 Annual Supplement to Amy S. Rushing NIST Handbook 135 and Joshua D. Kneifel NBS Special Publication 709 Barbara C. Lippiatt U.S. DEPARTMENT OF COMMERCE Technology Administration National Institute of Standards and Technology Prepared for United States Department of Energy Federal Energy Management Program September 2011 NISTIR 85-3273-26 ENERGY PRICE INDICES AND DISCOUNT FACTORS FOR LIFE-CYCLE COST ANALYSIS Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 April 1, 2011 to March 31, 2012 Data for the Federal Methodology for Life-Cycle Cost Analysis, Title 10, CFR, Part 436, Subpart A; and for the Energy Conservation Mandatory Performance Standards for New Federal Residential Buildings,

174

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

E-Print Network (OSTI)

Oil Prices, Stock Markets and Portfolio Investment: Evidence from Sector Analysis in Europe over This article extends the understanding of oil­stock market relationships over the last turbulent decade. Unlike returns to oil price changes differ greatly depending on the activity sector. In the out

Paris-Sud XI, Université de

175

Adjoint-Based Uncertainty Quantification and Sensitivity Analysis for Reactor Depletion Calculations  

E-Print Network (OSTI)

Depletion calculations for nuclear reactors model the dynamic coupling between the material composition and neutron flux and help predict reactor performance and safety characteristics. In order to be trusted as reliable predictive tools and inputs to licensing and operational decisions, the simulations must include an accurate and holistic quantification of errors and uncertainties in its outputs. Uncertainty quantification is a formidable challenge in large, realistic reactor models because of the large number of unknowns and myriad sources of uncertainty and error. We present a framework for performing efficient uncertainty quantification in depletion problems using an adjoint approach, with emphasis on high-fidelity calculations using advanced massively parallel computing architectures. This approach calls for a solution to two systems of equations: (a) the forward, engineering system that models the reactor, and (b) the adjoint system, which is mathematically related to but different from the forward system. We use the solutions of these systems to produce sensitivity and error estimates at a cost that does not grow rapidly with the number of uncertain inputs. We present the framework in a general fashion and apply it to both the source-driven and k-eigenvalue forms of the depletion equations. We describe the implementation and verification of solvers for the forward and ad- joint equations in the PDT code, and we test the algorithms on realistic reactor analysis problems. We demonstrate a new approach for reducing the memory and I/O demands on the host machine, which can be overwhelming for typical adjoint algorithms. Our conclusion is that adjoint depletion calculations using full transport solutions are not only computationally tractable, they are the most attractive option for performing uncertainty quantification on high-fidelity reactor analysis problems.

Stripling, Hayes Franklin

2013-08-01T23:59:59.000Z

176

Uncertainty analysis for unprotected accidents in sodium-cooled fast reactors.  

SciTech Connect

Reactor safety analyses often utilize a deterministic approach where in addition to performing best estimate calculations, uncertainty is accommodated by performing calculations with pessimistic values for input parameters that are important to safety. Here, a stochastic approach is considered for explicitly including uncertainty in safety parameters by applying Monte Carlo sampling coupled with established deterministic reactor safety analysis tools. The Monte Carlo approach yields frequency distributions for reactor safety metrics (e.g., peak temperatures) that can be compared to performance limits, allowing for an improved determination of the safety margin and a clear determination of which safety parameters are most important to the transient response. Because the approach enables the estimation of probabilities for violating safety boundaries, it should be useful in a risk-based regulatory environment. It has the advantage of not requiring any substantial rewriting of existing safety analysis computer codes.

Nutt, W. M.; Morris, E. E. (Nuclear Engineering Division)

2011-04-01T23:59:59.000Z

177

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

Science Conference Proceedings (OSTI)

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.

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

1995-01-01T23:59:59.000Z

178

Uncertainty analysis of an IGCC system with single-stage entrained-flow gasifier  

Science Conference Proceedings (OSTI)

Integrated Gasification Combined Cycle (IGCC) systems using coal gasification is an attractive option for future energy plants. Consequenty, understanding the system operation and optimizing gasifier performance in the presence of uncertain operating conditions is essential to extract the maximum benefits from the system. This work focuses on conducting such a study using an IGCC process simulation and a high-fidelity gasifier simulation coupled with stochastic simulation and multi-objective optimization capabilities. Coal gasifiers are the necessary basis of IGCC systems, and hence effective modeling and uncertainty analysis of the gasification process constitutes an important element of overall IGCC process design and operation. In this work, an Aspen Plus{reg_sign} steady-state process model of an IGCC system with carbon capture enables us to conduct simulation studies so that the effect of gasification variability on the whole process can be understood. The IGCC plant design consists of an single-stage entrained-flow gasifier, a physical solvent-based acid gas removal process for carbon capture, two model-7FB combustion turbine generators, two heat recovery steam generators, and one steam turbine generator in a multi-shaft 2x2x1 configuration. In the Aspen Plus process simulation, the gasifier is represented as a simplified lumped-parameter, restricted-equilibrium reactor model. In this work, we also make use of a distributed-parameter FLUENT{reg_sign} computational fluid dynamics (CFD) model to characterize the uncertainty for the entrained-flow gasifier. The CFD-based gasifer model is much more comprehensive, predictive, and hence better suited to understand the effects of uncertainty. The possible uncertain parameters of the gasifier model are identified. This includes input coal composition as well as mass flow rates of coal, slurry water, and oxidant. Using a selected number of random (Monte Carlo) samples for the different parameters, the CFD model is simulated to observe the variations in the output variables (such as syngas composition, gas and ash flow rates etc.). The same samples are then used to conduct simulations using the Aspen Plus IGCC model. The simulation results for the high-fidelity CFD-based gasifier model and the Aspen Plus equilibrium reactor model for selected uncertain parameters are then used to perform the estimation. Defining the ratio of CFD based results to the Aspen Plus result as the uncertainty factor (UF), the work quantifies the extent of uncertainty and then uses uniform* distribution to characterize the uncertainty factor distribution. The characterization and quantification of uncertainty is then used to conduct stochastic simulation of the IGCC system in Aspen Plus. The CAPE-OPEN compliant stochastic simulation capability allows one to conduct a rigorous analysis and generate the feasible space for the operation of the IGCC system. The stochastic simulation results can later be used to conduct multi-objective optimization of the gasifier using a set of identified decision variables. The CAPE-OPEN compliant multi-objective capability in Aspen Plus can be used to conduct the analysis. Since the analysis is based on the uncertainty modeling studies of the gasifier, the optimization accounts for possible uncertainties in the operation of the system. The results for the optimized IGCC system and the gasifier, obtained from the stochastic simulation results, are expected to be more rigorous and hence closer to those obtained from CFD-based rigorous modeling.

Shastri, Y.; Diwekar, U.; Zitney, S.

2008-01-01T23:59:59.000Z

179

A Probabilistic Graphical Approach to Computing Electricity Price Duration Curves under Price and  

E-Print Network (OSTI)

A Probabilistic Graphical Approach to Computing Electricity Price Duration Curves under Price,oren}@ieor.berkeley.edu Abstract-- The electricity price duration curve (EPDC) repre- sents the probability distribution function of the electricity price considered as a random variable. The price uncertainty comes both from the demand side

Oren, Shmuel S.

180

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis-2013  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

8 8 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2013 Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 Amy S. Rushing Joshua D. Kneifel Barbara C. Lippiatt http://dx.doi.org/10.6028/NIST.IR.85-3273-28 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 85-3273-28 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2013 Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 Amy S. Rushing Joshua D. Kneifel Barbara C. Lippiatt Applied Economics Office Engineering Laboratory http://dx.doi.org/10.6028/NIST.IR.85-3273-28

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2012  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

7 7 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2012 Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 Amy S. Rushing Joshua D. Kneifel Barbara C. Lippiatt http://dx.doi.org/10.6028/NIST.IR.85-3273-27 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 85-3273-27 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2012 Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 Amy S. Rushing Joshua D. Kneifel Barbara C. Lippiatt Applied Economics Office Engineering Laboratory http://dx.doi.org/10.6028/NIST.IR.85-3273-27

182

An Analysis of the Price Elasticity of Demand for Household Appliances  

SciTech Connect

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.

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

2008-01-25T23:59:59.000Z

183

Nuclear data uncertainty analysis for the generation IV gas-cooled fast reactor  

Science Conference Proceedings (OSTI)

For the European 2400 MW Gas-cooled Fast Reactor (GoFastR), this paper summarizes a priori uncertainties, i.e. without any integral experiment assessment, of the main neutronic parameters which were obtained on the basis of the deterministic code system ERANOS (Edition 2.2-N). JEFF-3.1 cross-sections were used in conjunction with the newest ENDF/B-VII.0 based covariance library (COMMARA-2.0) resulting from a recent cooperation of the Brookhaven and Los Alamos National Laboratories within the Advanced Fuel Cycle Initiative. The basis for the analysis is the original GoFastR concept with carbide fuel pins and silicon-carbide ceramic cladding, which was developed and proposed in the first quarter of 2009 by the 'French alternative energies and Atomic Energy Commission', CEA. The main conclusions from the current study are that nuclear data uncertainties of neutronic parameters may still be too large for this Generation IV reactor, especially concerning the multiplication factor, despite the fact that the new covariance library is quite complete; These uncertainties, in relative terms, do not show the a priori expected increase with bum-up as a result of the minor actinide and fission product build-up. Indeed, they are found almost independent of the fuel depletion, since the uncertainty associated with {sup 238}U inelastic scattering results largely dominating. This finding clearly supports the activities of Subgroup 33 of the Working Party on International Nuclear Data Evaluation Cooperation (WPEC), i.e. Methods and issues for the combined use of integral experiments and covariance data, attempting to reduce the present unbiased uncertainties on nuclear data through adjustments based on available experimental data. (authors)

Pelloni, S.; Mikityuk, K. [Paul Scherrer Inst., 5232 Villigen PSI (Switzerland)

2012-07-01T23:59:59.000Z

184

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

SciTech Connect

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.

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

2005-05-11T23:59:59.000Z

185

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

NLE Websites -- All DOE Office Websites (Extended Search)

Energy Markets and Policy Group * Energy Analysis Department Energy Markets and Policy Group * Energy Analysis Department An Analysis of the Effects of Residential Photovoltaic Energy Systems on Home Sales Prices in California Ben Hoen, Peter Cappers, Mark Thayer, Ryan Wiser Lawrence Berkeley National Laboratory LBNL Webinar June 9 th , 2011 This work was supported by the Office of Energy Efficiency and Renewable Energy (Solar Energy Technologies Program) of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, by the National Renewable Energy Laboratory under Contract No. DEK-8883050, and by the Clean Energy States Alliance.

186

Investment and Upgrade in Distributed Generation under Uncertainty  

E-Print Network (OSTI)

of the uncertainty in the natural gas price. Treat- ment ofits exposure to risk from natural gas price volatility. Inits exposure to the natural gas price and maximising its

Siddiqui, Afzal

2008-01-01T23:59:59.000Z

187

Investment and Upgrade in Distributed Generation under Uncertainty  

E-Print Network (OSTI)

in the natural gas price. Treat- ment of uncertainty viato risk from natural gas price volatility. In particular,exposure to the natural gas price and maximising its cost

Siddiqui, Afzal

2008-01-01T23:59:59.000Z

188

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

E-Print Network (OSTI)

in residential selling prices as PV systems increase inhas an effect on the sale price of PV homes (i.e. , a fixedcomparable” homes, sales prices of PV homes are “compared”

Hoen, Ben

2011-01-01T23:59:59.000Z

189

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

E-Print Network (OSTI)

has an effect on the sale price of PV homes (i.e. , a fixedcomparable” homes, sales prices of PV homes are “ compared”difference in home prices between PV and non- PV homes prior

Cappers, Peter

2012-01-01T23:59:59.000Z

190

An Analysis of the Price Elasticity of Demand for Household Appliances  

E-Print Network (OSTI)

D. and R. Rao. Effect of Price on the Demand for Durables:1997 Tellis, G. The Price Elasticity of Selective Demand: A1997 4 G. Tellis. "The Price Elasticity of Selective Demand:

Dale, Larry

2008-01-01T23:59:59.000Z

191

Resort real estate : an economic analysis of second come pricing behavior in Park City, Utah  

E-Print Network (OSTI)

The purpose of this research project is to examine the market pricing behavior of vacation homes in resort property markets. To accomplish this a price index is constructed to track real price fluctuations from 1981 to ...

Larsen, Brady W

2010-01-01T23:59:59.000Z

192

Competition and Prices in the Deregulated Gas Pipeline Network: A Multivariate Cointegration Analysis  

E-Print Network (OSTI)

in the long run. For example, gas prices stochastically inin this paper to anMyzenatural gas prices in the deregulatedthat all of the natural gas price series analyzed are I(1).

Walls, W. David

1993-01-01T23:59:59.000Z

193

Own-price and income elasticities for household electricity demand : a survey of literature using meta-regression analysis.  

E-Print Network (OSTI)

??Maria Wist Langmoen Own-price and income elasticities for household electricity demand -A Literature survey using meta-regression analysis Economists have been modelling the electricity demand for… (more)

Langmoen, Maria Wist

2004-01-01T23:59:59.000Z

194

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

Science Conference Proceedings (OSTI)

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.

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

1995-02-01T23:59:59.000Z

195

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

E-Print Network (OSTI)

Analysts increasingly have used probabilistic approaches to evaluate the uncertainty in reserves estimates based on a decline curve analysis. This is because the results represent statistical analysis of historical data that usually possess significant amounts of noise. Probabilistic approaches usually provide a distribution of reserves estimates with three confidence levels (P10, P50 and P90) and a corresponding 80% confidence interval. The question arises: how reliable is this 80% confidence interval? In other words, in a large set of analyses, is the true value of reserves contained within this interval 80% of the time? Our investigation indicates that it is common in practice for true values of reserves to lie outside the 80% confidence interval much more than 20% of the time using traditional statistical analyses. This indicates that uncertainty is being underestimated, often significantly. Thus, the challenge in probabilistic reserves estimation using a decline curve analysis is not only how to appropriately characterize probabilistic properties of complex production data sets, but also how to determine and then improve the reliability of the uncertainty quantifications. This thesis presents an improved methodology for probabilistic quantification of reserves estimates using a decline curve analysis and practical application of the methodology to actual individual well decline curves. The application of our proposed new method to 100 oil and gas wells demonstrates that it provides much wider 80% confidence intervals, which contain the true values approximately 80% of the time. In addition, the method yields more accurate P50 values than previously published methods. Thus, the new methodology provides more reliable probabilistic reserves estimation, which has important impacts on economic risk analysis and reservoir management.

Wang, Yuhong

2003-05-01T23:59:59.000Z

196

The impact of uncertainty and risk measures  

E-Print Network (OSTI)

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

Jo, Soojin; Jo, Soojin

2012-01-01T23:59:59.000Z

197

Probabilistic accident consequence uncertainty analysis -- Late health effects uncertain assessment. Volume 2: Appendices  

SciTech Connect

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 late health effects models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the expert panel on late health effects, (4) short biographies of the experts, and (5) the aggregated results of their responses.

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

1997-12-01T23:59:59.000Z

198

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

SciTech Connect

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.

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

2011-09-01T23:59:59.000Z

199

DRAFT DO NOT QUOTE Energy Prices and Energy Intensity in China: A Structural Decomposition Analysis and Econometrics Study  

E-Print Network (OSTI)

Since the start of its economic reforms in 1978, China's energy prices relative to other prices have increased. At the same time, its energy intensity, i.e., energy consumption per unit of Gross Domestic Product (GDP), has declined dramatically, by about 70%, in spite of increases in energy consumption. Is this just a coincidence? Or does a systematic relationship exist between energy prices and energy intensity? In this study, we examine whether and how China’s energy price changes affect its energy intensity trend during 1980-2002 at a macro level. We conduct the research by using two complementary economic models: the input-output-based structural decomposition analysis (SDA) and econometric regression models and by using a decomposition method of own-price elasticity of energy intensity. Findings include a negative own-price elasticity of energy intensity, a price-inducement effect on energyefficiency improvement, and a greater sensitivity (in terms of the reaction of energy intensity towards changes in energy prices) of the industry sector, compared to the overall economy. Analysts can use these results as a starting point for China's energy and carbon

Xiaoyu Shi; Karen R. Polenske; Xiaoyu Shi; Karen R. Polenske

2005-01-01T23:59:59.000Z

200

Perspectives Gained in an Evaluation of Uncertainty, Sensitivity, and Decision Analysis Software  

SciTech Connect

The following software packages for uncertainty, sensitivity, and decision analysis were reviewed and also tested with several simple analysis problems: Crystal Ball, RiskQ, SUSA-PC, Analytica, PRISM, Ithink, Stella, LHS, STEPWISE, and JMP. Results from the review and test problems are presented. The study resulted in the recognition of the importance of four considerations in the selection of a software package: (1) the availability of an appropriate selection of distributions, (2) the ease with which data flows through the input sampling, model evaluation, and output analysis process, (3) the type of models that can be incorporated into the analysis process, and (4) the level of confidence in the software modeling and results.

Davis, F.J.; Helton, J.C.

1999-02-24T23:59:59.000Z

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

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

Science Conference Proceedings (OSTI)

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.

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

1995-01-01T23:59:59.000Z

202

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

Science Conference Proceedings (OSTI)

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.

