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they are not comprehensive nor are they the most current set.
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1

Solar Energy Market Forecast | Open Energy Information  

Open Energy Info (EERE)

Solar Energy Market Forecast Solar Energy Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast Agency/Company /Organization: United States Department of Energy Sector: Energy Focus Area: Solar Topics: Market analysis, Technology characterizations Resource Type: Publications Website: giffords.house.gov/DOE%20Perspective%20on%20Solar%20Market%20Evolution References: Solar Energy Market Forecast[1] Summary " Energy markets / forecasts DOE Solar America Initiative overview Capital market investments in solar Solar photovoltaic (PV) sector overview PV prices and costs PV market evolution Market evolution considerations Balance of system costs Silicon 'normalization' Solar system value drivers Solar market forecast Additional resources"

2

ANL Wind Power Forecasting and Electricity Markets | Open Energy  

Open Energy Info (EERE)

ANL Wind Power Forecasting and Electricity Markets ANL Wind Power Forecasting and Electricity Markets Jump to: navigation, search Logo: Wind Power Forecasting and Electricity Markets Name Wind Power Forecasting and Electricity Markets Agency/Company /Organization Argonne National Laboratory Partner Institute for Systems and Computer Engineering of Porto (INESC Porto) in Portugal, Midwest Independent System Operator and Horizon Wind Energy LLC, funded by U.S. Department of Energy Sector Energy Focus Area Wind Topics Pathways analysis, Technology characterizations Resource Type Software/modeling tools Website http://www.dis.anl.gov/project References Argonne National Laboratory: Wind Power Forecasting and Electricity Markets[1] Abstract To improve wind power forecasting and its use in power system and electricity market operations Argonne National Laboratory has assembled a team of experts in wind power forecasting, electricity market modeling, wind farm development, and power system operations.

3

Price and Load Forecasting in Volatile Energy Markets  

Science Conference Proceedings (OSTI)

With daily news stories about wildly fluctuating electricity prices and soaring natural gas prices, forecasters' responsibilities are expanding, visibility is increasing, and pressure exists to produce more frequent forecasts and more kinds of forecasts. The proceedings of EPRI's 13th Forecasting Symposium, held November 13-15 in Nashville, Tennessee, address current forecasting issues and developments, as well as explain the role that forecasters have played in recent events in energy markets.

2001-12-05T23:59:59.000Z

4

Mathematical and computer modelling reports: Modeling and forecasting energy markets with the intermediate future forecasting system  

Science Conference Proceedings (OSTI)

This paper describes the Intermediate Future Forecasting System (IFFS), which is the model used to forecast integrated energy markets by the U.S. Energy Information Administration. The model contains representations of supply and demand for all of the ...

Frederic H. Murphy; John J. Conti; Susan H. Shaw; Reginald Sanders

1989-09-01T23:59:59.000Z

5

Forecasting next-day price of electricity in the Spanish energy market using artificial neural networks  

Science Conference Proceedings (OSTI)

In this paper, next-day hourly forecasts are calculated for the energy price in the electricity production market of Spain. The methodology used to achieve these forecasts is based on artificial neural networks, which have been used successfully in recent ... Keywords: ART network, Backpropagation network, Box-Jenkins, Electricity market, Neural networks, Time series forecasting

Raúl Pino; José Parreno; Alberto Gomez; Paolo Priore

2008-02-01T23:59:59.000Z

6

Forecasting the Market Penetration of Energy Conservation Technologies: The Decision Criteria for Choosing a Forecasting Model  

E-Print Network (OSTI)

An important determinant of our energy future is the rate at which energy conservation technologies, once developed, are put into use. At Synergic Resources Corporation, we have adapted and applied a methodology to forecast the use of conservation technologies. This paper briefly discusses the observed patterns of the diffusion of new' technologies and the determinants (both sociological and economic) which have been proposed to explain the variation in the diffusion rates. Existing market penetration models are reviewed and their capability to forecast the use of conservation technologies is assessed using a set of criteria developed for this purpose. The reasoning behind the choice of criteria is discussed. The criteria includes the range of hypothesized influences to market penetration that are incorporated into the models and the applicability of the available parameter estimates. The attributes of our methodology and forecasting model choice (a behavioral lag equation developed by Mathtech, Inc.), are displayed using a list of the judgment criteria. This method was used to forecast the use of electricity conservation technologies in industries located in the Pacific Northwest for the Bonneville Power Administration.

Lang, K.

1982-01-01T23:59:59.000Z

7

Dynamic filter weights neural network model integrated with differential evolution for day-ahead price forecasting in energy market  

Science Conference Proceedings (OSTI)

In this paper a new dynamic model for forecasting electricity prices from 1 to 24h in advance is proposed. The model is a dynamic filter weight Adaline using a sliding mode weight adaptation technique. The filter weights for this neuron constitute of ... Keywords: Differential evolution, Dynamic filter weights neuron, Energy market, Local linear wavelet neural network, Sliding mode control

S. Chakravarty; P. K. Dash

2011-09-01T23:59:59.000Z

8

Voluntary Green Power Market Forecast through 2015  

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

158 158 May 2010 Voluntary Green Power Market Forecast through 2015 Lori Bird National Renewable Energy Laboratory Ed Holt Ed Holt & Associates, Inc. Jenny Sumner and Claire Kreycik National Renewable Energy Laboratory National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Operated by the Alliance for Sustainable Energy, LLC Contract No. DE-AC36-08-GO28308 Technical Report NREL/TP-6A2-48158 May 2010 Voluntary Green Power Market Forecast through 2015 Lori Bird National Renewable Energy Laboratory Ed Holt Ed Holt & Associates, Inc. Jenny Sumner and Claire Kreycik National Renewable Energy Laboratory

9

Forecasting consumer products using prediction markets  

E-Print Network (OSTI)

Prediction Markets hold the promise of improving the forecasting process. Research has shown that Prediction Markets can develop more accurate forecasts than polls or experts. Our research concentrated on analyzing Prediction ...

Trepte, Kai

2009-01-01T23:59:59.000Z

10

An evaluation of market penetration forecasting methodologies for new residential and commercial energy technologies  

SciTech Connect

Forecasting market penetration is an essential step in the development and assessment of new technologies. This report reviews several methodologies that are available for market penetration forecasting. The primary objective of this report is to help entrepreneurs understand these methodologies and aid in the selection of one or more of them for application to a particular new technology. This report also illustrates the application of these methodologies, using examples of new technologies, such as the heat pump, drawn from the residential and commercial sector. The report concludes with a brief discussion of some considerations in selecting a forecasting methodology for a particular situation. It must be emphasized that the objective of this report is not to construct a specific market penetration model for new technologies but only to provide a comparative evaluation of methodologies that would be useful to an entrepreneur who is unfamiliar with the range of techniques available. The specific methodologies considered in this report are as follows: subjective estimation methods, market surveys, historical analogy models, time series models, econometric models, diffusion models, economic cost models, and discrete choice models. In addition to these individual methodologies, which range from the very simple to the very complex, two combination approaches are also briefly discussed: (1) the economic cost model combined with the diffusion model and (2) the discrete choice model combined with the diffusion model. This discussion of combination methodologies is not meant to be exhaustive. Rather, it is intended merely to show that many methodologies often can complement each other. A combination of two or more different approaches may be better than a single methodology alone.

Raju, P.S.; Teotia, A.P.S.

1985-05-01T23:59:59.000Z

11

Energy conservation and official UK energy forecasts  

SciTech Connect

Behind the latest United Kingdom (UK) official forecasts of energy demand are implicit assumptions about future energy-price elasticities. Mr. Pearce examines the basis of the forecasts and finds that the long-term energy-price elasticities that they imply are two or three times too low. The official forecasts substantially understate the responsiveness of demand to energy price rises. If more-realistic price elasticities were assumed, the official forecasts would imply a zero primary energy-demand growth to 2000. This raises the interesting possibility of a low energy future being brought about entirely by market forces. 15 references, 3 tables.

Pearce, D.

1980-09-01T23:59:59.000Z

12

Forecasting Wind Markets  

U.S. Energy Information Administration (EIA)

Emerging Technologies, Data, and NEM Modeling Issues in Wind Resource Supply Data and Modeling Chris Namovicz ASA Committee on Energy Statistics

13

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Title of Paper Annual Energy Outlook Forecast Evaluation Title of Paper Annual Energy Outlook Forecast Evaluation by Susan H. Holte OIAF has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Natural gas has generally been the fuel with the least accurate forecasts of consumption, production, and prices. Natural gas was the last fossil fuel to be deregulated following the strong regulation of energy markets in the 1970s and early 1980s. Even after deregulation, the behavior

14

Voluntary Green Power Market Forecast through 2015  

SciTech Connect

Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

2010-05-01T23:59:59.000Z

15

Voluntary Green Power Market Forecast through 2015  

SciTech Connect

Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

2010-05-01T23:59:59.000Z

16

Solar future: 1978. [Market forecast to 1992  

SciTech Connect

The growth in sales of solar heating equipment is discussed. Some forecasts are made for the continued market growth of collectors, pool systems, and photovoltaics. (MOW)

Butt, S.H.

1978-03-01T23:59:59.000Z

17

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

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

18

Base Resource Forecasts - Power Marketing - Sierra Nevada Region...  

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

Marketing > Base Resource Forecasts Base Resource Forecasts Note: Annual, rolling (monthly for 12 months), base resource forecasts are posted when they become available. Annual...

19

Developing electricity forecast web tool for Kosovo market  

Science Conference Proceedings (OSTI)

In this paper is presented a web tool for electricity forecast for Kosovo market for the upcoming ten years. The input data i.e. electricity generation capacities, demand and consume are taken from the document "Kosovo Energy Strategy 2009-2018" compiled ... Keywords: .NET, database, electricity forecast, internet, simulation, web

Blerim Rexha; Arben Ahmeti; Lule Ahmedi; Vjollca Komoni

2011-02-01T23:59:59.000Z

20

ENERGY DEMAND FORECAST METHODS REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400 .......................................................................................................................................1-1 ENERGY DEMAND FORECASTING AT THE CALIFORNIA ENERGY COMMISSION: AN OVERVIEW

Note: This page contains sample records for the topic "forecasted energy market" 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

Model documentation: electricity market module. [15 year forecasts  

SciTech Connect

This report documents the electricity market model. This model is a component of the Intermediate Future Forecasting System (IFFS), the energy market model used to provide projections of energy markets up to 15 years into the future. The electricity market model was developed by the Supply Analysis and Integration Branch as part of building the larger system. This report is written for an audience consisting of mathematical economists, statisticians, operations research analysts, and utility planners. This report contains an overview and a mathematical specification of the electricity market module. It includes a description of the model logic and the individual subroutines in the computer code. A companion document Intermediate Future Forecasting System: Executive Summary (DOE/EIA-430) provides an overview of the components in IFFS and their linkages. 22 figures, 2 tables.

Sanders, R.C.; Murphy, F.H.

1984-12-01T23:59:59.000Z

22

Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations  

E-Print Network (OSTI)

Power Forecasting in Five U.S. Electricity Markets MISO NYISO PJM ERCOT CAISO Peak load 109,157 MW (7 ........................................................................................... 18 4 WIND POWER FORECASTING AND ELECTRICITY MARKET OPERATIONS............................................................ 18 4-1 Market Operation and Wind Power Forecasting in Five U.S. Electricity Markets .......... 21 #12

Kemner, Ken

23

Wind power forecasting in U.S. electricity markets.  

Science Conference Proceedings (OSTI)

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts.

Botterud, A.; Wang, J.; Miranda, V.; Bessa, R. J.; Decision and Information Sciences; INESC Porto

2010-04-01T23:59:59.000Z

24

Wind power forecasting in U.S. Electricity markets  

Science Conference Proceedings (OSTI)

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. (author)

Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro; Bessa, Ricardo J.

2010-04-15T23:59:59.000Z

25

Forecast Energy | Open Energy Information  

Open Energy Info (EERE)

Forecast Energy Forecast Energy Jump to: navigation, search Name Forecast Energy Address 2320 Marinship Way, Suite 300 Place Sausalito, California Zip 94965 Sector Services Product Intelligent Monitoring and Forecasting Services Year founded 2010 Number of employees 11-50 Company Type For profit Website http://www.forecastenergy.net Coordinates 37.865647°, -122.496315° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.865647,"lon":-122.496315,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

26

Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence  

E-Print Network (OSTI)

Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence Department of Computer Science on the application of neural networks in forecasting stock market prices. With their ability to discover patterns. Section 3 covers current analytical and computer methods used to forecast stock market prices

Lawrence, Ramon

27

Electricity Market Price Forecasting: Neural Networks versus Weighted-Distance Nearest Neighbours  

E-Print Network (OSTI)

In today's deregulated markets, forecasting energy prices is becoming more and more important. In the short term, expected price pro les help market participants to determine their bidding strategies.

A. Troncoso; J.M. Riquelme; Alicia Troncoso Lora; J.L. Martínez; A. Gómez; Jose Riquelme Santos; Jesus Riquelme Santos

2001-01-01T23:59:59.000Z

28

Customization and Marketing of Monsoon Forecasts A CSIRCMMACS Synergy  

E-Print Network (OSTI)

Customization and Marketing of Monsoon Forecasts A CSIRCMMACS Synergy Criteria for Technical forecasts of monsoon can significantly aid many sectors like agriculture, power and production industries to the operational forecast, to develop and deliver customized monsoon forecasts based on user need is required

Swathi, P S

29

Long-term Stock Market Forecasting using Gaussian Processes  

E-Print Network (OSTI)

Address3 email4 Abstract5 Forecasting stock market prices is an attractive topic to researchers from6 to analyze18 and forecast stock prices and index changes. The accuracy of these techniques is still an19-term predictions in stock prices.32 33 1.2 Motivation34 In stock market, investors need long-term forecasting

de Freitas, Nando

30

Time Series Analysis and Forecasting in Stock Market Investments  

E-Print Network (OSTI)

Time Series Analysis and Forecasting in Stock Market Investments Ted Chi-Wei Fung Department and forecasting have been used as methods to help precisely on the task of stock market prediction by using past data. This paper will discuss three different models to create a time series analysis and forecast

Zanibbi, Richard

31

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Robert P. Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast

32

Annual Energy Outlook 2001 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Economic Growth World Oil Prices Total Energy Consumption Residential and Commercial Sectors Industrial Sector Transportation Sector Electricity Natural Gas Petroleum Coal Three other organizations—Standard & Poor’s DRI (DRI), the WEFA Group (WEFA), and the Gas Research Institute (GRI) [95]—also produce comprehensive energy projections with a time horizon similar to that of AEO2001. The most recent projections from those organizations (DRI, Spring/Summer 2000; WEFA, 1st Quarter 2000; GRI, January 2000), as well as other forecasts that concentrate on petroleum, natural gas, and international oil markets, are compared here with the AEO2001 projections. Economic Growth Differences in long-run economic forecasts can be traced primarily to

33

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Highlights Highlights World energy consumption is projected to increase by 57 percent from 2002 to 2025. Much of the growth in worldwide energy use in the IEO2005 reference case forecast is expected in the countries with emerging economies. Figure 1. World Marketed Energy Consumptiion by Region, 1970-2025. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data In the International Energy Outlook 2005 (IEO2005) reference case, world marketed energy consumption is projected to increase on average by 2.0 percent per year over the 23-year forecast horizon from 2002 to 2025—slightly lower than the 2.2-percent average annual growth rate from 1970 to 2002. Worldwide, total energy use is projected to grow from 412 quadrillion British thermal units (Btu) in 2002 to 553 quadrillion Btu in

34

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation by Susan H. Holte In this paper, the Office of Integrated Analysis and Forecasting (OIAF) of the Energy Information Administration (EIA) evaluates the projections published in the Annual Energy Outlook (AEO), (1) by comparing the projections from the Annual Energy Outlook 1982 through the Annual Energy Outlook 2001 with actual historical values. A set of major consumption, production, net import, price, economic, and carbon dioxide emissions variables are included in the evaluation, updating similar papers from previous years. These evaluations also present the reasons and rationales for significant differences. The Office of Integrated Analysis and Forecasting has been providing an

35

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sánchez The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors,

36

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sanchez by Esmeralda Sanchez Errata -(7/14/04) The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors, expressed as the percentage difference between the Reference Case projection and actual historic value, shown for every AEO and for each year in the forecast horizon (for a given variable). The historical data are typically taken from the Annual Energy Review (AER). The last column of Table 1 provides a summary of the most recent average absolute forecast errors. The calculation of the forecast error is shown in more detail in Tables 2 through 18. Because data for coal prices to electric generating plants were not available from the AER, data from the Monthly Energy Review (MER), July 2003 were used.

37

Bloomberg New Energy Finance Carbon Markets formerly New Energy...  

Open Energy Info (EERE)

London-based carbon markets division of New Energy Finance which provides analysis, price forecasting, consultancy and risk management services relating to carbon. References...

38

A Forecast for the California Labor Market  

E-Print Network (OSTI)

issue for the state. A Forecast for the California Laborto Go? ” The UCLA Anderson Forecast for the Nation andAngeles: UCLA Anderson Forecast: Nation 1.1 – 1.9. Dhawan,

Mitchell, Daniel J. B.

2001-01-01T23:59:59.000Z

39

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Table 2. Total Energy Consumption, Actual vs. Forecasts Table 3. Total Petroleum Consumption, Actual vs. Forecasts Table 4. Total Natural Gas Consumption, Actual vs. Forecasts Table 5. Total Coal Consumption, Actual vs. Forecasts Table 6. Total Electricity Sales, Actual vs. Forecasts Table 7. Crude Oil Production, Actual vs. Forecasts Table 8. Natural Gas Production, Actual vs. Forecasts Table 9. Coal Production, Actual vs. Forecasts Table 10. Net Petroleum Imports, Actual vs. Forecasts Table 11. Net Natural Gas Imports, Actual vs. Forecasts Table 12. Net Coal Exports, Actual vs. Forecasts Table 13. World Oil Prices, Actual vs. Forecasts Table 14. Natural Gas Wellhead Prices, Actual vs. Forecasts Table 15. Coal Prices to Electric Utilities, Actual vs. Forecasts

40

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand The demand forecast is the combined product of the hard work and expertise of numerous California Energy previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

Note: This page contains sample records for the topic "forecasted energy market" 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

Evaluation of errors in national energy forecasts.  

E-Print Network (OSTI)

??Energy forecasts are widely used by the U.S. government, politicians, think tanks, and utility companies. While short-term forecasts were reasonably accurate, medium and long-range forecasts… (more)

Sakva, Denys

2005-01-01T23:59:59.000Z

42

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand.Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

43

Energy forecasting: the troubled past of looking the future  

SciTech Connect

Energy forecasts have hardly been distinguished by their accuracy. Why forecasts go awry, and the impact these prominent tools have, is explored. A brief review of the record is given. Because of their allure, their popularity in he media, and their usefulness as tools in political battles, forecasts have played a significant role so far. The danger is that they represent and enhance a fix 'em up, tinkering approach, to the detriment of more efficient free-market policies.

Kutler, E.

1986-01-01T23:59:59.000Z

44

Market penetration of new energy technologies  

SciTech Connect

This report examines the characteristics, advantages, disadvantages, and, for some, the mathematical formulas of forecasting methods that can be used to forecast the market penetration of renewable energy technologies. Among the methods studied are subjective estimation, market surveys, historical analogy models, cost models, diffusion models, time-series models, and econometric models. Some of these forecasting methods are more effective than others at different developmental stages of new technologies.

Packey, D.J.

1993-02-01T23:59:59.000Z

45

Annual Energy Outlook with Projections to 2025-Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2004 with Projections to 2025 Forecast Comparisons Index (click to jump links) Economic Growth World Oil Prices Total Energy Consumption Electricity Natural Gas Petroleum Coal The AEO2004 forecast period extends through 2025. One other organization—Global Insight, Incorporated (GII)—produces a comprehensive energy projection with a similar time horizon. Several others provide forecasts that address one or more aspects of energy markets over different time horizons. Recent projections from GII and others are compared here with the AEO2004 projections. Economic Growth Printer Friendly Version Average annual percentage growth Forecast 2002-2008 2002-2013 2002-2025 AEO2003 3.2 3.3 3.1 AEO2004 Reference 3.3 3.2 3.0

46

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Market and STEO Error Forecast Error from 1998 to 2003 (2 Futures Market and STEO Error Forecast Error from 1998to 2003 (Months 13- Forecast from 1998 to 2003 (Months 1-12)

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

2005-01-01T23:59:59.000Z

47

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: * Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the

48

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast. Miguel Garcia

49

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Energy Consumption by End-Use Sector Energy Consumption by End-Use Sector In the IEO2005 projections, end-use energy consumption in the residential, commercial, industrial, and transportation sectors varies widely among regions and from country to country. One way of looking at the future of world energy markets is to consider trends in energy consumption at the end-use sector level. With the exception of the transportation sector, which is almost universally dominated by petroleum products at present, the mix of energy use in the residential, commercial, and industrial sectors can vary widely from country to country, depending on a combination of regional factors, such as the availability of energy resources, the level of economic development, and political, social, and demographic factors. This chapter outlines the International Energy Outlook 2005 (IEO2005) forecast for regional energy consumption by end-use sector.

50

Building Energy Software Tools Directory: Energy Usage Forecasts  

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

Alphabetically Tools by Platform PC Mac UNIX Internet Tools by Country Related Links Energy Usage Forecasts Energy Usage Forecasts Quick and easy web-based tool that provides...

51

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Analysis Papers > Annual Energy Outlook Forecast Evaluation Analysis Papers > Annual Energy Outlook Forecast Evaluation Release Date: February 2005 Next Release Date: February 2006 Printer-friendly version Annual Energy Outlook Forecast Evaluation* Table 1.Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Printer Friendly Version Average Absolute Percent Error Variable AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 AEO82 to AEO2004 Consumption Total Energy Consumption 1.9 2.0 2.1 2.1 2.1 2.1 Total Petroleum Consumption 2.9 3.0 3.1 3.1 3.0 2.9 Total Natural Gas Consumption 7.3 7.1 7.1 6.7 6.4 6.5 Total Coal Consumption 3.1 3.3 3.5 3.6 3.7 3.8 Total Electricity Sales 1.9 2.0 2.3 2.3 2.3 2.4 Production Crude Oil Production 4.5 4.5 4.5 4.5 4.6 4.7

52

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

53

Annual Energy Outlook Forecast Evaluation-Table 1  

Annual Energy Outlook 2012 (EIA)

Annual Energy Outlook Forecast Evaluation > Table 1 Annual Energy Outlook Forecast Evaluation Table 1. Comparison of Absolute Percent Errors for AEO Forecast Evaluation, 1996 to...

54

Mid-range energy-forecasting system: structure, forecasts, and critique  

SciTech Connect

The Mid-Range Energy Forecasting System (MEFS) is a large-scale, interdisciplinary model of the US energy system maintained by the US Department of Energy. MEFS provides long-run regional forecasts of delivered prices for electricity, coal, gasoline, residual, distillate, and natural gas. A number of sets of MEFS forecasts are usually issued, each set corresponding to a different scenario. Because it forecasts prices and since these forecasts are regularly disseminated, MEFS is of considerable practical interest. A critical guide of the model's output for potential users is provided in this paper. The model's logic is described, the latest forecasts from MEFS are presented, and the reasonableness of both the forecasts and the methodology are critically evaluated. The manner in which MEFS interfaces with the Oil Market Simulation Model, which forecasts crude oil price, is also discussed. The evaluation concludes that while there are serious problems with MEFS, selective use can prove very helpful. 17 references, 1 figure, 2 tables.

DeSouza, G.

1980-01-01T23:59:59.000Z

55

Residential/commercial market for energy technologies  

SciTech Connect

The residential/commercial market sector, particularly as it relates to energy technologies, is described. Buildings account for about 25% of the total energy consumed in the US. Market response to energy technologies is influenced by several considerations. Some considerations discussed are: industry characteristics; market sectors; energy-consumption characeristics; industry forecasts; and market influences. Market acceptance may be slow or nonexistent, the technology may have little impact on energy consumption, and redesign or modification may be necessary to overcome belatedly perceived market barriers. 7 figures, 20 tables.

Glesk, M.M.

1979-08-01T23:59:59.000Z

56

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Evaluation Evaluation Annual Energy Outlook Forecast Evaluation by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the impacts were not incorporated in the AEO projections until their enactment or effective dates in accordance with EIA's requirement to remain policy neutral and include only current laws and regulations in the AEO reference case projections.

57

Annual Energy Outlook 1998 Forecasts - Preface  

Gasoline and Diesel Fuel Update (EIA)

1998 With Projections to 2020 1998 With Projections to 2020 Annual Energy Outlook 1999 Report will be Available on December 9, 1998 Preface The Annual Energy Outlook 1998 (AEO98) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA's National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO98 reference case. The next section, “Legislation and Regulations,” describes the assumptions made with regard to laws that affect energy markets and discusses evolving legislative and regulatory issues. “Issues in Focus” discusses three current energy issues—electricity restructuring, renewable portfolio standards, and carbon emissions. It is followed by the analysis

58

Forecasting for energy and chemical decision analysis  

SciTech Connect

This paper focuses on uncertainty and bias in forecasts used for major energy and chemical investment decisions. Probability methods for characterizing uncertainty in the forecast are reviewed. Sources of forecasting bias are classified based on the results of relevant psychology research. Examples are drawn from the energy and chemical industry to illustrate the value of explicit characterization of uncertainty and reduction of bias in forecasts.

Cazalet, E.G.

1984-08-01T23:59:59.000Z

59

Electricity market clearing price forecasting under a deregulated electricity market .  

E-Print Network (OSTI)

??Under deregulated electric market, electricity price is no longer set by the monopoly utility company rather it responds to the market and operating conditions. Offering… (more)

Yan, Xing

2009-01-01T23:59:59.000Z

60

Wind forecasting objectives for utility schedulers and energy traders  

DOE Green Energy (OSTI)

The wind energy industry and electricity producers can benefit in a number of ways from increased wind forecast accuracy. Higher confidence in the reliability of wind forecasts can help persuade an electric utility to increase the penetration of wind energy into its operating system and to augment the capacity value of wind electric generation. Reliable forecasts can also assist daily energy traders employed by utilities in marketing the available and anticipated wind energy to power pools and other energy users. As the number of utilities with wind energy experience grows, and wind energy penetration levels increase, the need for reliable wind forecasts will likely grow as well. This period of wind energy growth also coincides with advances in computer weather prediction technology that could lead to more accurate wind forecasts. Thus, it is important to identify the type of forecast information needed by utility schedulers and energy traders. This step will help develop approaches to the challenge of wind forecasting that will result in useful products being supplied to utilities or other energy generating entities. This paper presents the objectives, approach, and current findings of a US Department of Energy National Renewable Energy Laboratory (DOE/NREL) initiative to develop useful wind forecasting tools for utilities involved with wind energy generation. The focus of this initiative thus far has been to learn about the needs of prospective utility users. NREL representatives conducted a series of onsite interviews with key utility staff, usually schedulers and research planners, at seven US utilities. The purpose was to ascertain information on actual scheduling and trading procedures, and how utilities could integrate wind forecasting into these activities.

Schwartz, M.N. [National Renewable Energy Lab., Golden, CO (United States); Bailey, B.H. [AWS Scientific, Inc., Albany, NY (United States)

1998-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasted energy market" 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

Voluntary Green Power Market Forecast through 2015  

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

predicting how consumers will react to factors affecting the voluntary market. The analysis includes a negative policy impacts scenario designed to reflect impacts on the...

62

United States energy supply and demand forecasts 1979-1995  

SciTech Connect

Forecasts of U.S. energy supply and demand by fuel type and economic sector, as well as historical background information, are presented. Discussion and results pertaining to the development of current and projected marginal energy costs, and their comparison with market prices, are also presented.

Walton, H.L.

1979-01-01T23:59:59.000Z

63

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

64

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

65

Price Forecasting and Optimal Operation of Wholesale Customers in a Competitive Electricity Market.  

E-Print Network (OSTI)

??This thesis addresses two main issues: first, forecasting short-term electricity market prices; and second, the application of short-term electricity market price forecasts to operation planning… (more)

Zareipour, Hamidreza

2006-01-01T23:59:59.000Z

66

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

67

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

68

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work and expertise of numerous, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

69

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

70

Free World energy survey: historical overview and long-term forecast  

SciTech Connect

This report gives a historical overview of international energy markets from the 1950s to date, and an analysis of future energy prices, economic growth, and potential supply instabilities. Forecasts of energy demand by region and fuel type are provided.

