National Library of Energy BETA

Sample records for outlook forecast evaluation

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

    Reports and Publications (EIA)

    2010-01-01

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

  2. 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.

    2000-01-07

    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.

  3. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    1996-08-01

    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.

  4. 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.

    2013-10-01

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

  5. Short-Term Energy Outlook

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

    ... U.S. Energy Information Administration | Short-Term Energy Outlook June 2015 2 * The National Oceanic and Atmospheric Administration (NOAA) forecasts warmer summer temperatures ...

  6. Short-term energy outlook annual supplement, 1993

    SciTech Connect (OSTI)

    1993-08-06

    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.

  7. Short-term energy outlook, annual supplement 1994

    SciTech Connect (OSTI)

    Not Available

    1994-08-01

    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 January 2014

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

    4 1 January 2014 Short-Term Energy Outlook (STEO) Highlights This edition of the Short-Term Energy Outlook is the first to include forecasts for 2015. After falling to the...

  9. Short-Term Energy Outlook January 2014

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

    This edition of the Short-Term Energy Outlook is the first to include forecasts ... U.S. Energy Information Administration | Short-Term Energy Outlook January 2014 2 Global ...

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

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

    Annual Energy Outlook Retrospective Review: Evaluation of 2014 and Prior Reference Case Projections March 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | AEO Retrospective Review: Evaluation of 2014 and Prior Reference Case Projections i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's

  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.

    2013-10-01

    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. Short-Term Energy Outlook

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

    This edition of the Short-Term Energy Outlook is the first to include forecasts ... to an average of 2.72gal in 2016. U.S. Energy Information Administration | Short-Term ...

  13. Winter Weather Outlook

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

    0 Winter Weather Outlook With the chill of colder temperatures in the air, we can rest assured that the icy grips of winter are just around the corner. The Climate Prediction Center (CPC), a specialized part of the National Weather Service (NWS), has issued its annual winter outlook for the 2000-2001 winter season. The CPC, located in Camp Springs, Maryland, is a government agency that focuses its predictions on Earth's climate. In comparison to the NWS forecasts of short-term weather events,

  14. Short-term energy outlook, Annual supplement 1995

    SciTech Connect (OSTI)

    1995-07-25

    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.

  15. Energy Markets Outlook

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

    Energy Markets Outlook For National Association for Business Economics March 7, 2016 | Washington, D.C. By Adam Sieminski, Administrator Forecast -3 -2 -1 0 1 2 3 4 5 6 82 84 86 88 90 92 94 96 98 100 2011-Q1 2012-Q1 2013-Q1 2014-Q1 2015-Q1 2016-Q1 2017-Q1 Implied stock change and balance (right axis) World production (left axis) World consumption (left axis) world supply and demand million barrels per day implied stock change million barrels per day Global oil inventories are forecast to

  16. Short-Term Energy Outlook June 2013

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

    1 June 2013 Short-Term Energy Outlook (STEO) Highlights * After increasing to 119 per ... in 2013 and to 3.37 per gallon in 2014. Energy price forecasts are highly uncertain, and ...

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

    SciTech Connect (OSTI)

    Not Available

    1994-02-07

    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

    1994-07-01

    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

    1994-08-02

    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)

    1995-08-02

    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. Short-Term Energy Outlook Model Documentation: Coal Supply, Demand, and Prices

    Reports and Publications (EIA)

    2016-01-01

    The coal module of the Short-Term Energy Outlook (STEO) model is designed to provide forecasts of U.S. production, consumption, imports, exports, inventories, and prices.

  2. Assumptions to the Annual Energy Outlook 2015

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

    Assumptions to the Annual Energy Outlook 2015 September 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2015 i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or

  3. Short-Term Energy Outlook Supplement: Summer 2013 Outlook for Residential Electric Bills

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

    Summer 2013 Outlook for Residential Electric Bills June 2013 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | STEO Supplement: Summer 2013 Outlook for Residential Electric Bills i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by

  4. Short-Term Energy Outlook

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

    Outlook September 2015 1 September 2015 Short-Term Energy Outlook (STEO) Highlights * ... U.S. Energy Information Administration | Short-Term Energy Outlook September 2015 2 Global ...

  5. Annual Energy Outlook 2011

    Gasoline and Diesel Fuel Update (EIA)

    ... Energy Outlook | www.eia.govsteo Annual Energy Outlook | www.eia.govaeo International ... 28,259 27,470 Rocky Mountain Greater Green River Hilliard-Baxter-Mancos 13,302 13,285 ...

  6. August 2012 Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    August 2012 1 August 2012 Short-Term Energy Outlook Highlights  EIA projects that the Brent crude oil spot price will average about $103 per barrel during the second half of 2012, about $3.50 per barrel higher than in last month's Outlook. The forecast Brent crude oil spot price falls to an average of $100 per barrel in 2013. The projected West Texas Intermediate (WTI) crude oil spot price discount to Brent crude oil narrows from about $14 in the third quarter of 2012 to $9 by late 2013.

  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. Short-Term Outlook for Hydrocarbon Gas Liquids

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

    Outlook for Hydrocarbon Gas Liquids March 2016 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Short-Term Energy Outlook for Hydrocarbon Gas Liquids i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee

  9. Short-term energy outlook, January 1999

    SciTech Connect (OSTI)

    1999-01-01

    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.

  10. Short-Term Energy Outlook Supplement: 2014 Outlook for Gulf of Mexico Hurricane-Related Production Outages

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

    4 Outlook for Gulf of Mexico Hurricane-Related Production Outages June 2014 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | STEO Supplement: 2014 Hurricane Outlook i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other

  11. Supplement to the Annual Energy Outlook 1993

    SciTech Connect (OSTI)

    Not Available

    1993-02-17

    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)

    1995-05-02

    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. Short-Term Energy Outlook

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

    4 1 October 2014 Short-Term Energy and Winter Fuels Outlook (STEO) Highlights EIA ... than last winter (see EIA Short-Term Energy Outlook and Winter Fuels Outlook ...

  14. Annual Energy Outlook2014

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

    For further information . . . The Annual Energy Outlook 2014 (AEO2014) was prepared by the U.S. Energy Information Administration (EIA), under the direction of John J. Conti...

  15. Short-Term Energy Outlook

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

    March 2015 Short-Term Energy Outlook (STEO) Highlights North Sea Brent crude oil ... U.S. Energy Information Administration | Short-Term Energy Outlook March 2015 2 ...

  16. Annual Energy Outlook Retrospective Review - Energy Information

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

    Administration Annual Energy Outlook Retrospective Review Release Date: March 25, 2015 | Next Release Date: April 2017 | Report Number: DOE/EIA-0640(2014) Evaluation of 2014 and Prior Reference Case Projections The U.S. Energy Information Administration (EIA) produces projections of energy production, consumption and prices each year in the Annual Energy Outlook (AEO). Each year, EIA also produces an AEO Retrospective Review document, which presents a comparison between realized energy

  17. Short-Term Energy Outlook Model Documentation: Hydrocarbon Gas Liquids Supply and Demand

    Reports and Publications (EIA)

    2015-01-01

    The hydrocarbon gas liquids (ethane, propane, butanes, and natural gasoline) module of the Short-Term Energy Outlook (STEO) model is designed to provide forecasts of U.S. production, consumption, refinery inputs, net imports, and inventories.

  18. Short-Term Energy Outlook Model Documentation: Regional Residential Propane Price Model

    Reports and Publications (EIA)

    2009-01-01

    The regional residential propane price module of the Short-Term Energy Outlook (STEO) model is designed to provide residential retail price forecasts for the 4 Census regions: Northeast, South, Midwest, and West.

  19. Short-Term Energy Outlook Model Documentation: Regional Residential Heating Oil Price Model

    Reports and Publications (EIA)

    2009-01-01

    The regional residential heating oil price module of the Short-Term Energy Outlook (STEO) model is designed to provide residential retail price forecasts for the 4 census regions: Northeast, South, Midwest, and West.

  20. Short-Term Energy Outlook Model Documentation: Petroleum Product Prices Module

    Reports and Publications (EIA)

    2015-01-01

    The petroleum products price module of the Short-Term Energy Outlook (STEO) model is designed to provide U.S. average wholesale and retail price forecasts for motor gasoline, diesel fuel, heating oil, and jet fuel.

  1. Short-Term Energy Outlook Model Documentation: Motor Gasoline Consumption Model

    Reports and Publications (EIA)

    2011-01-01

    The motor gasoline consumption module of the Short-Term Energy Outlook (STEO) model is designed to provide forecasts of total U.S. consumption of motor gasolien based on estimates of vehicle miles traveled and average vehicle fuel economy.

  2. Short-term energy outlook, April 1999

    SciTech Connect (OSTI)

    1999-04-01

    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.

  3. Short-term energy outlook, July 1998

    SciTech Connect (OSTI)

    1998-07-01

    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.

  4. Supplement to the annual energy outlook 1994

    SciTech Connect (OSTI)

    1994-03-01

    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.

  5. Annual Energy Outlook 2015

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

    Annual Energy Outlook 2015 AEO Annual Energy Outlook AEO2015 Annual Energy Outlook 2015 API American Petroleum Institute bbl Barrels bbl/d Barrels per day Brent North Sea Brent Btu British thermal unit(s) CAFE Corporate average fuel economy CAIR Clean Air Interstate Rule CHP Combined heat and power CO2 Carbon dioxide CPI Consumer price index CSAPR Cross-State Air Pollution Rule CTL Coal-to-liquids E85 Motor fuel containing up to 85% ethanol EIA U.S. Energy Information Administration EOR Enhanced

  6. Geothermal Technologies Office Current Outlook | Department of...

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

    Current Outlook Geothermal Technologies Office Current Outlook PDF icon 2015 GRC GTO ... GRC Annual Meeting 2015 Presentation: GTO Current Outlook Geothermal Technologies Office ...

  7. Energy Market Outlook

    Office of Energy Efficiency and Renewable Energy (EERE)

    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.

  8. Tribal Economic Outlook Conference

    Broader source: Energy.gov [DOE]

    Hosted by Northern Arizona University, the Tribal Economic Outlook Conference will preview the conditions that will impact business and economy in the year ahead. Hear what the experts are predicting for 2016 at the tribal, state, and local level.

  9. International Energy Outlook 2014

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

    band is very wide 2 WTI price dollars per barrel Source: EIA, Short-Term Energy Outlook, June 2015 0 25 50 75 100 125 150 Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct...

  10. International Energy Outlook 2014

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

    band is very wide 2 WTI price dollars per barrel Source: EIA, Short-Term Energy Outlook, May 2015 0 25 50 75 100 125 150 Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct...

  11. China Energy Outlook

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

    X I A O J I E X U C H A I R F E L L O W , W O R L D E N E R G Y C H I N A O U T L O O K I N S T I T U T E O F W O R L D E C O N O M I C S A N D P O L I T I C S , C H I N E S E A C A D E M Y O F S O C I A L S C I E N C E S China Energy Outlook 2020 2014-7-15 Washington DC World Energy China Outlook | Xiaojie Xu and Chen Tangsi | xuoffice@vip.sina.com 1 World Energy China Outlook 2014-2015 Annual interactive Energy Outlook Mid-year Updates IWEP Energy Chinese Academy of Social Sciences 2014-7-15

  12. Supplement to the annual energy outlook 1995

    SciTech Connect (OSTI)

    Not Available

    1995-02-01

    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.

  13. Annual Energy Outlook 2015

    Gasoline and Diesel Fuel Update (EIA)

    14, 2014 Annual Energy Outlook 2014 foresees growth of LNG as a fuel for railroads The U.S. Energy Information Administration expects liquefied natural gas, or LNG, to play an increasing role in powering freight locomotives in the coming years. EIA's Reference case, in its recently released Annual Energy Outlook 2014 indicates that growing natural gas production and lower natural gas spot prices compared to crude oil prices could provide significant cost savings for locomotives that use LNG as a

  14. International energy outlook 1996

    SciTech Connect (OSTI)

    1996-05-01

    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.

  15. Annual energy outlook 1995, with projections to 2010

    SciTech Connect (OSTI)

    1995-01-01

    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.

  16. Short-Term Energy Outlook

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

    5 1 October 2015 Short-Term Energy and Winter Fuels Outlook (STEO) Highlights EIA ... U.S. Energy Information Administration | Short-Term Energy and Winter Fuels Outlook ...

  17. Short-Term Energy Outlook

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

    April 2015 1 April 2015 Short-Term Energy and Summer Fuels Outlook (STEO) ... U.S. Energy Information Administration | Short-Term Energy and Summer Fuels Outlook April ...

  18. Short-Term Energy Outlook

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

    3 1 Short-Term Energy Outlook April 2003 Overview World Oil Markets. Crude oil prices fell ... Sources: History: EIA; Projections: Short-Term Energy Outlook, April 2003. 0 10 20 30 40 ...

  19. Short-Term Energy Outlook

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

    June 2014 1 June 2014 Short-Term Energy Outlook (STEO) Highlights North Sea Brent ... U.S. Energy Information Administration | Short-Term Energy Outlook June 2014 2 Global ...

  20. International energy outlook 2005

    SciTech Connect (OSTI)

    2005-07-01

    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'.

  1. 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.

    2012-09-01

    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.

  2. Agricultural Outlook Forum

    Broader source: Energy.gov [DOE]

    Hosted by the U.S. Department of Agriculture on February 19–20 in Crystal City, Virginia, the theme of the 91st Annual Agricultural Outlook Forum will be centered on “Smart Agriculture in the 21st Century.”

  3. Annual energy outlook 1994: With projections to 2010

    SciTech Connect (OSTI)

    Not Available

    1994-01-01

    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. Registration Open for Winter Fuels Outlook Conference on October 10, 2012 |

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

    Department of Energy 0, 2012 Registration Open for Winter Fuels Outlook Conference on October 10, 2012 September 12, 2012 - 11:16am Addthis The U.S. Department of Energy's Office of Electricity Delivery and Energy Reliability, U.S. Energy Information Administration (EIA), and the National Association of State Energy Officials are hosting the 2012 - 2013 Winter Fuels Outlook Conference on Wednesday, October 10, 2012 in Washington, DC. This important supply and demand forecast event will

  5. Registration Open for Winter Fuels Outlook Conference on October 12, 2011 |

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

    Department of Energy 2, 2011 Registration Open for Winter Fuels Outlook Conference on October 12, 2011 September 19, 2011 - 4:55pm Addthis The U.S. Department of Energy's Office of Electricity Delivery and Energy Reliability, U.S. Energy Information Administration (EIA), and the National Association of State Energy Officials invite you to participate in the 2011 - 2012 Winter Fuels Outlook Conference. This important supply and demand forecast event will be held on Wednesday, October 12,

  6. International Energy Outlook 2016-World energy demand and economc outlook -

    Gasoline and Diesel Fuel Update (EIA)

    Energy Information Administration Analysis & Projections International Energy Outlook 2016 Release Date: May 11, 2016 | Next Release Date: September 2017 | Complete PDF anticipated May 23 Chapter 1. World energy demand and economic outlook Overview The International Energy Outlook 2016 (IEO2016) Reference case projects significant growth in worldwide energy demand over the 28-year period from 2012 to 2040. Total world consumption of marketed energy expands from 549 quadrillion British

  7. International energy outlook 2006

    SciTech Connect (OSTI)

    2006-06-15

    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.

  8. Natural Gas Winter Outlook 2000-2001

    Reports and Publications (EIA)

    2000-01-01

    This article is based on the Winter Fuels Outlook published in the 4th Quarter Short-Term Energy Outlook and discusses the supply and demand outlook from October 2000 through March 2001.

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

    SciTech Connect (OSTI)

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

    2005-02-09

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

  10. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    Administration | Annual Energy Outlook 2015 Reference case Energy Information Administration Annual Energy Outlook 2015 Table A15. Coal supply, disposition, and prices ...

  11. Short Term Energy Outlook ,October 2002

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

    October 2002 1 Short-Term Energy Outlook October 2002 Overview World Oil Markets: ... Energy Information AdministrationShort-Term Energy Outlook -- October 2002 2 The OPEC ...