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

1995-01-01T23:59:59.000Z

203

A New Hybrid Approach for Analysis of Factors Affecting Crude Oil Price  

Science Conference Proceedings (OSTI)

In this paper, a new hybrid approach is presented to analyze factors affecting crude oil price using rough set and wavelet neural network. Related factors that affect crude oil price are found using text mining technique and Brent oil price is chosen ... Keywords: crude oil price, prediction, rough set, wavelet neural network

Wei Xu; Jue Wang; Xun Zhang; Wen Zhang; Shouyang Wang

2007-05-01T23:59:59.000Z

204

Evaluating the role of uncertainty in electric utility capacity planning  

SciTech Connect

This final report on Evaluating the Role of Uncertainty in Electric Utility Capacity Planning is divided into separate sections addressing demand, supply and the simultaneous consideration of both and describes several mathematical characterizations of the effects of uncertainty on the capacity expansion decision. The basic objective is to develop more robust models which can appropriately include the fundamental uncertainties associated with capacity expansion planning in the electric utility industry. Much of what has been developed in this project has been incorporated into a long-term, computer model for capacity expansion planning. A review is provided of certain deterministic capacity expansion methodologies. The effect of load curve uncertainty on capacity planning is considered and the use of a certain expected load curve to account for uncertainty in demand is proposed. How uncertainty influences the allocation of capital costs among the various load curve realizations is also discussed. The supply side uncertainties of fuel prices and random availability of generating units are considered. In certain cases it is shown that the use of the expected fuel costs will furnish a solution which minimizes the total expected costs. The effect of derating units to account for their random availability is also characterized. A stochastic linear program formulated to examine the simultaneous consideration of fuel cost and demand uncertainties is analyzed. This volume includes the report text one appendix with information on linear programming-based analysis of marginal cost pricing in the electric utility industry.

Soyster, A.L.

1981-08-31T23:59:59.000Z

205

Stochastic modelling of landfill leachate and biogas production incorporating waste heterogeneity. Model formulation and uncertainty analysis  

Science Conference Proceedings (OSTI)

A mathematical model simulating the hydrological and biochemical processes occurring in landfilled waste is presented and demonstrated. The model combines biochemical and hydrological models into an integrated representation of the landfill environment. Waste decomposition is modelled using traditional biochemical waste decomposition pathways combined with a simplified methodology for representing the rate of decomposition. Water flow through the waste is represented using a statistical velocity model capable of representing the effects of waste heterogeneity on leachate flow through the waste. Given the limitations in data capture from landfill sites, significant emphasis is placed on improving parameter identification and reducing parameter requirements. A sensitivity analysis is performed, highlighting the model's response to changes in input variables. A model test run is also presented, demonstrating the model capabilities. A parameter perturbation model sensitivity analysis was also performed. This has been able to show that although the model is sensitive to certain key parameters, its overall intuitive response provides a good basis for making reasonable predictions of the future state of the landfill system. Finally, due to the high uncertainty associated with landfill data, a tool for handling input data uncertainty is incorporated in the model's structure. It is concluded that the model can be used as a reasonable tool for modelling landfill processes and that further work should be undertaken to assess the model's performance.

Zacharof, A.I.; Butler, A.P

2004-07-01T23:59:59.000Z

206

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

SciTech Connect

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

United States. Bonneville Power Administration.

2005-11-01T23:59:59.000Z

207

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 1231 Reserves...

208

Do Producer Prices Lead Consumer Prices?  

E-Print Network (OSTI)

increased rapidly. Excluding food and energy, prices of crude materials and intermediate goods rose at annual rates of 7.2 and 16.7 percent, respectively. At the same time, however, prices of consumer goods and services excluding food and energy increased a more modest 2.9 percent. Many analysts are concerned that recent increases in the prices of crude and intermediate goods may be passed through to consumers, resulting in a higher rate of inflation in consumer prices later this year and perhaps in 1996. This article examines whether price increases at the early stages of production should be expected to move through the production chain, leading to increases in consumer prices. In the first section, a review of basic economic theory suggests there should be a pass-through effect—that is, producer prices should lead and thereby help predict consumer prices. A more sophisticated analysis, though, suggests the pass-through effect may be weak. In the second section, an examination of the empirical evidence indicates that producer prices are not always good predictors of consumer prices. The article Todd E. Clark is an economist at the Federal Reserve Bank of Kansas City. Mangal Goswami, a research associate at the bank, helped prepare the article. concludes that the recent increases in some producer prices do not necessarily signal higher inflation.

E. Clark

1994-01-01T23:59:59.000Z

209

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

Science Conference Proceedings (OSTI)

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

Atkinson, R.

2012-07-31T23:59:59.000Z

210

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

E-Print Network (OSTI)

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

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

2005-01-01T23:59:59.000Z

211

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

E-Print Network (OSTI)

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

Shi, Xiaoyu

2006-01-01T23:59:59.000Z

212

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

E-Print Network (OSTI)

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

Dolan, Amelia Jane

2011-01-01T23:59:59.000Z

213

Report on INL Activities for Uncertainty Reduction Analysis of FY11  

SciTech Connect

This report presents the status of activities performed at INL under the ARC Work Package on 'Uncertainty Reduction Analyses' that has a main goal the reduction of uncertainties associated with nuclear data on neutronic integral parameters of interest for the design of advanced fast reactors under consideration by the ARC program. First, an analysis of experiments was carried out. For both JOYO (the first Japanese fast reactor) and ZPPR-9 (a large size zero power plutonium fueled experiment performed at ANL-W in Idaho) the performance of ENDF/B-VII.0 is quite satisfying except for the sodium void configurations of ZPPR-9, but for which one has to take into account the approximation of the modeling. In fact, when one uses a more detailed model (calculations performed at ANL in a companion WP) more reasonable results are obtained. A large effort was devoted to the analysis of the irradiation experiments, PROFIL-1 and -2 and TRAPU, performed at the French fast reactor PHENIX. For these experiments a pre-release of the ENDF/B-VII.1 cross section files was also used, in order to provide validation feedback to the CSWEG nuclear data evaluation community. In the PROFIL experiments improvements can be observed for the ENDF/B-VII.1 capture data in 238Pu, 241Am, 244Cm, 97Mo, 151Sm, 153Eu, and for 240Pu(n,2n). On the other hand, 240,242Pu, 95Mo, 133Cs and 145Nd capture C/E results are worse. For the major actinides 235U and especially 239Pu capture C/E's are underestimated. For fission products, 105,106Pd, 143,144Nd and 147,149Sm are significantly underestimated, while 101Ru and 151Sm are overestimated. Other C/E deviations from unity are within the combined experimental and calculated statistical uncertainty. From the TRAPU analysis, the major improvement is in the predicted 243Cm build-up, presumably due to an improved 242Cm capture evaluation. The COSMO experiment was also analyzed in order to provide useful feedback on fission cross sections. It was found out that ENDF/B-VII.1 238,240Pu fission cross sections have improved with respect to VII.0 files while 242Pu's fission cross section has not.

G. Plamiotti; H. Hiruta; M. Salvatores

2011-09-01T23:59:59.000Z

214

Firm Size Transmission Effect and Price-Volume Relationship Analysis During Financial Tsunami Periods  

Science Conference Proceedings (OSTI)

Investors attend importance to forecast the price of financial assets, thus, the factors affecting the stock price are usually the focus of financial research in the field, in which the most important factors to scholars are firm size transmission effect ... Keywords: Cointegration Test, Firm Size Transmission Effect, Granger-Causality Test, Price-Volume Relationship, Unit Root Test

Wei-Chiang Samuelson Hong; Shih-Yung Wei; Kai Wang

2011-07-01T23:59:59.000Z

215

Empirical Analysis of Metering Price Discrimination: Evidence from Concession Sales at Movie Theaters  

Science Conference Proceedings (OSTI)

Prices for goods such as blades for razors, ink for printers, and concessions at movies are often set well above cost. Theory has shown that this could yield a profitable price discrimination strategy often termed “metering.” The idea is ... Keywords: concession sales, empirical industrial organization, entertainment, metering, movie theaters, price discrimination

Ricard Gil; Wesley R. Hartmann

2009-11-01T23:59:59.000Z

216

The Analysis on the Sensitivity of Steel Enterprise to Iron Ore Price  

Science Conference Proceedings (OSTI)

In order to analyze the different influences on Chinese domestic and abroad steel enterprises from a rise in material prices, this paper mainly researches on the sensitivity of major steel companies' cost to iron ore price and coke price. It applys sensitivity ... Keywords: sensitivity, panel data model, steel enterprises

Yingming Mao; Han Qiao

2011-10-01T23:59:59.000Z

217

The Fundamentals of Locational Marginal Pricing (LMP): Examples of Pricing Outcomes on the PJM System  

Science Conference Proceedings (OSTI)

As power industry restructuring continues, more and more industry participants will be exposed to financial uncertainties created by locational marginal pricing. These uncertainties differ from those experienced under traditional regulation as well as from the resource adequacy-related price spikes experienced in the Midwest in 1998 and in the West during 2000-2001. Instead, locational marginal pricing systems create uncertainty in the cost of transporting power from resources to loads. This report will ...

2003-12-15T23:59:59.000Z

218

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

SciTech Connect

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

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

2011-04-12T23:59:59.000Z

219

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

Science Conference Proceedings (OSTI)

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.

Oladosu, Gbadebo A [ORNL

2009-01-01T23:59:59.000Z

220

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

SciTech Connect

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

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

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

An inquiry into the potential of scenario analysis for dealing with uncertainty in strategic environmental assessment in China  

SciTech Connect

Strategic environmental assessment (SEA) inherently needs to address greater levels of uncertainty in the formulation and implementation processes of strategic decisions, compared with project environmental impact assessment. The range of uncertainties includes internal and external factors of the complex system that is concerned in the strategy. Scenario analysis is increasingly being used to cope with uncertainty in SEA. Following a brief introduction of scenarios and scenario analysis, this paper examines the rationale for scenario analysis in SEA in the context of China. The state of the art associated with scenario analysis applied to SEA in China was reviewed through four SEA case analyses. Lessons learned from these cases indicated the word 'scenario' appears to be abused and the scenario-based methods appear to be misused due to the lack of understanding of an uncertain future and scenario analysis. However, good experiences were also drawn on, regarding how to integrate scenario analysis into the SEA process in China, how to cope with driving forces including uncertainties, how to combine qualitative scenario storylines with quantitative impact predictions, and how to conduct assessments and propose recommendations based on scenarios. Additionally, the ways to improve the application of this tool in SEA were suggested. We concluded by calling for further methodological research on this issue and more practices.

Zhu Zhixi, E-mail: zhuzhixi@gmail.com; Bai, Hongtao, E-mail: bahonta@gmail.com; Xu He, E-mail: seacenter@nankai.edu.cn; Zhu Tan, E-mail: zhutan@nankai.edu.cn

2011-11-15T23:59:59.000Z

222

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

SciTech Connect

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.

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

2011-12-01T23:59:59.000Z

223

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

NLE Websites -- All DOE Office Websites (Extended Search)

4476E 4476E An Analysis of the Effects of Residential Photovoltaic Energy Systems on Home Sales Prices in California Ben Hoen, Ryan Wiser, Peter Cappers and Mark Thayer Environmental Energy Technologies Division April 2011 Download from http://eetd.lbl.gov/ea/emp/reports/lbnl-4476e.pdf This work was supported by the Office of Energy Efficiency and Renewable Energy (Solar Energy Technologies Program) of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, by the National Renewable Energy Laboratory under Contract No. DEK-8883050, and by the Clean Energy States Alliance. ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Disclaimer This document was prepared as an account of work sponsored by the United States Government.

224

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

DOE Green Energy (OSTI)

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

Emery, K.

2009-08-01T23:59:59.000Z

225

Using Decline Curve Analysis, Volumetric Analysis, and Bayesian Methodology to Quantify Uncertainty in Shale Gas Reserve Estimates  

E-Print Network (OSTI)

Probabilistic decline curve analysis (PDCA) methods have been developed to quantify uncertainty in production forecasts and reserves estimates. However, the application of PDCA in shale gas reservoirs is relatively new. Limited work has been done on the performance of PDCA methods when the available production data are limited. In addition, PDCA methods have often been coupled with Arp’s equations, which might not be the optimum decline curve analysis model (DCA) to use, as new DCA models for shale reservoirs have been developed. Also, decline curve methods are based on production data only and do not by themselves incorporate other types of information, such as volumetric data. My research objective was to integrate volumetric information with PDCA methods and DCA models to reliably quantify the uncertainty in production forecasts from hydraulically fractured horizontal shale gas wells, regardless of the stage of depletion. In this work, hindcasts of multiple DCA models coupled to different probabilistic methods were performed to determine the reliability of the probabilistic DCA methods. In a hindcast, only a portion of the historical data is matched; predictions are made for the remainder of the historical period and compared to the actual historical production. Most of the DCA models were well calibrated visually when used with an appropriate probabilistic method, regardless of the amount of production data available to match. Volumetric assessments, used as prior information, were incorporated to further enhance the calibration of production forecasts and reserves estimates when using the Markov Chain Monte Carlo (MCMC) as the PDCA method and the logistic growth DCA model. The proposed combination of the MCMC PDCA method, the logistic growth DCA model, and use of volumetric data provides an integrated procedure to reliably quantify the uncertainty in production forecasts and reserves estimates in shale gas reservoirs. Reliable quantification of uncertainty should yield more reliable expected values of reserves estimates, as well as more reliable assessment of upside and downside potential. This can be particularly valuable early in the development of a play, because decisions regarding continued development are based to a large degree on production forecasts and reserves estimates for early wells in the play.

Gonzalez Jimenez, Raul 1988-

2012-12-01T23:59:59.000Z

226

High Electricity Prices  

E-Print Network (OSTI)

Generators supplying electricity markets are subject to volatile input and output prices and uncertain fuel availability. Price-risk may be hedged to a considerable extent but fuel-risk — water flows in the case of hydro and gas availability in the case of thermal plants — may not be. We show that a price-taking generator will only generate when the output price exceeds its marginal cost by an amount that reflects the value of the option to delay the use of stored fuel. The corresponding offer price is different from the theorized offer prices of static uniform auctions and more akin to pay-as-bid auction prices. We argue that the option value of delaying fuel use, which is an increasing function of spot price volatility and the uncertainty about fuel availability, must be considered when evaluating whether market power is present in electricity markets. The engineering approach to simulating an electricity supply curve, which has been used in market power evaluations to date, may lead to supply curves that are quite different from those that recognize possible fuel availability limitations, even in the complete absence of market power.

Kevin Counsell; Graeme Guthrie; Steen Videbeck

2006-01-01T23:59:59.000Z

227

Phillip Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Phillip Price Phil Price Sustainable Energy Systems Group Demand Response Research Center (DRRC) Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R2002 Berkeley CA 94720...

228

Gasoline Prices  

NLE Websites -- All DOE Office Websites (Extended Search)

and diesel price estimates from the Energy Information Administration Understanding Gas Prices Photo of gasoline receipt What determines the cost of gasoline? What's the...

229

Levy process-driven mean-reverting electricity price model: the marginal distribution analysis  

Science Conference Proceedings (OSTI)

We propose a class of stochastic mean-reverting models for electricity prices with Levy process-driven Ornstein-Uhlenbeck (OU) processes being the building blocks. We first fit marginal distributions of power price series to two special classes of distributions ... Keywords: Correlation structure, Electricity market signals, Electricity option pricing, Heavy-tail, Levy process, Ornstein-Uhlenbeck type process, Risk management, Unbalanced-tail

Shi-Jie Deng; Wenjiang Jiang

2005-10-01T23:59:59.000Z

230

Electricity Prices in a Competitive Environment: Marginal Cost Pricing  

Reports and Publications (EIA)

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?

Information Center

1997-08-01T23:59:59.000Z

231

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

SciTech Connect

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

Nakos, James Thomas

2005-12-01T23:59:59.000Z

232

Empirical Analysis of the Spot Market Implications of Price-Elastic...  

NLE Websites -- All DOE Office Websites (Extended Search)

absence of any significant, rapid demand-side response to the wholesale (or, spot market) price. For a variety of reasons, electricity industries continue to charge most consumers...

233

Modeling and Analysis of Price-Responsive Loads in the Operation of Smart Grids.  

E-Print Network (OSTI)

??In this thesis, a demand elasticity model is developed and tested for the dispatch of high voltage power systems and microgrids. The price obtained from… (more)

Ramos-Gaete, Felipe

2013-01-01T23:59:59.000Z

234

Restaurant Industry Stock Price Forecasting Model Utilizing Artificial Neural Networks to Combine Fundamental and Technical Analysis.  

E-Print Network (OSTI)

??Stock price forecasting is a classic problem facing analysts. Forcasting models have been developed for predicting individual stocks and stock indices around the world and… (more)

Dravenstott, Ronald W.

2012-01-01T23:59:59.000Z

235

On the design of sponsored keyword advertising slot auctions: An analysis of a generalized second-price auction approach  

Science Conference Proceedings (OSTI)

The generalized second-priceauction mechanism is commonly used in research in the context of keyword advertising slot auctioning. The mechanism sets the clearing prices for advertising slots on a search engine's Web pages such that the advertiser will ... Keywords: Advertising, Auctions, Click-through rate, Economic analysis, Electronic markets, Keywords, Location, Online advertising, Search engines, Sponsored search

He Huang; Robert J. Kauffman

2011-03-01T23:59:59.000Z

236

A Bayesian decision analysis in determining the optimal policy for pricing, production, and warranty of repairable products  

Science Conference Proceedings (OSTI)

A successful industry strategy should be managed to integrate the decisions, such as pricing, production, and customer services, in order to maximize profits. In fact, some research has been carried out to cope with the multiple considerations for the ... Keywords: Bayesian analysis, Deterioration, Mathematical programming, Non-homogeneous Poisson process, Warranty policy

Chih-Chiang Fang; Yeu-Shiang Huang

2008-11-01T23:59:59.000Z

237

Estimating the effect of future oil prices on petroleum engineering project investment yardsticks.  