1983-01-01T23:59:59.000Z

71

CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Demand Forecast report is the product of the efforts of many current and former California Energy Commission staff. Staff contributors to the current forecast are: Project Management and Technical Direction

72

Experience from hosting a corporate prediction market: benefits beyond the forecasts  

Science Conference Proceedings (OSTI)

Prediction markets are virtual stock markets used to gain insight and forecast events by leveraging the wisdom of crowds. Popularly applied in the public to cultural questions (election results, box-office returns), they have recently been applied by ... Keywords: artificial markets, forecasting, organizational knowledge, prediction markets, social media

Thomas A. Montgomery, Paul M. Stieg, Michael J. Cavaretta, Paul E. Moraal

2013-08-01T23:59:59.000Z

73

Bloomberg New Energy Finance Carbon Markets formerly New Energy Finance  

Open Energy Info (EERE)

formerly New Energy Finance formerly New Energy Finance Carbon Markets Group Jump to: navigation, search Name Bloomberg New Energy Finance Carbon Markets (formerly New Energy Finance Carbon Markets Group) Place London, United Kingdom Zip EC2A 1PQ Sector Carbon, Services Product London-based carbon markets division of New Energy Finance which provides analysis, price forecasting, consultancy and risk management services relating to carbon. References Bloomberg New Energy Finance Carbon Markets (formerly New Energy Finance Carbon Markets Group)[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Bloomberg New Energy Finance Carbon Markets (formerly New Energy Finance Carbon Markets Group) is a company located in London, United Kingdom .

74

California Wind Energy Forecasting System Development and Testing, Phase 1: Initial Testing  

Science Conference Proceedings (OSTI)

Wind energy forecasting uses sophisticated numerical weather forecasting and wind plant power generation models to predict the hourly energy generation of a wind power plant up to 48 hours in advance. As a result, it has great potential to address the needs of the California Independent System Operator (ISO) and the wind plant operators, as well as power marketers and buyers and utility system dispatch personnel. This report gives the results of 28 days of testing of wind energy forecasting at a Californ...

2003-01-31T23:59:59.000Z

75

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

H Tables H Tables Appendix H Comparisons With Other Forecasts, and Performance of Past IEO Forecasts for 1990, 1995, and 2000 Forecast Comparisons Three organizations provide forecasts comparable with those in the International Energy Outlook 2005 (IEO2005). The International Energy Agency (IEA) provides “business as usual” projections to the year 2030 in its World Energy Outlook 2004; Petroleum Economics, Ltd. (PEL) publishes world energy forecasts to 2025; and Petroleum Industry Research Associates (PIRA) provides projections to 2015. For this comparison, 2002 is used as the base year for all the forecasts, and the comparisons extend to 2025. Although IEA’s forecast extends to 2030, it does not publish a projection for 2025. In addition to forecasts from other organizations, the IEO2005 projections are also compared with those in last year’s report (IEO2004). Because 2002 data were not available when IEO2004 forecasts were prepared, the growth rates from IEO2004 are computed from 2001.

76

Wind Energy Forecasting Technology Update: 2004  

Science Conference Proceedings (OSTI)

This report describes the status of wind energy forecasting technology for predicting wind speed and energy generation of wind energy facilities short-term (minutes to hours), intermediate-term (hours to days), and long-term (months to years) average wind speed and energy generation. The information should be useful to companies that are evaluating or planning to incorporate wind energy forecasting into their operations.

2005-04-26T23:59:59.000Z

77

European Union Wind Energy Forecasting Model Development and Testing: U.S. Department of Energy -- EPRI Wind Turbine Verification Pr ogram  

Science Conference Proceedings (OSTI)

Wind forecasting can increase the strategic and market values of wind power from large wind facilities. This report summarizes the results of the European Union (EU) wind energy forecasting project and performance testing of the EU wind forecasting model. The testing compared forecast and observed wind speed and generation data from U.S. wind facilities.

1999-12-15T23:59:59.000Z

78

Annual Energy Outlook with Projections to 2025 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2005 Forecast Comparisons Table 32. Forecasts of annual average economic growth, 2003-2025 Printer Friendly Version Average annual percentage growth Forecast 2003-2009 2003-2014 2003-2025 AEO2004 3.5 3.2 3.0 AEO2005 Reference 3.4 3.3 3.1 Low growth 2.9 2.8 2.5 High growth 4.1 3.9 3.6 GII 3.4 3.2 3.1 OMB 3.6 NA NA CBO 3.5 3.1 NA OEF 3.5 3.5 NA Only one other organization—Global Insight, Incorporated (GII)—produces a comprehensive energy projection with a time horizon similar to that of AEO2005. Other organizations address one or more aspects of the energy markets. The most recent projection from GII, as well as other forecasts that concentrate on economic growth, international oil prices, energy

79

Voluntary Green Power Market Forecast through 2015  

E-Print Network (OSTI)

Office of Energy Efficiency and Renewable Energy Operated by the Alliance for Sustainable Energy, LLC Contract No. DE-AC36-08-GO28308NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof. Available electronically at

Lori Bird; Jenny Sumner; Claire Kreycik; Lori Bird; Jenny Sumner; Claire Kreycik

2010-01-01T23:59:59.000Z

80

Building Energy Software Tools Directory: Energy Usage Forecasts  

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

Energy Usage Forecasts Energy Usage Forecasts Energy Usage Forecasts Quick and easy web-based tool that provides free 14-day ahead energy usage forecasts based on the degree day forecasts for 1,200 stations in the U.S. and Canada. The user enters the daily non-weather base load and the usage per degree day weather factor; the tool applies the degree day forecast and displays the total energy usage forecast. Helpful FAQs explain the process and describe various options for the calculation of the base load and weather factor. Historical degree day reports and 14-day ahead degree day forecasts are available from the same site. Keywords degree days, historical weather, mean daily temperature, load calculation, energy simulation Validation/Testing Degree day data provided by AccuWeather.com, updated daily at 0700.

Note: This page contains sample records for the topic "forecasted energy market" 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

Combining artificial neural networks and statistics for stock-market forecasting  

Science Conference Proceedings (OSTI)

We have developed a stock-market forecasting system based on artificial neural networks. The system has been trained with the Standard & Poor 500 composite indexes of past twenty years. Meanwhile, the system produces the forecasts and adjusts ...

Shaun-Inn Wu; Ruey-Pyng Lu

1993-03-01T23:59:59.000Z

82

energy data + forecasting | OpenEI Community  

Open Energy Info (EERE)

energy data + forecasting energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. Links: FRED beta demo energy data + forecasting Syndicate content 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2084382122

83

Annual Energy Outlook Forecast Evaluation 2005  

Gasoline and Diesel Fuel Update (EIA)

Forecast Evaluation 2005 Forecast Evaluation 2005 Annual Energy Outlook Forecast Evaluation 2005 Annual Energy Outlook Forecast Evaluation 2005 * Then Energy Information Administration (EIA) produces projections of energy supply and demand each year in the Annual Energy Outlook (AEO). The projections in the AEO are not statements of what will happen but of what might happen, given the assumptions and methodologies used. The projections are business-as-usual trend projections, given known technology, technological and demographic trends, and current laws and regulations. Thus, they provide a policy-neutral reference case that can be used to analyze policy initiatives. EIA does not propose or advocate future legislative and regulatory changes. All laws are assumed to remain as currently enacted; however, the impacts of emerging regulatory changes, when defined, are reflected.

84

Optimization Online - Survivable Energy Markets  

E-Print Network (OSTI)

Mar 9, 2006... at the same time, the dayahead energy market and the reserve market in order to price through the market, beside energy, the overall cost of ...

85

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Download Adobe Acrobat Reader Printer friendly version on our site are provided in Adobe Acrobat Spreadsheets are provided in Excel Actual vs. Forecasts Formats Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF Table 12. World Oil Prices Excel, PDF Table 13. Natural Gas Wellhead Prices

86

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) MS Excel Viewer PDF (Acrobat Reader required Download Acrobat Reader ) Adobe Acrobat Reader Logo Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF

87

Forecasting Financial Time-Series using Artificial Market Models  

E-Print Network (OSTI)

We discuss the theoretical machinery involved in predicting financial market movements using an artificial market model which has been trained on real financial data. This approach to market prediction - in particular, forecasting financial time-series by training a third-party or 'black box' game on the financial data itself -- was discussed by Johnson et al. in cond-mat/0105303 and cond-mat/0105258 and was based on some encouraging preliminary investigations of the dollar-yen exchange rate, various individual stocks, and stock market indices. However, the initial attempts lacked a clear formal methodology. Here we present a detailed methodology, using optimization techniques to build an estimate of the strategy distribution across the multi-trader population. In contrast to earlier attempts, we are able to present a systematic method for identifying 'pockets of predictability' in real-world markets. We find that as each pocket closes up, the black-box system needs to be 'reset' - which is equivalent to sayi...

Gupta, N; Johnson, N F; Gupta, Nachi; Hauser, Raphael; Johnson, Neil F.

2005-01-01T23:59:59.000Z

88

Annual Energy Outlook Forecast Evaluation 2004  

Gasoline and Diesel Fuel Update (EIA)

2004 2004 * The Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) has produced annual evaluations of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and replacing the historical year of data with the most recent. The forecast evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute percent errors for several of the major variables for AEO82 through AEO2004. (There is no report titled Annual Energy Outlook 1988 due to a change in the naming convention of the AEOs.) The average absolute percent error is the simple mean of the absolute values of the percentage difference between the Reference Case projection and the

89

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

All U.S. energy markets including exports and imports U.S.Energy Markets All U.S. energy markets including imports andenergy markets All U.S. energy markets including imports and

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

2005-01-01T23:59:59.000Z

90

ANN-based Short-Term Load Forecasting in Electricity Markets  

E-Print Network (OSTI)

ANN-based Short-Term Load Forecasting in Electricity Markets Hong Chen Claudio A. Ca~nizares Ajit forecasting technique that considers electricity price as one of the main characteristics of the system load. B. Makram, "A Hybrid Wavelet- Kalman Filter Method for Load Forecasting," Electric Power Systems

Cañizares, Claudio A.

91

EVALUATION OF PV GENERATION CAPICITY CREDIT FORECAST ON DAY-AHEAD UTILITY MARKETS  

E-Print Network (OSTI)

EVALUATION OF PV GENERATION CAPICITY CREDIT FORECAST ON DAY-AHEAD UTILITY MARKETS Richard Perez of the NDFD-based solar radiation forecasts for several climatically distinct locations, the evaluation is now continued by testing the forecasts' end-use operational accuracy, focusing on their ability to accurately

Perez, Richard R.

92

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY AND TRANSPORTATION DIVISION B.B. Blevins Executive Director DISCLAIMER This report was prepared by a California has developed longterm forecasts of transportation energy demand as well as projected ranges

93

Understanding the China energy market: trends and opportunities 2006  

Science Conference Proceedings (OSTI)

The report is broken up into 4 Sections: Section I - Overview of China Energy Market (historical background, market value, consumption, production, reserves, export and import, market segmentation, market forecast); Section II - Market Analysis (PEST analysis, Porter's five forces analysis, socio-economic trends, consumption trends); Section III - Market Segments (electricity, oil, natural gas, liquefied natural gas, liquid petroleum gas, nuclear power, coal, renewables, photovoltaics, wind power, hydroelectric power. Each market segment details current and planned projects, and lists participants in that sector); and Section IV - Breaking Into the Market (regulatory framework, methods of market entry, foreign investment, challenges, government agencies).

Barbara Drazga

2005-05-15T23:59:59.000Z

94

EIA - Energy Market and Economic Impacts of the American Power Act ...  

U.S. Energy Information Administration (EIA)

Home > Forecasts & Analysis >Response to Congressionals and Other Requests > Energy market and Economic Impacts of th American Power Act of 2010 > Preface and Contacts

95

Review of methods for forecasting the market penetration of new technologies  

SciTech Connect

In 1993 the DOE Office of Energy Efficiency and Renewable Energy (EE) initiated a program called Quality Metrics. Quality Metrics was developed to measure the costs and benefits of technologies being developed by EE R&D programs. The impact of any new technology is directly related to its adoption by the market. The techniques employed to project market adoption are critical to measuring a new technology`s impact. Our purpose was to review current market penetration theories and models and develop a recommended approach for evaluating the market penetration of DOE technologies. The following commonly cited innovation diffusion theories were reviewed to identify analytical approaches relevant to new energy technologies: (1) the normal noncumulative adopter distribution method, (2) the Bass Model, (3) the Mansfield-Blackman Model, (4) the Fisher-Pry Model, (5) a meta-analysis of innovation diffusion studies. Of the theories reviewed, the Bass and Mansfield-Blackman models were found most applicable to forecasting the market penetration of electricity supply technologies. Their algorithms require input estimates which characterize the technology adoption behavior of the electricity supply industry. But, inadequate work has been done to quantify the technology adoption characteristics of this industry. The following energy technology market penetration models were also reviewed: (1) DOE`s Renewable Energy Penetration (REP) Model, (2) DOE`s Electricity Capacity Planning Submodule of the National Energy Modeling System (NEMS), (3) the Assessment of Energy Technologies (ASSET) model by Regional Economic Research, Inc., (4) the Market TREK model by the Electric Power Research Institute (EPRI). The two DOE models were developed for electricity generation technologies whereas the Regional Economic Research and EPRI models were designed for demand- side energy technology markets. Therefore, the review and evaluation focused on the DOE models.

Gilshannon, S.T.; Brown, D.R.

1996-12-01T23:59:59.000Z

96

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

National Laboratory Canadian Energy Research Institute U.S.Administration Energy Markets All U.S. energy marketsAll Canadian and U.S. energy markets All U.S. energy markets

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

2005-01-01T23:59:59.000Z

97

Energy forecasts: searching for truth amidst the numbers  

SciTech Connect

High and volatile fuel prices coupled with erratic fuel availability have made reliable fuel forecasting vitally important for the nation's energy industry. The costs of error or missed opportunities are now enormous for management, stockholders, bondholders, gas and electricity ratepayers, and, of course, utility regulators. Fuel market forecasts affect a host of management decisions ranging from tactical fuel planning (e.g., how much oil, coal, and, eventually, gas to purchase on the spot market over the next 3 months) to strategic power system planning (e.g., what generating mix is optimal for the 1990s) and oil and gas exploration and production (EandP) planning (e.g., what portfolio of gas prospects should be developed this decade in the lower 48 states). Often hundreds of millions and sometimes billions of dollars are at stake in areas as diverse as: Industrial energy marketing, Fuel procurement planning, Fuel mix and fuel ownership strategy, Corporate business strategy planning, Company RandD planning, Oil and gas EandP budget planning, Electricity load forecasting, Electricity capacity planning and operations.

1984-01-01T23:59:59.000Z

98

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff members in the Demand prepared the residential sector forecast. Mohsen Abrishami prepared the commercial sector forecast. Lynn

99

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

100

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Oil Markets Oil Markets IEO2005 projects that world crude oil prices in real 2003 dollars will decline from their current level by 2010, then rise gradually through 2025. In the International Energy Outlook 2005 (IEO2005) reference case, world demand for crude oil grows from 78 million barrels per day in 2002 to 103 million barrels per day in 2015 and to just over 119 million barrels per day in 2025. Much of the growth in oil consumption is projected for the emerging Asian nations, where strong economic growth results in a robust increase in oil demand. Emerging Asia (including China and India) accounts for 45 percent of the total world increase in oil use over the forecast period in the IEO2005 reference case. The projected increase in world oil demand would require an increment to world production capability of more than 42 million barrels per day relative to the 2002 crude oil production capacity of 80.0 million barrels per day. Producers in the Organization of Petroleum Exporting Countries (OPEC) are expected to be the major source of production increases. In addition, non-OPEC supply is expected to remain highly competitive, with major increments to supply coming from offshore resources, especially in the Caspian Basin, Latin America, and deepwater West Africa. The estimates of incremental production are based on current proved reserves and a country-by-country assessment of ultimately recoverable petroleum. In the IEO2005 oil price cases, the substantial investment capital required to produce the incremental volumes is assumed to exist, and the investors are expected to receive at least a 10-percent return on investment.

Note: This page contains sample records for the topic "forecasted energy market" 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

Advances in Volatility Modeling for Energy Markets: Methods for Reproducing Volatility Clustering, Fat Tails, Smiles, and Smirks in Energy Price Forecasts  

Science Conference Proceedings (OSTI)

This report describes research sponsored by the Electric Power Research Institute (EPRI) to develop a new model of energy price volatility. For many years, EPRI has worked with a flexible and tractable volatility model that successfully captures the term "structure of volatility," including the properties commonly referred to as "mean reversion" and "seasonality." However, that model does not capture random volatility, evidenced by volatility clustering, nor does it capture skewness and excess kurtosis i...

2011-12-30T23:59:59.000Z

102

Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets  

E-Print Network (OSTI)

In current restructured wholesale power markets, the short length of time series for prices makes it difficult to use empirical price data to test existing price forecasting tools and to develop new price forecasting tools. This study therefore proposes a two-stage approach for generating simulated price scenarios based on the available price data. The first stage consists of an Autoregressive Moving Average (ARMA) model for determining scenarios of cleared demands and scheduled generator outages (D&O), and a moment-matching method for reducing the number of D&O scenarios to a practical scale. In the second stage, polynomials are fitted between D&O and wholesale power prices in order to obtain price scenarios for a specified time frame. Time series data from the Midwest ISO (MISO) are used as a test system to validate the proposed approach. The simulation results indicate that the proposed approach is able to generate price scenarios for distinct seasons with empirically realistic characteristics.

Qun Zhou; Leigh Tesfatsion; Chen-Ching Liu

2009-01-01T23:59:59.000Z

103

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) PDF (Acrobat Reader required) Table 2. Total Energy Consumption HTML, Excel, PDF Table 3. Total Petroleum Consumption HTML, Excel, PDF Table 4. Total Natural Gas Consumption HTML, Excel, PDF Table 5. Total Coal Consumption HTML, Excel, PDF Table 6. Total Electricity Sales HTML, Excel, PDF Table 7. Crude Oil Production HTML, Excel, PDF Table 8. Natural Gas Production HTML, Excel, PDF Table 9. Coal Production HTML, Excel, PDF Table 10. Net Petroleum Imports HTML, Excel, PDF Table 11. Net Natural Gas Imports HTML, Excel, PDF Table 12. Net Coal Exports HTML, Excel, PDF Table 13. World Oil Prices HTML, Excel, PDF

104

Annual Energy Outlook Forecast Evaluation - Table 1. Forecast Evaluations:  

Gasoline and Diesel Fuel Update (EIA)

Average Absolute Percent Errors from AEO Forecast Evaluations: Average Absolute Percent Errors from AEO Forecast Evaluations: 1996 to 2000 Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Variable 1996 Evaluation: AEO82 to AEO93 1997 Evaluation: AEO82 to AEO97 1998 Evaluation: AEO82 to AEO98 1999 Evaluation: AEO82 to AEO99 2000 Evaluation: AEO82 to AEO2000 Consumption Total Energy Consumption 1.8 1.6 1.7 1.7 1.8 Total Petroleum Consumption 3.2 2.8 2.9 2.8 2.9 Total Natural Gas Consumption 6.0 5.8 5.7 5.6 5.6 Total Coal Consumption 2.9 2.7 3.0 3.2 3.3 Total Electricity Sales 1.8 1.6 1.7 1.8 2.0 Production Crude Oil Production 5.1 4.2 4.3 4.5 4.5

105

Bidding Strategy with Forecast Technology Based on Support Vector Machine in Electrcity Market  

E-Print Network (OSTI)

The participants of the electricity market concern very much the market price evolution. Various technologies have been developed for price forecast. SVM (Support Vector Machine) has shown its good performance in market price forecast. Two approaches for forming the market bidding strategies based on SVM are proposed. One is based on the price forecast accuracy, with which the being rejected risk is defined. The other takes into account the impact of the producer's own bid. The risks associated with the bidding are controlled by the parameters setting. The proposed approaches have been tested on a numerical example.

Gao, C; Napoli, R; Wan, Q

2007-01-01T23:59:59.000Z

106

Analysis of industrial markets for low and medium Btu coal gasification. [Forecasting  

SciTech Connect

Low- and medium-Btu gases (LBG and MBG) can be produced from coal with a variety of 13 existing and 25 emerging processes. Historical experience and previous studies indicate a large potential market for LBG and MBG coal gasification in the manufacturing industries for fuel and feedstocks. However, present use in the US is limited, and industry has not been making substantial moves to invest in the technology. Near-term (1979-1985) market activity for LBG and MBG is highly uncertain and is complicated by a myriad of pressures on industry for energy-related investments. To assist in planning its program to accelerate the commercialization of LBG and MBG, the Department of Energy (DOE) contracted with Booz, Allen and Hamilton to characterize and forecast the 1985 industrial market for LBG and MBG coal gasification. The study draws five major conclusions: (1) There is a large technically feasible market potential in industry for commercially available equipment - exceeding 3 quadrillion Btu per year. (2) Early adopters will be principally steel, chemical, and brick companies in described areas. (3) With no additional Federal initiatives, industry commitments to LBG and MBG will increase only moderately. (4) The major barriers to further market penetration are lack of economic advantage, absence of significant operating experience in the US, uncertainty on government environmental policy, and limited credible engineering data for retrofitting industrial plants. (5) Within the context of generally accepted energy supply and price forecasts, selected government action can be a principal factor in accelerating market penetration. Each major conclusion is discussed briefly and key implications for DOE planning are identified.

1979-07-30T23:59:59.000Z

107

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

against the risk of energy price fluctuations. In theory,The poor track record of energy price forecasting models hasof information about future energy prices, including most

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

2005-01-01T23:59:59.000Z

108

Forecasting Market Prices in a Supply Chain Game Christopher Kiekintveld, Jason Miller, Patrick R. Jordan, and Michael P. Wellman  

E-Print Network (OSTI)

Forecasting Market Prices in a Supply Chain Game Christopher Kiekintveld, Jason Miller, Patrick R, to forecast market prices in the Trading Agent Com- petition Supply Chain Management Game. As a guiding, Experimentation, Measurement Keywords Forecasting, Markets, Price prediction, Trading agent competition, Supply

Wellman, Michael P.

109

NREL: Energy Analysis - Market Analysis  

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

Market Analysis The laboratory's market analysis helps increase the use of renewable energy (RE) and energy efficiency (EE) technologies in the marketplace by providing strategic...

110

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022  

E-Print Network (OSTI)

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA or adequacy of the information in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast forecast. Bryan Alcorn and Mehrzad Soltani Nia prepared the industrial forecast. Miguel Garcia- Cerrutti

111

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Energy futures markets are ‘hubs’ that price and marketenergy price fluctuations. In theory, futures market pricesenergy prices, including most prominently, energy futures markets.

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

2005-01-01T23:59:59.000Z

112

Essays on Forecasting and Hedging Models in the Oil Market and Causality Analysis in the Korean Stock Market  

E-Print Network (OSTI)

In this dissertation, three related issues concerning empirical time series models for energy financial markets and the stock market were investigated. The purpose of this dissertation was to analyze the interdependence of price movements, focusing on the forecasting models for crude oil prices and the hedging models for gasoline prices, and to study the change in the contemporaneous causal relationship between investors' activities and stock price movements in the Korean stock market. In the first essay, the nature of forecasting crude oil prices based on financial data for the oil and oil product market is examined. As crack spread and oil-related Exchange-Traded Funds (ETFs) have enabled more consumers and investors to gain access to the crude oil and petroleum products markets, I investigated whether crack spread and oil ETFs were good predictors of oil prices and attempted to determine whether crack spread or oil ETFs were better at explaining oil price movements. In the second essay, the effectiveness of diverse hedging models for the unleaded gasoline price is examined using futures and ETFs. I calculated the optimal hedge ratios for gasoline futures and gasoline ETF utilizing several advanced econometric models and then compared their hedging performances. In the third essay, the contemporaneous causal relationship between multiple players' activities and stock price movements in the Korean stock market was investigated using the framework of a DAG model. The causal impacts of three players' activities in regard to stock return and stock price volatility are examined, concentrating on foreign investor activities. Within this framework, two Korean stock markets, the KSE and KOSDAQ markets, are analyzed and compared. Recognizing the global financial crisis of 2008, the change in casual relationships was examined in terms of pre- and post-break periods. In conclusion, when a multivariate econometric model is developed for multi-markets and multi-players, it is necessary to consider a number of attributes on data relations, including cointegration, causal relationship, time-varying correlation and variance, and multivariate non-normality. This dissertation employs several econometric models to specify these characteristics. This approach will be useful in further studies of the information transmission mechanism among multi-markets or multi-players.

Choi, Hankyeung

2012-08-01T23:59:59.000Z

113

Energy Merchant Marketing EMM | Open Energy Information  

Open Energy Info (EERE)

. References "Energy Merchant Marketing (EMM)" Retrieved from "http:en.openei.orgwindex.php?titleEnergyMerchantMarketingEMM&oldid344870" Categories: Clean Energy...

114

Energy Sector Market Analysis  

SciTech Connect

This paper presents the results of energy market analysis sponsored by the Department of Energy's (DOE) Weatherization and International Program (WIP) within the Office of Energy Efficiency and Renewable Energy (EERE). The analysis was conducted by a team of DOE laboratory experts from the National Renewable Energy Laboratory (NREL), Oak Ridge National Laboratory (ORNL), and Pacific Northwest National Laboratory (PNNL), with additional input from Lawrence Berkeley National Laboratory (LBNL). The analysis was structured to identify those markets and niches where government can create the biggest impact by informing management decisions in the private and public sectors. The analysis identifies those markets and niches where opportunities exist for increasing energy efficiency and renewable energy use.

Arent, D.; Benioff, R.; Mosey, G.; Bird, L.; Brown, J.; Brown, E.; Vimmerstedt, L.; Aabakken, J.; Parks, K.; Lapsa, M.; Davis, S.; Olszewski, M.; Cox, D.; McElhaney, K.; Hadley, S.; Hostick, D.; Nicholls, A.; McDonald, S.; Holloman, B.

2006-10-01T23:59:59.000Z

115

Assumptions to Annual Energy Outlook - Energy Information ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

116

Annual Energy Outlook 2006 with Projections to 2030 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2006 with Projections to 2030 Only GII produces a comprehensive energy projection with a time horizon similar to that of AEO2006. Other organizations address one or more aspects of the energy markets. The most recent projection from GII, as well as others that concentrate on economic growth, international oil prices, energy consumption, electricity, natural gas, petroleum, and coal, are compared here with the AEO2006 projections. Economic Growth In the AEO2006 reference case, the projected growth in real GDP, based on 2000 chain-weighted dollars, is 3.0 percent per year from 2004 to 2030 (Table 19). For the period from 2004 to 2025, real GDP growth in the AEO2006 reference case is similar to the average annual growth projected in AEO2005. The AEO2006 projections of economic growth are based on the August short-term forecast of GII, extended by EIA through 2030 and modified to reflect EIAÂ’s view on energy prices, demand, and production.

117

OpenEI Community - energy data + forecasting  

Open Energy Info (EERE)

FRED FRED http://en.openei.org/community/group/fred Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. energy data + forecasting Fri, 22 Jun 2012 15:30:20 +0000 Dbrodt 34

118

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

119

Support vector regression with chaos-based firefly algorithm for stock market price forecasting  

Science Conference Proceedings (OSTI)

Due to the inherent non-linearity and non-stationary characteristics of financial stock market price time series, conventional modeling techniques such as the Box-Jenkins autoregressive integrated moving average (ARIMA) are not adequate for stock market ... Keywords: Chaotic mapping, Firefly algorithm, Stock market price forecasting, Support vector regression

Ahmad Kazem; Ebrahim Sharifi; Farookh Khadeer Hussain; Morteza Saberi; Omar Khadeer Hussain

2013-02-01T23:59:59.000Z

120

Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy  

DOE Green Energy (OSTI)

The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.

Parks, K.; Wan, Y. H.; Wiener, G.; Liu, Y.

2011-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasted energy market" 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

Annual Energy Outlook 1998 Forecasts  

Gasoline and Diesel Fuel Update (EIA)

EIA Administrator's Press Briefing on the Annual Energy Outlook 1998 (AEO98) Annual Energy Outlook 1998 - Errata as of 3698 Data from the AEO98 Assumptions to the AEO98 (Nat'Gas...

122

Marketing Quality Energy Awareness  

E-Print Network (OSTI)

Marketing and quality concepts were utilized in developing an employee awareness plan to facilitate long term employee participation that improved energy efficiency 15%. The plan was successfully introduced on a test basis in two manufacturing locations and now is a part of overall operations. The marketing concepts aided in determining who was the customer and what functional value an awareness plan has for employees (customers). Quality concepts, including performance management, augmented marketing strategies by determining customer requirements, measurements and feedback. The agreed upon critical components were formatted into an organized plan of education, assigned responsibility, feedback and incentives.

Fortier, L. J.

1988-09-01T23:59:59.000Z

123

Fuzzy-neural model with hybrid market indicators for stock forecasting  

Science Conference Proceedings (OSTI)

A number of research had been carried out to forecast stock price based on technical indicators, which rely purely on historical stock price data. Nevertheless, their performance is not always satisfactory. In this paper, the effect of using hybrid market ...

A. A. Adebiyi; C. K. Ayo; S. O. Otokiti

2011-07-01T23:59:59.000Z

124

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series  

E-Print Network (OSTI)

in this report. #12;i ABSTRACT These electricity demand forms and instructions ask load-serving entities and Instructions for Electricity Demand Forecasts. California Energy Commission, Electricity Supply Analysis.................................................................................................................................7 Form 1 Historic and Forecast Electricity Demand

Abdel-Aal, Radwan E.

125

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

energy price fluctuations. In theory, futures market prices summarize privately available informationEnergy; Brookhaven National Laboratory Canadian Energy Research Institute U.S. Energy Information Administration Energy Marketsinformation about future energy prices, including most prominently, energy futures markets.

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

2005-01-01T23:59:59.000Z

126

Annual Energy Outlook 2001 - Market Trends  

Gasoline and Diesel Fuel Update (EIA)

Homepage Homepage Market Trends Economic Activity Renewables International Oil Markets Oil & Natural Gas Energy Demand Coal Electricity Emissions The projections in AEO2001 are not statements of what will happen but of what might happen, given the assumptions and methodologies used. The projections are business-as-usual trend forecasts, given known technology, technological and demographic trends, and current laws and regulations. Thus, they provide a policy-neutral reference case that can be used to analyze policy initiatives. EIA does not propose, advocate, or speculate on future legislative and regulatory changes. All laws are assumed to remain as currently enacted; however, the impacts of emerging regulatory changes, when defined, are reflected.

127

Wind Energy Forecasting Technology Update: 2006  

Science Conference Proceedings (OSTI)

The worldwide installed wind generation capacity increased by 25 and reached almost 60,000 MW worldwide during 2005. As wind capacity continues to grow and large regional concentrations of wind generation emerge, utilities and regional transmission organizations will increasingly need accurate same-day and next-day forecasts of wind energy generation to dispatch system generation and transmission resource and anticipate rapid changes of wind generation.

2006-12-05T23:59:59.000Z

128

Wind Energy Forecasting Technology Update: 2005  

Science Conference Proceedings (OSTI)

The worldwide installed wind generation capacity increased by 25 and reached almost 60,000 MW worldwide during 2005. As wind capacity continues to grow and large regional concentrations of wind generation emerge, utilities and regional transmission organizations will increasingly need accurate same-day and next-day forecasts of wind energy generation to dispatch system generation and transmission resource and anticipate rapid changes of wind generation. The project objective is to summarize the results o...

2006-03-31T23:59:59.000Z

129

The Market Price of Risk: Implications for Electricity Price Forecasting, Asset Valuation and Portfolio Risk Management  

Science Conference Proceedings (OSTI)

Forward Price Forecasting for Power Market Valuation (TR-111860, 1998) presented the basic theory on the market price of risk. However, continued development of the power market has led to additional complexities when applying the concept to electric power. This current report updates that earlier report based on subsequent development of the theory by EPRI and others and reflects two additional years of market data.

2000-12-07T23:59:59.000Z

130

Short-Term Energy Outlook - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

131

Delaware - State Energy Profile Overview - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

132

Georgia - State Energy Profile Overview - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

133

NREL: Energy Analysis - Energy Forecasting and Modeling Staff  

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

Energy Forecasting and Modeling Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Geraly Amador Clayton Barrows Greg Brinkman Brian W Bush Stuart Cohen Carolyn Davidson Paul Denholm Victor Diakov Aron Dobos Easan Drury Kelly Eurek Janine Freeman Marissa Hummon Jennie Jorganson Jordan Macknick Trieu Mai David Mulcahy David Palchak Ben Sigrin Daniel Steinberg Patrick Sullivan Aaron Townsend Laura Vimmerstedt Andrew Weekley Owen Zinaman Photo of Clayton Barrows. Clayton Barrows Postdoctoral Researcher Areas of expertise Power system modeling Primary research interests Power and energy systems

134

Forecasts of intercity passenger demand and energy use through 2000  

SciTech Connect

The development of national travel demand and energy-use forecasts for automobile and common-carrier intercity travel through the year 2000. The forecasts are driven by the POINTS (Passenger Oriented Intercity Network Travel Simulation) model, a model direct-demand model which accounts for competition among modes and destinations. Developed and used to model SMSA-to-SMSA business and nonbusiness travel, POINTS is an improvement over earlier direct demand models because it includes an explicit representation of cities' relative accessibilities and a utility maximizing behavorial multimodal travel function. Within POINTS, pathbuilding algorithms are used to determine city-pair travel times and costs by mode, including intramodal transfer times. Other input data include projections of SMSA population, public and private sector employment, and hotel and other retail receipts. Outputs include forecasts of SMSA-to-SMSA person trips and person-miles of travel by mode. For the national forecasts, these are expanded to represent all intercity travel (trips greater than 100 miles, one way) for two fuel-price cases. Under both cases rising fuel prices, accompanied by substantial reductions in model-energy intensities, result in moderate growth in total intercity passenger travel. Total intercity passenger travel is predicted to grow at approximately one percent per year, slightly fster than population growth, while air travel grows almost twice as fast as population. The net effect of moderate travel growth and substantial reduction in model energy intensities is a reduction of approximately 50 percent in fuel consumption by the intercity passenger travel market.

Kaplan, M.P.; Vyas, A.D.; Millar, M.; Gur, Y.

1982-01-01T23:59:59.000Z

135

Short-Term Solar Energy Forecasting Using Wireless Sensor Networks  

E-Print Network (OSTI)

Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Stefan Achleitner, Tao Liu in power output is a major concern and forecasting is, therefore, a top priority. We propose a sensing infrastructure to enable sensing of solar irradiance with application to solar array output forecasting

Cerpa, Alberto E.

136

Comparing Price Forecast Accuracy of Natural Gas Models andFutures Markets  

SciTech Connect

The purpose of this article is to compare the accuracy of forecasts for natural gas prices as reported by the Energy Information Administration's Short-Term Energy Outlook (STEO) and the futures market for the period from 1998 to 2003. The analysis tabulates the existing data and develops a statistical comparison of the error between STEO and U.S. wellhead natural gas prices and between Henry Hub and U.S. wellhead spot prices. The results indicate that, on average, Henry Hub is a better predictor of natural gas prices with an average error of 0.23 and a standard deviation of 1.22 than STEO with an average error of -0.52 and a standard deviation of 1.36. This analysis suggests that as the futures market continues to report longer forward prices (currently out to five years), it may be of interest to economic modelers to compare the accuracy of their models to the futures market. The authors would especially like to thank Doug Hale of the Energy Information Administration for supporting and reviewing this work.

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

2005-06-30T23:59:59.000Z

137

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Contacts Contacts The International Energy Outlook is prepared by the Energy Information Administration (EIA). General questions concerning the contents of the report should be referred to John J. Conti (john.conti@eia.doe.gov, 202-586-2222), Director, Office of Integrated Analysis and Forecasting. Specific questions about the report should be referred to Linda E. Doman (202/586-1041) or the following analysts: World Energy and Economic Outlook Linda Doman (linda.doman@eia.doe.gov, 202-586-1041) Macroeconomic Assumptions Nasir Khilji (nasir.khilji@eia.doe.gov, 202-586-1294) Energy Consumption by End-Use Sector Residential Energy Use John Cymbalsky (john.cymbalsky@eia.doe.gov, 202-586-4815) Commercial Energy Use Erin Boedecker (erin.boedecker@eia.doe.gov, 202-586-4791)

138

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

I: System for the Analysis of Global Energy Markets (SAGE) I: System for the Analysis of Global Energy Markets (SAGE) The projections of world energy consumption appearing in this yearÂ’s International Energy Outlook (IEO) are based on the Energy Information AdministrationÂ’s (EIAÂ’s) international energy modeling tool, System for the Analysis of Global Energy markets (SAGE). SAGE is an integrated set of regional models that provide a technology-rich basis for estimating regional energy consumption. For each region, reference case estimates of 42 end-use energy service demands (e.g., car, commercial truck, and heavy truck road travel; residential lighting; steam heat requirements in the paper industry) are developed on the basis of economic and demographic projections. Projections of energy consumption to meet the energy demands are estimated on the basis of each regionÂ’s existing energy use patterns, the existing stock of energy-using equipment, and the characteristics of available new technologies, as well as new sources of primary energy supply.

139

A GA-weighted ANFIS model based on multiple stock market volatility causality for TAIEX forecasting  

Science Conference Proceedings (OSTI)

Stock market forecasting is important and interesting, because the successful prediction of stock prices may promise attractive benefits. The economy of Taiwan relies on international trade deeply, and the fluctuations of international stock markets ... Keywords: ANFIS, Genetic algorithm, Neural network, Weighted rule

Liang-Ying Wei

2013-02-01T23:59:59.000Z

140

Searching for Google’s Value: Using Prediction Markets to Forecast Market Capitalization Prior to an Initial Public Offering  

E-Print Network (OSTI)

IPO underpricing is endemic. Many theories have been developed to explain it. To inform theory and to investigate the practical application of prediction markets in an IPO setting, we conducted markets designed to forecast post-IPO valuations before a particularly unique IPO: Google. The combination of results from these markets and the unique features of the IPO help us distinguish between underpricing theories. The evidence leans against theories which require large payments to buyers to overcome problems of asymmetric information between issuers and buyers. It is most consistent with theories where underpricing is in exchange for future benefits. The prediction market results also show that it is possible to forecast post-IPO market values and, therefore, avoid losses associated with underpricing when a firm wishes to do so.

unknown authors

2005-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasted energy market" 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.


141

Ameren Energy Marketing | Open Energy Information  

Open Energy Info (EERE)

Name Ameren Energy Marketing Place Missouri Utility Id 970 Utility Location Yes Ownership R NERC Location RFC NERC RFC Yes Activity Wholesale Marketing Yes Activity Retail...

142

Comparison of Energy Information Administration and Bonneville Power Administration load forecasts  

SciTech Connect

Comparisons of the modeling methodologies underlying the project Independence Evaluation System (PIES) and the Bonneville Power Administration forecasts are discussed in this paper. This Technical Memorandum is presented in order to reconcile apparent inconsistencies between the forecasts. These represent different purposes for the modeling effort as well as different forecasts. Nonetheless, both are appropriate within the context that they are intended. The BPA forecasts are site-specific, detailed, micro-level, yearly forecasts of the demand for electricity. PIES develops regional, macro forecasts and does not contain estimates of the timing of the completion of plants within the period of the forecast. The BPA forecast is intended to be utilized in analyzing a sub-regional capacity expansion program. PIES is a regional energy market-clearing, non-normative model which allows different scenarios to be compared by changing input variables. Clearly, both forecasts are dependent upon the accuracy of the assumptions and input variables included. However, the differing levels of aggregation and objectives require different types of input variables.

Reed, H.J.

1978-06-01T23:59:59.000Z

143

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network (OSTI)

of future contributions from various emerging transportation fuels and technologies is unknown. PotentiallyCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY AND TRANSPORTATION DIVISION B. B. Blevins Executive Director DISCLAIMER This report was prepared by a California

144

Distributed Energy Resources Market Diffusion Model  

E-Print Network (OSTI)

regional differences in energy markets and climates, as welldiverse climates and energy markets. These differences areanalyze the effect of other energy market policies in future

Maribu, Karl Magnus; Firestone, Ryan; Marnay, Chris; Siddiqui, Afzal S.

2006-01-01T23:59:59.000Z

145

Energy Efficiency in Regulated and Deregulated Markets  

E-Print Network (OSTI)

into other clean energy markets. The issue of doubleet al. , Energy Efficiency Policy and Market Failures, 20impede the functioning of markets, energy efficiency will be

Rotenberg, Edan

2005-01-01T23:59:59.000Z

146

Building Energy Software Tools Directory: Degree Day Forecasts  

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

Forecasts Forecasts Degree Day Forecasts example chart Quick and easy web-based tool that provides free 14-day ahead degree day forecasts for 1,200 stations in the U.S. and Canada. Degree Day Forecasts charts show this year, last year and three-year average. Historical degree day charts and energy usage forecasts are available from the same site. Keywords degree days, historical weather, mean daily temperature Validation/Testing Degree day data provided by AccuWeather.com, updated daily at 0700. Expertise Required No special expertise required. Simple to use. Users Over 1,000 weekly users. Audience Anyone who needs degree day forecasts (next 14 days) for the U.S. and Canada. Input Select a weather station (1,200 available) and balance point temperature. Output Charts show (1) degree day (heating and cooling) forecasts for the next 14

147

U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

148

Consumption & Efficiency - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

149

Environment - Analysis & Projections - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

150

Electricity - Analysis & Projections - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

151

Electricity Monthly Update - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

152

Indonesia - Analysis - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

153

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

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

154

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Natural Gas Natural gas is the fastest growing primary energy source in the IEO2005 forecast. Consumption of natural gas is projected to increase by nearly 70 percent between 2002 and 2025, with the most robust growth in demand expected among the emerging economies. Figure 34. World Natural Gas Consumption, 1980-2025 (Trillion Cubic Feet). Need help, contact the National Energy Information Center on 202-586-8800. Figure Data Figure 35. Natural Gas Consumption by Region, 1980-2025 (Trillion Cubic Feet). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 36. Increase in Natural Gas Consumption by Region and Country, 2002-2025. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data

155

Today's Forecast: Improved Wind Predictions | Department of Energy  

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

in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar --...

156

Price forecasting and optimal operation of wholesale customers in a competitive electricity market  

E-Print Network (OSTI)

c ? Hamidreza Zareipour 2006I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. This thesis addresses two main issues: first, forecasting short-term electricity market prices; and second, the application of short-term electricity market price forecasts to operation planning of demand-side Bulk Electricity Market Customers (BEMCs). The Ontario electricity market is selected as the primary case market and its structure is studied in detail. A set of explanatory variable candidates is then selected accordingly, which may explain price behavior in this market. In the process of selecting the explanatory variable candidates, some important issues, such as direct or indirect effects of the variables on price behavior, availability of the variables before real-time, choice of appropriate forecasting horizon and market time-line, are taken into account. Price and demand in three neighboring electricity markets, namely, the New York, New England, and PJM electricity markets, are also considered among the explanatory variable candidates.

Hamidreza Zareipour

2006-01-01T23:59:59.000Z

157

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center  

E-Print Network (OSTI)

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological forecast regimes at the wind energy site and fits a conditional predictive model for each regime

Washington at Seattle, University of

158

World Petroleum Supply/Demand Forecast - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

... surplus supply over demand for spring and summer quarters compared with some other forecasters such as Oil Market Intelligence, ...

159

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Electricity Electricity Electricity consumption nearly doubles in the IEO2005 projection period. The emerging economies of Asia are expected to lead the increase in world electricity use. Figure 58. World Net Electricity Consumption, 2002-2025 (Billion Kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 59. World Net Electricity Consumption by Region, 2002-2025 (Billion Kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data The International Energy Outlook 2005 (IEO2005) reference case projects that world net electricity consumption will nearly double over the next two decades.10 Over the forecast period, world electricity demand is projected to grow at an average rate of 2.6 percent per year, from 14,275 billion

160

Assumptions to the Annual Energy Outlook - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumption to the Annual Energy Outlook Petroleum Market Module Figure 8. Petroleum Administration for Defense Districts. Having problems, call our National Energy Information Center at 202-586-8800 for help. The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohols, ethers, and bioesters natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of U.S. refining

Note: This page contains sample records for the topic "forecasted energy market" 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

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

The International Energy Outlook 2005 (IEO2005) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2025. U.S. projections appearing in IEO2005 are consistent with those published in EIA's Annual Energy Outlook 2005 (AEO2005), which was prepared using the National Energy Modeling System (NEMS). The International Energy Outlook 2005 (IEO2005) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2025. U.S. projections appearing in IEO2005 are consistent with those published in EIA's Annual Energy Outlook 2005 (AEO2005), which was prepared using the National Energy Modeling System (NEMS). Table of Contents Projection Tables Reference Case High Economic Growth Case Low Economic Growth Case Reference Case Projections by End-Use Sector and Region Projections of Oil Production Capacity and Oil Production in Three Cases Projections of Nuclear Generating Capacity Highlights World Energy and Economic Outlook Outlook for World Energy Consumption World Economic Outlook Alternative Growth Cases

162

Annual Energy Outlook 1999 - Market Trend  

Gasoline and Diesel Fuel Update (EIA)

mrktrend.gif (2686 bytes) mrktrend.gif (2686 bytes) Economic Activity International Oil Markets Energy Demand Electricity Oil & Natural Gas Coal Emissions The projections in AEO99 are not statements of what will happen but of what might happen, given the assumptions and methodologies used. The projections are business-as-usual trend forecasts, given known technology, technological and demographic trends, and current laws and regulations. Thus, they provide a policy-neutral reference case that can be used to analyze policy initiatives. EIA does not propose, advocate, or speculate on future legislative and regulatory changes. All laws are assumed to remain as currently enacted; however, the impacts of emerging regulatory changes, when defined, are reflected. Because energy markets are complex, models are simplified representations of energy production and consumption, regulations, and producer and consumer behavior. Projections are highly dependent on the data, methodologies, model structures,

163

Today's Forecast: Improved Wind Predictions | Department of Energy  

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

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

164

Today's Forecast: Improved Wind Predictions | Department of Energy  

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

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

165

ANN-Based Short-Term Load Forecasting in Electricity Markets  

E-Print Network (OSTI)

Abstract—This paper proposes an Artificial Neural Network (ANN)-based short-term load forecasting technique that considers electricity price as one of the main characteristics of the system load, demonstrating the importance of considering pricing when predicting loading in today’s electricity markets. Historical load data from the Ontario Hydro system as well as pricing information from the neighboring system are used for testing, showing the good performance of the proposed method. Keywords: Short-term load forecasting, electricity markets, spot prices, Artificial Neural Networks (ANN)

Hong Chen; Claudio A. Cańizares; Ajit Singh

2001-01-01T23:59:59.000Z

166

RECS 1997 - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

167

Nuclear & Uranium - Analysis & Projections - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

168

Petroleum & Other Liquids - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

169

Natural Gas - Analysis & Projections - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

170

Countries - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance.

171

U.S. Energy Information Administration - EIA - Independent ...  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

172

Short-Term Energy Outlook - U.S. Energy Information Administration ...  

U.S. Energy Information Administration (EIA)

Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance. ... Market-Derived Probabilities: ...

173

Multiscale forecasting and risk measurement in the crude oil market.  

E-Print Network (OSTI)

???With the increasing trend of globalization and deregulation comes the increasing level of structural complexity in the crude oil market, which in turn leads to… (more)

He, Kaijian ( ???)

2011-01-01T23:59:59.000Z

174

Annual Energy Outlook 2000 - Market Trend  

Gasoline and Diesel Fuel Update (EIA)

mrktrend.gif (2686 bytes) Economic Activity International Oil Markets Energy Demand Electricity Oil & Natural Gas Coal Emissions The projections in AEO2000 are not statements of what will happen but of what might happen, given the assumptions and methodologies used. The projections are business-as-usual trend forecasts, given known technology, technological and demographic trends, and current laws and regulations. Thus, they provide a policy-neutral reference case that can be used to analyze policy initiatives. EIA does not propose, advocate, or speculate on future legislative and regulatory changes. All laws are assumed to remain as currently enacted; however, the impacts of emerging regulatory changes, when defined, are reflected.

175

Annual Energy Outlook with Projections to 2025 - Market Trends- Energy  

Gasoline and Diesel Fuel Update (EIA)

Energy Demand Energy Demand Annual Energy Outlook 2005 Market Trends - Energy Demand Figure 42. Energy use per capita and per dollar of gross domestic product, 1970-2025 (index, 1970 = 1). Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure data Average Energy Use per Person Increases in the Forecast Energy intensity, as measured by energy use per 2000 dollar of GDP, is projected to decline at an average annual rate of 1.6 percent, with efficiency gains and structural shifts in the economy offsetting growth in demand for energy services (Figure 42). The projected rate of decline falls between the average rate of 2.3 percent from 1970 through 1986, when energy prices increased in real terms, and the 0.7-percent rate from 1986 through

176

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Coal Coal Although coal use is expected to be displaced by natural gas in some parts of the world, only a slight drop in its share of total energy consumption is projected by 2025. Coal continues to dominate electricity and industrial sector fuel markets in emerging Asia. Figure 50. World Coal Consumption by Region, 1970-2025 (Billion Short Tons). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 51. Coal Share of World Energy Consumption by Sector, 2002, 2015, and 2025 (Percent). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 52. World Recoverable Coal Reserves. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data In the International Energy Outlook 2005 (IEO2005) reference case, world

177

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

G: Key Assumptions for the IEO2005 Kyoto Protocol Case G: Key Assumptions for the IEO2005 Kyoto Protocol Case Energy-Related Emissions of Greenhouse Gases The System for the Analysis of Global energy Markets (SAGE)—the model used by the Energy Information Administration (EIA) to prepare the International Energy Outlook 2005 (IEO2005) mid-term projections—does not include non-energy-related emissions of greenhouse gases, which are estimated at about 15 to 20 percent of total greenhouse gas emissions, based on inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC). SAGE models global energy supply and demand and, therefore, does not address agricultural and other non-energy-related emissions. EIA implicitly assumes that percentage reductions of non-energy-related emissions and their associated abatement costs will be similar to those for energy-related emissions. Non-energy-related greenhouse gas emissions are likely to grow faster than energy-related emissions; however, the marginal abatement costs for non-energy-related greenhouse gas emissions are not known and cannot be estimated reliably. In SAGE, each region’s emissions reduction goal under the Kyoto Protocol is based only on the corresponding estimate of that region’s energy-related carbon dioxide emissions, as determined by EIA data. It is assumed that the required reductions will also be proportionately less than if all gases were included.

178

Volume 15, number 5 June/July 2010 markets products analysis research forecasts  

E-Print Network (OSTI)

fundamentals, lumber and panel demand is going to grow too slowly to support today's production base, keeping/Veneer, Particle- board/MDF, USa, Canada Table 1 WOOD MARKETS' PRicE & HOuSing FOREcASTS: 2010­2011 Product

179

Forecasting market prices in a supply chain game q Christopher Kiekintveld a,*, Jason Miller b  

E-Print Network (OSTI)

), the simulation day, and the linear trend of selling prices from the previous ten days. For predicting future prices, we used the same set of features with the addition of the estimated customer demand trend (s). 4Forecasting market prices in a supply chain game q Christopher Kiekintveld a,*, Jason Miller b

Wellman, Michael P.

180

LBNL Renewable Energy Market and Policy Analysis | Open Energy...  

Open Energy Info (EERE)

LBNL Renewable Energy Market and Policy Analysis (Redirected from Renewable Energy Market and Policy Analysis at LBNL) Jump to: navigation, search Logo: Renewable Energy Market and...

Note: This page contains sample records for the topic "forecasted energy market" 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

LBNL Renewable Energy Market and Policy Analysis | Open Energy...  

Open Energy Info (EERE)

LBNL Renewable Energy Market and Policy Analysis Jump to: navigation, search Logo: Renewable Energy Market and Policy Analysis at LBNL Name Renewable Energy Market and Policy...

182

Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) | Open  

Open Energy Info (EERE)

Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Jump to: navigation, search LEDSGP green logo.png FIND MORE DIA TOOLS This tool is part of the Development Impacts Assessment (DIA) Toolkit from the LEDS Global Partnership. Tool Summary LAUNCH TOOL Name: Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Agency/Company /Organization: Energy Sector Management Assistance Program of the World Bank Sector: Energy Focus Area: Non-renewable Energy Topics: Baseline projection, Co-benefits assessment, GHG inventory Resource Type: Software/modeling tools User Interface: Spreadsheet Complexity/Ease of Use: Simple Website: www.esmap.org/esmap/EFFECT Cost: Free Equivalent URI: www.esmap.org/esmap/EFFECT Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Screenshot

183

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Table 1. Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Table 1. Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Average Absolute Percent Error Variable AEO82 to AEO98 AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 Consumption Total Energy Consumption 1.7 1.7 1.8 1.9 1.9 2.1 Total Petroleum Consumption 2.9 2.8 2.9 3.0 2.9 2.9 Total Natural Gas Consumption 5.7 5.6 5.6 5.5 5.5 6.5 Total Coal Consumption 3.0 3.2 3.3 3.5 3.6 3.7 Total Electricity Sales 1.7 1.8 1.9 2.4 2.5 2.4 Production Crude Oil Production 4.3 4.5 4.5 4.5 4.5 4.7 Natural Gas Production 4.8 4.7 4.6 4.6 4.4 4.4 Coal Production 3.6 3.6 3.5 3.7 3.6 3.8 Imports and Exports Net Petroleum Imports 9.5 8.8 8.4 7.9 7.4 7.5 Net Natural Gas Imports 16.7 16.0 15.9 15.8 15.8 15.4

185

A-Z Index - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

186

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

J: Regional Definitions J: Regional Definitions Figure J1. Map of the Six Basic Country Groupings. Need help, contact the National Energy Information Center at 202-586-8800. The six basic country groupings used in this report (Figure J1) are defined as follows: Mature Market Economies (15 percent of the 2005 world population): North America—United States, Canada, and Mexico; Western Europe—Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, and the United Kingdom; Mature Market Asia—Japan, Australia, and New Zealand. Transitional Economies (6 percent of the 2005 world population): Eastern Europe (EE)—Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Hungary, Macedonia, Poland, Romania, Serbia and Montenegro,

187

Analyzing and Forecasting Volatility Spillovers, Asymmetries and Hedging in Major Oil Markets  

E-Print Network (OSTI)

Abstract: Crude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at-Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas Intermediate (USA), Brent (North Sea), Dubai/Oman (Middle East), and Tapis (Asia-Pacific), which are likely to be highly correlated. This paper analyses the volatility spillover and asymmetric effects across and within the four markets, using three multivariate GARCH models, namely the constant conditional correlation (CCC), vector ARMA-GARCH (VARMA-GARCH) and vector ARMA-asymmetric GARCH (VARMA-AGARCH) models. A rolling window approach is used to forecast the 1-day ahead conditional correlations. The paper presents evidence of volatility spillovers and asymmetric effects on the conditional variances for most pairs of series. In addition, the forecast conditional correlations between pairs of crude oil returns have both positive and negative trends. Moreover, the optimal hedge ratios and optimal portfolio weights of crude oil across different assets and market portfolios are evaluated in order to provide important policy implications for risk management in crude oil markets.

Chia-lin Chang; Michael Mcaleer; Roengchai Tansuchat; Chia-lin Chang; Michael Mcaleer; Roengchai Tansuchat

2010-01-01T23:59:59.000Z

188

Market Analyses | Department of Energy  

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

Market Analyses Market Analyses Market Analyses November 1, 2013 - 11:40am Addthis Need information on the market potential for combined heat and power (CHP) in the U.S.? These assessments and analyses cover a wide range of markets including commercial and institutional buildings and facilities, district energy, and industrial sites. The market potential for CHP at federal sites and in selected states/regions is also examined. Commercial CHP and Bioenergy Systems for Landfills and Wastewater Treatment Plants Part I, 17 pp and Part II, 28 pp, Nov. 2007 Cooling, Heating, and Power for Commercial Buildings: Benefits Analysis, 310 pp, April 2002 Engine Driven Combined Heat and Power: Arrow Linen Supply, 21 pp, Dec. 2008 Integrated Energy Systems for Buildings: A Market Assessment, 77 pp,

189

National Renewable Energy Laboratory Technology Marketing ...  

National Renewable Energy Laboratory Technology Marketing Summaries. Here you’ll find marketing summaries for technologies available for licensing ...

190

Assumptions to the Annual Energy Outlook 2001 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2001, DOE/EIA-M060(2001) January 2001. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves

191

Assumptions to the Annual Energy Outlook 2002 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2002, DOE/EIA-M060(2002) (Washington, DC, January 2002). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves

192

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

Science Conference Proceedings (OSTI)

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

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

2005-02-09T23:59:59.000Z

193

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface This report presents international energy projections through 2025, prepared by the Energy Information Administration, including outlooks for major energy fuels and associated carbon dioxide emissions. The International Energy Outlook 2005 (IEO2005) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2025. U.S. projections appearing in IEO2005 are consistent with those published in EIAÂ’s Annual Energy Outlook 2005 (AEO2005), which was prepared using the National Energy Modeling System (NEMS). Although the IEO typically uses the same reference case as the AEO, IEO2005 has adopted the October futures case from AEO2005 as its reference case for the United States. The October futures case, which has an assumption of higher world oil prices than the AEO2005 reference case, now appears to be a more likely projection. The reference case prices will be reconsidered for the next AEO. Based on information available as of July 2005, the AEO2006 reference case will likely reflect world oil prices higher than those in the IEO2005 reference case.

194

The Value of Seasonal Climate Forecasts in Managing Energy Resources  

Science Conference Proceedings (OSTI)

Research and interviews with officials of the United States energy industry and a systems analysis of decision making in a natural gas utility lead to the conclusion that seasonal climate forecasts would only have limited value in fine tuning the ...

Edith Brown Weiss

1982-04-01T23:59:59.000Z

195

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model's parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. (Lawrence Berkeley Lab., CA (United States) Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.); Hwang, R. (Lawrence Berkeley Lab., CA (United States))

1992-02-01T23:59:59.000Z

196

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model`s parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. [Lawrence Berkeley Lab., CA (United States)]|[Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics]|[Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.; Hwang, R. [Lawrence Berkeley Lab., CA (United States)

1992-02-01T23:59:59.000Z

197

Cost forecasts: Euyropean International High-Energy Physics facilities - Million Swiss Francs at 1966 prices  

E-Print Network (OSTI)

Cost forecasts: Euyropean International High-Energy Physics facilities - Million Swiss Francs at 1966 prices

ECFA meeting

1966-01-01T23:59:59.000Z

198

Wind Energy Technology Trends: Comparing and Contrasting Recent Cost and Performance Forecasts (Poster)  

DOE Green Energy (OSTI)

Poster depicts wind energy technology trends, comparing and contrasting recent cost and performance forecasts.

Lantz, E.; Hand, M.

2010-05-01T23:59:59.000Z

199

Market Acceleration | Department of Energy  

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

Market Acceleration Market Acceleration Market Acceleration Photo of several men on a floating platform that is lowering monitoring tools into the ocean. The Water Power Program works to foster a commercial market for marine and hydrokinetic (MHK) energy devices in order to achieve its goal of the nation obtaining 15% of its electricity needs from all types of water power by 2030. Though marine and hydrokinetic energy is still in its infancy, the program is developing a robust portfolio of projects to accelerate wave, tidal and current project deployments and development of the MHK market in general. These projects include project siting activities, market assessments, environmental impact analyses, and research supporting technology commercialization. Learn more about the Water Power Program's work in the following areas of

200

Three Essays on Energy Economics and Forecasting  

E-Print Network (OSTI)

This dissertation contains three independent essays relating energy economics. The first essay investigates price asymmetry of diesel in South Korea by using the error correction model. Analyzing weekly market prices in the pass-through of crude oil, this model shows asymmetric price response does not exist at the upstream market but at the downstream market. Since time-variant residuals are found by the specified models for both weekly and daily retail prices at the downstream level, these models are implemented by a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) process. The estimated results reveal that retail prices increase fast in the rise of crude oil prices but decrease slowly in the fall of those. Surprisingly, retail prices rarely respond to changes of crude oil prices for the first five days. Based on collusive behaviors of retailers, this price asymmetry in Korea diesel market is explained. The second essay aims to evaluate the new incentive system for biodiesel in South Korea, which keeps the blend mandate but abolishes tax credits for government revenues. To estimate changed welfare from the new policy, a multivariate stochastic simulation method is applied into time-series data for the last five years. From the simulation results, the new biodiesel policy will lead government revenues to increases with the abolishment of tax credit. However, increased prices of blended diesel will cause to decrease demands of both biodiesel and blended diesel, so consumer and producer surplus in the transport fuel market will decrease. In the third essay, the Regression - Seasonal Autoregressive Integrated Moving Average (REGSARIMA) model is employed to predict the impact of air temperature on daily peak load demand in Houston. Compared with ARIMA and Seasonal Model, a REGARIMA model provides the more accurate prediction for daily peak load demand for the short term. The estimated results reveal air temperature in the Houston areas causes an increase in electricity consumption for cooling but to save that for heating. Since the daily peak electricity consumption is significantly affected by hot air temperature, this study makes a conclusion that it is necessary to establish policies to reduce urban heat island phenomena in Houston.

Shin, Yoon Sung

2011-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasted energy market" 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

NREL Market Analysis | Open Energy Information  

Open Energy Info (EERE)

NREL Market Analysis NREL Market Analysis Jump to: navigation, search Tool Summary Name: NREL Market analysis Agency/Company /Organization: National Renewable Energy Laboratory Sector: Energy Topics: Market analysis Website: www.nrel.gov/analysis/market_analysis.html NREL Market analysis Screenshot References: NREL Market analysis[1] Summary "The laboratory's market analysis helps increase the use of renewable energy (RE) and energy efficiency (EE) technologies in the marketplace by providing strategic information to stakeholders interested in rapidly changing electricity markets. Our high-quality and objective crosscutting assessments and analysis support informed decision making. Primary focuses include:" Energy Technology/Program Cost, Performance, and Market Data

202

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Appendix A.1 Natural Gas Price Data for Futures Market andSTEO Error A.1 Natural Gas Price Data for Futures Market andforecasts for natural gas prices as reported by the Energy

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

2005-01-01T23:59:59.000Z

203

Application of a new hybrid neuro-evolutionary system for day-ahead price forecasting of electricity markets  

Science Conference Proceedings (OSTI)

In this paper, a new forecast strategy is proposed for day-ahead prediction of electricity prices, which are so valuable for both producers and consumers in the new competitive electric power markets. However, electricity price has a nonlinear, volatile ... Keywords: Evolutionary algorithm, Hybrid neuro-evolutionary system, Neural network, Price forecast

Nima Amjady; Farshid Keynia

2010-06-01T23:59:59.000Z

204

Orphan drugs : future viability of current forecasting models, in light of impending changes to influential market factors  

E-Print Network (OSTI)

Interviews were conducted to establish a baseline for how orphan drug forecasting is currently undertaken by financial market and industry analysts with the intention of understanding the variables typically accounted for ...

Gottlieb, Joshua

2011-01-01T23:59:59.000Z

205

Energy Efficiency Markets in India  

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

Energy Efficiency Markets in India Speaker(s): S. Padmanabhan Date: June 2, 2005 - 12:00pm Location: Bldg. 90 Seminar HostPoint of Contact: Jayant Sathaye S. Padmanabhan has...

206

Energy Market Impacts of Alternative Greenhouse Gas Intensity Reduction Goals  

Gasoline and Diesel Fuel Update (EIA)

1 1 Energy Market Impacts of Alternative Greenhouse Gas Intensity Reduction Goals March 2006 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. Service Reports are prepared by the Energy Information Administration upon special request and are based on assumptions specified by the requester. Energy Information Administration / Energy Market Impacts of Alternative Greenhouse Gas Intensity Reduction Goals

207

Market barriers to energy efficiency  

SciTech Connect

Discussions of energy policy in an environmentally constrained world often focus on the use of tax instruments to internalize the external effects of energy utilization or achieve specified reductions in energy use in the most cost-effective manner. A substantial literature suggests, however, that significant opportunities exist to reduce energy utilization by implementing technologies that are cost-effective under prevailing economic conditions but that are not fully implemented by existing market institutions. This paper examines the theory of the market for energy-using equipment, showing that problems of imperfect information and transaction costs may bias rational consumers to purchase devices that use more energy than those that would be selected by a well-informed social planner guided by the criterion of economic efficiency. Consumers must base their purchase decisions on observed prices and expectations of postpurchase equipment performance. If it is difficult or costly for individuals to form accurate and precise expectations, the level of energy efficiency achieved by competitive markets will vary from the socially efficient outcome. Such market barriers'' suggest a role for regulatory intervention to improve market performance at prevailing energy prices.

Howarth, R.B. (Lawrence Berkeley Lab., CA (United States)); Andersson, B. (Stockholm School of Economics (Sweden))

1992-06-01T23:59:59.000Z

208

Market barriers to energy efficiency  

SciTech Connect

Discussions of energy policy in an environmentally constrained world often focus on the use of tax instruments to internalize the external effects of energy utilization or achieve specified reductions in energy use in the most cost-effective manner. A substantial literature suggests, however, that significant opportunities exist to reduce energy utilization by implementing technologies that are cost-effective under prevailing economic conditions but that are not fully implemented by existing market institutions. This paper examines the theory of the market for energy-using equipment, showing that problems of imperfect information and transaction costs may bias rational consumers to purchase devices that use more energy than those that would be selected by a well-informed social planner guided by the criterion of economic efficiency. Consumers must base their purchase decisions on observed prices and expectations of postpurchase equipment performance. If it is difficult or costly for individuals to form accurate and precise expectations, the level of energy efficiency achieved by competitive markets will vary from the socially efficient outcome. Such ``market barriers`` suggest a role for regulatory intervention to improve market performance at prevailing energy prices.

Howarth, R.B. [Lawrence Berkeley Lab., CA (United States); Andersson, B. [Stockholm School of Economics (Sweden)

1992-06-01T23:59:59.000Z

209

Rainbow Energy Marketing Corp | Open Energy Information  

Open Energy Info (EERE)

Rainbow Energy Marketing Corp Rainbow Energy Marketing Corp Jump to: navigation, search Name Rainbow Energy Marketing Corp Place North Dakota Utility Id 15711 Utility Location Yes Ownership W NERC Location MRO Activity Buying Transmission Yes Activity Wholesale Marketing Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png No rate schedules available. Average Rates No Rates Available References ↑ "EIA Form EIA-861 Final Data File for 2010 - File1_a" Retrieved from "http://en.openei.org/w/index.php?title=Rainbow_Energy_Marketing_Corp&oldid=411422" Categories: EIA Utility Companies and Aliases

210

Tractebel Energy Marketing Inc | Open Energy Information  

Open Energy Info (EERE)

Tractebel Energy Marketing Inc Tractebel Energy Marketing Inc Jump to: navigation, search Name Tractebel Energy Marketing Inc Place Texas Utility Id 19090 Utility Location Yes Ownership W NERC Location TRE NERC ERCOT Yes NERC MRO Yes NERC SERC Yes NERC SPP Yes NERC WECC Yes Activity Buying Transmission Yes Activity Wholesale Marketing Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png No rate schedules available. Average Rates No Rates Available References ↑ "EIA Form EIA-861 Final Data File for 2010 - File1_a" Retrieved from "http://en.openei.org/w/index.php?title=Tractebel_Energy_Marketing_Inc&oldid=411854

211

Assumptions to the Annual Energy Outlook 2000 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

212

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

energy policy initiatives (EIA 1990). Utilities rely on end-use forecasting models in order to assess market trends

Johnson, F.X.

2010-01-01T23:59:59.000Z

213

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

recent years, with higher capacity utilization rates reported for many existing nuclear facilities and expectations that most existing plants in the mature market and...

214

International Energy Outlook - World Oil Markets  

Gasoline and Diesel Fuel Update (EIA)

World Oil Markets World Oil Markets International Energy Outlook 2004 World Oil Markets In the IEO2004 forecast, OPEC export volumes are expected to more than double while non-OPEC suppliers maintain their edge over OPEC in overall production. Prices are projected to rise gradually through 2025 as the oil resource base is further developed. Throughout most of 2003, crude oil prices remained near the top of the range preferred by producers in the Organization of Petroleum Exporting Countries (OPEC), $22 to $28 per barrel for the OPEC “basket price.” OPEC producers continued to demonstrate disciplined adherence to announced cutbacks in production. Throughout 2003, the upward turn in crude oil prices was brought about by a combination of three factors. First, a general strike against the Chavez regime resulted in a sudden loss of much of Venezuela’s oil exports. Although the other OPEC producers agreed to increase their production capacities to make up for the lost Venezuelan output, the obvious strain on worldwide spare capacity kept prices high. Second, price volatility was exacerbated by internal conflict in Nigeria. Third, prospects for a return to normalcy in the Iraqi oil sector remained uncertain as residual post-war turmoil continued in Iraq.

215

Renewable Energy Markets and Policies  

E-Print Network (OSTI)

Renewable Energy Markets and Policies Romeo Pacudan, PhD Risoe National Laboratory, Denmark HAPUA Working Group No. 4 Meeting Renewable Energy and Environment in ASEAN Melia Hotel, Hanoi, Vietnam 23-24 June 2005 #12;1. Renewables in Energy Supply Share in Primary Energy Supply 5,9 5,7 4,8 5,8 0 1 2 3 4 5

216

Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts  

Reports and Publications (EIA)

The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

Information Center

2010-06-01T23:59:59.000Z

217

Coal News and Markets - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Financial market analysis and financial data for major energy companies. Environment. ... Country energy information, detailed and overviews. Highlights

218

Effect of Increased Natural Gas Exports on Domestic Energy Markets  

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

Effect of Increased Natural Gas Effect of Increased Natural Gas Exports on Domestic Energy Markets as requested by the Office of Fossil Energy January 2012 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the U.S. Department of Energy or other Federal agencies. U.S. Energy Information Administration | Effects of Increased Natural Gas Exports on Domestic Energy Markets i Contacts The Office of Energy Analysis prepared this report under the guidance of John Conti, Assistant

219

Gamesa Wind to Market | Open Energy Information  

Open Energy Info (EERE)

Market Jump to: navigation, search Name Gamesa Wind to Market Place Spain Sector Wind energy Product Represents the interests of wind project owner clients in the Spanish...

220

SURVIVABLE ENERGY MARKETS 1. Introduction. Recent ...  

E-Print Network (OSTI)

an in-depth analysis of energy markets design and procedural rules ..... are other information that can be collected to give market players the right economic.

Note: This page contains sample records for the topic "forecasted energy market" 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

National Renewable Energy Laboratory Technology Marketing ...  

National Renewable Energy Laboratory Technology Marketing Summaries. Here you’ll find marketing summaries for technologies available for licensing from the National ...

222

National Energy Technology Laboratory Technology Marketing ...  

National Energy Technology Laboratory Technology Marketing Summaries. Here you’ll find marketing summaries for technologies available for licensing from the ...

223

Annual Energy Outlook 2006 with Projections to 2030 - Market Trends -  

Gasoline and Diesel Fuel Update (EIA)

Market Trends - Market Drivers Market Trends - Market Drivers Annual Energy Outlook 2006 with Projections to 2030 Strong Economic Growth Is Expected To Continue Through 2030 Figure 24. Average annual growth rates of real GDP, labor frce, and productivity in three cases, 2004-2030 (percent per year). Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure data AEO2006 presents three views of economic growth for the forecast period from 2004 through 2030. Although probabilities are not assigned, the reference case reflects the most likely view of how the economy will unfold over the period. In the reference case, the NationÂ’s economic growth, measured in terms of real GDP based on 2000 chain-weighted dollars, is projected to average 3.0 percent per year (Figure 24). The labor force is

224

A forecasting model of tourist arrivals from major markets to Thailand  

E-Print Network (OSTI)

International tourism is a rapidly growing phenomenon hics. worldwide. However, the East Asia and Pacific Region is expected to be the focus of the worldwide tourism industry in the new millennium because tourist arrivals and receipts registered a growth about twice the rates of industrialized countries in the last decade. The tourism industry has become a powerful engine for economic development and a major foreign exchange generator. With such growth and increased competition, it is vitally important to forecast tourism demand in the region and understand the factors affecting demand. Considering the national importance of tourism, Thailand was chosen as the destination country with nine major markets as the countries of origin. A model was developed for each country to forecast tourism demand from that market. Multiple regression analysis was applied over time series data. The empirical results suggest that independent variables, such as income level in the country of origin, prices of tourism goods in the destination country, currency exchange rate between the origin and destination country, and rooms supply in destination, do affect tourism demand. Qualitative factors, represented by dummy variables, namely special promotional program and political unrest, show slight impact on demand. The study reveals that there are differences in the relative impacts of variables among the tourist generating countries. Thus, country-specific forecasting models and strategies must be formulated to reflect the uniqueness of each country of origin. Furthermore, forecasting techniques should include more qualitative factors to better asses their impacts on tourism demand. For future research, it is suggested that the models developed be updated regularly to reflect changes in the selected independent variables. Surveys and studies dealing with consumer motivation should be carried out to understand more about the tourists themselves and how they select particular destinations and types of tourism. Finally, in order to take advantage of modern technologies, the Internet is suggested as a tool to promote tourism.

Hao, Ching

1998-01-01T23:59:59.000Z

225

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

E-Print Network (OSTI)

the accuracy of two methods to forecast natural gas prices:forecasting models along with the AEO forecast. Appendix ATable 1. Forecast Year AEO Predicted Price from 1996-2003

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

2005-01-01T23:59:59.000Z

226

Properties of energy-price forecasts for scheduling  

Science Conference Proceedings (OSTI)

Wholesale electricity markets are becoming ubiquitous, offering consumers access to competitively-priced energy. The cost of energy is often correlated with its environmental impact; for example, environmentally sustainable forms of energy might benefit ...

Georgiana Ifrim; Barry O'Sullivan; Helmut Simonis

2012-10-01T23:59:59.000Z

227

Solar total energy systems final technical summary report. Volume I. Solar total energy systems market penetration  

SciTech Connect

The results of the market penetration analysis of Solar Total Energy Systems (STES) for the industrial sector are described. Performance data derived for STES commercial applications are included. The energy use and price forecasts used in the analysis are summarized. The STES Applications Model (SAM), has been used to develop data on STES development potential by state and industry as a function of time from 1985 through 2015. A second computer code, the Market Penetration Model (MPM), has been completed and used to develop forecasts of STES market penetration and national energy displacement by fuel type. This model was also used to generate sensitivity factors for incentives, and variations in assumptions of cost of STES competing fuel. Results for the STES performance analysis for commercial applications are presented. (MHR)

Bush, L.R.; Munjal, P.K.

1978-03-31T23:59:59.000Z

228

Energy Efficiency in Regulated and Deregulated Markets  

E-Print Network (OSTI)

at 274. 10. Id. 11. Id. ENERGY EFFICIENCY relative to market2002). 19. See id. at 204-205. ENERGY EFFICIENCY prices,it renders energy efficiency less attractive. In a market

Rotenberg, Edan

2005-01-01T23:59:59.000Z

229

Advanced Modeling of Renewable Energy Market Dynamics: May 2006  

SciTech Connect

This report documents a year-long academic project, presenting selected techniques for analysis of market growth, penetration, and forecasting applicable to renewable energy technologies. Existing mathematical models were modified to incorporate the effects of fiscal policies and were evaluated using available data. The modifications were made based on research and classification of current mathematical models used for predicting market penetration. An analysis of the results was carried out, based on available data. MATLAB versions of existing and new models were developed for research and policy analysis.

Evans, M.; Little, R.; Lloyd, K.; Malikov, G.; Passolt, G.; Arent, D.; Swezey, B.; Mosey, G.

2007-08-01T23:59:59.000Z

230

Assumptions to the Annual Energy Outlook 1999 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

coal.gif (4423 bytes) coal.gif (4423 bytes) The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Model Documentation: Coal Market Module of the National Energy Modeling System, DOE/EIA-MO60. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

231

Market Acceleration | Department of Energy  

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

Market Acceleration Market Acceleration Market Acceleration Photo of the Wanapum Dam. Hydropower contributes significantly to the nation's renewable energy portfolio; over the last decade, the United States obtained nearly 7% of its electricity from hydropower sources. Already the largest source of renewable electricity in the United States, there remains a vast untapped resource potential in hydropower. To achieve its vision of supporting 15% of our nation's electricity needs from water power by 2030, the Water Power Program works to address environmental and regulatory barriers that prevent significant amounts of deployment; to assess and quantify the value of hydropower to the nation's electric grid and its ability to integrate other variable renewable energy technologies; and to develop a vibrant U.S.

232

Assumptions to the Annual Energy Outlook - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumption to the Annual Energy Outlook Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2004, DOE/EIA-M060(2004) (Washington, DC, 2004). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of capacity utilization of mines, mining capacity, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

233

Regions in Energy Market Models  

DOE Green Energy (OSTI)

This report explores the different options for spatial resolution of an energy market model--and the advantages and disadvantages of models with fine spatial resolution. It examines different options for capturing spatial variations, considers the tradeoffs between them, and presents a few examples from one particular model that has been run at different levels of spatial resolution.

Short, W.

2007-02-01T23:59:59.000Z

234

California Regional Wind Energy Forecasting System Development, Vol. 3  

Science Conference Proceedings (OSTI)

The rated capacity of wind generation in California is expected to grow rapidly in the future beyond the approximately 2100 MW in place at the end of 2005. The main drivers are the state's 20 percent Renewable Portfolio Standard requirement in 2010 and the low cost of wind energy relative to other renewable energy sources. As wind is an intermittent generation resource and weather changes can cause large and rapid changes in output, system operators will need accurate and robust wind energy forecasting ...

2006-11-15T23:59:59.000Z

235

Press Room - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

American Energy Security and Innovation: An Assessment of North America's Energy Resources pdf. Subject: EIA, Energy Markets, Forecasts: Presented by:

236

Glossary - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance. ... State Energy Data System ...

237

California Wind Energy Forecasting System Development and Testing Phase 2: 12-Month Testing  

Science Conference Proceedings (OSTI)

This report describes results from the second phase of the California Wind Energy Forecasting System Development and Testing Project.

2003-07-22T23:59:59.000Z

238

Energy Market Outlook  

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

Helping Customers Meet Helping Customers Meet Their Diverse Energy Goals Federal Utility Partnership Working Group Spring 2013 - May 22-23 San Francisco, CA Hosted by: Pacific Gas and Electric Company 1 Company Facts  Fortune 200 company located in San Francisco, CA  $15B in operating revenues in 2011  20,000 employees Energy Supply  Services to 15M people: * 5.2M Electric accounts * 4.3M Natural Gas accounts  Peak electricity demand: 20,000 MW  Over 50% of PG&E's electric supply comes from non-greenhouse gas emitting facilities Service Territory  70,000 sq. miles with diverse topography  160,000 circuit miles of electric transmission and distribution lines  49,000 miles of natural gas transmission and distribution pipelines

239

ELECTRICITY DEMAND FORECAST COMPARISON REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005 ..............................................................................3 Residential Forecast Comparison ..............................................................................................5 Nonresidential Forecast Comparisons

240

Performance Contracting and Energy Efficiency in the State Government Market  

E-Print Network (OSTI)

the State Government Market Energy Performance Contractingin the State Government Market Energy Performance Contractsin size of the energy services market among states, we

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasted energy market" 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

Considerations for Emerging Markets for Energy Savings Certificates  

E-Print Network (OSTI)

in the broader energy efficiency markets and protocols thatsector of the energy efficiency market. Carbon Marketfor Emerging Markets for Energy Savings Certificates DE-

Friedman, Barry

2009-01-01T23:59:59.000Z

242

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Energy-Related Carbon Dioxide Emissions Energy-Related Carbon Dioxide Emissions In the coming decades, responses to environmental issues could affect patterns of energy use around the world. Actions to limit greenhouse gas emissions could alter the level and composition of energy-related carbon dioxide emissions by energy source. Figure 67. World Carbon Dioxide Emissions by Region, 2002-2025 (Gigawatts). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Carbon dioxide is one of the most prevalent greenhouse gases in the atmosphere. Anthropogenic (human-caused) emissions of carbon dioxide result primarily from the combustion of fossil fuels for energy, and as a result world energy use has emerged at the center of the climate change debate. In the International Energy Outlook 2005 (IEO2005) reference case, world

243

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Update on Petroleum, Natural Gas, Heating Oil and Gasoline.of the Market for Natural Gas Futures. Energy Journal 16 (Modeling Forum. 2003. Natural Gas, Fuel Diversity and North

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

2005-01-01T23:59:59.000Z

244

Emerging challenges in wind energy forecasting for Australia  

E-Print Network (OSTI)

Growing concern about climate change has led to significant interest in renewable energy resources such as wind energy. However, such non-storable energy sources present a significant issue – how to maintain continuity of supply in the event of possible disturbances to power production. For example, in the case of wind energy, such disturbances can result from extreme weather events due to frontal systems or rapidly evolving low pressure systems. Such events cannot be avoided, but if they can be accurately forecast, their impact can be minimized by ensuring that alternative sources are available to make up any power shortfalls. Thus as wind energy makes up an ever greater component of our energy supply, there is greater interest in developing models to produce accurate, local scale, wind-focused forecasts for wind farm sites that push the boundaries of current weather prediction techniques. In this article we present a case study focusing on the Woolnorth wind farm on the northwest tip of Tasmania, to highlight some of the key challenges that will be involved in developing such forecasts.

Merlinde J. Kay; Nicholas Cutler; Adam Micolich; Iain Macgill; Hugh Outhred Centre For Energy; Environmental Markets; South Wales

2008-01-01T23:59:59.000Z

245

U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance. ... Job Seekers › Policy Analysts ...

246

2008 Federal Energy Management Program (FEMP) Market Report  

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

JULY 2009 2008 FEDERAL ENERGY MANAGEMENT PROGRAM (FEMP) MARKET REPORT i 2008 FEMP Annual Market Report 2008 FEMP Annual Market Report The Market Environment for Federal Government...

247

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

the forecast. In 1978 the Natural Gas Policy Act was passedof Other Natural Gas Price Forecasts Researchers and policyresearchers and policy makers who utilize natural gas prices

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

2005-01-01T23:59:59.000Z

248

Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS  

E-Print Network (OSTI)

Comparisons are made of energy forecasts using results from the Industrial module of the National Energy Modeling System (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy Modeling System (ITEMS), a model developed for industrial energy analysis at the Pacific Northwest National Laboratory. Although the results are mixed, generally ITEMS show greater penetration of energy efficient technologies and thus lower energy use, even though the business as usual forecasts for ITEMS uses a higher discount rate than NEMS uses.

Roop, J. M.; Dahowski, R. T

2000-04-01T23:59:59.000Z

249

Energy Market Alerts - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Financial market analysis and financial data for major energy companies. Environment. Greenhouse gas data, ... Country energy information, detailed ...

250

Energy Efficiency in Regulated and Deregulated Markets  

E-Print Network (OSTI)

information and transaction costs impede the functioning of markets, energymarket barriers to energy efficiency by focusing on informationmarket suggest credi- ble information provision programs like Energy

Rotenberg, Edan

2005-01-01T23:59:59.000Z

251

Petroleum Market Module - Energy Information Administration  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 137 Petroleum Market Module Table 11.2. Year-round gasoline ...

252

NREL: Transmission Grid Integration - Energy Imbalance Markets  

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

utilities are therefore considering the adoption of a large-scale energy imbalance market to address fluctuations in electricity generation and load. In an energy imbalance...

253

Petroleum Marketing Annual 2001 - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Energy Information Administration (U.S. Dept. of Energy) ... Front Matter. Petroleum Marketing Annual Cover Page, Preface, and Table of Contents

254

U.S. Energy Market Outlook  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration Independent Statistics & Analysis www.eia.gov U.S. Energy Market Outlook for United States Association for ...

255

Review of Wind Energy Forecasting Methods for Modeling Ramping Events  

DOE Green Energy (OSTI)

Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

2011-03-28T23:59:59.000Z

256

Weather forecast-based optimization of integrated energy systems.  

SciTech Connect

In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.

Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.

2009-03-01T23:59:59.000Z

257

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Projections by End-Use Sector and Region Tables (2002-2025) Projections by End-Use Sector and Region Tables (2002-2025) Formats Reference Case Projections by End-Use Sector and Region Data Tables (1 to 15 complete) Excel PDF Table Title Table D1 Delivered Energy Consumption in the United States by End-Use Sector and Fuel Excel PDF Table D2 Delivered Energy Consumption in Canada by End-Use Sector and Fuel Excel PDF Table D3 Delivered Energy Consumption in Mexico by End-Use Sector and Fuel Excel PDF Table D4 Delivered Energy Consumption in Western Europe by End-Use Sector and Fuel Excel PDF Table D5 Delivered Energy Consumption in Japan by End-Use Sector and Fuel Excel PDF Table D6 Delivered Energy Consumption in Australia/New Zealand by End-Use Sector and Fuel Excel PDF Table D7 Delivered Energy Consumption in the Former Soviet Union by End-Use Sector and Fuel

258

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Low Economic Growth Case Projection Tables (1990-2025) Low Economic Growth Case Projection Tables (1990-2025) Formats Low Economic Growth Case Data Projection Tables (1 to 13 complete) Excel PDF Table Title Table C1 World Total Primary Energy Consumption by Region, Low Economic Growth Case Excel PDF Table C2 World Total Energy Consumption by Region and Fuel, Low Economic Growth Case Excel PDF Table C3 World Gross Domestic Product (GDP) by Region, Low Economic Growth Case Excel PDF Table C4 World Oil Consumption by Region, Low Economic Growth Case Excel PDF Table C5 World Natural Cas Consumption by Region, Low Economic Growth Case Excel PDF Table C6 World Coal Consumption by Region, Low Economic Growth Case Excel PDF Table C7 World Nuclear Energy Consumption by Region, Low Economic Growth Case Excel PDF Table C8 World Consumption of Hydroelectricity and Other Renewable Energy by Region, Low Economic Growth Case

259

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

High Economic Growth Case Projection Tables (1990-2025) High Economic Growth Case Projection Tables (1990-2025) Formats High Economic Growth Case Data Projection Tables (1 to 13 complete) Excel PDF Table Title Table B1 World Total Primary Energy Consumption by Region, High Economic Growth Case Excel PDF Table B2 World Total Energy Consumption by Region and Fuel, High Economic Growth Case Excel PDF Table B3 World Gross Domestic Product (GDP) by Region, High Economic Growth Case Excel PDF Table B4 World Oil Consumption by Region, High Economic Growth Case Excel PDF Table B5 World Natural Cas Consumption by Region, High Economic Growth Case Excel PDF Table B6 World Coal Consumption by Region, High Economic Growth Case Excel PDF Table B7 World Nuclear Energy Consumption by Region, High Economic Growth Case Excel PDF Table B8 World Consumption of Hydroelectricity and Other Renewable Energy by Region, High Economic Growth Case

260

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Projection Tables (1990-2025) Projection Tables (1990-2025) Formats All Reference Case Data Projection Tables (1 to 14 complete) Excel PDF Table Title Table A1 World Total Primary Energy Consumption by Region, Reference Case Excel PDF Table A2 World Total Energy Consumption by Region and Fuel, Reference Case Excel PDF Table A3 World Gross Domestic Product (GDP) by Region, Reference Case Excel PDF Table A4 World Oil Consumption by Region, Reference Case Excel PDF Table A5 World Natural Gas Consumption by Region, Reference Case Excel PDF Table A6 World Coal Consumption by Region, Reference Case Excel PDF Table A7 World Nuclear Energy Consumption by Region, Reference Case Excel PDF Table A8 World Consumption of Hydroelectricity and Other Renewable Energy by Region, Reference Case Excel PDF Table A9 World Net Electricity Consumption by Region, Reference Case

Note: This page contains sample records for the topic "forecasted energy market" 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

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Regional Definitions in the International Energy Outlook 2005 Regional Definitions in the International Energy Outlook 2005 Regular readers of the International Energy Outlook (IEO) will notice that, in this edition, the names used to describe country groupings have been changed. Although the organization of countries within the three major groupings has not changed, the nomenclature used in previous editions to describe the groups— namely, industrialized, EE/FSU, and developing— had become somewhat dated and did not accurately reflect the countries within them. Some analysts have argued that several of the countries in the “developing” group (South Korea and China, for instance) could fairly be called “industrialized” today. IEO2005 World Regions Map. Need help, contact the National Energy Information Center at 202-586-8800.

262

Renewable Energy Development in Regulated Markets, 2002  

Science Conference Proceedings (OSTI)

The slowdown in electricity market restructuring since 2000 has dramatically altered opportunities for marketing green energy to retail customers. Indeed, it has become less clear what role direct consumer demand for green energy may play in future renewable energy development. Currently, utilities, green energy activists, and marketers are pursuing a number of new concepts that may increase the scale of renewable energy development. This report evaluates the status and potential of these new green energ...

2003-02-24T23:59:59.000Z

263

Considerations in PromotingConsiderations in Promoting Markets for Sustainable EnergyMarkets for Sustainable Energy  

E-Print Network (OSTI)

Technology Conference 6 Market Barriers: Renewable Energy in Egypt ! Awareness and information ! FinancialConsiderations in PromotingConsiderations in Promoting Markets for Sustainable EnergyMarkets of markets for technologies in north and south #12;21 May 2003 Risø Energy Technology Conference 3 The Goal

264

Electricity price forecasting in a grid environment.  

E-Print Network (OSTI)

??Accurate electricity price forecasting is critical to market participants in wholesale electricity markets. Market participants rely on price forecasts to decide their bidding strategies, allocate… (more)

Li, Guang, 1974-

2007-01-01T23:59:59.000Z

265

Carbon Capital Markets | Open Energy Information  

Open Energy Info (EERE)

Carbon Capital Markets Place London, United Kingdom Zip W1J 8DY Sector Carbon Product London-based fund manager and trader specialising in the carbon and clean energy markets....

266

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

the entire forecast period, primarily because both weather-adjusted peak and electricity consumption were forecast. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, conservation, California Solar Initiative. #12

267

LBNL-60590 JART Distributed energy resources market  

E-Print Network (OSTI)

LBNL-60590 JART Distributed energy resources market diffusion model Karl Magnus Maribua , Ryan M by the Office of Electricity Delivery and Energy Reliability, Distributed Energy Program of the U.S. Department Policy 35 (2007) 4471­4484 Distributed energy resources market diffusion model Karl Magnus Maribua

268

Perils of Long-Range Energy Forecasting: Reflections on Looking Far Ahead  

E-Print Network (OSTI)

! #12;PERILS OF LONG-RANGE ENERGY FORCASTING 255 Fig. 1. Forecasts of the U.S. primary energy notable forecasts of the U.S. primary energy consumption in the year 2000 that were released between have been around energy matters for some time--is the goal of U.S. energy independence charted

Smil, Vaclav

269

Annual Energy Outlook with Projections to 2025-Market Trends - Market  

Gasoline and Diesel Fuel Update (EIA)

Market Drivers Market Drivers Annual Energy Outlook 2004 with Projections to 2025 Market Trends - Market Drivers Index (click to jump links) Trends in Economic Activity International Oil Markets Figure 38. Average annual growth rates of real GDP and economic factors, 1995-2025 (percent). Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure data Trends in Economic Activity Strong Economic Growth Is Expected To Continue The output of the Nation's economy, measured by gross domestic product (GDP), is projected to grow by 3.0 percent per year between 2002 and 2025 (with GDP based on 1996 chain-weighted dollars) (Figure 38). The projected growth rate is slightly lower than the 3.1-percent rate projected in AEO2003. The labor force is projected to increase by 0.9 percent per year

270

International Energy Outlook 2001 - World Oil Markets  

Gasoline and Diesel Fuel Update (EIA)

World Oil Markets World Oil Markets picture of a printer Printer Friendly Version (PDF) In the IEO2001 forecast, periodic production adjustments by OPEC members are not expected to have a significant long-term impact on world oil markets. Prices are projected to rise gradually through 2020 as the oil resource base is expanded. Crude oil prices remained above $25 per barrel in nominal terms for most of 2000 and have been near $30 per barrel in the early months of 2001. Prices were influenced by the disciplined adherence to announced cutbacks in production by members of the Organization of Petroleum Exporting Countries (OPEC). OPECÂ’s successful market management strategy was an attempt to avoid a repeat of the ultra-low oil price environment of 1998 and early 1999. Three additional factors contributed to the resiliency of oil prices in

271

Energy Efficiency Program and Market Trends  

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

Energy Efficiency Program and Market Trends Energy Efficiency Program and Market Trends EETD's energy efficiency program and market trends research includes technical, economic and policy analysis to inform public and private decision-making on public-interest issues related to utility-sector energy efficiency programs and regulation, and government-funded energy efficiency initiatives. LBNL's research in this area is focused on: Energy efficiency portfolio planning and market assessment, Design and implementation of a portfolio of energy efficiency programs that achieve various policy objectives Utility sector energy efficiency business models, Options for administering energy efficiency programs, Evaluation, measurement and verification of energy efficiency impacts and ESCO industry and market trends and performance.

272

Univariate modeling and forecasting of monthly energy demand time series using abductive and neural networks  

Science Conference Proceedings (OSTI)

Neural networks have been widely used for short-term, and to a lesser degree medium and long-term, demand forecasting. In the majority of cases for the latter two applications, multivariate modeling was adopted, where the demand time series is related ... Keywords: Abductive networks, Energy demand, Medium-term load forecasting, Neural networks, Time series forecasting, Univariate time series analysis

R. E. Abdel-Aal

2008-05-01T23:59:59.000Z

273

Large-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random Fields  

E-Print Network (OSTI)

pricing. Although it is known that probabilistic forecasts (which give a distribution over possible futureLarge-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random Fields Matt Wytock and J. Zico Kolter Abstract-- Short-term forecasting is a ubiquitous practice

Kolter, J. Zico

274

International Voluntary Renewable Energy Markets (Presentation)  

Science Conference Proceedings (OSTI)

This presentation provides an overview of international voluntary renewable energy markets, with a focus on the United States and Europe. The voluntary renewable energy market is the market in which consumers and institutions purchase renewable energy to match their electricity needs on a voluntary basis. In 2010, the U.S. voluntary market was estimated at 35 terawatt-hours (TWh) compared to 300 TWh in the European market, though key differences exist. On a customer basis, Australia has historically had the largest number of customers, pricing for voluntary certificates remains low, at less than $1 megawatt-hour, though prices depend on technology.

Heeter, J.

2012-06-01T23:59:59.000Z

275

The Strategy of Professional Forecasting  

E-Print Network (OSTI)

This paper develops and compares two theories of strategic behavior of professional forecasters. The first theory posits that forecasters compete in a forecasting contest with pre-specified rules. In equilibrium of a winner-take-all contest, forecasts are excessively differentiated. According to the alternative reputational cheap talk theory, forecasters aim at convincing the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts and the realized state. If the market expects forecaster honesty, forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded.

Marco Ottaviani; Peter Norman Sřrensen

2003-01-01T23:59:59.000Z

276

Short term wind power forecasting using time series neural networks  

Science Conference Proceedings (OSTI)

Forecasting wind power energy is very important issue in a liberalized market and the prediction tools can make wind energy be competitive in these kinds of markets. This paper will study an application of time-series and neural network for predicting ... Keywords: neural networks, time series, wind power forecasting

Mohammadsaleh Zakerinia; Seyed Farid Ghaderi

2011-04-01T23:59:59.000Z

277

Energy efficiency, market failures, and government policy  

SciTech Connect

This paper presents a framework for evaluating engineering-economic evidence on the diffusion of energy efficiency improvements. Four examples are evaluated within this framework. The analysis provides evidence of market failures related to energy efficiency. Specific market failures that may impede the adoption of cost-effective energy efficiency are discussed. Two programs that have had a major impact in overcoming these market failures, utility DSM programs and appliance standards, are described.

Levine, M.D.; Koomey, J.G.; McMahon, J.E.; Sanstad, A.H. [Lawrence Berkeley Lab., CA (United States). Energy and Environment Div.; Hirst, E. [Oak Ridge National Lab., TN (United States). Energy Div.

1994-03-01T23:59:59.000Z

278

U.S. Regional Energy Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

LBNL-57955 U.S. Regional Energy Demand Forecasts Using NEMS and GIS Jesse A. Cohen, Jennifer L Efficiency and Renewable Energy, Office of Planning, Budget, and Analysis of the U.S. Department of Energy-57955 U.S. Regional Energy Demand Forecasts Using NEMS and GIS Prepared for the Office of Planning

279

Increasing Global Renewable Energy Market Share  

E-Print Network (OSTI)

to experience even greater energy supply uncertainties and price increases from fossil fuels. Recent trendsIncreasing Global Renewable Energy Market Share: Recent Trends and Perspectives Final Report a time of growing volatility and uncertainty in world energy markets. Oil price increases, which hit oil

Damm, Werner

280

Annual Energy Outlook 2002 with Projections to 2020 - Table of...  

Gasoline and Diesel Fuel Update (EIA)

Issues in Focus Market Trends Energy Demand Electricity Oil and Natural Gas Coal Emissions Forecast Comparisons Major Assumptions for the Forecasts Summary of the AEO2002...

Note: This page contains sample records for the topic "forecasted energy market" 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

Energy Matters: Clean Energy Technology Markets | Department of Energy  

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

Matters: Clean Energy Technology Markets Matters: Clean Energy Technology Markets Energy Matters: Clean Energy Technology Markets October 21, 2011 - 12:48pm Addthis Senior Advisor Richard Kauffman's October 20, 2011 live chat on energy.gov on innovation and deployment, and on how we can ensure U.S. leadership in the global renewable energy race.
 Liisa O'Neill Liisa O'Neill Former New Media Specialist, Office of Public Affairs On Thursday, October 20th, Richard Kauffman, Senior Advisor to the Secretary of Energy, joined us on Energy.gov for an Energy Matters video livechat on the financial and deployment obstacles facing renewable energy technologies.
 
Kauffman spoke about what drew him to the Department from the private sector, and answered your questions -- via email, Twitter and Facebook --

282

Energy Information Administration / Petroleum Marketing Annual...  

Annual Energy Outlook 2012 (EIA)

55 Energy Information Administration Petroleum Marketing Annual 1997 Prices of Petroleum Products Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State...

283

Real options valuation in energy markets .  

E-Print Network (OSTI)

??Real options have been widely applied to analyze investment planning and asset valuation under uncertainty in many industries, especially energy markets. Because of their close… (more)

Zhou, Jieyun

2010-01-01T23:59:59.000Z

284

Enertech Marketing Services | Open Energy Information  

Open Energy Info (EERE)

Enertech Marketing Services Enertech Marketing Services Jump to: navigation, search Name Enertech Marketing Services Place Bangalore, Karnataka, India Zip 560041 Sector Services, Solar Product Enertech Marketing Services was established in the year 1997 with the purpose of providing products, services and solutions in the fields of energy conservation and alternative sources of energy, especially solar. References Enertech Marketing Services[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Enertech Marketing Services is a company located in Bangalore, Karnataka, India . References ↑ "Enertech Marketing Services" Retrieved from "http://en.openei.org/w/index.php?title=Enertech_Marketing_Services&oldid=344933"

285

Renewable Energy Market Update Webinar | Department of Energy  

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

Renewable Energy Market Update Webinar Renewable Energy Market Update Webinar January 29, 2014 11:00AM MST Attendees will learn about the latest developments of the five types of...

286

A new feature selection algorithm and composite neural network for electricity price forecasting  

Science Conference Proceedings (OSTI)

In a competitive electricity market, the forecasting of energy prices is an important activity for all the market participants either for developing bidding strategies or for making investment decisions. In this paper, a new forecast strategy is proposed ... Keywords: Composite neural network, Price forecast, Two stage feature selection technique

Farshid Keynia

2012-12-01T23:59:59.000Z

287

American Energy Markets ¤ Forthcoming in Energy Economics  

E-Print Network (OSTI)

Using recent advances in the Żeld of applied econometrics, we explore the strength of shared trends and shared cycles between North American natural gas and crude oil markets. In doing so, we use daily data from January 1991 to April 2001 on spot U.S. Henry Hub natural gas and WTI crude oil prices. The results show that has been `de-coupling ' of the prices of these two sources of energy as a result of oil and gas deregulation in the United States. We also investigate the inter-connectedness of North American natural gas markets and Żnd that North American natural gas prices are largely deŻned by the U.S. Henry Hub price trends.

Apostolos Serletis; Ricardo Rangel-ruiz; Apostolos Serletis Y; Ricardo Rangel-ruiz

2002-01-01T23:59:59.000Z

288

General Renewable Energy-Market Development Studies | Open Energy  

Open Energy Info (EERE)

General Renewable Energy-Market Development Studies General Renewable Energy-Market Development Studies Jump to: navigation, search Tool Summary Name: General Renewable Energy-Market Development Studies Agency/Company /Organization: World Bank Sector: Energy Topics: Finance, Market analysis, Policies/deployment programs, Co-benefits assessment Website: web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTENERGY2/EXTRENENERGYTK/0,, Country: China, Mexico Eastern Asia, Central America References: General Renewable Energy-Market Development Studies[1] Resources Energy-policy Framework Conditions for Electricity Markets and Renewable Energies: 21 Country Analyses, TERNA Wind Energy Programme, GTZ Global Renewable Energy Markets and Policies, Eric Martinot, University of Maryland, School of Public Affairs The Potentials of Renewable Energy, Thematic Background Paper,

289

Energy Imbalance Markets (Fact Sheet)  

DOE Green Energy (OSTI)

The anticipated increase in variable renewable generation, such as wind and solar power, over the next several years has raised concerns about how system operators will maintain balance between electricity production and demand in the Western Interconnection, especially in its smaller balancing authority areas (BAAs). Given renewable portfolio standards in the West, it is possible that more than 50 gigawatts of wind capacity will be installed by 2020. Significant quantities of solar generation are likely to be added as well. Meanwhile, uncertainties about future load growth and challenges siting new transmission and generation resources may add additional stresses on the Western Interconnection of the future. One proposed method of addressing these challenges is an energy imbalance market (EIM). An EIM is a means of supplying and dispatching electricity to balance fluctuations in generation and load. It aggregates the variability of generation and load over multiple balancing areas (BAs).

Not Available

2012-09-01T23:59:59.000Z

290

Texas Wind Energy Forecasting System Development and Testing, Phase 1: Initial Testing  

Science Conference Proceedings (OSTI)

This report describes initial results from the Texas Wind Energy Forecasting System Development and Testing Project at a 75-MW wind project in west Texas.

2003-12-31T23:59:59.000Z

291

Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts  

E-Print Network (OSTI)

bid is computed by exploiting the forecast energy price for the day ahead market, the historical windOptimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts Antonio statistics at the plant site and the day-ahead wind speed forecasts provided by a meteorological service. We

Giannitrapani, Antonello

292

Annual Energy Outlook with Projections to 2025 - Market Trends- Carbon  

Gasoline and Diesel Fuel Update (EIA)

Carbon Dioxide Emissions Carbon Dioxide Emissions Annual Energy Outlook 2005 Market Trends - Carbon Dioxide Emissions Higher Energy Consumption Forecast Increases Carbon Dioxide Emissions Figure 110. Carbon dioxide emissions by sector and fuel, 2003 and 2025 (million metric tons). Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure data Carbon dioxide emissions from energy use are projected to increase on average by 1.5 percent per year from 2003 to 2025, to 8,062 million metric tons (Figure 110). Emissions per capita are projected to grow by 0.7 percent per year. New carbon dioxide mitigation programs, more rapid improvements in technology, or more rapid adoption of voluntary programs could result in lower emissions levels than projected here.

293

Annual Energy Outlook with Projections to 2025-Market Trends - Carbon  

Gasoline and Diesel Fuel Update (EIA)

Carbon Dioxide Emissions Carbon Dioxide Emissions Annual Energy Outlook 2004 with Projections to 2025 Market Trends - Carbon Dioxide Emissions Index (click to jump links) Carbon Dioxide Emissions Emissions from Electricity Generation Carbon Dioxide Emissions Higher Energy Consumption Forecast Increases Carbon Dioxide Emissions Figure 115. Carbon dioxide emissions by sector and fuel, 1990-2025 (million metric tons). Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure data Carbon dioxide emissions from energy use are projected to increase on average by 1.5 percent per year from 2002 to 2025, to 8,142 million metric tons (Figure 115). Emissions per capita are projected to grow by 0.7 percent per year from 2002 to 2025. Carbon dioxide emissions in the residential sector, including emissions

294

Market impacts: Improvements in the industrial sector | ENERGY...  

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

energy performance Communicate energy efficiency Industrial energy management information center Market impacts: Improvements in the industrial sector An effective energy...

295

Power Contro Energy Management and Market Systems  

SciTech Connect

More efficient use of the nation's electrical energy infrastructure will result in minimizing the cost of energy to the end user. Using real time electrical market information coupled with defined rules, market opportunities can be identified that provide economic benefit for both users and marketers of electricity. This report describes the design of one such system and the features a fully functional system would provide. This report documents several investigated methods of controlling load diversity or shifting.

Tom Addison; Andrew Stanbury

2005-12-15T23:59:59.000Z

296

Context-aware parameter estimation for forecast models in the energy domain  

Science Conference Proceedings (OSTI)

Continuous balancing of energy demand and supply is a fundamental prerequisite for the stability and efficiency of energy grids. This balancing task requires accurate forecasts of future electricity consumption and production at any point in time. For ... Keywords: energy, forecasting, maintenance, parameter estimation

Lars Dannecker; Robert Schulze; Matthias Böhm; Wolfgang Lehner; Gregor Hackenbroich

2011-07-01T23:59:59.000Z

297

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching  

E-Print Network (OSTI)

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at a wind energy site and fits a conditional predictive model for each regime. Geographically dispersed was applied to 2-hour-ahead forecasts of hourly average wind speed near the Stateline wind energy center

Genton, Marc G.

298

Implementation of a Corporate Energy Accounting and Forecasting Model  

E-Print Network (OSTI)

The development and implementation of a Frito-Lay computer based energy consumption reporting and modeling program is discussed. The system has been designed to relate actual plant energy consumption to a standard consumption which incorporates the effects of weather, product mix, specific equipment types, and other plant factors. The model also provides energy consumption forecasts based on projected production, equipment improvements, and fuels mix. Development of the model began in August 1979 and was preceded by two years of complete auditing of all areas in two manufacturing plants plus specific processing lines in other plants to determine typical energy usage. Extensive analyses of the data resulted in the formulation of standards for the various pieces of equipment which are used as energy performance 'yardsticks'. Monthly reports permit equitable comparisons of plant energy consumption and isolation of those plants with the lowest efficiencies. The financial impact of increasing energy consumption, of the projected energy use for new plants or plant expansions, and of the effect of process changes on overall energy consumption can be also evaluated.

Kympton, H. W.; Bowman, B. M.

1981-01-01T23:59:59.000Z

299

Green Power Marketing | Open Energy Information  

Open Energy Info (EERE)

source source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Page Edit History Facebook icon Twitter icon » Green Power Marketing Jump to: navigation, search Gearbox installation at Xcel Energy's Ponnequin Wind Farm in Colorado. Photo from Jeroen van Dam, NREL 19257 Green power marketing provides market-based choices for electricity consumers to purchase power from environmentally preferred sources. The term "green power" defines power generated from renewable energy sources, such as wind power. Green power marketing has the potential to expand domestic markets for renewable energy technologies by fostering greater availability of renewable electric service options in retail markets.

300

Power marketing and renewable energy  

SciTech Connect

Power marketing refers to wholesale and retail transactions of electric power made by companies other than public power entities and the regulated utilities that own the generation and distribution lines. The growth in power marketing has been a major development in the electric power industry during the last few years, and power marketers are expected to realize even more market opportunities as electric industry deregulation proceeds from wholesale competition to retail competition. This Topical Issues Brief examines the nature of the power marketing business and its relationship with renewable power. The information presented is based on interviews conducted with nine power marketing companies, which accounted for almost 54% of total power sales by power marketers in 1995. These interviews provided information on various viewpoints of power marketers, their experience with renewables, and their respective outlooks for including renewables in their resource portfolios. Some basic differences exist between wholesale and retail competition that should be recognized when discussing power marketing and renewable power. At the wholesale level, the majority of power marketers stress the commodity nature of electricity. The primary criteria for developing resource portfolios are the same as those of their wholesale customers: the cost and reliability of power supplies. At the retail level, electricity may be viewed as a product that includes value-added characteristics or services determined by customer preferences.

Fang, J.M.

1997-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasted energy market" 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

Massachusetts - Seds - U.S. Energy Information Administration...  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

302

Oregon - Seds - U.S. Energy Information Administration (EIA)  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

303

Rhode Island - Seds - U.S. Energy Information Administration...  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

304

Maryland - Seds - U.S. Energy Information Administration (EIA...  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

305

New Hampshire - Seds - U.S. Energy Information Administration...  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

306

North Carolina - Seds - U.S. Energy Information Administration...  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

307

Vermont - Seds - U.S. Energy Information Administration (EIA...  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

308

Arkansas - Seds - U.S. Energy Information Administration (EIA...  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

309

Maine - Seds - U.S. Energy Information Administration (EIA)  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

310

Indiana - Seds - U.S. Energy Information Administration (EIA...  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

311

Texas - Seds - U.S. Energy Information Administration (EIA)  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

312

Arizona - Seds - U.S. Energy Information Administration (EIA...  

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

forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance Financial market analysis and financial data for major energy companies....

313

Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will tak  

E-Print Network (OSTI)

is familiar with solar energy issues, we hope that you will take a few moments to answer this short survey on your needs for information on solar energy resources and forecasting. This survey is conducted with the California Solar Energy Collaborative (CSEC) and the California Solar Initiative (CSI) our objective

Islam, M. Saif

314

Building America Market Partnerships | Department of Energy  

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

Market Partnerships Market Partnerships Building America Market Partnerships This photo shows two men silhouetted against a sky shaking hands, with the frame of a building under construction in the background. The U.S. Department of Energy (DOE) offers partnership opportunities, educational curricula, meetings, and webinars that help industry professionals bring research results to the market. DOE Challenge Home Through the DOE Challenge Home, the Building Technologies Office offers recognition to leading edge builders meeting extraordinary levels of excellence. Builders taking the challenge gain competitive advantage in the marketplace by providing their customers with unparalleled energy savings, quality, comfort, health, durability, and much more. Learn more about the DOE Challenge Home.

315

Beyond "Partly Sunny": A Better Solar Forecast | Department of Energy  

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

Beyond "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast December 7, 2012 - 10:00am Addthis The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. Minh Le Minh Le Program Manager, Solar Program What Do These Projects Do? The Energy Department is investing $8 million in two cutting-edge projects to increase the accuracy of solar forecasting at sub-hourly,

316

Energy Market and Economic Impacts of S.280, the Climate Stewardship and Innovation Act of 2007  

Gasoline and Diesel Fuel Update (EIA)

4 4 Energy Market and Economic Impacts of S. 280, the Climate Stewardship and Innovation Act of 2007 July 2007 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. Service Reports are prepared by the Energy Information Administration upon special request and are based on assumptions specified by

317

Light-Duty Diesel Vehicles: Market Issues and Potential Energy and Emissions Impacts  

Gasoline and Diesel Fuel Update (EIA)

2 2 Light-Duty Diesel Vehicles: Market Issues and Potential Energy and Emissions Impacts January 2009 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. Unless referenced otherwise, the information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. Service Reports are prepared by the Energy Information Administration upon special request and are based on assumptions specified by the requester.

318

Texas Wind Energy Forecasting System Development and Testing: Phase 2: 12-Month Testing  

Science Conference Proceedings (OSTI)

Wind energy forecasting systems are expected to support system operation in cases where wind generation contributes more than a few percent of total generating capacity. This report presents final results from the Texas Wind Energy Forecasting System Development and Testing Project at a 75-MW wind project in west Texas.

2004-09-30T23:59:59.000Z

319

Annual Energy Outlook 2000 - Market Trend - Carbon Emissions and Energy Use  

Gasoline and Diesel Fuel Update (EIA)

Homepage Homepage Economic Growth World Oil Prices Total Energy Consumption Residential and Commercial Sectors Industrial Sector Transportation Sector Electricity Natural Gas Petroleum Coal Three other organizations—Standard & Poor’s DRI (DRI), the WEFA Group (WEFA), and the Gas Research Institute (GRI)—also produce comprehensive energy projections with a time horizon similar to that of AEO2000. The most recent projections from those organizations (DRI, Spring/Summer 1999; WEFA, 1999; GRI, August 1998), as well as other forecasts that concentrate on petroleum, natural gas, and international oil markets, are compared here with the AEO2000 projections. Economic Growth Differences in long-run economic forecasts can be traced primarily to different views of the major supply-side determinants of growth in gross

320

Performance Contracting and Energy Efficiency in the State Government Market  

E-Print Network (OSTI)

State Government Market information about energy efficiencyEnergy Efficiency in the State Government Market assistance, and informationEnergy Performance Contracting Activity Using available baseline information on the state government market

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasted energy market" 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

Clean Markets | Open Energy Information  

Open Energy Info (EERE)

Markets Markets Jump to: navigation, search Name Clean Markets Place Philadelphia, Pennsylvania Zip 19118 Sector Services Product Philadelphia-based provider of market development services to companies entering or operating in environmentally sustainable markets. Coordinates 39.95227°, -75.162369° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.95227,"lon":-75.162369,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

322

Understanding the Industrial Market Sector: Responding to Changing Energy Markets  

Science Conference Proceedings (OSTI)

Industrial customers, particularly larger industrial customers, have always been an important customer population for energy providers. Because of their sometimes massive size, industrials have often had dedicated account representatives, and even customized rate plans and service delivery structures. As competition in energy markets develops, this population has often been the first customer population to encounter both the benefits and the problems associated with deregulation. It is important to recog...

1999-12-06T23:59:59.000Z

323

Understanding the Industrial Market Sector: Responding to Changing Energy Markets  

Science Conference Proceedings (OSTI)

Industrial customers, particularly larger industrial customers, have always been an important customer population for energy providers. Because of their sometimes massive size, industrials have often had dedicated account representatives, and even customized rate plans and service delivery structures. As competition in energy markets develops, this population has often been the first customer population to encounter both the benefits and the problems associated with deregulation. It is important to recog...

1999-11-30T23:59:59.000Z

324

Effect of Increased Natural Gas Exports on Domestic Energy Markets  

U.S. Energy Information Administration (EIA)

analytical agency within the U.S. Department of Energy. By law, EIA’s data, analyses, and forecasts are ... policy changes, and technological breakthroughs.

325

NREL: Technology Deployment - Wind Energy Deployment and Market...  

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

Wind Energy Deployment and Market Transformation NREL experts have a broad range of wind energy deployment and market transformation capabilities spanning more than 20 years of...

326

Annual Energy Outlook Forecast Evaluation - Tables 2-18  

Gasoline and Diesel Fuel Update (EIA)

Total Energy Consumption: AEO Forecasts, Actual Values, and Total Energy Consumption: AEO Forecasts, Actual Values, and Absolute and Percent Errors, 1985-1999 Publication 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Average Absolute Error (Quadrillion Btu) AEO82 79.1 79.6 79.9 80.8 82.0 83.3 1.8 AEO83 78.0 79.5 81.0 82.4 83.8 84.6 89.5 1.2 AEO84 78.5 79.4 81.2 83.1 85.0 86.4 93.5 1.5 AEO85 77.6 78.5 79.8 81.2 82.6 83.3 84.2 85.2 85.9 86.7 87.7 1.3 AEO86 77.0 78.8 79.8 80.6 81.5 82.9 84.0 84.8 85.7 86.5 87.9 88.4 87.8 88.7 3.6 AEO87 78.9 80.0 81.9 82.8 83.9 85.3 86.4 87.5 88.4 1.5 AEO89 82.2 83.7 84.5 85.4 86.4 87.3 88.2 89.2 90.8 91.4 90.9 91.7 1.8

327

Energy Forecasting in Volatile Times - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking ...

328

Historic Virginia Market Powered by Solar Energy | Department of Energy  

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

Historic Virginia Market Powered by Solar Energy Historic Virginia Market Powered by Solar Energy Historic Virginia Market Powered by Solar Energy November 3, 2010 - 11:00am Addthis Solar panels at the Community Market Building in Danville, Va., have generated 36.4 MWh of energy since March. | Photo Courtesy of Danville Solar panels at the Community Market Building in Danville, Va., have generated 36.4 MWh of energy since March. | Photo Courtesy of Danville Joshua DeLung The historic building where area farmers sell produce straight from the field to consumers is now home to Danville, Virg.'s first renewable energy project - a 154-panel solar energy system. The city, steeped in history, has taken this significant leap toward a new energy future by using a $202,000 Energy Efficiency and Conservation Block

329

Marketing Materials and Posters for Energy Entrepreneurs | Open Energy  

Open Energy Info (EERE)

Marketing Materials and Posters for Energy Entrepreneurs Marketing Materials and Posters for Energy Entrepreneurs Jump to: navigation, search Tool Summary Name: Marketing Materials and Posters for Energy Entrepreneurs Agency/Company /Organization: GVEP International Sector: Energy Focus Area: Solar Phase: Create a Vision Topics: - Energy Access, Finance Resource Type: Training materials User Interface: Website Website: www.gvepinternational.org/en/business/training-material Cost: Free UN Region: Eastern Africa Language: English Marketing materials (posters and flyers) to enable energy entrepreneurs in East Africa's rural and peri urban regions to market their products to attract new customers. GVEP International with funding support from the United States Agency for International Development (USAID) developed a set of marketing materials

330

Promoting Renewable Energy in a Market Environment  

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

Promoting Renewable Energy in a Market Environment: A Community-Based Approach for Aggregating Green Demand Rudd Mayer Eric Blank Randy Udall John Nielsen Land and Water Fund of...

331

Essays in energy and environmental markets  

E-Print Network (OSTI)

In this thesis, I explore issues related to energy and environmental markets. In the first chapter, I examine the benefits of complementary bidding mechanisms used in electricity auctions. I develop a model of complex ...

Reguant-Rido, Mar

2011-01-01T23:59:59.000Z

332

XLS - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

Forecast Volatility Expiry Lower Upper Source: Short-Term Energy Outlook, January 2014. Note: Confidence interval derived from options market ...

333

Data driven medium term electricity price forecasting in ontario electricity market and Nord Pool.  

E-Print Network (OSTI)

??Having accurate predictions on market price variations in the future is of great importance to participants in today’s electricity market. Many studies have been done… (more)

Torbaghan, Shahab Shariat

2010-01-01T23:59:59.000Z

334

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

and imports U.S. electricity and gas markets includingrepresentation of electricity and natural gas markets,initially to conduct electricity restructuring analysis in

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

2005-01-01T23:59:59.000Z

335

Economic Impacts of Advanced Weather Forecasting on Energy ...  

E-Print Network (OSTI)

Mar 5, 2010 ... Abstract: We analyze the impacts of adopting advanced weather forecasting systems at different levels of the decision-making hierarchy of the ...

336

NextEra Energy Power Marketing LLC | Open Energy Information  

Open Energy Info (EERE)

NextEra Energy Power Marketing LLC NextEra Energy Power Marketing LLC (Redirected from FPL Energy Power Marketing Inc) Jump to: navigation, search Name NextEra Energy Power Marketing LLC Place Florida Utility Id 49891 Utility Location Yes Ownership R Activity Transmission Yes Activity Buying Transmission Yes Activity Buying Distribution Yes Activity Wholesale Marketing Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png No rate schedules available. Average Rates No Rates Available References ↑ "EIA Form EIA-861 Final Data File for 2010 - File1_a" Retrieved from "http://en.openei.org/w/index.php?title=NextEra_Energy_Power_Marketing_LLC&oldid=412302"

337

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

index.html. Appendix A.1 Natural Gas Price Data for FuturesError STEO Error A.1 Natural Gas Price Data for Futuresof forecasts for natural gas prices as reported by the

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

2005-01-01T23:59:59.000Z

338

EA-121-B Dynegy Power Marketing, Inc | Department of Energy  

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

to Mexico. EA-121-B Dynegy Power Marketing, Inc More Documents & Publications EA-166-A Duke Energy Trading and Marketing, L.L.C EA-348 FPL Energy Power Marketing, Inc. EA-337...

339

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST  

E-Print Network (OSTI)

Policy Report, over the entire forecast period, primarily because both weather-adjusted peak and commercial sectors. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, California Solar Initiative. #12;ii #12

340

Energy Analysis Department A Review of Market MonitoringA Review of Market Monitoring  

E-Print Network (OSTI)

;Energy Analysis Department Approach (cont)Approach (cont) · Synthesize information on market monitoringEnergy Analysis Department A Review of Market MonitoringA Review of Market Monitoring Activities of authority - Reporting responsibilities - Impact of market monitoring: Case Studies #12;Energy Analysis

Note: This page contains sample records for the topic "forecasted energy market" 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

International Energy Outlook 2006 - World Coal Markets  

Gasoline and Diesel Fuel Update (EIA)

Coal Markets Coal Markets International Energy Outlook 2006 Chapter 5: World Coal Markets In the IEO2006 reference case, world coal consumption nearly doubles from 2003 to 2030, with the non-OECD countries accounting for 81 percent of the increase. CoalÂ’s share of total world energy consumption increases from 24 percent in 2003 to 27 percent in 2030. Figure 48. World Coal Consumption by Region, 1980-2030 (Billion Short Tons). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 49. Coal Share of World energy Consumption by Sector 2003, 2015, and 2030 (Percent). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Table 10. World Recoverable Coal Reserves (Billion Short Tons) Printer friendly version

342

Energy Forecast, ForskEL (Smart Grid Project) | Open Energy Information  

Open Energy Info (EERE)

Forecast, ForskEL (Smart Grid Project) Forecast, ForskEL (Smart Grid Project) Jump to: navigation, search Project Name Energy Forecast, ForskEL Country Denmark Coordinates 56.26392°, 9.501785° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":56.26392,"lon":9.501785,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

343

Energy and Oil Market Outlook  

Reports and Publications (EIA)

Presented by:Richard G. Newell, Administrator, U.S. Energy Information Administration, to: Senate Energy and Natural Resources CommitteeUnited States Senate; Washington, D.C.

Information Center

2011-02-03T23:59:59.000Z

344

Battery energy storage market feasibility study  

DOE Green Energy (OSTI)

Under the sponsorship of the Department of Energy`s Office of Utility Technologies, the Energy Storage Systems Analysis and Development Department at Sandia National Laboratories (SNL) contracted Frost and Sullivan to conduct a market feasibility study of energy storage systems. The study was designed specifically to quantify the energy storage market for utility applications. This study was based on the SNL Opportunities Analysis performed earlier. Many of the groups surveyed, which included electricity providers, battery energy storage vendors, regulators, consultants, and technology advocates, viewed energy storage as an important enabling technology to enable increased use of renewable energy and as a means to solve power quality and asset utilization issues. There are two versions of the document available, an expanded version (approximately 200 pages, SAND97-1275/2) and a short version (approximately 25 pages, SAND97-1275/1).

Kraft, S. [Frost and Sullivan, Mountain View, CA (United States); Akhil, A. [Sandia National Labs., Albuquerque, NM (United States). Energy Storage Systems Analysis and Development Dept.

1997-07-01T23:59:59.000Z

345

High Horizontal and Vertical Resolution Limited-Area Model: Near-Surface and Wind Energy Forecast Applications  

Science Conference Proceedings (OSTI)

As harvesting of wind energy grows, so does the need for improved forecasts from the surface to the top of wind turbines. To improve mesoscale forecasts of wind, temperature, and dewpoint temperature in this layer, two different approaches are ...

Natacha B. Bernier; Stéphane Bélair

2012-06-01T23:59:59.000Z

346

MARKet ALlocation (MARKAL) | Open Energy Information  

Open Energy Info (EERE)

MARKet ALlocation (MARKAL) MARKet ALlocation (MARKAL) Jump to: navigation, search Tool Summary Name: MARKet ALlocation (MARKAL) Agency/Company /Organization: Brookhaven National Laboratory Sector: Energy Topics: Baseline projection, Pathways analysis, Policies/deployment programs Resource Type: Software/modeling tools User Interface: Desktop Application Complexity/Ease of Use: Moderate Website: www.iea-etsap.org/web/Markal.asp Cost: Paid OpenEI Keyword(s): EERE tool References: MARKAL website[1] Related Tools Ventana's Energy, Environment, Economy-Society (E3S) Model Ex Ante Appraisal Carbon-Balance Tool (EX-ACT) General Equilibrium Model for Economy - Energy - Environment (GEM-E3) ... further results Find Another Tool FIND DEVELOPMENT IMPACTS ASSESSMENT TOOLS An integrated energy systems modeling platform that can be used to analyze

347

Energy Information Administration/Petroleum Marketing Annual  

Gasoline and Diesel Fuel Update (EIA)

9 9 Articles Feature articles on energy-related subjects are frequently included in this publication. The following ar- ticles and special focus items have appeared in previous issues. Propane Market Assessment for Winter 1997-1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . December 1997 A Contrast Between Distillate Fuel Oil Markets in Autumn 1996 and 1997 . . . . . . . . . . . . . . . . . . . . December 1997 A Comparison of Selected EIA-782 Data With Other Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . November 1997 Distillate Fuel Oil Assessment for Winter 1996-1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . December 1996 Propane Market Assessment for Winter 1996-1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . December 1996 Recent Distillate Fuel Oil Inventory Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . June 1996 Recent Trends in Motor Gasoline Stock Levels .

348

Restoring Equilibrium to Natural Gas Markets: Can Renewable Energy Help?  

E-Print Network (OSTI)

through Increased Deployment of Renewable Energy and EnergyNatural Gas Markets: Can Renewable Energy Help? Ryan Wiserenergy supplies. Proponents of renewable energy technologies

Wiser, Ryan; Bolinger, Mark

2005-01-01T23:59:59.000Z

349

Restoring Equilibrium to Natural Gas Markets: Can Renewable Energy Help?  

E-Print Network (OSTI)

Deployment of Renewable Energy and Energy Efficiency,” canGas Markets: Can Renewable Energy Help? Ryan Wiser and MarkProponents of renewable energy technologies identify these

Wiser, Ryan; Bolinger, Mark

2005-01-01T23:59:59.000Z

350

Market Sheet - Energy Innovation Portal  

for the U.S. Department of Energy’s National ... of 10 cm and a total package height of 5 cm will likely be spec’ed at 0.10 C/W and a power consumption ...

351

Assessing the Impact of Different Satellite Retrieval Methods on Forecast Available Potential Energy  

Science Conference Proceedings (OSTI)

The isentropic form for available potential energy (APE) is used to analyze the impact of the inclusion of satellite temperature retrieval data on forecasts made with the NASA Goddard Laboratory for Atmospheres (GLA) fourth order model. Two ...

Linda M. Whittaker; Lyle H. Horn

1990-01-01T23:59:59.000Z

352

DND: a model for forecasting electrical energy usage by water-resource subregion  

SciTech Connect

A forecast methodology was derived from principles of econometrics using exogenous variables, i.e., cost of electricity, consumer income, and price elasticity as indicators of growth for each consuming sector: residential, commercial, and industrial. The model was calibrated using forecast data submitted to the Department of Energy (DOE) by the nine Regional Electric Reliability Councils. Estimates on electrical energy usage by specific water-resource subregion were obtained by normalizing forecasted total electrical energy usage by state into per capita usage. The usage factor and data on forecasted population were applied for each water resource subregion. The results derived using the model are self-consistent and in good agreement with DOE Energy Information Administration projections. The differences that exist are largely the result of assumptions regarding specific aggregations and assignment of regional-system reliability and load factors. 8 references, 2 figures, 13 tables.

Sonnichsen, J.C. Jr.

1980-02-01T23:59:59.000Z

353

Petroleum Marketing Annual 1995 - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Internet E-Mail: dgatton@eia.doe.gov Energy Information Administration / Petroleum Marketing Annual 1995 ii. Preface The Petroleum Marketing Annual (PMA) provides in-

354

Energy and Financial Markets Overview: Crude Oil Price Formation  

U.S. Energy Information Administration (EIA)

• E&P costs • E&P investments • E&P innovations Physical balancing • Inventories Markets & market behavior • Energy prices ? spot ? futures ? options

355

Energy & Financial Markets: What Drives Crude Oil Prices ...  

U.S. Energy Information Administration (EIA)

Overview. As part of its Energy and Financial Markets Initiative, EIA is assessing the various factors that may influence oil prices — physical market factors as ...

356

New Zealand Energy Data: Electricity Balance and Market Data...  

Open Energy Info (EERE)

electricity. Included here are three datasets: electricity energy balance (2005 - 2009), electricity market snapshot (2009), and market competition statistics (2004 - 2009).
...

357

EIA-Assumptions to the Annual Energy Outlook - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2007 Petroleum Market Module Figure 9. Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, and bioesters), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. The PMM contains a linear programming (LP) representation of U.S. refining

358

Survey and forecast of marketplace supply and demand for energy- efficient lighting products  

SciTech Connect

The rapid growth in demand for energy-efficient lighting products has led to supply shortages for certain products. To understand the near-term (1- to 5-year) market for energy-efficient lighting products, a selected set of utilities and lighting product manufacturers were surveyed in early 1991. Two major U. S. government programs, EPA's Green Lights and DOE's Federal Relighting Initiative, were also examined to assess their effect on product demand. Lighting product manufacturers predicted significant growth through 1995. Lamp manufacturers indicated that compact fluorescent lamp shipments tripled between 1988 and 1991, and predicted that shipments would again triple, rising from 25 million units in 1991 to 72 million units in 1995. Ballast manufacturers predicted that demand for power-factorcorrected ballasts (both magnetic and electronic) would grow from 59.4 million units in 1991 to 71.1 million units in 1995. Electronic ballasts were predicted to grow from 11% of ballast demand in 1991 to 40% in 1995. Manufacturers projected that electronic ballast supply shortages would continue until late 1992. Lamp and ballast producers indicated that they had difficulty in determining what additional supply requirements might result due to demand created by utility programs. Using forecasts from 27 surveyed utilities and assumptions regarding the growth of U. S. utility lighting DSM programs, low, median, and high forecasts were developed for utility expenditures for lighting incentives through 1994. The projected median figure for 1992 was $316 million, while for 1994, the projected median figure was $547 million. The allocation of incentive dollars to various products and the number of units needed to meet utility-stimulated demand were also projected. To provide a better connection between future supply and demand, a common database is needed that captures detailed DSM program information including incentive dollars and unit-volume mix by product type.

Gough, A. (Lighting Research Inst., New York, NY (United States)); Blevins, R. (Plexus Research, Inc., Donegal, PA (United States))

1992-12-01T23:59:59.000Z

359

Essays on U.S. energy markets  

E-Print Network (OSTI)

This dissertation examines three facets of U.S. energy use and policy. First, I examine the Gulf Coast petroleum refining industry to determine the structure of the industry. Using the duality between cost-minimization and production functions, I estimate the demand for labor to determine the underlying production function. The results indicate that refineries have become more capital intensive due to the relative price increase of labor. The industry has consolidated in response to higher labor costs and costs of environmental compliance. Next, I examine oil production in the United States. An empirical model based on the theoretical framework of Pindyck is used to estimate production. This model differs from previous research by using state level data rather than national level data. The results indicate that the production elasticity with respect to reserves and the price elasticity of supply are both inelastic in the long run. The implication of these findings is that policies designed to increase domestic production through subsidies, tax breaks, or royalty reductions will likely provide little additional oil. We simulate production under three scenarios. In the most extreme scenario, prices double between 2005 and 2030 while reserves increase by 50%. Under this scenario, oil production in 2030 is approximately the same as the 2005 level. The third essay estimates demand for fossil fuels in the U.S. and uses these estimates to forecast CO2 emissions. The results indicate that there is almost no substitution from one fossil fuel to another and that all three fossil fuels are inelastic in the long run. Additionally, all three fuels respond differently to changes in GDP. The result of the differing elasticities with respect to GDP is that the energy mix has changed over time. The implication for forecasting CO2 emissions is that models that cannot distinguish changes in the energy mix are not effective in forecasting CO2 emissions.

Brightwell, David Aaron

2008-08-01T23:59:59.000Z

360

Element Markets LLC | Open Energy Information  

Open Energy Info (EERE)

Markets LLC Markets LLC Jump to: navigation, search Name Element Markets LLC Place Houston, Texas Zip 77027 Sector Renewable Energy, Services Product Houston-based firm that develops renewable energy projects and provides commercial advisory services to enterprises seeking to manage its emissions or renewable energy assets. Coordinates 29.76045°, -95.369784° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":29.76045,"lon":-95.369784,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

Note: This page contains sample records for the topic "forecasted energy market" 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

MARKet ALlocation (MARKAL) | Open Energy Information  

Open Energy Info (EERE)

MARKet ALlocation (MARKAL) MARKet ALlocation (MARKAL) (Redirected from MARKAL) Jump to: navigation, search Tool Summary Name: MARKet ALlocation (MARKAL) Agency/Company /Organization: Brookhaven National Laboratory Sector: Energy Topics: Baseline projection, Pathways analysis, Policies/deployment programs Resource Type: Software/modeling tools User Interface: Desktop Application Complexity/Ease of Use: Moderate Website: www.iea-etsap.org/web/Markal.asp Cost: Paid OpenEI Keyword(s): EERE tool References: MARKAL website[1] Related Tools Ventana's Energy, Environment, Economy-Society (E3S) Model Ex Ante Appraisal Carbon-Balance Tool (EX-ACT) General Equilibrium Model for Economy - Energy - Environment (GEM-E3) ... further results Find Another Tool FIND DEVELOPMENT IMPACTS ASSESSMENT TOOLS

362

Capital Markets Climate Initiative | Open Energy Information  

Open Energy Info (EERE)

Markets Climate Initiative Markets Climate Initiative Jump to: navigation, search Name Capital Markets Climate Initiative Agency/Company /Organization World Economic Forum Partner UK Department of Energy and Climate Sector Climate Topics Finance, Low emission development planning, -LEDS Website http://www.decc.gov.uk/en/cont Country India, Kenya, South Africa, Mexico, Tanzania Southern Asia, Eastern Africa, Southern Africa, Central America, Eastern Africa References CMCI[1] World Economic Forum[2] The Capital Markets Climate Initiative (CMCI) is a public-private initiative designed to support the scale up of private finance flows for low carbon technologies, solutions and infrastructure in developing economies by: Developing a common understanding amongst policy makers of why and

363

EA-296-B Rainbow Energy Marketing Corporation | Department of...  

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

(OE): EA-296-B Rainbow Energy Marketing Corporation Application to Export Electric Energy OE Docket No. EA-296-B Rainbow Energy Marketing Corp EA-342-A Royal Bank of Canada...

364

Consensus forecast of U. S. energy supply and demand to the year 2000  

DOE Green Energy (OSTI)

Methods used in forecasting energy supply and demand are described, and recent forecasts are reviewed briefly. Forecasts to the year 2000 are displayed in tables and graphs and are used to prepare consensus forecasts for each form of fuel and energy supply. Fuel demand and energy use by consuming sector are tabulated for 1972 and 1975 for the various fuel forms. The distribution of energy consumption by use sector, as projected for the years 1985 and 2000 in the ERDA-48 planning report (Scenario V), is normalized to match the consensus energy supply forecasts. The results are tabulated listing future demand for each fuel and energy form by each major energy-use category. Recent estimates of U.S. energy resources are also reviewed briefly and are presented in tables for each fuel and energy form. The outlook for fossil fuel resources to the year 2040, as developed by the Institute for Energy Analysis at the Oak Ridge Associated Universities, is also presented.

Lane, J.A.

1976-02-01T23:59:59.000Z

365

Energy Market Profiles: Hospital Buildings, Equipment, and Energy Use  

Science Conference Proceedings (OSTI)

This report profiles the U.S. healthcare market on size and energy-related characteristics and provides energy benchmarking data that can be used to make meaningful comparisons between healthcare facilities. The intent of the report is to provide both utility and hospital managers with a better understanding of the key characteristics of the healthcare market and enhance their abilities to assess how well their facilities are performing relative to hospitals with similar energy equipment.

1999-12-22T23:59:59.000Z

366

EA-216 TransAlta Energy Marketing (U.S) Inc | Department of Energy  

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

TransAlta Energy Marketing (U.S) Inc EA-216 TransAlta Energy Marketing (U.S) Inc Order authorizing TransAlta Energy Marketing (U.S) Inc to export electric energy to Canada. EA-216...

367

Energy usage in super markets  

SciTech Connect

The supermarket industry used 450 billion Btu's of energy each day, enough to heat 2 million homes. But more important than the overall energy usage is what energy is costing the supermarket operator; in many cases energy costs exceed rent. This special research report is designed to help the supermarket management determine if their stores are excessive energy users and to provide valuable data for planning remodels and new stores. The report is presented in five sections. The first two sections, General Observations and Monthly Electrical Usage and Demand Power, can easily be used by all supermarket operators. The third and fourth sections contain more detailed statistics that will be valuable to industry people who want to analyze energy usage more thoroughly. The statistics in section 1-4 are reported for various geographic regions and store sizes. Section five is the sample distribution which provides an insight into what other stores are using for refrigeration, lighting, etc. The information in this report is average for a typical supermarket and should be used only as that when compared to a specific supermarket facility.

Gerke, E.

1976-01-01T23:59:59.000Z

368

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

information about natural gas supply and demand. As amarket Calibrating natural gas supply and demand conditionsnation-wide natural gas market, equalizing supply with

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

2005-01-01T23:59:59.000Z

369

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

E-Print Network (OSTI)

coal supply. The natural gas supply covers six categories:renewables, oil supply, natural gas supply, natural gasnation-wide natural gas market, equalizing supply with

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

2005-01-01T23:59:59.000Z

370

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

about natural gas supply and demand. As a result, someCalibrating natural gas supply and demand conditions withelectricity and natural gas markets, demand-side management

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

2005-01-01T23:59:59.000Z

371

EIA-Assumptions to the Annual Energy Outlook - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumptions to the Annual Energy Outlook 2007 Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2007, DOE/EIA-M060(2007) (Washington, DC, 2007). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

372

Modeling and Analysis Papers - Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Evaluation > Table 1 Evaluation > Table 1 Table 1. Comparison of Absolute Percent Errors for AEO Forecast Evaluation, 1996 to 2002 Average Absolute Percent Error Variable AEO82 to AEO97 AEO82 to AEO98 AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 Consumption Total Energy Consumption 1.6 1.7 1.7 1.8 1.9 1.9 Total Petroleum Consumption 2.8 2.9 2.8 2.9 3.0 2.9 Total Natural Gas Consumption 5.8 5.7 5.6 5.6 5.5 5.5 Total Coal Consumption 2.7 3.0 3.2 3.3 3.5 3.6 Total Electricity Sales 1.6 1.7 1.8 1.9 2.4 2.5 Production Crude Oil Production 4.2 4.3 4.5 4.5 4.5 4.5 Natural Gas Production 5.0 4.8 4.7 4.6 4.6 4.4 Coal Production 3.7 3.6 3.6 3.5 3.7 3.6 Imports and Exports Net Petroleum Imports 10.1 9.5 8.8 8.4 7.9 7.4 Net Natural Gas Imports 17.4 16.7 16.0 15.9 15.8 15.8 Net Coal Exports

373

PV Installation Labor Market Analysis and PV JEDI Tool Developments (Presentation), NREL (National Renewable Energy Laboratory)  

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

PV Installation Labor Market Analysis PV Installation Labor Market Analysis and PV JEDI Tool Developments Barry Friedman NREL Strategic Energy Analysis Center May 16, 2012 World Renewable Energy Forum Denver, Colorado NREL/PR-6A20-55130 NATIONAL RENEWABLE ENERGY LABORATORY Disclaimer 2 DISCLAIMER AGREEMENT These information ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy LLC ("Alliance") for the U.S. Department of Energy (the "DOE"). It is recognized that disclosure of these Data is provided under the following conditions and warnings: (1) these Data have been prepared for reference purposes only; (2) these Data consist of forecasts, estimates or assumptions made on a best-

374

On-line economic optimization of energy systems using weather forecast information.  

Science Conference Proceedings (OSTI)

We establish an on-line optimization framework to exploit weather forecast information in the operation of energy systems. We argue that anticipating the weather conditions can lead to more proactive and cost-effective operations. The framework is based on the solution of a stochastic dynamic real-time optimization (D-RTO) problem incorporating forecasts generated from a state-of-the-art weather prediction model. The necessary uncertainty information is extracted from the weather model using an ensemble approach. The accuracy of the forecast trends and uncertainty bounds are validated using real meteorological data. We present a numerical simulation study in a building system to demonstrate the developments.

Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.

2009-01-01T23:59:59.000Z

375

2008 Solar Technologies Market Report | Open Energy Information  

Open Energy Info (EERE)

Page Page Edit with form History Facebook icon Twitter icon » 2008 Solar Technologies Market Report Jump to: navigation, search Tool Summary Name: 2008 Solar Technologies Market Report Agency/Company /Organization: United States Department of Energy Sector: Energy Focus Area: Renewable Energy, Solar, - Concentrating Solar Power, - Solar PV Topics: Market analysis, Resource assessment Resource Type: Publications Website: www1.eere.energy.gov/solar/pdfs/46025.pdf Cost: Free 2008 Solar Technologies Market Report Screenshot References: 2008 Solar Technologies Market Report[1] Logo: 2008 Solar Technologies Market Report "The focus of this report is the U.S. solar electricity market, including photovoltaic (PV) and concentrating solar power (CSP) technologies. The

376

Federal Energy Management Program: Market Studies for Distributed...  

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

Energy Resources and Combined Heat and Power to someone by E-mail Share Federal Energy Management Program: Market Studies for Distributed Energy Resources and Combined...

377

Scaling Energy Efficiency in the Heart of the Residential Market...  

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

Scaling Energy Efficiency in the Heart of the Residential Market: Increasing Middle America's Access to Capital for Energy Improvements Title Scaling Energy Efficiency in the Heart...

378

The Strategic Impact of Changing Energy Markets on the Aluminum ...  

Science Conference Proceedings (OSTI)

Presentation Title, The Strategic Impact of Changing Energy Markets on the ... of a structural change in energy prices, both for primary energy and electricity.

379

Energy Market Profiles: Volume 3: 1995 Industrial Energy Use Baseline  

Science Conference Proceedings (OSTI)

Energy use and equipment profiles at the region, segment, and end-use levels provide key information required to lay the groundwork for major marketing decisions. These decisions include how desirable a market is for utility entry, how quickly to enter a market, and how to best narrow a research focus. This study provides utility managers and decisionmakers with industrial market profiles for 10 regions of the United States. This report is available only to funders of Program 101A or 101.001. Funders may...