  12. Annual Energy Outlook Retrospective Review

    Reports and Publications (EIA)

    2015-01-01

    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.

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

    SciTech Connect (OSTI)

    1996-02-01

    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.

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

    SciTech Connect (OSTI)

    1997-04-01

    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.

  15. International energy outlook 1998

    SciTech Connect (OSTI)

    1998-04-01

    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.

  16. International energy outlook 1999

    SciTech Connect (OSTI)

    1999-03-01

    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.

  17. Assumptions and Expectations for Annual Energy Outlook 2015: Oil and Gas Working Group

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

    Assumptions and Expectations for Annual Energy Outlook 2016: Oil and Gas Working Group AEO2016 Oil and Gas Supply Working Group Meeting Office of Petroleum, Gas, and Biofuels Analysis December 1, 2015| Washington, DC http://www.eia.gov/forecasts/aeo/workinggroup/ WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE We welcome feedback on our assumptions and documentation * The AEO Assumptions report http://www.eia.gov/forecasts/aeo/assumptions/

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

    SciTech Connect (OSTI)

    1996-07-01

    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.

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

    SciTech Connect (OSTI)

    1998-01-01

    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.

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

    SciTech Connect (OSTI)

    1997-10-14

    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.

  1. International Energy Outlook 2016 - Energy Information Administration

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

    International Energy Outlook 2016 Release Date: May 11, 2016 | Next Release Date: September 2017 | Complete PDF anticipated May 23 Preface International Energy Outlook 2014 cover. The International Energy Outlook 2016 (IEO2016) presents an assessment by the U.S. Energy Information Administration (EIA) of the outlook for international energy markets through 2040. U.S. projections appearing in IEO2016 are consistent with those published in EIA's Annual Energy Outlook 2015 (AEO2015). IEO2016 is

  2. Changes in Natural Gas Monthly Consumption Data Collection and the Short-Term Energy Outlook

    Reports and Publications (EIA)

    2010-01-01

    Beginning with the December 2010 issue of the Short-Term Energy Outlook (STEO), the Energy Information Administration (EIA) will present natural gas consumption forecasts for the residential and commercial sectors that are consistent with recent changes to the Form EIA-857 monthly natural gas survey.

  3. Short-Term Energy Outlook Model Documentation: Other Petroleum Products Consumption Model

    Reports and Publications (EIA)

    2011-01-01

    The other petroleum product consumption module of the Short-Term Energy Outlook (STEO) model is designed to provide U.S. consumption forecasts for 6 petroleum product categories: asphalt and road oil, petrochemical feedstocks, petroleum coke, refinery still gas, unfinished oils, and other miscvellaneous products

  4. Short-Term Energy Outlook Model Documentation: Petroleum Products Supply Module

    Reports and Publications (EIA)

    2013-01-01

    The Petroleum Products Supply Module of the Short-Term Energy Outlook (STEO) model provides forecasts of petroleum refinery inputs (crude oil, unfinished oils, pentanes plus, liquefied petroleum gas, motor gasoline blending components, and aviation gasoline blending components) and refinery outputs (motor gasoline, jet fuel, distillate fuel, residual fuel, liquefied petroleum gas, and other petroleum products).

  5. International Energy Outlook 2013

    Gasoline and Diesel Fuel Update (EIA)

    5 U.S. Energy Information Administration | International Energy Outlook 2013 Reference case projections by end-use sector and country grouping Table F1. Total world delivered energy consumption by end-use sector and fuel, 2010-2040 (quadrillion Btu) Sector/fuel Projections Average annual percent change, 2010-2040 2010 2015 2020 2025 2030 2035 2040 Residential Liquids 9.5 9.5 9.1 8.9 8.7 8.5 8.3 -0.4 Natural gas 19.9 20.8 22.6 24.8 27.1 29.0 30.8 1.5 Coal 4.6 4.4 4.5 4.5 4.4 4.4 4.3 -0.3

  6. International Energy Outlook 2013

    Gasoline and Diesel Fuel Update (EIA)

    5 U.S. Energy Information Administration | International Energy Outlook 2013 Reference case projections by end-use sector and country grouping Table F11. Delivered energy consumption in Russia by end-use sector and fuel, 2010-2040 (quadrillion Btu) Sector/fuel Projections Average annual percent change, 2010-2040 2010 2015 2020 2025 2030 2035 2040 Residential Liquids 0.3 0.3 0.3 0.3 0.3 0.3 0.3 -0.7 Natural gas 2.8 2.7 2.8 2.9 3.1 3.3 3.5 0.8 Coal 0.3 0.3 0.3 0.3 0.2 0.2 0.2 -1.5 Electricity 0.4

  7. International Energy Outlook 2013

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | International Energy Outlook 2013 Reference case projections by end-use sector and country grouping Table F13. Delivered energy consumption in China by end-use sector and fuel, 2010-2040 (quadrillion Btu) Sector/fuel Projections Average annual percent change, 2010-2040 2010 2015 2020 2025 2030 2035 2040 Residential Liquids 1.2 1.1 1.1 1.1 1.0 1.0 0.9 -1.0 Natural gas 0.9 1.6 2.5 3.5 4.7 5.9 7.1 7.2 Coal 3.0 2.9 3.0 3.0 3.0 3.0 2.9 -0.2 Electricity 1.8

  8. International Energy Outlook 2013

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | International Energy Outlook 2013 Reference case projections by end-use sector and country grouping Table F15. Delivered energy consumption in Other Non-OECD Asia by end-use sector and fuel, 2010-2040 (quadrillion Btu) Sector/fuel Projections Average annual percent change, 2010-2040 2010 2015 2020 2025 2030 2035 2040 Residential Liquids 0.5 0.5 0.5 0.5 0.6 0.6 0.6 0.3 Natural gas 0.4 0.4 0.6 0.7 0.8 0.9 1.1 3.7 Coal 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.4

  9. International Energy Outlook 2013

    Gasoline and Diesel Fuel Update (EIA)

    1 U.S. Energy Information Administration | International Energy Outlook 2013 Reference case projections by end-use sector and country grouping Table F17. Delivered energy consumption in Africa by end-use sector and fuel, 2010-2040 (quadrillion Btu) Sector/fuel Projections Average annual percent change, 2010-2040 2010 2015 2020 2025 2030 2035 2040 Residential Liquids 0.7 0.7 0.7 0.7 0.7 0.8 0.8 0.5 Natural gas 0.2 0.2 0.3 0.3 0.4 0.5 0.6 3.4 Coal 0.1 0.1 0.1 0.1 0.1 0.2 0.2 2.5 Electricity 0.6

  10. International Energy Outlook 2013

    Gasoline and Diesel Fuel Update (EIA)

    3 U.S. Energy Information Administration | International Energy Outlook 2013 Reference case projections by end-use sector and country grouping Table F19. Delivered energy consumption in Other Central and South America by end-use sector and fuel, 2010-2040 (quadrillion Btu) Sector/fuel Projections Average annual percent change, 2010-2040 2010 2015 2020 2025 2030 2035 2040 Residential Liquids 0.3 0.4 0.3 0.3 0.3 0.3 0.3 -0.1 Natural gas 0.4 0.5 0.6 0.7 0.8 1.0 1.1 3.2 Coal 0.0 0.0 0.0 0.0 0.0 0.0

  11. International Energy Outlook 2013

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | International Energy Outlook 2013 Reference case projections by end-use sector and country grouping Table F3. Delivered energy consumption in the United States by end-use sector and fuel, 2010-2040 (quadrillion Btu) Sector/fuel Projections Average annual percent change, 2010-2040 2010 2015 2020 2025 2030 2035 2040 Residential Liquids 1.1 1.1 1.0 1.0 0.9 0.9 0.9 -1.0 Natural gas 4.9 4.8 4.6 4.5 4.5 4.3 4.2 -0.5 Coal 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -1.6

  12. International Energy Outlook 2013

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | International Energy Outlook 2013 Reference case projections by end-use sector and country grouping Table F5. Delivered energy consumption in Mexico and Chile by end-use sector and fuel, 2010-2040 (quadrillion Btu) Sector/fuel Projections Average annual percent change, 2010-2040 2010 2015 2020 2025 2030 2035 2040 Residential Liquids 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.1 Natural gas 0.1 0.1 0.1 0.1 0.1 0.1 0.1 3.4 Coal 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.2

  13. International Energy Outlook 2013

    Gasoline and Diesel Fuel Update (EIA)

    1 U.S. Energy Information Administration | International Energy Outlook 2013 Reference case projections by end-use sector and country grouping Table F7. Delivered energy consumption in Japan by end-use sector and fuel, 2010-2040 (quadrillion Btu) Sector/fuel Projections Average annual percent change, 2010-2040 2010 2015 2020 2025 2030 2035 2040 Residential Liquids 0.6 0.5 0.5 0.5 0.5 0.4 0.4 -1.2 Natural gas 0.4 0.4 0.4 0.5 0.5 0.5 0.5 0.3 Coal 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -- Electricity 1.1 1.2

  14. International Energy Outlook 2013

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | International Energy Outlook 2013 High Oil Price case projections Table D1. World total primary energy consumption by region, High Oil Price case, 2009-2040 (quadrillion Btu) Region History Projections Average annual percent change, 2010-2040 2009 2010 2015 2020 2025 2030 2035 2040 OECD OECD Americas 117.0 120.2 119.5 124.2 128.2 131.8 136.7 144.7 0.6 United States a 94.9 97.9 96.0 99.4 100.9 101.4 103.0 107.3 0.3 Canada 13.7 13.5 13.9 14.3 15.3 16.4

  15. GRC Annual Meeting 2015 Presentation: GTO Current Outlook | Department...

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

    GRC Annual Meeting 2015 Presentation: GTO Current Outlook GRC Annual Meeting 2015 Presentation: GTO Current Outlook PDF icon 2015 GRC GTO Current Outlook final.pdf More Documents & ...

  16. Instructions for using HSPD-12 Authenticated Outlook Web Access...

    Energy Savers [EERE]

    Instructions for using HSPD-12 Authenticated Outlook Web Access (OWA) Instructions for using HSPD-12 Authenticated Outlook Web Access (OWA) Provides instructions for remote Outlook...

  17. Evaluation of Forecasted Southeast Pacific Stratocumulus in the NCAR, GFDL and ECMWF Models

    SciTech Connect (OSTI)

    Hannay, C; Williamson, D L; Hack, J J; Kiehl, J T; Olson, J G; Klein, S A; Bretherton, C S; K?hler, M

    2008-01-24

    We examine forecasts of Southeast Pacific stratocumulus at 20S and 85W during the East Pacific Investigation of Climate (EPIC) cruise of October 2001 with the ECMWF model, the Atmospheric Model (AM) from GFDL, the Community Atmosphere Model (CAM) from NCAR, and the CAM with a revised atmospheric boundary layer formulation from the University of Washington (CAM-UW). The forecasts are initialized from ECMWF analyses and each model is run for 3 days to determine the differences with the EPIC field data. Observations during the EPIC cruise show a stable and well-mixed boundary layer under a sharp inversion. The inversion height and the cloud layer have a strong and regular diurnal cycle. A key problem common to the four models is that the forecasted planetary boundary layer (PBL) height is too low when compared to EPIC observations. All the models produce a strong diurnal cycle in the Liquid Water Path (LWP) but there are large differences in the amplitude and the phase compared to the EPIC observations. This, in turn, affects the radiative fluxes at the surface. There is a large spread in the surface energy budget terms amongst the models and large discrepancies with observational estimates. Single Column Model (SCM) experiments with the CAM show that the vertical pressure velocity has a large impact on the PBL height and LWP. Both the amplitude of the vertical pressure velocity field and its vertical structure play a significant role in the collapse or the maintenance of the PBL.

  18. Short-Term Energy Outlook

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

    1 December 2014 Short-Term Energy Outlook (STEO) Highlights North Sea Brent crude oil ... winter are expected to help lessen U.S. Energy Information Administration | Short-Term ...

  19. Short-Term Energy Outlook

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

    Global oil inventory builds in the third quarter U.S. Energy Information Administration | Short-Term Energy Outlook November 2015 2 of 2015 averaged 1.6 million bd, down from 2.0 ...

  20. Short-Term Energy Outlook

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

    ... U.S. Energy Information Administration | Short-Term Energy Outlook August 2014 2 Global Petroleum and Other Liquids EIA's world oil balance is virtually unchanged from last month's ...

  1. Short-Term Energy Outlook

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

    ... EIA expects the Henry Hub natural gas spot price to average 3.34million British U.S. Energy Information Administration | Short-Term Energy Outlook February 2015 2 thermal units ...

  2. Short-Term Energy Outlook

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

    (833Q) Short-Term Energy Outlook iuarterly Projections August 1983 Energy Information Administration Washington, D.C. 20585 t rt jrt- .ort- iort- iort- iort- nort- lort- '.ort- ...

  3. Short-Term Energy Outlook

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

    EIA projects end-of-October stocks will be 3,919 Bcf, 121 Bcf (3.2%) more than the five-year average. U.S. Energy Information Administration | Short-Term Energy Outlook July 2015 2 ...

  4. Short-Term Energy Outlook

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

    This would be the second-highest injection season on record. U.S. Energy Information Administration | Short-Term Energy Outlook May 2015 2 Low natural gas prices in recent ...

  5. Short-Term Energy Outlook

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

    3.69 per MMBtu in 2013 and 3.78 per MMBtu in 2014. U.S. Energy Information Administration | Short-Term Energy Outlook December 2013 2 Global Crude Oil and Liquid Fuels Total ...

  6. Short-Term Energy Outlook

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

    3.68 per MMBtu in 2013 and 3.84 per MMBtu in 2014. U.S. Energy Information Administration | Short-Term Energy Outlook November 2013 2 Global Crude Oil and Liquid Fuels ...

  7. Short-Term Energy Outlook

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

    will average 4.77MMBtu in 2014 and 4.50MMBtu in 2015. U.S. Energy Information Administration | Short-Term Energy Outlook July 2014 2 Global Petroleum and Other Liquids EIA ...

  8. Short-Term Energy Outlook

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

    0.4 million bd lower, respectively, than in July's STEO. U.S. Energy Information Administration | Short-Term Energy Outlook August 2015 2 Natural gas working inventories were ...

  9. 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

    2011-09-13

    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.

  10. International Energy Outlook 2014

    Gasoline and Diesel Fuel Update (EIA)

    Implications of Increasing Light Tight Oil Production for U.S. Refining May 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Implications of Increasing Light Oil Production on the U.S. Refining System i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts

  11. Outlook optimistic for 1997 E and P industry

    SciTech Connect (OSTI)

    Popov, S.

    1997-01-01

    The ninth annual Arthur Andersen Oil and Gas Industry Outlook Survey of company executives` forecasts for the US exploration and production industry were presented last month at the 17th Annual Energy Symposium. The consulting firm surveyed the chief financial officers of more than 350 US E and P companies, with 92 companies responding, including 8 majors, 9 large and 75 small independents. Overall, top E and P company executives predict 1997 to be a healthy year for the oil and gas industry. The paper discusses demand and supply, oil and gas prices, capital spending, employment, rig counts and availability, problems and opportunities.

  12. April 2013 Short-Term Energy and Summer Fuels Outlook

    Gasoline and Diesel Fuel Update (EIA)

    and Summer Fuels Outlook (STEO) Highlights  During the April-through-September summer driving season this year, regular gasoline retail prices are forecast to average $3.63 per gallon. The projected monthly average regular retail gasoline price falls from $3.69 per gallon in May to $3.57 per gallon in September. EIA expects regular gasoline retail prices to average $3.56 per gallon in 2013 and $3.39 per gallon in 2014, compared with $3.63 per gallon in 2012. The July 2013 New York harbor

  13. Short-Term Energy Outlook

    Reports and Publications (EIA)

    2016-01-01

    Short-term energy supply, demand, and price projections through 2015 for the United States and international oil forecasts.

  14. Short-Term Energy Outlook- May 2003

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

    3 1 Short-Term Energy Outlook May 2003 Overview World Oil Markets. The April 24 meeting of ... Sources: History: EIA; Projections: Short-Term Energy Outlook, May 2003. Energy ...

  15. Short Term Energy Outlook, December 2002

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

    December 2002 1 Short-Term Energy Outlook December 2002 Overview World Oil Markets: ... Sources: History: EIA; Projections: Short-Term Energy Outlook, December 2002. 0 10 20 30 ...

  16. Short-Term Energy Outlook February 2014

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

    4 1 February 2014 Short-Term Energy Outlook (STEO) Highlights Temperatures east of the ... U.S. Energy Information Administration | Short-Term Energy Outlook February 2014 2 Global ...

  17. Short Term Energy Outlook, March 2003

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

    3 1 Short-Term Energy Outlook March 2003 Overview World Oil Markets. February crude oil ... Sources: History: EIA; Projections: Short-Term Energy Outlook, March 2003. 0 10 20 30 40 ...

  18. Short Term Energy Outlook, February 2003

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

    3 1 Short-Term Energy Outlook February 2003 Overview World Oil Markets. World oil markets ... Sources: History: EIA; Projections: Short-Term Energy Outlook, February 2003. 0 10 20 30 ...

  19. Short Term Energy Outlook ,November 2002

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

    November 2002 1 Short-Term Energy Outlook November 2002 Overview World Oil Markets: During ... Sources: History: EIA; Projections: Short-Term Energy Outlook, November 2002. 0 10 20 30 ...

  20. Short-Term Energy Outlook: Changes to the Natural Gas Storage Regions

    Gasoline and Diesel Fuel Update (EIA)

    Short-Term Energy Outlook: Changes to the Natural Gas Storage Regions December 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Short-Term Energy Outlook: Changes to the Natural Gas Storage Regions 1 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are

  1. Microsoft Word - Hurricane Outlook.doc

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

    Information Administration/Short-Term Energy Outlook Supplement - June 2010 1 June 2010 Short-Term Energy Outlook Supplement: 2010 Outlook for Hurricane-Related Production Outages in the Gulf of Mexico Highlights  The National Oceanic and Atmospheric Administration's (NOAA) Atlantic Hurricane Season Outlook, released on May 27, 2010, predicted that the Atlantic basin will likely experience above-normal tropical weather activity during the upcoming hurricane season (June 1 - November 30). 1

  2. Review of EIA Oil Production Outlooks

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

    Review of EIA oil production outlooks For 2014 EIA Energy Conference July 15, 2014 | Washington, DC By Samuel Gorgen, Upstream Analyst Overview Gorgen, Tight Oil Production Trends EIA Conference, July 15, 2014 2 * Drilling Productivity Report performance review - Permian - Eagle Ford - Bakken * Crude oil production projections - Short-Term Energy Outlook - Annual Energy Outlook - International tight oil outlook * New DPR region highlights: Utica Drilling Productivity Report review - major tight

  3. 2015 Trilateral Energy Outlook Project

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

    2015 Trilateral Energy Outlook Project December 2015 Prepared by: The National Energy Board Canada Secretaría de Energía de México U.S. Energy Information Administration 2015 Trilateral Energy Outlook Project i This report was prepared in support of the North American Cooperation on Energy Information by the National Energy Board Canada (NEB), the Secretaría de Energía de México (SENER), and the U.S. Energy Information Administration (EIA). Results do not necessarily reflect the countries'

  4. World nuclear outlook 1994

    SciTech Connect (OSTI)

    1994-12-01

    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.

  5. World nuclear outlook 1995

    SciTech Connect (OSTI)

    1995-09-29

    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.

  6. The outlook for natural gas

    SciTech Connect (OSTI)

    1993-12-31

    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.

  7. Annual energy outlook 1999, with projections to 2020

    SciTech Connect (OSTI)

    1998-12-01

    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.

  8. State Energy Efficiency Program Evaluation Inventory - Energy Information

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

    Administration Analysis & Projections Glossary › FAQS › Overview Projection Data Monthly short-term forecasts to 2016 Annual projections to 2040 International projections All projections reports Analysis & Projections Major Topics Most popular Annual Energy Outlook related Congressional & other requests International Energy Outlook related Presentations Recurring Short-Term Outlook Related Special outlooks Testimony All reports Browse by Tag Alphabetical Frequency Tag Cloud

  9. Solar Forecasting

    Broader source: Energy.gov [DOE]

    On December 7, 2012, DOE announced $8 million to fund two solar projects that are helping utilities and grid operators better forecast when, where, and how much solar power will be produced at U.S....

  10. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

    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.

  11. Short-Term Energy Outlook Supplement: Weather Sensitivity in Natural Gas Markets

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

    Short-Term Energy Outlook Supplement: Weather Sensitivity in Natural Gas Markets October 2014 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | STEO Supplement: Weather Sensitivity in Natural Gas Markets i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are

  12. Short-Term Energy Outlook - U.S. Energy Information Administration (EIA)

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

    ‹ Analysis & Projections Short-Term Energy Outlook Release Date: May 10, 2016 | Next Release Date: June 7, 2016 | Full Report | Text Only | All Tables | All Figures Glossary › FAQS › Overview STEO Report Highlights Prices Global Petroleum and Other Liquids U.S. Petroleum and Other Liquids Natural Gas Coal Electricity Renewables and Carbon Dioxide Emissions U.S. Economic Assumptions Data Figures Tables Custom Table Builder Real Prices Viewer Forecast Changes (PDF) Special Analysis Price

  13. Short-Term Energy Outlook - U.S. Energy Information Administration (EIA)

    Gasoline and Diesel Fuel Update (EIA)

    ‹ Analysis & Projections Short-Term Energy Outlook Release Date: May 10, 2016 | Next Release Date: June 7, 2016 | Full Report | Text Only | All Tables | All Figures Glossary › FAQS › Overview STEO Report Highlights Prices Global Petroleum and Other Liquids U.S. Petroleum and Other Liquids Natural Gas Coal Electricity Renewables and Carbon Dioxide Emissions U.S. Economic Assumptions Data Figures Tables Custom Table Builder Real Prices Viewer Forecast Changes (PDF) Special Analysis Price

  14. Short-Term Energy Outlook Model Documentation: Natural Gas Consumption and Prices

    Reports and Publications (EIA)

    2015-01-01

    The natural gas consumption and price modules of the Short-Term Energy Outlook (STEO) model are designed to provide consumption and end-use retail price forecasts for the residential, commercial, and industrial sectors in the nine Census districts and natural gas working inventories in three regions. Natural gas consumption shares and prices in each Census district are used to calculate an average U.S. retail price for each end-use sector.

  15. 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.

    1989-03-01

    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.

  16. Energy Information Administration/Short-Term Energy Outlook ...

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

    5 1 Short-Term Energy Outlook August 2005 Short-Term Energy Outlook - Regional Enhancements Starting with this edition of the Short-Term Energy Outlook (STEO), EIA is introducing ...

  17. Energy Information Administration/Short-Term Energy Outlook ...

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

    April 2005 1 Short-Term Energy Outlook April 2005 2005 Summer Motor Gasoline Outlook ... Energy Information AdministrationShort-Term Energy Outlook - April 2005 2 High levels of ...

  18. Energy Information Administration/Short-Term Energy Outlook ...

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

    6 1 April 2006 Short-Term Energy Outlook and Summer Fuels Outlook April 11, 2006 Release ... Energy Information AdministrationShort-Term Energy Outlook - April 2006 2 Higher diesel ...

  19. Annual Energy Outlook 2015 - Appendix F

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

    F-3 U.S. Energy Information Administration | Annual Energy Outlook 2015 Regional maps Figure F2. Electricity market module regions Source: U.S. Energy Information Administration, ...

  20. Annual Energy Outlook 2015 - Appendix A

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

    Reference case Table A2. Energy consumption by sector and source (quadrillion Btu per year, unless otherwise noted) Energy Information Administration Annual Energy Outlook 2015 ...

  1. Annual Energy Outlook 2015 - Appendix A

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

    3 U.S. Energy Information Administration | Annual Energy Outlook 2015 Reference case Table A6. Industrial sector key indicators and consumption Energy Information Administration ...

  2. Annual Energy Outlook 2015 - Appendix A

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

    6 Reference case Energy Information Administration Annual Energy Outlook 2015 Table A3. Energy prices by sector and source (2013 dollars per million Btu, unless otherwise noted) ...

  3. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    2015 Reference case Table A12. Petroleum and other liquids prices (2013 dollars per gallon, unless otherwise noted) Energy Information Administration Annual Energy Outlook 2015 ...

  4. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    Reference case Energy Information Administration Annual Energy Outlook 2015 Table A17. Renewable energy consumption by sector and source (quadrillion Btu per year) Sector and ...

  5. Annual Energy Outlook 2015 - Energy Information Administration

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

    Annual Energy Outlook 2015 Release Date: April 14, 2015 | Next Release Date: June 2016 | ... Executive summary Economic growth Prices Delivered energy consumption by sector Energy ...

  6. Assumptions to the Annual Energy Outlook 2014 - Abbreviations

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

    AEO: Annual Energy Outlook AEO2012: Annual Energy Outlook 2012 AFUE: Average Fuel Use Efficiency ANWR: Artic National Wildlife Refuge ARRA2009: American Recovery and...

  7. International energy outlook 1997 with projections to 2015

    SciTech Connect (OSTI)

    1997-04-01

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

  8. Energy Information Administration/Short-Term Energy Outlook ...

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

    January 2005 1 Short-Term Energy Outlook January 2005 Winter Fuels Update (Figure 1) ... Energy Information AdministrationShort-Term Energy Outlook - January 2005 2 Because oil ...

  9. Energy Information Administration/Short-Term Energy Outlook ...

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

    5 1 Short-Term Energy Outlook June 2005 2005 Summer Motor Fuels Outlook Update (Figure 1) ... recently diminished; in practice, only Energy Information AdministrationShort-Term ...

  10. Natural Gas Summary from the Short-Term Energy Outlook

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

    change the pattern of annual demand shifts reported in earlier Outlooks. Short-Term Natural Gas Market Outlook, December 2002 History Projections Sep-02 Oct-02 Nov-02...

  11. Annual energy outlook 1997 with projections to 2015

    SciTech Connect (OSTI)

    1996-12-01

    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.

  12. Forecast Change

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

    Forecast Change 2011 2012 2013 2014 2015 2016 from 2015 United States Usage (kWh) 3,444 3,354 3,129 3,037 3,153 3,143 -0.3% Price (centskWh) 12.06 12.09 12.58 13.04 12.95 12.96 ...

  13. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01

    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.

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

    SciTech Connect (OSTI)

    1998-10-01

    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. Annual outlook for US electric power, 1986

    SciTech Connect (OSTI)

    Not Available

    1986-04-24

    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.

  16. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    Annual Energy Outlook 2015 AEO Annual Energy Outlook AEO2015 Annual Energy Outlook 2015 API American Petroleum Institute bbl Barrels bbl/d Barrels per day Brent North Sea Brent Btu British thermal unit(s) CAFE Corporate average fuel economy CAIR Clean Air Interstate Rule CHP Combined heat and power CO2 Carbon dioxide CPI Consumer price index CSAPR Cross-State Air Pollution Rule CTL Coal-to-liquids E85 Motor fuel containing up to 85% ethanol EIA U.S. Energy Information Administration EOR Enhanced

  17. Short-Term Energy Outlook March 2014

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

    ... EIA expects the WTI discount to average 10bbl in 2014 and 11bbl in 2015. U.S. Energy Information Administration | Short-Term Energy Outlook March 2014 2 Cold weather also ...

  18. Short-Term Energy Outlook May 2014

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

    ... than in last month's STEO, and 4.33MMBtu in 2015. U.S. Energy Information Administration | Short-Term Energy Outlook May 2014 2 Global Petroleum and Other Liquids EIA ...

  19. Short-Term Energy Outlook February 2016

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

    in 2017, compared with an average of 2.63MMBtu in 2015. U.S. Energy Information Administration | Short-Term Energy Outlook February 2016 2 Global Petroleum and Other Liquid Fuels ...

  20. Short-Term Energy Outlook March 2016

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

    other renewables increases from 8% in 2016 to 9% in 2017. U.S. Energy Information Administration | Short-Term Energy Outlook March 2016 2 Global Petroleum and Other Liquid Fuels ...

  1. Short Term Energy Outlook, January 2003

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

    3 1 Short-Term Energy Outlook January 2003 Overview World Oil Markets. The oil market is ... underground storage levels at a much Energy Information AdministrationShort-Term ...

  2. Short-Term Energy Outlook September 2014

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

    ... Projected natural gas working U.S. Energy Information Administration | Short-Term Energy Outlook September 2014 2 inventories reach 3.48 Tcf at the end of October, 0.34 Tcf below ...

  3. Short-Term Energy Outlook April 2014

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

    will average 4.44MMBtu in 2014 and 4.11MMBtu in 2015. U.S. Energy Information Administration | Short-Term Energy Outlook April 2014 2 Global Petroleum and Other Liquids EIA ...

  4. Short-Term Energy Outlook July 2013

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

    1 July 2013 Short-Term Energy Outlook (STEO) Highlights The U.S. Energy Information Administration (EIA) expects that the Brent crude oil spot price will average 102 per ...

  5. 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.

  6. 2016 NASEO Energy Policy Outlook Conference

    Broader source: Energy.gov [DOE]

    NASEO’s Energy Policy Outlook Conference is the national forum to connect with and learn from state energy officials working on innovative energy policies and programs, and to engage with federal officials on priority energy issues.

  7. Annual energy outlook 1998 with projections to 2020

    SciTech Connect (OSTI)

    1997-12-01

    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.

  8. Annual Energy Outlook 2011 Reference Case

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

    October 9, 2012 | Washington, DC Annual Energy Outlook 2013: Modeling Updates in the Transportation Sector WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE Overview 2 * Modeling updates made to the Annual Energy Outlook 2013 Reference case * Light-duty vehicle technology updates * Heavy-duty natural gas vehicles * Preliminary results (Working group presentation for discussion purposes. Do not quote or cite as results are subject to change)

  9. Summer 2003 Motor Gasoline Outlook.doc

    Gasoline and Diesel Fuel Update (EIA)

    3 1 Short-Term Energy Outlook April 2003 Summer 2003 Motor Gasoline Outlook Summary For the upcoming summer season (April to September 2003), high crude oil costs and other factors are expected to yield average retail motor gasoline prices higher than those of last year. Current crude oil prices reflect a substantial uncertainty premium due to concerns about the current conflict in the Persian Gulf, lingering questions about whether Venezuelan oil production will recover to near pre-strike

  10. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | Annual Energy Outlook 2015 Reference case Table A4. Residential sector key indicators and consumption (quadrillion Btu per year, unless otherwise noted) Energy Information Administration / Annual Energy Outlook 2015 Table A4. Residential sector key indicators and consumption (quadrillion Btu per year, unless otherwise noted) Key indicators and consumption Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Key indicators

  11. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    1 U.S. Energy Information Administration | Annual Energy Outlook 2015 Reference case Table A5. Commercial sector key indicators and consumption (quadrillion Btu per year, unless otherwise noted) Energy Information Administration / Annual Energy Outlook 2015 Table A5. Commercial sector key indicators and consumption (quadrillion Btu per year, unless otherwise noted) Key indicators and consumption Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Key indicators

  12. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    A-3 U.S. Energy Information Administration | Annual Energy Outlook 2015 Reference case Table A2. Energy consumption by sector and source (quadrillion Btu per year, unless otherwise noted) Energy Information Administration / Annual Energy Outlook 2015 Table A2. Energy consumption by sector and source (quadrillion Btu per year, unless otherwise noted) Sector and source Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Energy consumption Residential Propane

  13. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    23 U.S. Energy Information Administration | Annual Energy Outlook 2015 Reference case Table A11. Petroleum and other liquids supply and disposition (million barrels per day, unless otherwise noted) Energy Information Administration / Annual Energy Outlook 2015 Table A11. Petroleum and other liquids supply and disposition (million barrels per day, unless otherwise noted) Supply and disposition Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Crude oil Domestic

  14. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | Annual Energy Outlook 2015 Reference case Table A13. Natural gas supply, disposition, and prices (trillion cubic feet per year, unless otherwise noted) Energy Information Administration / Annual Energy Outlook 2015 Table A13. Natural gas supply, disposition, and prices (trillion cubic feet, unless otherwise noted) Supply, disposition, and prices Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Supply Dry gas production

  15. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    5 U.S. Energy Information Administration | Annual Energy Outlook 2015 Reference case Energy Information Administration / Annual Energy Outlook 2015 Table A18. Energy-related carbon dioxide emissions by sector and source (million metric tons, unless otherwise noted) Sector and source Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Residential Petroleum .............................................................. 61 64 50 45 41 37 33 -2.4% Natural gas

  16. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | Annual Energy Outlook 2015 Reference case Energy Information Administration / Annual Energy Outlook 2015 Table A21. International petroleum and other liquids supply, disposition, and prices (million barrels per day, unless otherwise noted) Supply, disposition, and prices Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Crude oil spot prices (2013 dollars per barrel) Brent

  17. Annual Energy Outlook 2011 Reference Case

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

    Outlook for U.S. Coal and Nuclear Electricity Generation for 2013 EIA Energy Conference June 18, 2013 | Washington, DC by Jim Diefenderfer, Office of Electricity, Coal, Nuclear & Renewables Analysis U. S. Energy Information Administration Over time the electricity mix gradually shifts to lower-carbon options, led by growth in natural gas and renewable generation 2 U.S. electricity net generation trillion kilowatthours Source: EIA, Annual Energy Outlook 2013 25% 19% 42% 13% 1% Nuclear Oil and

  18. DOE/EIA-0202(84/3Q) Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    3Q) Short-Term Energy Outlook pn Quarterly Projections August 1984 Published: September 1984 Energy Information Administration Washington, D.C. t- jrt .ort lort .iort .iort iort iort iort ort Tt jm .erm -Term Term Term Term Term Term Term Term Term Term Term Term Term -Term -Term nergy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy ^nergy Outlook Outlook Outlook Outlook Outlook Outlook Outlook

  19. DOE/EIA-0202(84/4Q) Short-Term Energy Outlook Quarterly Projections

    Gasoline and Diesel Fuel Update (EIA)

    4Q) Short-Term Energy Outlook Quarterly Projections October 1984 Published: November 1984 Energy Information Administration Washington, D.C. t rt jrt .ort lort iort lort iort lort \ort ort Tt .erm Term Term Term Term Term Term Term Term Term Term Term Term Term -Term -Term xrm nergy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy ^nergy Outlook Outlook Outlook Outlook Outlook Outlook Outlook

  20. DOE/EIA-0202(85/2Q) Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    2Q) Short-Term Energy Outlook amm Quarterly Projections April 1985 Published: May 1985 Energy Information Administration Washington, D C t rt jrt .ort lort .iort iort iort lort '.ort ort .erm -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term xrm nergy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Outlook Outlook Outlook Outlook Outlook Outlook Outlook

  1. DOE/EIA-0202(85/3Q) Short-Term Energy Outlook Quarterly Projections

    Gasoline and Diesel Fuel Update (EIA)

    3Q) Short-Term Energy Outlook Quarterly Projections July 1985 Published: August 1985 Energy Information Administration Washington, D C t rt jrt .ort lort iort iort iort iort '.ort ort Tt .-m .erm -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy ^nergy Outlook Outlook Outlook Outlook Outlook Outlook Outlook

  2. Short-Term Energy Outlook September 2013

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

    The U.S. Energy Information Administration's (EIA) forecast for Brent crude oil spot ... of 2013 and 96 per barrel during 2014. Energy price forecasts are highly uncertain and ...

  3. LED Watch: The Outlook for OLEDs | Department of Energy

    Energy Savers [EERE]

    Watch: The Outlook for OLEDs LED Watch: The Outlook for OLEDs PDF icon LED Watch: December 2014 More Documents & Publications 2015 ARTICLES What's Next for Solid-State Lighting - February 2015 OLED Stakeholder Report

  4. Energy Information Administration/Short-Term Energy Outlook ...

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

    July 2005 1 Short-Term Energy Outlook July 2005 2005 Summer Motor Fuels Outlook Update ... other Persian Gulf countries in 2005 and Energy Information AdministrationShort-Term ...

  5. Short-Term Energy and Winter Fuels Outlook October 2013

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

    3 1 October 2013 Short-Term Energy and Winter Fuels Outlook (STEO) Highlights EIA ... 5-year average (see EIA Short-Term Energy and Winter Fuels Outlook slideshow). ...

  6. Energy Information Administration/Short-Term Energy Outlook ...

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

    5 1 Short-Term Energy Outlook May 2005 2005 Summer Motor Gasoline Outlook Update (Figure ... or 2.5 percent per year, down from the Energy Information AdministrationShort-Term ...

  7. Energy Information Administration/Short-Term Energy Outlook ...

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

    5 1 October 2005 Short-Term Energy Outlook and Winter Fuels Outlook October 12, 2005 ... of an active hurricane season on domestic energy supply and prices are unfortunately being ...

  8. INFOGRAPHIC: Offshore Wind Outlook | Department of Energy

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

    INFOGRAPHIC: Offshore Wind Outlook INFOGRAPHIC: Offshore Wind Outlook December 12, 2012 - 2:15pm Addthis According to a new report commissioned by the Energy Department, a U.S. offshore wind industry that takes advantage of this abundant domestic resource could support up to 200,000 manufacturing, construction, operation and supply chain jobs across the country and drive over $70 billion in annual investments by 2030. Infographic by <a href="node/379579">Sarah Gerrity</a>.

  9. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    1 U.S. Energy Information Administration | Annual Energy Outlook 2015 Reference case Energy Information Administration / Annual Energy Outlook 2015 Table A16. Renewable energy generating capacity and generation (gigawatts, unless otherwise noted) Net summer capacity and generation Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Electric power sector 1 Net summer capacity Conventional hydroelectric power ...................... 78.1 78.3 79.2 79.6 79.7 79.8 80.1

  10. Annual Energy Outlook 2015 - Appendix B

    Gasoline and Diesel Fuel Update (EIA)

    5 U.S. Energy Information Administration | Annual Energy Outlook 2015 Regional maps Figure F4. Oil and gas supply model regions F-5 U.S. Energy Information Administration | Annual Energy Outlook 2014 Regional maps Figure F4. Oil and gas supply model regions Figure F4. Oil and Gas Supply Model Regions Atlantic WA MT WY ID NV UT CO AZ NM OK IA KS MO IL IN KY TN MS AL FL GA SC NC WV PA NJ MD DE NY CT ME RI MA NH VA WI MI OH NE SD MN ND AR OR CA VT East (1) Gulf of Mexico LA Gulf Coast (2)

  11. Annual Energy Outlook 2015 - Appendix F

    Gasoline and Diesel Fuel Update (EIA)

    1 U.S. Energy Information Administration | Annual Energy Outlook 2015 Source: U.S. Energy Information Administration, Office of Energy Analysis. U.S. Energy Information Administration / Annual Energy Outlook 2010 213 Appendix F Regional Maps Figure F1. United States Census Divisions Pacific South Atlantic Middle Atlantic New England West South Central West North Central East North Central Mountain AK WA MT WY ID NV UT CO AZ NM TX OK IA KS MO IL IN KY TN MS AL FL GA SC NC WV PA NJ MD DE NY CT VT

  12. DOE/EIA-0202(85/4Q) Short-Term Energy Outlook OBIS Quarterly

    Gasoline and Diesel Fuel Update (EIA)

    5/4Q) Short-Term Energy Outlook OBIS Quarterly Projections October 1985 Energy Information Administration Washington, D C t rt jrt .ort lort .iort aort iort iort <.ort ort Tt .-m .erm Term Term Term Term Term Term Term Term Term Term Term Term Term -Term -Term xrm uergy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy ^nergy Outlook Outlook Outlook Outlook Outlook Outlook Outlook Outlook Outlook

  13. DOE/EIA-0202|83/2Q)-1 Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    |83/2Q)-1 Short-Term Energy Outlook Volume 1-Quarterly Projections May 1983 Energy Information Administration Washington, D.C. t rt jrt .ort lort iort iort lOrt iort '.ort- ort Tt . m .erm Term Term Term Term Term Term Term Term Term Term Term Term Term -Term -Term nergy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy ^nergy Outlook Outlook Outlook Outlook Outlook Outlook Outlook Outlook Outlook

  14. Supplemental Tables to the Annual Energy Outlook

    Reports and Publications (EIA)

    2015-01-01

    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.

  15. DOE/EIA-0202(85/1Q) Short-Term Energy Outlook Quarterly Projections

    Gasoline and Diesel Fuel Update (EIA)

    1Q) Short-Term Energy Outlook Quarterly Projections January 1985 Published: February 1985 Energy Information Administration Washington, D.C. t rt jrt .ort lort lort lort nort lort *.ort ort Tt .m .erm -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term uergy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy ^nergy Outlook Outlook Outlook Outlook Outlook Outlook

  16. Annual Energy Outlook 2011 Reference Case

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

    August 14, 2012 | Washington, DC Annual Energy Outlook 2013: Modeling Updates in the Transportation Sector WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE Overview 2 AEO2013 Transportation Model Updates Washington, D.C., August 2012 Discussion purposes only - Do not cite or circulate * Light-duty vehicle - Light-duty vehicle technology update based on EPA/NHTSA Notice of Proposed Rule for model years 2017 through 2025 * Heavy-duty vehicle

  17. Annual Energy Outlook 2014 Modeling Updates

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

    Analysis; Energy Consumption and Efficiency Analysis July 23, 2013 | Washington, DC Annual Energy Outlook 2014: Modeling Updates in the Transportation Sector Overview 2 AEO2014 Transportation Model Updates Washington, D.C., July 2013 Discussion purposes only - Do not cite or circulate * Light-duty vehicle - Vehicle miles traveled by age cohort, update modeling parameters, employment and VMT - E85 demand - Battery electric vehicle cost, efficiency, and availability * Heavy-duty vehicle, rail,

  18. Annual Energy Outlook 2014 Preliminary Results

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

    Working Group 2 September 25, 2013 | Washington, DC By Trisha Hutchins and Nicholas Chase Office of Transportation Energy Consumption and Efficiency Analysis Annual Energy Outlook 2014: transportation modeling updates and preliminary results Overview 2 AEO2014 Transportation Working Group 2: Modeling updates and preliminary results Washington, D.C., September 25, 2013 Discussion purposes only - Do not cite or circulate * Macroeconomic drivers - GDP, population, world oil price * Light-duty

  19. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    2 Reference case Table A10. Electricity trade (billion kilowatthours, unless otherwise noted) Energy Information Administration / Annual Energy Outlook 2015 Table A10. Electricity trade (billion kilowatthours, unless otherwise noted) Electricity trade Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Interregional electricity trade Gross domestic sales Firm power .......................................................... 156 157 122 63 28 28 28 -6.2% Economy

  20. EIA - Annual Energy Outlook 2014 Early Release

    Gasoline and Diesel Fuel Update (EIA)

    Analysis & Projections Annual Energy Outlook 2015 Release Date: April 14, 2015 | Next Release Date: June 2016 | correction | full report Overview Data Reference Case Side Cases Interactive Table Viewer By Section Executive summary Economic growth Prices Delivered energy consumption by sector Energy consumption by primary fuel Energy intensity Energy production, imports, and exports Electricity generation Energy-related carbon dioxide emissions Appendices Table Title Formats Summary Reference

  1. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    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 Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Crude oil Lower 48 average wellhead price 1 (2013 dollars per barrel) ...................................... 96 97 75 87 101 117 136 1.3% Production (million barrels per day) 2 United States total ............................................... 6.50 7.44

  2. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    6 Reference case Table A19. Energy-related carbon dioxide emissions by end use (million metric tons) Energy Information Administration / Annual Energy Outlook 2015 Table A19. Energy-related carbon dioxide emissions by end use (million metric tons) Sector and end use Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Residential Space heating ........................................................ 228 293 248 236 228 218 207 -1.3% Space cooling

  3. Assumptions to the Annual Energy Outlook 2015

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

    Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2015 [1] (AEO2015), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy

  4. International energy outlook 1995, May 1995

    SciTech Connect (OSTI)

    1995-06-01

    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.

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

    Reports and Publications (EIA)

    1998-01-01

    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.

  6. Instructions for using HSPD-12 Authenticated Outlook Web Access (OWA) |

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

    Department of Energy using HSPD-12 Authenticated Outlook Web Access (OWA) Instructions for using HSPD-12 Authenticated Outlook Web Access (OWA) Provides instructions for remote Outlook access using HSPD-12 Badge. PDF icon HSPD-12 Badge Instructions More Documents & Publications User Guide for Remote Access to VDI/Workplace Using PIV Headquarters Facilities Master Security Plan - Chapter 1, Physical Security Audit Report: IG-0860

  7. Annual Energy Outlook 2013 Early Release Reference Case

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

    emission intensity index, 20051 Source: EIA, Annual Energy Outlook 2015 Reference case History Projections 2013 Carbon dioxide emissions per 2009 dollar GDP Energy use per 2009...

  8. Energy Information Administration/Short-Term Energy Outlook ...

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

    February 2005 1 Short-Term Energy Outlook February 2005 Winter Fuels Update (Figure 1) ... Given this stock build, OPEC said it would reconsider market conditions and Energy ...

  9. QUARTER SHORT-TERM ENERGY OUTLOOK QUARTERLY PROJECTIONS ENERGY...

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

    1Q) 1991 1 QUARTER SHORT-TERM ENERGY OUTLOOK QUARTERLY PROJECTIONS ENERGY INFORMATION ADMINISTRATION February 1991 This publication may be purchased from the Superintendent of ...

  10. QUARTER SHORT-TERM ENERGY OUTLOOK QUARTERLY PROJECTIONS ENERGY...

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

    >OEEIA-0202(923Q) 1992 3 QUARTER SHORT-TERM ENERGY OUTLOOK QUARTERLY PROJECTIONS ENERGY INFORMATION ADMINISTRATION August 1992 This publication and other Energy Information ...

  11. United States Annual Energy Outlook 2012 (Early Release) | Open...

    Open Energy Info (EERE)

    URI: cleanenergysolutions.orgcontentunited-states-annual-energy-outlook-2 Language: English Policies: "Deployment Programs,Regulations" is not in the list of possible...

  12. SEP Special Projects Report: Future Outlook and Appendix

    SciTech Connect (OSTI)

    None

    2000-07-01

    The Sharing Success appendix provides the future outlook for SEP as well as charts and graphs for grants and Special Projects.

  13. Natural Gas Summary from the Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    to increase because of accelerated economic growth and generally lower prices. Short-Term Natural Gas Market Outlook, October 2003 History Projections Jul-03 Aug-03 Sep-03...

  14. Natural Gas Summary from the Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    to increase because of accelerated economic growth and generally lower prices. Short-Term Natural Gas Market Outlook, November 2003 History Projections Aug-03 Sep-03 Oct-03...

  15. DOE/EIA-0202(84/1Q) Short-Term Energy Outlook Quarterly Projections

    Gasoline and Diesel Fuel Update (EIA)

    1Q) Short-Term Energy Outlook Quarterly Projections February 1984 Published: March 1984 Energy Information Administration Washington, D.C. t rt jrt- .ort- iort- iort- .iort- iort- lort- <ort- ort Tt- .erm -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term -Term Term Term .-Term -Term uergy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy ^nergy Outlook Outlook Outlook Outlook Outlook

  16. probabilistic energy production forecasts

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

    energy production forecasts - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary ...

  17. Wind Power Forecasting Data

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

    Operations Call 2012 Retrospective Reports 2012 Retrospective Reports 2011 Smart Grid Wind Integration Wind Integration Initiatives Wind Power Forecasting Wind Projects Email...

  18. Forecasting Water Quality & Biodiversity

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

    Forecasting Water Quality & Biodiversity March 25, 2015 Cross-cutting Sustainability ... that measure feedstock production, water quality, water quantity, and biodiversity. ...

  19. Wind Power Forecasting

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

    data Presentations BPA Super Forecast Methodology Related Links Near Real-time Wind Animation Meteorological Data Customer Supplied Generation Imbalance Dynamic Transfer Limits...

  20. DOE/EIA-0202(84/2QH Short-Term Energy Outlook Quarterly Projections

    Gasoline and Diesel Fuel Update (EIA)

    2QH Short-Term Energy Outlook Quarterly Projections May 1984 Published: June 1984 Energy Information Administration Washington, D.C. t rt jrt .ort lort .iort .iort- iort- iort- '.ort- ort- .m .erm Term Term Term Term Term Term Term Term Term Term Term Term i-Term rTerm -Term xrm uergy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy Energy ^nergy Outlook Outlook Outlook Outlook Outlook Outlook Outlook

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

    SciTech Connect (OSTI)

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04

    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.

  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.

    2011-08-26

    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. EIA - Annual Energy Outlook 2016 Early Release

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

    AEO2016 Early Release: Summary of Two Cases Release Date: May 17, 2016 | Full Report Release Date: July 7, 2016 | Report Number: DOE/EIA-0383ER(2016) This release is an annotated PowerPoint summary and the data for two cases from the Annual Energy Outlook 2016-the Reference case and the No Clean Power Plan case. The AEO2016 full version, including additional cases and discussion, will be released July 7, 2016. Download the AEO2016 Early Release: An Annotated Summary of Two Cases The Annual

  4. Annual Energy Outlook 2015 - Appendix A

    Gasoline and Diesel Fuel Update (EIA)

    6 Reference case Table A7. Transportation sector key indicators and delivered energy consumption Energy Information Administration / Annual Energy Outlook 2015 Table A7. Transportation sector key indicators and delivered energy consumption Key indicators and consumption Reference case Annual growth 2013-2040 (percent) 2012 2013 2020 2025 2030 2035 2040 Key indicators Travel indicators (billion vehicle miles traveled) Light-duty vehicles less than 8,501 pounds .... 2,578 2,644 2,917 3,090 3,287

  5. International Energy Outlook 2016-Electricity - Energy Information

    Gasoline and Diesel Fuel Update (EIA)

    Administration 5. Electricity Overview In the International Energy Outlook 2016 (IEO2016) Reference case, world net electricity generation increases 69% by 2040, from 21.6 trillion kilowatthours (kWh) in 2012 to 25.8 trillion kWh in 2020 and 36.5 trillion kWh in 2040. Electricity is the world's fastest-growing form of end-use energy consumption, as it has been for many decades. Power systems have continued to evolve from isolated, small grids to integrated national markets and even

  6. Annual Energy Outlook 2015 - Appendix B

    Gasoline and Diesel Fuel Update (EIA)

    B-1 U.S. Energy Information Administration | Annual Energy Outlook 2015 Table B1. Total energy supply, disposition, and price summary (quadrillion Btu per year, unless otherwise noted) Supply, disposition, and prices 2013 Projections 2020 2030 2040 Low economic growth Reference High economic growth Low economic growth Reference High economic growth Low economic growth Reference High economic growth Production Crude oil and lease condensate .................... 15.6 22.2 22.2 22.2 20.8 21.1 21.3

  7. Annual Energy Outlook 2015 - Appendix B

    Gasoline and Diesel Fuel Update (EIA)

    C-1 U.S. Energy Information Administration | Annual Energy Outlook 2015 Table C1. Total energy supply, disposition, and price summary (quadrillion Btu per year, unless otherwise noted) Supply, disposition, and prices 2013 Projections 2020 2030 2040 Low oil price Reference High oil price Low oil price Reference High oil price Low oil price Reference High oil price Production Crude oil and lease condensate .................... 15.6 20.9 22.2 25.6 18.2 21.1 26.2 15.0 19.9 20.9 Natural gas plant

  8. Annual Energy Outlook 2015 - Appendix D

    Gasoline and Diesel Fuel Update (EIA)

    D-1 U.S. Energy Information Administration | Annual Energy Outlook 2015 Table D1. Total energy supply, disposition, and price summary (quadrillion Btu per year, unless otherwise noted) Supply, disposition, and prices 2013 Projections 2020 2030 2040 Reference High oil and gas resource Reference High oil and gas resource Reference High oil and gas resource Production Crude oil and lease condensate ................................... 15.6 22.2 26.3 21.1 32.6 19.9 34.6 Natural gas plant liquids

  9. Annual Energy Outlook 2015 - Appendix F

    Gasoline and Diesel Fuel Update (EIA)

    3 U.S. Energy Information Administration | Annual Energy Outlook 2015 Regional maps Figure F2. Electricity market module regions Source: U.S. Energy Information Administration, Office of Energy Analysis. 1 2 3 4 5 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 6 7 1. ERCT TRE All 2. FRCC FRCC All 3. MROE MRO East 4. MROW MRO West 5. NEWE NPCC New England 6. NYCW NPCC NYC/Westchester 7. NYLI NPCC Long Island 8. NYUP NPCC Upstate NY 9. RFCE RFC East 10. RFCM RFC Michigan 11. RFCW RFC West 12. SRDA

  10. Annual Energy Outlook 2015 - Appendix F

    Gasoline and Diesel Fuel Update (EIA)

    6 Regional maps Figure F5. Natural gas transmission and distribution model regions 218 U.S. Energy Information Administration / Annual Energy Outlook 2010 Figure F5. Natural Gas Transmission and Distribution Model Regions Pacifi c (9) Moun tain (8) CA (12) AZ/N M (11) W. North Centr al (4) W. South Centr al (7) E. South Centr al (6) E. North Centr al (3) S. Atlan tic (5) FL (10) Mid. Atlan tic (2) New Engl. (1) W. Canad a E. Canad a MacK enzie Alask a Canad a Offsh ore and LNG Mexic o Baham as

  11. Annual Energy Outlook 2015 - Appendix F

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | Annual Energy Outlook 2015 Regional maps Figure F6. Coal supply regions WA ID OR CA NV UT TX OK AR MO LA MS AL GA FL TN SC NC KY VA WV WY CO SD ND MI MN WI IL IN OH MD PA NJ DE CT MA NH VT NY ME RI MT NE IA KS MI AZ NM 500 0 SCALE IN MILES APPALACHIA Northern Appalachia Central Appalachia Southern Appalachia INTERIOR NORTHERN GREAT PLAINS Eastern Interior Western Interior Gulf Lignite Dakota Lignite Western Montana Wyoming, Northern Powder River Basin

  12. Fujifilm_NERSC_StorageOutlook.pptx

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

    A Storage Outlook for Energy Sciences: Data Intensive, Throughput and Exascale Computing --- 1 --- October, 2 013 National Energy Research Scientific ! Computing Center (NERSC) * L ocated a t B erkeley L ab * User facility to support 6 DOE Offices of Science: * 5000 u sers, 7 00 r esearch p rojects * 48 s tates; 6 5% f rom u niversi=es * Hundreds o f u sers e ach d ay * ~1500 p ublica=ons p er y ear * With s ervices f or c onsul=ng, d ata analysis a nd m ore --- 2 --- Types of Computing at NERSC

  13. Using Wikipedia to forecast disease

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

    Using Wikipedia to forecast disease Using Wikipedia to forecast disease Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. December 22, 2014 Using Wikipedia to forecast disease Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. Contact Nancy Ambrosiano Communications Office (505) 667-0471 Email "A global disease-forecasting system will improve

  14. NREL: Transmission Grid Integration - Forecasting

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

    Forecasting NREL researchers use solar and wind resource assessment and forecasting techniques to develop models that better characterize the potential benefits and impacts of ...

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

    SciTech Connect (OSTI)

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

    2014-05-01

    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.

  16. Short-Term Outlook for Hydrocarbon Gas Liquids - Energy Information...

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

    Figures Tables Custom Table Builder Real Prices Viewer Forecast Changes (PDF) Special ... The liquid fuels production forecast reflects a 1.24 million bd decline in crude oil ...

  17. Short-Term Energy Outlook Model Documentation: Carbon Dioxide (CO2) Emissions Model

    Reports and Publications (EIA)

    2009-01-01

    Description of the procedures for estimating carbon dioxide emissions in the Short-Term Energy Outlook

  18. Outlook for Biomass Ethanol Production and Demand

    Reports and Publications (EIA)

    2000-01-01

    This paper presents a midterm forecast for biomass ethanol production under three different technology cases for the period 2000 to 2020, based on projections developed from the Energy Information Administration's National Energy Modeling System. An overview of cellulose conversion technology and various feedstock options and a brief history of ethanol usage in the United States are also presented.

  19. Acquisition Forecast | Department of Energy

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

    Acquisition Forecast Acquisition Forecast Acquisition Forecast It is the policy of the U.S. Department of Energy (DOE) to provide timely information to the public regarding DOE's forecast of future prime contracting opportunities and subcontracting opportunities which are available via the Department's major site and facilities management contractors. This forecast has been expanded to also provide timely status information for ongoing prime contracting actions that are valued in excess of the

  20. The forecast calls for flu

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

    The forecast calls for flu Science on the Hill: The forecast calls for flu Using mathematics, computer programs, statistics and information about how disease develops and spreads, a research team at Los Alamos National Laboratory found a way to forecast the flu season and even next week's sickness trends. January 15, 2016 Forecasting flu A team from Los Alamos has developed a method to predict flu outbreaks based in part on influenza-related searches of Wikipedia. The forecast calls for flu

  1. Natural Gas Summary from the Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    63 and 2.72 per MMBtu during the months through October without the wide variations that occurred over the spring and early summer months (Short-Term Energy Outlook, August 2002)....

  2. The Outlook for Energy: A View to 2030

    Broader source: Energy.gov [DOE]

    Presents an outlook on the future supply and demand for energy until the year 2030, with a major focus on oil, natural gas, coal, and renewable sources of energy.

  3. Workshop to Examine Outlook for State and Federal Policies to...

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

    around the country will discuss the outlook for state and federal policies to help expand geothermal energy at an all-day workshop scheduled for Reno, Nevada on October 4. The...

  4. Energy Information Administration/Short-Term Energy Outlook ...

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

    5 1 Short-Term Energy Outlook September 2005 Hurricane Katrina (Figures 1 and 2) The Gulf ... Service (MMS) and the Department of Energy) with shut-in oil and natural gas ...

  5. IN-SPIRE: Creating a Visualization from Microsoft Outlook

    ScienceCinema (OSTI)

    None

    2012-12-31

    IN-SPIRE can harvest text from Microsoft Outlook e-mail messages via a simple drag-and-drop mechanism. This is great for mailing lists or systems that send search results via e-mail.

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

    Reports and Publications (EIA)

    2003-01-01

    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.

  7. Short-Term Energy and Winter Fuels Outlook October 2013

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

    3 1 October 2013 Short-Term Energy and Winter Fuels Outlook (STEO) Highlights EIA projects average U.S. household expenditures for natural gas and propane will increase by 13%...

  8. Natural Gas Summary from the Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    the rest of the winter and perhaps well into spring, with prices averaging 4.90 per MMBtu through March and 4.45 in April (Short-Term Energy Outlook, February 2003). Wellhead...

  9. Natural Gas Summary from the Short-Term Energy Outlook

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

    the rest of the winter and the first part of spring, with prices averaging 5.19 per MMBtu through March and 4.58 in April (Short-Term Energy Outlook, February 2004). Wellhead...

  10. Natural Gas Summary from the Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    commercial sector demand are offset by lower demand in the electric power sector. Short-Term Natural Gas Market Outlook, September 2003 History Projections Jun-03 Jul-03 Aug-03...

  11. Natural Gas Summary from the Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    by 1.8 percent as the economy continues to expand and prices ease slightly. Short-Term Natural Gas Market Outlook, January 2004 History Projections Oct-03 Nov-03 Dec-03...

  12. Natural Gas Summary from the Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    economy. In 2003, natural gas demand growth is expected across all sectors. Short-Term Natural Gas Market Outlook, July 2002 History Projections Apr-02 Ma May-02 Jun-02...

  13. Natural Gas Summary from the Short-Term Energy Outlook

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

    of 2005 relative to the first quarter of 2004 and relatively lower fuel oil prices. Short-Term Natural Gas Market Outlook, April 2004 History Projections Jan-04 Feb-04 Mar-04...

  14. Natural Gas Summary from the Short-Term Energy Outlook

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

    should relieve some of the potential upward price pressure on the domestic market Short-Term Natural Gas Market Outlook, January 2003 History Projections Oct-02 Nov-02 Dec-02...

  15. Natural Gas Summary from the Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    because of somewhat weaker prices and higher demand in the electric power sector. Short-Term Natural Gas Market Outlook, July 2003 History Projections Apr-03 May-03 Jun-03 Jul-03...

  16. Natural Gas Summary from the Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    than those of 2003, when stocks after the winter of 2002-2003 were at record lows. Short-Term Natural Gas Market Outlook, December 2003 History Projections Sep-03 Oct-03 Nov-03...

  17. Natural Gas Summary from the Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    power sector eases and relative coal and fuel oil spot prices decline somewhat. Short-Term Natural Gas Market Outlook, May 2004 History Projections Feb-04 Mar-04 Apr-04 May-04...

  18. Natural Gas Summary from the Short-Term Energy Outlook

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

    demand in the first quarter of 2005 relative to the first quarter of 2004. Short-Term Natural Gas Market Outlook, March 2004 History Projections Dec-03 Jan-04 Feb-04...

  19. The Outlook for Renewable Electricity in the United States

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

    The Outlook for Renewable Electricity in the United States For 2014 EIA Energy Conference July 14, 2014 | Washington, DC By Gwen Bredehoeft Assessing the role of policy and other uncertainties Renewables have accounted for an increasing share of capacity additions over the last decade U.S. annual electricity generation capacity additions gigawatts Source: EIA, Annual Energy Outlook 2014 0 10 20 30 40 50 60 1990 1995 2000 2005 2010 Other renewables Solar Wind Hydropower and other Natural gas and

  20. Annual Energy Outlook 2013 Renewable Electricity Working Group

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

    Annual Energy Outlook 2013 Renewable Electricity Working Group Summary, Aug. 2, 2012 On Thursday, August 2 EIA held the first of two Renewable Electricity Working Groups to discuss issues related to the development of the Annual Energy Outlook 2013. The meeting was well attended by stakeholders from EIA, other DOE staff, industry associations, and interested consultants. Attendance included those there in person and through conference call/web interface. The meeting agenda can be found on Page 2

  1. Annual Energy Outlook 2014: Electricity Working Group Meeting-72413

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

    Electricity Analysis Team Office of Electricity, Coal, Nuclear, and Renewables Analysis Office of Energy Analysis Annual Energy Outlook 2014: Electricity Working Group Meeting July 24, 2013 Annual Energy Outlook 2014 Reference Case: Key Changes 2 Electricity Analysis Team, July 24th, 2013 * Environmental Rules - Updates to NEMS modeling of MATS - RGGI cap tightened to reflect February 2013 MOU * Enhancements - Reserve margins and capacity payments - Spinning and operating reserves - Operations

  2. International Energy Outlook 2016-Executive Summary - Energy Information

    Gasoline and Diesel Fuel Update (EIA)

    Administration Executive Summary print version The outlook for energy use worldwide presented in the International Energy Outlook 2016 (IEO2016) continues to show rising levels of demand over the next three decades, led by strong increases in countries outside of the Organization for Economic Cooperation and Development (OECD) [3], particularly in Asia. Non-OECD Asia, including China and India, account for more than half of the world's total increase in energy consumption over the 2012 to

  3. Annual Energy Outlook 2011 Reference Case

    Gasoline and Diesel Fuel Update (EIA)

    April 2016 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 Annual Coal Distribution Report 2014 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as

  4. Assumptions to the Annual Energy Outlook 2015

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

    00 Appendix A: Handling of federal and selected state legislation and regulations in the AEO Residential sector Legislation Brief description AEO handling Basis A. National Appliance Energy Conservation Act of 1987 (NAECA87) Requires Secretary of Energy to set minimum efficiency standards for various appliance categories with periodic updates Include categories represented in the AEO residential sector forecast Public Law 100-12 a. Room air conditioners Sets standards for room air conditioners

  5. Assumptions to the Annual Energy Outlook 2015

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

    International Energy Module The National Energy Modeling System International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the IEM computes Brent and WTI prices, provides a supply curve of world

  6. Final Report- Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations

    Broader source: Energy.gov [DOE]

    Four major research objectives were completed over the course of this study. Three of the objectives were to evaluate three, new, state-of-the-art solar irradiance forecasting models. The fourth objective was to improve the California independent system operator’s load forecasts by integrating behind-the-meter photovoltaic forecasts.

  7. Annual Energy Outlook 2013 - Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    Active hurricane season expected to shut-in higher amount of oil and natural gas production An above-normal 2013 hurricane season is expected to cause a median production loss of about 19 million barrels of U.S. crude oil and 46 billion cubic feet of natural gas production in the Gulf of Mexico, according to the new forecast from the U.S. Energy Information Administration. That's about one-third more than the amount of oil and gas production knocked offline during last year's hurricane season.

  8. NASEO 2010 Winter Fuels Outlook Conference October 13, 2010...

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

    warmer than forecast If 10% colder than forecast Heating oil 12 0 25 Natural gas 4 -7 12 Propane 8 -3 18 Electricity -2 -6 2 Average of all fuels 3 -6 10 Source: EIA Short-Term...

  9. Unconventional gas outlook: resources, economics, and technologies

    SciTech Connect (OSTI)

    Drazga, B.

    2006-08-15

    The report explains the current and potential of the unconventional gas market including country profiles, major project case studies, and new technology research. It identifies the major players in the market and reports their current and forecasted projects, as well as current volume and anticipated output for specific projects. Contents are: Overview of unconventional gas; Global natural gas market; Drivers of unconventional gas sources; Forecast; Types of unconventional gas; Major producing regions Overall market trends; Production technology research; Economics of unconventional gas production; Barriers and challenges; Key regions: Australia, Canada, China, Russia, Ukraine, United Kingdom, United States; Major Projects; Industry Initiatives; Major players. Uneconomic or marginally economic resources such as tight (low permeability) sandstones, shale gas, and coalbed methane are considered unconventional. However, due to continued research and favorable gas prices, many previously uneconomic or marginally economic gas resources are now economically viable, and may not be considered unconventional by some companies. Unconventional gas resources are geologically distinct in that conventional gas resources are buoyancy-driven deposits, occurring as discrete accumulations in structural or stratigraphic traps, whereas unconventional gas resources are generally not buoyancy-driven deposits. The unconventional natural gas category (CAM, gas shales, tight sands, and landfill) is expected to continue at double-digit growth levels in the near term. Until 2008, demand for unconventional natural gas is likely to increase at an AAR corresponding to 10.7% from 2003, aided by prioritized research and development efforts. 1 app.

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

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

    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. ...

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

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

    and Outlook for the U.S. Non-Automotive Fuel Cell Industry: Impacts of Government ... ORNLTM-2011101 STATUS AND OUTLOOK FOR THE U.S. NON-AUTOMOTIVE FUEL CELL INDUSTRY: ...

  12. INSTRUCTIONS FOR USING HSPD-12 AUTHENTICATED OUTLOOK WEB ACCESS (OWA)

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

    7/2013 Page 1 INSTRUCTIONS FOR USING HSPD-12 AUTHENTICATED OUTLOOK WEB ACCESS (OWA) Outlook Web Access provides access to unencrypted email only and is suitable for use from any computer. HSPD-12 OWA REQUIREMENTS:  An EITS provided Exchange email account  A DOE issued HSPD-12 badge  DOEnet or Internet access and a supported web browser  A smart card reader installed* on your computer (*Windows Vista, Windows XP, MAC OS X 10.7 & 10.8, will also require smart card software to be

  13. Using Wikipedia to forecast diseases

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

    Using Wikipedia to forecast diseases Using Wikipedia to forecast diseases Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. November 13, 2014 Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Contact Nancy Ambrosiano Communications Office (505)

  14. An Updated Annual Energy Outlook 2009 Reference Case Reflecting Provisions of the American Recovery and Reinvestment Act and Recent Changes in the Economic Outlook

    Reports and Publications (EIA)

    2009-01-01

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

  15. Annual Energy Outlook 2009 with Projections to 2030

    SciTech Connect (OSTI)

    2009-03-01

    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.

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

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

    Figures Tables Custom Table Builder Real Prices Viewer Forecast Changes (PDF) Special ... Previous STEO Forecasts: Changes in Forecast from Last Month STEO Archives March 2016 ...

  17. Supply Forecast and Analysis (SFA)

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

    Science Team Leader Oak Ridge National Laboratory DOE Bioenergy Technologies Office (BETO) 2015 Project Peer Review Supply Forecast and Analysis (SFA) 2 | Bioenergy Technologies ...

  18. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01

    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.

  19. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    Zip: 94965 Region: Bay Area Sector: Services Product: Intelligent Monitoring and Forecasting Services Year Founded: 2010 Website: www.forecastenergy.net Coordinates:...

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

    SciTech Connect (OSTI)

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

    2011-02-15

    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.

  1. Solar Energy Market Forecast | Open Energy Information

    Open Energy Info (EERE)

    Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast AgencyCompany Organization: United States Department of Energy Sector:...

  2. Module 6 - Metrics, Performance Measurements and Forecasting...

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

    6 - Metrics, Performance Measurements and Forecasting Module 6 - Metrics, Performance Measurements and Forecasting This module focuses on the metrics and performance measurement ...

  3. Intermediate future forecasting system

    SciTech Connect (OSTI)

    Gass, S.I.; Murphy, F.H.; Shaw, S.H.

    1983-12-01

    The purposes of the Symposium on the Department of Energy's Intermediate Future Forecasting System (IFFS) were: (1) to present to the energy community details of DOE's new energy market model IFFS; and (2) to have an open forum in which IFFS and its major elements could be reviewed and critiqued by external experts. DOE speakers discussed the total system, its software design, and the modeling aspects of oil and gas supply, refineries, electric utilities, coal, and the energy economy. Invited experts critiqued each of these topics and offered suggestions for modifications and improvement. This volume documents the proceedings (papers and discussion) of the Symposium. Separate abstracts have been prepared for each presentation for inclusion in the Energy Data Base.

  4. Assumptions to Annual Energy Outlook - Energy Information Administration

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

    Assumptions to AEO2015 Release Date: September 10, 2015 | Next Release Date: September 2016 | full report Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2015 AEO2015 [1] (AEO2015), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed

  5. Annual Energy Outlook 2015 Modeling updates in the Transportation sector

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

    For AEO2015 Working Group July 30, 2014 | Washington, DC By Nicholas Chase, Trisha Hutchins, John Maples Office of Energy Consumption and Efficiency Analysis Modeling updates in the transportation sector Data updates 2 * Update historical fuel consumption data to latest state energy data (2011), annual national data from Monthly Energy Review (2012), and most recent Short-Term Energy Outlook * Update historical light-duty vehicle attribute data through 2013 (pending) * Update historical

  6. February 2013 Short-Term Energy Outlook (STEO)

    Gasoline and Diesel Fuel Update (EIA)

    Erin Boedecker, Session Moderator April 27, 2011 | Washington, DC Energy Demand. Efficiency, and Consumer Behavior 16 17 18 19 20 21 22 23 24 25 2005 2010 2015 2020 2025 2030 2035 2010 Technology Reference Expanded Standards Expanded Standards + Codes -7.6% ≈ 0 Expanded standards and codes case limits combined buildings delivered energy to 21 quadrillion Btu by 2035 2 Erin Boedecker, EIA Energy Conference, April 27, 2011 delivered energy quadrillion Btu Source: EIA, Annual Energy Outlook 2011

  7. Short-Term Energy Outlook April 2000--STEO Preface

    Gasoline and Diesel Fuel Update (EIA)

    April 2000 Summer 2000 Motor Gasoline Outlook Summary For the upcoming summer season (April to September), motor gasoline markets are projected to exhibit an extraordinarily tight supply/demand balance. * Retail gasoline prices (regular grade) are expected to average $1.46 per gallon, 25 percent higher than last summer's average of $1.17 per gallon. That projection also exceeds the previous (current-dollar) record summer average of $1.35 recorded in 1981. Nominal prices are expected to reach a

  8. International Energy Outlook 2016-Natural gas - Energy Information

    Gasoline and Diesel Fuel Update (EIA)

    Administration 3. Natural gas Overview Consumption of natural gas worldwide is projected to increase from 120 trillion cubic feet (Tcf) in 2012 to 203 Tcf in 2040 in the International Energy Outlook 2016 (IEO2016) Reference case. By energy source, natural gas accounts for the largest increase in world primary energy consumption. Abundant natural gas resources and robust production contribute to the strong competitive position of natural gas among other resources. Natural gas remains a key

  9. International Energy Outlook 2016-Transportation sector energy consumption

    Gasoline and Diesel Fuel Update (EIA)

    - Energy Information Administration 8. Transportation sector energy consumption Overview In the International Energy Outlook 2016 (IEO2016) Reference case, transportation sector delivered energy consumption increases at an annual average rate of 1.4%, from 104 quadrillion British thermal units (Btu) in 2012 to 155 quadrillion Btu in 2040. Transportation energy demand growth occurs almost entirely in regions outside of the Organization for Economic Cooperation and Development (non-OECD), with

  10. Demand and Price Outlook for Phase 2 Reformulated Gasoline, 2000

    Gasoline and Diesel Fuel Update (EIA)

    Demand and Price Outlook for Phase 2 Reformulated Gasoline, 2000 Tancred Lidderdale and Aileen Bohn (1) Contents * Summary * Introduction * Reformulated Gasoline Demand * Oxygenate Demand * Logistics o Interstate Movements and Storage o Local Distribution o Phase 2 RFG Logistics o Possible Opt-Ins to the RFG Program o State Low Sulfur, Low RVP Gasoline Initiatives o NAAQS o Tier 2 Gasoline * RFG Production Options o Toxic Air Pollutants (TAP) Reduction o Nitrogen Oxides (NOx) Reduction o

  11. Science on Tap - Forecasting illness

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

    Science on Tap - Forecasting illness Science on Tap - Forecasting illness WHEN: Mar 17, 2016 5:30 PM - 7:00 PM WHERE: UnQuarked Wine Room 145 Central Park Square, Los Alamos, New Mexico 87544 USA CONTACT: Linda Anderman (505) 665-9196 CATEGORY: Bradbury INTERNAL: Calendar Login Event Description Mark your calendars for this event held every third Thursday from 5:30 to 7 p.m. A short presentation is followed by a lively discussion on a different subject each month. Forecasting the flu (and other

  12. Instructions for Using Secure Email via Outlook Web Access | Department of

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

    Energy Secure Email via Outlook Web Access Instructions for Using Secure Email via Outlook Web Access Outlook Web Access provides access to unencrypted email only and is suitable for use from any computer. Secure Email Requirements: An EITS provided Exchange email account An EITS provided RSA SecureID Token with an active account in the EITS-managed RSA Authentication Server Appropriate access granted Active Directory group membership DOEnet or Internet access and a supported web browser

  13. Statement from Secretary of Energy Samuel W. Bodman Regarding EIA's Updated Annual Energy Outlook

    Broader source: Energy.gov [DOE]

    WASHINGTON, DC - Earlier today the Department of Energy's Energy Information Administration released their Annual Energy Outlook 2008. Energy Secretary Samuel Bodman made the following statement...

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

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

    Analysis & Projections Short-Term Energy Outlook Release ... Data Figures Tables Custom Table Builder Real Prices Viewer ... March 8, 2016 Electric power sector solar capacity series ID ...

  15. Microsoft PowerPoint - BP 2030 Outlook (EIA conference Apr 2011).ppt

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

    BP Energy Outlook 2030 Washington, DC 26 April 2011 Energy Outlook 2030 2 © BP 2011 Global trends US particulars What can bend the trend? Outline Energy Outlook 2030 3 © BP 2011 Non-OECD economies drive consumption growth Billion toe Billion toe 0 2 4 6 8 10 12 14 16 18 1990 2000 2010 2020 2030 OECD Non-OECD 0 2 4 6 8 10 12 14 16 18 1990 2000 2010 2020 2030 Renewables Hydro Nuclear Coal Gas Oil * * Includes biofuels Energy Outlook 2030 4 © BP 2011 Gas and renewables win as fuel shares

  16. Acquisition Forecast Download | Department of Energy

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

    Acquisition Forecast Download Acquisition Forecast Download Click on the link to download a copy of the DOE HQ Acquisition Forecast. File Acquisition-Forecast-2016-05-06.xlsx More Documents & Publications Small Business Program Manager Directory EA-1900: Notice of Availability of a Draft Environmental Assessment Small Business Program Manager Directory

  17. Issues in Midterm Analysis and Forecasting

    Reports and Publications (EIA)

    1999-01-01

    Final issue of this report. Presents a series of eight papers, which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1999, as well as other significant issues in midterm energy markets.

  18. Selected papers on fuel forecasting and analysis

    SciTech Connect (OSTI)

    Gordon, R.L.; Prast, W.G.

    1983-05-01

    Of the 19 presentations at this seminar, covering coal, uranium, oil, and gas issues as well as related EPRI research projects, eleven papers are published in this volume. Nine of the papers primarily address coal-market analysis, coal transportation, and uranium supply. Two additional papers provide an evaluation and perspective on the art and use of coal-supply forecasting models and on the relationship between coal and oil prices. The authors are energy analysts and EPRI research contractors from academia, the consulting profession, and the coal industry. A separate abstract was prepared for each of the 11 papers.

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

    SciTech Connect (OSTI)

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

    2009-06-01

    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.

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

    SciTech Connect (OSTI)

    1998-04-01

    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.

  1. International Energy Outlook 2016-Petroleum and other liquid fuels - Energy

    Gasoline and Diesel Fuel Update (EIA)

    Information Administration 2. Petroleum and other liquid fuels Overview In the International Energy Outlook 2016 (IEO2016) Reference case, worldwide consumption of petroleum and other liquid fuels increases from 90 million barrels per day (b/d) in 2012 to 100 million b/d in 2020 and 121 million b/d in 2040. Much of the growth in world liquid fuels consumption is projected for the emerging, non-Organization for Economic Cooperation and Development (non-OECD) economies of Asia, the Middle

  2. 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

    2014-04-30

    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.

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

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

    Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report PDF icon Wind Forecast Improvement Project ...

  4. Uncertainty Reduction in Power Generation Forecast Using Coupled...

    Office of Scientific and Technical Information (OSTI)

    quantify the forecast uncertainty by reducing prediction intervals of forecasts. ... means, e.g., using weather-based models, and reduce forecast errors prediction intervals. ...

  5. Picture of the Week: Forecasting Flu

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

    3 Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? March 6, 2016 flu epidemics modellled using social media Watch the video on YouTube. Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? Using real-time data from Wikipedia and social media, Sara del

  6. Forecasting the 2013–2014 influenza season using Wikipedia

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

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are appliedmore » to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.« less

  7. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect (OSTI)

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are applied to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.

  8. EIA lowers forecast for summer gasoline prices

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

    EIA lowers forecast for summer gasoline prices U.S. gasoline prices are expected to be ... according to the new monthly forecast from the U.S. Energy Information Administration. ...

  9. Wind Forecasting Improvement Project | Department of Energy

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

    Forecasting Improvement Project Wind Forecasting Improvement Project October 3, 2011 - 12:12pm Addthis This is an excerpt from the Third Quarter 2011 edition of the Wind Program R&D Newsletter. In July, the Department of Energy launched a $6 million project with the National Oceanic and Atmospheric Administration (NOAA) and private partners to improve wind forecasting. Wind power forecasting allows system operators to anticipate the electrical output of wind plants and adjust the electrical

  10. NREL: Resource Assessment and Forecasting Home Page

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

    NREL's resource assessment and forecasting research supports industry, government, and academia by providing renewable energy resource measurements, models, maps, and support services. These resources are used to plan and develop renewable energy technologies and support climate change research. Learn more about NREL's resource assessment and forecasting research: Capabilities Facilities Research staff Data and resources. Resource assessment and forecasting research is primarily performed at

  11. EPRI conference proceedings: solar and wind power - 1982 status and outlook

    SciTech Connect (OSTI)

    DeMeo, E.A.

    1983-02-01

    Separate abstracts were prepared for 18 papers in this proceedings. Not separately abstracted are speeches and presentations covering: past progress and future directions in solar and wind power research and development, new directions in Federal solar electric programs, Solar Energy Research Institute status and outlook, ARCO Solar Industries' involvement in the production of potential solar electric technologies, wind power status and outlook, utility requirements, roles and rewards, and a panel discussion on solar and wind power status and outlook as viewed from industrial, utility, financial, and government perspectives. (LEW)

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

    SciTech Connect (OSTI)

    1996-04-01

    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.

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

    SciTech Connect (OSTI)

    Thomas, L.C.

    1994-10-01

    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.

  14. Workshop to Examine Outlook for State and Federal Policies to Promote Geothermal Energy in the West

    Broader source: Energy.gov [DOE]

    Experts from around the country will discuss the outlook for state and federal policies to help expand geothermal energy at an all-day workshop scheduled for Reno, Nevada on October 4.

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

    Gasoline and Diesel Fuel Update (EIA)

    Previous Short-Term Energy Outlook reports are available in the original Adobe Acrobat PDF file with text, charts, and tables, or just the monthly data tables in an Excel file. +...

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

    SciTech Connect (OSTI)

    1998-02-01

    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.

  17. Measuring Changes in Energy Efficiency for the Annual Energy Outlook 2002

    Reports and Publications (EIA)

    2002-01-01

    This paper describes the methodology used to develop the National Energy Modeling System estimate of projected aggregate energy efficiency and to describe the results of applying it to the Annual Energy Outlook 2002 (AEO2002) reference case.

  18. Impacts of Unconventional Gas Technology in the Annual Energy Outlook 2000

    Reports and Publications (EIA)

    2000-01-01

    This paper describes the methodology used in the National Energy Modeling System (NEMS) to represent unconventional gas technologies and their impacts on projections in the Annual Energy Outlook 2000 (AEO2000).

  19. FROZEN HEAT A GLOBAL OUTLOOK ON METHANE GAS HYDRATES EXECUTIVE SUMMARY

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

    FROZEN HEAT A GLOBAL OUTLOOK ON METHANE GAS HYDRATES EXECUTIVE SUMMARY Beaudoin, Y. C., Boswell, R., Dallimore, S. R., and Waite, W. (eds), 2014. Frozen Heat: A UNEP Global Outlook on Methane Gas Hydrates. United Nations Environment Programme, GRID-Arendal. © United Nations Environment Programme, 2014 This publication may be reproduced in whole or in part and in any form for educational or non-profit purposes without special permission from the copyright holder, provided acknowledgement of the

  20. Annual Energy Outlook 2014 foresees growth of LNG as a fuel for railroads

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

    14, 2014 Annual Energy Outlook 2014 foresees growth of LNG as a fuel for railroads The U.S. Energy Information Administration expects liquefied natural gas, or LNG, to play an increasing role in powering freight locomotives in the coming years. EIA's Reference case, in its recently released Annual Energy Outlook 2014 indicates that growing natural gas production and lower natural gas spot prices compared to crude oil prices could provide significant cost savings for locomotives that use LNG as a

  1. Status and Outlook for the U.S. Non-Automotive Fuel Cell Industry: Impacts

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

    of Government Policies and Assessment of Future Opportunities | Department of Energy 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. Non-Automotive Fuel Cell Industry: Impacts of Government Policies and Assessment of Future Opportunities This report prepared by Oak Ridge National Laboratory examines the progress that has been made in U.S. non-automotive fuel cell

  2. Savannah River Site 2012 Outlook: Transuranic Waste Program Set to Safely

    Office of Environmental Management (EM)

    Reach Milestone | Department of Energy 2012 Outlook: Transuranic Waste Program Set to Safely Reach Milestone Savannah River Site 2012 Outlook: Transuranic Waste Program Set to Safely Reach Milestone January 1, 2012 - 12:00pm Addthis By May, Savannah River Nuclear Solutions expects to be shipping transuranic waste to the Waste Isolation Pilot Plant almost continuously, using six TRUPACT-III shipping containers like the one shown here. By May, Savannah River Nuclear Solutions expects to be

  3. Introduction to energy storage with market analysis and outlook

    SciTech Connect (OSTI)

    Schmid, Robert; Pillot, Christophe

    2014-06-16

    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. Annual Energy Outlook 2016: Electricity Sector Preliminary Results

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

    Electricity Sector Preliminary Results For Electricity AEO2016 Working Group February 10, 2016| Washington, DC By EIA, Office of Electricity, Coal, Nuclear & Renewables Analysis WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE Summary 2 Electricity Analysis Team February 10, 2016 * Address issues raised by stakeholders * Discuss recent developments- updates to generator status and capital costs * Present preliminary AEO2016 forecast

  5. Annual Energy Outlook 2011 with Projections to 2035

    SciTech Connect (OSTI)

    2011-04-01

    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.

  6. 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

    2011-03-28

    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.

  7. ARM - CARES - Tracer Forecast for CARES

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

    CampaignsCarbonaceous Aerosols and Radiative Effects Study (CARES)Tracer Forecast for CARES Related Links CARES Home AAF Home ARM Data Discovery Browse Data Post-Campaign Data Sets Field Updates CARES Wiki Campaign Images Experiment Planning Proposal Abstract and Related Campaigns Science Plan Operations Plan Measurements Forecasts News News & Press Backgrounder (PDF, 1.45MB) G-1 Aircraft Fact Sheet (PDF, 1.3MB) Contacts Rahul Zaveri, Lead Scientist Tracer Forecasts for CARES This webpage

  8. Solar Forecast Improvement Project | Department of Energy

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

    NOAA also will provide advanced satellite products. INNOVATIONS NOAA is providing numerical weather prediction (NWP) modeling with new information that will help solar forecasts. ...

  9. Development and Demonstration of Advanced Forecasting, Power...

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

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

  10. NREL: Resource Assessment and Forecasting - Webmaster

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

    email address: Your message: Send Message Printable Version Resource Assessment & Forecasting Home Capabilities Facilities Working with Us Research Staff Data & Resources Did...

  11. Forecast and Funding Arrangements - Hanford Site

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

    Annual Waste Forecast and Funding Arrangements About Us Hanford Site Solid Waste Acceptance Program What's New Acceptance Criteria Acceptance Process Becoming a new Hanford...

  12. Annual energy outlook 2009 with projections to 2030

    SciTech Connect (OSTI)

    2009-03-15

    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.

  13. December 2012 Short-Term Energy Outlook (STEO)

    Gasoline and Diesel Fuel Update (EIA)

    (STEO)  EIA expects that the Brent crude oil spot price will average $110 per barrel in the fourth quarter of 2012, while the West Texas Intermediate (WTI) crude oil spot price will average $89 per barrel. The Brent and WTI crude oil spot prices are forecast to average $104 per barrel and $88 per barrel, respectively, in 2013. The projected WTI discount to Brent crude oil, which averaged $23 per barrel in November 2012, falls to an average of $11 per barrel by the fourth quarter of 2013. This

  14. Annual Energy Outlook 2013 with Projections to 2040

    SciTech Connect (OSTI)

    2013-04-01

    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.

  15. NP2010: An Assessment and Outlook for Nuclear Physics

    SciTech Connect (OSTI)

    Lancaster, James

    2014-05-22

    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.

  16. Data Collection and Comparison with Forecasted Unit Sales of...

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

    Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types PDF icon Data Collection ...

  17. Study forecasts disappearance of conifers due to climate change

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

    Study forecasts disappearance of conifers due to climate change Study forecasts disappearance of conifers due to climate change New results, reported in a paper released today in ...

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

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

    Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits ... Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits ...

  19. Modeling and forecasting the distribution of Vibrio vulnificus...

    Office of Scientific and Technical Information (OSTI)

    Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay Citation Details In-Document Search Title: Modeling and forecasting the distribution of Vibrio ...

  20. Improving the Accuracy of Solar Forecasting Funding Opportunity...

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

    Improving the Accuracy of Solar Forecasting Funding Opportunity Improving the Accuracy of Solar Forecasting Funding Opportunity Through the Improving the Accuracy of Solar ...

  1. U.S. Chamber of Commerce Biofuels Dialogue Series: Outlook for an Emerging

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

    Global Biofuels Market | Department of Energy Commerce Biofuels Dialogue Series: Outlook for an Emerging Global Biofuels Market U.S. Chamber of Commerce Biofuels Dialogue Series: Outlook for an Emerging Global Biofuels Market January 29, 2008 - 10:53am Addthis Remarks as Prepared For Delivery by Secretary Bodman Thank you very much, Bruce, for that kind introduction. My thanks also to Tom Donahue and the leadership of the Chamber for inviting me to be with you today. I was quite pleased to

  2. Propane Market Outlook Key Market Trends, Opportunities, and Threats Facing the Consumer

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

    Propane Market Outlook Key Market Trends, Opportunities, and Threats Facing the Consumer Propane Industry Through 2025 Prepared for the Propane Education & Research Council (PERC) by: ICF International, Inc. 9300 Lee Highway Fairfax, VA 22031 Tel (703) 218-2758 www.icfi.com Principal Author: Mr. Michael Sloan msloan@icfi.com P R E S E N T E D B Y : Propane Market Outlook at a Glance ¡ ICF projects consumer propane sales to grow by about 800 million gallons (9 percent) between 2014 and

  3. 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.

    1994-02-01

    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.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

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

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  8. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    Offshore Lubricants Market Forecast Home There are currently no posts in this category. Syndicate...

  9. Coal Fired Power Generation Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    Coal Fired Power Generation Market Forecast Home There are currently no posts in this category. Syndicate...

  10. Text-Alternative Version LED Lighting Forecast

    Office of Energy Efficiency and Renewable Energy (EERE)

    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....

  11. energy data + forecasting | OpenEI Community

    Open Energy Info (EERE)

    energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in...

  12. Forecast of transportation energy demand through the year 2010

    SciTech Connect (OSTI)

    Mintz, M.M.; Vyas, A.D.

    1991-04-01

    Since 1979, the Center for Transportation Research (CTR) at Argonne National Laboratory (ANL) has produced baseline projections of US transportation activity and energy demand. These projections and the methodologies used to compute them are documented in a series of reports and research papers. As the lastest in this series of projections, this report documents the assumptions, methodologies, and results of the most recent projection -- termed ANL-90N -- and compares those results with other forecasts from the current literature, as well as with the selection of earlier Argonne forecasts. This current forecast may be used as a baseline against which to analyze trends and evaluate existing and proposed energy conservation programs and as an illustration of how the Transportation Energy and Emission Modeling System (TEEMS) works. (TEEMS links disaggregate models to produce an aggregate forecast of transportation activity, energy use, and emissions). This report and the projections it contains were developed for the US Department of Energy's Office of Transportation Technologies (OTT). The projections are not completely comprehensive. Time and modeling effort have been focused on the major energy consumers -- automobiles, trucks, commercial aircraft, rail and waterborne freight carriers, and pipelines. Because buses, rail passengers services, and general aviation consume relatively little energy, they are projected in the aggregate, as other'' modes, and used primarily as scaling factors. These projections are also limited to direct energy consumption. Projections of indirect energy consumption, such as energy consumed in vehicle and equipment manufacturing, infrastructure, fuel refining, etc., were judged outside the scope of this effort. The document is organized into two complementary sections -- one discussing passenger transportation modes, and the other discussing freight transportation modes. 99 refs., 10 figs., 43 tabs.

  13. NREL: Resource Assessment and Forecasting - Research Staff

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

    Research Staff NREL's resource assessment and forecasting research staff provides expertise in renewable energy measurement and instrumentation through NREL's Power Systems Engineering Center. Photo not available Linda Crow - Administrative Associate B.S. Environmental Studies, The Evergreen State College Linda currently works for the Resource Assessment and Forecasting group as their administrative support. She has worked with scientists at the Office of Science at the Air Force Academy and at

  14. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01

    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.

  15. Biodiesel Supply and Consumption in the Short-Term Energy Outlook

    Reports and Publications (EIA)

    2009-01-01

    The historical biodiesel consumption data published in the Energy Information Administration's Monthly Energy Review March 2009 edition were revised to account for imports and exports. Table 10.4 of the Monthly Energy Review was expanded to display biodiesel imports, exports, stocks, stock change, and consumption. Similar revisions were made in the April 2009 edition of the Short-Term Energy Outlook (STEO).

  16. Short-Term Energy Carbon Dioxide Emissions Forecasts August 2009

    Reports and Publications (EIA)

    2009-01-01

    Supplement to the Short-Term Energy Outlook. Short-term projections for U.S. carbon dioxide emissions of the three fossil fuels: coal, natural gas, and petroleum.

  17. 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

    2007-10-04

    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.

  18. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

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

    1994-09-01

    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.

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

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

    Data Figures Tables Custom Table Builder Real Prices Viewer Forecast Changes (PDF) Special ... Power Producer (IPP) consumption. c Renewable energy includes minor components of ...

  20. A Processor to get UV-A and UV-B Radiation Products from the ECMWF Forecast

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

    System A Processor to get UV-A and UV-B Radiation Products from the ECMWF Forecast System Morcrette, Jean-Jacques European Centre for Medium-Range Weather Forecasts Category: Radiation A new processor for evaluating the UV-B and UV-A radiation at the surface, based on modifications to the current shortwave radiation scheme of the ECMWF forecast system is described. Sensitivity studies of the UV surface irradiance and Erythemal Dose Rate to spectral resolution, representation and atmospheric

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

    Gasoline and Diesel Fuel Update (EIA)

    also are evaluated for convergence. Each NEMS component represents the effects and costs of legislation and environmental regulations that affect that sector. NEMS accounts...

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

    SciTech Connect (OSTI)

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

    2005-06-30

    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.

  3. 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.

    1995-02-01

    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.

  4. Annual Energy Outlook 2016 Early Release: Annotated Summary of Two Cases

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

    Early Release: Annotated Summary of Two Cases May 17, 2016 The Annual Energy Outlook 2016 (AEO2016) Early Release features two cases: the Reference case and a case excluding implementation of the Clean Power Plan (CPP) Reference case: A business-as-usual trend estimate, given known technology and technological and demographic trends. The Reference case assumes CPP compliance through mass-based standards that establish caps on CO2 emissions from fossil-fired generators covered by the CPP. The

  5. Solar Forecasting Gets a Boost from Watson, Accuracy Improved...

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

    Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM ...

  6. PBL FY 2003 Second Quarter Review Forecast of Generation Accumulated...

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

    the rate period (i.e., FY 2002-2006), a forecast of that end-of-year Accumulated Net Revenue (ANR) will be completed. If the ANR at the end of the forecast year falls below the...

  7. Combined Heat And Power Installation Market Forecast | OpenEI...

    Open Energy Info (EERE)

    Combined Heat And Power Installation Market Forecast Home There are currently no posts in this category. Syndicate...

  8. DOE Taking Wind Forecasting to New Heights | Department of Energy

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

    Taking Wind Forecasting to New Heights DOE Taking Wind Forecasting to New Heights May 18, 2015 - 3:24pm Addthis A 2013 study conducted for the U.S. Department of Energy (DOE) by the National Oceanic and Atmospheric Administration (NOAA), AWS Truepower, and WindLogics in the Great Plains and Western Texas, demonstrated that wind power forecasts can be improved substantially using data collected from tall towers, remote sensors, and other devices, and incorporated into improved forecasting models

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

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01

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

  10. Wind power forecasting in U.S. electricity markets.

    SciTech Connect (OSTI)

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

    2010-04-01

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

  11. Wind power forecasting in U.S. Electricity markets

    SciTech Connect (OSTI)

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

    2010-04-15

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

  12. Uncertainty Reduction in Power Generation Forecast Using Coupled

    Office of Scientific and Technical Information (OSTI)

    Wavelet-ARIMA (Conference) | SciTech Connect Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA Citation Details In-Document Search Title: Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA 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

  13. Forecasting longitudinal changes in oropharyngeal tumor morphology throughout the course of head and neck radiation therapy

    SciTech Connect (OSTI)

    Yock, Adam D.; Kudchadker, Rajat J.; Rao, Arvind; Dong, Lei; Beadle, Beth M.; Garden, Adam S.; Court, Laurence E.

    2014-08-15

    Purpose: To create models that forecast longitudinal trends in changing tumor morphology and to evaluate and compare their predictive potential throughout the course of radiation therapy. Methods: Two morphology feature vectors were used to describe 35 gross tumor volumes (GTVs) throughout the course of intensity-modulated radiation therapy for oropharyngeal tumors. The feature vectors comprised the coordinates of the GTV centroids and a description of GTV shape using either interlandmark distances or a spherical harmonic decomposition of these distances. The change in the morphology feature vector observed at 33 time points throughout the course of treatment was described using static, linear, and mean models. Models were adjusted at 0, 1, 2, 3, or 5 different time points (adjustment points) to improve prediction accuracy. The potential of these models to forecast GTV morphology was evaluated using leave-one-out cross-validation, and the accuracy of the models was compared using Wilcoxon signed-rank tests. Results: Adding a single adjustment point to the static model without any adjustment points decreased the median error in forecasting the position of GTV surface landmarks by the largest amount (1.2 mm). Additional adjustment points further decreased the forecast error by about 0.4 mm each. Selection of the linear model decreased the forecast error for both the distance-based and spherical harmonic morphology descriptors (0.2 mm), while the mean model decreased the forecast error for the distance-based descriptor only (0.2 mm). The magnitude and statistical significance of these improvements decreased with each additional adjustment point, and the effect from model selection was not as large as that from adding the initial points. Conclusions: The authors present models that anticipate longitudinal changes in tumor morphology using various models and model adjustment schemes. The accuracy of these models depended on their form, and the utility of these models includes the characterization of patient-specific response with implications for treatment management and research study design.

  14. Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

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

    Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting Preprint Jie Zhang 1 , Bri-Mathias Hodge 1 , Siyuan Lu 2 , Hendrik F. Hamann 2 , Brad Lehman 3 , Joseph Simmons 4 , Edwin Campos 5 , and Venkat Banunarayanan 6 1 National Renewable Energy Laboratory 2 IBM TJ Watson Research Center 3 Northeastern University 4 University of Arizona 5 Argonne National Laboratory 6 U.S. Department of Energy Presented at the IEEE Power and Energy Society General Meeting Denver,

  15. The Wind Forecast Improvement Project (WFIP). A Public-Private Partnership Addressing Wind Energy Forecast Needs

    SciTech Connect (OSTI)

    Wilczak, James M.; Finley, Cathy; Freedman, Jeff; Cline, Joel; Bianco, L.; Olson, J.; Djalaova, I.; Sheridan, L.; Ahlstrom, M.; Manobianco, J.; Zack, J.; Carley, J.; Benjamin, S.; Coulter, R. L.; Berg, Larry K.; Mirocha, Jeff D.; Clawson, K.; Natenberg, E.; Marquis, M.

    2015-10-30

    The Wind Forecast Improvement Project (WFIP) is a public-private research program, the goals of which are to improve the accuracy of short-term (0-6 hr) wind power forecasts for the wind energy industry and then to quantify the economic savings that accrue from more efficient integration of wind energy into the electrical grid. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that include the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models to improve model initial conditions; and second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the U.S. (the upper Great Plains, and Texas), and included 12 wind profiling radars, 12 sodars, 184 instrumented tall towers and over 400 nacelle anemometers (provided by private industry), lidar, and several surface flux stations. Results demonstrate that a substantial improvement of up to 14% relative reduction in power root mean square error (RMSE) was achieved from the combination of improved NOAA numerical weather prediction (NWP) models and assimilation of the new observations. Data denial experiments run over select periods of time demonstrate that up to a 6% relative improvement came from the new observations. The use of ensemble forecasts produced even larger forecast improvements. Based on the success of WFIP, DOE is planning follow-on field programs.

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    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.

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

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01

    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.

  18. DOE, EIA, and NASEO Host Winter Fuels Outlook Conference on October 8, 2013

    Broader source: Energy.gov [DOE]

    This supply and demand forecast event will address the effects of projected weather and market factors that may affect the supply, distribution and prices of petroleum, natural gas and electricity this winter.

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

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

    Forecast industrial sector consumption of natural gas increases by 2.4% in 2016 and by 2.0% in 2017, as new fertilizer and chemical projects come online. Figure 17: U.S. Total ...

  20. Evaluation

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

    Savings Portfolio (122013) Energy Smart Grocer Impact Evaluation (102013) Energy Smart Industrial - Energy Management Pilot Impact Evaluation (22013) Clark PUD Home...

  1. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

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

    2014-12-30

    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.

  2. Global disease monitoring and forecasting with Wikipedia

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

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: accessmore » logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.« less

  3. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: access logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.

  4. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J.

    2011-02-23

    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.

  5. Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

    SciTech Connect (OSTI)

    Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat

    2015-08-05

    Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output. forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.

  6. International Energy Outlook 2016-Energy-related CO2 emissions - Energy

    Gasoline and Diesel Fuel Update (EIA)

    Information Administration 9. Energy-related CO2 emissions Overview Because anthropogenic emissions of carbon dioxide (CO2) result primarily from the combustion of fossil fuels, energy consumption is at the center of the climate change debate. In the International Energy Outlook 2016 (IEO2016) Reference case, world energy-related CO2 emissions [331] increase from 32.3 billion metric tons in 2012 to 35.6 billion metric tons in 2020 and to 43.2 billion metric tons in 2040. The Reference case

  7. 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.

    2012-09-01

    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.

  8. Industrial end-use forecasting that incorporates DSM and air quality

    SciTech Connect (OSTI)

    Tutt, T.; Flory, J.

    1995-05-01

    The California Energy Commission (CEC) and major enregy utilities in California have generally depended on simple aggregate intensity or economic models to forecast energy use in the process industry sector (which covers large industries employing basic processes to transform raw materials, such as paper mills, glass plants, and cement plants). Two recent trends suggests that the time has come to develop a more disaggregate process industry forecasting model. First, recent efforts to improve air quality, especially by the South Coast Air Quality Management District (SCAQMD), could significantly affect energy use by the process industry by altering the technologies and processes employed in order to reduce emissions. Second, there is a renewed interest in Demand-Side Management (DSM), not only for utility least-cost planning, but also for improving the economic competitiveness and environmental compliance of the pro{minus}cess industries. A disaggregate forecasting model is critical to help the CEC and utilities evaluate both the air quality and DSM impacts on energy use. A crucial obstacle to the development and use of these detailed process industry forecasting models is the lack of good data about disaggregate energy use in the sector. The CEC is nearing completion of a project to begin to overcome this lack of data. The project is testing methds of developing detailed energy use data, collecting an initial database for a large portion of southern California, and providing recommendations and direction for further data collection efforts.

  9. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

    Complex Terrain | Department of Energy for Wind Forecasting Improvement Project in Complex Terrain Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain February 12, 2014 - 10:47am Addthis On February 11, 2014 the Wind Program announced a Notice of Intent to issue a funding opportunity entitled "Wind Forecasting Improvement Project in Complex Terrain." By researching the physical processes that take place in complex terrain, this funding would

  10. DOE Benefits Forecasts: Report of the External Peer Review Panel |

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

    Department of Energy Benefits Forecasts: Report of the External Peer Review Panel DOE Benefits Forecasts: Report of the External Peer Review Panel A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts. PDF icon Report of the External Peer Review Panel More Documents & Publications Industrial Technologies Funding Profile by Subprogram Survey of Emissions Models for Distributed Combined Heat and Power

  11. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical

    Office of Scientific and Technical Information (OSTI)

    Modelling Approach (Journal Article) | SciTech Connect Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach Citation Details In-Document Search Title: Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the

  12. Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

    Office of Scientific and Technical Information (OSTI)

    (BNL) Field Campaign Report (Technical Report) | SciTech Connect SciTech Connect Search Results Technical Report: Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report Citation Details In-Document Search Title: Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report The Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) [http://www.arm.gov/campaigns/osc2013rwpcf]

  13. Energy Conservation Program: Data Collection and Comparison with Forecasted

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

    Unit Sales for Five Lamp Types, Notice of Data Availability | Department of Energy Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability This document is the notice of data availability for Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types. PDF icon

  14. 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.

    2012-09-01

    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.

  15. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    Title: 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory When considering the amount of shortwave radiation incident on a photovoltaic solar array and, ...

  16. Improving the Accuracy of Solar Forecasting Funding Opportunity...

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

    These projects aim to improve the accuracy of solar forecasting that could increase penetration of solar power by enabling more certainty in power prediction from solar power ...

  17. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic...

    Office of Scientific and Technical Information (OSTI)

    Title: Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates ...

  18. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

    SciTech Connect (OSTI)

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-12-08

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

  19. DOE Announces Webinars on Solar Forecasting Metrics, the DOE...

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

    DOE Announces Webinars on Solar Forecasting Metrics, the DOE ... from adopting the latest energy efficiency and renewable ... to liquids technology, advantages of using natural gas, ...

  20. FY 2004 Second Quarter Review Forecast of Generation Accumulated...

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

    Bonneville Power Administration Power Business Line Generation (PBL) Accumulated Net Revenue Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net...

  1. PBL FY 2003 Third Quarter Review Forecast of Generation Accumulated...

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

    2003 Bonneville Power Administration Power Business Line Generation Accumulated Net Revenue Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net...

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28

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

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

    SciTech Connect (OSTI)

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

    2008-01-07

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

  4. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01

    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.

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

    SciTech Connect (OSTI)

    McNamara, Laura A.

    2010-08-01

    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.

  6. Evaluation

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

    of Array Irradiance Models at Locations across the United States Matthew Lave, Member, IEEE, William Hayes, Andrew Pohl, and Clifford W. Hansen Abstract-We report an evaluation of...

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

    SciTech Connect (OSTI)

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

    2012-07-01

    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.

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

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

    for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations | Department of Energy 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 Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The Wind Forecast Improvement

  9. 3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information

    Open Energy Info (EERE)

    TIER Environmental Forecast Group Inc 3TIER Jump to: navigation, search Name: 3TIER Environmental Forecast Group Inc (3TIER) Place: Seattle, Washington Zip: 98121 Sector: Renewable...

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

    SciTech Connect (OSTI)

    Zheng, Nina; Zhou, Nan; Fridley, David

    2010-09-01

    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.

  11. Forecasting the Magnitude of Sustainable Biofeedstock Supplies: the Challenges and the Rewards

    SciTech Connect (OSTI)

    Graham, Robin Lambert

    2007-01-01

    Forecasting the magnitude of sustainable biofeedstock supplies is challenging because of 1) the myriad of potential feedstock types and their management 2) the need to account for the spatial variation of both the supplies and their environmental and economic consequences, and 3) the inherent challenges of optimizing across economic and environmental considerations. Over the last two decades U.S. biomass forecasts have become increasingly complex and sensitive to environmental and economic considerations. More model development and research is needed however, to capture the landscape and regional tradeoffs of differing biofeedstock supplies especially with regards water quality concerns and wildlife/biodiversity. Forecasts need to be done in the context of the direction of change and what the probable land use and attendant environmental and economic outcomes would be if biofeedstocks were not being produced. To evaluate sustainability, process-oriented models need to be coupled or used to inform sector models and more work needs to be done on developing environmental metrics that are useful for evaluating economic and environmental tradeoffs. These challenges are exciting and worthwhile as they will enable the bioenergy industry to capture environmental and social benefits of biofeedstock production and reduce risks.

  12. Integration of Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Chakrabarti, Bhujanga B.; Subbarao, Krishnappa; Loutan, Clyde; Guttromson, Ross T.

    2010-04-20

    In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (CAISO) real life data have shown the effectiveness and efficiency of the proposed approach.

  13. Secretary Moniz's Remarks at the Wilson Center on the “2015 U.S. Energy Policy Outlook: Opportunities and Challenges”-- As Delivered

    Broader source: Energy.gov [DOE]

    Secretary Moniz's remarks, as delivered, on the “2015 U.S. Energy Policy Outlook: Opportunities and Challenges” at the Wilson Center in Washington, DC on January 7, 2015.

  14. 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.

    2011-12-06

    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.

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

    SciTech Connect (OSTI)

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

    2005-07-01

    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.

  16. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

    After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

  17. Short-Term Energy Outlook - U.S. Energy Information Administration (EIA)

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

    2 : Energy Prices Either scripts and active content are not permitted to run or Adobe Flash Player version ${version_major}.${version_minor}.${version_revision} or greater is not installed. Get Adobe Flash Player a Average for all sulfur contents. b Average self-service cash price. c Includes fuel oils No. 4, No. 5, No. 6, and topped crude. - = no data available Notes: Prices are not adjusted for inflation. The approximate break between historical and forecast values is shown with estimates and

  18. Short-Term Energy Outlook Model Documentation: Electricity Generation and Fuel Consumption Models

    Gasoline and Diesel Fuel Update (EIA)

    Model Documentation: Electricity Generation and Fuel Consumption Models January 2014 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | STEO Model Documentation: Electricity Generation and Fuel Consumption Models i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts

  19. Assumptions and Expectations for Annual Energy Outlook 2014: Oil and Gas Working Group

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

    4: Oil and Gas Working Group AEO2014 Oil and Gas Supply Working Group Meeting Office of Petroleum, Gas, and Biofuels Analysis July 25, 2013 | Washington, DC http://www.eia.gov/forecasts/aeo/workinggroup/ WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE Introduction/Background Office of Petroleum, Gas, and Biofuels Analysis Working Group Presentation for Discussion Purposes Washington, DC, July 25, 2013 DO NOT QUOTE OR CITE as results are

  20. The outlook for the economic and environmental performance of australia's national electricity market in 2030

    SciTech Connect (OSTI)

    Simshauser, Paul; Doan, Thao; Lacey, Ben

    2007-07-15

    CO{sub 2} emissions in Australia's NEM have increased from 117 Mt in 1990 to 169 Mt in 2002. Without policy intervention, emissions are forecast to further rise to 265 Mt by 2030. An analysis of the economic and environmental impact of various generation technology options suggests that the most likely technology glide path will be gas-fired generation in the medium term, with IGCC + CCS or nuclear being the dominant baseload technology over the long run. (author)

  1. 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

  2. Solar Trackers Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    Solar Trackers Market Forecast Home John55364's picture Submitted by John55364(100) Contributor 12 May, 2015 - 03:54 Solar Trackers Market - Global Industry Analysis, Size, Share,...

  3. Energy Forecasting Framework and Emissions Consensus Tool (EFFECT...

    Open Energy Info (EERE)

    Tool (EFFECT) EFFECT is an open, Excel-based modeling tool used to forecast greenhouse gas emissions from a range of development scenarios at the regional and national levels....

  4. Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels

    Reports and Publications (EIA)

    2003-01-01

    This paper presents a short-term monthly forecasting model of West Texas Intermediate crude oil spot price using Organization for Economic Cooperation and Development (OECD) petroleum inventory levels.

  5. ARM - PI Product - CCPP-ARM Parameterization Testbed Model Forecast...

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

    love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : CCPP-ARM Parameterization Testbed Model Forecast Data Dataset contains the NCAR...

  6. Recently released EIA report presents international forecasting data

    SciTech Connect (OSTI)

    1995-05-01

    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.

  7. Value of Improved Short-Term Wind Power Forecasting

    SciTech Connect (OSTI)

    Hodge, B. M.; Florita, A.; Sharp, J.; