Sample records for outlook forecast evaluation

  1. CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE -APRIL 2014

    E-Print Network [OSTI]

    de Lijser, Peter

    CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE - APRIL 2014 Anil Puri, Ph.D. -- Director-year increase in the debt ceiling -- both of which proceeded without the usual drama. Second, the private sector, corporate coffers are flush with cash, and low US energy prices have dramatically improved the global

  2. The Rationality of EIA Forecasts under Symmetric and Asymmetric Loss

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01T23:59:59.000Z

    Agency: 1982-2005a, Annual Energy Outlook, EIA, Washington,Agency: 2004, Annual Energy Outlook Forecast Evaluation,Agency: 2005b, Annual Energy Outlook, EIA, Washington, D.C.

  3. Energy consumption and expenditure projections by population group on the basis of the annual energy outlook 1999 forecast

    SciTech Connect (OSTI)

    Poyer, D.A.; Balsley, J.H.

    2000-01-07T23:59:59.000Z

    This report presents an analysis of the relative impact of the base-case scenario used in Annual Energy Outlook 1999 on different population groups. Projections of energy consumption and expenditures, as well as energy expenditure as a share of income, from 1996 to 2020 are given. The projected consumption of electricty, natural gas, distillate fuel, and liquefied petroleum gas during this period is also reported for each population group. In addition, this report compares the findings of the Annual Energy Outlook 1999 report with the 1998 report. Changes in certain indicators and information affect energy use forecasts, and these effects are analyzed and discussed.

  4. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    NONE

    1996-08-01T23:59:59.000Z

    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.

  5. A NEW APPROACH FOR EVALUATING ECONOMIC FORECASTS

    E-Print Network [OSTI]

    Vertes, Akos

    APPROACH FOR EVALUATING ECONOMIC FORECASTS Tara M. Sinclair , H.O. Stekler, and Warren Carnow Department of Economics The George Washington University Monroe Hall #340 2115 G Street NW Washington, DC 20052 JEL Codes, Mahalanobis Distance Abstract This paper presents a new approach to evaluating multiple economic forecasts

  6. Metrics for Evaluating the Accuracy of Solar Power Forecasting (Presentation)

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B.; Florita, A.; Lu, S.; Hamann, H.; Banunarayanan, V.

    2013-10-01T23:59:59.000Z

    This presentation proposes a suite of metrics for evaluating the performance of solar power forecasting.

  7. Short-term energy outlook, annual supplement 1994

    SciTech Connect (OSTI)

    Not Available

    1994-08-01T23:59:59.000Z

    The Short-Term Energy Outlook Annual Supplement (Supplement) is published once a year as a complement to the Short-Term Energy Outlook (Outlook), Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts.

  8. Short-term energy outlook annual supplement, 1993

    SciTech Connect (OSTI)

    NONE

    1993-08-06T23:59:59.000Z

    The Short-Term Energy Outlook Annual Supplement (supplement) is published once a year as a complement to the Short-Term Energy Outlook (Outlook), Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts.

  9. FORECASTING SOLAR RADIATION PRELIMINARY EVALUATION OF AN APPROACH

    E-Print Network [OSTI]

    Perez, Richard R.

    FORECASTING SOLAR RADIATION -- PRELIMINARY EVALUATION OF AN APPROACH BASED UPON THE NATIONAL, and undertake a preliminary evaluation of, a simple solar radiation forecast model using sky cover predictions forecasts is 0.05o in latitude and longitude. Solar Radiation model: The model presented in this paper

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

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    2 2. Annual Energy Outlook (Administration’s Annual Energy Outlook forecasted price (of Energy, Annual Energy Outlook 2004 with Projections to

  11. Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.; Florita, A.; Lu, S.; Hamann, H. F.; Banunarayanan, V.

    2013-10-01T23:59:59.000Z

    Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

  12. Post-Construction Evaluation of Forecast Accuracy Pavithra Parthasarathi1

    E-Print Network [OSTI]

    Levinson, David M.

    Post-Construction Evaluation of Forecast Accuracy Pavithra Parthasarathi1 David Levinson 2 February, the assumed networks to the actual in-place networks and other travel behavior assumptions that went

  13. Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    day Forecast -1.0 2012 2013 2014 OPEC countries North America Russia and Caspian Sea Latin America North Sea Other Non-OPEC Source: Short-Term Energy Outlook, November 2013 -1 0...

  14. Energy consumption and expenditure projections by income quintile on the basis of the Annual Energy Outlook 1997 forecast

    SciTech Connect (OSTI)

    Poyer, D.A.; Allison, T.

    1998-03-01T23:59:59.000Z

    This report presents an analysis of the relative impacts of the base-case scenario used in the Annual Energy Outlook 1997, published by the US Department of Energy, Energy Information Administration, on income quintile groups. Projected energy consumption and expenditures, and projected energy expenditures as a share of income, for the period 1993 to 2015 are reported. Projected consumption of electricity, natural gas, distillate fuel, and liquefied petroleum gas over this period is also reported for each income group. 33 figs., 11 tabs.

  15. Short-term energy outlook, Annual supplement 1995

    SciTech Connect (OSTI)

    NONE

    1995-07-25T23:59:59.000Z

    This supplement is published once a year as a complement to the Short- Term Energy Outlook, Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts. Chap. 2 analyzes the response of the US petroleum industry to the recent four Federal environmental rules on motor gasoline. Chap. 3 compares the EIA base or mid case energy projections for 1995 and 1996 (as published in the first quarter 1995 Outlook) with recent projections made by four other major forecasting groups. Chap. 4 evaluates the overall accuracy. Chap. 5 presents the methology used in the Short- Term Integrated Forecasting Model for oxygenate supply/demand balances. Chap. 6 reports theoretical and empirical results from a study of non-transportation energy demand by sector. The empirical analysis involves the short-run energy demand in the residential, commercial, industrial, and electrical utility sectors in US.

  16. Short-Term Energy Outlook September 2013

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

    day Forecast -0.9 2012 2013 2014 OPEC countries North America Russia and Caspian Sea Latin America North Sea Other Non-OPEC Source: Short-Term Energy Outlook, September 2013 -1...

  17. Short-term energy outlook quarterly projections. First quarter 1994

    SciTech Connect (OSTI)

    Not Available

    1994-02-07T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short- term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets.

  18. International energy outlook 1994

    SciTech Connect (OSTI)

    Not Available

    1994-07-01T23:59:59.000Z

    The International Energy Outlook 1994 (IEO94) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets between 1990 and 2010. The report is provided as a statistical service to assist energy managers and analysts, both in government and in the private sector. These forecasts are used by international agencies, Federal and State governments, trade associations, and other planners and decisionmakers. They are published pursuant to the Depart. of Energy Organization Act of 1977 (Public Law 95-91), Section 205(c). The IEO94 projections are based on US and foreign government policies in effect on October 1, 1993-which means that provisions of the Climate Change Action Plan unveiled by the Administration in mid-October are not reflected by the US projections.

  19. Short-term energy outlook. Quarterly projections, Third quarter 1994

    SciTech Connect (OSTI)

    Not Available

    1994-08-02T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202). The feature article for this issue is Demand, Supply and Price Outlook for Reformulated Gasoline, 1995.

  20. Short-term energy outlook. Quarterly projections, Third quarter 1995

    SciTech Connect (OSTI)

    NONE

    1995-08-02T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent projections with those of other forecasting services, and discusses current topics related to the short-term energy markets. The forecast period for this issue of the Outlook extends from the third quarter of 1995 through the fourth quarter of 1996. Values for the second quarter of 1995, however, are preliminary EIA estimates.

  1. The Rationality of EIA Forecasts under Symmetric and Asymmetric Loss

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01T23:59:59.000Z

    2005a, Annual Energy Outlook, EIA, Washington, D.C. Energy2005b, Annual Energy Outlook, EIA, Washington, D.C. Granger,Paper ???? The Rationality of EIA Forecasts under Symmetric

  2. Fuels outlook for oil/propane

    SciTech Connect (OSTI)

    Weigand, P.

    1995-09-01T23:59:59.000Z

    The outlook for using oil and propane as fuels is outlined. The following topics are discussed: factors affecting price of the burner tip, supply and demand forecast, distribution costs and availability, alternate fuels economics, propane prices, No. 2 oil prices, natural gas vs. 1% residual HP prices, and future for industrial oil and propane consumers.

  3. Evaluation Framework and Tools for Distributed Energy Resources

    E-Print Network [OSTI]

    Gumerman, Etan Z.; Bharvirkar, Ranjit R.; LaCommare, Kristina Hamachi; Marnay, Chris

    2003-01-01T23:59:59.000Z

    Administration. 2001. "Annual Energy Outlook 2002." DOE/EIA-SOAPP TAF T&D TSI Annual Energy Outlook 2002 combined heatEIA) 2002 Annual Energy Outlook (AEO) forecast anticipates

  4. Evaluation of Advanced Wind Power Forecasting Models Results of the Anemos Project

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Evaluation of Advanced Wind Power Forecasting Models ­ Results of the Anemos Project I. Martí1.kariniotakis@ensmp.fr Abstract An outstanding question posed today by end-users like power system operators, wind power producers or traders is what performance can be expected by state-of-the-art wind power prediction models. This paper

  5. Real-Time Forecasting for the Antarctic: An Evaluation of the Antarctic Mesoscale Prediction System (AMPS)*

    E-Print Network [OSTI]

    Howat, Ian M.

    Real-Time Forecasting for the Antarctic: An Evaluation of the Antarctic Mesoscale Prediction System. MANNING AND JORDAN G. POWERS Mesoscale and Microscale Meteorology Division, National Center.S. Antarctic Program's field operations, the Antarctic Mesoscale Prediction System (AMPS) was implemented in Oc

  6. Evaluation of WRF Forecasts of Tornadic and Nontornadic Outbreaks When Initialized with Synoptic-Scale Input

    E-Print Network [OSTI]

    Doswell III, Charles A.

    Evaluation of WRF Forecasts of Tornadic and Nontornadic Outbreaks When Initialized with Synoptic outbreak simulations are compared with 50 primarily nontornadic outbreak simulations initialized tornadoes (e.g., Stensrud et al. 1997, hereafter SCB97; Doswell and Bosart 2001; Doswell et al. 2006

  7. Key Milestones/Outlook

    Broader source: Energy.gov [DOE]

    Key Milestones/Outlook per the Department of Energy 2015 Congressional Budget Request, Environmental Management, March 2014

  8. WEST VIRGINIA ECONOMIC OUTLOOK

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    WEST VIRGINIA ECONOMIC OUTLOOK 2009 BUREAU OF BUSINESS AND ECONOMIC RESEARCH College of Business and Economics West Virginia University #12;West Virginia Economic Outlook 2009 George W. Hammond, Associate Director, BBER, and Associate Professor of Economics West Virginia Economic Outlook 2009 is published

  9. Short-term energy outlook: Quarterly projections, Third quarter 1992

    SciTech Connect (OSTI)

    Not Available

    1992-08-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The principal users of the Outlook are managers and energy analysts in private industry and government. The forecast period for this issue of the Outlook extends from the third quarter of 1992 through the fourth quarter of 1993. Values for the second quarter of 1992, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding.

  10. Short-term energy outlook, January 1999

    SciTech Connect (OSTI)

    NONE

    1999-01-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares the Short-Term Energy Outlook (energy supply, demand, and price projections) monthly. The forecast period for this issue of the Outlook extends from January 1999 through December 2000. Data values for the fourth quarter 1998, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the January 1999 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the STIFS model. 28 figs., 19 tabs.

  11. Supplement to the Annual Energy Outlook 1993

    SciTech Connect (OSTI)

    Not Available

    1993-02-17T23:59:59.000Z

    The Supplement to the Annual Energy Outlook 1993 is a companion document to the Energy Information Administration`s (EIA) Annual Energy Outlook 1993 (AEO). Supplement tables provide the regional projections underlying the national data and projections in the AEO. The domestic coal, electric power, commercial nuclear power, end-use consumption, and end-use price tables present AEO forecasts at the 10 Federal Region level. World coal tables provide data and projections on international flows of steam coal and metallurgical coal, and the oil and gas tables provide the AEO oil and gas supply forecasts by Oil and Gas Supply Regions and by source of supply. All tables refer to cases presented in the AEO, which provides a range of projections for energy markets through 2010.

  12. Short-term energy outlook: Quarterly projections. Second quarter 1995

    SciTech Connect (OSTI)

    NONE

    1995-05-02T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent projections with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the second quarter of 1995 through the fourth quarter of 1996. Values for the first quarter of 1995, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data, compiled into the second quarter 1995 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service.

  13. Evaluation of forecasting techniques for short-term demand of air transportation

    E-Print Network [OSTI]

    Wickham, Richard Robert

    1995-01-01T23:59:59.000Z

    Forecasting is arguably the most critical component of airline management. Essentially, airlines forecast demand to plan the supply of services to respond to that demand. Forecasts of short-term demand facilitate tactical ...

  14. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    to  predict daily solar radiation.   Agriculture and Forest and Chuo, S.   2008.  Solar radiation forecasting using Short?term forecasting of solar radiation:   A statistical 

  15. Annual Energy Outlook 2012

    Gasoline and Diesel Fuel Update (EIA)

    Administration Annual Energy Outlook 2012 17 Table A7. Transportation sector key indicators and delivered energy consumption (continued) Key indicators and consumption...

  16. Oil and Gas Outlook

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

    Gas Outlook For Independent Petroleum Association of America November 13, 2014 | Palm Beach, FL By Adam Sieminski, Administrator U.S. Energy Information Administration Recent...

  17. Annual Energy Outlook 2012

    Gasoline and Diesel Fuel Update (EIA)

    3 U.S. Energy Information Administration | Annual Energy Outlook 2012 Reference case Table A6. Industrial sector key indicators and consumption Energy Information Administration ...

  18. Annual Energy Outlook 2012

    Gasoline and Diesel Fuel Update (EIA)

    36 Reference case Energy Information Administration Annual Energy Outlook 2012 6 Table A3. Energy prices by sector and source (2010 dollars per million Btu, unless otherwise...

  19. Annual Energy Outlook 2012

    Gasoline and Diesel Fuel Update (EIA)

    1 U.S. Energy Information Administration | Annual Energy Outlook 2012 Reference case Table A5. Commercial sector key indicators and consumption (quadrillion Btu per year, unless...

  20. Annual Energy Outlook 2012

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | Annual Energy Outlook 2012 Table G1. Heat rates Fuel Units Approximate heat content Coal 1 Production . . . . . . . . . . . . . . . . . ....

  1. Annual Energy Outlook 2012

    Gasoline and Diesel Fuel Update (EIA)

    for Defense Districts 216 U.S. Energy Information Administration Annual Energy Outlook 2010 Figure F3. Petroleum Administration for Defense Districts AK WA NV AZ OR...

  2. Annual Energy Outlook 2012

    Gasoline and Diesel Fuel Update (EIA)

    end of table. (continued on next page) U.S. Energy Information Administration | Annual Energy Outlook 2012 116 Comparison with other projections Table 28. Comparison of coal...

  3. Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01T23:59:59.000Z

    Solar irradiance data . . . . . . . . . . . . .Accuracy . . . . . . . . . . . . . . . . . Solar Resourcev Uncertainty In Solar Resource: Forecasting

  4. Short-term energy outlook quarterly projections: First quarter 1993

    SciTech Connect (OSTI)

    Not Available

    1993-02-03T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.). The forecast period for this issue of the Outlook extends from the first quarter of 1993 through the fourth quarter of 1994. Values for the fourth quarter of 1992, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding.

  5. Short-term energy outlook, Quarterly projections. Third quarter 1993

    SciTech Connect (OSTI)

    NONE

    1993-08-04T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the third quarter of 1993 through the fourth quarter of 1994. Values for the second quarter of 1993, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding.

  6. Outlook export contacts and groups Migrate Outlook Contacts to gmail

    E-Print Network [OSTI]

    Aalberts, Daniel P.

    Outlook export contacts and groups Migrate Outlook Contacts to gmail 1. In Outlook 2007 on the File menu, click Import and Export. 1a. For Outlook 2010 on the File menu, click Open, then Import 2. Click Export to a file, and then click Next. #12;3. Click Comma Separated Values (Windows), and then click Next

  7. Supplement to the annual energy outlook 1994

    SciTech Connect (OSTI)

    NONE

    1994-03-01T23:59:59.000Z

    This report is a companion document to the Annual Energy Outlook 1994 (AEO94), (DOE/EIA-0383(94)), released in Jan. 1994. Part I of the Supplement presents the key quantitative assumptions underlying the AEO94 projections, responding to requests by energy analysts for additional information on the forecasts. In Part II, the Supplement provides regional projections and other underlying details of the reference case projections in the AEO94. The AEO94 presents national forecasts of energy production, demand and prices through 2010 for five scenarios, including a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices. These forecasts are used by Federal, State, and local governments, trade associations, and other planners and decisionmakers in the public and private sectors.

  8. Short-term energy outlook, July 1998

    SciTech Connect (OSTI)

    NONE

    1998-07-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares The Short-Term Energy Outlook (energy supply, demand, and price projections) monthly for distribution on the internet at: www.eia.doe.gov/emeu/steo/pub/contents.html. In addition, printed versions of the report are available to subscribers in January, April, July and October. The forecast period for this issue of the Outlook extends from July 1998 through December 1999. Values for second quarter of 1998 data, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the July 1998 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. 28 figs., 19 tabs.

  9. Short-term energy outlook, April 1999

    SciTech Connect (OSTI)

    NONE

    1999-04-01T23:59:59.000Z

    The forecast period for this issue of the Outlook extends from April 1999 through December 2000. Data values for the first quarter 1999, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the April 1999 version of the Short-Term Integrated forecasting system (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the STIFS model. 25 figs., 19 tabs.

  10. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    and validation.   Solar Energy.   73:5, 307? Perez, R. , forecast database.   Solar Energy.   81:6, 809?812.  forecasts in the US.   Solar Energy.   84:12, 2161?2172.  

  11. Supplement to the annual energy outlook 1995

    SciTech Connect (OSTI)

    Not Available

    1995-02-01T23:59:59.000Z

    This section of the Supplement to the Annual Energy Outlook 1995 present the major assumptions of the modeling system used to generate the projections in the Annual Energy Outlook 1995 (AEO95). In this context, assumptions include general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports listed in Appendix B. A synopsis of the National Energy Modeling System (NEMS), the model components, and the interrelationships of the modules is presented. The NEMS is developed and maintained by the office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projection of domestic energy-economy markets in the midterm time period and perform policy analyses requested by various government agencies and the private sector.

  12. Energy Market Outlook

    Broader source: Energy.gov [DOE]

    Presentation covers the Federal Utility Partnership Working Group Energy Market Outlook: Helping Customers Meet Their Diverse Energy Goals, held on May 22-23, 2013 in San Francisco, California.

  13. Missouri Agriculture Outlook Conference

    E-Print Network [OSTI]

    Noble, James S.

    Missouri Agriculture Outlook Conference Conference Information This conference will discuss the drivers of Missouri agricultural and bio-fuel markets and the implications for Missouri farmsDr.JonHagler, DirectoroftheMissouriDepartment ofAgriculture. · Outlookpresentationsderivedfrom thelatestbaselineresultsof

  14. Annual Energy Outlook 2013

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

    oil and natural gas outlook IAEE International Conference June 16, 2014 | New York, NY By Adam Sieminski, EIA Administrator The U.S. has experienced a rapid increase in natural gas...

  15. Annual Energy Outlook 2013

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

    Energy Outlook Oil and Gas Strategies Summit May 21, 2014 | New York, NY By Adam Sieminski, EIA Administrator The U.S. has experienced a rapid increase in natural gas and oil...

  16. Annual Energy Outlook 2012

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

    5 U.S. Energy Information Administration | Annual Energy Outlook 2012 Regional maps Figure F4. Oil and gas supply model regions Figure F4. Oil and Gas Supply Model Regions Atlantic...

  17. Annual energy outlook 1995, with projections to 2010

    SciTech Connect (OSTI)

    NONE

    1995-01-01T23:59:59.000Z

    The Annual Energy Outlook 1995 (AEO95) presents the midterm energy forecasts of the Energy Information Administration (EIA). This year`s report presents projections and analyses of energy supply, demand, and prices through 2010, based on results from the National Energy Modeling System (NEMS). Quarterly forecasts of energy supply and demand for 1995 and 1996 are published in the Short-Term Energy Outlook (February 1995). Forecast tables for the five cases examined in the AEO95 are provided in Appendixes A through C. Appendix A gives historical data and forecasts for selected years from 1992 through 2010 for the reference case. Appendix B presents two additional cases, which assume higher and lower economic growth than the reference case. Appendix C presents two cases that assume higher and lower world oil prices. Appendix D presents a summary of the forecasts in units of oil equivalence. Appendix E presents a summary of household energy expenditures. Appendix F provides detailed comparisons of the AEO95 forecasts with those of other organizations. Appendix G briefly describes NEMS and the major AEO95 forecast assumptions. Appendix H presents a stand-alone high electricity demand case. Appendix 1 provides a table of energy conversion factors and a table of metric conversion factors. 89 figs., 23 tabs.

  18. Short-Term Energy Outlook: Quarterly projections. Fourth quarter 1993

    SciTech Connect (OSTI)

    Not Available

    1993-11-05T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the fourth quarter of 1993 through the fourth quarter of 1994. Values for the third quarter of 1993, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications.

  19. International energy outlook 1996

    SciTech Connect (OSTI)

    NONE

    1996-05-01T23:59:59.000Z

    This International Energy Outlook presents historical data from 1970 to 1993 and EIA`s projections of energy consumption and carbon emissions through 2015 for 6 country groups. Prospects for individual fuels are discussed. Summary tables of the IEO96 world energy consumption, oil production, and carbon emissions projections are provided in Appendix A. The reference case projections of total foreign energy consumption and of natural gas, coal, and renewable energy were prepared using EIA`s World Energy Projection System (WEPS) model. Reference case projections of foreign oil production and consumption were prepared using the International Energy Module of the National Energy Modeling System (NEMS). Nuclear consumption projections were derived from the International Nuclear Model, PC Version (PC-INM). Alternatively, nuclear capacity projections were developed using two methods: the lower reference case projections were based on analysts` knowledge of the nuclear programs in different countries; the upper reference case was generated by the World Integrated Nuclear Evaluation System (WINES)--a demand-driven model. In addition, the NEMS Coal Export Submodule (CES) was used to derive flows in international coal trade. As noted above, foreign projections of electricity demand are now projected as part of the WEPS. 64 figs., 62 tabs.

  20. Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

    2012-09-01T23:59:59.000Z

    Historically, a number of wind energy integration studies have investigated the value of using day-ahead wind power forecasts for grid operational decisions. These studies have shown that there could be large cost savings gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter-term (0 to 6-hour-ahead) wind power forecasts. In 2010, the Department of Energy and National Oceanic and Atmospheric Administration partnered to fund improvements in short-term wind forecasts and to determine the economic value of these improvements to grid operators, hereafter referred to as the Wind Forecasting Improvement Project (WFIP). In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined, then the economic results of a production cost model simulation are analyzed.

  1. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    Downward surface solar radiation  data released at 12 UTC forecast shortwave radiation with data obtained from the radiation:   A statistical approach using satellite data.   

  2. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    2.1.2 European Solar Radiation Atlas (ESRA)2.4 Evaluation of Solar Forecasting . . . . . . . . .2.4.1 Solar Variability . . . . . . . . . . . . .

  3. Annual energy outlook 1994: With projections to 2010

    SciTech Connect (OSTI)

    Not Available

    1994-01-01T23:59:59.000Z

    The Annual Energy Outlook 1994 (AEO94) presents the midterm energy forecasts of the Energy Information Administration (EIA). This year`s report presents projects and analyses of energy supply, demand, and prices through 2010, based for the first time on results from the National Energy Modeling System (NEMS). NEMS is the latest in a series of computer-based energy modeling systems used over the past 2 decades by EIA and its predecessor organization, the Federal Energy Administration, to analyze and forecast energy consumption and supply in the midterm period (about 20 years). Quarterly forecasts of energy supply and demand for 1994 and 1995 are published in the Short-Term Energy Outlook (February 1994). Forecast tables for 2000, 2005, and 2010 for each of the five scenarios examined in the AEO94 are provided in Appendices A through E. The five scenarios include a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices. Appendix F provides detailed comparisons of the AEO94 forecasts with those of other organizations. Appendix G briefly described the NEMS and the major AEO94 forecast assumptions. Appendix H summarizes the key results for the five scenarios.

  4. International energy outlook 2005

    SciTech Connect (OSTI)

    NONE

    2005-07-01T23:59:59.000Z

    This report presents international energy projections through 2025, prepared by the Energy Information Administration. The outlooks for major energy fuels are discussed, along with electricity, transportation, and environmental issues. After a chapter entitled 'Highlights', the report begins with a review of world energy and an economic outlook. The IEO2005 projections cover a 24 year period. The next chapter is on world oil markets. Natural gas and coal reserves and resources, consumption and trade discussed. The chapter on electricity deals with primary fuel use for electricity generation, and regional developments. The final section is entitled 'Energy-related greenhouse gas emissions'.

  5. Short-term energy outlook. Quarterly projections, first quarter 1995

    SciTech Connect (OSTI)

    Not Available

    1995-02-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). The forecast period for this issue of the Outlook extends from the first quarter of 1995 through the fourth quarter of 1996. Values for the fourth quarter of 1994, however, are preliminary EIA estimates or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data, compiled into the first quarter 1995 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service. The cases are produced using the Short-Term Integrated Forecasting System (STIFS). The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. The EIA model is available on computer tape from the National Technical Information Service.