1999-01-05T23:59:59.000Z

380

Volume 15, number 3 april 2010 markets products analysis research forecasts  

E-Print Network (OSTI)

demand is only slowly climbing back. While there are some exceptions, it appears that "constrained capaci around the world in almost all wood products. While WOOD MARKETS' supply and demand models have been Board Foot Club global statistics 6 Global Sawnwood, USa, Canada international Wood markets Group inc

Note: This page contains sample records for the topic "forecasted energy market" 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

3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information  

Open Energy Info (EERE)

TIER Environmental Forecast Group Inc 3TIER TIER Environmental Forecast Group Inc 3TIER Jump to: navigation, search Name 3TIER Environmental Forecast Group Inc (3TIER) Place Seattle, Washington Zip 98121 Sector Renewable Energy Product Seattle-based, renewable energy assessment and forecasting company. Coordinates 47.60356°, -122.329439° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":47.60356,"lon":-122.329439,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

382

U.S. Department of Energy Workshop Report: Solar Resources and Forecasting  

DOE Green Energy (OSTI)

This report summarizes the technical presentations, outlines the core research recommendations, and augments the information of the Solar Resources and Forecasting Workshop held June 20-22, 2011, in Golden, Colorado. The workshop brought together notable specialists in atmospheric science, solar resource assessment, solar energy conversion, and various stakeholders from industry and academia to review recent developments and provide input for planning future research in solar resource characterization, including measurement, modeling, and forecasting.

Stoffel, T.

2012-06-01T23:59:59.000Z

383

European Wind Energy Conference -Brussels, Belgium, April 2008 Data mining for wind power forecasting  

E-Print Network (OSTI)

European Wind Energy Conference - Brussels, Belgium, April 2008 Data mining for wind power-term forecasting of wind energy produc- tion up to 2-3 days ahead is recognized as a major contribution the improvement of predic- tion systems performance is recognised as one of the priorities in wind energy research

Paris-Sud XI, Université de

384

MPC for Wind Power Gradients --Utilizing Forecasts, Rotor Inertia, and Central Energy Storage  

E-Print Network (OSTI)

MPC for Wind Power Gradients -- Utilizing Forecasts, Rotor Inertia, and Central Energy Storage iterations. We demonstrate our method in simulations with various wind scenarios and prices for energy. INTRODUCTION Today, wind power is the most important renewable energy source. For the years to come, many

385

Final Report on California Regional Wind Energy Forecasting Project:Application of NARAC Wind Prediction System  

DOE Green Energy (OSTI)

Wind power is the fastest growing renewable energy technology and electric power source (AWEA, 2004a). This renewable energy has demonstrated its readiness to become a more significant contributor to the electricity supply in the western U.S. and help ease the power shortage (AWEA, 2000). The practical exercise of this alternative energy supply also showed its function in stabilizing electricity prices and reducing the emissions of pollution and greenhouse gases from other natural gas-fired power plants. According to the U.S. Department of Energy (DOE), the world's winds could theoretically supply the equivalent of 5800 quadrillion BTUs of energy each year, which is 15 times current world energy demand (AWEA, 2004b). Archer and Jacobson (2005) also reported an estimation of the global wind energy potential with the magnitude near half of DOE's quote. Wind energy has been widely used in Europe; it currently supplies 20% and 6% of Denmark's and Germany's electric power, respectively, while less than 1% of U.S. electricity is generated from wind (AWEA, 2004a). The production of wind energy in California ({approx}1.2% of total power) is slightly higher than the national average (CEC & EPRI, 2003). With the recently enacted Renewable Portfolio Standards calling for 20% of renewables in California's power generation mix by 2010, the growth of wind energy would become an important resource on the electricity network. Based on recent wind energy research (Roulston et al., 2003), accurate weather forecasting has been recognized as an important factor to further improve the wind energy forecast for effective power management. To this end, UC-Davis (UCD) and LLNL proposed a joint effort through the use of UCD's wind tunnel facility and LLNL's real-time weather forecasting capability to develop an improved regional wind energy forecasting system. The current effort of UC-Davis is aimed at developing a database of wind turbine power curves as a function of wind speed and direction, using its wind tunnel facility at the windmill farm at the Altamont Pass. The main objective of LLNL's involvement is to provide UC-Davis with improved wind forecasts to drive the parameterization scheme of turbine power curves developed from the wind tunnel facility. Another objective of LLNL's effort is to support the windmill farm operation with real-time wind forecasts for the effective energy management. The forecast skill in capturing the situation to meet the cut-in and cutout speed of given turbines would help reduce the operation cost in low and strong wind scenarios, respectively. The main focus of this report is to evaluate the wind forecast errors of LLNL's three-dimensional real-time weather forecast model at the location with the complex terrain. The assessment of weather forecast accuracy would help quantify the source of wind energy forecast errors from the atmospheric forecast model and/or wind-tunnel module for further improvement in the wind energy forecasting system.

Chin, H S

2005-07-26T23:59:59.000Z

386

Effects of the Financial Crisis on Photovoltaics: An Analysis of Changes in Market Forecasts from 2008 to 2009  

DOE Green Energy (OSTI)

To examine how the financial crisis has impacted expectations of photovoltaic production, demand and pricing over the next several years, we surveyed the market forecasts of industry analysts that had issued projections in 2008 and 2009. We find that the financial crisis has had a significant impact on the PV industry, primarily through increasing the cost and reducing the availability of investment into the sector. These effects have been more immediately experienced by PV installations than by production facilities, due to the different types and duration of investments, and thus PV demand has been reduced by a greater proportion than PV production. By reducing demand more than production, the financial crisis has accelerated previously expected PV overcapacity and resulting price declines.

Bartlett, J. E.; Margolis, R. M.; Jennings, C. E.

2009-09-01T23:59:59.000Z

387

Forecasting multi-appliance usage for smart home energy management  

Science Conference Proceedings (OSTI)

We address the problem of forecasting the usage of multiple electrical appliances by domestic users, with the aim of providing suggestions about the best time to run appliances in order to reduce carbon emissions and save money (assuming time-of-use ...

Ngoc Cuong Truong, James McInerney, Long Tran-Thanh, Enrico Costanza, Sarvapali D. Ramchurn

2013-08-01T23:59:59.000Z

388

Press Room - Presentations - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

State Energy Working Group Washington, DC—December 22, 2009 Annual Energy Outlook 2010 Reference Case pdf ppt. Subject: Forecasts, Energy Markets: Presented ...

389

The National Energy Modeling System: An Overview 2000 - Commercial...  

Gasoline and Diesel Fuel Update (EIA)

demand module (CDM) forecasts energy consumption by Census division for eight marketed energy sources plus solar and geothermal energy. For the three major commercial sector...

390

Issues in midterm analysis and forecasting, 1996  

SciTech Connect

This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation.

NONE

1996-08-01T23:59:59.000Z

391

International Energy Outlook 2006 - World Oil Markets  

Gasoline and Diesel Fuel Update (EIA)

Oil Markets Oil Markets International Energy Outlook 2006 Chapter 3: World Oil Markets In the IEO2006 reference case, world oil demand increases by 47 percent from 2003 to 2030. Non-OECD Asia, including China and India, accounts for 43 percent of the increase. In the IEO2006 reference case, world oil demand grows from 80 million barrels per day in 2003 to 98 million barrels per day in 2015 and 118 million barrels per day in 2030. Demand increases strongly despite world oil prices that are 35 percent higher in 2025 than in last yearÂ’s outlook. Much of the growth in oil consumption is projected for the nations of non-OECD Asia, where strong economic growth is expected. Non-OECD Asia (including China and India) accounts for 43 percent of the total increase in world oil use over the projection period.

392

Volume 15, number 1 February 2010 markets products analysis research Forecasts  

E-Print Network (OSTI)

outlooks Features 4 China: Wood market trends global statistics 6 australia, new Zealand, usa, Canada.woodmarkets.com. #12;ItisexpectedthatChina'stotalwoodfibre demand on a roundwood equivalent basis (RWE) will reach 350

393

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

E-Print Network (OSTI)

2003). Balancing Natural Gas Policy - Fueling the Demands ofThis lead to the Natural Gas Policy Act (NGPA) in 1978 whichnatural gas markets, demand-side management programs, development of renewable sources, and environmental policies. ”

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

2005-01-01T23:59:59.000Z

394

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

E-Print Network (OSTI)

1 1.1 History of Natural Gaspdf/table13.pdf> History of Natural Gas Regulation TheUnderstanding the history of the natural gas market helps to

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

2005-01-01T23:59:59.000Z

395

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

E-Print Network (OSTI)

is on the rise, natural gas demand is expected to grow 2.4%has resulted in higher natural gas demand and volatility andelectricity and natural gas markets, demand-side management

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

2005-01-01T23:59:59.000Z

396

Analysis and forecast of the capesize bulk carriers shipping market using Artificial Neural Networks  

E-Print Network (OSTI)

Investing in the bulk carrier market constitutes a rather risky investment due to the volatility of the bulk carrier freight rates. In this study it is attempted to uncover the benefits of using Artificial Neural Networks ...

Voudris, Athanasios V

2006-01-01T23:59:59.000Z

397

Forecasting the Growth of Green Power Markets in the United States  

E-Print Network (OSTI)

....................................................... 45 The Pace of Electricity Reform to reduce the environmental footprint of the electricity generation sector. Though many believe that state electricity markets offers a complementary approach to encourage renewable electricity supply. In particular

398

Forecasting the Growth of Green Power Markets in the United States  

E-Print Network (OSTI)

....................................................... 46 The Pace of Electricity Reform to reduce the environmental footprint of the electricity generation sector. Though many believe that state electricity markets offers a complementary approach to encourage renewable electricity supply. In particular

399

Current State of the Voluntary Renewable Energy Market (Presentation...  

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

Current State of the Voluntary Renewable Energy Market Jenny Heeter, NREL Renewable Energy Markets Conference 2013 Austin, Texas September 24, 2013 NRELPR-6A20-60357 2 Voluntary...

400

August 28 Webinar to Explore Renewable Energy Market Trends ...  

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

August 28 Webinar to Explore Renewable Energy Market Trends August 28 Webinar to Explore Renewable Energy Market Trends August 21, 2013 - 12:18pm Addthis The U.S. Department of...

Note: This page contains sample records for the topic "forecasted energy market" 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

The Strategic Impact of Changing Energy Markets on the Aluminium ...  

Science Conference Proceedings (OSTI)

Feb 18, 2010 ... What is going on in global energy markets? ? What does this mean ... The global energy markets have exhibited considerable volatility over the past .... CRU Analysis. Principal ... CRU contacts for further information or follow up:

402

Energy Market and Economic Impacts of S.2191, the Lieberman-Warner climate Security Act of 2007  

Gasoline and Diesel Fuel Update (EIA)

1 1 Energy Market and Economic Impacts of S. 2191, the Lieberman-Warner Climate Security Act of 2007 April 2008 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. Service Reports are prepared by the Energy Information Administration upon special request and are based on assumptions specified by

403

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network (OSTI)

local-level wholesale energy market price dynamics and localare included. Energy factor market prices, the shape of theare included. Energy factor market prices, the shape of the

Jaffee, Dwight M.; Stanton, Richard; Wallace, Nancy E.

2010-01-01T23:59:59.000Z

404

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network (OSTI)

local-level wholesale energy market price dynamics and localare included. Energy factor market prices, the shape of theare included. Energy factor market prices, the shape of the

Jaffee, Dwight; Stanton, Richard; Wallace, Nancy

2012-01-01T23:59:59.000Z

405

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network (OSTI)

contractual, energy and market-related characteristics. Afunction of local energy-market and weather characteristicslocal-level wholesale energy market price dynamics and local

Jaffee, Dwight; Stanton, Richard; Wallace, Nancy

2012-01-01T23:59:59.000Z

406

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network (OSTI)

contractual, energy and market-related characteristics. Alocal-level wholesale energy market price dynamics and localexpenses, and energy factor market inputs. In a companion

Jaffee, Dwight M.; Stanton, Richard; Wallace, Nancy E.

2010-01-01T23:59:59.000Z

407

Energy & Financial Markets: What Drives Crude Oil Prices? - Energy  

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

& Financial Markets - U.S. Energy Information Administration (EIA) & Financial Markets - U.S. Energy Information Administration (EIA) U.S. Energy Information Administration - EIA - Independent Statistics and Analysis Sources & Uses Petroleum & Other Liquids Crude oil, gasoline, heating oil, diesel, propane, and other liquids including biofuels and natural gas liquids. Natural Gas Exploration and reserves, storage, imports and exports, production, prices, sales. Electricity Sales, revenue and prices, power plants, fuel use, stocks, generation, trade, demand & emissions. Consumption & Efficiency Energy use in homes, commercial buildings, manufacturing, and transportation. Coal Reserves, production, prices, employ- ment and productivity, distribution, stocks, imports and exports. Renewable & Alternative Fuels

408

Market Transformation: Solar Energy Technologies Program (SETP) (Fact Sheet)  

DOE Green Energy (OSTI)

Fact sheet summarizing the goals and activities of the DOE Solar Energy Technologies Program efforts within its market transformation subprogram.

Not Available

2009-10-01T23:59:59.000Z

409

Enhancements to ANNSTLF, EPRI's Short Term Load Forecaster  

Science Conference Proceedings (OSTI)

Reliable hourly load forecasts are important to electric utilities, power marketers, energy service providers, and independent system operators. To meet this need, EPRI's Artificial Neural Net Short Term Load Forecaster (ANNSTLF), which is already implemented at more than thirty-five utilities, was recently enhanced for greater accuracy and user friendliness.

1997-12-08T23:59:59.000Z

410

Annual Energy Outlook 2001-Appendix G: Major Assumptions for the Forecasts  

Gasoline and Diesel Fuel Update (EIA)

Forecasts Forecasts Summary of the AEO2001 Cases/ Scenarios - Appendix Table G1 bullet1.gif (843 bytes) Model Results (Formats - PDF, ZIP) - Appendix Tables - Reference Case - 1998 to 2020 bullet1.gif (843 bytes) Download Report - Entire AEO2001 (PDF) - AEO2001 by Chapters (PDF) bullet1.gif (843 bytes) Acronyms bullet1.gif (843 bytes) Contacts Related Links bullet1.gif (843 bytes) Assumptions to the AEO2001 bullet1.gif (843 bytes) Supplemental Data to the AEO2001 (Only available on the Web) - Regional and more detailed AEO 2001 Reference Case Results - 1998, 2000 to 2020 bullet1.gif (843 bytes) NEMS Conference bullet1.gif (843 bytes) Forecast Homepage bullet1.gif (843 bytes) EIA Homepage Appendix G Major Assumptions for the Forecasts Component Modules Major Assumptions for the Annual Energy Outlook 2001

411

Energy Information Administration / Supplement to: Energy Market and Economic Im  

Gasoline and Diesel Fuel Update (EIA)

Supplement to: Energy Market and Economic Impacts of S. 280, the Climate Stewardship and Innovation Act Supplement to: Energy Market and Economic Impacts of S. 280, the Climate Stewardship and Innovation Act of 2007 1 Supplement to: Energy Market and Economic Impacts of S. 280, the Climate Stewardship and Innovation Act of 2007 October 2007 This paper responds to a September 18, 2007, letter from Senators Barrasso, Inhofe, and Voinovich, hereinafter referred to as the BIV request, seeking further energy and economic analysis to supplement information presented in the Energy Information Administration's (EIA) recent analysis of S. 280, the Climate Stewardship and Innovation Act of 2007 1 . The BIV request raises issues that would also apply in the context of EIA analyses of other policy proposals. A copy of the request letter is provided in Appendix A. To meet the Senators' desire for an expedited response, this paper is organized around the main issues

412

Renewable Energy Market Update | Department of Energy  

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

MST Attendees will learn about the latest developments of the five types of renewable energy technologies (biomass, geothermal, low-head hydro, solar, and wind). Attendees will...

413

Quantifying the Impact of Wind Energy on Market Coupling  

E-Print Network (OSTI)

Quantifying the Impact of Wind Energy on Market Coupling Hélène Le Cadre Mathilde Didier Abstract and of the uncertainty resulting from the introduction of renewable energy on the procurement total cost, on the market- formation on the quantities of renewable energy produced by the other markets, we show that the providers

Recanati, Catherine

414

California Wind Energy Forecasting Program Description and Status - 2000: California Energy Commission--EPRI Wind Energy Forecasting Program  

Science Conference Proceedings (OSTI)

The modern era of wind power began in the early 1980s when the first large installations of modern wind turbines were installed in California. The industry has grown rapidly in recent years and, at the end of 1999, the total installed wind capacity was 13.4 gigawatts (GW) worldwide and 2.5 GW in the U.S., of which about 1.6 GW is operating in California. Deregulation of the California electricity markets in 1998 created a challenge for the California investor-owned utilitiies and the owners and operators...

2000-12-18T23:59:59.000Z

415

Market Brief: Status of the Voluntary Renewable Energy Certificate Market (2011 Data)  

Science Conference Proceedings (OSTI)

This report documents the status and trends of U.S. 'voluntary' markets -- those in which consumers and institutions purchase renewable energy to match their electricity needs on a voluntary basis. Voluntary REC markets continue to exhibit growth and spur renewable energy development. Voluntary green power markets provide an additional revenue stream for renewable energy projects and raise consumer awareness of the benefits of renewable energy. Although a full estimate of the size of the voluntary market is not available for 2011, this review uses indicative metrics to capture 2011 voluntary market trends.

Heeter, J.; Armstrong, P.; Bird, L.

2012-09-01T23:59:59.000Z

416

European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind Generation by a Dynamic  

E-Print Network (OSTI)

European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind forecasting. I. INTRODUCTION HE actual large-scale integration of wind energy in several European countries enhance the position of wind energy compared to other dispatchable forms of generation. Predicting

Paris-Sud XI, Université de

417

Distributed Energy Resources Market Diffusion Model  

SciTech Connect

Distributed generation (DG) technologies, such as gas-fired reciprocating engines and microturbines, have been found to be economically beneficial in meeting commercial-sector electrical, heating, and cooling loads. Even though the electric-only efficiency of DG is lower than that offered by traditional central stations, combined heat and power (CHP) applications using recovered heat can make the overall system energy efficiency of distributed energy resources (DER) greater. From a policy perspective, however, it would be useful to have good estimates of penetration rates of DER under various economic and regulatory scenarios. In order to examine the extent to which DER systems may be adopted at a national level, we model the diffusion of DER in the US commercial building sector under different technical research and technology outreach scenarios. In this context, technology market diffusion is assumed to depend on the system's economic attractiveness and the developer's knowledge about the technology. The latter can be spread both by word-of-mouth and by public outreach programs. To account for regional differences in energy markets and climates, as well as the economic potential for different building types, optimal DER systems are found for several building types and regions. Technology diffusion is then predicted via two scenarios: a baseline scenario and a program scenario, in which more research improves DER performance and stronger technology outreach programs increase DER knowledge. The results depict a large and diverse market where both optimal installed capacity and profitability vary significantly across regions and building types. According to the technology diffusion model, the West region will take the lead in DER installations mainly due to high electricity prices, followed by a later adoption in the Northeast and Midwest regions. Since the DER market is in an early stage, both technology research and outreach programs have the potential to increase DER adoption, and thus, shift building energy consumption to a more efficient alternative.

Maribu, Karl Magnus; Firestone, Ryan; Marnay, Chris; Siddiqui,Afzal S.

2006-06-16T23:59:59.000Z

418

Modelling Correlation in Carbon and Energy Markets  

E-Print Network (OSTI)

, reflecting usage of installed generation capacity. The two hydrocarbon fuels, whose price interactions with carbon emission allowances are under consideration in this study, natural gas and hard coal, together account for approximately 35% of total fuel input... Modelling Correlation in Carbon and Energy Markets Philipp Koenig February 2011 CWPE 1123 & EPRG 1107 www.eprg.group.cam.ac.uk E P R G W O R K IN G P A P E R Abstract Modelling Correlation...

Koenig, Philipp

2011-02-10T23:59:59.000Z

419

Distributed Energy Resources Market Diffusion Model  

SciTech Connect

Distributed generation (DG) technologies, such as gas-fired reciprocating engines and microturbines, have been found to be economically beneficial in meeting commercial-sector electrical, heating, and cooling loads. Even though the electric-only efficiency of DG is lower than that offered by traditional central stations, combined heat and power (CHP) applications using recovered heat can make the overall system energy efficiency of distributed energy resources (DER) greater. From a policy perspective, however, it would be useful to have good estimates of penetration rates of DER under various economic and regulatory scenarios. In order to examine the extent to which DER systems may be adopted at a national level, we model the diffusion of DER in the US commercial building sector under different technical research and technology outreach scenarios. In this context, technology market diffusion is assumed to depend on the system's economic attractiveness and the developer's knowledge about the technology. The latter can be spread both by word-of-mouth and by public outreach programs. To account for regional differences in energy markets and climates, as well as the economic potential for different building types, optimal DER systems are found for several building types and regions. Technology diffusion is then predicted via two scenarios: a baseline scenario and a program scenario, in which more research improves DER performance and stronger technology outreach programs increase DER knowledge. The results depict a large and diverse market where both optimal installed capacity and profitability vary significantly across regions and building types. According to the technology diffusion model, the West region will take the lead in DER installations mainly due to high electricity prices, followed by a later adoption in the Northeast and Midwest regions. Since the DER market is in an early stage, both technology research and outreach programs have the potential to increase DER adoption, and thus, shift building energy consumption to a more efficient alternative.

Maribu, Karl Magnus; Firestone, Ryan; Marnay, Chris; Siddiqui,Afzal S.

2006-06-16T23:59:59.000Z

420

CSP Technology, Markets and Development Presentation | Open Energy  

Open Energy Info (EERE)

CSP Technology, Markets and Development Presentation CSP Technology, Markets and Development Presentation Jump to: navigation, search Tool Summary LAUNCH TOOL Name: CSP Technology, Markets and Development Presentation Agency/Company /Organization: National Renewable Energy Laboratory Sector: Energy Focus Area: Solar, - Concentrating Solar Power Topics: Market analysis, Technology characterizations Resource Type: Presentation, Training materials Website: prod-http-80-800498448.us-east-1.elb.amazonaws.com//w/images/0/0a/CSP_ References: CSP Technology, Markets and Development Presentation[1] Presentation References ↑ "CSP Technology, Markets and Development Presentation" Retrieved from "http://en.openei.org/w/index.php?title=CSP_Technology,_Markets_and_Development_Presentation&oldid=686664"

Note: This page contains sample records for the topic "forecasted energy market" 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

SHOET-TERM - Energy Information Administration  

U.S. Energy Information Administration (EIA)

System, maintained by the Energy Analysis and Forecasting Division of the Office of Energy Markets and End Use. 21. PennWell Publishing Company., ...

422

Hierarchically structured energy markets as novel smart grid control approach  

Science Conference Proceedings (OSTI)

The paper investigates the self-stabilization of hierarchically structured markets. We propose a new approach that is motivated by the physical structure of the energy grid and generalizes classical market structures in a natural way. Hierarchical markets ... Keywords: agents, hierarchical markets, simulation, smart grid

Jörg Lässig; Benjamin Satzger; Oliver Kramer

2011-10-01T23:59:59.000Z

423

Energy Crossroads: Market Data | Environmental Energy Technologies...  

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

Skip messages Jump to page content Jump to page footer Home Environmental Energy Technologies Division Emergency Contacts Intranet A-Z Index Staff How Do I? License a technology...

424

Empowering the Market: How Building Energy Performance Rating...  

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

Empowering the Market: How Building Energy Performance Rating and Disclosure Policies Encourage U.S. Energy Efficiency Secondary menu About us Press room Contact Us Portfolio...

425

U.S. Department of Energy Technology Marketing Summaries ...  

Site Map; Printable Version; Share this resource. Send a link to U.S. Department of Energy Technology Marketing Summaries - Energy Innovation Portalto ...

426

Technology-to-Market Team | Department of Energy  

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

Efficiency and Renewable Energy's (EERE's) technologies and initiatives. Tech-to-Market works to attract additional private sector investment in clean energy development, to...

427

Coal Market Module of the National Energy Modeling System ...  

U.S. Energy Information Administration (EIA)

Coal Market Module of the National Energy Modeling System Model Documentation 2013 June 2013 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy

428

NREL: Power Technologies Energy Data Book - Chapter 4. Forecasts...  

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

Databook Home More Search Options Search Site Map Featured Links Biomass Energy Data Book Buildings Energy Data Book Hydrogen Energy Data Book Transportation Energy Data Book...

429

Details, Details... The Impact of Market Rules on Emerging "Green " Energy Markets  

E-Print Network (OSTI)

Green power marketing is creating a customer-driven market for renewable energy resources, including solar, wind, geothermal, biomass, and hydropower. Yet there are a number of “market barriers” to the creation of a workable green power market, and the ultimate success of retail markets for green power products will depend critically on the detailed “market rules ” established at the onset of restructuring and on a number of “market facilitation ” efforts. By surveying green power marketers and reviewing regulatory filings, this paper identifies and analyzes the types of restructuring market rules and market facilitation efforts that impact the competitive market for electricity services broadly, and the retail market for green power specifically. Taking a marketer perspective as our point of reference, we emphasize those rules and efforts that most effectively target key market barriers and that might be most successful in expanding the market for retail green power products. This information should help those interested in encouraging the development of the green power market during the early years of electricity restructuring.

Ernest Orlando Lawrence; Ryan Wiser; Steven Pickle; Joseph Eto

1998-01-01T23:59:59.000Z

430

Market Brief: Status of the Voluntary Renewable Energy Certificate Market (2011 Data)  

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

Market Brief: Status of the Market Brief: Status of the Voluntary Renewable Energy Certificate Market (2011 Data) Jenny Heeter, Philip Armstrong, and Lori Bird National Renewable Energy Laboratory Technical Report NREL/TP-6A20-56128 September 2012 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory 15013 Denver West Parkway Golden, Colorado 80401 303-275-3000 * www.nrel.gov Contract No. DE-AC36-08GO28308 Market Brief: Status of the Voluntary Renewable Energy Certificate Market (2011 Data) Jenny Heeter, Philip Armstrong, and Lori Bird National Renewable Energy Laboratory Prepared under Task Nos. SAO9.3110 and SA12 0324

431

CONSULTANT REPORT DEMAND FORECAST EXPERT  

E-Print Network (OSTI)

CONSULTANT REPORT DEMAND FORECAST EXPERT PANEL INITIAL forecast, end-use demand modeling, econometric modeling, hybrid demand modeling, energyMahon, Carl Linvill 2012. Demand Forecast Expert Panel Initial Assessment. California Energy

432

International Energy Outlook 1999 - World Oil Markets  

Gasoline and Diesel Fuel Update (EIA)

oil.gif (4669 bytes) oil.gif (4669 bytes) A moderate view of future oil market developments is reflected in IEO99. Sustained high levels of oil prices are not expected, whereas continued expansion of the oil resource base is anticipated. The crude oil market was wracked with turbulence during 1998, as prices fell by one-third on average from 1997 levels. Even without adjusting for inflation, the world oil price in 1998 was the lowest since 1973. The declining oil prices were influenced by an unexpected slowdown in the growth of energy demand worldwide—less than any year since 1990—and by increases in oil supply, particularly in 1997. Although the increase in world oil production in 1998 was smaller than in any year since 1993, efforts to bolster prices by imposing further limits on production were

433

Commercial nuclear and uranium market forecasts for the United States and the world outside communist areas. Analysis report AR/ES/80-02  

SciTech Connect

Nuclear power forecasts prepared by the Energy Information Administration (EIA) of the United States Department of Energy are presented. The domestic forecasts from the EIA Annual Report to Congress for 1978 (published in July 1979) are detailed for the two time frames considered in the EIA analytical hierarchy: the midterm, encompassing the 1985, 1990, and 1995 milestones and the long term, beyond 1995 to the year 2020. EIA nuclear forecasts for the balance of nations in the World Outside Communist Areas (WOCA) are also presented through the year 2000. In turn, an assessment is made of the uranium consumption requirements implied by both the domestic and WOCA nuclear power forecasts. A discussion is included of appropriate fuel cycle assumptions, sensitivities, and price projections.

Clark, R.G.; Reynolds, A.W.

1980-01-01T23:59:59.000Z

434

Forecasting technology costs via the Learning Curve - Myth or Magic?  

E-Print Network (OSTI)

is generally considered to be traditional fossil fuel power stations, hence making a further assumption that such a value for cost can be forecasted). In situations where niche markets exist (for example solar PV electricity for remote areas or hand held... Solar PV provides a good example of the use and dangers of using experience curves to forecast future costs of an energy technology. It is a good example since solar PV modules are generally accessed by an international market allowing for worldwide...

Alberth, Stephan

435

Increasing access to the carbon market ENERGY, CLIMATE  

E-Print Network (OSTI)

· workshops; Knowledge and information management;· Research, policy analysis, and market surveil-· lanceIncreasing access to the carbon market ENERGY, CLIMATE AND SUSTAINABLE DEVELOPMENT 2008 #12;2 World is growing in parallel. With a dynamic carbon market under constant development, the Energy and Carbon Fi

436

Analysis of the Russian Market for Building Energy Efficiency  

Science Conference Proceedings (OSTI)

This report provides analysis of the Russian energy efficiency market for the building sector from the perspective of U.S. businesses interested in exporting relevant technologies, products and experience to Russia. We aim to help U.S. energy efficiency and environmental technologies businesses to better understand the Russian building market to plan their market strategy.