E-Print Network (OSTI)

This study proposes two methods, (1) a probabilistic method based on historical oil prices and (2) a method based on Gaussian simulation, to model future prices of oil. With these methods to model future oil prices, we can calculate the ranges of uncertainty in traditional probability indicators based on cash flow analysis, such as net present values, net present value to investment ratio and internal rate of return. We found that conventional methods used to quantify uncertainty which use high, low and base prices produce uncertainty ranges far narrower than those observed historically. These methods fail because they do not capture the "shocks" in oil prices that arise from geopolitical events or supply-demand imbalances. Quantifying uncertainty is becoming increasingly important in the petroleum industry as many current investment opportunities in reservoir development require large investments, many in harsh exploration environments, with intensive technology requirements. Insight into the range of uncertainty, particularly for downside, may influence our investment decision in these difficult areas.

Mendjoge, Ashish V

2003-12-01T23:59:59.000Z

238

Uncertainty analysis of integrated gasification combined cycle systems based on Frame 7H versus 7F gas turbines  

SciTech Connect

Integrated gasification combined cycle (IGCC) technology is a promising alternative for clean generation of power and coproduction of chemicals from coal and other feedstocks. Advanced concepts for IGCC systems that incorporate state-of-the-art gas turbine systems, however, are not commercially demonstrated. Therefore, there is uncertainty regarding the future commercial-scale performance, emissions, and cost of such technologies. The Frame 7F gas turbine represents current state-of-practice, whereas the Frame 7H is the most recently introduced advanced commercial gas turbine. The objective of this study was to evaluate the risks and potential payoffs of IGCC technology based on different gas turbine combined cycle designs. Models of entrained-flow gasifier-based IGCC systems with Frame 7F (IGCC-7F) and 7H gas turbine combined cycles (IGCC-7H) were developed in ASPEN Plus. An uncertainty analysis was conducted. Gasifier carbon conversion and project cost uncertainty are identified as the most important uncertain inputs with respect to system performance and cost. The uncertainties in the difference of the efficiencies and costs for the two systems are characterized. Despite uncertainty, the IGCC-7H system is robustly preferred to the IGCC-7F system. Advances in gas turbine design will improve the performance, emissions, and cost of IGCC systems. The implications of this study for decision-making regarding technology selection, research planning, and plant operation are discussed. 38 refs., 11 figs., 5 tabs.

Yunhua Zhu; H. Christopher Frey [Pacific Northwest National Laboratory, Richland, WA (United States)

2006-12-15T23:59:59.000Z

239

Why do Motor Gasoline Prices Vary Regionally? California Case Study  

Reports and Publications (EIA)

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

Information Center

1998-07-15T23:59:59.000Z

240

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

Science Conference Proceedings (OSTI)

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.

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

1997-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

An Analysis of Precipitation Variability, Persistence, and Observational Data Uncertainty in the Western United States  

Science Conference Proceedings (OSTI)

This paper presents an intercomparison of precipitation observations for the western United States. Using nine datasets, the authors provide a comparative climatology and season- and location-specific evaluations of precipitation uncertainty for ...

Kristen J. Guirguis; Roni Avissar

2008-10-01T23:59:59.000Z

242

Implications of Parameter Uncertainty on Soil Moisture Drought Analysis in Germany  

Science Conference Proceedings (OSTI)

Simulated soil moisture is increasingly used to characterize agricultural droughts but its parametric uncertainty, which essentially affects all hydrological fluxes and state variables, is rarely considered for identifying major drought events. In ...

Luis Samaniego; Rohini Kumar; Matthias Zink

2013-02-01T23:59:59.000Z

243

System level assessment of uncertainty in aviation environmental policy impact analysis  

E-Print Network (OSTI)

This thesis demonstrates the assessment of uncertainty of a simulation model at the system level, which takes into account the interaction between the modules that comprise the system. Results from this system level ...

Liem, Rhea Patricia

2010-01-01T23:59:59.000Z

244

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  

Science Conference Proceedings (OSTI)

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.

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

2010-11-01T23:59:59.000Z

245

PRICE LEVELS AND DISPERSION WITH ASYMMETRIC INFORMATION.  

E-Print Network (OSTI)

??In the extensive literature on price dispersions that exists to date, there is a gap in the analysis of how market structure affects prices as… (more)

Bhattacharya, Tanmoy

2011-01-01T23:59:59.000Z

246

Markovian reliability analysis under uncertainty with an application on the shutdown system of the Clinch River Breeder Reactor  

SciTech Connect

A methodology for the assessment of uncertainties about reliability of nuclear reactor systems described by markov models is developed, and the uncertainties about the failure probability of the shutdown system of the Clinch River Breeder Reactor (CRBR) are assessed. Failure and repair rates and all other inputs of reliability analysis are taken as random variables with known probability distribution functions (pdf's). The pdf of reliability is calculated by both a Monte Carlo simulation and a Taylor series expansion approximation. Three techniques are developed to reduce the computational effort: ordering of system states, merging of Markov processes, and judicious choice of time steps. A Markov model has been used for reliability analysis under uncertainty of the shutdown system of the CRBR. It accounts for common-cause failures, interdependences between unavailability of the system and occurrence of transients, and inspection and maintenance procedures that depend on the state of the system and that include possibility of human errors. Under these conditions, the failure probability of the shutdown system differs significantly from that computed without common-cause failures, human errors, and input uncertainties.

Papazoglou, I.A.; Gyftopoulos, E.P.

1980-01-01T23:59:59.000Z

247

A Quantitative Analysis of Oil-Price Shocks, Systematic Monetary Policy, and Economic Downturns  

E-Print Network (OSTI)

for their comments. The views expressed here are those of the authors and do not necessarily represent Are the recessionary consequences of oil-price shocks due to oil-price shocks themselves or to contractionary monetary policies that arise in response to inflation concerns engendered by rising oil prices? Can systematic monetary policy be used to alleviate the consequences of oil shocks on the economy? This paper builds a dynamic general equilibrium model of monopolistic competition in which oil and money matter to study these questions. The economy's response to oil-price shocks is examined under a variety of monetary policy rules in environments with flexible and sticky prices. We find that easy-inflation policies amplify the negative output response to positive oil shocks and that systematic monetary policy accounts for up to two thirds of the fall in output. On the other hand, we show that a monetary policy that targets the (overall) price level substantially alleviates the impact of oil-price shocks

Sylvan Leduc; Keith Sill; Sylvain Leduc; Keith Sill

2004-01-01T23:59:59.000Z

248

TRENDS IN AGRICULTURE PRICE DECLINES AND ANALYSIS OF THE CONDITIONALITIES IN THE DECEMBER 2008 WTO AGRICULTURE CHAIR’S TEXT SYNOPSIS  

E-Print Network (OSTI)

This paper begins by highlighting the frequency of price declines experienced by developing countries. It then touches on the use of the price-based Special Safeguard Provision (SSG) by developed countries. The paper then looks at the conditionalities of the WTO Agriculture Chair’s December 2008 text (TN/AG/W/4/Rev.4). These include exclusion of en route shipments from the price-based SSM coverage; the trigger and remedy, and the omission to take into account the value declines in ad valorem duties when prices drop; the cross-check; and the exclusion of preferential trade from SSM coverage. An analysis of these conditionalities is provided. Some of these clauses, if agreed upon, will severely curtail countries ’ ability to invoke the price-based SSM. In addition, once invoked, the remedies, as they are currently drafted, are not likely to be effective in shielding domestic producers from price volatilities.

unknown authors

2009-01-01T23:59:59.000Z

249

Report on INL Activities for Uncertainty Reduction Analysis of FY12  

SciTech Connect

The work scope of this project related to the Work Packages of “Uncertainty Reduction Analyses” with the goal of reducing nuclear data uncertainties is to produce a set of improved nuclear data to be used both for a wide range of validated advanced fast reactor design calculations, and for providing guidelines for further improvements of the ENDF/B files (i.e. ENDF/B-VII, and future releases). Recent extensive sensitivity/uncertainty studies, performed within an international OECD-NEA initiative, have quantified for the first time the impact of current nuclear data uncertainties on design parameters of the major FCR&D and GEN-IV systems, and in particular on Na-cooled fast reactors with different fuels (oxide or metal), fuel composition (e.g. different Pu/TRU ratios) and different conversion ratios. These studies have pointed out that present uncertainties on the nuclear data should be significantly reduced, in order to get full benefit from the advanced modeling and simulation initiatives. Nuclear data plays a fundamental role in performance calculations of advanced reactor concepts. Uncertainties in the nuclear data propagate into uncertainties in calculated integral quantities, driving margins and costs in advanced system design, operation and safeguards. This package contributes to the resolution of technical, cost, safety, security and proliferation concerns in a multi-pronged, systematic, science-based R&D approach. The Nuclear Data effort identifies and develops small scale, phenomenon-specific experiments informed by theory and engineering to reduce the number of large, expensive integral experiments. The Nuclear Data activities are leveraged by effective collaborations between experiment and theory, between DOE programs and offices, at national laboratories and universities, both domestic and international. The primary objective is to develop reactor core sensitivity and uncertainty analyses that identify the improvement needs of key nuclear data which would facilitate fast spectrum system optimization and assure safety performance. The inclusion of fast spectrum integral experiment data is key to minimizing the impact of nuclear data uncertainties on reactor core performance calculations, thus providing the best nuclear data needs assessment. This report presents the status of activities performed at INL under the ARC Work Package previously mentioned. As major achievement this year a comprehensive adjustment, including 87 experiments, was carried out. The results of this adjustment provide useful insights and helpful feedback to both nuclear data evaluation and measurer communities. In the following, we will document first the theory that underlines the adjustment methodology, and then we will illustrate the sensitivity coefficient computation and the nuclear data and experiment selection. Subsequently, the adjustment results will be shown, and, finally, conclusions, including future work, will be provided.

G. Palmiotti; M. Salvatores

2012-09-01T23:59:59.000Z

250

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

E-Print Network (OSTI)

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

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

2008-01-01T23:59:59.000Z

251

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

E-Print Network (OSTI)

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

Ensor, Jeffrey D. (Jeffrey Douglas)

2005-01-01T23:59:59.000Z

252

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis- 2010  

Energy.gov (U.S. Department of Energy (DOE))

Report describes the 2010 edition of energy price indices and discount factors for performing life-cycle cost analyses of energy and water conservation and renewable energy projects in federal facilities.

253

Seasonal Volatility in Energy Prices: Modeling Seasonality in Natural Gas and Electricity Price Volatility  

Science Conference Proceedings (OSTI)

The modeling and measurement of price uncertainty are essential prerequisites to asset valuation and risk management in electric power. Practical, realistic models must take into account the systematic time patterns exhibited by price volatility. This report uses new data and techniques to reexamine the seasonal nature of energy price volatility.

2004-12-15T23:59:59.000Z

254

Empirical Analysis of the Spot Market Implications ofPrice-Responsive Demand  

SciTech Connect

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

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

2005-08-01T23:59:59.000Z

255

Economic Analysis of Energy Crop Production in the U.S. - Location, Quantities, Price, and Impacts on Traditional Agricultural Crops  

DOE Green Energy (OSTI)

POLYSYS is used to estimate US locations where, for any given energy crop price, energy crop production can be economically competitive with conventional crops. POLYSYS is a multi-crop, multi-sector agricultural model developed and maintained by the University of Tennessee and used by the USDA-Economic Research Service. It includes 305 agricultural statistical districts (ASD) which can be aggregated to provide state, regional, and national information. POLYSYS is being modified to include switchgrass, hybrid poplar, and willow on all land suitable for their production. This paper summarizes the preliminary national level results of the POLYSYS analysis for selected energy crop prices for the year 2007 and presents the corresponding maps (for the same prices) of energy crop production locations by ASD. Summarized results include: (1) estimates of energy crop hectares (acres) and quantities (dry Mg, dry tons), (2) identification of traditional crops allocated to energy crop production and calculation of changes in their prices and hectares (acres) of production, and (3) changes in total net farm returns for traditional agricultural crops. The information is useful for identifying areas of the US where large quantities of lowest cost energy crops can most likely be produced.

Walsh, M.E.; De La Torre Ugarte, D.; Slinsky, S.; Graham, R.L.; Shapouri, H.; Ray, D.

1998-10-04T23:59:59.000Z

256

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

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

5 November 2007 Generic Technical Issue Discussion on 5 November 2007 Generic Technical Issue Discussion on Sensitivity and Uncertainty Analysis and Model Support Attendees: Representatives from Department of Energy-Headquarters (DOE-HQ) and the U.S. Nuclear Regulatory Commission (NRC) met at the DOE offices in Germantown, Maryland on 15 November 2007. Representatives from Department of Energy-Savannah River (DOE-SR) and the South Carolina Department of Health and Environmental Control (SCDHEC) participated in the meeting via a teleconference link. Discussion: DOE believes that based on the position papers provided prior to the meeting, DOE and NRC staff have many areas of agreement and no significant areas of disagreement with respect to the specific sensitivity and uncertainty analysis requirements articulated in the respective DOE and NRC requirements. The NRC

257

Greater Risk in Coal Supply and Price -- Need to Revisit Coal Procurement  

Science Conference Proceedings (OSTI)

Although spot coal prices have declined significantly from the peaks reached during 2001, they remain above pre-spike levels. This report provides analysis and perspective on the implications and likely long-term effects of the spike in spot coal prices that occurred in late 2000 and 2001. The report analyzes factors that will continue to exert upward pressure on coal prices over the next several years, key uncertainties relating to the future balance between coal supply and demand, and strategies for ma...

2002-12-03T23:59:59.000Z

258

Natural Gas Citygate Price  

Annual Energy Outlook 2012 (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...

259

Cheese Prices  

E-Print Network (OSTI)

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

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

2003-08-25T23:59:59.000Z

260

Sarah Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Sarah K Price Sarah Price Energy Efficiency Standards Group Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R4000 Berkeley CA 94720 Office Location: 90-4128B (510)...

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Marisa Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Marisa Dawn Price Marisa Price Communications Office Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R3029B Berkeley CA 94720 Office Location: 90-2056B (510) 495-2713...

262

Uncertainty Analysis of the Conducted Interferences in a DC-DC Converter  

E-Print Network (OSTI)

.A. Vasconcelos Laboratorio de Computação Evolucionaria Universidade Federal de Minas Gerais Belo Horizonte measurement of conducted interferences and its PDF is rapidly determined, when compared to the Monte Carlo (MC) approach. Keywords - Electromagnetic Compatibility, Monte Carlo, Parametric Uncertainty, Power Electronics

Paris-Sud XI, Université de

263

Incorporation of phenomenological uncertainties in probabilistic safety analysis - application to LMFBR core disruptive accident energetics  

SciTech Connect

This report describes a method for quantifying frequency and consequence uncertainty distribution associated with core disruptive accidents (CDAs). The method was developed to estimate the frequency and magnitude of energy impacting the reactor vessel head of the Clinch River Breeder Plant (CRBRP) given the occurrence of hypothetical CDAs. The methodology is illustrated using the CRBR example.

Najafi, B.; Theofanous, T.G.; Rumble, E.T.; Atefi, B.

1984-08-01T23:59:59.000Z

264

Error Uncertainty Analysis of GPCP Monthly Rainfall Products: A Data-Based Simulation Study  

Science Conference Proceedings (OSTI)

This paper focuses on estimating the error uncertainty of the monthly 2.5° × 2.5° rainfall products of the Global Precipitation Climatology Project (GPCP) using rain gauge observations. Two kinds of GPCP products are evaluated: the satellite-only ...

Mekonnen Gebremichael; Witold F. Krajewski; Mark Morrissey; Darin Langerud; George J. Huffman; Robert Adler

2003-12-01T23:59:59.000Z

265

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

Science Conference Proceedings (OSTI)

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.

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

2013-10-01T23:59:59.000Z

266

Gas Prices  

NLE Websites -- All DOE Office Websites (Extended Search)

Prices Gasoline Prices for U.S. Cities Click on the map to view gas prices for cities in your state. AK VT ME NH NH MA MA RI CT CT DC NJ DE DE NY WV VA NC SC FL GA AL MS TN KY IN...

267

Automating calibration, sensitivity and uncertainty analysis of complex models using the R package Flexible Modeling Environment (FME): SWAT as an example  

Science Conference Proceedings (OSTI)

Parameter optimization and uncertainty issues are a great challenge for the application of large environmental models like the Soil and Water Assessment Tool (SWAT), which is a physically-based hydrological model for simulating water and nutrient cycles ... Keywords: Calibration, FME, Monte Carlo, R, SWAT, Sensitivity and uncertainty analysis

Yiping Wu; Shuguang Liu

2012-05-01T23:59:59.000Z

268

Incorporating uncertainty into electric utility projections and decisions  

Science Conference Proceedings (OSTI)

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

Hanson, D.A.

1992-01-01T23:59:59.000Z

269

Incorporating uncertainty into electric utility projections and decisions  

Science Conference Proceedings (OSTI)

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

Hanson, D.A.

1992-07-01T23:59:59.000Z

270

An Econometric Analysis of the Relationship among the U.S. Ethanol, Corn and Soybean Sectors, and World Oil Prices.  

E-Print Network (OSTI)

??This thesis aimed to investigate the relationships among the following variables: U.S. corn prices, U.S. ethanol production, U.S. soybean prices and world oil prices. After… (more)

Savernini, Maira Q. M.

2009-01-01T23:59:59.000Z

271

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

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.

Frederik Reitsma; Gerhard Strydom; Bismark Tyobeka; Kostadin Ivanov

2012-10-01T23:59:59.000Z

272

Uncertainty analysis routine for the Ocean Thermal Energy Conversion (OTEC) biofouling measurement device and data reduction procedure. [HTCOEF code  

DOE Green Energy (OSTI)

Biofouling and corrosion of heat exchanger surfaces in Ocean Thermal Energy Conversion (OTEC) systems may be controlling factors in the potential success of the OTEC concept. Very little is known about the nature and behavior of marine fouling films at sites potentially suitable for OTEC power plants. To facilitate the acquisition of needed data, a biofouling measurement device developed by Professor J. G. Fetkovich and his associates at Carnegie-Mellon University (CMU) has been mass produced for use by several organizations in experiments at a variety of ocean sites. The CMU device is designed to detect small changes in thermal resistance associated with the formation of marine microfouling films. An account of the work performed at the Pacific Northwest Laboratory (PNL) to develop a computerized uncertainty analysis for estimating experimental uncertainties of results obtained with the CMU biofouling measurement device and data reduction scheme is presented. The analysis program was written as a subroutine to the CMU data reduction code and provides an alternative to the CMU procedure for estimating experimental errors. The PNL code was used to analyze sample data sets taken at Keahole Point, Hawaii; St. Croix, the Virgin Islands; and at a site in the Gulf of Mexico. The uncertainties of the experimental results were found to vary considerably with the conditions under which the data were taken. For example, uncertainties of fouling factors (where fouling factor is defined as the thermal resistance of the biofouling layer) estimated from data taken on a submerged buoy at Keahole Point, Hawaii were found to be consistently within 0.00006 hr-ft/sup 2/-/sup 0/F/Btu, while corresponding values for data taken on a tugboat in the Gulf of Mexico ranged up to 0.0010 hr-ft/sup 2/-/sup 0/F/Btu. Reasons for these differences are discussed.

Bird, S.P.

1978-03-01T23:59:59.000Z

273

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

SciTech Connect

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.

Michael Pernice

2012-10-01T23:59:59.000Z

274

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

DOE Green Energy (OSTI)

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.

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

2013-10-01T23:59:59.000Z

275

Uncertainty induced by QCD coupling in the CTEQ global analysis of parton distributions  

SciTech Connect

We examine the dependence of parton distribution functions (PDFs) on the value of the QCD coupling strength {alpha}{sub s}(M{sub Z}). We explain a simple method that is rigorously valid in the quadratic approximation normally applied in PDF fitting, and fully reproduces the correlated dependence of theoretical cross sections on {alpha}{sub s} and PDF parameters. This method is based on a statistical relation that allows one to add the uncertainty produced by {alpha}{sub s}, computed with some special PDF sets, in quadrature with the PDF uncertainty obtained for the fixed {alpha}{sub s} value (such as the CTEQ6.6 PDF set). A series of four CTEQ6.6AS PDFs realizing this approach, for {alpha}{sub s} values in the interval 0.116{<=}{alpha}{sub s}(M{sub Z}){<=}0.120, is presented. Using these PDFs, the combined {alpha}{sub s} and PDF uncertainty is assessed for theoretical predictions at the Fermilab Tevatron and Large Hadron Collider.

Lai, Hung-Liang [Taipei Municipal University of Education, Taipei, Taiwan (China); Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824-1116 (United States); Huston, Joey; Li, Zhao; Pumplin, Jon; Stump, Daniel; Yuan, C.-P. [Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824-1116 (United States); Nadolsky, Pavel [Department of Physics, Southern Methodist University, Dallas, Texas 75275-0175 (United States)

2010-09-01T23:59:59.000Z

276

An Analysis of Incentives for Network Infrastructure Investment Under Different Pricing Strategies  

Science Conference Proceedings (OSTI)

The Internet is making a significant transition from primarily a network of desktop computers to a network variety of connected information devices such as personal digital assistants and global positioning system-based devices. On the other hand, new ... Keywords: Internet pricing, infrastructure investment, investment incentives, net neutrality, simulation

Alok Gupta; Boris Jukic; Dale O. Stahl; Andrew B. Whinston

2011-06-01T23:59:59.000Z

277

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

E-Print Network (OSTI)

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

Colón-Jiménez, Ely X

2010-01-01T23:59:59.000Z

278

Residential response to price changes in natural gas service: A short-run analysis  

Science Conference Proceedings (OSTI)

Residential consumer demand for natural gas services is determined by numerous components including natural gas and competing fuel prices, weather patterns, appliance ownership characteristics, income, and energy conservation measure implementation. This study utilizes household-level data on a set of the determinants of residential natural gas demand, combined with corresponding consumption observations, to analyze the price response over the [open quotes]short-run[close quotes] period, in which primary natural gas-consuming appliances are fixed. Two model specifications are employed in this study to model the natural gas demand function and derive short-run price elasticity estimates. These are the Error Components (EC) and Fixed Effects (FE) models. These specifications result in elastic short-run responses estimates ranging between [minus]2.164 and [minus]7.015. These values contrast with the inelastic short-run estimated responses presented in previous empirical work, and the likelihood of actually observing such large short-run responses is expected to be small. The large estimates developed in the current study are evidently due to the use of household-specific data that incorporates disaggregated factors that influence monthly fluctuations in demand. This level of detail is subsumed within the aggregated data employed in prior studies. The price elasticity estimates developed in this study are directly applicable to short-run fuel demand analyses. The estimates are also applicable to the development, implementation, and evaluation of energy conservation programs.

Wilson, P.A.

1992-01-01T23:59:59.000Z

279

Statistically based uncertainty analysis for ranking of component importance in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor  

SciTech Connect

The Analytic Hierarchy Process (AHP) has been used to help determine the importance of components and phenomena in thermal-hydraulic safety analyses of nuclear reactors. The AHP results are based, in part on expert opinion. Therefore, it is prudent to evaluate the uncertainty of the AHP ranks of importance. Prior applications have addressed uncertainty with experimental data comparisons and bounding sensitivity calculations. These methods work well when a sufficient experimental data base exists to justify the comparisons. However, in the case of limited or no experimental data the size of the uncertainty is normally made conservatively large. Accordingly, the author has taken another approach, that of performing a statistically based uncertainty analysis. The new work is based on prior evaluations of the importance of components and phenomena in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor (ANSR), a new facility now in the design phase. The uncertainty during large break loss of coolant, and decay heat removal scenarios is estimated by assigning a probability distribution function (pdf) to the potential error in the initial expert estimates of pair-wise importance between the components. Using a Monte Carlo sampling technique, the error pdfs are propagated through the AHP software solutions to determine a pdf of uncertainty in the system wide importance of each component. To enhance the generality of the results, study of one other problem having different number of elements is reported, as are the effects of a larger assumed pdf error in the expert ranks. Validation of the Monte Carlo sample size and repeatability are also documented.

Wilson, G.E.

1992-01-01T23:59:59.000Z

280

Measuring and Explaining Electricity Price Changes in Restructured States  

Science Conference Proceedings (OSTI)

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)

Fagan, Mark L.

2006-06-15T23:59:59.000Z

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Stephanie Price  

Energy.gov (U.S. Department of Energy (DOE))

Stephanie Price is a communicator at the National Renewable Energy Laboratory, which assists EERE in providing technical content for many of its websites.

282

PRICE SPECULATION  

E-Print Network (OSTI)

The price of crude oil in the U.S. had never exceeded $40 per barrel until mid-2004. By 2006 it reached $70 per barrel, and in July 2008 it reached a peak of $145. By the end of 2008 it had plummeted to about $30 before increasing again, reaching about $110 in 2011. Are “speculators ” to blame for at least part of the volatility and sharp run-ups in price? We clarify the potential and actual effects of speculators, and investors in general, on commodity prices. We focus on crude oil, but our approach can be applied to other commodities. We first address the question of what is meant by “oil price speculation, ” and how it relates to investments in oil reserves, oil inventories, or oil price derivatives (such as futures contracts). Next we outline the ways in which one could speculate on oil prices. Finally, we turn to the data, and calculate counterfactual prices that would have occurred from 1999 to 2012 in the absence of speculation. Our framework is based on a simple and transparent model of supply and demand in the cash and storage markets for a commodity. It lets us determine whether speculation as the driver of price changes is consistent with the data on production, consumption, inventory changes, and changes in convenience yields given reasonable elasticity assumptions. We show speculation had little, if any, effect on prices and volatility.

Christopher R. Knittel; Robert S. Pindyck; Christopher R. Knittel; Robert S. Pindyck

2013-01-01T23:59:59.000Z

283

Snuller Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Snuller Price Energy and Environmental Economics NOTICE Due to the current lapse of federal funding, Berkeley Lab websites are accessible, but may not be updated until Congress...

284

Essays on Price Dynamics  

E-Print Network (OSTI)

Small Regular Price Changes . . . . . . . . . . . . . . .4 The Cyclicality of Effective Prices2.3 Wholesale Price vs. Retail

Hong, Gee Hee

2012-01-01T23:59:59.000Z

285

Literature Review of Uncertainty of Analysis Methods (PV F-Chart Program), Report to the Texas Commission on Environmental Quality  

E-Print Network (OSTI)

This report reviews the reported uncertainty of the PV F-Chart analysis method by reviewing the published related accuracy of PV F-Chart analysis versus measured data, PV F-Chart predictions versus other methods, and PV F-Chart predictions versus TRNSYS simulations. This report begins with a review of the history of the PV F-Chart method, and includes an example PV F-Chart calculation. In summary, from the literature it was found that hourly PV F-Chart analysis versus measured data were shown to be within 4% of on-site measurement, PV F-Chart predictions versus TRNSYS simulations and another graphical method were also within 4% of annual values.

Haberl, J. S.; Cho, S.

2004-01-01T23:59:59.000Z

286

Analysis of customer response to electricity rate structures which create an endogenous electricity price  

SciTech Connect

In the 1970's, concern over the availability and cost of fossil fuels led to use of electricity rates designed to conserve energy. Under several rates the marginal electricity price was endogenous. Two such rates were inverted block rates and voluntary time-of-use (TOU) rates. Both rates have the potential to alter welfare by changing electricity-usage patterns. Both require special methodological treatment. The problem of modeling demand under block rates was addressed in several fields. The most-sophisticated solution to date is a maximum likelihood approach first used in labor economics. However, as demonstrated in this thesis, this approach may cause misspecification of the likelihood function. In this thesis, a correctly specified maximum-likelihood model is developed, in which the simultaneous determination of usage and the marginal price resulting from the block rate are explicitly modeled in a unified framework. The resulting likelihood function is not continuously differentiable. However, maximization of this likelihood function is shown to produce asymptotically normal parameter estimates. The model is used to estimate the demand for electricity under a two-tier inverted block rate. Results show very small elasticities of demand with respect to each component of the rate structure. Comparison estimates using other methodologies demonstrate the problems which can arise if the endogenous price is not carefully treated.

Kuester, K.A.

1986-01-01T23:59:59.000Z

287

Essays on Three Price Judgments: Price Fairness, Price Magnitude, and Price Expectation.  

E-Print Network (OSTI)

??This dissertation addresses three important price judgments: price fairness, price magnitude, and price expectation. Developed over three chapters, the main objective of this research is… (more)

Bhowmick, Sandeep

2010-01-01T23:59:59.000Z

288

Dynamic Pricing and Learning in Electricity Markets  

Science Conference Proceedings (OSTI)

We analyze the price-formation process in an infinite-horizon oligopoly model where hydroelectric generators engage in dynamic price-based competition. The analysis focuses on the role of "indifference" prices, i.e., prices that equate the gains from ... Keywords: Dynamic auctions, Economics, Games: stochastic, Natural resources: energy, Noncooperative, Restructured electricity markets, Water resources

Alfredo Garcia; Enrique Campos-Nañez; James Reitzes

2005-03-01T23:59:59.000Z

289

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

SciTech Connect

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.

Langton, C.; Kosson, D.

2009-11-30T23:59:59.000Z

290

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

Science Conference Proceedings (OSTI)

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.

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

2011-04-19T23:59:59.000Z

291

An inverse scheme for sensitivity and uncertainty analysis in basin modeling: the resolution limits of Easy%Ro  

E-Print Network (OSTI)

One of the major contributors to uncertainties in basin modeling arises from the determination of the parameters necessary for reconstructing the thermal history due to the importance of the thermal maturity in evaluating the petroleum potential of a basin. The methods to determine these uncertainties need to be developed, tested and applied. Two major methods (geodynamic models and calibration of paleoheat flow to thermal indicators) are available for determining the paleoheat flux of a sedimentary basin. Of the latter, the chemical kinetic model Easy%Ro (Sweeney and Burnham, 1990) is widely used and has a firm foundation in laboratory experiments and calibration. The Easy%Ro model calculates the systematic variation of vitrinite reflectance with time and temperature. Even though Easy%Ro is widely used for constraining paleoheat flow by calibrating and modeling vitrinite reflectance, its ability to resolve paleoheat flow and its success in providing the relationship between vitrinite reflectance and the thermal history of a sedimentary basin is not yet investigated and determined quantitatively. This study provides the first quantitative approach to determine the resolution limits of the chemical kinetic model, Easy%Ro. Paleothermal gradients are calibrated against vitrinite reflectance using the Easy%Ro model plugged into a single parameter inverse engine in order to perform sensitivity analysis and assess the uncertainty. Vitrinite reflectance data is obtained from the B-1 , Lulu-1 , Mona-1 , Sten-1 and Q-1 wells located in the Danish Central Trough, in the North Sea. A range of geothermal gradients are investigated using the model. As a quantitative measure of mismatch between modeled and measured values, the mean squared residual (MSR) is used (MSR =(1/n) [](Ro[]-Ro[])²). A 90% confidence level on the best answer (lowest MSR) is taken to represent the acceptable error range for the particular model. The sensitivity of the Easy%Ro model to changes in geothermal gradient and its ability to resolve thermal history are investigated from the determined uncertainties associated with scatter in the calibration data (measured vitrinite reflectance). The results are used to elaborate on Easy%Ro resolution limits with respect to thermal history.

Huvaz, Ozkan

2000-01-01T23:59:59.000Z

292

Literature Review of Uncertainty of Analysis Methods (Inverse Model Toolkit), Report to the Texas Commission on Environmental Quality  

E-Print Network (OSTI)

This report reviews the reported uncertainty of ASHRAE’s Inverse Model Toolkit (IMT) analysis method and the linear, and change-point linear algorithms that it uses by reviewing the published literature on the related accuracy of IMT and its algorithms versus other well-accepted statistical analysis tools, such as SAS. This report begins with a review of the history of the IMT, and the linear and change-point linear models. Then it reviews the published comparisons of the IMT and other analysis software, relying heavily on the accuracy testing that was performed as part of ASHRAE’s Research Project 1050-RP. It also includes a detailed description of the basic algorithms and an example of the IMT weather-normalization analysis. In summary, from the literature it was found that the algorithms in the IMT almost exactly reproduce the same regression analysis one would get by running any one of the programs that it was compared against (i.e., usually to several significant digits). Therefore, it can be concluded that the IMT is accurate, when it is called upon to perform weather normalized regressions for modeling building energy use.

Haberl, J. S.; Cho, S.

2004-01-01T23:59:59.000Z

293

Retail Price Drivers and their Financial Consequences  

E-Print Network (OSTI)

making the data available. Retail Price Drivers and their Financial Consequences What are the drivers of retailers ' prices and what, if any, are their financial consequences? The results of a large-scale quantitative analysis show that retail prices are mainly driven by pricing history (50%), acquisition costs (25%), and demand feedback (12.5%). In contrast to pricing history, demand-based pricing is associated with higher retailer (and manufacturer) financial performance. The remaining price drivers: category management, store traffic, and store brand performance, affect manufacturer and retailer performance in more complex ways.

Shuba Srinivasan; Koen Pauwels; Vincent Nijs; Mike Hanssens; Carl Mela; Scott Neslin For Comments; Suggestions The Paper

2003-01-01T23:59:59.000Z

294

Lynn Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Lynn Price China Energy Group Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R2002 Berkeley CA 94720 Office Location: 90-2108 (510) 486-6519 LKPrice@lbl.gov NOTICE Due...

295

Snuller Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Snuller Price Energy and Environmental Economics This speaker was a visiting speaker who delivered a talk or talks on the date(s) shown at the links below. This speaker is not...

296

PRICE GOUGING  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

home heating costs? How will those be affected? With an overall increase in the price of heating oil and natural gas, we expect that there may be an increase in home heating costs...

297

Phillip Price  

NLE Websites -- All DOE Office Websites (Extended Search)

90-2006 (510) 486-7875 PNPrice@lbl.gov Dr. Phillip Price has a Ph.D. in physics from the University of Kentucky, and has worked in the Indoor Environment Department since 1992. In...

298

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

Science Conference Proceedings (OSTI)

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.

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

1990-05-01T23:59:59.000Z

299

Markets & Finance - Analysis & Projections - U.S. Energy Information  

Gasoline and Diesel Fuel Update (EIA)

Most Requested Most Requested Change category... Most Requested Electricity Financial Markets Financial Reporting System All Reports Filter by: All Data Analysis Projections Weekly Reports Today in Energy - Markets & Finance Short, timely articles with graphs about recent issues and trends in financial markets Monthly Reports Market Prices and Uncertainty Report Released: January 7, 2014 This is a regular monthly supplement to the EIA Short-Term Energy Outlook. (archived versions) Archived Versions Market Prices and Uncertainty Report - Archive Energy & Financial Markets: What Drives Crude Oil Prices? Released: December 14, 2011 An assessment of the various factors that may influence oil prices - physical market factors as well as those related to trading and financial

300

ResGrid: A Grid-Aware Toolkit for Reservoir Uncertainty Analysis  

E-Print Network (OSTI)

or measurement. Reservoir studies concerned with responses affecting value, e.g. ­ Peak oil rate ­ Cumulative oil ­ Drilling performance analysis with high-rate data "UCOMS" #12;Oil Industry in Louisiana · Major oil ­ 17 petroleum refineries (capacity 2.8M barrels/day) ­ Ports receive ultra large oil tankers ­ 20

Allen, Gabrielle

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

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

DOE Green Energy (OSTI)

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

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

2012-02-21T23:59:59.000Z

302

Use of Sensitivity and Uncertainty Analysis in the Design of Reactor Physics and Criticality Benchmark Experiments for Advanced Nuclear Fuel  

SciTech Connect

Framatome ANP, Sandia National Laboratories (SNL), Oak Ridge National Laboratory (ORNL), and the University of Florida are cooperating on the U.S. Department of Energy Nuclear Energy Research Initiative (NERI) project 2001-0124 to design, assemble, execute, analyze, and document a series of critical experiments to validate reactor physics and criticality safety codes for the analysis of commercial power reactor fuels consisting of UO{sub 2} with {sup 235}U enrichments {>=}5 wt%. The experiments will be conducted at the SNL Pulsed Reactor Facility.Framatome ANP and SNL produced two series of conceptual experiment designs based on typical parameters, such as fuel-to-moderator ratios, that meet the programmatic requirements of this project within the given restraints on available materials and facilities. ORNL used the Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI) to assess, from a detailed physics-based perspective, the similarity of the experiment designs to the commercial systems they are intended to validate. Based on the results of the TSUNAMI analysis, one series of experiments was found to be preferable to the other and will provide significant new data for the validation of reactor physics and criticality safety codes.

Rearden, B.T. [Oak Ridge National Laboratory (United States); Anderson, W.J. [Framatome ANP, Inc. (France); Harms, G.A. [Sandia National Laboratories (United States)

2005-08-15T23:59:59.000Z

303

Crude Oil Affects Gasoline Prices  

U.S. Energy Information Administration (EIA)

Crude Oil Affects Gasoline Prices. WTI Crude Oil Price. Retail Gasoline Price. Source: Energy Information Administration

304

Price supports and demand in commodity market modeling  

E-Print Network (OSTI)

Gerdner, B. L. "Futures Prices in Supply Analysis." Amer. J.Service. Spot and Futures Prices." Limited Dcpenden{avec Leuthold, R. ~1. "The Price Performance on the Futures

Riboud, Chris; Rausser, Gordon C.

1981-01-01T23:59:59.000Z

305

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

E-Print Network (OSTI)

the spot market price of energy in a competitive wholesalethrough” the spot market price of energy for all of theadditional energy at the spot market price. Another example

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

2005-01-01T23:59:59.000Z

306

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

and Demand Response under Uncertainty • F P t : wholesale natural gasdemand response and DER under uncertain electricity and natural gasand Demand Response under Uncertainty Energy Price Models We assume that the logarithms of the deseasonalized electricity and natural gas

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

307

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

SciTech Connect

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

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

2010-01-01T23:59:59.000Z

308

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

Science Conference Proceedings (OSTI)

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.

Sung, Yixing (Westinghouse Electric Company LLC, Cranberry Township, PA); Adams, Brian M.; Secker, Jeffrey R. (Westinghouse Electric Company LLC, Cranberry Township, PA)

2011-12-01T23:59:59.000Z

309

Short-Term World Oil Price Forecast  

Gasoline and Diesel Fuel Update (EIA)

4 4 Notes: This graph shows monthly average spot West Texas Intermediate crude oil prices. Spot WTI crude oil prices peaked last fall as anticipated boosts to world supply from OPEC and other sources did not show up in actual stocks data. So where do we see crude oil prices going from here? Crude oil prices are expected to be about $28-$30 per barrel for the rest of this year, but note the uncertainty bands on this projection. They give an indication of how difficult it is to know what these prices are going to do. Also, EIA does not forecast volatility. This relatively flat forecast could be correct on average, with wide swings around the base line. Let's explore why we think prices will likely remain high, by looking at an important market barometer - inventories - which measures the

310

SRM Pricing Policy  

Science Conference Proceedings (OSTI)

... rates are used to calculate the price for each ... Therefore, prices for new lots and renewal issues of ... changed, all SRMs may be re-priced taking into ...

2012-11-16T23:59:59.000Z

311

Pennsylvania Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

- GasBuddy.com Pennsylvania Gas Prices (selected cities) - GasBuddy.com Pennsylvania Gas Prices (organized by county) - Automotive.com Gas Prices of the United States:...

312

Retrospective Evaluation of Appliance Price Trends  

NLE Websites -- All DOE Office Websites (Extended Search)

efficiency standards, appliance energy efficiency, cost-benefit analysis, price forecasts, Techno-Economic Analysis URL https:isswprod.lbl.govlibraryview-docspublic...

313

Prices & Trends  

Energy.gov (U.S. Department of Energy (DOE))

The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment. Learn about EIA and Energy Department organizations that track energy prices and trends.

314

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

SciTech Connect

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.

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

2010-09-01T23:59:59.000Z

315

Understanding Crude Oil Prices  

E-Print Network (OSTI)

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

Hamilton, James Douglas

2008-01-01T23:59:59.000Z

316

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

E-Print Network (OSTI)

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

Ellerman, A. Denny

1996-01-01T23:59:59.000Z

317

Average Commercial Price  

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

Residential Price Average Commercial Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes...

318

What Do We Learn from the Price of Crude Oil Futures?” working paper  

E-Print Network (OSTI)

Abstract: Based on a two-country, multi-period general equilibrium model of the spot and futures markets for crude oil, we show that there is no theoretical support for the common view that oil futures prices are accurate predictors of the spot price in the mean-squared prediction error (MSPE) sense; yet under certain conditions there is support for the view that oil futures prices are unbiased predictors. Our empirical analysis documents that futures-based forecasts typically are less accurate than the no-change forecast and biased, although the bias is small. Much of the MSPE is driven by the variability of the futures price about the expected spot price, as captured by the basis. Empirically, the fluctuations in the oil futures basis are larger and more persistent than fluctuations in the basis of foreign exchange futures. Within the context of our theoretical model, this anomaly can be explained by the marginal convenience yield of oil inventories. We show that increased uncertainty about future oil supply shortfalls under plausible assumptions causes the basis to decline and precautionary demand for crude oil to increase, resulting in an immediate increase in the real spot price that is not necessarily associated with an accumulation of oil inventories. Our main result is that the negative of the basis may be viewed as an index of fluctuations in the price of crude oil driven by precautionary demand for oil. An empirical analysis of this index provides independent evidence of how shifts in market expectations about future oil supply shortfalls affect the spot price of crude oil. Such expectation shifts have been difficult to quantify, yet have been shown to play an important role in explaining oil price fluctuations. Our empirical results are consistent with related evidence in the literature obtained by alternative methodologies.

Ron Alquist; Lutz Kilian

2007-01-01T23:59:59.000Z

319

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

Science Conference Proceedings (OSTI)

In this study, we applied version 4 of the Community Land Model (CLM4) integrated with an uncertainty quantification (UQ) framework to 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning a wide range of climate ...

Maoyi Huang; Zhangshuan Hou; L. Ruby Leung; Yinghai Ke; Ying Liu; Zhufeng Fang; Yu Sun

320

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

Science Conference Proceedings (OSTI)

In this study, the authors applied version 4 of the Community Land Model (CLM4) integrated with an uncertainty quantification (UQ) framework to 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning a wide range of ...

Maoyi Huang; Zhangshuan Hou; L. Ruby Leung; Yinghai Ke; Ying Liu; Zhufeng Fang; Yu Sun

2013-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

Assessing the Performance of an Ensemble Forecast System in Predicting the Magnitude and the Spectrum of Analysis and Forecast Uncertainties  

Science Conference Proceedings (OSTI)

The ability of an ensemble to capture the magnitude and spectrum of uncertainty in a local linear space spanned by the ensemble perturbations is assessed. Numerical experiments are carried out with a reduced resolution 2004 version of the model ...

Elizabeth Satterfield; Istvan Szunyogh

2011-04-01T23:59:59.000Z

322

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

E-Print Network (OSTI)

with complementarities among goods as they can be found in procurement, energy markets, transportation, and the sale of these mechanisms is that by allowing market participants to reveal more comprehensive information about cost, Sandholm and Begg 2006). Much recent research in Information Systems is devoted to the design and analysis

Cengarle, María Victoria

323

An Analysis of Short-Term Risk in Power System Pricing  

Science Conference Proceedings (OSTI)

The power system planning process will undergo changes as the electric utility industry transforms into a competitive market. This report presents a methodology that uses classical decision analysis, sampling theory, and load forecasting theory to evaluate short-term risk in power system planning.

1999-08-12T23:59:59.000Z

324

Price Risk Management in the Midst of a Credit Crisis  

E-Print Network (OSTI)

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

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

2009-03-26T23:59:59.000Z

325

Market structure and the price of electricity: An ex ante analysis of the deregulated Swedish electricity market  

Science Conference Proceedings (OSTI)

Following new legislation the Swedish electricity market is about to be deregulated. The new system is designed to ensure competition in production and supply. The main motive for deregulation is to increase competition and thus achieve lower market prices. A possible threat to this outcome is the high degree of concentration on the seller side that characterizes the Swedish electricity market. In this paper we show that given the current structure of firms on the supply side, deregulation is not a sufficient condition for lower equilibrium prices in the electricity market. We use a numerical model to explore the quantitative relation between the Cournot-equilibrium price, the number of firms, and the size distribution of firms in the Swedish electricity market. We compute equilibrium electricity prices and a welfare measure in order to quantify the effect of asymmetric market concentration on competition. 3 refs., 1 fig., 6 tabs.

Andersson, B.; Bergman, L. [Stockholm School of Economics (Sweden)

1995-12-31T23:59:59.000Z

326

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

E-Print Network (OSTI)

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

L'Hegaret, Guillaume

2004-01-01T23:59:59.000Z

327

Threshold Effects of Energy Price Changes ?  

E-Print Network (OSTI)

The effectiveness of policies to reduce the use of energy depend on the elasticity of substitution between the various inputs and on the rate of technological progress. This paper presents a theoretical model emphasising energy investments’ characteristics of uncertainty and irreversibility that result in hypotheses concerning the relative values of substitution parameters and rates of technological change in periods of high and increasing energy prices and in periods of low prices. The theoretical model suggests that threshold level effects exist. Firms are induced to substitute away from energy only if prices of energy exceed a certain threshold level and they reverse the technology only if prices are low enough. Using panel data for the Dutch economy we do not find threshold effects in the level of energy prices.

Daan P. Van Soest A; Gerard H. Kuper B; Jan Jacobs C

2000-01-01T23:59:59.000Z

328

Managing Energy Price Risk with Derivatives  

NLE Websites -- All DOE Office Websites (Extended Search)

Managing Energy Price Risk with Derivatives Managing Energy Price Risk with Derivatives Speaker(s): Douglas Hale Date: September 18, 2003 - 12:00pm Location: Bldg. 90 Seminar Host/Point of Contact: Joseph Eto Energy derivatives came into being with the deregulation of the petroleum and natural gas industries in the early 1980s. Although derivatives-forwards, futures and options-have been used in American agriculture since the mid-1800's to manage price risk, they were unnecessary in regulated energy industries. Deregulation revealed that oil, gas and electricity prices are exceptionally volatile. Companies were forced to cope with the uncertainty in energy prices; they latched onto derivatives as one tool for managing that risk. Enron's collapse brought energy derivatives to public attention. Following the derivative linked

329

October 2009Rethinking Real Time Electricity Pricing  

E-Print Network (OSTI)

Most US consumers are charged a near-constant retail price for electricity, despite substantial hourly variation in the wholesale market price. This paper evaluates the …rst program to expose residential consumers to hourly real time pricing (RTP). I …nd that enrolled households are statistically signi…cantly price elastic and that consumers responded by conserving energy during peak hours, but remarkably did not increase average consumption during o¤-peak times. Welfare analysis suggests that program households were not su ¢ ciently price elastic to generate e ¢ ciency gains that substantially outweigh the estimated costs of the advanced electricity meters required to observe hourly consumption. Although in electricity pricing, congestion pricing, and many other settings, economists’intuition is that prices should be aligned with marginal costs, residential RTP may provide an important real-world example of a situation where this is not currently welfare-enhancing given contracting or information costs.

Hunt Allcott; Hunt Allcott; Bill Hogan; Erich Muehlegger; Larry Katz; Erin Mansur; Sendhil Mullainathan; Paul Niehaus; Chris Nosko; Ariel Pakes; Dave Rapson; Rob Stavins; Frank Wolak

2009-01-01T23:59:59.000Z

330

Internet Resource Pricing Models, Mechanisms, and Methods  

E-Print Network (OSTI)

With the fast development of video and voice network applications, CDN (Content Distribution Networks) and P2P (Peer-to-Peer) content distribution technologies have gradually matured. How to effectively use Internet resources thus has attracted more and more attentions. For the study of resource pricing, a whole pricing strategy containing pricing models, mechanisms and methods covers all the related topics. We first introduce three basic Internet resource pricing models through an Internet cost analysis. Then, with the evolution of service types, we introduce several corresponding mechanisms which can ensure pricing implementation and resource allocation. On network resource pricing methods, we discuss the utility optimization in economics, and emphasize two classes of pricing methods (including system optimization and entities' strategic optimizations). Finally, we conclude the paper and forecast the research direction on pricing strategy which is applicable to novel service situation in the near future.

He, Huan; Liu, Ying

2011-01-01T23:59:59.000Z

331

The New Era of Corn, Soybean, and Wheat Prices  

E-Print Network (OSTI)

Prices have changed so much for what we sell and buy that it is almost impossible to feel confident in the decisions you make.”-- Agriculture Online, July 5, 2008 Prices of corn, soybeans, and wheat started moving higher in the fall of 2006 and have remained generally high and well above average prices in the previous 30 years. These higher prices, and the volatility associated with the higher prices, have resulted in the kind of uncertainty reflected in the quote above. Are higher prices here to stay? If so, what is the expected level and variability of prices during the new era? From a producer’s standpoint, the question really is, “What is a good price for corn, soybeans and wheat? ” These questions

Darrel Good; Scott Irwin

2008-01-01T23:59:59.000Z

332

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

SciTech Connect

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

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

2013-05-22T23:59:59.000Z

333

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

SciTech Connect

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

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

2013-01-31T23:59:59.000Z

334

Price controls and international petroleum product prices  

SciTech Connect

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.

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

1980-02-01T23:59:59.000Z

335

Trading and Prices in Commodity Markets  

U.S. Energy Information Administration (EIA)

Trading and Prices in Commodity Markets EIA 2013 Workshop on Financial and Physical Oil Market Linkages ... Director of Energy Markets and Financial Analysis

336

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

Science Conference Proceedings (OSTI)

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.

Kiedrowski, Brian C. [Los Alamos National Laboratory

2012-06-19T23:59:59.000Z

337

Natural Gas Wellhead Price  

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

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 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 2007 2008 2009 2010 2011 2012 View History U.S. 6.25 7.97 3.67 4.48 3.95 2.66 1922-2012 Alabama 7.44 9.65 4.32 4.46 1967-2010 Alaska 5.63 7.39 2.93 3.17 1967-2010 Arizona 5.98 7.09 3.19 4.11 1967-2010 Arkansas

338

Uncertainty Assessments in Severe Nuclear Accident Scenarios  

Science Conference Proceedings (OSTI)

Managing uncertainties in industrial systems is a daily challenge to ensure improved design, robust operation, accountable performance and responsive risk control. This paper aims to illustrate the different depth analyses that the uncertainty software ... Keywords: Monte Carlo simulation, nuclear power plant, sensitivity analysis, severe accident, uncertainty

Bertrand Iooss; Fabrice Gaudier; Michel Marques; Bertrand Spindler; Bruno Tourniaire

2009-09-01T23:59:59.000Z

339

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

E-Print Network (OSTI)

Response Program, ISO-NE Real-Time Price Response Program,rather than real time market prices) is more compatible withare correlated to real-time market prices, customers may be

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

2005-01-01T23:59:59.000Z

340

PRICE GOUGING | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

PRICE GOUGING PRICE GOUGING PRICE GOUGING More Documents & Publications PRICE GOUGING Department of Energy Response to Hurricane Katrina Fact Sheet Department of Energy Response to...

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

INTERIM VALIDATION REPORT MIDDLE DISTILLATE PRICE MONITORING SYSTEM  

E-Print Network (OSTI)

1977-1978 HEATING OIL PRICES II-1 II-3 II-3 Wholesale PricesI-7 ANALYSIS 01:' Hm1E HEATING OIL PRICES FOR THE 1977-1978regarding No. 2 heating oil price data for the 1977-1978

Hopelain, D.G.

2011-01-01T23:59:59.000Z

342

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

Science Conference Proceedings (OSTI)

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

Gallimore, David L. [Los Alamos National Laboratory

2012-06-13T23:59:59.000Z

343

Electricity Market Price Forecasting in a Price-responsive Smart Grid Environment  

E-Print Network (OSTI)

of this load is to use electricity market price forecasts to op- timally schedule a combination of the gas of Electricity Market Price Forecasting Errors: A Demand-Side Analysis Hamidreza Zareipour, Member, IEEE, Claudio--Several techniques have been proposed in the liter- ature to forecast electricity market prices and improve forecast

344

Methods of economic analysis applied to fusion research: discount rate determination and the fossil fuel price effect  

SciTech Connect

In current and previous efforts, ECON has provided a preliminary economic assessment of a fusion research program. Part of this effort was the demonstration of a methodology for the estimation of reactor system costs and risk and for the treatment of program alternatives as a series of steps (tests) to buy information, thereby controlling program risk and providing a sound economic rationale for properly constructed research programs. The first phase of work also identified two areas which greatly affect the overall economic evaluation of fusion research and which warranted further study in the second phase. This led to the two tasks of the second phase reported herein: (1) discount rate determination and (2) evaluation of the effect of the expectation of the introduction of fusion power on current fossil fuel prices. In the first task, various conceptual measures of the social rate of discount were reviewed and critiqued. In the second task, a benefit area that had been called out by ECON was further examined. Long-range R and D yields short-term benefits in the form of lower nonrenewable energy resource prices because the R and D provides an expectation of future competition for the remaining reserves at the time of technology availability. ECON developed a model of optimal OPEC petroleum pricing as a function of the expectation of future competing technologies. It was shown that the existence of this expectation lowers the optimal OPEC export price and that accelerated technology R and D programs should provide further price decreases. These price reductions translate into benefits to the U.S. of at least a billion dollars.