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

    SciTech Connect (OSTI)

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

    2005-02-09T23:59:59.000Z

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

  7. NatioNal aNd Global Forecasts West VirGiNia ProFiles aNd Forecasts

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    · NatioNal aNd Global Forecasts · West VirGiNia ProFiles aNd Forecasts · eNerGy · Healt Global Insight, paid for by the West Virginia Department of Revenue. 2013 WEST VIRGINIA ECONOMIC OUTLOOKWest Virginia Economic Outlook 2013 is published by: Bureau of Business & Economic Research West

  8. Weather Forecast Data an Important Input into Building Management Systems 

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01T23:59:59.000Z

    GEPS 21 members ? Provides probabilistic forecasts ? Can give useful outlooks for longer term weather forecasts ? Scribe matrix from GDPS ? includes UMOS post processed model data ? Variables like Temperature, humidity post processed by UMOS ? See...://collaboration.cmc.ec.gc.ca/cmc/cmoi/cmc-prob-products/ ? Link to experimental 3-day outlook of REPS quilts ? http://collaboration.cmc.ec.gc.ca/cmc/cmoi/cmc-prob-products.reps Users can also make their own products from ensemble forecast data? Sample ascii matrix of 2m temperature could be fed...

  9. Missouri Agriculture Outlook Conference

    E-Print Network [OSTI]

    Noble, James S.

    Missouri Agriculture Outlook Conference Conference Information Join us to discuss the drivers of Missouri agricultural and bio-fuels markets and participate in a special review of international policy implications for Missouri agriculture. Registration Deadline To guarantee space availability, please register

  10. Annual Energy Outlook 2012

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

    A n n u a l E n e r g y Ou t l o o k 2 0 1 2 For further information . . . The Annual Energy Outlook 2012 was prepared by the U.S. Energy Information Administration (EIA), under...

  11. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    and validation.   Solar Energy.   73:5, 307? Perez, R. , irradiance forecasts for solar energy applications based on using satellite data.   Solar Energy 67:1?3, 139?150.  

  12. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

    transport and  numerical weather modeling.   J.  Applied cross correlations.    Weather and Forecasting, 8:4, 401?of radiation for numerical weather prediction and climate 

  13. International energy outlook 2006

    SciTech Connect (OSTI)

    NONE

    2006-06-15T23:59:59.000Z

    This report presents international energy projections through 2030, prepared by the Energy Information Administration. After a chapter entitled 'Highlights', the report begins with a review of world energy and economic outlook, followed by energy consumption by end-use sector. The next chapter is on world oil markets. Natural gas, world coal market and electricity consumption and supply are then discussed. The final chapter covers energy-related carbon dioxide emissions.

  14. EIA - Annual Energy Outlook 2014 Early Release

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

    Annual Energy Outlook 2013 LED Light emitting diode AEO2014 Annual Energy Outlook 2014 LNG Liquefied natural gas ATRA American Taxpayer Relief Act of 2012 LPG Liquefied petroleum...

  15. Short-term energy outlook: Quarterly projections, second quarter 1997

    SciTech Connect (OSTI)

    NONE

    1997-04-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly short-term energy supply, demand, and price projections for publication in January, April, July, and October in the Outlook. The forecast period for this issue of the Outlook extends from the second quarter of 1997 through the fourth quarter of 1998. Values for the first quarter of 1997, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the second quarter 1997 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the Short-Term Integrated Forecasting System (STIFS). 34 figs., 19 tabs.

  16. Short-term energy outlook. Quarterly projections, first quarter 1996

    SciTech Connect (OSTI)

    NONE

    1996-02-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Outlook. The forecast period for this issue of the Outlook extends from the first quarter of 1996 through the fourth quarter of 1997. Values for the fourth quarter of 1995, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data, compiled into the first quarter 1996 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service. The cases are produced using the Short-Term Integrated Forecasting System (STIFS). The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook.

  17. Annual Energy Outlook Retrospective Review

    Reports and Publications (EIA)

    2015-01-01T23:59:59.000Z

    The Annual Energy Outlook Retrospective Review provides a yearly comparison between realized energy outcomes and the Reference case projections included in previous Annual Energy Outlooks (AEO) beginning with 1982. This edition of the report adds the AEO 2012 projections and updates the historical data to incorporate the latest data revisions.

  18. Short-term energy outlook, quarterly projections, first quarter 1998

    SciTech Connect (OSTI)

    NONE

    1998-01-01T23:59:59.000Z

    The forecast period for this issue of the Outlook extends from the first quarter of 1998 through the fourth quarter of 1999. Values for the fourth quarter of 1997, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the first quarter 1998 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are adjusted by EIA to reflect EIA assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the STIFS model. 24 figs., 19 tabs.

  19. Short-term energy outlook: Quarterly projections, fourth quarter 1997

    SciTech Connect (OSTI)

    NONE

    1997-10-14T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly short-term energy supply, demand, and price projections for printed publication in January, April, July, and October in the Short-Term Energy Outlook. The details of these projections, as well as monthly updates on or about the 6th of each interim month, are available on the internet at: www.eia.doe.gov/emeu/steo/pub/contents.html. The forecast period for this issue of the Outlook extends from the fourth quarter of 1997 through the fourth quarter of 1998. Values for the fourth quarter of 1997, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the fourth quarter 1997 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. 19 tabs.

  20. Short-term energy outlook. Quarterly projections, third quarter 1996

    SciTech Connect (OSTI)

    NONE

    1996-07-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in January, April, July, and October in the Outlook. The forecast period for this issue of the Outlook extends from the third quarter of 1996 through the fourth quarter of 1997. Values for the second quarter of 1996, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data, compiled in the third quarter 1996 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service.

  1. International energy outlook 1998

    SciTech Connect (OSTI)

    NONE

    1998-04-01T23:59:59.000Z

    The International Energy Outlook 1998 (IEO98) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2020. Projections in IEO98 are displaced according to six basic country groupings. The industrialized region includes projections for four individual countries -- the United States, Canada, Mexico, and Japan -- along with the subgroups Western Europe and Australasia (defined as Australia, New Zealand, and the US Territories). The developing countries are represented by four separate regional subgroups: developing Asia, Africa, Middle East, and Central and South America. China and India are represented in developing Asia. New to this year`s report, country-level projections are provided for Brazil -- which is represented in Central and South America. Eastern Europe and the former Soviet Union (EE/FSU) are considered as a separate country grouping. The report begins with a review of world trends in energy demand. Regional consumption projections for oil, natural gas, coal, nuclear power, and renewable energy (hydroelectricity, geothermal, wind, solar, and other renewables) are presented in five fuel chapters, with a review of the current status of each fuel on a worldwide basis. Summary tables of the IEO98 projections for world energy consumption, carbon emissions, oil production, and nuclear power generating capacity are provided in Appendix A. 88 figs., 77 tabs.

  2. International energy outlook 1999

    SciTech Connect (OSTI)

    NONE

    1999-03-01T23:59:59.000Z

    This report presents international energy projections through 2020, prepared by the Energy Information Administration. The outlooks for major energy fuels are discussed, along with electricity, transportation, and environmental issues. The report begins with a review of world trends in energy demand. The historical time frame begins with data from 1970 and extends to 1996, providing readers with a 26-year historical view of energy demand. The IEO99 projections covers a 24-year period. The next part of the report is organized by energy source. Regional consumption projections for oil, natural gas, coal, nuclear power, and renewable energy (hydroelectricity, geothermal, wind, solar, and other renewables) are presented in the five fuel chapters, along with a review of the current status of each fuel on a worldwide basis. The third part of the report looks at energy consumption in the end-use sectors, beginning with a chapter on energy use for electricity generation. New to this year`s outlook are chapters on energy use in the transportation sector and on environmental issues related to energy consumption. 104 figs., 87 tabs.

  3. The Budget Outlook and Options for Fiscal Policy Alan J. Auerbach

    E-Print Network [OSTI]

    Sadoulet, Elisabeth

    The Budget Outlook and Options for Fiscal Policy Alan J. Auerbach William G. Gale Peter R. Orszag;ABSTRACT This paper examines the federal budget outlook and evaluates alternative fiscal policy choices. Official projections of the federal budget surplus have declined dramatically in the past year. Adjusting

  4. Use of Data Denial Experiments to Evaluate ESA Forecast Sensitivity Patterns

    SciTech Connect (OSTI)

    Zack, J; Natenberg, E J; Knowe, G V; Manobianco, J; Waight, K; Hanley, D; Kamath, C

    2011-09-13T23:59:59.000Z

    The overall goal of this multi-phased research project known as WindSENSE is to develop an observation system deployment strategy that would improve wind power generation forecasts. The objective of the deployment strategy is to produce the maximum benefit for 1- to 6-hour ahead forecasts of wind speed at hub-height ({approx}80 m). In this phase of the project the focus is on the Mid-Columbia Basin region which encompasses the Bonneville Power Administration (BPA) wind generation area shown in Figure 1 that includes Klondike, Stateline, and Hopkins Ridge wind plants. The Ensemble Sensitivity Analysis (ESA) approach uses data generated by a set (ensemble) of perturbed numerical weather prediction (NWP) simulations for a sample time period to statistically diagnose the sensitivity of a specified forecast variable (metric) for a target location to parameters at other locations and prior times referred to as the initial condition (IC) or state variables. The ESA approach was tested on the large-scale atmospheric prediction problem by Ancell and Hakim 2007 and Torn and Hakim 2008. ESA was adapted and applied at the mesoscale by Zack et al. (2010a, b, and c) to the Tehachapi Pass, CA (warm and cools seasons) and Mid-Colombia Basin (warm season only) wind generation regions. In order to apply the ESA approach at the resolution needed at the mesoscale, Zack et al. (2010a, b, and c) developed the Multiple Observation Optimization Algorithm (MOOA). MOOA uses a multivariate regression on a few select IC parameters at one location to determine the incremental improvement of measuring multiple variables (representative of the IC parameters) at various locations. MOOA also determines how much information from each IC parameter contributes to the change in the metric variable at the target location. The Zack et al. studies (2010a, b, and c), demonstrated that forecast sensitivity can be characterized by well-defined, localized patterns for a number of IC variables such as 80-m wind speed and vertical temperature difference. Ideally, the data assimilation scheme used in the experiments would have been based upon an ensemble Kalman filter (EnKF) that was similar to the ESA method used to diagnose the Mid-Colombia Basin sensitivity patterns in the previous studies. However, the use of an EnKF system at high resolution is impractical because of the very high computational cost. Thus, it was decided to use the three-dimensional variational analysis data assimilation that is less computationally intensive and more economically practical for generating operational forecasts. There are two tasks in the current project effort designed to validate the ESA observational system deployment approach in order to move closer to the overall goal: (1) Perform an Observing System Experiment (OSE) using a data denial approach which is the focus of this task and report; and (2) Conduct a set of Observing System Simulation Experiments (OSSE) for the Mid-Colombia basin region. The results of this task are presented in a separate report. The objective of the OSE task involves validating the ESA-MOOA results from the previous sensitivity studies for the Mid-Columbia Basin by testing the impact of existing meteorological tower measurements on the 0- to 6-hour ahead 80-m wind forecasts at the target locations. The testing of the ESA-MOOA method used a combination of data assimilation techniques and data denial experiments to accomplish the task objective.

  5. Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications

    E-Print Network [OSTI]

    Niyogi, Dev

    (GEM) for Mesoscale Weather Forecasting Applications DEV NIYOGI Department of Agronomy, and Department form 13 May 2008) ABSTRACT Current land surface schemes used for mesoscale weather forecast models use model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM

  6. Short-Term Energy Outlook

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

    Chart Gallery for April 2015 Short-Term Energy Outlook U.S. Energy Information Administration Independent Statistics & Analysis 0 20 40 60 80 100 120 140 160 180 200 220 Jan 2014...

  7. Outlook for Industrial Energy Benchmarking 

    E-Print Network [OSTI]

    Hartley, Z.

    2000-01-01T23:59:59.000Z

    OUTLOOK FOR INDUSTRIAL ENERGY BENCHMARKING Zoe Hartley Environmental Protection Specialist U.S. Environmental Protection Agency Washington, DC ABSTRACT The U.S. Environmental Protection Agency is exploring options to sponsor an ~d~ ~~gy...

  8. Short-term energy outlook. Quarterly projections, 2nd quarter 1994

    SciTech Connect (OSTI)

    Not Available

    1994-05-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. The forecast period for this issue of the Outlook extends from the second quarter of 1994 through the fourth quarter of 1995. Values for the first quarter of 1994, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available. The historical energy data, compiled into the second quarter 1994 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service. The cases are produced using the STIFS. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. The EIA model is available on computer tape from the National Technical Information Service.

  9. LED Watch: The Outlook for OLEDs

    Broader source: Energy.gov [DOE]

    December 2014 LED Watch: The Outlook for OLEDs James Brodrick, U.S. Department of Energy LD+A Magazine

  10. GLOBAL BIOFUELS OUTLOOK MAELLE SOARES PINTO

    E-Print Network [OSTI]

    GLOBAL BIOFUELS OUTLOOK 2010-2020 MAELLE SOARES PINTO DIRECTOR BIOFUELS EUROPE & AFRICA WORLD BIOFUELS MARKETS, ROTTERDAM MARCH 23, 2011 #12;Presentation Overview · Global Outlook ­ Biofuels Mandates in 2010 ­ Total Biofuels Supply and Demand ­ Regional Supply and Demand Outlook to 2020 ­ Biofuels

  11. World nuclear outlook 1995

    SciTech Connect (OSTI)

    NONE

    1995-09-29T23:59:59.000Z

    As part of the EIA program to provide energy information, this analysis report presents the current status and projections through 2015 of nuclear capacity, generation, and fuel cycle requirements for all countries in the world using nuclear power to generate electricity for commercial use. It also contains information and forecasts of developments in the uranium market. Long-term projections of US nuclear capacity, generation, and spent fuel discharges for two different scenarios through 2040 are developed for the Department of Energy`s Office of Civilian Radioactive Waste Management (OCRWM). In turn, the OCRWM provides partial funding for preparation of this report. The projections of uranium requirements are provided to the Organization for Economic Cooperation and Development (OECD) for preparation of the Nuclear Energy Agency/OECD report, Summary of Nuclear Power and Fuel Cycle Data in OECD Member Countries.

  12. World nuclear outlook 1994

    SciTech Connect (OSTI)

    NONE

    1994-12-01T23:59:59.000Z

    As part of the EIA program to provide energy information, this analysis report presents the current status and projections through 2010 of nuclear capacity, generation, and fuel cycle requirements for all countries in the world using nuclear power to generate electricity for commercial use. It also contains information and forecasts of developments in the uranium market. Long-term projections of US nuclear capacity, generation, and spent fuel discharges for three different scenarios through 2040 are developed for the Department of Energy`s Office of Civilian Radioactive Waste Management (OCRWM). In turn, the OCRWM provides partial funding for preparation of this report. The projections of uranium requirements are provided to the Organization for Economic Cooperation and Development (OECD) for preparation of the Nuclear Energy Agency/OECD report, Summary of Nuclear Power and Fuel Cycle Data in OECD Member Countries.

  13. Annual energy outlook 1999, with projections to 2020

    SciTech Connect (OSTI)

    NONE

    1998-12-01T23:59:59.000Z

    The Annual Energy Outlook 1999 (AEO99) 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 AEO99 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 current energy issues--the economic decline in East Asia, growth in demand for natural gas, vehicle emissions standards, competitive electricity pricing, renewable portfolio standards, and carbon emissions. It is followed by the analysis of energy market trends. The analysis in AEO99 focuses primarily on a reference case and four other cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. Forecast tables for these cases are provided in Appendixes A through C. Appendixes D and E present a summary of the reference case forecasts in units of oil equivalence and household energy expenditures. The AEO99 projections are based on Federal, State, and local laws and regulations in effect on July 1, 1998. Pending legislation and sections of existing legislation for which funds have not been appropriated are not reflected in the forecasts. Historical data used for the AEOI99 projections were the most current available as of July 31, 1998, when most 1997 data but only partial 1998 data were available.

  14. CSUF Economic Outlook and Forecasts Midyear Update, April 2011

    E-Print Network [OSTI]

    de Lijser, Peter

    and government support) to fundamental forces (business and consumption spending) has reached a more advanced, (4) sustained elevated oil prices, and (5) financial shocks from the European sovereign debt crisis, reflecting continued but moderate expansion. Consumption Spending. Real personal consumption expenditure fell

  15. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    NONE

    1998-07-01T23:59:59.000Z

    Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

  16. Outlook: The Next Twenty Years

    SciTech Connect (OSTI)

    Murayama, Hitoshi

    2003-12-07T23:59:59.000Z

    I present an outlook for the next twenty years in particle physics. I start with the big questions in our field, broken down into four categories: horizontal, vertical, heaven, and hell. Then I discuss how we attack the bigquestions in each category during the next twenty years. I argue for a synergy between many different approaches taken in our field.

  17. The outlook for natural gas

    SciTech Connect (OSTI)

    NONE

    1993-12-31T23:59:59.000Z

    The proceedings of the Institute of Gas Technology`s Houston Conference on the Outlook for Natural Gas held October 5, 1993 are presented. A separate abstract was prepared for each paper for inclusion in the Energy Science and Technology Database.

  18. The solar electric power outlook

    SciTech Connect (OSTI)

    Kemp, J.W.

    1995-12-31T23:59:59.000Z

    The outlook for solar electric power plants is discussed. The following topics are discussed: Amoco/Envon solar vision, multi-megawatt solar power projects, global carbon dioxide emission estimates, pollution and electric power generation, social costs of pollution economies of scale, thin-film power module, rooftop market strategy, regulatory issues regarding rooftop systems, and where do we go from here?

  19. Hanford and the tri-cities economy: Review and outlook, March 1989

    SciTech Connect (OSTI)

    Scott, M.J.; Belzer, D.B.; March, S.J.; Beck, D.M.; Schultz, R.W.; Harkreader, S.A.

    1989-03-01T23:59:59.000Z

    The economy of the Tri-Cities, Washington area (primarily, Benton and Franklin Counties) is in transition due to major changes in two Department of Energy programs at Hanford---the abrupt ending of the Basalt Waste Isolation Project (BWIP) in December 1987 and the placing of the N Reactor in ''cold standby'' status in February 1988. This report reviews the economic situation in the Tri-Cities during 1988 and presents forecasts for key economic indicators for 1989. This report will be updated about every six months to review the changes in the area economy and forecast the near-term outlook. 6 figs., 33 tabs.

  20. China's Energy and Carbon Emissions Outlook to 2050

    E-Print Network [OSTI]

    Zhou, Nan

    2011-01-01T23:59:59.000Z

    Agency (IEA). 2009. World Energy Outlook 2009. Paris: OECDlines in the 2009 World Energy Outlook 450 ppm scenario.Agency (IEA)’s 2009 World Energy Outlook 450 ppm scenario.

  1. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

    Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

    2011-04-01T23:59:59.000Z

    This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

  2. Annual Energy Outlook 2015 - Appendix A

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

    2 Reference case Table A10. Electricity trade (billion kilowatthours, unless otherwise noted) Energy Information Administration Annual Energy Outlook 2015 Table A10. Electricity...

  3. Energy Information Administration / Annual Energy Outlook 2011

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

    Administration Annual Energy Outlook 2011 1 7 Table A7. Transportation Sector Key Indicators and Delivered Energy Consumption (Continued) Key Indicators and Consumption...

  4. EIA - Annual Energy Outlook 2014 Early Release

    Gasoline and Diesel Fuel Update (EIA)

    gain perspective on how variations in key assumptions can lead to different outlooks for energy markets. To provide a basis against which alternative cases and policies can be...

  5. Annual Energy Outlook 2015 - Energy Information Administration

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

    gain perspective on how variations in key assumptions can lead to different outlooks for energy markets. In addition to the alternative cases prepared for AEO2015, EIA has...

  6. Annual Energy Outlook 2013 - Energy Information Administration

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

    Annual Energy Outlook 2013 Release Dates: April 15 - May 2, 2013 | Next Early Release Date: December 2013 (See release cycle changes) | correction | full report Overview Data...

  7. EIA - Annual Energy Outlook 2011 Early Release

    Gasoline and Diesel Fuel Update (EIA)

    January STEO Annual projections to 2040 International projections All projections reports Analysis & Projections Major Topics Most popular Annual Energy Outlook related...

  8. Annual energy outlook 1997 with projections to 2015

    SciTech Connect (OSTI)

    NONE

    1996-12-01T23:59:59.000Z

    The Annual Energy Outlook 1997 (AEO97) presents midterm forecasts of energy supply, demand, and prices through 2015 prepared by the Energy Information Administration (EIA). These projections are based on results of EIA`s National Energy Modeling System (NEMS). This report begins with a summary of the reference case, followed by a discussion of the legislative assumptions and evolving legislative and regulatory issues. ``Issues in Focus`` discusses emerging energy issues and other topics of particular interest. It is followed by the analysis of energy market trends. The analysis in AEO97 focuses primarily on a reference case and four other cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. Forecast tables for these cases are provided in Appendixes A through C. Appendixes D and E present summaries of the reference case forecasts in units of oil equivalence and household energy expenditures. Twenty-three other cases explore the impacts of varying key assumptions in NEMS--generally, technology penetration, with the major results shown in Appendix F. Appendix G briefly describes NEMS and the major AEO97 assumptions, with a summary table. 114 figs., 22 tabs.

  9. Annual energy outlook 2005 with projections to 2025

    SciTech Connect (OSTI)

    NONE

    2005-02-01T23:59:59.000Z

    The Annual Energy Outlook 2005 (AEO2005) presents midterm forecasts of energy supply, demand, and prices through 2025 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA's National Energy Modelling System (NEMS). The report begins with an 'Overview' summarizing the AEO2005 reference case. The next section, 'Legislation and Regulations', discusses evolving legislative and regulatory issues in the USA. Issues in Focus includes discussions on key energy market issues and examines their potential impacts. In particular, it includes a discussion of the world oil price assumptions used in the reference case and four alternative world oil price cases examined in AEO2005. 'Issues in Focus' is followed by 'Market Trends', which provides a summary of energy market trends in the AEO2005 forecast. The analysis in AEO2005 focuses primarily on a reference case, lower and higher economic growth cases, and four alternative oil price cases, a low world oil price case, an October oil futures case, and two high world oil price cases. Forecast tables for those cases are provided in Appendixes A through D. The major results for the alterative cases, which explore the impacts of varying key assumption in NEMS (such as rates of technology penetration), are summarized in Appendix E. Appendix F briefly describes NEMS and the alternative cases. 115 figs., 38 tabs., 8 apps.

  10. International energy outlook 1997 with projections to 2015

    SciTech Connect (OSTI)

    NONE

    1997-04-01T23:59:59.000Z

    The International Energy Outlook 1997 (IE097) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2015.

  11. Space-time forecasting and evaluation of wind speed with statistical tests for comparing accuracy of spatial predictions

    E-Print Network [OSTI]

    Hering, Amanda S.

    2010-10-12T23:59:59.000Z

    High-quality short-term forecasts of wind speed are vital to making wind power a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information...

  12. Soviet Union oil sector outlook grows bleaker still

    SciTech Connect (OSTI)

    Not Available

    1991-08-12T23:59:59.000Z

    This paper reports on the outlook for the U.S.S.R's oil sector which grows increasingly bleak and with it prospects for the Soviet economy. Plunging Soviet oil production and exports have analysts revising near term oil price outlooks, referring to the Soviet oil sector's self-destructing and Soviet oil production in a freefall. County NatWest, Washington, citing likely drops in Soviet oil production and exports (OGJ, Aug. 5, p. 16), has jumped its projected second half spot price for West Texas intermediate crude by about $2 to $22-23/bbl. Smith Barney, New York, forecasts WTI postings at $24-25/bbl this winter, largely because of seasonally strong world oil demand and the continued collapse in Soviet oil production. It estimates the call on oil from the Organization of Petroleum Exporting Countries at more than 25 million b/d in first quarter 1992. That would be the highest level of demand for OPEC oil since 1980, Smith Barney noted.

  13. World Biodiesel Markets The Outlook to 2010

    E-Print Network [OSTI]

    World Biodiesel Markets The Outlook to 2010 A special study from F.O. Licht and Agra CEAS This important new study provides a detailed analysis of the global biodiesel market and the outlook for growth, including the regulatory and trade framework, feedstock supply and price developments, biodiesel production

  14. Short-term energy outlook, October 1998. Quarterly projections, 1998 4. quarter

    SciTech Connect (OSTI)

    NONE

    1998-10-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares The Short-Term Energy Outlook (energy supply, demand, and price projections) monthly for distribution on the Internet at: www.eia.doe.gov/emeu/steo/pub/contents.html. In addition, printed versions of the report are available to subscribers in January, April, July and October. The forecast period for this issue of the Outlook extends from October 1998 through December 1999. Values for third quarter of 1998 data, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the October 1998 version of the Short-term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding.

  15. Short-term energy outlook. Volume 2. Methodology

    SciTech Connect (OSTI)

    Not Available

    1982-05-01T23:59:59.000Z

    This volume updates models and forecasting methodologies used and presents information on new developments since November 1981. Chapter discusses the changes in forecasting methodology for motor gasoline demand, electricity sales, coking coal, and other petroleum products. Coefficient estimates, summary statistics, and data sources for many of the short-term energy models are provided. Chapter 3 evaluates previous short-term forecasts for the macroeconomic variables, total energy, petroleum supply and demand, coal consumption, natural gas, and electricity fuel shares. Chapter 4 reviews the relationship of total US energy consumption to economic activity between 1960 and 1981.

  16. Annual outlook for US electric power, 1986

    SciTech Connect (OSTI)

    Not Available

    1986-04-24T23:59:59.000Z

    This document includes summary information on the ownership structure of the US electric utility industry, a description of electric utility regulation, and identification of selected factors likely to affect US electricity markets from 1985 through 1995. This Outlook expands upon projections first presented in the Annual Energy Outlook 1985, offering additional discussion of projected US electricity markets and regional detail. It should be recognized that work on the Annual Energy Outlook 1985 had been completed prior to the sharp reductions in world oil prices experienced early in 1986.

  17. Annual energy outlook 1998 with projections to 2020

    SciTech Connect (OSTI)

    NONE

    1997-12-01T23:59:59.000Z

    The Annual Energy Outlook 1998 (AEO98) is the first AEO with projections to 2020. Key issues for the forecast extension are trends in energy efficiency improvements, the effects of increasing production and productivity improvements on energy prices, and the reduction in nuclear generating capacity. Projections in AEO98 also reflect a greater shift to electricity market restructuring. Restructuring is addressed through several changes that are assumed to occur in the industry, including a shorter capital recovery period for capacity expansion decisions and a revised financial structure that features a higher cost of capital as the result of higher competitive risk. Both assumptions tend to favor less capital-intensive generation technologies, such as natural gas, over coal or baseload renewable technologies. The forecasts include specific restructuring plans in those regions that have announced plans. California, New York, and New England are assumed to begin competitive pricing in 1998. The provisions of the California legislation for stranded cost recovery and price caps are incorporated. In New York and New England, stranded cost recovery is assumed to be phased out by 2008.

  18. 2015 NASEO Energy Policy Outlook Conference

    Broader source: Energy.gov [DOE]

    BETO Director Jonathan Male will be speaking at the National Association of State Energy Organization Energy Policy Outlook Conference, which will be taking place from February 3–6 at the Washington, D.C.

  19. Energy Information Administration / Annual Energy Outlook 2011

    Gasoline and Diesel Fuel Update (EIA)

    23.60 28.73 28.99 28.68 27.92 27.22 0.6% Energy Information Administration Annual Energy Outlook 2011 1 4 Table A6. Industrial Sector Key Indicators and Consumption...

  20. EIA - Annual Energy Outlook 2012 Early Release

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

    Report Number: DOEEIA-0383ER(2012) This release is an abridged version of the Annual Energy Outlook that highlights changes in the AEO Reference case projections for key energy...

  1. Annual Energy Outlook 2015 - Appendix A

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

    8 Reference case Table A14. Oil and gas supply Energy Information Administration Annual Energy Outlook 2015 Table A14. Oil and gas supply Production and supply Reference case...

  2. Annual Energy Outlook 2015 - Appendix A

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

    Outlook 2015 Table A17. Renewable energy consumption by sector and source (quadrillion Btu per year) Sector and source Reference case Annual growth 2013-2040 (percent) 2012 2013...

  3. Agricultural Outlook Forum | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataEnergyDepartment ofATVMAgricultural Outlook Forum Agricultural Outlook

  4. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    and forecasting of solar radiation data: a review,”forecasting of solar- radiation data,” Solar Energy, vol.sequences of global solar radiation data for isolated sites:

  5. Lead -- supply/demand outlook

    SciTech Connect (OSTI)

    Schnull, T. [Noranda, Inc., Toronto, Ontario (Canada)

    1999-03-01T23:59:59.000Z

    As Japan goes--so goes the world. That was the title of a recent lead article in The Economist that soberly discussed the potential of much more severe global economic problems occurring, if rapid and coordinated efforts were not made to stabilize the economic situation in Asia in general, and in Japan in particular. During the first 6 months of last year, commodity markets reacted violently to the spreading economic problems in Asia. More recent currency and financial problems in Russia have exacerbated an already unpleasant situation. One commodity after another--including oil, many of the agricultural commodities, and each of the base metals--have dropped sharply in price. Many are now trading at multiyear lows. Until there is an overall improvement in the outlook for these regions, sentiment will likely continue to be negative, and metals prices will remain under pressure. That being said, lead has maintained its value better than many other commodities during these difficult times, finding support in relatively strong fundamentals. The author takes a closer look at those supply and demand fundamentals, beginning with consumption.

  6. The U.S. Oil and Natural Gas Production Outlook

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

    Oil and Natural Gas Production Outlook for PRG Energy Outlook Conference September 22, 2014 by Adam Sieminski, Administrator 0 20 40 60 80 100 120 1980 1985 1990 1995 2000 2005...

  7. DOE/EIA-0383(2009) Annual Energy Outlook 2009

    E-Print Network [OSTI]

    Laughlin, Robert B.

    2009-01-01T23:59:59.000Z

    DOE/EIA-0383(2009) March 2009 Annual Energy Outlook 2009 With Projections to 2030 #12;For Further Information . . . The Annual Energy Outlook 2009 was prepared by the Energy Information Administration, under for the Annual Energy Outlook 2009 during 2009. Other contributors to the report include Justine Barden, Joseph

  8. OECD Internet Economy Outlook 2012 Access the complete publication at

    E-Print Network [OSTI]

    Weske, Mathias

    From: OECD Internet Economy Outlook 2012 Access the complete publication at: http://dx.doi.org/10 and development", in OECD Internet Economy Outlook 2012, OECD Publishing. http://dx.doi.org/10 of international law. #12;OECD Internet Economy Outlook © OECD 2012 63 Chapter 2 Internet trends and development

  9. Annual energy outlook 2006 with projections to 2030

    SciTech Connect (OSTI)

    NONE

    2006-02-15T23:59:59.000Z

    The Annual Energy Outlook 2006 (AEO2006), prepared by the Energy Information Administration (EIA), presents long-term forecasts of energy supply, demand, and prices through 2030. The projections are based on results from EIA's National Energy Modeling System (NEMS). The report begins with an 'Overview' summarizing the AEO2006 reference case and comparing it with the AEO2005 reference case. The next section, 'Legislation and Regulations', discusses evolving legislation and regulatory issues, including recently enacted legislation and regulation, such as the Energy Policy Act of 2005, and some that are proposed. 'Issues in Focus' includes a discussion of the basis of EIA's substantial revision of the world oil price trend used in the projections. Other topics examined include: energy technologies on the cusp of being introduced; mercury emissions control technologies; and U.S. greenhouse gas intensity. 'Issues in Focus' is followed by 'Energy Market Trends', which provides a summary of the AEO2006 projections for energy markets. The analysis in AEO2006 focuses primarily on a reference case, lower and higher economic growth cases, and lower and higher energy price cases. In addition, more than 30 alternative cases are included in AEO2006. Complete tables for the five primary cases are provided in Appendixes A through C. Major results from many of the alternative cases are provided in Appendix D. Appendix E briefly describes NEMS and the alternatives cases. 112 figs., 25 tabs., 7 apps.

  10. SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK DRAFTSTAFFREPORT May ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION B. B assessment of the capability of the physical electricity system to provide power to meet electricity demand

  11. Configure Outlook 2010 with Exchange Server

    E-Print Network [OSTI]

    Qiu, Weigang

    Configure Outlook 2010 with Exchange Server #12;1. Navigate to the Windows Start Menu (or press. #12;14. E-mail server settings will now auto configure. 15. Once the Auto Account Setup is configured server settings or additional server types. 3. Click the Next > button. #12;4. Select Microsoft Exchange

  12. Supplemental Tables to the Annual Energy Outlook

    Reports and Publications (EIA)

    2014-01-01T23:59:59.000Z

    The Annual Energy Outlook (AEO) Supplemental tables were generated for the reference case of the AEO using the National Energy Modeling System, a computer-based model which produces annual projections of energy markets. Most of the tables were not published in the AEO, but contain regional and other more detailed projections underlying the AEO projections.

  13. Energy Information Administration / Annual Energy Outlook 2011

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

    r) 9.8 9.8 9.0 8.9 8.9 9.0 9.2 -0.2% Energy Information Administration Annual Energy Outlook 2011 2 Table A1. Total Energy Supply and Disposition Summary (Continued)...

  14. Energy Information Administration / Annual Energy Outlook 2011

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

    . 0.03 0.03 0.03 0.03 0.02 0.02 0.02 -1.4% Energy Information Administration Annual Energy Outlook 2011 1 0 Table A4. Residential Sector Key Indicators and Consumption...

  15. Energy Information Administration / Annual Energy Outlook 2011

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

    . 8.60 8.49 8.98 9.48 9.93 10.47 11.03 1.0% Energy Information Administration Annual Energy Outlook 2011 1 2 Table A5. Commercial Sector Key Indicators and Consumption...

  16. Neutrino oscillations: present status and outlook

    E-Print Network [OSTI]

    Thomas Schwetz

    2007-10-26T23:59:59.000Z

    I summarize the status of three-flavour neutrino oscillations with date of Oct. 2007, and provide an outlook for the developments to be expected in the near future. Furthermore, I discuss the status of sterile neutrino oscillation interpretations of the LSND anomaly in the light of recent MiniBooNE results, and comment on implications for the future neutrino oscillation program.

  17. Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model (Released in the STEO March 1998)

    Reports and Publications (EIA)

    1998-01-01T23:59:59.000Z

    The blending of oxygenates, such as fuel ethanol and methyl tertiary butyl ether (MTBE), into motor gasoline has increased dramatically in the last few years because of the oxygenated and reformulated gasoline programs. Because of the significant role oxygenates now have in petroleum product markets, the Short-Term Integrated Forecasting System (STIFS) was revised to include supply and demand balances for fuel ethanol and MTBE. The STIFS model is used for producing forecasts in the Short-Term Energy Outlook. A review of the historical data sources and forecasting methodology for oxygenate production, imports, inventories, and demand is presented in this report.

  18. Evaluating the Performance of Planetary Boundary Layer and Cloud Microphysical Parameterization Schemes in Convection-Permitting Ensemble Forecasts using

    E-Print Network [OSTI]

    Xue, Ming

    uncertainty in how to include various processes (e.g., drop breakup and ice-phase categories 1 Evaluating the Performance of Planetary Boundary Layer and Cloud Microphysical Parameterization In this study, the ability of several cloud microphysical and planetary boundary layer parameterization schemes

  19. FAA (federal Aviation Administration) aviation forecasts - fiscal years 1983-1994

    SciTech Connect (OSTI)

    Not Available

    1983-02-01T23:59:59.000Z

    This report contains the Fiscal Years 1983-1994 Federal Aviation Administration (FAA) forecasts of aviation activity at FAA facilities. These include airports with FAA control towers, air route traffic control centers, and flight service stations. Detailed forecasts were made for the four major users of the national aviation system: air carriers, air taxi/commuters, general aviation and the military. The forecasts have been prepared to meet the budget and planning needs of the constituent units of the FAA and to provide information that can be used by state and local authorities, by the aviation industry and the general public. The overall outlook for the forecast period is for moderate economic growth, relatively stable real fuel prices, and decreasing inflation. Based upon these assumptions, aviation activity is forecast to increase by Fiscal Year 1994 by 97 percent at towered airports, 50 percent at air route traffic control centers, and 54 percent in flight services performed. Hours flown by general aviation is forecast to increase 56 percent and helicopter hours flown 80 percent. Scheduled domestic revenue passenger miles (RPM's) are forecast to increase 81 percent, with scheduled international RPM's forecast to increase by 80 percent and commuter RPM's forecast to increase by 220 percent.

  20. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect (OSTI)

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04T23:59:59.000Z

    On December 14, 2009, the reference-case projections from Annual Energy Outlook 2010 were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in itigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings.

  1. Comparative Analysis of Modeling Studies on China's Future Energy and Emissions Outlook

    E-Print Network [OSTI]

    Zheng, Nina

    2010-01-01T23:59:59.000Z

    Agency (IEA). 2009. World Energy Outlook 2009. Paris: OECDsection of the IEA World Energy Outlook 2009. At the sameEnergy Agency (IEA)’s World Energy Outlook (WEO) 2009, which

  2. A critical evaluation of the upper ocean heat budget in the Climate Forecast System Reanalysis data for the south central equatorial Pacific

    SciTech Connect (OSTI)

    Liu H.; Lin W.; Liu, X.; Zhang, M.

    2011-08-26T23:59:59.000Z

    Coupled ocean-atmospheric models suffer from the common bias of a spurious rain belt south of the central equatorial Pacific throughout the year. Observational constraints on key processes responsible for this bias are scarce. The recently available reanalysis from a coupled model system for the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) data is a potential benchmark for climate models in this region. Its suitability for model evaluation and validation, however, needs to be established. This paper examines the mixed layer heat budget and the ocean surface currents - key factors for the sea surface temperature control in the double Inter-Tropical Convergence Zone in the central Pacific - from 5{sup o}S to 10{sup o}S and 170{sup o}E to 150{sup o}W. Two independent approaches are used. The first approach is through comparison of CFSR data with collocated station observations from field experiments; the second is through the residual analysis of the heat budget of the mixed layer. We show that the CFSR overestimates the net surface flux in this region by 23 W m{sup -2}. The overestimated net surface flux is mainly due to an even larger overestimation of shortwave radiation by 44 W m{sup -2}, which is compensated by a surface latent heat flux overestimated by 14 W m{sup -2}. However, the quality of surface currents and the associated oceanic heat transport in CFSR are not compromised by the surface flux biases, and they agree with the best available estimates. The uncertainties of the observational data from field experiments are also briefly discussed in the present study.

  3. International energy outlook 1995, May 1995

    SciTech Connect (OSTI)

    NONE

    1995-06-01T23:59:59.000Z

    The International Energy Outlook 1995 (IEO95) presents an assessment by the Energy Information Administration (EIA) of the international energy market outlook through 2010. The report is an extension of the EIA`s Annual Energy Outlook 1995 (AEO95), which was prepared using the National Energy Modeling System (NEMS). US projections appearing in the IEO95 are consistent with those published in the AEO95. IEO95 is provided as a statistical service to energy managers and analysts, both in government and in the private sector. The projects are used by international agencies, Federal and State governments, trade associations, and other planners and decisionmakers. They are published pursuant to the Department of energy Organization Act of 1977 (Public Law 95-91), Section 295(c). The IEO95 projections are based on US and foreign government policies in effect on October 1, 1994. IEO95 displays projections according to six basic country groupings. The regionalization has changed since last year`s report. Mexico has been added to the Organization for Economic Cooperation and Development (OECD), and a more detailed regionalization has been incorporated for the remainder of the world, including the following subgroups: non-OECD Asia, Africa, Middle East, and Central and South America. China is included in non-OECD Asia. Eastern Europe and the former Soviet Union are combined in the EE/FSU subgroup.

  4. EIA - Annual Energy Outlook (AEO) 2012 Data Tables

    Gasoline and Diesel Fuel Update (EIA)

    75. Imported Liquids by Source XLS Table 76. Conversion Factors XLS About the Annual Energy Outlook Contact information and staff Press release AEO2012 Early Release AEO2012...

  5. EIA - Annual Energy Outlook (AEO) 2011 Data Tables

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

    75. Imported Liquids by Source XLS Table 76. Conversion Factors XLS About the Annual Energy Outlook Contact Information and Staff About the National Energy Modeling System (NEMS)...

  6. U.S. Energy Information Administration | Annual Energy Outlook...

    Gasoline and Diesel Fuel Update (EIA)

    Energy Information Administration | Annual Energy Outlook 2011 Regional maps Figure F2. Electricity market module regions Source: U.S. Energy Information Administration, Office...

  7. U.S. Energy Information Administration | Annual Energy Outlook...

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

    Energy Information Administration | Annual Energy Outlook 2013 Regional maps Figure F2. Electricity market module regions Source: U.S. Energy Information Administration, Office...

  8. EIA - Annual Energy Outlook (AEO) 2013 Data Tables

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

    and Income and Employment by Region Table 74. Conversion Factors About the Annual Energy Outlook Contact information and staff Press release Press conference presentation...

  9. Outlook for Energy and Implications for Irrigated Agriculture 

    E-Print Network [OSTI]

    Patton, W. P.; Lacewell, R. D.

    1977-01-01T23:59:59.000Z

    TR- 87 1977 Outlook for Energy and Implications for Irrigated Agriculture W.P. Patton R.D. Lacewell Texas Water Resources Institute Texas A&M University ...

  10. Assumptions to Annual Energy Outlook - Energy Information Administrati...

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

    January STEO Annual projections to 2040 International projections All projections reports Analysis & Projections Major Topics Most popular Annual Energy Outlook related...

  11. Improving Groundwater Predictions Utilizing Seasonal Precipitation Forecasts from General Circulation Models

    E-Print Network [OSTI]

    Arumugam, Sankar

    Improving Groundwater Predictions Utilizing Seasonal Precipitation Forecasts from General. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater

  12. Price forecasting for U.S. cattle feeders: which technique to apply?

    E-Print Network [OSTI]

    Hicks, Geoff Cody

    1997-01-01T23:59:59.000Z

    both feeder cattle costs and corn costs, and maximizing fed cattle prices. This research strives to evaluate the accuracy of six distinct price forecasting techniques over an eleven year period. The forecast techniques selected for this analysisare...

  13. Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Florita, A.; Hodge, B. M.; Freedman, J.

    2014-05-01T23:59:59.000Z

    The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

  14. Global Biodiesel Market Trends,Global Biodiesel Market Trends, Outlook and OpportunitiesOutlook and Opportunities

    E-Print Network [OSTI]

    Global Biodiesel Market Trends,Global Biodiesel Market Trends, Outlook and OpportunitiesPresident, Emerging Markets Online http://www.emerginghttp://www.emerging--markets.commarkets.com Author, Biodiesel 2020: A Global Market SurveyAuthor, Biodiesel 2020: A Global Market Survey Columnist

  15. Colorado 2014 Economic Outlook: There are No Guarantees

    E-Print Network [OSTI]

    Colorado 2014 Economic Outlook: There are No Guarantees Dr. Martin Shields Regional Economics Institute Colorado State University #12;The Important Economic Issues · The economy is no longer "recovering the recovery looked like · 2014 outlook · Does economic growth improve individual well-being? #12;"Recovery

  16. Energy for 500 million Homes: Drivers and Outlook for

    E-Print Network [OSTI]

    -up analysis of residential building energy consumption in China using data from a wide variety of sourcesLBNL-2417E Energy for 500 million Homes: Drivers and Outlook for Residential Energy Consumption and Outlook for Residential Energy Consumption in China Nan Zhou*, Michael A. McNeil, Mark Levine Keywords

  17. Alberta's Energy Reserves 2007 and Supply/Demand Outlook

    E-Print Network [OSTI]

    Laughlin, Robert B.

    Alberta's Energy Reserves 2007 and Supply/Demand Outlook 2008-2017 0 ST98-2008 Energy Resources RESOURCES CONSERVATION BOARD ST98-2008: Alberta's Energy Reserves 2007 and Supply/Demand Outlook 2008: Reserves Andy Burrowes, Rick Marsh, Nehru Ramdin, and Curtis Evans; Supply/Demand and Economics

  18. Technology Forecasting Scenario Development

    E-Print Network [OSTI]

    Technology Forecasting and Scenario Development Newsletter No. 2 October 1998 Systems Analysis was initiated on the establishment of a new research programme entitled Technology Forecasting and Scenario and commercial applica- tion of new technology. An international Scientific Advisory Panel has been set up

  19. Rainfall-River Forecasting

    E-Print Network [OSTI]

    US Army Corps of Engineers

    ;2Rainfall-River Forecasting Joint Summit II NOAA Integrated Water Forecasting Program · Minimize losses due management and enhance America's coastal assets · Expand information for managing America's Water Resources, Precipitation and Water Quality Observations · USACE Reservoir Operation Information, Streamflow, Snowpack

  20. Short-Term Energy Outlook September 2014

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctoberOutlook September

  1. EIA - Annual Energy Outlook 2014 Early Release

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0 Year-1InformationDieselAnnual Energy Outlook 2015 Release

  2. Annual Energy Outlook Report | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof EnergyInnovation in Carbon Capture and SequestrationAnemoi RenovablesAnjanOutlook

  3. Ris Energy Report 5 Renewable energy outlook for selected regions 1 4 Renewable energy outlook for selected regions

    E-Print Network [OSTI]

    Risø Energy Report 5 Renewable energy outlook for selected regions 1 4 Renewable energy outlook, are now gradually expanding their role in global energy supply. In 2004, renewable energy from all sources.2 0.0% Biomass 48.3 10.4% Total renewable 60.9 13.1% Total global primary energy consumption 465.4 100

  4. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluating A PotentialJumpGermanFife Energy Park atFisiaFlorida:Forecast Energy Jump to:

  5. Probabilistic manpower forecasting

    E-Print Network [OSTI]

    Koonce, James Fitzhugh

    1966-01-01T23:59:59.000Z

    PROBABILISTIC MANPOWER FORECASTING A Thesis JAMES FITZHUGH KOONCE Submitted to the Graduate College of the Texas ASSAM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May, 1966 Major Subject...: Computer Science and Statistics PROBABILISTIC MANPOWER FORECASTING A Thesis By JAMES FITZHUGH KOONCE Submitted to the Graduate College of the Texas A@M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May...

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

    E-Print Network [OSTI]

    Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

    2005-01-01T23:59:59.000Z

    Administration. 2004a. Annual Energy Outlook 2004. U.S.Assumptions of the Annual Energy Outlook 2004. DOE/EIA-0554(and Definitions AEO – Annual Energy Outlook ArcGIS - ESRI

  7. UPF Forecast | Y-12 National Security Complex

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

    Uranium Processing Facility UPF Forecast UPF Forecast UPF Procurement provides the following forecast of subcontracting opportunities. Keep in mind that these requirements may be...

  8. Long Term Forecast ofLong Term Forecast of TsunamisTsunamis

    E-Print Network [OSTI]

    : ImproveImprove NOAANOAA''ss understandingunderstanding and forecast capabilityand forecast capability inin

  9. The U.S. Natural Gas and Shale Production Outlook

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

    Natural Gas and Shale Production Outlook for North American Gas Forum September 29, 2014 by Adam Sieminski, Administrator The U.S. has experienced a rapid increase in natural gas...

  10. Supply, Demand, and Export Outlook for North American Oil and...

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

    Supply, Demand, and Export Outlook for North American Oil and Gas For Energy Infrastructure Summit September 15, 2014 | Houston, TX By Adam Sieminski, EIA Administrator 0 20 40 60...

  11. Global Liquefied Natural Gas Market: Status and Outlook, The

    Reports and Publications (EIA)

    2003-01-01T23:59:59.000Z

    The Global Liquefied Natural Gas Market: Status & Outlook was undertaken to characterize the global liquefied natural gas (LNG) market and to examine recent trends and future prospects in the LNG market.

  12. Material World: Forecasting Household Appliance Ownership in a Growing Global Economy

    E-Print Network [OSTI]

    Letschert, Virginie

    2010-01-01T23:59:59.000Z

    Paris IEA (2006). World Energy Outlook, International EnergyAgency. IEA (2002). World Energy Outlook, Internationalprimarily in the IEA’s World Energy Outlook (WEO) 2002 (2000

  13. Material World: Forecasting Household Appliance Ownership in a Growing Global Economy

    E-Print Network [OSTI]

    Letschert, Virginie

    2010-01-01T23:59:59.000Z

    Agency. IEA (2002). World Energy Outlook, InternationalParis IEA (2006). World Energy Outlook, International Energyprimarily in the IEA’s World Energy Outlook (WEO) 2002 (2000

  14. NWS Product Definition Document (PDD) for: Refinement of SPC Experimental Enhanced Resolution Thunderstorm Outlook

    E-Print Network [OSTI]

    NWS Product Definition Document (PDD) for: Refinement of SPC Experimental Enhanced Resolution replaces an existing PDD, whose evaluation period expired on 15 February 2008, and revises the current SPC will also evaluate changes in the distribution of SPC forecaster workload and the ability to maintain

  15. A methodology for forecasting carbon dioxide flooding performance

    E-Print Network [OSTI]

    Marroquin Cabrera, Juan Carlos

    1998-01-01T23:59:59.000Z

    A methodology was developed for forecasting carbon dioxide (CO2) flooding performance quickly and reliably. The feasibility of carbon dioxide flooding in the Dollarhide Clearfork "AB" Unit was evaluated using the methodology. This technique is very...

  16. CSUF Economic Outlook and Forecasts Mid-Year Update -April 2012

    E-Print Network [OSTI]

    de Lijser, Peter

    . Second, oil prices have risen steadily during this year, posing a significant risk to the world economy at a moderate pace -- a notch below the U.S. long-run potential growth and well below the historical rates in the first half by higher energy prices and a "soft-landing" of emerging market economies. Developments

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

    Reports and Publications (EIA)

    2009-01-01T23:59:59.000Z

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

  18. Steam System Forecasting and Management

    E-Print Network [OSTI]

    Mongrue, D. M.; Wittke, D. O.

    1982-01-01T23:59:59.000Z

    '. This and the complex and integrated nature of the plants energy balance makes steam system forecasting and management essential for optimum use of the plant's energy. This paper discusses the method used by Union carbide to accomplish effective forecasting...

  19. China's Energy and Carbon Emissions Outlook to 2050

    E-Print Network [OSTI]

    Zhou, Nan

    2011-01-01T23:59:59.000Z

    forecast of energy demand underlying both scenarios does not take into consideration resource constraints which, in the case of ChinaChina’s oil reserve forecast and analysis based on peak oil models”, Energy

  20. Consensus Coal Production Forecast for

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    Consensus Coal Production Forecast for West Virginia 2009-2030 Prepared for the West Virginia Summary 1 Recent Developments 2 Consensus Coal Production Forecast for West Virginia 10 Risks References 27 #12;W.Va. Consensus Coal Forecast Update 2009 iii List of Tables 1. W.Va. Coal Production

  1. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16T23:59:59.000Z

    EMGT 835 FIELD PROJECT: Improving Inventory Control Using Forecasting By Juan Mario Balandran jmbg@hotmail.com Master of Science The University of Kansas Fall Semester, 2005 An EMGT Field Project report submitted...............................................................................................................................................10 Current Inventory Forecast Process ...........................................................................................10 Development of Alternative Forecast Process...