Lychuk, Taras; Evans, Meredydd; Halverson, Mark A.; Roshchanka, Volha

2012-12-01T23:59:59.000Z

437

September 4 Webinar to Explore Renewable Energy Market Trends | Department  

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

4 Webinar to Explore Renewable Energy Market Trends 4 Webinar to Explore Renewable Energy Market Trends September 4 Webinar to Explore Renewable Energy Market Trends August 21, 2013 - 12:18pm Addthis The U.S. Department of Energy (DOE) Office of Indian Energy, the DOE Office of Energy Efficiency and Renewable Energy's Tribal Energy Program, and the Western Area Power Administration (WAPA) will present the next Tribal Renewable Energy Series webinar, "Renewable Energy Market Expectations and Trends," on Wednesday, September 4, 2013, from 1:00 p.m. to 2:30 p.m. Eastern Time. "There are many factors that will drive the growth of the renewable energy market and influence the pace of that growth," said Randy Manion, Renewable Energy Program Manager at WAPA. "Among them are growing awareness of the many benefits associated with a low-carbon economy,

438

LOAD FORECASTING Eugene A. Feinberg  

E-Print Network (OSTI)

's electricity price forecasting model, produces forecast of gas demand consistent with electric load. #12Gas demand Council's Market Price of Electricity Forecast Natural GasDemand Electric Load Aggregating Natural between the natural gas and electricity and new uses of natural gas emerge. T natural gas forecasts

Feinberg, Eugene A.

439

2010 Solar Market Transformation Analysis and Tools | Open Energy  

Open Energy Info (EERE)

2010 Solar Market Transformation Analysis and Tools 2010 Solar Market Transformation Analysis and Tools Jump to: navigation, search Tool Summary Name: 2010 Solar Market Transformation Analysis and Tools Agency/Company /Organization: U.S. Department of Energy Sector: Energy Focus Area: Renewable Energy, Solar Topics: Market analysis, Pathways analysis, Technology characterizations Resource Type: Publications, Guide/manual Website: www1.eere.energy.gov/solar/pdfs/2010_mt_overview.pdf 2010 Solar Market Transformation Analysis and Tools Screenshot References: 2010 Solar Market Transformation Analysis and Tools[1] This document describes the DOE-funded solar market transformation analysis and tools under developm This document describes the DOE-funded solar market transformation analysis and tools under development in FY10 so that stakeholders can access

440

U.S. Energy Information Administration / 2012 Uranium Marketing...  

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

U.S. Energy Information Administration 2012 Uranium Marketing Annual Report 2012 Uranium Marketing Annual Report Release Date: May 16, 2013 Next Release Date: May 2014 U.S....

Note: This page contains sample records for the topic "forecasted energy market" 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

NREL: Energy Analysis - Market Analysis Models and Tools  

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

Energy Analysis Search More Search Options Site Map Printable Version Market Analysis Models and Tools The following is a list of models and tools that are used for market...

442

Optimization of time-based rates in forward energy markets  

E-Print Network (OSTI)

This paper presents a new two-step design approach of Time-Based Rate (TBR) programs for markets with a high penetration of variable energy sources such as wind power. First, an optimal market time horizon must be determined ...

Wang, J.

443

Energy and Financial Markets Overview: Crude Oil Price Formation  

Gasoline and Diesel Fuel Update (EIA)

Richard Newell, Administrator Richard Newell, Administrator May 5, 2011 Energy and Financial Markets Overview: Crude Oil Price Formation EIA's Energy and Financial Markets Initiative 2 Richard Newell, May 5, 2011 * Collection of critical energy information to improve market transparency - improved petroleum storage capacity data - other improvements to data quality and coverage * Analysis of energy and financial market dynamics to improve understanding of what drives energy prices - internal analysis and sponsorship of external research * Outreach with other Federal agencies, experts, and the public - expert workshops - public sessions at EIA's energy conferences - solicitation of public comment on EIA's data collections

444

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Policy Office Electricity Modeling System POEMS U.S. Department of Energy NANGAS/IPM NANGAS North American

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

2005-01-01T23:59:59.000Z

445

Interaction of Compliance and Voluntary Renewable Energy Markets  

SciTech Connect

In recent years, both compliance and voluntary markets have emerged to help support the development of renewable energy resources. Both of these markets are growing rapidly and today about half of U.S. states have RPS policies in place, with a number of these policies adopted in the last several years. In addition, many states have recently increased the stringency of their RPS policies. This paper examines key market interaction issues between compliance and voluntary renewable energy markets. It provides an overview of both the compliance and voluntary markets, addressing each market's history, purpose, size, scope, and benefits while addressing issues, including double counting.

Bird, L.; Lokey, E.

2007-10-01T23:59:59.000Z

446

The Small Office Market: Size, Business Diversity, and Energy Choices  

Science Conference Proceedings (OSTI)

In its entirety, the office segment represents about 20 percent of total commercial electricity use in the United States or roughly $15 billion. Natural gas revenues are about $3 billion. Large offices provide an attractive market for energy providers because they represent a large fraction energy use; but the small office segment of the market, though less familiar, is also significant. This report provides an overview of the office market as a whole and a detailed picture of the small office market. Th...

1999-06-09T23:59:59.000Z

447

Noncommercial Trading in the Energy Futures Market  

Reports and Publications (EIA)

How do futures markets affect spot market prices? This is one of the most pervasive questions surrounding futures markets, and it has been analyzed in numerous ways for many commodities.

Information Center

1996-05-01T23:59:59.000Z

448

Forecasting the market for SO sub 2 emission allowances under uncertainty  

SciTech Connect

This paper deals with the effects of uncertainty and risk aversion on market outcomes for SO{sub 2} emission allowance prices and on electric utility compliance choices. The 1990 Clean Air Act Amendments (CAAA), which are briefly reviewed here, provide for about twice as many SO{sub 2} allowances to be issued per year in Phase 1 (1995--1999) than in Phase 2. Considering the scrubber incentives in Phase 1, there is likely to be substantial emission banking for use in Phase 2. Allowance prices are expected to increase over time at a rate less than the return on alternative investments, so utilities which are risk neutral, or potential speculators in the allowance market, are not expected to bank allowances. The allowances will be banked by utilities that are risk averse. The Argonne Utility Simulation Model (ARGUS2) is being revised to incorporate the provisions of the CAAA acid rain title and to simulate SO{sub 2} allowance prices, compliance choices, capacity expansion, system dispatch, fuel use, and emissions using a unit level data base and alternative scenario assumptions. 1 fig.

Hanson, D.; Molburg, J.; Fisher, R.; Boyd, G.; Pandola, G.; Lurie, G.; Taxon, T.

1991-01-01T23:59:59.000Z

449

Cargill Power Markets LLC | Open Energy Information  

Open Energy Info (EERE)

Power Markets LLC Jump to: navigation, search Name Cargill Power Markets LLC Place Minnesota Utility Id 2481 Utility Location Yes Ownership W NERC Location MRO Activity Buying...

450

University of Colorado Technology Marketing Summaries - Energy ...  

University of Colorado Technology Marketing Summaries. Here you’ll find marketing summaries for technologies available for licensing from the University of Colorado ...

451

Market Monitoring Tools | Department of Energy  

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

Market Monitoring Tools Market Monitoring Tools Use dispatch, profit, revenueoffer price, withholding sensitivities to identify opportunities for local advantage that give some...

452

Independence Power Marketing | Open Energy Information  

Open Energy Info (EERE)

Power Marketing Place New York Utility Id 49921 Utility Location Yes Ownership R NERC Location NPCC Activity Wholesale Marketing Yes References EIA Form EIA-861 Final...

453

Energy estimator for weather forecasts dynamic power management of wireless sensor networks  

Science Conference Proceedings (OSTI)

Emerging Wireless Sensor Networks (WSN) consist of spatially distributed autonomous sensors. Although an embedded battery has limited autonomy, most WSNs outperform this drawback by harvesting ambient energy from the environment. Nevertheless, this external ... Keywords: design tools, dynamic power management, weather forecasts, wireless sensor networks

Nicolas Ferry; Sylvain Ducloyer; Nathalie Julien; Dominique Jutel

2011-09-01T23:59:59.000Z

454

Markets & Finance - U.S. Energy Information Administration (EIA)  

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

Markets & Finance Markets & Finance Glossary › FAQS › Overview Data Market Prices and Uncertainty Charts Archive Analysis & Projections Most Requested Electricity Financial Markets Financial Reporting System Working Papers Market Prices and Uncertainty Report What Drives Crude Oil Prices All Reports Don't miss: EIA's monthly Market Prices and Uncertainty Report or What Drives Crude Oil Prices? (an analysis of 7 key factors that may influence oil prices, physical market factorsand factors related to trading and financial markets). Crude oil price volatility and uncertainty› Evolution of WTI futures Source: U.S. Energy Information Administration, Short-Term Energy Outlook, Market Prices and Uncertainty Report. Heating oil price volatility and uncertainty› RBOB and Heating oil implied volatility

455

Exploiting weather forecasts for sizing photovoltaic energy bids  

E-Print Network (OSTI)

a stochastic model for PV power generation and a model for the electricity market with financial penalties, we temperature, change remarkably over the year. As a consequence, PV power generation cannot be modelled, without having to resort to complex time-varying stochastic models of PV pow

Giannitrapani, Antonello

456

Petroleum & Other Liquids - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & Finance. ... 2013 | Next Release: December 10, 2013.

457

The World Bank Partnership for Market Readiness (PMR) | Open Energy  

Open Energy Info (EERE)

for Market Readiness (PMR) for Market Readiness (PMR) Jump to: navigation, search Logo: The World Bank Partnership for Market Readiness (PMR) - Brazil Name The World Bank Partnership for Market Readiness (PMR) - Brazil Agency/Company /Organization World Bank Partner Australia, Denmark, EC, Germany, Japan, Netherlands, Norway Spain, Switzerland, UK, and US Sector Climate, Energy Focus Area Non-renewable Energy, Buildings, Economic Development, Energy Efficiency, Goods and Materials, Greenhouse Gas, Grid Assessment and Integration, Industry, Offsets and Certificates, People and Policy, Transportation Topics Baseline projection, Finance, GHG inventory, Implementation, Low emission development planning, Market analysis, Policies/deployment programs Website http://wbcarbonfinance.org/Rou

458

1 Energy Markets and Policy Group Energy Analysis Department The Impact of Wind Power Projects  

E-Print Network (OSTI)

1 Energy Markets and Policy Group · Energy Analysis Department The Impact of Wind Power Projects, Wind & Hydropower Technologies Program #12;2 Energy Markets and Policy Group · Energy Analysis · Conclusions and Further Research #12;3 Energy Markets and Policy Group · Energy Analysis Department Proximity

459

NREL: Energy Analysis - Dani Salyer  

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

Data Analysis and Visualization Group Energy Forecasting and Modeling Group Market and Policy Impact Analysis Group Technology Systems and Sustainability Analysis Group...

460

Optimized renewable energy forecasting in local distribution networks  

Science Conference Proceedings (OSTI)

The integration of renewable energy sources (RES) into local energy distribution networks becomes increasingly important. Renewable energy highly depends on weather conditions, making it difficult to maintain stability in such networks. To still enable ...

Robert Ulbricht; Ulrike Fischer; Wolfgang Lehner; Hilko Donker

2013-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasted energy market" 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

EA-319-A Fortis Energy Marketing & Trading GP (BNP Paribas Energy...  

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

GP) More Documents & Publications EA-319 Fortis Energy Marketing & Trading GP Natural Gas Imports and Exports - Second Quarter Report 2013 EA-223-A CMS Marketing, Services and...

462

Energy Information Administration/Petroleum Marketing Annual  

Gasoline and Diesel Fuel Update (EIA)

Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . December 1999 Propane Market Assessment for Winter 1997-1997 . . . . . . . . . . . . . . . . . . . . . . . . . . ....

463

Static Equilibrium: Forecasting Long-Term Energy Prices  

Science Conference Proceedings (OSTI)

This report describes a static equilibrium model that can be used by power companies to analyze retirement and investment decisions. Given deterministic expectations of prices, technology alternatives, and growth rates, the model defines a long-term equilibrium for an electricity market that can be used as a practical starting point for analyzing dynamic equilibrium, the distribution of outcomes associated with investment and retirement in a probabilistic world. The report includes a spreadsheet that ca...

2005-09-21T23:59:59.000Z

464

University of California Energy Institute The California Electricity Market  

E-Print Network (OSTI)

University of California Energy Institute The California Electricity Market: What a long strange trip it's been #12;University of California Energy Institute Market Organization in California · ISO of California Energy Institute Transmission Pricing Models · Fixed cost pricing models (cost recovery

California at Berkeley. University of

465

Impacts of the Kyoto Protocol on U.S. Energy Markets and Economic...  

Gasoline and Diesel Fuel Update (EIA)

Economic Activity October 1998 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 This report was...

466

On the economic analysis of problems in energy efficiency: Market barriers, market failures, and policy implications  

SciTech Connect

In his recent paper in The Energy Journal, Ronald Sutherland argues that several so-called market barriers'' to energy efficiency frequently cited in the literature are not market failures in the conventional sense and are thus irrelevant for energy policy. We argue that Sutherland has inadequately analyzed the idea of market barrier and misrepresented the policy implications of microeconomics. We find that economic theory, correctly interpreted, does not provide for the categorical dismissal of market barriers. We explore important methodological issues underlying the debate over market barriers, and discuss the importance of reconciling the findings of non-economic social sciences with the economic analysis of energy demand and consumer decision-making. We also scrutinize Sutherland's attempt to apply finance theory to rationalize high implicit discount rates observed in energy-related choices, and find this use of finance theory to be inappropriate.

Sanstad, A.H.; Koomey, J.G.; Levine, M.D.

1993-01-01T23:59:59.000Z

467

On the economic analysis of problems in energy efficiency: Market barriers, market failures, and policy implications  

SciTech Connect

In his recent paper in The Energy Journal, Ronald Sutherland argues that several so-called ``market barriers`` to energy efficiency frequently cited in the literature are not market failures in the conventional sense and are thus irrelevant for energy policy. We argue that Sutherland has inadequately analyzed the idea of market barrier and misrepresented the policy implications of microeconomics. We find that economic theory, correctly interpreted, does not provide for the categorical dismissal of market barriers. We explore important methodological issues underlying the debate over market barriers, and discuss the importance of reconciling the findings of non-economic social sciences with the economic analysis of energy demand and consumer decision-making. We also scrutinize Sutherland`s attempt to apply finance theory to rationalize high implicit discount rates observed in energy-related choices, and find this use of finance theory to be inappropriate.

Sanstad, A.H.; Koomey, J.G.; Levine, M.D.

1993-01-01T23:59:59.000Z

468

EIA highlights key factors in new energy and financial markets ...  

U.S. Energy Information Administration (EIA)

Yesterday, EIA launched a new web-based assessment highlighting key factors that can affect crude oil prices called "Energy and Financial Markets: What Drives Crude ...

469

"28 U.S. Energy Information Administration / 2012 Uranium Marketing...  

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

2972,27010 84757,26774 86527,24732 89835,22269 97466,23264 "28 U.S. Energy Information Administration 2012 Uranium Marketing Annual Report"...

470

U.S. Energy Information Administration / 2012 Uranium Marketing...  

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

rounding. Weighted-average prices are not adjusted for inflation. Source: U.S. Energy Information Administration, Form EIA-858 "Uranium Marketing Annual Survey" (2012)....

471

Renewable Energy for Electricity Generation in Latin America: Market,  

Open Energy Info (EERE)

for Electricity Generation in Latin America: Market, for Electricity Generation in Latin America: Market, Technologies, and Outlook (Webinar) Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Renewable Energy for Electricity Generation in Latin America: Market, Technologies, and Outlook (Webinar) Focus Area: Water power Topics: Market Analysis Website: www.leonardo-energy.org/webinar-renewable-energy-electricity-generatio Equivalent URI: cleanenergysolutions.org/content/renewable-energy-electricity-generati Language: English Policies: "Deployment Programs,Financial Incentives" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Demonstration & Implementation This video teaches the viewer about the current status and future

472

NREL-Solar Technologies Market Report | Open Energy Information  

Open Energy Info (EERE)

NREL-Solar Technologies Market Report NREL-Solar Technologies Market Report Jump to: navigation, search Tool Summary Name: NREL-Solar Technologies Market Report Agency/Company /Organization: National Renewable Energy Laboratory Sector: Energy Focus Area: Solar Topics: Market analysis, Technology characterizations Website: www.nrel.gov/analysis/pdfs/46025.pdf NREL-Solar Technologies Market Report Screenshot References: NREL Solar Tech Market Report[1] Logo: NREL-Solar Technologies Market Report "The focus of this report is the U.S. solar electricity market, including photovoltaic (PV) and concentrating solar power (CSP) technologies. The report is organized into five chapters. Chapter 1 provides an overview of global and U.S. installation trends. Chapter 2 presents production and shipment data, material and supply chain issues, and solar industry

473

Model documentation, Coal Market Module of the National Energy Modeling System  

Science Conference Proceedings (OSTI)

This report documents the objectives and the conceptual and methodological approach used in the development of the National Energy Modeling System`s (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1998 (AEO98). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s two submodules. These are the Coal Production Submodule (CPS) and the Coal Distribution Submodule (CDS). CMM provides annual forecasts of prices, production, and consumption of coal for NEMS. In general, the CDS integrates the supply inputs from the CPS to satisfy demands for coal from exogenous demand models. The international area of the CDS forecasts annual world coal trade flows from major supply to major demand regions and provides annual forecasts of US coal exports for input to NEMS. Specifically, the CDS receives minemouth prices produced by the CPS, demand and other exogenous inputs from other NEMS components, and provides delivered coal prices and quantities to the NEMS economic sectors and regions.

NONE

1998-01-01T23:59:59.000Z

474

Market Transformation: A Practical Guide to Designing and Evaluating Energy Efficient Programs  

Science Conference Proceedings (OSTI)

One widely accepted paradigm for energy efficiency marketing is called market transformation. This theory holds that energy efficiency programs should be designed to transform markets by reducing market barriers, thus allowing energy efficient products and services to become widely available and adopted by energy customers. Market transformation theory also states that these market changes should become persistent and self-sustaining.

2001-04-19T23:59:59.000Z

475

Assumptions to the Annual Energy Outlook 2001 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for

476

Assumptions to the Annual Energy Outlook 2002 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for

477

Fuel Cell Markets Ltd | Open Energy Information  

Open Energy Info (EERE)

Fuel Cell Markets Ltd Place Buckinghamshire, United Kingdom Zip SL0 9AQ Sector Hydro, Hydrogen Product Fuel Cell Markets was set up to assist companies in the fuel cell and...

478

Idea and Innovation Markets | Department of Energy  

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

Idea and Innovation Markets Idea and Innovation Markets MondayTechTransferTrinityBallroom4AmidonDoE - TT Animoto2012.pdf More Documents & Publications FINALDOEOGPVer1-2b07Ju...

479

Test application of a semi-objective approach to wind forecasting for wind energy applications  

SciTech Connect

The test application of the semi-objective (S-O) wind forecasting technique at three locations is described. The forecasting sites are described as well as site-specific forecasting procedures. Verification of the S-O wind forecasts is presented, and the observed verification results are interpreted. Comparisons are made between S-O wind forecasting accuracy and that of two previous forecasting efforts that used subjective wind forecasts and model output statistics. (LEW)

Wegley, H.L.; Formica, W.J.

1983-07-01T23:59:59.000Z

480

NextEra Energy Power Marketing LLC (Massachusetts) | Open Energy  

Open Energy Info (EERE)

LLC (Massachusetts) LLC (Massachusetts) Jump to: navigation, search Name NextEra Energy Power Marketing LLC Place Massachusetts Utility Id 49891 References EIA Form EIA-861 Final Data File for 2010 - File2_2010[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png No rate schedules available. Average Rates Transportation: $0.0442/kWh References ↑ "EIA Form EIA-861 Final Data File for 2010 - File2_2010" Retrieved from "http://en.openei.org/w/index.php?title=NextEra_Energy_Power_Marketing_LLC_(Massachusetts)&oldid=412709" Categories: EIA Utility Companies and Aliases Utility Companies Organizations Stubs What links here Related changes

Note: This page contains sample records for the topic "forecasted energy market" 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.


481

New Market, Maryland: Energy Resources | Open Energy Information  

Open Energy Info (EERE)

Market, Maryland: Energy Resources Market, Maryland: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 39.3826031°, -77.2694278° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.3826031,"lon":-77.2694278,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

482

October 24, 2013 Energy Midstream and Marketing  

E-Print Network (OSTI)

and Marketing program will focus on 1) natural gas 2) crude oil and 3) NGL midstream and other topics as related will address what it takes to get oil and gas to market, potential obstacles, supply, and other market factors: 405.744.6143 If you would like more information on this program, please contact us or visit

Veiga, Pedro Manuel Barbosa

483

An Analysis of the Link between Ethanol, Energy, and Crop Markets Simla Tokgoz and Amani Elobeid  

E-Print Network (OSTI)

An Analysis of the Link between Ethanol, Energy, and Crop Markets Simla Tokgoz and Amani Elobeid that the composition of a country'svehiclefleetdeterminesthedirectionoftheresponseofethanolconsumptionto changes in the sugar market affect the competing ethanol market. Keywords: agricultural markets, energy, ethanol

Beresnev, Igor

484

Renewable Energy Market Expectations and Trends Webinar | Department of  

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

Market Expectations and Trends Webinar Market Expectations and Trends Webinar Renewable Energy Market Expectations and Trends Webinar September 4, 2013 11:00AM MDT Webinar The U.S. Department of Energy (DOE) Office of Indian Energy Policy and Programs, Office of Energy Efficiency and Renewable Energy Tribal Energy Program, and Western Area Power Administration (WAPA) are pleased to continue their sponsorship of the Tribal Renewable Energy Webinar Series. The webinar will be held from 11 a.m. to 12:30 p.m. Mountain time. The growth and pace of the renewable energy market will be driven by many factors, including awareness and concern over remaining non-renewable resources, the need for imported energy and the security issues surrounding that need, and government support and financial incentives. Participants

485

California Regional Wind Energy Forecasting System Development, Volume 2:  

Science Conference Proceedings (OSTI)

The rated capacity of wind generation in California is expected to grow rapidly in the future beyond the approximately 2100 MW in place at the end of 2005. The main drivers are the state's 20 percent renewable portfolio standard requirement in 2010 and the low cost of wind energy relative to other renewable energy sources.

2006-11-15T23:59:59.000Z

486

Energy market of the European union: common or segmented?  

Science Conference Proceedings (OSTI)

The European energy market operates on the premise of open and competitive markets among its 27 member states. But the gas and electricity market dynamics and levels of competitiveness vary enormously across the EU 27. Among the issues are unequal implementation of electricity and gas directives, a lack of independent energy regulators, the absence of proper and full unbundling, and discriminatory third-party access to the infrastructure. (author)

Nowak, Bartlomiej

2010-12-15T23:59:59.000Z

487

EA-216-B TransAlta Energy Marketing (U.S) Inc | Department of...  

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

B TransAlta Energy Marketing (U.S) Inc EA-216-B TransAlta Energy Marketing (U.S) Inc Order authorizing TransAlta Energy Marketing (U.S) Inc to export electric energy to Canada....

488

EA-216-C TransAlta Energy Marketing (U.S.)Inc. | Department of...  

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

C TransAlta Energy Marketing (U.S.)Inc. EA-216-C TransAlta Energy Marketing (U.S.)Inc. Order authorizing TransAlta Energy Marketing (U.S.) Inc to export electric energy to Canada....

489

EA-163 Duke Energy Trading and Marketing, L.L.C | Department...  

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

Duke Energy Trading and Marketing, L.L.C EA-163 Duke Energy Trading and Marketing, L.L.C Order authorizing Duke Energy Trading and Marketing, L.L.C to export e;ectric energy to...

490

EA-166-A Duke Energy Trading and Marketing, L.L.C | Department...  

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

-A Duke Energy Trading and Marketing, L.L.C EA-166-A Duke Energy Trading and Marketing, L.L.C Order authorizing Duke Energy Trading and Marketing, L.L.C to export electric energy...

491

EA-166 Duke Energy Trading and Marketing, L.L.C | Department...  

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

Duke Energy Trading and Marketing, L.L.C EA-166 Duke Energy Trading and Marketing, L.L.C Order authorizing Duke Energy Trading and Marketing, L.L.C to export electric energy to...

492

EA-163-A Duke Energy Trading and Marketing, L.L.C | Department...  

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

-A Duke Energy Trading and Marketing, L.L.C EA-163-A Duke Energy Trading and Marketing, L.L.C Order authorizing Duke Energy Trading and Marketing, L.L.C to export electric energy...

493

EA-166 Duke Energy Trading and Marketing, L.L.C | Department...  

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

EA-166 Duke Energy Trading and Marketing, L.L.C EA-166 Duke Energy Trading and Marketing, L.L.C Order authorizing Duke Energy Trading and Marketing, L.L.C to export electric energy...

494

The Incremental Benefits of the Nearest Neighbor Forecast of U.S. Energy Commodity Prices  

E-Print Network (OSTI)

This thesis compares the simple Autoregressive (AR) model against the k- Nearest Neighbor (k-NN) model to make a point forecast of five energy commodity prices. Those commodities are natural gas, heating oil, gasoline, ethanol, and crude oil. The data for the commodities are monthly and, for each commodity, two-thirds of the data are used for an in-sample forecast, and the remaining one-third of the data are used to perform an out-of-sample forecast. Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) are used to compare the two forecasts. The results showed that one method is superior by one measure but inferior by another. Although the differences of the two models are minimal, it is up to a decision maker as to which model to choose. The Diebold-Mariano (DM) test was performed to test the relative accuracy of the models. For all five commodities, the results failed to reject the null hypothesis indicating that both models are equally accurate.

Kudoyan, Olga

2010-12-01T23:59:59.000Z

495

Solar Renewable Energy Certificate (SREC) Markets: Status and Trends  

DOE Green Energy (OSTI)

This paper examines experience in solar renewable energy certificate (SREC) markets in the United States. It describes how SREC markets function--key policy design provisions, eligible technologies, state and regional eligibility rules, solar alternative compliance payments, measurement and verification methods, long-term contracting provisions, and rate caps. It also examines the trends of SREC markets--trading volumes, sourcing trends, trends in the size of solar photovoltaic (PV) systems driven by these markets, and trends in price and compliance. Throughout, the paper explores key issues and challenges facing SREC markets and attempts by policymakers to address some of these market barriers. Data and information presented in this report are derived from SREC tracking systems, brokers and auctions, published reports, and information gleaned from market participants and interviews with state regulators responsible for SREC market implementation. The last section summarizes key findings.

Bird, L.; Heeter, J.; Kreycik, C.

2011-11-01T23:59:59.000Z

496

EIA - Annual Energy Outlook 2009 - Report Chapters  

Gasoline and Diesel Fuel Update (EIA)

Chapters pdf image Overview pdf image Market Trends in Economic Activity pdf image Energy Demand Projections pdf image Electricity Forecast pdf image Oil and Natural Gas...

497

EIA - Annual Energy Outlook 2010 - Report Chapters  

Annual Energy Outlook 2012 (EIA)

Chapters pdf image Overview pdf image Market Trends in Economic Activity pdf image Energy Demand Projections pdf image Electricity Forecast pdf image Oil and Natural Gas...

498

Short-Term Energy Carbon Dioxide Emissions Forecasts August 2009  

Reports and Publications (EIA)

Supplement to the Short-Term Energy Outlook. Short-term projections for U.S. carbon dioxide emissions of the three fossil fuels: coal, natural gas, and petroleum.

Information Center

2009-08-11T23:59:59.000Z

499

Growth Diagnostics for Dark Energy models and EUCLID forecast  

E-Print Network (OSTI)

In this work we introduce a new set of parameters $(r_{g}, s_{g})$ involving the linear growth of matter perturbation that can distinguish and constrain different dark energy models very efficiently. Interestingly, for $\\Lambda$CDM model these parameters take exact value $(1,1)$ at all red shifts whereas for models different from $\\Lambda$CDM, they follow different trajectories in the $(r_{g}, s_{g})$ phase plane. By considering the parametrization for the dark energy equation of state ($w$) and for the linear growth rate ($f_{g}$), we show that different dark energy behaviours with similar evolution of the linear density contrast, can produce distinguishable trajectories in the $(r_{g}, s_{g})$ phase plane. Moreover, one can put stringent constraint on these phase plane using future measurements like EUCLID ruling out some of the dark energy behaviours.

Sampurnanand; Anjan A. Sen

2013-01-06T23:59:59.000Z

500

73-428/19-624 The Transformation of Energy Markets  

E-Print Network (OSTI)

the poster child for advocates of a strong government role in energy markets. This course will blend to volatile energy prices, renewable portfolio standards in electric power generation, coal and nuclear

Blumsack, Seth