1978-09-25T23:59:59.000Z

345

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

Science Conference Proceedings (OSTI)

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)?

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

2005-08-01T23:59:59.000Z

346

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...

347

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...

348

Overshooting of agricultural prices  

E-Print Network (OSTI)

Rotenberg, Julio J. , "Sticky Prices in the United States,"Monetary Policy on United States Agriculture. A Fix-Price,Flex-Price Approach," Unpublished Ph.D. Disser- tation,

Stamoulis, Kostas G.; Rausser, Gordon C.

1987-01-01T23:59:59.000Z

349

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...

350

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...

351

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...

352

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...

353

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...

354

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...

355

Georgia Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices ... History; Imports Price: 6.79: 9.71: 3.73: 4.39: 4.20: 2.78: 1999-2012: Pipeline and Distribution Use Price : 1967-2005: ...

356

Michigan Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Wellhead Price: NA: 5.63: 3.92: 3.79 : 1967-2010: Imports Price: ...

357

Retail Price Changes Lag Spot Prices  

Gasoline and Diesel Fuel Update (EIA)

1 1 Notes: While EIA cannot claim to explain all of the factors that drive retail gasoline prices, we have had a fair amount of success in exploring the relationship between wholesale and retail prices. In particular, we have looked closely at the "pass-through" of changes in spot prices to the retail market. This graph shows a weighted national average of spot prices for regular gasoline -both conventional and reformulated (shown in red), and EIA's weekly survey price for retail regular (again both conventional and reformulated). As you can see, spot prices tend to be more volatile (and would be even more so on a daily basis), while these changes are smoother by the time they reach the retail pump. Furthermore, by looking at the peaks, you can see the retail prices seem to lag the spot price changes

358

Price forecasting for notebook computers  

E-Print Network (OSTI)

This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a series of time periods, and the rates of change in the influence of individual features are estimated. A time series analysis is used to forecast and can be used, for example, to forecast (1) notebook computer price at introduction, and (2) rate of price erosion for a notebook's life cycle. Results indicate that this approach can forecast the price of a notebook computer up to four months in advance of its introduction with an average error of under 10% and the rate of price erosion to within 10% of the price for seven months after introduction-the length of the typical life cycle of a notebook. Since all data are publicly available, this approach can be used to assist managerial decision making in the notebook computer industry, for example, in determining when and how to upgrade a model and when to introduce a new model.

Rutherford, Derek Paul

1997-01-01T23:59:59.000Z

359

Uncertainty in Integrated Assessment Scenarios  

SciTech Connect

The determination of climate policy is a decision under uncertainty. The uncertainty in future climate change impacts is large, as is the uncertainty in the costs of potential policies. Rational and economically efficient policy choices will therefore seek to balance the expected marginal costs with the expected marginal benefits. This approach requires that the risks of future climate change be assessed. The decision process need not be formal or quantitative for descriptions of the risks to be useful. Whatever the decision procedure, a useful starting point is to have as accurate a description of climate risks as possible. Given the goal of describing uncertainty in future climate change, we need to characterize the uncertainty in the main causes of uncertainty in climate impacts. One of the major drivers of uncertainty in future climate change is the uncertainty in future emissions, both of greenhouse gases and other radiatively important species such as sulfur dioxide. In turn, the drivers of uncertainty in emissions are uncertainties in the determinants of the rate of economic growth and in the technologies of production and how those technologies will change over time. This project uses historical experience and observations from a large number of countries to construct statistical descriptions of variability and correlation in labor productivity growth and in AEEI. The observed variability then provides a basis for constructing probability distributions for these drivers. The variance of uncertainty in growth rates can be further modified by expert judgment if it is believed that future variability will differ from the past. But often, expert judgment is more readily applied to projected median or expected paths through time. Analysis of past variance and covariance provides initial assumptions about future uncertainty for quantities that are less intuitive and difficult for experts to estimate, and these variances can be normalized and then applied to mean trends from a model for uncertainty projections. The probability distributions of these critical model drivers, and the resulting uncertainty in projections from a range of models, can provide the basis of future emission scenario set designs.

Mort Webster

2005-10-17T23:59:59.000Z

360

Residential Heating Oil Prices  

U.S. Energy Information Administration (EIA)

We normally collect and publish this data twice a month, but given the low stocks and high prices, we started tracking the prices weekly.

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Natural Gas Wellhead Price  

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

included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes...

362

Primer on Gasoline Prices  

Reports and Publications (EIA)

This brochure answers, in laymen's terms, questions such as "What are the components of the retail price of gasoline? Why do gasoline prices fluctuate?

Information Center

2009-07-15T23:59:59.000Z

363

Natural Gas Wellhead Prices  

U.S. Energy Information Administration (EIA)

Slide 19 of 27. Price: Wellhead. Natural gas wellhead prices are projected to move up 5 percent this winter, averaging about $2.28 per Mcf during this ...

364

Crude Oil Price Forecast  

U.S. Energy Information Administration (EIA)

We believe crude oil prices will strengthen somewhat, but prices will rise much more slowly than they fell, and they are expected to remain lower in ...

365

Price Liquefied Sabine Pass, LA Natural Gas Exports Price ...  

U.S. Energy Information Administration (EIA)

Price Liquefied Sabine Pass, LA Natural Gas Exports Price to Brazil (Dollars per Thousand Cubic Feet)

366

Modeling natural gas prices as a random walk: The advantages for generation planning  

SciTech Connect

Random walk modeling allows decision makers to evaluate risk mitigation strategies. Easily constructed, the random walk provides probability information that long-term fuel forecasts do not. This is vital to meeting the ratepayers` need for low-cost power, the shareholders` financial objectives, and the regulators` desire for straightforward information. Power generation planning depends heavily on long-term fuel price forecasts. This is particularly true for natural gas-fired plants, because fuel expenses are a significant portion of busbar costs and are subject to considerable uncertainty. Accurate forecasts, then, are critical - especially if electric utilities are to take advantage of the current low cost of natural gas technologies and their relatively clean burning characteristics, without becoming overdependent on a fuel that might significantly increase in price. Moreover, the transition to a more competitive generation market requires a more market-driven planning process. Current planning techniques use several long-term fuel forecasts - one serving as an expected case and others for sensitivity analysis - as inputs for modeling production costs. These forecasts are deterministic: For every time interval there is one, and only one projected fuel price - a serious limitation. Further, past natural gas price predictions have been erroneous and may be susceptible to bias. Today, deregulation of the natural gas production industry allows for a new approach in long-term fuel forecasting. Using NYMEX information, a random walk model of natural gas prices can be constructed. A random walk assumes that prices move randomly, and in modeling prices in this context one would be sure to include this all-important price volatility.

Felder, F.A.

1995-11-01T23:59:59.000Z

367

What Is Price Volatility  

Gasoline and Diesel Fuel Update (EIA)

What Is Price Volatility? What Is Price Volatility? The term "price volatility" is used to describe price fluctuations of a commodity. Volatility is measured by the day-to-day percentage difference in the price of the commodity. The degree of variation, not the level of prices, defines a volatile market. Since price is a function of supply and demand, it follows that volatility is a result of the underlying supply and demand characteristics of the market. Therefore, high levels of volatility reflect extraordinary characteristics of supply and/or demand. Prices of basic energy (natural gas, electricity, heating oil) are generally more volatile than prices of other commodities. One reason that energy prices are so volatile is that many consumers are extremely limited in their ability to substitute other fuels when the price, of natural gas

368

The uncertainties in estimating measurement uncertainties  

SciTech Connect

All measurements include some error. Whether measurements are used for accountability, environmental programs or process support, they are of little value unless accompanied by an estimate of the measurements uncertainty. This fact is often overlooked by the individuals who need measurements to make decisions. This paper will discuss the concepts of measurement, measurements errors (accuracy or bias and precision or random error), physical and error models, measurement control programs, examples of measurement uncertainty, and uncertainty as related to measurement quality. Measurements are comparisons of unknowns to knowns, estimates of some true value plus uncertainty; and are no better than the standards to which they are compared. Direct comparisons of unknowns that match the composition of known standards will normally have small uncertainties. In the real world, measurements usually involve indirect comparisons of significantly different materials (e.g., measuring a physical property of a chemical element in a sample having a matrix that is significantly different from calibration standards matrix). Consequently, there are many sources of error involved in measurement processes that can affect the quality of a measurement and its associated uncertainty. How the uncertainty estimates are determined and what they mean is as important as the measurement. The process of calculating the uncertainty of a measurement itself has uncertainties that must be handled correctly. Examples of chemistry laboratory measurement will be reviewed in this report and recommendations made for improving measurement uncertainties.

Clark, J.P.; Shull, A.H.

1994-07-01T23:59:59.000Z

369

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

Science Conference Proceedings (OSTI)

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.

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

2006-10-01T23:59:59.000Z

370

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

Science Conference Proceedings (OSTI)

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.

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

2010-05-01T23:59:59.000Z

371

Quantifying uncertainty in LCA-modelling of waste management systems  

SciTech Connect

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

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

2012-12-15T23:59:59.000Z

372

Diesel Fuel Price Pass-through  

Gasoline and Diesel Fuel Update (EIA)

Diesel Fuel Price Pass-through Diesel Fuel Price Pass-through EIA Home > Petroleum > Petroleum Feature Articles Diesel Fuel Price Pass-through Printer-Friendly PDF Diesel Fuel Price Pass-through by Michael Burdette and John Zyren* Over the past several years, the Energy Information Administration (EIA) has extensively studied the relationships between wholesale and retail markets for petroleum products. Beginning with gasoline, we looked at the two ends of the pricing structure in the U.S. market: daily spot prices, which capture sales of large quantities of product between refiners, importers/exporters, and traders; and weekly retail prices, measured at local gasoline outlets nationwide. In the course of this analysis, EIA has found that the relationships between spot and retail prices are consistent and predictable, to the extent that changes in spot prices can be used to forecast subsequent changes in retail prices for the appropriate regions. This article represents the extension of this type of analysis and modeling into the diesel fuel markets.

373

State energy price and expenditure report 1993  

SciTech Connect

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.

1995-12-01T23:59:59.000Z

374

MTBE Prices Responded to Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: On top of the usual factors impacting gasoline prices, natural gas has had some influence recently. MTBE is an oxygenate used in most of the RFG consumed in the U.S. Generally, it follows gasoline prices and its own supply/demand balance factors. But this winter, we saw it respond strongly to natural gas prices. MTBE is made from methanol and isobutylene, which in turn come from methane and butane. Both methane and butane come from natural gas streams. Until this year, the price of natural gas has been so low that it had little effect. But the surge that occurred in December and January pulled MTBE up . Keep in mind that about 11% MTBE is used in a gallon of RFG, so a 30 cent increase in MTBE is only about a 3 cent increase in the price of RFG. While we look ahead at this summer, natural gas prices should be

375

Three Essays on Retail Price Dynamics  

E-Print Network (OSTI)

of Reference Prices . . . . . . . . . . . . . . . . . . . .2.4.5 Reference Prices andChain-Level Prices . . . . . . . . . . . . . .

Elberg, Andres

2010-01-01T23:59:59.000Z

376

Appendix A: Fuel Price Forecast Introduction..................................................................................................................................... 1  

E-Print Network (OSTI)

Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts............................................................................................................................... 12 Oil Price Forecast Range

377

MTBE Prices Responded to Natural Gas Prices  

U.S. Energy Information Administration (EIA)

On top of the usual factors impacting gasoline prices, natural gas has had some influence recently. ... Both methane and butane come from natural gas streams.

378

Maryland Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Maryland Maryland Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Baltimore BaltimoreGasPrices.com Automotive.com MapQuest.com Bethesda BethesdaGasPrices.com Automotive.com MapQuest.com Bowie BowieGasPrices.com Automotive.com MapQuest.com Frederick FrederickGasPrices.com Automotive.com MapQuest.com Gaithersburg GaithersburgGasPrices.com Automotive.com MapQuest.com Other Maryland Cities MarylandGasPrices.com (search by city or ZIP code) - GasBuddy.com Maryland Gas Prices (selected cities) - GasBuddy.com Maryland Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Maryland Cities - MapQuest

379

Massachusetts Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Massachusetts Massachusetts Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Boston BostonGasPrices.com Automotive.com MapQuest.com Brockton BrocktonGasPrices.com Automotive.com MapQuest.com Cambridge CambridgeGasPrices.com Automotive.com MapQuest.com Fall River FallRiverGasPrices.com Automotive.com MapQuest.com Haverhill HaverhillGasPrices.com Automotive.com MapQuest.com Lawrence LawrenceGasPrices.com Automotive.com MapQuest.com Lowell LowellGasPrices.com Automotive.com MapQuest.com New Bedford NewBedfordGasPrices.com Automotive.com Mapquest.com Taunton TauntonGasPrices.com Automotive.com MapQuest.com

380

Ohio Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Ohio Ohio Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Akron AkronGasPrices.com Automotive.com Mapquest.com Cincinnati CincinnatiGasPrices.com Automotive.com Mapquest.com Cleveland ClevelandGasPrices.com Automotive.com Mapquest.com Columbus ColumbusGasPrices.com Automotive.com Mapquest.com Dayton DaytonGasPrices.com Automotive.com Mapquest.com Toledo ToledoGasPrices.com Automotive.com Mapquest.com Other Ohio Cities OhioGasPrices.com (search by city or ZIP code) - GasBuddy.com Ohio Gas Prices (selected cities) - GasBuddy.com Ohio Gas Prices (organized by county) - Automotive.com

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Regional Retail Gasoline Prices  

Gasoline and Diesel Fuel Update (EIA)

7 7 Notes: Retail gasoline prices, like those for distillate fuels, have hit record prices nationally and in several regions this year. The national average regular gasoline price peaked at $1.68 per gallon in mid-June, but quickly declined, and now stands at $1.45, 17 cents higher than a year ago. Two regions, in particular, experienced sharp gasoline price runups this year. California, which often has some of the highest prices in the nation, saw prices peak near $1.85 in mid-September, while the Midwest had average prices over $1.87 in mid-June. Local prices at some stations in both areas hit levels well over $2.00 per gallon. The reasons for the regional price runups differed significantly. In the Midwest, the introduction of Phase 2 RFG was hampered by low stocks,

382

Virginia Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Virginia Virginia Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Alexandria AlexandriaGasPrices.com Automotive.com Mapquest.com Arlington ArlingtonGasPrices.com Automotive.com Mapquest.com Chesapeake ChesapeakeGasPrices.com Automotive.com Mapquest.com Hampton HamptonGasPrices.com Automotive.com Mapquest.com Newport News NewportNewsGasPrices.com Automotive.com Mapquest.com Norfolk NorfolkGasPrices.com Automotive.com Mapquest.com Portsmouth PortsmouthGasPrices.com Automotive.com Mapquest.com Richmond RichmondGasPrices.com Automotive.com Mapquest.com Virginia Beach VirginiaBeachGasPrices.com Automotive.com Mapquest.com

383

Illinois Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Illinois Illinois Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Arlington Heights ArlingtonHeightsGasPrices.com Automotive.com MapQuest.com Aurora AuroraGasPrices.com Automotive.com MapQuest.com Bloomington BloomingtonGasPrices.com Automotive.com MapQuest.com Champaign ChampaignGasPrices.com Automotive.com MapQuest.com Chicago ChicagoGasPrices.com Automotive.com MapQuest.com Decatur DecaturGasPrices.com Automotive.com Mapquest.com Elgin ElginGasPrices.com Automotive.com MapQuest.com Joliet JolietGasPrices.com Automotive.com MapQuest.com Naperville NapervilleGasPrices.com Automotive.com MapQuest.com

384

Oklahoma Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Oklahoma Oklahoma Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Lawton LawtonGasPrices.com Automotive.com Mapquest.com Norman NormanGasPrices.com Automotive.com Mapquest.com Oklahoma City OklahomaCityGasPrices.com Automotive.com Mapquest.com Tulsa TulsaGasPrices.com Automotive.com Mapquest.com Other Oklahoma Cities OklahomaGasPrices.com (search by city or ZIP code) - GasBuddy.com Oklahoma Gas Prices (selected cities) - GasBuddy.com Oklahoma Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Oklahoma Cities - MapQuest Oklahoma Gas Prices (organized by county, search by ZIP code) -

385

Tennessee Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Tennessee Tennessee Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Chattanooga ChattanoogaGasPrices.com Automotive.com Mapquest.com Clarksville ClarksvilleGasPrices.com Automotive.com Mapquest.com Knoxville KnoxvilleGasPrices.com Automotive.com Mapquest.com Memphis MemphisGasPrices.com Automotive.com Mapquest.com Murfreesboro MurfreesboroGasPrices.com Automotive.com Mapquest.com Nashville NashvilleGasPrices.com Automotive.com Mapquest.com Other Tennessee Cities TennesseeGasPrices.com (search by city or ZIP code) - GasBuddy.com Tennessee Gas Prices (selected cities) - GasBuddy.com Tennessee Gas Prices (organized by county) - Automotive.com

386

Wisconsin Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Wisconsin Wisconsin Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Appleton AppletonGasPrices.com Automotive.com Mapquest.com Eau Claire EauClaireGasPrices.com Automotive.com Mapquest.com Green Bay GreenBayGasPrices.com Automotive.com Mapquest.com Kenosha KenoshaGasPrices.com Automotive.com Mapquest.com Madison MadisonGasPrices.com Automotive.com Mapquest.com Milwaukee MilwaukeeGasPrices.com Automotive.com Mapquest.com Other Wisconsin Cities WisconsinGasPrices.com (search by city or ZIP code) - GasBuddy.com Wisconsin Gas Prices (selected cities) - GasBuddy.com Wisconsin Gas Prices (organized by county) - Automotive.com

387

PRICE & AVAILABILITY UPDATES  

E-Print Network (OSTI)

4.3 Price & Availability Updates File when titles transferred to new supplier..................... 5 4.4 Format of the ‘Day ’ element in Availability Dates......................................................... 5 5 Example of Price & Availability Updates transmission....................................................... 5 6 Price & Availability Updates file header............................................................................. 7 Example of a complete Price & Availability Updates file header....................................... 12 7 Price & Availability Updates “message level ” content...................................................... 13 8 Price & Availability Updates “line level ” content............................................................... 14 Example showing Order "line level " segments NOI to DNC.............................................. 21 9 Price & Availability Updates message trailer.................................................................... 21 10 Price & Availability Updates file trailer............................................................................ 22 NOTE: The TRADACOMS Price & Availability Updates message is not recommended for new implementations. The recommended formats for the communication of book product information are the ONIX for Books Product Information message and Supply Update message.

unknown authors

2010-01-01T23:59:59.000Z

388

Higher Prices from Entry: Pricing of Brand-Name Drugs  

E-Print Network (OSTI)

with Distance Figure 6 Cumulative Unexpected Price Effectsand Paul J. Seguin, "Price Volatility, Trading Volume andGoods in Pharmaceutical Price In- dexes," American Economic

Perloff, Jeffrey M.; Suslow, Valerie Y.; Seguin, Paul J.