  2. timber quality Modelling and forecasting

    E-Print Network [OSTI]

    Forest and timber quality in Europe Modelling and forecasting yield and quality in Europe Forest and timber quality in Europe Modelling and forecasting yield and quality in Europe M E F Y Q U E #12;Valuing and the UK ­ are working closely together to develop a model to help forecast timber growth, yield, quality

  3. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    electricity demand forecast means that the region's electricity needs would grow by 5,343 average megawattsDemand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required in electricity demand is, of course, crucial to determining the need for new electricity resources and helping

  4. Gas energy supply outlook through 2010

    SciTech Connect (OSTI)

    Kalisch, R.B.

    1986-03-01T23:59:59.000Z

    Late in 1984 the American Gas Association published a study by the Gas Supply Committee titled, ''The Outlook for Gas Energy Through 2010.'' This study was a joint effort by many people of the gas industry including GRI, IGT and AGA. The study observed that come 1646 Tcf of natural gas is judged to be ultimately recoverable in the US. Of this total, 665 Tcf were produced up to year-end 1984. At that time an additional 197 Tcf were categorized as proved reserves, i.e., known to exist with reasonable certainty and producible under current economic and operating conditions. An additional 784 Tcf were classified as potential supply. In short, about 60 % of the nation's ultimately recoverable resource still is available; only 40 % has been produced to data. This is a formidable gas resource for the lower-48; in 1984 the production level was about 17 Tcf; proved reserves were approximately 163 Tcf - more than nine times the 1984 production. 2 references, 2 tables.

  5. Legal improvements brighten North Africa production outlook

    SciTech Connect (OSTI)

    NONE

    1997-05-12T23:59:59.000Z

    North Africa`s three main oil producing countries soon will reap benefits of past moves by their governments to encourage investment by international companies. Production of crude oil and natural gas in Algeria, Egypt, and Libya is ready to increase from suppressed levels of the recent past, says International Energy Agency, Paris. The gains are possible despite political risks, total reserves accounting for only 4% of the world`s crude reserves, and oil prices well below levels of the 1980s, when the countries` flow rates peaked. The reason: producing oil in North Africa is profitable. In a recent study entitled North Africa Oil and Gas, IEA attributes the bright production outlook to improvements that the countries` governments have made in the past decade to hydrocarbon laws and the fiscal terms they offer international investors. According to announced plans, the three countries` combined capacity to produce crude oil will rise 18% by the year 2000 to 3.65 million b/d, and a further gain of 700,000 b/d is possible. IEA expects production capacity for natural gas to increase 50% from its 1995 level by 2000 to a combined 139.4 billion cu m/year. This paper discusses production capacities, Algeria`s record, improvements in Egypt, and Libya`s changes.

  6. Status and Outlook for the U.S. Non-Automotive Fuel Cell Industry...

    Office of Environmental Management (EM)

    Status and Outlook for the U.S. Non-Automotive Fuel Cell Industry: Impacts of Government Policies and Assessment of Future Opportunities Status and Outlook for the U.S....

  7. Mexico’s Deteriorating Oil Outlook: Implications and Energy Options for the Future

    E-Print Network [OSTI]

    Shields, David

    2008-01-01T23:59:59.000Z

    No. 8: David Shields, Mexico’s Deteriorating Oil Outlook:of California, Berkeley Mexico’s Deteriorating Oil Outlook:and the Environment in Mexico, 2005. No. 14: Kevin P.

  8. Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards "Top-Runner Approach"

    E-Print Network [OSTI]

    Komiyama, Ryoichi

    2008-01-01T23:59:59.000Z

    ABORATORY Japan’s Residential Energy Demand Outlook to 2030o r n i a Japan’s Residential Energy Demand Outlook to 2030residential sector, where energy demand has grown vigorously

  9. Mexico’s Deteriorating Oil Outlook: Implications and Energy Options for the Future

    E-Print Network [OSTI]

    Shields, David

    2008-01-01T23:59:59.000Z

    Mexico’s Deteriorating Oil Outlook: Implications and EnergyMexico’s Deteriorating Oil Outlook: Implications and EnergyA ccelerates Mexico’s crude oil production, which reached a

  10. Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards "Top-Runner Approach"

    E-Print Network [OSTI]

    Komiyama, Ryoichi

    2008-01-01T23:59:59.000Z

    L ABORATORY Japan’s Residential Energy Demand Outlook tol i f o r n i a Japan’s Residential Energy Demand Outlook toParticularly in Japan’s residential sector, where energy

  11. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary and interpretation of information from National Weather Service watches and warnings by10 decision makers such an outlier to the regional severe weather climatology. An analysis of the synoptic and13 mesoscale

  12. Fuel Price Forecasts INTRODUCTION

    E-Print Network [OSTI]

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

  13. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    Quantifying PV power output variability,” Solar Energy, vol.each solar sen at node i, P(t) the total power output of theSolar Forecasting Historically, traditional power generation technologies such as fossil and nu- clear power which were designed to run in stable output

  14. Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

    Forecasting and Resource Assessment, 1 st Edition, Editors:Forecasting and Resource Assessment, 1 st Edition, Editors:Forecasting and Resource Assessment, 1 st Ed.. Editor: Jan

  15. WEST VIRGINIA SPECIAL THANKS TO THE 2014 ECONOMIC OUTLOOK CONFERENCE SPONSORS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    2015 WEST VIRGINIA ECONOMIC OUTLOOK #12;SPECIAL THANKS TO THE 2014 ECONOMIC OUTLOOK CONFERENCE SPONSORS: WEST VIRGINIA DEPARTMENT OF REVENUE CHAMBERS ENDOWED PROGRAM FOR ELECTRONIC BUSINESS #12;Cover WEST VIRGINIA ECONOMIC OUTLOOKWest Virginia Economic Outlook 2015 is published by: Bureau of Business

  16. Evaluation of Mixed-Phase Cloud Parameterizations in Short-Range Weather Forecasts with CAM3 and AM2 for Mixed-Phase Arctic Cloud Experiment

    SciTech Connect (OSTI)

    Xie, S; Boyle, J; Klein, S; Liu, X; Ghan, S

    2007-06-01T23:59:59.000Z

    By making use of the in-situ data collected from the recent Atmospheric Radiation Measurement Mixed-Phase Arctic Cloud Experiment, we have tested the mixed-phase cloud parameterizations used in the two major U.S. climate models, the National Center for Atmospheric Research Community Atmosphere Model version 3 (CAM3) and the Geophysical Fluid Dynamics Laboratory climate model (AM2), under both the single-column modeling framework and the U.S. Department of Energy Climate Change Prediction Program-Atmospheric Radiation Measurement Parameterization Testbed. An improved and more physically based cloud microphysical scheme for CAM3 has been also tested. The single-column modeling tests were summarized in the second quarter 2007 Atmospheric Radiation Measurement metric report. In the current report, we document the performance of these microphysical schemes in short-range weather forecasts using the Climate Chagne Prediction Program Atmospheric Radiation Measurement Parameterizaiton Testbest strategy, in which we initialize CAM3 and AM2 with realistic atmospheric states from numerical weather prediction analyses for the period when Mixed-Phase Arctic Cloud Experiment was conducted.

  17. FORECAST OF ENSEMBLE POWER PRODUCTION BY GRID-CONNECTED PV SYSTEMS Elke Lorenz*, Detlev Heinemann*, Hashini Wickramarathne*, Hans Georg Beyer +

    E-Print Network [OSTI]

    Heinemann, Detlev

    FORECAST OF ENSEMBLE POWER PRODUCTION BY GRID-CONNECTED PV SYSTEMS Elke Lorenz*, Detlev HeinemannH, Spicherer Straße 48, D-86157 Augsburg, Germany ABSTRACT: The contribution of power production by PV systems and evaluate an approach to forecast regional PV power production. The forecast quality was investigated

  18. Forecasting oilfield economic performance

    SciTech Connect (OSTI)

    Bradley, M.E. (Univ. of Chicago, IL (United States)); Wood, A.R.O. (BP Exploration, Anchorage, AK (United States))

    1994-11-01T23:59:59.000Z

    This paper presents a general method for forecasting oilfield economic performance that integrates cost data with operational, reservoir, and financial information. Practices are developed for determining economic limits for an oil field and its components. The economic limits of marginal wells and the role of underground competition receive special attention. Also examined is the influence of oil prices on operating costs. Examples illustrate application of these concepts. Categorization of costs for historical tracking and projections is recommended.

  19. Update and Outlook for the Fusion Energy Sciences Program

    E-Print Network [OSTI]

    Update and Outlook for the Fusion Energy Sciences Program E.J. Synakowski Associate Director, Office of Science Fusion Energy Sciences Fusion Power Associates Annual Meeting Washington, D.C. December Energy Sciences 3D topologies Samuel Barish, Lead,: Validation Platforms, Stellarators Steve Eckstrand

  20. Annual Energy Outlook 2009 with Projections to 2030

    SciTech Connect (OSTI)

    None

    2009-03-01T23:59:59.000Z

    The Annual Energy Outlook 2009 (AEO2009), prepared by the Energy Information Administration (EIA), presents long-term projections of energy supply, demand, and prices through 2030, based on results from EIA’s National Energy Modeling System (NEMS). EIA published an “early release” version of the AEO2009 reference case in December 2008.

  1. Viewpoints, Outlook Nov. 22, 2007, 7:35PM

    E-Print Network [OSTI]

    Valero-Cuevas, Francisco

    Viewpoints, Outlook Nov. 22, 2007, 7:35PM $100 oil means it's time for the Sputnik treatment Energy for the world. In a welcome sign, Congress recently handled energy in a refreshingly high-minded way when and population densities were low, we could slide. But we live in an increasingly energy-hungry world

  2. Achievements and Outlook 2012 SA Water Centre for Water

    E-Print Network [OSTI]

    Mayer, Wolfgang

    Achievements and Outlook 2012 SA Water Centre for Water Management and Reuse #12;Contents Our Breaking News 35 SA Water Centre for Water Management and Reuse University of South Australia Mawson Lakes Campus Mawson Lakes SA 5095 Telephone: +61 (08) 8302 3338 Fax: +61 (08) 8302 3386 Web: unisa.edu.au/water

  3. The 2009 Outlook for Texas Rural Land Values 

    E-Print Network [OSTI]

    Klinefelter, Danny A.

    2009-03-26T23:59:59.000Z

    use. When a market is Danny Klinfelter* E-550 3/09 The 2009 Outlook for Texas Rural Land Values Agriculture and the 2008 Credit Crisis in equilibrium, only the top producers would actually earn a profit through superior management, while...

  4. Still Crazy After All These Years: Understanding the Budget Outlook

    E-Print Network [OSTI]

    Sadoulet, Elisabeth

    1 Still Crazy After All These Years: Understanding the Budget Outlook Alan J. Auerbach, Jason spending enacted since then, the Congressional Budget Office (CBO, 2007b) currently projects a baseline surplus of $586 billion in the unified budget over the next 10 years. Under the baseline, the deficit

  5. The Outlook for Energy: A View to 2040

    E-Print Network [OSTI]

    Ferrari, Silvia

    Southeast Asia Latin America Fertility Rate* Children per Woman * Source: World Bank & United Nations OECD Biomass Other Renewables Oil Nuclear Quadrillion BTUs OECD Coal Gas ExxonMobil 2013 Outlook for Energy #12 Nuclear Other Renewables Source: Smil, Energy Transitions (1800-1960) #12;Conclusions ExxonMobil 2013

  6. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01T23:59:59.000Z

    This presentation describes the importance of good forecasting for variable generation, the different approaches used by industry, and the importance of validated high-quality data.

  7. ELECTRICITY DEMAND FORECAST COMPARISON REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005.................................................................................................................................3 PACIFIC GAS & ELECTRIC PLANNING AREA ........................................................................................9 Commercial Sector

  8. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN Manager Joseph O' Hagan Project Manager Kelly Birkinshaw Program Area Manager ENERGY-RELATED ENVIRONMENTAL

  9. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    Energy Commission's final forecasts for 2012­2022 electricity consumption, peak, and natural gas demand Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand

  10. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    the California Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand

  11. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak, and natural Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility

  12. Application of Fast Marching Methods for Rapid Reservoir Forecast and Uncertainty Quantification

    E-Print Network [OSTI]

    Olalotiti-Lawal, Feyisayo

    2013-05-17T23:59:59.000Z

    Rapid economic evaluations of investment alternatives in the oil and gas industry are typically contingent on fast and credible evaluations of reservoir models to make future forecasts. It is often important to also quantify inherent risks...

  13. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    · NATIONAL AND GLOBAL FORECASTS · WEST VIRGINIA PROFILES AND FORECASTS · ENERGY · HEALTHCARE Research West Virginia University College of Business and Economics P.O. Box 6527, Morgantown, WV 26506 EXPERT OPINION PROVIDED BY Keith Burdette Cabinet Secretary West Virginia Department of Commerce

  14. Conservation The Northwest ForecastThe Northwest Forecast

    E-Print Network [OSTI]

    & Resources Creating Mr. Toad's Wild Ride for the PNW's Energy Efficiency InCreating Mr. Toad's Wild RideNorthwest Power and Conservation Council The Northwest ForecastThe Northwest Forecast ­­ Energy EfficiencyEnergy Efficiency Dominates ResourceDominates Resource DevelopmentDevelopment Tom EckmanTom Eckman

  15. China's Energy and Carbon Emissions Outlook to 2050

    SciTech Connect (OSTI)

    Zhou, Nan; Fridley, David; McNeil, Michael; Zheng, Nina; Ke, Jing; Levine, Mark

    2011-02-15T23:59:59.000Z

    As a result of soaring energy demand from a staggering pace of economic expansion and the related growth of energy-intensive industry, China overtook the United States to become the world's largest contributor to CO{sub 2} emissions in 2007. At the same time, China has taken serious actions to reduce its energy and carbon intensity by setting both a short-term energy intensity reduction goal for 2006 to 2010 as well as a long-term carbon intensity reduction goal for 2020. This study presents a China Energy Outlook through 2050 that assesses the role of energy efficiency policies in transitioning China to a lower emission trajectory and meeting its intensity reduction goals. Over the past few years, LBNL has established and significantly enhanced its China End-Use Energy Model which is based on the diffusion of end-use technologies and other physical drivers of energy demand. This model presents an important new approach for helping understand China's complex and dynamic drivers of energy consumption and implications of energy efficiency policies through scenario analysis. A baseline ('Continued Improvement Scenario') and an alternative energy efficiency scenario ('Accelerated Improvement Scenario') have been developed to assess the impact of actions already taken by the Chinese government as well as planned and potential actions, and to evaluate the potential for China to control energy demand growth and mitigate emissions. In addition, this analysis also evaluated China's long-term domestic energy supply in order to gauge the potential challenge China may face in meeting long-term demand for energy. It is a common belief that China's CO{sub 2} emissions will continue to grow throughout this century and will dominate global emissions. The findings from this research suggest that this will not necessarily be the case because saturation in ownership of appliances, construction of residential and commercial floor area, roadways, railways, fertilizer use, and urbanization will peak around 2030 with slowing population growth. The baseline and alternative scenarios also demonstrate that China's 2020 goals can be met and underscore the significant role that policy-driven energy efficiency improvements will play in carbon mitigation along with a decarbonized power supply through greater renewable and non-fossil fuel generation.

  16. 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. Hall Deputy Director Energy Efficiency and Demand Analysis Division Scott W. Matthews Acting Executive

  17. Mathematical Forecasting Donald I. Good

    E-Print Network [OSTI]

    Boyer, Robert Stephen

    Mathematical Forecasting Donald I. Good Technical Report 47 September 1989 Computational Logic Inc the physical behavior of computer programs can reduce these risks for software engineering in the same way that it does for aerospace and other fields of engineering. Present forecasting capabilities for computer

  18. Regional-seasonal weather forecasting

    SciTech Connect (OSTI)

    Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

    1980-08-01T23:59:59.000Z

    In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

  19. Short Term Hourly Load Forecasting Using Abductive Networks R. E. Abdel-Aal

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Physical Sciences, Research Institute, King Fahd University of Petroleum and Minerals, Dhahran, Saudi for forecasting next-day hourly loads have been developed. Evaluated on data for the 6th year, the models give. INTRODUCTION Accurate load forecasting is a key requirement for the planning and economic and secure operation

  20. Development and Demonstration of a Relocatable Ocean OSSE System: Optimizing Ocean Observations for Hurricane Forecast

    E-Print Network [OSTI]

    forecasts for individual storms and improved seasonal forecast of the ocean thermal energy availableDevelopment and Demonstration of a Relocatable Ocean OSSE System: Optimizing Ocean Observations in the Gulf of Mexico is being extended to provide NOAA the ability to evaluate new ocean observing systems

  1. Application of a medium-range global hydrologic probabilistic forecast scheme to the Ohio River Basin

    SciTech Connect (OSTI)

    Voisin, Nathalie; Pappenberger, Florian; Lettenmaier, D. P.; Buizza, Roberto; Schaake, John

    2011-08-15T23:59:59.000Z

    A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003-2007. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium Range Weather Forecasts (ECMWF) analysis temperatures and wind, and Tropical Rainfall Monitoring Mission Multi Satellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF ensemble prediction system (EPS) 10-day ensemble forecast. A parallel set up was used where ECMWF EPS forecasts were interpolated to the spatial scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The flood prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. Initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.

  2. EIA-An Updated Annual Energy Outlook 2009 Reference Case Reflecting...

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

    This report updates the Reference Case presented in the Annual Energy Outlook 2009 based on recently enacted legislation and the changing macroeconomic environment. Contents...

  3. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN with primary contributions in the area of decision support for reservoir planning and management Commission Energy-Related Environmental Research Joseph O' Hagan Contract Manager Joseph O' Hagan Project

  4. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN: California Energy Commission Energy-Related Environmental Research Joseph O' Hagan Contract Manager Joseph O' Hagan Project Manager Kelly Birkinshaw Program Area Manager ENERGY-RELATED ENVIRONMENTAL RESEARCH Martha

  5. Weather forecasting : the next generation : the potential use and implementation of ensemble forecasting

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01T23:59:59.000Z

    This thesis discusses ensemble forecasting, a promising new weather forecasting technique, from various viewpoints relating not only to its meteorological aspects but also to its user and policy aspects. Ensemble forecasting ...

  6. Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China

    SciTech Connect (OSTI)

    Zhou, Nan; McNeil, Michael A.; Levine, Mark

    2009-06-01T23:59:59.000Z

    China's rapid economic expansion has propelled it to the rank of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modelling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities. From this analysis, we can conclude that Chinese residential energy consumption will more than double by 2020, from 6.6 EJ in 2000 to 15.9 EJ in 2020. This increase will be driven primarily by urbanization, in combination with increases in living standards. In the urban and higher income Chinese households of the future, most major appliances will be common, and heated and cooled areas will grow on average. These shifts will offset the relatively modest efficiency gains expected according to current government plans and policies already in place. Therefore, levelling and reduction of growth in residential energy demand in China will require a new set of more aggressive efficiency policies.

  7. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

    Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-01-01T23:59:59.000Z

    EIA). 1996a. Annual Energy Outlook 1996. DOE/EIA- 0383(DC. _______________. 1996b. Annual Energy Outlook 1997. DOE/DC. _______________. 1997. Annual Energy Outlook 1998. DOE/

  9. 2007 Florida Hard Clam Aquaculture Outlook So what's in store for the new year? Expec-

    E-Print Network [OSTI]

    Florida, University of

    ://usda.mannlib.cornell.edu. The current economic outlook for U.S. aquacultural producers for 2007 is clouded by wide swings in energy2007 Florida Hard Clam Aquaculture Outlook So what's in store for the new year? Expec- tations projects. Meeting details are on Page 5. Regarding market trends, the annual Buyer's Guide of Seafood

  10. West Virginia Economic Outlook 2012 George W. Hammond, Associate Director, BBER,

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    West Virginia Economic Outlook 2012 George W. Hammond, Associate Director, BBER, and Associate Professor of Economics West Virginia Economic Outlook 2012 is published by the Bureau of Business and Economic Research at the College of Business and Economics, West Virginia University, P.O. Box 6527

  11. West Virginia Economic Outlook 2010 George W. Hammond, Associate Director, BBER,

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    West Virginia Economic Outlook 2010 George W. Hammond, Associate Director, BBER, and Associate Professor of Economics West Virginia Economic Outlook 2010 is published by the Bureau of Business and Economic Research at the College of Business and Economics, West Virginia University, P.O. Box 6025

  12. West Virginia Economic Outlook 2011 George W. Hammond, Associate Director, BBER,

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    West Virginia Economic Outlook 2011 George W. Hammond, Associate Director, BBER, and Associate Professor of Economics West Virginia Economic Outlook 2011 is published by the Bureau of Business and Economic Research at the College of Business and Economics, West Virginia University, P.O. Box 6025

  13. Probabilistic Performance Forecasting for Unconventional Reservoirs With Stretched-Exponential Model

    E-Print Network [OSTI]

    Can, Bunyamin

    2011-08-08T23:59:59.000Z

    a reserves-evaluation workflow that couples the traditional decline-curve analysis with a probabilistic forecasting frame. The stretched-exponential production decline model (SEPD) underpins the production behavior. Our recovery appraisal workflow...

  14. Thirty-Year Solid Waste Generation Maximum and Minimum Forecast for SRS

    SciTech Connect (OSTI)

    Thomas, L.C.

    1994-10-01T23:59:59.000Z

    This report is the third phase (Phase III) of the Thirty-Year Solid Waste Generation Forecast for Facilities at the Savannah River Site (SRS). Phase I of the forecast, Thirty-Year Solid Waste Generation Forecast for Facilities at SRS, forecasts the yearly quantities of low-level waste (LLW), hazardous waste, mixed waste, and transuranic (TRU) wastes generated over the next 30 years by operations, decontamination and decommissioning and environmental restoration (ER) activities at the Savannah River Site. The Phase II report, Thirty-Year Solid Waste Generation Forecast by Treatability Group (U), provides a 30-year forecast by waste treatability group for operations, decontamination and decommissioning, and ER activities. In addition, a 30-year forecast by waste stream has been provided for operations in Appendix A of the Phase II report. The solid wastes stored or generated at SRS must be treated and disposed of in accordance with federal, state, and local laws and regulations. To evaluate, select, and justify the use of promising treatment technologies and to evaluate the potential impact to the environment, the generic waste categories described in the Phase I report were divided into smaller classifications with similar physical, chemical, and radiological characteristics. These smaller classifications, defined within the Phase II report as treatability groups, can then be used in the Waste Management Environmental Impact Statement process to evaluate treatment options. The waste generation forecasts in the Phase II report includes existing waste inventories. Existing waste inventories, which include waste streams from continuing operations and stored wastes from discontinued operations, were not included in the Phase I report. Maximum and minimum forecasts serve as upper and lower boundaries for waste generation. This report provides the maximum and minimum forecast by waste treatability group for operation, decontamination and decommissioning, and ER activities.

  15. Short-term energy outlook, quarterly projections, second quarter 1998

    SciTech Connect (OSTI)

    NONE

    1998-04-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly short-term energy supply, demand, and price projections. The details of these projections, as well as monthly updates, are available on the Internet at: www.eia.doe.gov/emeu/steo/pub/contents.html. The paper discusses outlook assumptions; US energy prices; world oil supply and the oil production cutback agreement of March 1998; international oil demand and supply; world oil stocks, capacity, and net trade; US oil demand and supply; US natural gas demand and supply; US coal demand and supply; US electricity demand and supply; US renewable energy demand; and US energy demand and supply sensitivities. 29 figs., 19 tabs.

  16. Biodiesel Outlook - An Engine Manufacturer's Perspective | Department of

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny: The FutureCommentsEnergyand SustainedBio-Oil Deployment inEnergy Outlook -

  17. The Outlook for Renewable Electricity in the United States

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14TotalThe Outlook for Renewable Electricity in the United

  18. EIA - Annual Energy Outlook (AEO) 2013 Data Tables

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0 Year-1InformationDieselAnnual Energy Outlook 2015 Release Date:

  19. Short-Term Energy Outlook Supplement: 2013 Outlook for Gulf of Mexico Hurricane-Related Production Outages

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del Sol HomeFacebookScholarship Fund3 Outlook for Gulf of Mexico Hurricane-Related

  20. Short-Term Energy Outlook Supplement: 2015 Outlook for Gulf of Mexico Hurricane-Related Production Outages

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctoberOutlook September45

  1. Forecasting consumer products using prediction markets

    E-Print Network [OSTI]

    Trepte, Kai

    2009-01-01T23:59:59.000Z

    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 ...

  2. Massachusetts state airport system plan forecasts.

    E-Print Network [OSTI]

    Mathaisel, Dennis F. X.

    This report is a first step toward updating the forecasts contained in the 1973 Massachusetts State System Plan. It begins with a presentation of the forecasting techniques currently available; it surveys and appraises the ...

  3. Management Forecast Quality and Capital Investment Decisions

    E-Print Network [OSTI]

    Goodman, Theodore H.

    Corporate investment decisions require managers to forecast expected future cash flows from potential investments. Although these forecasts are a critical component of successful investing, they are not directly observable ...

  4. Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations

    E-Print Network [OSTI]

    Kemner, Ken

    forecasting methods and better integration of advanced wind power forecasts into system and plant operations and wind power plants) ­ Review and assess current practices Propose and test new and improved approachesWind Power Forecasting andWind Power Forecasting and Electricity Market Operations Audun Botterud

  5. 1995 shipment review & five year forecast

    SciTech Connect (OSTI)

    Fetherolf, D.J. Jr. [East Penn Manufacturing Co., Inc., Lyon Station, PA (United States)

    1996-01-01T23:59:59.000Z

    This report describes the 1995 battery shipment review and five year forecast for the battery market. Historical data is discussed.