1995-01-01T23:59:59.000Z

389

Higher Prices from Entry: Pricing of Brand-Name Drugs  

E-Print Network (OSTI)

4 Bertrand and Cartel Prices Vary with z 7T, CS L Figure 5Distance Cumulative Abnormal Price Changes (%) Dissimilarof New Drug Figure 6 Cumulative Unexpected Price Effects

Perloff, Jeffrey M.; Suslow, Valerie Y.; Seguin, Paul J.

1995-01-01T23:59:59.000Z

390

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

E-Print Network (OSTI)

The dynamics of the U.S. and Canada natural gas spot markets are evolving through deregulation policies and technological advances. Economic theory suggests that these markets will be integrated. The key question is the extent of integration among the markets. This thesis characterizes the degree of dynamic integration among 11 major natural gas markets, six from the U.S. and five from Canada, and determines each individual markets’ role in price discovery. This is the first study to include numerous Canadian markets in a North American natural gas market study. Causal flows modeling using directed acyclic graphs in conjunction with time series analysis are used to explain the relationships among the markets. Daily gas price data from 1994 to 2009 are used. The 11 natural gas market prices are tied together with nine long-run co-integrating relationships. All markets are included in the co-integration space, providing evidence the markets are integrated. Results show the degree of integration varies by region. Further results indicate no clear price leader exists among the 11 markets. Dawn market is exogenous in contemporaneous time, while Sumas market is an information sink. Henry Hub plays a significant role in the price discovery of markets in the U.S. Midwest and Northeast, but little to markets in the west. The uncertainty of a markets’ price depends primarily on markets located in nearby regions. Policy makers may use information on market integration for important policy matters in efforts of attaining efficiency. Gas traders benefit from knowing the price discovery relationships.

Olsen, Kyle

2010-12-01T23:59:59.000Z

391

State Volume Price Volume Price Volume Price Volume Price Volume Price  

Gasoline and Diesel Fuel Update (EIA)

7 7 2000 2001 2002 2003 2004 State Volume Price Volume Price Volume Price Volume Price Volume Price Pipeline (Canada) Eastport, ID..................... 830,351 3.79 802,182 4.71 759,647 2.83 R 623,652 4.72 707,885 5.30 Calais, ME ...................... 123,521 4.50 152,486 4.47 124,991 3.49 R 115,301 R 5.85 102,292 6.44 Detroit, MI ....................... 6,171 3.82 405 9.34 1,948 3.56 2,514 5.96 1,117 6.27 Marysville, MI.................. 0 -- 0 -- 74 3.95 0 -- 303 7.80 St. Clair, MI..................... 17,198 4.45 21,747 4.54 28,441 3.19 5,202 5.84 22,853 6.50 International Falls, MN .... 3,022 2.77 617 4.85 602 3.01 0 -- 0 -- Noyes, MN...................... 469,361 3.75 448,898 4.19 402,621 3.09 R 359,801 5.04 399,298 5.77 Warroad, MN .................. 4,576 3.95 5,318 4.52

392

Examination Procedure for Price Verification  

Science Conference Proceedings (OSTI)

... advertised or displayed at the same price that was ... to permit 2 % of products to be inaccurately priced? ... overall quality of a store's pricing practices. ...

2013-06-28T23:59:59.000Z

393

C. Uniform Unit Pricing Regulation  

Science Conference Proceedings (OSTI)

... to permit retail stores that voluntarily provide unit pricing to present prices using various ... with requirements that specify that the unit price is to be ...

2013-10-25T23:59:59.000Z

394

All Price Tables.vp  

Annual Energy Outlook 2012 (EIA)

8. Coal and Retail Electricity Prices and Expenditures, Ranked by State, 2011 Rank Coal Retail Electricity Prices Expenditures Prices Expenditures State Dollars per Million Btu...

395

South Carolina Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Pipeline and Distribution Use Price : 1967-2005: Citygate Price: ...

396

Spot Distillate & Crude Oil Prices  

U.S. Energy Information Administration (EIA)

Retail distillate prices follow the spot distillate markets, and crude oil prices have been the main driver behind distillate spot price increases until recently.

397

Basic definitions of uncertainty  

Science Conference Proceedings (OSTI)

... Glossary. The following definitions are given in the ISO Guide to the Expression of Uncertainty in Measurement. Many additional ...

398

Uncertainty Machine — User's Manual  

Science Conference Proceedings (OSTI)

... Figure 8: Resistance — Densities. ... Supplement 1 to the “Guide to the expression of uncertainty in measurement” — Propagation of distributions ...

2013-07-19T23:59:59.000Z

399

Treatment of measurement uncertainties at the power burst facility  

SciTech Connect

The treatment of measurement uncertainty at the Power Burst Facility provides a means of improving data integrity as well as meeting standard practice reporting requirements. This is accomplished by performing the uncertainty analysis in two parts, test independent uncertainty analysis and test dependent uncertainty analysis. The test independent uncertainty analysis is performed on instrumentation used repeatedly from one test to the next, and does not have to be repeated for each test except for improved or new types of instruments. A test dependent uncertainty analysis is performed on each test based on the test independent uncertainties modified as required by test specifications, experiment fixture design, and historical performance of instruments on similar tests. The methodology for performing uncertainty analysis based on the National Bureau of Standards method is reviewed with examples applied to nuclear instrumentation.

Meyer, L.C.

1980-01-01T23:59:59.000Z

400

Natural Gas Spot Prices:  

Gasoline and Diesel Fuel Update (EIA)

4 of 26 4 of 26 Notes: Spot wellhead prices last summer averaged well over $4.00 per thousand cubic feet during a normally low-price season. During the fall, these prices stayed above $5.00 per thousand cubic feet, more than double the year-ago average price. In January, the spot wellhead price averaged a record $8.98 per thousand cubic feet. Spot prices at the wellhead have never been this high for such a prolonged period. The chief reason for these sustained high gas prices was, and still is, uneasiness about the supply situation. Concern about the adequacy of winter supplies loomed throughout most of the summer and fall as storage levels remained significantly depressed. Last December, the most severe assumptions about low storage levels became real, when the spot price

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Understanding Crude Oil Prices  

E-Print Network (OSTI)

2004. “OPEC’s Optimal Crude Oil Price,” Energy Policy 32(2),Figure 3. Price of crude oil contract maturing December ofbarrels per day. Monthly crude oil production Iran Iraq

Hamilton, James Douglas

2008-01-01T23:59:59.000Z

402

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,...

403

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...

404

Diesel prices slightly decrease  

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

3, 2013 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...

405

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,...

406

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...

407

Florida Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Citygate Price: 4.79: 4.68: 4.54: 4.47: 4.26: 4.33: 1989-2013: ...

408

Michigan Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) Area: ... History; Citygate Price: 4.74: 4.99: 4.52: 4.48: 4.13: NA: ...

409

Maine Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Citygate Price: 6.72: 8.18: 11.03: NA: NA: 7.19: 1989-2013: ...

410

Pennsylvania Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Citygate Price: 6.14: 7.58: 8.34: 7.51: 7.39: 6.16: 1989-2013: ...

411

Alabama Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) Area: ... History; Citygate Price: 4.81: 5.12: 5.31: 4.92: 4.64: NA: ...

412

Career Services Pricing Information  

Science Conference Proceedings (OSTI)

Job/Resume Posting and Prices Career Services Pricing Information Career Services Career Services chemistry jobs classifieds employment fats global help wanted job Jobs member membership network oils science jobs ...

413

Diesel prices decrease  

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

to 3.88 a gallon on Monday. That's down 0.4 cents from a week ago, based on the weekly price survey by the U.S. Energy Information Administration. Diesel prices were highest in...

414

Retail Propane Prices  

Gasoline and Diesel Fuel Update (EIA)

6 Notes: Consistent with spot prices, residential propane prices have been higher all winter than during the past several years. The recent surge is mainly the result of the surge...

415

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

E-Print Network (OSTI)

Asymmetrically to Crude Oil Price Changes? ”, QuarterlyS. , A. Shepard. “Sticky Prices, Inventories, and MarketGas Wars: Retail Gasoline Price Fluctua- tions”, Review of

Noel, Michael

2004-01-01T23:59:59.000Z

416

Asymmetric Wholesale Pricing: Theory and Evidence  

Science Conference Proceedings (OSTI)

Asymmetric pricing or asymmetric price adjustment is the phenomenon where prices rise more readily than they fall. We offer and provide empirical support for a new theory of asymmetric pricing in wholesale prices. Wholesale prices may adjust asymmetrically ... Keywords: asymmetric price adjustment, asymmetric pricing, channel of distribution, channel pricing, cost of price adjustment, economic model, menu cost, retailing, scanner data, wholesale price

Sourav Ray; Haipeng (Allan) Chen; Mark E. Bergen; Daniel Levy

2006-03-01T23:59:59.000Z

417

Price Sound Laboratory  

Science Conference Proceedings (OSTI)

Price Sound Laboratory. NVLAP Lab Code: 200874-0. Address and Contact Information: 638 RALEIGH STREET WINNIPEG ...

2013-10-31T23:59:59.000Z

418

EIA Energy Prices  

U.S. Energy Information Administration (EIA)

This publication includes total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, ...

419

EIA Oil price timeline  

U.S. Energy Information Administration (EIA)

Crude oil, gasoline, heating oil, diesel, propane, ... Sales, revenue and prices, power plants, fuel use, stocks, generation, trade, demand & emissions.

420

Real-time pricing -- supplanted by Price-risk derivatives?  

Science Conference Proceedings (OSTI)

Future trends in pricing options for wholesale electrical generation are discussed. Specifically, the effect of price derivatives on electricity consumption are examined. Economic analyses are presented for customer demand in real-time pricing scenarios with and without a price derivative hedge. It is determined that consumption will be curtailed even when price caps have been purchased. Consumption behavior is also analyzed to determine the effect of different price caps; regardless of price, consumption is curtailed in response to price.

O`Sheasy, M.

1997-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Wisconsin Natural Gas Prices  

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

Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.04 8.71 6.70 6.14 5.65 4.88 1984-2012 Residential Price 12.02 12.81 10.76 10.34 9.77 9.23 1967-2012 Percentage of...

422

California Gasoline Price Study  

Gasoline and Diesel Fuel Update (EIA)

DIRECTOR, PETROLEUM DIVISION DIRECTOR, PETROLEUM DIVISION ENERGY INFORMATION ADMINISTRATION U.S. DEPARTMENT OF ENERGY BEFORE THE SUBCOMMITTEE ON ENERGY AND RESOURCES COMMITTEE ON GOVERNMENT REFORM U.S. HOUSE OF REPRESENTATIVES MAY 9, 2005 Mr. Chairman, I appreciate this opportunity to testify today on the Energy Information Administration's (EIA) insights into factors affecting recent gasoline prices. EIA is the statutorily chartered statistical and analytical agency within the U.S. Department of Energy. We are charged with providing objective, timely, and relevant data, analysis, and projections for the use of the Department of Energy, other Government agencies, the U.S. Congress, and the public. We produce data and analysis reports that are meant to assist policy makers in determining energy policy. Because we have an element of

423

Short-Term Energy Outlook Market Prices and Uncertainty Report  

U.S. Energy Information Administration (EIA)

uptick in unplanned crude oil production outages and increased tensions in the ... since May of this year, ... 2017 Levelized Costs AEO 2012 Early Release Author:

424

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

A Joint Model of the Global Crude Oil Market and the U.S.Noureddine. 2002. World crude oil and natural gas: a demandelasticity of demand for crude oil, not gasoline. Results

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

425

Short-Term Energy Outlook Market Prices and Uncertainty Report  

U.S. Energy Information Administration (EIA)

lower on November 7 compared to October 1 and nearly matching its lowest point in ... volume for the first 10 months is lagging from the same time ...

426

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

Model of the Global Crude Oil Market and the U.S. RetailNoureddine. 2002. World crude oil and natural gas: a demandanalysis of the demand for oil in the Middle East. Energy

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

427

Utility spot pricing study : Wisconsin  

E-Print Network (OSTI)

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

Caramanis, Michael C.

1982-01-01T23:59:59.000Z

428

Uncertainties in Gapped Graphene  

E-Print Network (OSTI)

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

Eylee Jung; Kwang S. Kim; DaeKil Park

2011-07-27T23:59:59.000Z

429

Sources of uncertainty in the calculation of loads on supports of piping systems  

SciTech Connect

Loads on piping systems are obtained from an analysis of the piping system. The piping system analysis involves uncertainties from various sources. These sources of uncertainties are discussed and ranges of uncertainties are illustrated by simple examples. The sources of uncertainties are summarized and assigned a judgmental ranking of the typical relative significance of the uncertainty.

Rodabaugh, E.C.

1984-06-01T23:59:59.000Z

430

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

E-Print Network (OSTI)

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

Chiyangwa, Diana Kudakwashe

2010-01-01T23:59:59.000Z

431

Appreciating Wind Energy's Probabilistic Nature within the Uncertainty Context of Electric Power System Network Planning  

Science Conference Proceedings (OSTI)

Electric power system network planning is influenced by the uncertainty in many parameters, such as future customer-demand/fossil-fuel-price parameter projections and new generation plant locations, which can generally be modeled in an approximate or ...

Daniel J. Burke, M. J. O'Malley

2013-01-01T23:59:59.000Z

432

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 Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

433

Average Commercial Price  

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

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 Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

434

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 Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

435

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 Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

436

Average Residential Price  

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

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 Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

437

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

E-Print Network (OSTI)

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

Tabors, Richard D.

1991-01-01T23:59:59.000Z

438

Revised 1997 Retail Electricity Price Forecast Principal Author: Ben Arikawa  

E-Print Network (OSTI)

Revised 1997 Retail Electricity Price Forecast March 1998 Principal Author: Ben Arikawa Electricity Energy Commission until adopted at a public meeting. #12;Revised 1997 Retail Price Forecast, December ELECTRICITY PRICE FORECAST Introduction The Electricity Analysis Office of the California Energy Commission

439

Main elements for pig price forecasting A. VIGNE M. RIEU  

E-Print Network (OSTI)

Main elements for pig price forecasting A. VIGNE M. RIEU I.T.P., Service Economie, 34, boulevard de the analysis of the past results. Forecasting consists in modelizing each component of pig price from la Gare, 31500 Toulouse The highly fluctuating variation of pig prices results from several

Recanati, Catherine

440

Montana Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.72 7.50 3.16 3.64 1967-2010 Imports Price 6.66 8.22 3.88 4.13 3.75 2.45 1989-2012 Exports Price 6.16 8.14 3.63 4.05 3.82 2.40 1989-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.42 7.71 5.63 5.17 5.11 4.23 1984-2012 Residential Price 9.91 11.45 9.50 8.64 8.80 8.06 1967-2012 Percentage of Total Residential Deliveries included in Prices 99.9 99.9 99.8 99.8 99.8 99.8 1989-2012 Commercial Price 9.76 11.32 9.41 8.54 8.66 7.98 1967-2012 Percentage of Total Commercial Deliveries included in Prices 78.5 79.6 49.2 54.6 53.3 52.9 1990-2012 Industrial Price 9.75 11.04 9.06 8.07 8.13 7.54 1997-2012 Percentage of Total Industrial Deliveries included in Prices

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Louisiana Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 7.02 8.73 3.82 4.23 1967-2010 Imports Price 6.98 9.76 3.89 4.84 7.57 7.98 1989-2012 Exports Price -- -- -- 7.07 9.63 11.80 2007-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.22 9.58 5.96 5.43 5.67 3.48 1984-2012 Residential Price 14.20 15.49 13.15 11.73 11.37 11.54 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 11.83 13.52 10.46 9.88 9.36 8.44 1967-2012 Percentage of Total Commercial Deliveries included in Prices 98.0 98.4 92.0 85.9 83.6 78.0 1990-2012 Industrial Price 7.08 9.32 4.31 4.68 4.25 2.96 1997-2012 Percentage of Total Industrial Deliveries included in Prices