  6. Consensus Coal Production And Price Forecast For

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    Consensus Coal Production And Price Forecast For West Virginia: 2011 Update Prepared for the West December 2011 © Copyright 2011 WVU Research Corporation #12;#12;W.Va. Consensus Coal Forecast Update 2011 i Table of Contents Executive Summary 1 Recent Developments 3 Consensus Coal Production And Price Forecast

  7. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 2: Electricity Demand by Utility Planning Area Energy Policy Report. The forecast includes three full scenarios: a high energy demand case, a low

  8. LOAD FORECASTING Eugene A. Feinberg

    E-Print Network [OSTI]

    Feinberg, Eugene A.

    , regression, artificial intelligence. 1. Introduction Accurate models for electric power load forecasting to make important decisions including decisions on pur- chasing and generating electric power, load for different operations within a utility company. The natures 269 #12;270 APPLIED MATHEMATICS FOR POWER SYSTEMS

  9. Calculator simplifies field production forecasting

    SciTech Connect (OSTI)

    Bixler, B.

    1982-05-01T23:59:59.000Z

    A method of forecasting future field production from an assumed average well production schedule and drilling schedule has been programmed for the HP-41C hand-held programmable computer. No longer must tedious row summations be made by hand for staggered well production schedules. Details of the program are provided.

  10. Electric Load Forecasting

    E-Print Network [OSTI]

    -commitment, coordination, and interchange evaluation. In addition, the liberalization of electric energy markets worldwide has led to the development of energy exchanges where consumers, 1066-033X/07/$25.00©2007IEEE OCTOBER/GODDARD SPACE FLIGHT CENTER SCIENTIFIC VISUALIZATION STUDIO Authorized licensed use limited to: Katholieke

  11. Short-term energy outlook. Quarterly projections, second quarter 1996

    SciTech Connect (OSTI)

    NONE

    1996-04-01T23:59:59.000Z

    The Energy Information Administration prepares quarterly, short-term energy supply, demand, and price projections. The forecasts in this issue cover the second quarter of 1996 through the fourth quarter of 1997. Changes to macroeconomic measures by the Bureau of Economic Analysis have been incorporated into the STIFS model used.

  12. Short-Term Energy Outlook Supplement: Uncertainties in the Short-Term Global Petroleum and Other Liquids Supply Forecast

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSettingUncertainties in the Short-Term

  13. Modifications to incorporate competitive electricity prices in the annual energy outlook 1998 - electricity market module

    SciTech Connect (OSTI)

    NONE

    1998-02-01T23:59:59.000Z

    The purpose of this report is to describe modifications to the Electricity Market Module (EMM) for the Annual Energy Outlook 1998. It describes revisions necessary to derive competitive electricity prices and the corresponding reserve margins.

  14. Comparative Analysis of Modeling Studies on China's Future Energy and Emissions Outlook

    E-Print Network [OSTI]

    Zheng, Nina

    2010-01-01T23:59:59.000Z

    International Energy Agency (IEA). 2009. World EnergyChina-specific section of the IEA World Energy Outlook 2009.while LBNL, McKinsey and IEA all employed bottom-up modeling

  15. Mexico’s Deteriorating Oil Outlook: Implications and Energy Options for the Future

    E-Print Network [OSTI]

    Shields, David

    2008-01-01T23:59:59.000Z

    No. 8: David Shields, Mexico’s Deteriorating Oil Outlook:years. Estimating oil reserves in Mexico has long been aof as yet unproven oil reserves in Mexico’s part of the

  16. Original documentation created by University of Central Florida. Outlook 2007 vs GroupWise

    E-Print Network [OSTI]

    Mukhtar, Saqib

    Original documentation created by University of Central Florida. Outlook to in GW!) Personal folders are stored in the Cabinet #12;Original documentation created as a grey envelope. #12;Original documentation created by University of Central

  17. Original documentation created by University of Central Florida. Outlook 2010 vs GroupWise

    E-Print Network [OSTI]

    Mukhtar, Saqib

    Original documentation created by University of Central Florida. Outlook #12;Original documentation created by University of Central Florida. Cabinet as a grey envelope. #12;Original documentation created by University of Central

  18. Forecasting the monthly volume of orders for southern pine lumber - an econometric model

    E-Print Network [OSTI]

    Jackson, Ben Douglas

    1973-01-01T23:59:59.000Z

    the orders estimates should be minimal, and the benefits of forecasting should exceed the costs. Included in this matter of convenience is the mathematical simplicity of the computations and their evaluation. With these essential characteristics in mind... FORECASTING THE MONTHLY VOLUME OF ORDERS FOR SOUTHERN PINE LUMBER - AH ECONOMETRIC MODEL A Thesis by BEN DOUGLAS JACKSON Submitted to the Graduate College of Texas ASM University in Partial fulfillment of the requirement for the degree...

  19. Review of Wind Energy Forecasting Methods for Modeling Ramping Events

    SciTech Connect (OSTI)

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

    2011-03-28T23:59:59.000Z

    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.

  20. The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations – the Northern Study Area.

    SciTech Connect (OSTI)

    Finley, Cathy [WindLogics

    2014-04-30T23:59:59.000Z

    This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times. A comprehensive analysis of wind energy forecast errors for the various model-based power forecasts was presented for a suite of wind energy ramp definitions. The results compiled over the year-long study period showed that the power forecasts based on the research models (ESRL_RAP, HRRR) more accurately predict wind energy ramp events than the current operational forecast models, both at the system aggregate level and at the local wind plant level. At the system level, the ESRL_RAP-based forecasts most accurately predict both the total number of ramp events and the occurrence of the events themselves, but the HRRR-based forecasts more accurately predict the ramp rate. At the individual site level, the HRRR-based forecasts most accurately predicted the actual ramp occurrence, the total number of ramps and the ramp rates (40-60% improvement in ramp rates over the coarser resolution forecast

  1. NREL: Transmission Grid Integration - Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible for Renewable Energy: Grid IntegrationReport AvailableForecasting NREL researchers use

  2. Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01T23:59:59.000Z

    US DOE. 1995a. Annual Energy Outlook 1995, with ProjectionsAdministration (ELA) 1995 Annual Energy Outlook (AEO); 1990of Energy's Annual Energy Outlook ( US DOE 1995a). A l l

  3. Introduction to energy storage with market analysis and outlook

    SciTech Connect (OSTI)

    Schmid, Robert [Institut für Experimentelle Physik, Technische Universität Bergakademie Freiberg, Leipziger Straße 23, 09596 Freiberg (Germany); Pillot, Christophe [AVICENNE Energy, LITWIN Building, 10 rue Jean-Jaurès, La Défense 11, Puteaux Cedex (France)

    2014-06-16T23:59:59.000Z

    At first, the rechargeable battery market in 2012 will be described by technology - lead acid, NiCd, NiMH, lithium ion - and application - portable electronics, power tools, e-bikes, automotive, energy storage. This will be followed by details of the lithium ion battery market value chain from the raw material to the final application. The lithium ion battery market of 2012 will be analyzed and split by applications, form factors and suppliers. There is also a focus on the cathode, anode, electrolyte and separator market included. This report will also give a forecast for the main trends and the market in 2020, 2025. To conclude, a forecast for the rechargeable battery market by application for 2025 will be presented. Since energy storage plays an important role for the growing Electric Vehicle (EV) market, this EV issue is closely considered throughout this analysis.

  4. Funding Opportunity Announcement for Wind Forecasting Improvement...

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

    collects data on a variety of physical processes that impact the wind forecasts used by wind farms, system operators and other industry professionals. By having access to...

  5. Upcoming Funding Opportunity for Wind Forecasting Improvement...

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

    collects data on a variety of physical processes that impact the wind forecasts used by wind farms, system operators and other industry professionals. By having access to...

  6. Solid low-level waste forecasting guide

    SciTech Connect (OSTI)

    Templeton, K.J.; Dirks, L.L.

    1995-03-01T23:59:59.000Z

    Guidance for forecasting solid low-level waste (LLW) on a site-wide basis is described in this document. Forecasting is defined as an approach for collecting information about future waste receipts. The forecasting approach discussed in this document is based solely on hanford`s experience within the last six years. Hanford`s forecasting technique is not a statistical forecast based upon past receipts. Due to waste generator mission changes, startup of new facilities, and waste generator uncertainties, statistical methods have proven to be inadequate for the site. It is recommended that an approach similar to Hanford`s annual forecasting strategy be implemented at each US Department of Energy (DOE) installation to ensure that forecast data are collected in a consistent manner across the DOE complex. Hanford`s forecasting strategy consists of a forecast cycle that can take 12 to 30 months to complete. The duration of the cycle depends on the number of LLW generators and staff experience; however, the duration has been reduced with each new cycle. Several uncertainties are associated with collecting data about future waste receipts. Volume, shipping schedule, and characterization data are often reported as estimates with some level of uncertainty. At Hanford, several methods have been implemented to capture the level of uncertainty. Collection of a maximum and minimum volume range has been implemented as well as questionnaires to assess the relative certainty in the requested data.

  7. Geothermal wells: a forecast of drilling activity

    SciTech Connect (OSTI)

    Brown, G.L.; Mansure, A.J.; Miewald, J.N.

    1981-07-01T23:59:59.000Z

    Numbers and problems for geothermal wells expected to be drilled in the United States between 1981 and 2000 AD are forecasted. The 3800 wells forecasted for major electric power projects (totaling 6 GWe of capacity) are categorized by type (production, etc.), and by location (The Geysers, etc.). 6000 wells are forecasted for direct heat projects (totaling 0.02 Quads per year). Equations are developed for forecasting the number of wells, and data is presented. Drilling and completion problems in The Geysers, The Imperial Valley, Roosevelt Hot Springs, the Valles Caldera, northern Nevada, Klamath Falls, Reno, Alaska, and Pagosa Springs are discussed. Likely areas for near term direct heat projects are identified.

  8. Online Forecast Combination for Dependent Heterogeneous Data

    E-Print Network [OSTI]

    Sancetta, Alessio

    the single individual forecasts. Several studies have shown that combining forecasts can be a useful hedge against structural breaks, and forecast combinations are often more stable than single forecasts (e.g. Hendry and Clements, 2004, Stock and Watson, 2004... in expectations. Hence, we have the following. Corollary 4 Suppose maxt?T kl (Yt, hwt,Xti)kr ? A taking expectation on the left hand side, adding 2A ? T and setting ? = 0 in mT (?), i.e. TX t=1 E [lt (wt)? lt (ut...

  9. The Value of Wind Power Forecasting

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

    Wind Power Forecasting Preprint Debra Lew and Michael Milligan National Renewable Energy Laboratory Gary Jordan and Richard Piwko GE Energy Presented at the 91 st American...

  10. U-M Construction Forecast December 15, 2011 U-M Construction Forecast

    E-Print Network [OSTI]

    Kamat, Vineet R.

    U-M Construction Forecast December 15, 2011 U-M Construction Forecast Spring ­ Fall 2012 As of December 15, 2011 Prepared by AEC Preliminary & Advisory #12;U-M Construction Forecast December 15, 2011 Overview · Campus by campus · Snapshot in time ­ Not all projects · Construction coordination efforts

  11. Annual Energy Outlook 2011 with Projections to 2035

    SciTech Connect (OSTI)

    None

    2011-04-01T23:59:59.000Z

    The projections in the Energy Information Administration's (EIA) Annual Energy Outlook 2011 (AEO2011) focus on the factors that shape the U.S. energy system over the long term. Under the assumption that current laws and regulations remain unchanged throughout the projections, the AEO2011 Reference case provides the basis for examination and discussion of energy production, consumption, technology, and market trends and the direction they may take in the future. It also serves as a starting point for analysis of potential changes in energy policies. But AEO2011 is not limited to the Reference case. It also includes 57 sensitivity cases (see Appendix E, Table E1), which explore important areas of uncertainty for markets, technologies, and policies in the U.S. energy economy. Key results highlighted in AEO2011 include strong growth in shale gas production, growing use of natural gas and renewables in electric power generation, declining reliance on imported liquid fuels, and projected slow growth in energy-related carbon dioxide (CO2) emissions even in the absence of new policies designed to mitigate greenhouse gas (GHG) emissions. AEO2011 also includes in-depth discussions on topics of special interest that may affect the energy outlook. They include: impacts of the continuing renewal and updating of Federal and State laws and regulations; discussion of world oil supply and price trends shaped by changes in demand from countries outside the Organization for Economic Cooperation and Development or in supply available from the Organization of the Petroleum Exporting Countries; an examination of the potential impacts of proposed revisions to Corporate Average Fuel Economy standards for light-duty vehicles and proposed new standards for heavy-duty vehicles; the impact of a series of updates to appliance standard alone or in combination with revised building codes; the potential impact on natural gas and crude oil production of an expanded offshore resource base; prospects for shale gas; the impact of cost uncertainty on construction of new electric power plants; the economics of carbon capture and storage; and the possible impact of regulations on the electric power sector under consideration by the U.S. Environmental Protection Agency (EPA). Some of the highlights from those discussions are mentioned in this Executive Summary. Readers interested in more detailed analyses and discussions should refer to the 'Issues in focus' section of this report.

  12. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    has developed longterm forecasts of transportation energy demand as well as projected ranges of transportation fuel and crude oil import requirements. The transportation energy demand forecasts makeCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY

  13. Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting

    E-Print Network [OSTI]

    Plale, Beth

    Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting Nithya N. Vijayakumar {rramachandran, xli}@itsc.uah.edu Abstract-- Mesoscale meteorology forecasting as a data driven application Triggers, Data Mining, Stream Processing, Meteorology Forecasting I. INTRODUCTION Mesoscale meteorologists

  14. 1992 five year battery forecast

    SciTech Connect (OSTI)

    Amistadi, D.

    1992-12-01T23:59:59.000Z

    Five-year trends for automotive and industrial batteries are projected. Topic covered include: SLI shipments; lead consumption; automotive batteries (5-year annual growth rates); industrial batteries (standby power and motive power); estimated average battery life by area/country for 1989; US motor vehicle registrations; replacement battery shipments; potential lead consumption in electric vehicles; BCI recycling rates for lead-acid batteries; US average car/light truck battery life; channels of distribution; replacement battery inventory end July; 2nd US battery shipment forecast.

  15. Annual energy outlook 2009 with projections to 2030

    SciTech Connect (OSTI)

    NONE

    2009-03-15T23:59:59.000Z

    The Annual Energy Outlook 2009 (AEO009), presents long-term projections of energy supply, demand, and prices through 2030, based on results from EIA's National Energy Modeling System (NEMS). EIA published an 'early release' version of the AEO009 reference case in December 2008. The report begins with an 'Executive Summary' that highlights key aspects of the projections. It is followed by a 'Legislation and Regulations' section that discusses evolving legislation and regulatory issues, including a summary of recently enacted legislation, such as the Energy Improvement and Extension Act of 2008 (EIEA2008). The next section, 'Issues in Focus,' contains discussions of selected topics, including: the impacts of limitations on access to oil and natural gas resources on the Federal Outer Continental Shelf (OCS); the implications of uncertainty about capital costs for new electricity generating plants; and the result of extending the Federal renewable production tax credit (PTC). It also discusses the relationship between natural gas and oil prices and the basis of the world oil price and production trends in AEO2009.

  16. New England electricity supply outlook: Summer 1998 -- and beyond

    SciTech Connect (OSTI)

    NONE

    1998-07-01T23:59:59.000Z

    New England is in the third summer of a protracted electricity supply shortage that began with the shutdown of a substantial quantity of nuclear generating capacity, particularly the 2,630 megawatts (MW) from the three Millstone units located in Connecticut and owned and operated by Northeast Utilities. This report was prepared in response to a request from Senator Christopher Dodd and Senator Joseph Lieberman, both of Connecticut, that the Department of Energy provide an update of its June 1997 report, New England Electricity Supply Outlook, Summer 1997--and Beyond, which examines measures that might be taken to ease the supply shortage, particularly measured to relieve transmission constraints that restrict the import of electricity into Connecticut. In the interval since the 1997 report, three changes have occurred in the region`s overall electric supply context that are particularly significant: the Millstone 3 nuclear unit (1,150 MW) has been put back into service at full capacity; electricity demand is higher, due primarily to regional economic growth. The region`s projected 1998 peak demand is 22,100 MW, 1,531 MW higher than the region`s 1997 peak; and many new additions to the region`s generating capacity have been announced, with projected completion dates varying between 1999 and 2002. If all of the announced projects were completed--which appears unlikely--the total additions would exceed 25,000 MW. A small number of new transmission projects have also been announced.

  17. Proceedings: Energy-efficient office technologies: The outlook and market

    SciTech Connect (OSTI)

    Brown, D.; Gould, S.; Halperson, C. (Policy Research Associates, Inc., Reston, VA (United States))

    1992-12-01T23:59:59.000Z

    Energy-Efficient Office Technologies. The Outlook and Market Workshop held from June 17 to 18, 1992, in San Jose, California, was planned with the goal of developing and implementing strategies to make more energy-efficient office automation equipment a part of the modern business environment. The consumption of electricity in the office environment has increased dramatically since the advent of the desktop personal computer for the mass market. During that same period, other office automation equipment, such as facsimile machines (faxes) and convenience copiers, has also proliferated, contributing to a dramatic increase in plug loads. Participants in the workshop gathered in plenary session to hear a series of stage-setting'' informal presentations, then divided into three concurrent working groups: PCs, Workstations, and Terminals; Imaging Technologies: Printers, Copiers, and Facsimile Machines; and LANS, Software, and Telecommunications. These working groups developed brief consensus statements of the state of the art and trends in energy efficiency and power management; user acceptance; and energy-efficiency implementation strategies. More complete statistics on power consumption by office equipment are needed to heighten awareness among end users and to facilitate better design for new office space. The collaboration of manufacturers, customers, and energy suppliers across international boundaries is critical to identify mechanisms to improve energy performance in the commercial office environment The most promising strategies will work best if they are voluntary, market-driven, and are truly the end result of a common vision.

  18. The Wind Forecast Improvement Project (WFIP): A Public/Private...

    Office of Environmental Management (EM)

    The Wind Forecast Improvement Project (WFIP): A PublicPrivate Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The...

  19. Forecasting of Solar Radiation Detlev Heinemann, Elke Lorenz, Marco Girodo

    E-Print Network [OSTI]

    Heinemann, Detlev

    Forecasting of Solar Radiation Detlev Heinemann, Elke Lorenz, Marco Girodo Oldenburg University have been presented more than twenty years ago (Jensenius, 1981), when daily solar radiation forecasts

  20. Alternative methods for forecasting GDP Dominique Gugan

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    analysis. Better forecast performance for macroeconomic variables will lead to Paris School of Economics the speed of computers that can develop search algorithms from appropriate selection criteria, Devroye. 1 Introduction Forecasting macroeconomic variables such as GDP and inflation play an important role

  1. 2013 Midyear Economic Forecast Sponsorship Opportunity

    E-Print Network [OSTI]

    de Lijser, Peter

    2013 Midyear Economic Forecast Sponsorship Opportunity Thursday, April 18, 2013, ­ Hyatt Regency Irvine 11:30 a.m. ­ 1:30 p.m. Dr. Anil Puri presents his annual Midyear Economic Forecast addressing and Economics at California State University, Fullerton, the largest accredited business school in California

  2. Dynamic Algorithm for Space Weather Forecasting System

    E-Print Network [OSTI]

    Fischer, Luke D.

    2011-08-08T23:59:59.000Z

    /effective forecasts, and we have performed preliminary benchmarks on this algorithm. The preliminary benchmarks yield surprisingly effective results thus far?forecasts have been made 8-16 hours into the future with significant magnitude and trend accuracy, which is a...

  3. Nonparametric models for electricity load forecasting

    E-Print Network [OSTI]

    Genève, Université de

    Electricity consumption is constantly evolving due to changes in people habits, technological innovations1 Nonparametric models for electricity load forecasting JANUARY 23, 2015 Yannig Goude, Vincent at University Paris-Sud 11 Orsay. His research interests are electricity load forecasting, more generally time

  4. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand, EndUser Natural Gas Demand, and Energy Efficiency SEPTEMBER 2013 CEC2002013004SDV1REV CALIFORNIA The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 1: Statewide Electricity Demand and Methods

  5. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1994-02-01T23:59:59.000Z

    This publication documents the load forecast scenarios and assumptions used to prepare BPA`s Whitebook. It is divided into: intoduction, summary of 1993 Whitebook electricity demand forecast, conservation in the load forecast, projection of medium case electricity sales and underlying drivers, residential sector forecast, commercial sector forecast, industrial sector forecast, non-DSI industrial forecast, direct service industry forecast, and irrigation forecast. Four appendices are included: long-term forecasts, LTOUT forecast, rates and fuel price forecasts, and forecast ranges-calculations.

  6. Figure 1. Day 1 SPC Fire Weather Outlook graphic showing a critical area over parts of the western U.S.,

    E-Print Network [OSTI]

    Figure 1. Day 1 SPC Fire Weather Outlook graphic showing a critical area over parts of the western. INTRODUCTION The Storm Prediction Center (SPC) in Norman, OK prepares national Fire Weather Outlooks valid thunderstorms, result in a significant threat of wildfires. The SPC Fire Weather Outlook contains both a text

  7. Annual Energy Outlook 2013 with Projections to 2040

    SciTech Connect (OSTI)

    none,

    2013-04-01T23:59:59.000Z

    The Annual Energy Outlook 2013 (AEO2013), prepared by the U.S. Energy Information Administration (EIA), presents long-term projections of energy supply, demand, and prices through 2040, based on results from EIA’s National Energy Modeling System. The report begins with an “Executive summary” that highlights key aspects of the projections. It is followed by a “Legislation and regulations” section that discusses evolving legislative and regulatory issues, including a summary of recently enacted legislation and regulations, such as: Updated handling of the U.S. Environmental Protection Agency’s (EPA) National Emissions Standards for Hazardous Air Pollutants for industrial boilers and process heaters; New light-duty vehicle (LDV) greenhouse gas (GHG) and corporate average fuel economy (CAFE) standards for model years 2017 to 2025; Reinstatement of the Clean Air Interstate Rule (CAIR) after the court’s announcement of intent to vacate the Cross-State Air Pollution Rule (CSAPR); and Modeling of California’s Assembly Bill 32, the Global Warming Solutions Act (AB 32), which allows for representation of a cap-and-trade program developed as part of California’s GHG reduction goals for 2020. The “Issues in focus” section contains discussions of selected energy topics, including a discussion of the results in two cases that adopt different assumptions about the future course of existing policies, with one case assuming the elimination of sunset provisions in existing policies and the other case assuming the elimination of the sunset provisions and the extension of a selected group of existing public policies—CAFE standards, appliance standards, and production tax credits. Other discussions include: oil price and production trends in AEO2013; U.S. reliance on imported liquids under a range of cases; competition between coal and natural gas in electric power generation; high and low nuclear scenarios through 2040; and the impact of growth in natural gas liquids production. The “Market trends” section summarizes the projections for energy markets. The analysis in AEO2013 focuses primarily on a Reference case, Low and High Economic Growth cases, and Low and High Oil Price cases. Results from a number of other alternative cases also are presented, illustrating uncertainties associated with the Reference case projections for energy demand, supply, and prices. Complete tables for the five primary cases are provided in Appendixes A through C. Major results from many of the alternative cases are provided in Appendix D. Complete tables for all the alternative cases are available on EIA’s website in a table browser at http://www.eia.gov/oiaf/aeo/tablebrowser. AEO2013 projections are based generally on federal, state, and local laws and regulations in effect as of the end of September 2012. The potential impacts of pending or proposed legislation, regulations, and standards (and sections of existing legislation that require implementing regulations or funds that have not been appropriated) are not reflected in the projections. In certain situations, however, where it is clear that a law or regulation will take effect shortly after the Annual Energy Outlook (AEO) is completed, it may be considered in the projection.

  8. Energy Efficiency Design Options for Residential Water Heaters: Economic Impacts on Consumers

    E-Print Network [OSTI]

    Lekov, Alex

    2011-01-01T23:59:59.000Z

    Administration. 2010. Annual Energy Outlook 2010 withthe price forecasts in EIA’s Annual Energy Outlook 2010. The

  9. NP2010: An Assessment and Outlook for Nuclear Physics

    SciTech Connect (OSTI)

    Lancaster, James

    2014-05-22T23:59:59.000Z

    This grant provided partial support for the National Research Council’s (NRC) decadal survey of nuclear physics. This is part of NRC’s larger effort to assess and discuss the outlook for different fields in physics and astronomy, Physics 2010, which takes place approximately every ten years. A report has been prepared as a result of the study that is intended to inform those who are interested about the current status of research in this area and to help guide future developments of the field. A pdf version of the report is available for download, for free, at http://www.nap.edu/catalog.php?record_id=13438. Among the principal conclusions reached in the report are that the nuclear physics program in the United States has been especially well managed, principally through a recurring long-range planning process conducted by the community, and that current opportunities developed pursuant to that planning process should be exploited. In the section entitled “Building the Foundation for the Future,” the report notes that attention needs to be paid to certain elements that are essential to the continued vitality of the field. These include ensuring that education and research at universities remain a focus for funding and that a plan be developed to ensure that forefront-computing resources, including exascale capabilities when developed, be made available to nuclear science researchers. The report also notes that nimbleness is essential for the United States to remain competitive in a rapidly expanding international nuclear physics arena and that streamlined and flexible procedures should be developed for initiating and managing smaller-scale nuclear science projects.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19T23:59:59.000Z

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

  13. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST

    E-Print Network [OSTI]

    procurement process at the California Public Utilities Commission. This forecast was produced with the Energy Commission demand forecast models. Both the staff draft energy consumption and peak forecasts are slightly and commercial sectors. Keywords Electricity demand, electricity consumption, demand forecast, weather

  14. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    and water pumping sectors. Mark Ciminelli forecasted energy for transportation, communication and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data at the California Public Utilities Commission. This forecast was produced with the Energy Commission demand forecast

  15. Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)

    SciTech Connect (OSTI)

    Hodge, B. M.; Ela, E.; Milligan, M.