442

Nebraska Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 4.86 6.22 2.97 3.98 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.67 8.12 5.87 5.62 5.11 4.31 1984-2012 Residential Price 11.15 11.11 9.34 8.95 8.84 8.68 1967-2012 Percentage of Total Residential Deliveries included in Prices 85.7 87.1 87.8 87.4 87.3 85.8 1989-2012 Commercial Price 9.16 9.62 7.44 7.08 6.69 6.19 1967-2012 Percentage of Total Commercial Deliveries included in Prices 63.9 57.5 61.3 60.6 60.6 55.8 1990-2012 Industrial Price 7.97 9.12 6.02 5.85 5.61 4.34 1997-2012 Percentage of Total Industrial Deliveries included in Prices 9.7 10.2 8.9 8.2 7.6 6.8 1997-2012 Vehicle Fuel Price 15.10 15.29 1994-2012 Electric Power Price

443

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 Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

444

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 Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

445

Consumer Prices During  

Gasoline and Diesel Fuel Update (EIA)

City Gate City Gate City gate prices represent the total cost paid by gas distribu- tion companies for gas received at the point where the gas is physically transferred from a pipeline company or trans- mission system. This price is intended to reflect all charges for the acquisition, storage, and transportation of gas as well as other charges associated with the LDC's obtaining the gas for sale to consumers. Prices paid at the city gate by local distribution companies rose substantially between 1995 and 1996, climbing from $2.78 per thousand cubic feet to $3.27, an increase of 18 percent. Residential Residential consumers pay the highest price for natural gas. It increased to $6.34 per thousand cubic feet from the 1995 price of $6.06 per thousand cubic feet. However, the 1996 price was 1 percent lower than the 1994 price. In recent years, only modest changes in constant dollars have been

446

Connecticut Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Connecticut Connecticut Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Bridgeport BridgeportGasPrices.com Automotive.com MapQuest.com Hartford HartfordGasPrices.com Automotive.com MapQuest.com New Haven NewHavenGasPrices.com Automotive.com MapQuest.com Stamford Automotive.com MapQuest.com Waterbury Automotive.com MapQuest.com West Hartford Automotive.com MapQuest.com Other Connecticut Cities ConnecticutGasPrices.com (search by city or ZIP code) - GasBuddy.com Connecticut Gas Prices (selected cities) - GasBuddy.com Connecticut Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Connecticut Cities - MapQuest

447

Average Residential Price  

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

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 Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

448

Fundamentals Explain High Prices  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: One can use a simple model to deal with price/fundamental relationships. This one predicts monthly average WTI price as a function of OECD total petroleum stock deviations from the normal levels . The graph shows the model as it begins predicting prices in 1992. It shows how well the model has predicted not only the direction, but the magnitude of prices over this 8+ year period. While the model is simple and not perfect, it does predict the overall trends and, in particular, the recent rise in prices. It also shows that prices may have over-shot the fundamental balance for a while -- at least partially due to speculative concerns over Mideast tensions, winter supply adequacy, and Iraq's export policies. Prices now seem to be correcting, and may even undershoot briefly

449

Energy prices, production  

E-Print Network (OSTI)

on 0 1 2 3 4 5 6 7 8 9 price U K P ./kW h CHP adoption electyricity price to gas price ratio Figure 3. Energy price and CHP annual adoption (UK). Source: DTI (2002b) -5.00% 0.00% 5.00% 10.00% 15.00% 20... .00% 199119921993199419951996199719981999200020012002 an nu al g ro w th r at e in C H P a do pt io n 0 0.2 0.4 0.6 0.8 1 1.2 1.4 price U K P ./kW h CHP adoption Gas price 10 Gas prices leveled off from 1996 onwards and then increased considerably growing by 33% during 1999-2002. In recent...

Bonilla, David

450

Advanced Coal Wind Hybrid: Economic Analysis  

E-Print Network (OSTI)

Coal prices have been far less volatile than natural gas prices.Coal Prices Figure 9 is similar to Figure 8 except the natural gas pricesCoal Wind Hybrid: Economic Analysis interested in natural gas prices

Phadke, Amol

2008-01-01T23:59:59.000Z

451

RUMINATIONS ON NDA MEASUREMENT UNCERTAINTY COMPARED TO DA UNCERTAINTY  

Science Conference Proceedings (OSTI)

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.

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

2010-06-17T23:59:59.000Z

452

SMART: A Stochastic Multiscale Model for the Analysis of Energy Resources, Technology, and Policy  

Science Conference Proceedings (OSTI)

We address the problem of modeling energy resource allocation, including dispatch, storage, and the long-term investments in new technologies, capturing different sources of uncertainty such as energy from wind, demands, prices, and rainfall. We also ... Keywords: analysis of algorithms, artificial intelligence, queues, simulation, statistical analysis

Warren B. Powell; Abraham George; Hugo Simão; Warren Scott; Alan Lamont; Jeffrey Stewart

2012-10-01T23:59:59.000Z

453

Weighing the Costs and Benefits of Renewables Portfolio Standards: A Comparative Analysis of State-Level Policy Impact Projections  

E-Print Network (OSTI)

An Overview of Alternative Fossil Fuel Price and Carbonof renewable technology cost, fossil fuel price uncertainty,energy, including the fossil fuel hedge value of renewable

Chen, Cliff; Wiser, Ryan; Bolinger, Mark

2007-01-01T23:59:59.000Z

454

Missouri Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 1967-1997 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.53 8.03 7.06 6.17 5.85 5.27 1984-2012 Residential Price 13.42 13.36 12.61 11.66 12.02 12.25 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 11.82 12.02 10.81 10.28 9.99 9.54 1967-2012 Percentage of Total Commercial Deliveries included in Prices 76.9 77.5 76.7 76.5 73.1 69.2 1990-2012 Industrial Price 10.84 11.32 9.55 8.70 8.54 7.93 1997-2012 Percentage of Total Industrial Deliveries included in Prices 12.8 13.9 13.2 13.1 13.4 12.5 1997-2012 Vehicle Fuel Price 8.44 8.66 7.86 6.34 6.11 5.64 1994-2012

455

Arkansas Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 6.61 8.72 3.43 3.84 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.55 8.88 7.86 6.76 6.27 5.36 1984-2012 Residential Price 13.08 14.09 13.39 11.53 11.46 11.82 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 10.07 11.32 10.72 8.89 8.90 7.99 1967-2012 Percentage of Total Commercial Deliveries included in Prices 70.4 64.5 59.4 55.6 51.5 40.2 1990-2012 Industrial Price 9.51 10.56 8.44 7.28 7.44 6.38 1997-2012 Percentage of Total Industrial Deliveries included in Prices 4.2 3.9 3.7 2.8 2.1 1.9 1997-2012 Vehicle Fuel Price 8.39 -- -- -- -- 9.04 1994-2012

456

Iowa Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.80 8.28 5.62 5.69 5.27 4.84 1984-2012 Residential Price 11.76 11.91 9.83 9.57 9.54 9.46 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 9.97 10.25 7.88 7.81 7.55 7.13 1967-2012 Percentage of Total Commercial Deliveries included in Prices 77.7 75.8 72.5 72.0 72.1 72.3 1990-2012 Industrial Price 8.56 9.32 6.23 6.10 5.78 4.70 1997-2012 Percentage of Total Industrial Deliveries included in Prices 6.5 6.6 6.4 5.8 5.5 5.2 1997-2012 Vehicle Fuel Price 11.68 -- -- -- -- -- 1990-2012 Electric Power Price 7.73 W W W W 3.84 1997-2012

457

Maine Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 7.57 9.77 4.48 4.94 4.40 3.45 1999-2012 Exports Price -- -- 5.62 4.53 4.46 4.30 2007-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 10.46 13.47 8.64 8.19 8.14 7.73 1984-2012 Residential Price 16.90 17.47 16.43 14.14 14.20 15.94 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 99.9 100.0 100.0 1989-2012 Commercial Price 14.82 15.87 13.94 11.71 11.69 12.22 1967-2012 Percentage of Total Commercial Deliveries included in Prices 46.2 45.0 51.0 45.0 45.8 42.1 1990-2012 Industrial Price 13.40 14.89 9.12 11.23 10.89 10.35 1997-2012 Percentage of Total Industrial Deliveries included in Prices 0.8 0.8 1.2 0.6 0.5 0.4 1997-2012

458

Idaho Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 6.31 7.88 3.86 4.19 3.90 2.59 1989-2012 Exports Price -- 7.43 4.49 5.85 4.74 -- 1999-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.68 7.48 5.63 4.82 4.65 4.07 1984-2012 Residential Price 11.47 11.07 10.54 8.95 8.80 8.26 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 10.67 10.28 9.77 8.21 8.09 7.35 1967-2012 Percentage of Total Commercial Deliveries included in Prices 84.8 86.0 83.7 82.0 80.8 77.0 1990-2012 Industrial Price 9.39 9.18 8.53 6.39 6.36 5.73 1997-2012 Percentage of Total Industrial Deliveries included in Prices 2.0 1.9 1.7 1.8 2.0 1.9 1997-2012

459

Maryland Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price NA NA NA NA 1967-2010 Imports Price 7.25 9.09 4.05 5.37 5.30 13.82 1999-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 9.24 10.23 8.02 6.49 6.26 5.67 1984-2012 Residential Price 15.17 16.07 13.73 12.44 12.10 12.17 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 79.3 77.0 1989-2012 Commercial Price 12.30 13.12 10.87 9.87 10.29 10.00 1967-2012 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 27.3 24.7 1990-2012 Industrial Price 11.59 13.46 10.70 9.05 8.61 8.01 1997-2012 Percentage of Total Industrial Deliveries included in Prices 7.8 6.3 5.3 5.3 5.5 5.1 1997-2012

460

Alabama Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 7.44 9.65 4.32 4.46 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.78 9.84 7.61 6.46 5.80 5.18 1984-2012 Residential Price 18.14 18.30 18.12 15.79 15.08 16.20 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 15.06 15.58 14.94 13.34 12.36 12.55 1967-2012 Percentage of Total Commercial Deliveries included in Prices 79.8 80.2 78.8 79.3 78.9 76.2 1990-2012 Industrial Price 8.70 10.57 6.48 6.64 5.57 4.35 1997-2012 Percentage of Total Industrial Deliveries included in Prices 24.0 27.2 27.9 23.7 23.5 22.1 1997-2012 Vehicle Fuel Price -- 17.32 19.17 16.24 11.45 17.99 1990-2012

Note: This page contains sample records for the topic "analysis price uncertainty" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Massachusetts Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 7.32 10.34 5.90 4.86 4.77 3.69 1989-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 9.34 10.29 8.29 7.74 7.04 6.03 1984-2012 Residential Price 16.99 17.18 14.85 14.53 13.81 13.22 1967-2012 Percentage of Total Residential Deliveries included in Prices 99.9 85.0 85.6 85.4 89.3 87.8 1989-2012 Commercial Price 15.08 15.25 12.85 12.00 11.68 10.68 1967-2012 Percentage of Total Commercial Deliveries included in Prices 65.3 57.9 56.9 52.1 50.0 48.6 1990-2012 Industrial Price 14.83 15.23 12.07 10.41 10.14 9.82 1997-2012 Percentage of Total Industrial Deliveries included in Prices 29.9 20.6 21.1 19.4 20.6 17.7 1997-2012 Vehicle Fuel Price 12.84 13.80 12.99 12.48 4.28 14.81 1990-2012

462

Vermont Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 8.51 9.74 6.34 6.54 5.81 4.90 1989-2012 Pipeline and Distribution Use Price 1982-2005 Citygate Price 10.03 10.66 9.33 8.29 7.98 6.63 1984-2012 Residential Price 15.99 18.31 17.29 16.14 16.17 16.73 1980-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 12.79 14.31 12.96 11.82 11.90 12.09 1980-2012 Percentage of Total Commercial Deliveries included in Prices 100 100 100 100 100 100 1990-2012 Industrial Price 9.08 9.60 7.93 6.57 6.09 4.89 1997-2012 Percentage of Total Industrial Deliveries included in Prices 78.0 79.6 77.9 77.1 80.9 100.0 1997-2012 Electric Power Price 7.72 9.14 5.66 5.73 5.26 4.14 1997-2012

463

Pennsylvania Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price NA NA NA NA 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 9.35 10.39 7.81 7.04 6.28 5.52 1984-2012 Residential Price 14.66 16.22 14.74 12.90 12.46 11.99 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 91.2 88.6 1989-2012 Commercial Price 12.77 14.29 11.83 10.47 10.42 10.24 1967-2012 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 48.5 42.1 1990-2012 Industrial Price 10.64 12.09 9.19 8.23 9.86 9.58 1997-2012 Percentage of Total Industrial Deliveries included in Prices 5.4 5.7 4.5 3.8 2.0 1.3 1997-2012 Vehicle Fuel Price 10.83 8.30 5.15 3.76 3.40 7.96 1990-2012

464

Indiana Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.78 7.58 4.05 4.13 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.83 8.94 5.59 5.52 4.97 4.23 1984-2012 Residential Price 11.29 12.65 10.81 8.63 9.46 8.94 1967-2012 Percentage of Total Residential Deliveries included in Prices 96.2 95.0 93.6 94.1 94.6 94.5 1989-2012 Commercial Price 10.20 11.14 9.18 7.55 8.04 7.68 1967-2012 Percentage of Total Commercial Deliveries included in Prices 78.1 77.9 73.9 72.5 70.2 67.5 1990-2012 Industrial Price 8.45 10.48 6.91 5.65 6.53 6.19 1997-2012 Percentage of Total Industrial Deliveries included in Prices 7.4 6.7 7.0 5.6 3.5 1.9 1997-2012 Vehicle Fuel Price 6.09 7.94 4.08 5.19 13.24 12.29 1990-2012

465

Florida Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price NA NA NA NA 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.97 9.73 5.76 5.49 5.07 3.93 1984-2012 Residential Price 20.61 21.07 20.18 17.89 18.16 18.31 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 98.0 97.7 1989-2012 Commercial Price 13.07 14.45 11.09 10.60 11.14 10.41 1967-2012 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 38.5 37.0 1990-2012 Industrial Price 10.56 11.72 9.41 8.33 8.07 6.96 1997-2012 Percentage of Total Industrial Deliveries included in Prices 3.1 3.0 3.2 3.0 3.0 2.7 1997-2012 Vehicle Fuel Price 12.82 15.56 13.16 17.98 5.56 9.83 1989-2012

466

Utah Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Utah Utah Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Layton LaytonGasPrices.com Automotive.com MapQuest.com Ogden OgdenGasPrices.com Automotive.com MapQuest.com Orem OremGasPrices.com Automotive.com MapQuest.com Provo ProvoGasPrices.com Automotive.com MapQuest.com Salt Lake City SaltLakeCityGasPrices.com Automotive.com MapQuest.com Sandy SandyGasPrices.com Automotive.com MapQuest.com West Jordan WestJordanGasPrices.com Automotive.com MapQuest.com West Valley City WestValleyCityGasPrices.com Other Utah Cities UtahGasPrices.com (search by city or ZIP code) - GasBuddy.com Utah Gas Prices (selected cities) - GasBuddy.com

467

Connecticut Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.67 10.24 6.81 6.58 5.92 5.12 1984-2012 Residential Price 16.39 17.85 14.81 14.93 13.83 14.17 1967-2012 Percentage of Total Residential Deliveries included in Prices 98.2 97.7 97.5 97.3 96.8 96.7 1989-2012 Commercial Price 12.61 13.81 9.92 9.55 8.48 8.40 1967-2012 Percentage of Total Commercial Deliveries included in Prices 71.5 70.7 69.0 65.4 65.4 65.1 1990-2012 Industrial Price 10.54 12.63 8.44 9.60 9.16 8.83 1997-2012 Percentage of Total Industrial Deliveries included in Prices 50.0 47.3 37.5 31.1 31.0 32.3 1997-2012 Vehicle Fuel Price 20.57 24.04 15.26 16.31 18.59 13.70 1992-2012 Electric Power Price 7.81 10.48 4.89 5.70 5.09 3.99 1997-2012

468

Oregon Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.27 5.33 4.00 4.92 1979-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.14 8.82 7.79 6.78 5.84 5.21 1984-2012 Residential Price 14.65 13.89 14.52 12.49 11.76 11.22 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 12.36 11.57 11.86 10.10 9.60 8.91 1967-2012 Percentage of Total Commercial Deliveries included in Prices 98.5 98.5 98.4 97.4 97.4 96.9 1990-2012 Industrial Price 9.30 9.07 9.70 7.05 6.84 5.87 1997-2012 Percentage of Total Industrial Deliveries included in Prices 21.8 20.1 18.9 17.1 17.1 16.7 1997-2012 Vehicle Fuel Price 6.59 8.03 7.11 5.61 4.23 4.57 1992-2012

469

Arizona Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.98 7.09 3.19 4.11 1967-2010 Exports Price 6.94 8.09 3.79 4.57 4.28 3.07 1989-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.25 8.49 7.21 6.59 5.91 4.68 1984-2012 Residential Price 17.21 17.60 17.65 15.87 15.04 15.75 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 12.84 13.01 12.15 10.72 9.99 9.35 1967-2012 Percentage of Total Commercial Deliveries included in Prices 93.4 93.1 88.0 88.7 87.8 86.6 1990-2012 Industrial Price 10.49 10.47 8.19 7.54 6.86 5.78 1997-2012 Percentage of Total Industrial Deliveries included in Prices 31.3 29.6 29.1 25.5 24.2 21.4 1997-2012

470

Colorado Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 4.57 6.94 3.21 3.96 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.23 6.98 5.09 5.26 4.94 4.26 1984-2012 Residential Price 8.84 9.77 8.80 8.13 8.25 8.31 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 8.10 9.01 7.56 7.58 7.84 7.58 1967-2012 Percentage of Total Commercial Deliveries included in Prices 95.7 95.2 94.8 94.6 93.8 92.2 1990-2012 Industrial Price 7.21 8.76 6.57 5.84 6.42 5.79 1997-2012 Percentage of Total Industrial Deliveries included in Prices 0.5 0.6 0.5 5.2