    2011-10-01T23:59:59.000Z

    This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

  16. 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]

    Islam, M. Saif

    Page 1 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 take a few moments to answer this short survey

  17. PSO (FU 2101) Ensemble-forecasts for wind power

    E-Print Network [OSTI]

    PSO (FU 2101) Ensemble-forecasts for wind power Analysis of the Results of an On-line Wind Power Ensemble- forecasts for wind power (FU2101) a demo-application producing quantile forecasts of wind power correct) quantile forecasts of the wind power production are generated by the application. However

  18. 1993 Solid Waste Reference Forecast Summary

    SciTech Connect (OSTI)

    Valero, O.J.; Blackburn, C.L. [Westinghouse Hanford Co., Richland, WA (United States); Kaae, P.S.; Armacost, L.L.; Garrett, S.M.K. [Pacific Northwest Lab., Richland, WA (United States)

    1993-08-01T23:59:59.000Z

    This report, which updates WHC-EP-0567, 1992 Solid Waste Reference Forecast Summary, (WHC 1992) forecasts the volumes of solid wastes to be generated or received at the US Department of Energy Hanford Site during the 30-year period from FY 1993 through FY 2022. The data used in this document were collected from Westinghouse Hanford Company forecasts as well as from surveys of waste generators at other US Department of Energy sites who are now shipping or plan to ship solid wastes to the Hanford Site for disposal. These wastes include low-level and low-level mixed waste, transuranic and transuranic mixed waste, and nonradioactive hazardous waste.

  19. Max Tech Appliance Design: Potential for Maximizing U.S. Energy Savings through Standards

    E-Print Network [OSTI]

    Garbesi, Karina

    2011-01-01T23:59:59.000Z

    Administration, Annual Energy Outlook. Can be downloaded at:forecasts in its Annual Energy Outlook (AEO) [2], based onaeo/overview/). In its Annual Energy Outlook (AEO) (http://

  20. Modeling the Capacity and Emissions Impacts of Reduced Electricity Demand. Part 1. Methodology and Preliminary Results.

    E-Print Network [OSTI]

    Coughlin, Katie

    2013-01-01T23:59:59.000Z

    2011).pdf. ———. 2012a. “Annual Energy Outlook (AEO) 2012. ”2013. “Annual Energy Outlook - Model Documentation. ”forecast, the Annual Energy Outlook (AEO) (DOE EIA 2012a).

  1. New Method and Reporting of Uncertainty in LBNL National Energy Modeling System Runs

    E-Print Network [OSTI]

    Gumerman, Etan Z.; LaCommare, Kristina Hamachi; Marnay, Chris

    2002-01-01T23:59:59.000Z

    PV Quad SO 2 TWh Annual Energy Outlook combined GPRA caseshows the most recent Annual Energy Outlook (AEO) value, theradical. The Annual Energy Outlook forecasts unrestricted

  2. Characterizing emerging industrial technologies in energy models

    E-Print Network [OSTI]

    Laitner, John A. Skip; Worrell, Ernst; Galitsky, Christina; Hanson, Donald A.

    2003-01-01T23:59:59.000Z

    EIA), 2001. “Annual Energy Outlook 2002,” Energy Informationas forecasted in the Annual Energy Outlook 2002, we estimateQuads based on the Annual Energy Outlook 2002 (AEO 2002) (

  3. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    supervised data preparation. Steven Mac and Keith O'Brien prepared the historical energy consumption data. Nahid Movassagh forecasted consumption for the agriculture and water pumping sectors. Cynthia Rogers generation, conservation, energy efficiency, climate zone, investorowned, public, utilities, additional

  4. Wind Speed Forecasting for Power System Operation 

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

    In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

  5. STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES

    E-Print Network [OSTI]

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

  6. Wind Speed Forecasting for Power System Operation

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

    In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

  7. Potential Economic Value of Seasonal Hurricane Forecasts

    E-Print Network [OSTI]

    Emanuel, Kerry Andrew

    This paper explores the potential utility of seasonal Atlantic hurricane forecasts to a hypothetical property insurance firm whose insured properties are broadly distributed along the U.S. Gulf and East Coasts. Using a ...

  8. Text-Alternative Version LED Lighting Forecast

    Broader source: Energy.gov [DOE]

    The DOE report Energy Savings Forecast of Solid-State Lighting in General Illumination Applications estimates the energy savings of LED white-light sources over the analysis period of 2013 to 2030....

  9. Essays in International Macroeconomics and Forecasting

    E-Print Network [OSTI]

    Bejarano Rojas, Jesus Antonio

    2012-10-19T23:59:59.000Z

    This dissertation contains three essays in international macroeconomics and financial time series forecasting. In the first essay, I show, numerically, that a two-country New-Keynesian Sticky Prices model, driven by monetary and productivity shocks...

  10. olitically speaking, the outlook for the World Summit on Sustainable Devel-

    E-Print Network [OSTI]

    Kammen, Daniel M.

    P olitically speaking, the outlook for the World Summit on Sustainable Devel- opment is grim days discussing how the world can continue to develop without jeopardizing the Earth's resources of fresh water reserves, the use of unsustainable energy sources, food security, habitat loss Few observers

  11. ACM Outlook, Volume 24, No. 4, Oct. 1996, pp. 24-9. The Electronic Issue Forum

    E-Print Network [OSTI]

    Peha, Jon M.

    1 ACM Outlook, Volume 24, No. 4, Oct. 1996, pp. 24-9. The Electronic Issue Forum: A Tool for Distance Learning Jon M. Peha Carnegie Mellon University Abstract This paper describes Electronic Issue for distance learning. Electronic issue forums incite valuable student interactions that are often lost when

  12. ORNL/TM-2011/101 Status and Outlook for the U.S.

    E-Print Network [OSTI]

    ORNL/TM-2011/101 Status and Outlook for the U.S. Non-Automotive Fuel Cell Industry FUEL CELL INDUSTRY: IMPACTS OF GOVERNMENT POLICIES AND ASSESSMENT OF FUTURE OPPORTUNITIES David .................................................................................................. 5 3. THE U.S. INDUSTRY IN 2010

  13. Duke Health Briefs: Positive Outlook Linked to Longer Life in Heart Patients

    E-Print Network [OSTI]

    Hunter, David

    Duke Health Briefs: Positive Outlook Linked to Longer Life in Heart Patients keywords : CardiologyMinute. Here's some health advice to take to heart: if you want to live longer, stay happy. A recent Duke study of more than 800 heart patients found that those who reported experiencing more positive emotions

  14. State-of-the-Art and Outlook: Thermal Properties of Phase Change Wallboard Rooms 

    E-Print Network [OSTI]

    Feng, G.; Liang, R.; Li, G.

    2006-01-01T23:59:59.000Z

    ICEBO2006, Shenzhen, China Envelope Technologies for Building Energy Efficiency Vol.II-2-4 State-of-the Art and Outlook: Thermal Properties of Phase Change Wallboard Rooms1 Guohui Feng Ruobing Liang Li Gang Ph.D. Professor...

  15. Economic Outlook 20122013 12/9/2011 Marshall J. Vest, mvest@eller.arizona.edu

    E-Print Network [OSTI]

    Wong, Pak Kin

    Growth, TUS (retail, restaurant & bar, food, and gasoline) NominalReal 20 #12;Economic Outlook 20122013 and hiring "on hold" Housing woes Distressed sales Falling prices Population mobility ­ lowest since 1948 facing a long list of negatives but spending anyway Retail sales up 9.1% through October (Y/Y) Led

  16. CLOUD GAMING ONWARD: RESEARCH OPPORTUNITIES AND OUTLOOK Kuan-Ta Chen1

    E-Print Network [OSTI]

    Chen, Sheng-Wei

    CLOUD GAMING ONWARD: RESEARCH OPPORTUNITIES AND OUTLOOK Kuan-Ta Chen1 , Chun-Ying Huang2 ABSTRACT Cloud gaming has become increasingly more popular in the academia and the industry, evident by the large numbers of related research papers and startup companies. Some pub- lic cloud gaming services have

  17. HVDC Connected Offshore Wind Power Plants: Review and Outlook of Current Research

    E-Print Network [OSTI]

    Bak, Claus Leth

    HVDC Connected Offshore Wind Power Plants: Review and Outlook of Current Research Jakob Glasdam-of-the-art review on grid integration of large offshore wind power plants (OWPPs) using high voltage direct voltage Sørensen Wind Power, Electrical Systems DONG Energy Fredericia, Denmark jakgl@dongenergy.dk Mogens Blanke

  18. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01T23:59:59.000Z

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  19. Forecasting long-term gas production from shale

    E-Print Network [OSTI]

    Cueto-Felgueroso, Luis

    Oil and natural gas from deep shale formations are transforming the United States economy and its energy outlook. Back in 2005, the US Energy Information Administration published projections of United States natural gas ...

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01T23:59:59.000Z

    gas price forecasts with contemporaneous natural gas pricesreference-case natural gas price forecast, and that have notof AEO 2009 Natural Gas Price Forecast to NYMEX Futures

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01T23:59:59.000Z

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

  2. Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    to accurately forecast natural gas prices. Many policyseek alternative methods to forecast natural gas prices. Thethe accuracy of forecasts for natural gas prices as reported

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    gas price forecasts with contemporaneous natural gas pricesreference-case natural gas price forecast, and that have notof AEO 2008 Natural Gas Price Forecast to NYMEX Futures

  4. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    the base-case natural gas price forecast, but to alsogas price forecasts with contemporaneous natural gas pricesof AEO 2010 Natural Gas Price Forecast to NYMEX Futures

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01T23:59:59.000Z

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

  6. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

    Templeton, K.J.; Clary, J.L.

    1994-09-01T23:59:59.000Z

    This report describes a 30-year forecast of the solid waste volumes by container type. The volumes described are low-level mixed waste (LLMW) and transuranic/transuranic mixed (TRU/TRUM) waste. These volumes and their associated container types will be generated or received at the US Department of Energy Hanford Site for storage, treatment, and disposal at Westinghouse Hanford Company`s Solid Waste Operations Complex (SWOC) during a 30-year period from FY 1994 through FY 2023. The forecast data for the 30-year period indicates that approximately 307,150 m{sup 3} of LLMW and TRU/TRUM waste will be managed by the SWOC. The main container type for this waste is 55-gallon drums, which will be used to ship 36% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of 55-gallon drums is Past Practice Remediation. This waste will be generated by the Environmental Restoration Program during remediation of Hanford`s past practice sites. Although Past Practice Remediation is the primary generator of 55-gallon drums, most waste generators are planning to ship some percentage of their waste in 55-gallon drums. Long-length equipment containers (LECs) are forecasted to contain 32% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of LECs is the Long-Length Equipment waste generator, which is responsible for retrieving contaminated long-length equipment from the tank farms. Boxes are forecasted to contain 21% of the waste. These containers are primarily forecasted for use by the Environmental Restoration Operations--D&D of Surplus Facilities waste generator. This waste generator is responsible for the solid waste generated during decontamination and decommissioning (D&D) of the facilities currently on the Surplus Facilities Program Plan. The remaining LLMW and TRU/TRUM waste volume is planned to be shipped in casks and other miscellaneous containers.

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

    E-Print Network [OSTI]

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

    2000-01-01T23:59:59.000Z

    of the Department of Energy's Office of Industrial Technologies, EIA extracted energy use infonnation from the Annual Energy Outlook (AEO) - 2000 (8) for each of the seven # The Pacific Northwest National Laboratory is operated by Battelle Memorial Institute... Energy Technology Conference, Houston, Texas, pp.115-124. 7. U.S. Department of Energy. 1994. Manufacturing Consumption ofEnergy, J99J. DOEIEIA-0512(91). Washington, D. C. 8. U.S. Department of Energy. 1999. Annual Energy Outlook. 2000...

  8. Energy Use in China: Sectoral Trends and Future Outlook

    SciTech Connect (OSTI)

    Zhou, Nan; McNeil, Michael A.; Fridley, David; Lin, Jiang; Price,Lynn; de la Rue du Can, Stephane; Sathaye, Jayant; Levine, Mark

    2007-10-04T23:59:59.000Z

    This report provides a detailed, bottom-up analysis ofenergy consumption in China. It recalibrates official Chinese governmentstatistics by reallocating primary energy into categories more commonlyused in international comparisons. It also provides an analysis of trendsin sectoral energy consumption over the past decades. Finally, itassesses the future outlook for the critical period extending to 2020,based on assumptions of likely patterns of economic activity,availability of energy services, and energy intensities. The followingare some highlights of the study's findings: * A reallocation of sectorenergy consumption from the 2000 official Chinese government statisticsfinds that: * Buildings account for 25 percent of primary energy, insteadof 19 percent * Industry accounts for 61 percent of energy instead of 69percent * Industrial energy made a large and unexpected leap between2000-2005, growing by an astonishing 50 percent in the 3 years between2002 and 2005. * Energy consumption in the iron and steel industry was 40percent higher than predicted * Energy consumption in the cement industrywas 54 percent higher than predicted * Overall energy intensity in theindustrial sector grew between 2000 and 2003. This is largely due tointernal shifts towards the most energy-intensive sub-sectors, an effectwhich more than counterbalances the impact of efficiency increases. *Industry accounted for 63 percent of total primary energy consumption in2005 - it is expected to continue to dominate energy consumption through2020, dropping only to 60 percent by that year. * Even assuming thatgrowth rates in 2005-2020 will return to the levels of 2000-2003,industrial energy will grow from 42 EJ in 2005 to 72 EJ in 2020. * Thepercentage of transport energy used to carry passengers (instead offreight) will double from 37 percent to 52 percent between 2000 to 2020,.Much of this increase is due to private car ownership, which willincrease by a factor of 15 from 5.1 million in 2000 to 77 million in2020. * Residential appliance ownership will show signs of saturation inurban households. The increase in residential energy consumption will belargely driven by urbanization, since rural homes will continue to havelow consumption levels. In urban households, the size of appliances willincrease, but its effect will be moderated by efficiency improvements,partially driven by government standards. * Commercial energy increaseswill be driven both by increases in floor space and by increases inpenetration of major end uses such as heating and cooling. Theseincreases will be moderated somewhat, however, by technology changes,such as increased use of heat pumps. * China's Medium- and Long-TermDevelopment plan drafted by the central government and published in 2004calls for a quadrupling of GDP in the period from 2000-2020 with only adoubling in energy consumption during the same period. A bottom-upanalysis with likely efficiency improvements finds that energyconsumption will likely exceed the goal by 26.12 EJ, or 28 percent.Achievements of these goals will there fore require a more aggressivepolicy of encouraging energy efficiency.

  9. Comparing Price Forecast Accuracy of Natural Gas Models andFutures Markets

    SciTech Connect (OSTI)

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

    2005-06-30T23:59:59.000Z

    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.

  10. Outlook for renewable energy technologies: Assessment of international programs and policies

    SciTech Connect (OSTI)

    Branstetter, L.J.; Vidal, R.C.; Bruch, V.L.; Zurn, R.

    1995-02-01T23:59:59.000Z

    The report presents an evaluation of worldwide research efforts in three specific renewable energy technologies, with a view towards future United States (US) energy security, environmental factors, and industrial competitiveness. The overall energy technology priorities of foreign governments and industry leaders, as well as the motivating factors for these priorities, are identified and evaluated from both technological and policy perspectives. The specific technologies of interest are wind, solar thermal, and solar photovoltaics (PV). These program areas, as well as the overall energy policies of Denmark, France, Germany, Italy, the United Kingdom (UK), Japan, Russia, and the European Community as a whole are described. The present and likely future picture for worldwide technological leadership in these technologies-is portrayed. The report is meant to help in forecasting challenges to US preeminence in the various technology areas, particularly over the next ten years, and to help guide US policy-makers as they try to identify specific actions which would help to retain and/or expand the US leadership position.

  11. Situation and outlook for foreign and domestic rice trade: recommendations to expand U.S. market share 

    E-Print Network [OSTI]

    Bates, Kathy

    1991-01-01T23:59:59.000Z

    SITUATION AND OUTLOOK FOR FOREIGN AND DOMESTIC RICE TRADE: RECOMMENDATIONS TO EXPAND U. S. MARKET SHARE A Professional Paper by Kathy Bates Submitted to the College of Agriculture and Life Sciences of Texas A&M University in partial... was compiled, I created a 157 page circular which was approved by the World Agricultural Outlook Board and published in October of 1989. This publication contains the latest available supply and distribution estimates for each country in the Foreign...

  12. Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast Role of the Economic Forecast..................................................................................................................................... 2 Economic Growth Assumptions

  13. Viability, Development, and Reliability Assessment of Coupled Coastal Forecasting Systems

    E-Print Network [OSTI]

    Singhal, Gaurav

    2012-10-19T23:59:59.000Z

    disaster, Cook Inlet (CI) and Prince William Sound (PWS) are regions that suffer from a lack of accurate wave forecast information. This dissertation develops high- resolution integrated wave forecasting schemes for these regions in order to meet...

  14. Potential to Improve Forecasting Accuracy: Advances in Supply Chain Management

    E-Print Network [OSTI]

    Datta, Shoumen

    2008-07-31T23:59:59.000Z

    Forecasting is a necessity almost in any operation. However, the tools of forecasting are still primitive in view of the great strides made by research and the increasing abundance of data made possible by automatic ...

  15. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output Perturbation

    E-Print Network [OSTI]

    Washington at Seattle, University of

    Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output. This is typically not feasible for mesoscale weather prediction carried out locally by organizations without by simulating realizations of the geostatistical model. The method is applied to 48-hour mesoscale forecasts

  16. The effect of multinationality on management earnings forecasts

    E-Print Network [OSTI]

    Runyan, Bruce Wayne

    2005-08-29T23:59:59.000Z

    This study examines the relationship between a firm??s degree of multinationality and its managers?? earnings forecasts. Firms with a high degree of multinationality are subject to greater uncertainty regarding earnings forecasts due...

  17. Wind Power Forecasting Error Distributions over Multiple Timescales (Presentation)

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01T23:59:59.000Z

    This presentation presents some statistical analysis of wind power forecast errors and error distributions, with examples using ERCOT data.

  18. Weighted Parametric Operational Hydrology Forecasting Thomas E. Croley II1

    E-Print Network [OSTI]

    1 Weighted Parametric Operational Hydrology Forecasting Thomas E. Croley II1 1 Great Lakes forecasts in operational hydrology builds a sample of possibilities for the future, of climate series from-parametric method can be extended into a new weighted parametric hydrological forecasting technique to allow

  19. A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION

    E-Print Network [OSTI]

    Boyer, Edmond

    1 A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION in the realm of solar radiation forecasting. In this work, two forecasting models: Autoregressive Moving. The very first results show an improvement brought by this approach. 1. INTRODUCTION Solar radiation

  20. AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.

    E-Print Network [OSTI]

    Povinelli, Richard J.

    AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

  1. Univariate Modeling and Forecasting of Monthly Energy Demand Time Series

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural dedicated models to forecast the 12 individual months directly. Results indicate better performance is superior to naïve forecasts based on persistence and seasonality, and is better than results quoted

  2. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    requirements. The transportation energy demand forecasts make assumptions about fuel price forecastsCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY ENERGY COMMISSION Gordon Schremp, Jim Page, and Malachi Weng-Gutierrez Principal Authors Jim Page Project

  3. PSO (FU 2101) Ensemble-forecasts for wind power

    E-Print Network [OSTI]

    PSO (FU 2101) Ensemble-forecasts for wind power Wind Power Ensemble Forecasting Using Wind Speed the problems of (i) transforming the meteorological ensembles to wind power ensembles and, (ii) correcting) data. However, quite often the actual wind power production is outside the range of ensemble forecast

  4. A first large-scale flood inundation forecasting model

    SciTech Connect (OSTI)

    Schumann, Guy J-P; Neal, Jeffrey C.; Voisin, Nathalie; Andreadis, Konstantinos M.; Pappenberger, Florian; Phanthuwongpakdee, Kay; Hall, Amanda C.; Bates, Paul D.

    2013-11-04T23:59:59.000Z

    At present continental to global scale flood forecasting focusses on predicting at a point discharge, with little attention to the detail and accuracy of local scale inundation predictions. Yet, inundation is actually the variable of interest and all flood impacts are inherently local in nature. This paper proposes a first large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas and at continental scales. The model was built for the Lower Zambezi River in southeast Africa to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. The inundation model domain has a surface area of approximately 170k km2. ECMWF meteorological data were used to force the VIC (Variable Infiltration Capacity) macro-scale hydrological model which simulated and routed daily flows to the input boundary locations of the 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of many river channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst at the same time representing the floodplain at an appropriate and efficient scale. The modeling system was first calibrated using water levels on the main channel from the ICESat (Ice, Cloud, and land Elevation Satellite) laser altimeter and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of about 1 km (one model resolution) compared to an observed flood edge of the event. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2. However, initial model test runs in forecast mode revealed that it is crucial to account for basin-wide hydrological response time when assessing lead time performances notwithstanding structural limitations in the hydrological model and possibly large inaccuracies in precipitation data.

  5. Navy Mobility Fuels Forecasting System Phase 4 report

    SciTech Connect (OSTI)

    Das, S.; Hadder, G.R.; Leiby, P.N.; Lee, R.; Davis, R.M.

    1988-09-01T23:59:59.000Z

    The Department of Navy's Maritime Strategy is designed to maintain military readiness and the ability to operate in all major theaters of the world. Mobility fuels required for sea, air, and land operations are vital components of the Navy's peacetime and wartime strategies. The purpose of the Navy's Mobility Fuels Technology Program is to understand fuel supply and fuel property impacts on Navy equipment performance and fleet readiness and operations. Oak Ridge National Laboratory (ORNL) has assisted the Department of Navy in developing and testing a methodology for forecasting mobility fuel availability, quality, and relative price, as well as evaluating options to increase fuel supplies during world oil supply disruptions. Publicly available models developed by the Energy Information Administration of the Department of Energy were selected as the foundation of the Navy Mobility Fuels Forecasting System (NMFFS). The NMFFS was enhanced as ORNL reviewed data on world oil reserves, production and prices, trends in crude oil and refined product quality, and changes in refinery process technology. The system was used to analyze the availability, quality, and relative price of military fuels that could be produced in several domestic and foreign refining regions under Business-As-Usual (BAU) and two hypothetical world crude oil disruption scenarios in the year 1995. 25 refs., 11 figs., 29 tabs.

  6. Evaluating state markets for residential wind systems: Results from an economic and policy analysis tool

    E-Print Network [OSTI]

    Edwards, Jennifer L.; Wiser, Ryan; Bolinger, Mark; Forsyth, Trudy

    2004-01-01T23:59:59.000Z

    Administration (2003). Annual Energy Outlook 2003. DOE/EIA-SP SWAT TVA USDA Annual Energy Outlook American Wind Energyaccording to the 2003 Annual Energy Outlook. Although this

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

    E-Print Network [OSTI]

    Lang, K.

    1982-01-01T23:59:59.000Z

    capital requirements and research and development programs in the alum inum industry. : CONCLUSIONS Forecasting the use of conservation techndlo gies with a market penetration model provides la more accountable method of projecting aggrega...

  8. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    , Gary Occhiuzzo, and Keith O'Brien prepared the historical energy consumption data. Nahid Movassagh forecasted consumption for the agriculture and water pumping sectors. Don Schultz and Doug Kemmer developed. California Energy Commission, Electricity Supply Analysis Division. Publication Number: CEC2002012001CMFVI

  9. Facebook IPO updated valuation and user forecasting

    E-Print Network [OSTI]

    Facebook IPO ­ updated valuation and user forecasting Based on: Amendment No. 6 to Form S-1 (May 9. Peter Cauwels and Didier Sornette, Quis pendit ipsa pretia: facebook valuation and diagnostic Extreme Growth JPMPaper Cauwels and Sornette 840 1110 1820 S1- filing- May 9 2012 1006 1105 1371 Facebook

  10. Modeling of Uncertainty in Wind Energy Forecast

    E-Print Network [OSTI]

    regression and splines are combined to model the prediction error from Tunø Knob wind power plant. This data of the thesis is quantile regression and splines in the context of wind power modeling. Lyngby, February 2006Modeling of Uncertainty in Wind Energy Forecast Jan Kloppenborg Møller Kongens Lyngby 2006 IMM-2006

  11. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Sripada, Yaji

    for generating textual summaries. Our algorithm has been implemented in a weather forecast generation system. 1 presentation, aid human understanding of the underlying data sets. SUMTIME is a research project aiming turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP

  12. Forecasting sudden changes in environmental pollution patterns

    E-Print Network [OSTI]

    Olascoaga, Maria Josefina

    Forecasting sudden changes in environmental pollution patterns María J. Olascoagaa,1 and George of Mexico in 2010. We present a methodology to predict major short-term changes in en- vironmental River's mouth in the Gulf of Mexico. The resulting fire could not be extinguished and the drilling rig

  13. New Concepts in Wind Power Forecasting Models

    E-Print Network [OSTI]

    Kemner, Ken

    New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, João Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind characteristics (mainly speed and direction) in wind parks connected to a power grid. Renyi's Entropy is combined

  14. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand, EndUser Natural Gas Demand, and Energy Efficiency DECEMBER 2013 CEC2002013004SFV1 CALIFORNIA and expertise of numerous California Energy Commission staff members in the Demand Analysis Office. In addition

  15. SIMULATION AND FORECASTING IN INTERMODAL CONTAINER TERMINAL

    E-Print Network [OSTI]

    Gambardella, Luca Maria

    SIMULATION AND FORECASTING IN INTERMODAL CONTAINER TERMINAL Luca Maria Gambardella1 , Gianluca@idsia.ch 2 LCST, La Spezia Container Terminal, La Spezia (IT) 3 DSP, Data System & Planning sa, Manno (CH working in intermodal container terminals. INTRODUCTION The amount of work a container terminal deals

  16. Forecast Technical Document Felling and Removals

    E-Print Network [OSTI]

    of local investment and business planning. Timber volume production will be estimated at sub. Planning of operations. Control of the growing stock. Wider reporting (under UKWAS). The calculation fellings and removals are handled in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan

  17. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27T23:59:59.000Z

    This paper presents a nonparametric diffusion modeling approach for forecasting partially observed noisy turbulent modes. The proposed forecast model uses a basis of smooth functions (constructed with the diffusion maps algorithm) to represent probability densities, so that the forecast model becomes a linear map in this basis. We estimate this linear map by exploiting a previously established rigorous connection between the discrete time shift map and the semi-group solution associated to the backward Kolmogorov equation. In order to smooth the noisy data, we apply diffusion maps to a delay embedding of the noisy data, which also helps to account for the interactions between the observed and unobserved modes. We show that this delay embedding biases the geometry of the data in a way which extracts the most predictable component of the dynamics. The resulting model approximates the semigroup solutions of the generator of the underlying dynamics in the limit of large data and in the observation noise limit. We will show numerical examples on a wide-range of well-studied turbulent modes, including the Fourier modes of the energy conserving Truncated Burgers-Hopf (TBH) model, the Lorenz-96 model in weakly chaotic to fully turbulent regimes, and the barotropic modes of a quasi-geostrophic model with baroclinic instabilities. In these examples, forecasting skills of the nonparametric diffusion model are compared to a wide-range of stochastic parametric modeling approaches, which account for the nonlinear interactions between the observed and unobserved modes with white and colored noises.

  18. Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price forecast of the Fifth Northwest Power

    E-Print Network [OSTI]

    Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price as traded on the wholesale, short-term (spot) market at the Mid-Columbia trading hub. This price represents noted. BASE CASE FORECAST The base case wholesale electricity price forecast uses the Council's medium

  19. Operational forecasting based on a modified Weather Research and Forecasting model

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18T23:59:59.000Z

    Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

  20. Forecastability as a Design Criterion in Wind Resource Assessment: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01T23:59:59.000Z

    This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

  1. Is China on Track to Comply with Its 2020 Copenhagen Carbon Intensity Commitment?

    E-Print Network [OSTI]

    Yang, Yuan; Zhang, Junjie; Wang, Can

    2014-01-01T23:59:59.000Z

    International Energy Outlook (IEO) 2013 forecasts China’s COto forecast energy consumption directly. The China Energy

  2. CECS Seminar Series "Evaluating GALS Systems for System Integration-Outlook and Future Prospects"

    E-Print Network [OSTI]

    Shinozuka, Masanobu

    for secure energy efficient wireless sensor nodes. In this context the possibilities for energy reduction.Sc. degree in Electrical Engineering at Faculty of Electronic Eng. Nis, Serbia in 2001, and his Dr

  3. Annual Energy Outlook Retrospective Review: Evaluation of 2014 and Prior Reference Case Projections

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline prices4 OilU.S. OffshoreOilAnnual Coal<

  4. Test application of a semi-objective approach to wind forecasting for wind energy applications

    SciTech Connect (OSTI)

    Wegley, H.L.; Formica, W.J.

    1983-07-01T23:59:59.000Z

    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)

  5. Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Clark, C.; Cline, J.; Benjamin, S.; Wilczak, J.; Marquis, M.; Finley, C.; Stern, A.; Freedman, J.

    2012-09-01T23:59:59.000Z

    The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis.

  6. Apples with apples: accounting for fuel price risk in comparisons of gas-fired and renewable generation

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2003-01-01T23:59:59.000Z

    from the EIA’s Annual Energy Outlook 2001 and 2002,forecast contained in Annual Energy Outlook 2003 a seven-forecast contained in Annual Energy Outlook 2003. the six-

  7. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

    Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David

    2014-12-30T23:59:59.000Z

    A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

  8. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J. (Decision and Information Sciences); (INESC Porto)

    2011-02-23T23:59:59.000Z

    The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

  9. Preliminary Evaluation of the Section 1603 Treasury Grant Program for Renewable Power Projects in the United States

    E-Print Network [OSTI]

    Bolinger, Mark

    2012-01-01T23:59:59.000Z

    EIA). 2009a. Annual Energy Outlook 2009 (Updated Reference2009b. Annual Energy Outlook 2009 (Originally Publishedfrom the EIA’s Annual Energy Outlook 2009 reference case

  10. Preliminary Evaluation of the Impact of the Section 1603 Treasury Grant Program on Renewable Energy Deployment in 2009

    E-Print Network [OSTI]

    Bolinger, Mark

    2010-01-01T23:59:59.000Z

    EIA). 2009a. Annual Energy Outlook 2009 (Updated Reference2009b. Annual Energy Outlook 2009 (Originally Publishedfrom the EIA’s Annual Energy Outlook 2009 reference case

  11. Why Models Don%3CU%2B2019%3Et Forecast.

    SciTech Connect (OSTI)

    McNamara, Laura A.

    2010-08-01T23:59:59.000Z

    The title of this paper, Why Models Don't Forecast, has a deceptively simple answer: models don't forecast because people forecast. Yet this statement has significant implications for computational social modeling and simulation in national security decision making. Specifically, it points to the need for robust approaches to the problem of how people and organizations develop, deploy, and use computational modeling and simulation technologies. In the next twenty or so pages, I argue that the challenge of evaluating computational social modeling and simulation technologies extends far beyond verification and validation, and should include the relationship between a simulation technology and the people and organizations using it. This challenge of evaluation is not just one of usability and usefulness for technologies, but extends to the assessment of how new modeling and simulation technologies shape human and organizational judgment. The robust and systematic evaluation of organizational decision making processes, and the role of computational modeling and simulation technologies therein, is a critical problem for the organizations who promote, fund, develop, and seek to use computational social science tools, methods, and techniques in high-consequence decision making.

  12. Table of Contents Page 2National High Magnetic Field Laboratory and Its Forecasted Impact on the Florida Economy

    E-Print Network [OSTI]

    Weston, Ken

    Impact on the Florida Economy History and Evaluation of the Economic Impact of the Magnet Lab Forecasted Impact on the Florida Economy The National Science Foundation (NSF) awarded the National High generated by Magnet Lab activities across the broader statewide economy. Since 1990, the Magnet Lab has

  13. 49th Annual international outlook issue. [World oil gas exploration and development trends

    SciTech Connect (OSTI)

    Not Available

    1994-08-01T23:59:59.000Z

    This article represents the World Oil's 49th annual outlook. It discusses oil and gas exploration information, pricing, drilling activity, production, and reserves. It discusses the various reasons for increases or decreases in drilling activity in the various production regions of the earth. The article is broken down into the various geo-political regions and each region is described individually. These regions are described as North America, South America, Western Europe, Eastern Europe, Africa, the Middle East, the Far East (China, Indonesia, Viet Nam, etc.), and the South Pacific (Australia, New Zealand, New Guinea). Information on production, pricing, and drilling is presented in tabular formats along with a narrative discussion.

  14. Short-Term Energy Outlook Supplement: Energy-weighted industrial production indices

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctoberOutlook

  15. Evaluation of the Weather Research and Forecasting Model on

    E-Print Network [OSTI]

    Basu, Sukanta

    : Implications for Wind Energy Brandon Storm*, Wind Science and Engineering Research Center, Texas Tech this region more favorable for wind energy production. At the same time, the presence of LLJs can direct ramifications for renewable wind energy production (e.g. Sisterson and Frenzen8

  16. DISCOVER-AQ Outlook for Monday, July 18, 2011 Good flying conditions are forecasted for Monday, though we should keep an eye on possible late

    E-Print Network [OSTI]

    Humidity Pleasant Weak Front Dying 50% by late afternoon Tuesday Wind Shift #12;Tuesday Humidity >50% Clouds Wind Shift Wind Shift . But timing is difficult. NAM 200 mb winds (knots)/ heights (dm) #12;Tuesday 8 am: Upper level trough moves

  17. Thirty-year solid waste generation forecast for facilities at SRS

    SciTech Connect (OSTI)

    Not Available

    1994-07-01T23:59:59.000Z

    The information supplied by this 30-year solid waste forecast has been compiled as a source document to the Waste Management Environmental Impact Statement (WMEIS). The WMEIS will help to select a sitewide strategic approach to managing present and future Savannah River Site (SRS) waste generated from ongoing operations, environmental restoration (ER) activities, transition from nuclear production to other missions, and decontamination and decommissioning (D&D) programs. The EIS will support project-level decisions on the operation of specific treatment, storage, and disposal facilities within the near term (10 years or less). In addition, the EIS will provide a baseline for analysis of future waste management activities and a basis for the evaluation of the specific waste management alternatives. This 30-year solid waste forecast will be used as the initial basis for the EIS decision-making process. The Site generates and manages many types and categories of waste. With a few exceptions, waste types are divided into two broad groups-high-level waste and solid waste. High-level waste consists primarily of liquid radioactive waste, which is addressed in a separate forecast and is not discussed further in this document. The waste types discussed in this solid waste forecast are sanitary waste, hazardous waste, low-level mixed waste, low-level radioactive waste, and transuranic waste. As activities at SRS change from primarily production to primarily decontamination and decommissioning and environmental restoration, the volume of each waste s being managed will change significantly. This report acknowledges the changes in Site Missions when developing the 30-year solid waste forecast.

  18. Weather Forecast Data an Important Input into Building Management Systems

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01T23:59:59.000Z

    it can generate as much or more energy that it needs ? Building activities need N kWhrs per day (solar panels, heating, etc) ? Harvested from solar panels & passive solar. Amount depends on weather ? NWP models forecast DSWRF @ surface (MJ/m2...://collaboration.cmc.ec.gc.ca/cmc/cmoi/SolarScribe/SolarScribe/ CMC NWP datasets for Day 2 Forecasts ? Regional Deterministic Prediction System (RDPS) ? RDPS raw model data ? 10 km resolution, North America, 000-054 forecasts ? Data at: http...

  19. Forecasting model of the PEPCO service area economy. Volume 3

    SciTech Connect (OSTI)

    Not Available

    1984-03-01T23:59:59.000Z

    Volume III describes and documents the regional economic model of the PEPCO service area which was relied upon to develop many of the assumptions of future values of economic and demographic variables used in the forecast. The PEPCO area model is mathematically linked to the Wharton long-term forecast of the U.S. Volume III contains a technical discussion of the structure of the regional model and presents the regional economic forecast.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28T23:59:59.000Z

    On December 17, 2008, the reference-case projections from Annual Energy Outlook 2009 (AEO 2009) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof), differences in capital costs and O&M expenses, or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired or nuclear generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers; and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal, uranium, and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

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

    SciTech Connect (OSTI)

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

    2008-01-07T23:59:59.000Z

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

  2. Wind Power Forecasting Error Distributions: An International Comparison; Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

    2012-09-01T23:59:59.000Z

    Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

  3. Wind Forecast Improvement Project Southern Study Area Final Report...

    Office of Environmental Management (EM)

    Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report.pdf More Documents & Publications Computational Advances in Applied...

  4. Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures

    E-Print Network [OSTI]

    Richard A. Berk; Brian Kriegler; Jong-Ho Baek

    2011-01-01T23:59:59.000Z

    Forecasting Dangerous Inmate Misconduct: An Applications ofof Term Length more dangerous than other inmates servingIV beds or moving less dangerous Level IV inmates to Level

  5. Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures

    E-Print Network [OSTI]

    Berk, Richard; Kriegler, Brian; Baek, Jong-Ho

    2005-01-01T23:59:59.000Z

    Forecasting Dangerous Inmate Misconduct: An Applications ofof Term Length more dangerous than other inmates servingIV beds or moving less dangerous Level IV inmates to Level

  6. Forecasting the underlying potential governing climatic time series

    E-Print Network [OSTI]

    Livina, V N; Mudelsee, M; Lenton, T M

    2012-01-01T23:59:59.000Z

    We introduce a technique of time series analysis, potential forecasting, which is based on dynamical propagation of the probability density of time series. We employ polynomial coefficients of the orthogonal approximation of the empirical probability distribution and extrapolate them in order to forecast the future probability distribution of data. The method is tested on artificial data, used for hindcasting observed climate data, and then applied to forecast Arctic sea-ice time series. The proposed methodology completes a framework for `potential analysis' of climatic tipping points which altogether serves anticipating, detecting and forecasting climate transitions and bifurcations using several independent techniques of time series analysis.

  7. Sandia National Laboratories: Solar Energy Forecasting and Resource...

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

    & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource Assessment, provides an authoritative voice on the...

  8. analytical energy forecasting: Topics by E-print Network

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

    COMMISSION Tom Gorin Lynn Marshall Principal Author Tom Gorin Project 11 Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Computer Technologies and...

  9. Econometric model and futures markets commodity price forecasting

    E-Print Network [OSTI]

    Just, Richard E.; Rausser, Gordon C.

    1979-01-01T23:59:59.000Z

    Versus CCll1rnercial Econometric M:ldels." Uni- versity ofWorking Paper No. 72 ECONOMETRIC ! 'econometric forecasts with the futures

  10. Optimization Online - Data Assimilation in Weather Forecasting: A ...

    E-Print Network [OSTI]

    M. Fisher

    2007-02-14T23:59:59.000Z

    Feb 14, 2007 ... Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization. M. Fisher(Mike.Fisher ***at*** ecmwf.int)

  11. Weather-based yield forecasts developed for 12 California crops

    E-Print Network [OSTI]

    Lobell, David; Cahill, Kimberly Nicholas; Field, Christopher

    2006-01-01T23:59:59.000Z

    RESEARCH ARTICLE Weather-based yield forecasts developed fordepend largely on the weather, measurements from existingpredictions. We developed weather-based models of statewide

  12. Using Customers' Reported Forecasts to Predict Future Sales

    E-Print Network [OSTI]

    Gordon, Geoffrey J.

    Using Customers' Reported Forecasts to Predict Future Sales Nihat Altintas , Alan Montgomery , Michael Trick Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA 15213. nihat

  13. Reducing the demand forecast error due to the bullwhip effect in the computer processor industry

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01T23:59:59.000Z

    Intel's current demand-forecasting processes rely on customers' demand forecasts. Customers do not revise demand forecasts as demand decreases until the last minute. Intel's current demand models provide little guidance ...

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

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    of two methods to forecast natural gas prices: using theof two methods to forecast natural gas prices is performed:accurate average forecast of natural gas prices than the

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01T23:59:59.000Z

    Gas Price Forecast With natural gas prices significantlyto the EIA’s natural gas price forecasts in AEO 2004 and AEOon the AEO 2005 natural gas price forecasts will likely once

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01T23:59:59.000Z

    revisions to the EIA’s natural gas price forecasts in AEOsolely on the AEO 2005 natural gas price forecasts willComparison of AEO 2005 Natural Gas Price Forecast to NYMEX

  17. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    to estimate the base-case natural gas price forecast, but toComparison of AEO 2010 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts from

  18. Renewable Forecast Min-Max2020.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiation Protection Technical s o Freiberge s 3 c/)RenewableRenewable EnergyForecast of

  19. Forecast and Funding Arrangements - Hanford Site

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC) Environmental Assessments (EA)Budget(DANCE) Target 1Annual Waste Forecast and Funding

  20. Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA

    SciTech Connect (OSTI)

    Hou, Zhangshuan; Etingov, Pavel V.; Makarov, Yuri V.; Samaan, Nader A.

    2014-10-27T23:59:59.000Z

    In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of forecasts. We use automatically coupled wavelet transform and autoregressive integrated moving-average (ARIMA) forecasting to reflect multi-scale variability of forecast errors. The proposed analysis reveals slow-changing “quasi-deterministic” components of forecast errors. This helps improve forecasts produced by other means, e.g., using weather-based models, and reduce forecast errors prediction intervals.

  1. Short term forecasting of solar radiation based on satellite data

    E-Print Network [OSTI]

    Heinemann, Detlev

    Short term forecasting of solar radiation based on satellite data Elke Lorenz, Annette Hammer University, D-26111 Oldenburg Forecasting of solar irradiance will become a major issue in the future integration of solar energy resources into existing energy supply structures. Fluctuations of solar irradiance

  2. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center

    E-Print Network [OSTI]

    Washington at Seattle, University of

    Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime meteorological data from sites upwind of wind farms can be efficiently used to improve short-term forecasts acknowledges the support of PPM Energy, Inc. The data used in this work were obtained from Oregon State

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

    E-Print Network [OSTI]

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

  4. A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size

    E-Print Network [OSTI]

    Hansens, Jim

    A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size Andrew. R.Lawrence@ecmwf.int #12;Abstract An ensemble-based data assimilation approach is used to transform old en- semble. The impact of the transformations are propagated for- ward in time over the ensemble's forecast period

  5. RESERVOIR INFLOW FORECASTING USING NEURAL NETWORKS CHANDRASHEKAR SUBRAMANIAN

    E-Print Network [OSTI]

    Manry, Michael

    a mixture of hydroelectric and non- hydroelectric power, the economics of the hydroelectric plants depend, and to economically allocate the load between various non-hydroelectric plants. Neural networks provide an attractive technology for inflow forecasting, because of (1) their success in power load forecasting 1- 6 , and (2

  6. Introducing the Canadian Crop Yield Forecaster Aston Chipanshi1

    E-Print Network [OSTI]

    Miami, University of

    for crop yield forecasting and risk analysis. Using the Census Agriculture Region (CAR) as the unit Climate Decision Support and Adaptation, Agriculture and Agri-Food Canada, 1011, Innovation Blvd, Saskatoon, SK S7V 1B7, Canada The Canadian Crop Yield Forecaster (CCYF) is a statistical modelling tool

  7. Wind-Wave Probabilistic Forecasting based on Ensemble

    E-Print Network [OSTI]

    have to be jointly taken into account in some decision-making problems, e.g. offshore wind farmWind-Wave Probabilistic Forecasting based on Ensemble Predictions Maxime FORTIN Kongens Lyngby 2012.imm.dtu.dk IMM-PhD-2012-86 #12;Summary Wind and wave forecasts are of a crucial importance for a number

  8. Wind Power Forecasting: State-of-the-Art 2009

    E-Print Network [OSTI]

    Kemner, Ken

    Wind Power Forecasting: State-of-the-Art 2009 ANL/DIS-10-1 Decision and Information Sciences about Argonne and its pioneering science and technology programs, see www.anl.gov. #12;Wind Power................................................ 14 2.2.3 Critical Processes for Wind Forecast

  9. 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 for electric vehicles. #12;ii #12;iii ABSTRACT The Preliminary California Energy Demand Forecast 2012 includes three full scenarios: a high energy demand case, a low energy demand case, and a mid energy demand

  10. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST, and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption STAFFFINALREPORT NOVEMBER 2007 CEC-200-2007-015-SF2 Arnold Schwarzenegger, Governor #12;CALIFORNIA ENERGY

  11. 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 Manager Kae Lewis Acting Manager Demand Analysis Office Valerie T. Hall Deputy Director Energy Efficiency Demand Forecast report is the product of the efforts of many current and former California Energy

  12. Distribution Based Data Filtering for Financial Time Series Forecasting

    E-Print Network [OSTI]

    Bailey, James

    recent past. In this paper, we address the challenge of forecasting the behavior of time series using@unimelb.edu.au Abstract. Changes in the distribution of financial time series, particularly stock market prices, can of stock prices, which aims to forecast the future values of the price of a stock, in order to obtain

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

    E-Print Network [OSTI]

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

  14. Draft for Public Comment Appendix A. Demand Forecast

    E-Print Network [OSTI]

    in the planning process. Electricity demand is forecast to grow from 20,080 average megawatts in 2000 to 25 forecast of electricity demand is a required component of the Council's Northwest Regional Conservation and Electric Power Plan.1 Understanding growth in electricity demand is, of course, crucial to determining

  15. FORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS

    E-Print Network [OSTI]

    Keller, Arturo A.

    resources resulting in water stress. Effective water management ­ a solution Supply side management Demand side management #12;Developing a regression equation based on cluster analysis for forecasting waterFORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS by Bruce Bishop Professor of Civil

  16. Forecasting Uncertainty Related to Ramps of Wind Power Production

    E-Print Network [OSTI]

    Boyer, Edmond

    - namic reserve quantification [8], for the optimal oper- ation of combined wind-hydro power plants [5, 1Forecasting Uncertainty Related to Ramps of Wind Power Production Arthur Bossavy, Robin Girard - The continuous improvement of the accuracy of wind power forecasts is motivated by the increasing wind power

  17. Impact of PV forecasts uncertainty in batteries management in microgrids

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    -- Photovoltaic systems, Batteries, Forecasting I. INTRODUCTION This paper presents first results of a study Energies and Energy Systems Sophia Antipolis, France andrea.michiorri@mines-paristech.fr Abstract production forecast algorithm is used in combination with a battery schedule optimisation algorithm. The size

  18. Forecasting Building Occupancy Using Sensor Network James Howard

    E-Print Network [OSTI]

    Hoff, William A.

    of the forecasting algorithm for the different conditions. 1. INTRODUCTION According to the U.S. Department of Energy could take advantage of times when electricity cost is lower, to chill a cold water storage tankForecasting Building Occupancy Using Sensor Network Data James Howard Colorado School of Mines

  19. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01T23:59:59.000Z

    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.

  20. Comparison of Wind Power and Load Forecasting Error Distributions: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Florita, A.; Orwig, K.; Lew, D.; Milligan, M.

    2012-07-01T23:59:59.000Z

    The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent System Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.

  1. Verification of hourly forecasts of wind turbine power output

    SciTech Connect (OSTI)

    Wegley, H.L.

    1984-08-01T23:59:59.000Z

    A verification of hourly average wind speed forecasts in terms of hourly average power output of a MOD-2 was performed for four sites. Site-specific probabilistic transformation models were developed to transform the forecast and observed hourly average speeds to the percent probability of exceedance of an hourly average power output. (This transformation model also appears to have value in predicting annual energy production for use in wind energy feasibility studies.) The transformed forecasts were verified in a deterministic sense (i.e., as continuous values) and in a probabilistic sense (based upon the probability of power output falling in a specified category). Since the smoothing effects of time averaging are very pronounced, the 90% probability of exceedance was built into the transformation models. Semiobjective and objective (model output statistics) forecasts were made compared for the four sites. The verification results indicate that the correct category can be forecast an average of 75% of the time over a 24-hour period. Accuracy generally decreases with projection time out to approx. 18 hours and then may increase due to the fairly regular diurnal wind patterns that occur at many sites. The ability to forecast the correct power output category increases with increasing power output because occurrences of high hourly average power output (near rated) are relatively rare and are generally not forecast. The semiobjective forecasts proved superior to model output statistics in forecasting high values of power output and in the shorter time frames (1 to 6 hours). However, model output statistics were slightly more accurate at other power output levels and times. Noticeable differences were observed between deterministic and probabilistic (categorical) forecast verification results.

  2. Comparison of the 1984 DOE/EIA annual energy outlook and the 1984 GRI baseline projection

    SciTech Connect (OSTI)

    Ashby, A.; Holtberg, P.; Woods, T.

    1985-01-01T23:59:59.000Z

    A comparative analysis of the Gas Research Institute (GRI) Baseline Projection of US Energy Supply and Demand with the DOE/EIA 1984 Annual Energy Outlook shows many similar assumptions, but many cases of widening differences between the projections of primary energy consumption and sector-specific energy consumption. The DOE/EIA expects a faster and more significant decline in the electricity to natural gas price ratio, lower sector-specific end-use prices of refined petroleum products, and a faster growth in industrial raw material energy demand. In contrast to the GRI report, it also omits an estimate of industrial cogeneration and does not retire any exisiting generating capacity. The report examines the basic assumptions and results of both projections using five scenarios. 17 tables.

  3. Comparative Analysis of Modeling Studies on China's Future Energy and Emissions Outlook

    SciTech Connect (OSTI)

    Zheng, Nina; Zhou, Nan; Fridley, David

    2010-09-01T23:59:59.000Z

    The past decade has seen the development of various scenarios describing long-term patterns of future Greenhouse Gas (GHG) emissions, with each new approach adding insights to our understanding of the changing dynamics of energy consumption and aggregate future energy trends. With the recent growing focus on China's energy use and emission mitigation potential, a range of Chinese outlook models have been developed across different institutions including in China's Energy Research Institute's 2050 China Energy and CO2 Emissions Report, McKinsey & Co's China's Green Revolution report, the UK Sussex Energy Group and Tyndall Centre's China's Energy Transition report, and the China-specific section of the IEA World Energy Outlook 2009. At the same time, the China Energy Group at Lawrence Berkeley National Laboratory (LBNL) has developed a bottom-up, end-use energy model for China with scenario analysis of energy and emission pathways out to 2050. A robust and credible energy and emission model will play a key role in informing policymakers by assessing efficiency policy impacts and understanding the dynamics of future energy consumption and energy saving and emission reduction potential. This is especially true for developing countries such as China, where uncertainties are greater while the economy continues to undergo rapid growth and industrialization. A slightly different assumption or storyline could result in significant discrepancies among different model results. Therefore, it is necessary to understand the key models in terms of their scope, methodologies, key driver assumptions and the associated findings. A comparative analysis of LBNL's energy end-use model scenarios with the five above studies was thus conducted to examine similarities and divergences in methodologies, scenario storylines, macroeconomic drivers and assumptions as well as aggregate energy and emission scenario results. Besides directly tracing different energy and CO{sub 2} savings potential back to the underlying strategies and combination of efficiency and abatement policy instruments represented by each scenario, this analysis also had other important but often overlooked findings.

  4. How USDA Forecasts Production and Supply/Demand 

    E-Print Network [OSTI]

    Anderson, David P.; O'Brien, Daniel; Welch, Mark

    2009-06-01T23:59:59.000Z

    estimate of planted and harvested acres. This survey uses two different samples, called frames. The first is the area frame, which is the land area of the United States. This ensures that the population of farmers is covered by the survey. The second....? National Agricultural Statistics Service and Office of the Chief Economist, World Agricultural Outlook Board. Miscellaneous Publication No. 1554, March 1999. Educational programs of the Texas AgriLife Extension Service are open to all people without...

  5. Development and testing of improved statistical wind power forecasting methods.

    SciTech Connect (OSTI)

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J. (Decision and Information Sciences); (INESC Porto)

    2011-12-06T23:59:59.000Z

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

  6. Incorporating Forecast Uncertainty in Utility Control Center

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian

    2014-07-09T23:59:59.000Z

    Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)

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

    SciTech Connect (OSTI)

    Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

    2005-07-01T23:59:59.000Z

    The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

  8. November 14, 2000 A Quarterly Forecast of U.S. Trade

    E-Print Network [OSTI]

    Shyy, Wei

    November 14, 2000 A Quarterly Forecast of U.S. Trade in Services and the Current Account, 2000 of Forecast*** We forecast that the services trade surplus, which declined from 1997 to 1998 and edged upward. That is, from a level of $80.6 billion in 1999, we forecast that the services trade surplus will be $80

  9. Smard Grid Software Applications for Distribution Network Load Forecasting Eugene A. Feinberg, Jun Fei

    E-Print Network [OSTI]

    Feinberg, Eugene A.

    of the distribution network. Keywords: load forecasting, feeder, transformer, load pocket, SmartGrid I. INTRODUCTION

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

    SciTech Connect (OSTI)

    Lantz, E.; Hand, M.

    2010-05-01T23:59:59.000Z

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

  11. USING BOX-JENKINS MODELS TO FORECAST FISHERY DYNAMICS: IDENTIFICATION, ESTIMATION, AND CHECKING

    E-Print Network [OSTI]

    ~ is illustrated by developing a model that makes monthly forecasts of skipjack tuna, Katsuwonus pelamis, catches

  12. Development and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices

    Broader source: Energy.gov [DOE]

    Development and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices

  13. ASSESSING THE QUALITY AND ECONOMIC VALUE OF WEATHER AND CLIMATE FORECASTS

    E-Print Network [OSTI]

    Katz, Richard

    INFORMATION SYSTEM · Forecast -- Conditional probability distribution for event Z = z indicates forecast tornado #12;(1.2) FRAMEWORK · Joint Distribution of Observations & Forecasts Observed Weather = Forecast probability p (e.g., induced by Z) · Reliability Diagram Observed weather: = 1 (Adverse weather occurs) = 0

  14. Natural Priors, CMSSM Fits and LHC Weather Forecasts

    E-Print Network [OSTI]

    Allanach, B C; Cranmer, Kyle; Lester, Christopher G; Weber, Arne M

    2007-08-07T23:59:59.000Z

    ar X iv :0 70 5. 04 87 v3 [ he p- ph ] 5 J ul 20 07 Preprint typeset in JHEP style - HYPER VERSION DAMTP-2007-18 Cavendish-HEP-2007-03 MPP-2007-36 Natural Priors, CMSSM Fits and LHC Weather Forecasts Benjamin C Allanach1, Kyle Cranmer2... ’s likely discoveries. There are big differences between nature of the questions answered by a forecast, and the ques- tions that will be answered by the experiments themselves when they have acquired compelling data. A weather forecast predicting “severe...

  15. 2012 Energy and Climate Outlook M A S S A C H U S E T T S I N S T I T U T E O F T E C H N O L O G Y

    E-Print Network [OSTI]

    of Global Change 1 2012 Energy and Climate Outlook The world faces immense environmental challenges2012 Energy and Climate Outlook M A S S A C H U S E T T S I N S T I T U T E O F T E C H N O L O G Y change. The 2012 Energy and Climate Outlook uses a projection modeling system developed by MIT's Joint

  16. Situation and outlook for foreign and domestic rice trade: recommendations to expand U.S. market share

    E-Print Network [OSTI]

    Bates, Kathy

    1991-01-01T23:59:59.000Z

    Is Right", ic 'ew 7 8 Tough, Clndy, " World Grain Situation and Outlook", Circular Series, USDA, FAS, Supplement 449 October 1989. United States Department of Agriculture, , Economic Research Service, "Government Programs for Rice", 'o od Review Jan... and is cholesterol free. Less re6ned grades of oil are used as leather conditioners. TABLES 36 IA retina Area Irold Sogianing Rough Nailed Total 202AL Total Endrng ar Earvestod Stocks Production Production Inports Exports Douostic Stocks Consuupt1on Jan...

  17. Optimally controlling hybrid electric vehicles using path forecasting

    E-Print Network [OSTI]

    Katsargyri, Georgia-Evangelina

    2008-01-01T23:59:59.000Z

    Hybrid Electric Vehicles (HEVs) with path-forecasting belong to the class of fuel efficient vehicles, which use external sensory information and powertrains with multiple operating modes in order to increase fuel economy. ...

  18. Recently released EIA report presents international forecasting data

    SciTech Connect (OSTI)

    NONE

    1995-05-01T23:59:59.000Z

    This report presents information from the Energy Information Administration (EIA). Articles are included on international energy forecasting data, data on the use of home appliances, gasoline prices, household energy use, and EIA information products and dissemination avenues.

  19. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    G. Bel; C. P. Connaughton; M. Toots; M. M. Bandi

    2015-03-29T23:59:59.000Z

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  20. OCTOBER-NOVEMBER FORECAST FOR 2014 CARIBBEAN BASIN HURRICANE ACTIVITY

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    and hurricanes, but instead predicts both hurricane days and Accumulated Cyclone Energy (ACE). Typically, while) tropical cyclone (TC) activity. We have decided to issue this forecast, because Klotzbach (2011) has

  1. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07T23:59:59.000Z

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  2. Forecasting and strategic inventory placement for gas turbine aftermarket spares

    E-Print Network [OSTI]

    Simmons, Joshua T. (Joshua Thomas)

    2007-01-01T23:59:59.000Z

    This thesis addresses the problem of forecasting demand for Life Limited Parts (LLPs) in the gas turbine engine aftermarket industry. It is based on work performed at Pratt & Whitney, a major producer of turbine engines. ...

  3. Optimally Controlling Hybrid Electric Vehicles using Path Forecasting

    E-Print Network [OSTI]

    Kolmanovsky, Ilya V.

    The paper examines path-dependent control of Hybrid Electric Vehicles (HEVs). In this approach we seek to improve HEV fuel economy by optimizing charging and discharging of the vehicle battery depending on the forecasted ...

  4. africa conditional forecasts: Topics by E-print Network

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

    forecasts had the potential to improve resource management but instead played only a marginal role in real-world decision making. 1 A widespread perception that the quality of the...

  5. accident risk forecasting: Topics by E-print Network

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

    forecasts had the potential to improve resource management but instead played only a marginal role in real-world decision making. 1 A widespread perception that the quality of the...

  6. Forecasting Volatility in Stock Market Using GARCH Models

    E-Print Network [OSTI]

    Yang, Xiaorong

    2008-01-01T23:59:59.000Z

    Forecasting volatility has held the attention of academics and practitioners all over the world. The objective for this master's thesis is to predict the volatility in stock market by using generalized autoregressive conditional heteroscedasticity(GARCH...

  7. Forecasting Returns and Volatilities in GARCH Processes Using the Bootstrap

    E-Print Network [OSTI]

    Romo, Juan

    Forecasting Returns and Volatilities in GARCH Processes Using the Bootstrap Lorenzo Pascual, Juan generated by GARCH processes. The main advantage over other bootstrap methods previously proposed for GARCH by having conditional heteroscedasticity. Generalized Autoregressive Conditionally Heteroscedastic (GARCH

  8. Adaptive sampling and forecasting with mobile sensor networks

    E-Print Network [OSTI]

    Choi, Han-Lim

    2009-01-01T23:59:59.000Z

    This thesis addresses planning of mobile sensor networks to extract the best information possible out of the environment to improve the (ensemble) forecast at some verification region in the future. To define the information ...

  9. Dispersion in analysts' forecasts: does it make a difference? 

    E-Print Network [OSTI]

    Adut, Davit

    2004-09-30T23:59:59.000Z

    Financial analysts are an important group of information intermediaries in the capital markets. Their reports, including both earnings forecasts and stock recommendations, are widely transmitted and have a significant impact on stock prices (Womack...

  10. FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007

    E-Print Network [OSTI]

    ......................................................................... 11 3. Demand Side Management (DSM) Program Impacts................................... 13 4. Demand Sylvia Bender Manager DEMAND ANALYSIS OFFICE Scott W. Matthews Chief Deputy Director B.B. Blevins Forecast Methods and Models ....................................................... 14 5. Demand-Side

  11. An econometric analysis and forecasting of Seoul office market

    E-Print Network [OSTI]

    Kim, Kyungmin

    2011-01-01T23:59:59.000Z

    This study examines and forecasts the Seoul office market, which is going to face a big supply in the next few years. After reviewing several previous studies on the Dynamic model and the Seoul Office market, this thesis ...

  12. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

    Through the Improving the Accuracy of Solar Forecasting Funding Opportunity, DOE is funding solar projects that are helping utilities, grid operators, solar power plant owners, and other...

  13. Variable Selection and Inference for Multi-period Forecasting Problems

    E-Print Network [OSTI]

    Pesaran, M Hashem; Pick, Andreas; Timmermann, Allan

    Variable Selection and Inference for Multi-period Forecasting Problems? M. Hashem Pesaran Cambridge University and USC Andreas Pick De Nederlandsche Bank and Cambridge University, CIMF Allan Timmermann UC San Diego and CREATES January 26, 2009...

  14. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    Bel, G; Toots, M; Bandi, M M

    2015-01-01T23:59:59.000Z

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  15. Dispersion in analysts' forecasts: does it make a difference?

    E-Print Network [OSTI]

    Adut, Davit

    2004-09-30T23:59:59.000Z

    Financial analysts are an important group of information intermediaries in the capital markets. Their reports, including both earnings forecasts and stock recommendations, are widely transmitted and have a significant impact on stock prices (Womack...

  16. Mesoscale predictability and background error convariance estimation through ensemble forecasting

    E-Print Network [OSTI]

    Ham, Joy L

    2002-01-01T23:59:59.000Z

    Over the past decade, ensemble forecasting has emerged as a powerful tool for numerical weather prediction. Not only does it produce the best estimate of the state of the atmosphere, it also could quantify the uncertainties associated with the best...

  17. Subhourly wind forecasting techniques for wind turbine operations

    SciTech Connect (OSTI)

    Wegley, H.L.; Kosorok, M.R.; Formica, W.J.

    1984-08-01T23:59:59.000Z

    Three models for making automated forecasts of subhourly wind and wind power fluctuations were examined to determine the models' appropriateness, accuracy, and reliability in wind forecasting for wind turbine operation. Such automated forecasts appear to have value not only in wind turbine control and operating strategies, but also in improving individual wind turbine control and operating strategies, but also in improving individual wind turbine operating strategies (such as determining when to attempt startup). A simple persistence model, an autoregressive model, and a generalized equivalent Markhov (GEM) model were developed and tested using spring season data from the WKY television tower located near Oklahoma City, Oklahoma. The three models represent a pure measurement approach, a pure statistical method and a statistical-dynamical model, respectively. Forecasting models of wind speed means and measures of deviations about the mean were developed and tested for all three forecasting techniques for the 45-meter level and for the 10-, 30- and 60-minute time intervals. The results of this exploratory study indicate that a persistence-based approach, using onsite measurements, will probably be superior in the 10-minute time frame. The GEM model appears to have the most potential in 30-minute and longer time frames, particularly when forecasting wind speed fluctuations. However, several improvements to the GEM model are suggested. In comparison to the other models, the autoregressive model performed poorly at all time frames; but, it is recommended that this model be upgraded to an autoregressive moving average (ARMA or ARIMA) model. The primary constraint in adapting the forecasting models to the production of wind turbine cluster power output forecasts is the lack of either actual data, or suitable models, for simulating wind turbine cluster performance.

  18. Streamflow forecasting for large-scale hydrologic systems

    E-Print Network [OSTI]

    Awwad, Haitham Munir

    1991-01-01T23:59:59.000Z

    STREAMFLOW FORECASTING FOR LARGE-SCALE HYDROLOGIC SYSTEMS A Thesis by HAITHAM MUNIR AWWAD Submitted to the Office of Graduate Studies of Texas AkM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May... 1991 Major Subject: Civil Engineering STREAMFLOW FORECASTING FOR LARGE-SCALE HYDROLOGIC SYSTEMS A Thesis by HAITHAM MUNIR AWWAD Approved as to style and content by: uan B. Valdes (Chair of Committee) alph A. Wurbs (Member) Marshall J. Mc...

  19. A model for short term electric load forecasting

    E-Print Network [OSTI]

    Tigue, John Robert

    1975-01-01T23:59:59.000Z

    A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE, III Submitted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE May 1975 Major... Subject: Electrical Engineering A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE& III Approved as to style and content by: (Chairman of Committee) (Head Depart t) (Member) ;(Me r (Member) (Member) May 1975 ABSTRACT...

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

    E-Print Network [OSTI]

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

    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...

  1. Probabilistic wind power forecasting -European Wind Energy Conference -Milan, Italy, 7-10 May 2007 Probabilistic short-term wind power forecasting

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Probabilistic wind power forecasting - European Wind Energy Conference - Milan, Italy, 7-10 May 2007 Probabilistic short-term wind power forecasting based on kernel density estimators J´er´emie Juban jeremie.juban@ensmp.fr; georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting tools

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-01-01T23:59:59.000Z

    vs. AEO 2001 Price Forecast Natural Gas Price (nominal $/if forwards forecasts) or natural gas-fired generation (ifs reference case forecast of natural gas prices delivered to

  3. American Solar Energy Society Proc. ASES Annual Conference, Raleigh, NC, EVALUATION OF NUMERICAL WEATHER PREDICTION

    E-Print Network [OSTI]

    Perez, Richard R.

    © American Solar Energy Society ­ Proc. ASES Annual Conference, Raleigh, NC, EVALUATION;© American Solar Energy Society ­ Proc. ASES Annual Conference, Raleigh, NC, irradiance forecasts over OF NUMERICAL WEATHER PREDICTION SOLAR IRRADIANCE FORECASTS IN THE US Richard Perez ASRC, Albany, NY, Perez

  4. Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards"Top-Runner Approach"

    SciTech Connect (OSTI)

    Lacommare, Kristina S H; Komiyama, Ryoichi; Marnay, Chris

    2008-05-15T23:59:59.000Z

    As one of the measures to achieve the reduction in greenhouse gas emissions agreed to in the"Kyoto Protocol," an institutional scheme for determining energy efficiency standards for energy-consuming appliances, called the"Top-Runner Approach," was developed by the Japanese government. Its goal is to strengthen the legal underpinnings of various energy conservation measures. Particularly in Japan's residential sector, where energy demand has grown vigorously so far, this efficiency standard is expected to play a key role in mitigating both energy demand growth and the associated CO2 emissions. This paper presents an outlook of Japan's residential energy demand, developed by a stochastic econometric model for the purpose of analyzing the impacts of the Japan's energy efficiency standards, as well as the future stochastic behavior of income growth, demography, energy prices, and climate on the future energy demand growth to 2030. In this analysis, we attempt to explicitly take into consideration more than 30 kinds of electricity uses, heating, cooling and hot water appliances in order to comprehensively capture the progress of energy efficiency in residential energy end-use equipment. Since electricity demand, is projected to exhibit astonishing growth in Japan's residential sector due to universal increasing ownership of electric and other appliances, it is important to implement an elaborate efficiency standards policy for these appliances.

  5. Iran`s petroleum policy: Current trends and the future outlook

    SciTech Connect (OSTI)

    Pezeshki, S.; Fesharaki, F.

    1994-12-01T23:59:59.000Z

    The Iranian economy and political situation have undergone radical changes since the 1979 Islamic revolution. The excesses of the early years of the revolution have gradually given way to moderation and a more pragmatic economic policy--based on the principles of the free market. The petroleum policy, as a subset of the economic policies, has been somewhat affected by the political and economic developments in Iran. The petroleum policy has changed from a position of no foreign participation to a position that includes a desire for foreign participation, the text of a model contract, and an attempt to introduce new technologies in the upstream sector. This report provides an overview of the key issues facing the Iranian oil industry and the economic context in which the oil industry is operating in Iran. It describes the evolution of policies meant to move the oil industry toward the free market; it discusses Iran`s oil trading partners, the outlook for refining and project investments, and current and likely future developments in the natural gas and petrochemical sectors. In short, the report provides an up-to-date assessment of the Iranian petroleum sector and its likely evolution in the future.

  6. Survey of Variable Generation Forecasting in the West: August 2011 - June 2012

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01T23:59:59.000Z

    This report surveyed Western Interconnection Balancing Authorities regarding their implementation of variable generation forecasting, the lessons learned to date, and recommendations they would offer to other Balancing Authorities who are considering variable generation forecasting. Our survey found that variable generation forecasting is at an early implementation stage in the West. Eight of the eleven Balancing Authorities interviewed began forecasting in 2008 or later. It also appears that less than one-half of the Balancing Authorities in the West are currently utilizing variable generation forecasting, suggesting that more Balancing Authorities in the West will engage in variable generation forecasting should more variable generation capacity be added.

  7. Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-01-01T23:59:59.000Z

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the “flying brick” technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.

  8. Short-term planning and forecasting for petroleum. Master's thesis

    SciTech Connect (OSTI)

    Elkins, R.D.

    1988-06-01T23:59:59.000Z

    The Defense Fuel Supply Center (DFSC) has, in recent past, been unable to adequately forecast for short-term petroleum requirements. This has resulted in inaccurate replenishment quantities and required short-notice corrections, which interrupted planned resupply methods. The relationship between the annual CINCLANTFLT DFM budget and sales from the the Norfolk Defense Fuel Support Point (DFSP) is developed and the past sales data from the Norfolk DFSP is used to construct seasonality indices. Finally, the budget/sales relationship is combined with the seasonality indices to provide a new forecasting model. The model is then compared with the current one for FY-88 monthly forecasts. The comparison suggests that the new model can provide accurate, timely requirements data and improve resupply of the Norfolk Defense Fuel Support Point.

  9. Three Essays on Energy Economics and Forecasting

    E-Print Network [OSTI]

    Shin, Yoon Sung

    2012-02-14T23:59:59.000Z

    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...

  10. Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price.................................................................................................................................. 27 INTRODUCTION The Council prepares and periodically updates a 20-year forecast of wholesale to forecast wholesale power prices. AURORAxmp® provides the ability to inco

  11. Integration of Behind-the-Meter PV Fleet Forecasts into Utility...

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

    Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Clean...

  12. Application of the Stretched Exponential Production Decline Model to Forecast Production in Shale Gas Reservoirs

    E-Print Network [OSTI]

    Statton, James Cody

    2012-07-16T23:59:59.000Z

    . This study suggests a type curve is most useful when 24 months or less is available to forecast. The SEPD model generally provides more conservative forecasts and EUR estimates than Arps' model with a minimum decline rate of 5%....

  13. SHORT-TERM FORECASTING OF SOLAR RADIATION BASED ON SATELLITE DATA WITH STATISTICAL METHODS

    E-Print Network [OSTI]

    Heinemann, Detlev

    SHORT-TERM FORECASTING OF SOLAR RADIATION BASED ON SATELLITE DATA WITH STATISTICAL METHODS Annette governing the insolation, forecasting of solar radiation makes the description of development of the cloud

  14. Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast

    E-Print Network [OSTI]

    ............................................................................................................................... 12 Oil Price Forecast Range. The price of crude oil was $25 a barrel in January of 2000. In July 2008 it averaged $127, even approachingSixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast Introduction

  15. Impacts of Improved Day-Ahead Wind Forecasts on Power Grid Operations: September 2011

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01T23:59:59.000Z

    This study analyzed the potential benefits of improving the accuracy (reducing the error) of day-ahead wind forecasts on power system operations, assuming that wind forecasts were used for day ahead security constrained unit commitment.

  16. Solar Variability and Forecasting Jan Kleissl, Chi Chow, Matt Lave, Patrick Mathiesen,

    E-Print Network [OSTI]

    Homes, Christopher C.

    Forecasting Benefits Use of state-of-art wind and solar forecasts reduces WECC operating costs by up to 14/MWh of wind and solar generation). WECC operating costs could be reduced by an additional $500 million

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    late January 2008, extend its natural gas futures strip anComparison of AEO 2008 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts from

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01T23:59:59.000Z

    Comparison of AEO 2007 Natural Gas Price Forecast to NYMEXs reference case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01T23:59:59.000Z

    Comparison of AEO 2006 Natural Gas Price Forecast to NYMEXs reference case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01T23:59:59.000Z

    Comparison of AEO 2009 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

  1. Status of Centralized Wind Power Forecasting in North America: May 2009-May 2010

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01T23:59:59.000Z

    Report surveys grid wind power forecasts for all wind generators, which are administered by utilities or regional transmission organizations (RTOs), typically with the assistance of one or more wind power forecasting companies.

  2. Earnings Management Pressure on Audit Clients: Auditor Response to Analyst Forecast Signals

    E-Print Network [OSTI]

    Newton, Nathan J.

    2013-06-26T23:59:59.000Z

    This study investigates whether auditors respond to earnings management pressure created by analyst forecasts. Analyst forecasts create an important earnings target for management, and professional standards direct auditors to consider how...

  3. Forecasting the demand for electric vehicles: accounting for attitudes and perceptions

    E-Print Network [OSTI]

    Bierlaire, Michel

    prediction, transportation, attitudes and perceptions, hybrid choice models, fractional factorial design: survey design, model estimation and forecasting. We develop a stated preferences (SP) survey with issues related to the application of models designed to forecast demand for new alternatives, most

  4. Streamflow Forecasting Based on Statistical Applications and Measurements Made with Rain Gage and Weather Radar

    E-Print Network [OSTI]

    Hudlow, M.D.

    Techniques for streamflow forecasting are developed and tested for the Little Washita River in Oklahoma. The basic input for streamflow forecasts is rainfall. the rainfall amounts may be obtained from several sources; however, this study...

  5. Projected Regional Impacts of Appliance Efficiency Standards for the U.S. Residential Sector

    E-Print Network [OSTI]

    Koomey, J.G.

    2010-01-01T23:59:59.000Z

    D O E . 1996a. Annual Energy Outlook 1996, with ProjectionsELA) 1996 Annual Energy Outlook (AEO) (US D O E 1996a).1055.1 Joules. The Annual Energy Outlook (1996) forecast for

  6. A sensitivity analysis of the treatment of wind energy in the AEO99 version of NEMS

    E-Print Network [OSTI]

    Osborn, Julie G.; Wood, Frances; Richey, Cooper; Sanders, Sandy; Short, Walter; Koomey, Jonathan

    2001-01-01T23:59:59.000Z

    Administration. 1998. Annual Energy Outlook 1999: WithDepartment of Energy’s Annual Energy Outlook (AEO) forecastDepartment of Energy’s Annual Energy Outlook 1999 (AEO99)

  7. Distributed Generation Potential of the U.S. Commercial Sector

    E-Print Network [OSTI]

    LaCommare, Kristina Hamachi; Edwards, Jennifer L.; Gumerman, Etan; Marnay, Chris

    2005-01-01T23:59:59.000Z

    GPRA NEMS O&M R&D Annual Energy Outlook combined heat andnotably the Annual Energy Outlook (AEO). EIA’s forecasts areto produce the Annual Energy Outlook (AEO), and model runs

  8. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    Energy Agency (IEA). World Energy Outlook 2009. Paris: OECD/IEA, 2009. ———. World Energy Outlook 2010. Paris: OECD/IEA,Energy Agency, World Energy Outlook 2010, 232. forecasts, if

  9. Short-Term Energy Outlook Supplement: Status of Libyan Loading Ports and Oil and Natural Gas Fields

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctoberOutlookShort-Term

  10. Forecast of contracting and subcontracting opportunities. Fiscal year 1996

    SciTech Connect (OSTI)

    NONE

    1996-02-01T23:59:59.000Z

    This forecast of prime and subcontracting opportunities with the U.S. Department of Energy and its MAO contractors and environmental restoration and waste management contractors, is the Department`s best estimate of small, small disadvantaged and women-owned small business procurement opportunities for fiscal year 1996. The information contained in the forecast is published in accordance with Public Law 100-656. It is not an invitation for bids, a request for proposals, or a commitment by DOE to purchase products or services. Each procurement opportunity is based on the best information available at the time of publication and may be revised or cancelled.

  11. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

  12. Central Wind Power Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01T23:59:59.000Z

    The report addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America.

  13. Evaluation of Greenhouse Gas and Criteria Emissions From Conventional and Hybrid Off-Road Equipment

    E-Print Network [OSTI]

    Cao, Tanfeng

    2014-01-01T23:59:59.000Z

    76, No. 179. 3. Annual Energy Outlook 2014, US Department of76, No. 179. 3. Annual Energy Outlook 2014, US Department of76, No. 179. 6. Annual Energy Outlook 2013, US Department of

  14. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 15 SEPTEMBER 28, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the second year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  15. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 27 OCTOBER 10, 2013

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fifth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  16. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 16 AUGUST 29, 2013

    E-Print Network [OSTI]

    that we are trying to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index This is the fifth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early for ACE using three categories as defined in Table 1. Table 1: ACE forecast definition. Parameter

  17. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 3 AUGUST 16, 2012

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fourth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  18. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 12 OCTOBER 25, 2012

    E-Print Network [OSTI]

    Gray, William

    to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined This is the fourth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting for individual event parameters such as named storms and hurricanes. We issue forecasts for ACE using three

  19. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 28 OCTOBER 11, 2012

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fourth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  20. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 13 SEPTEMBER 26, 2013

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fifth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1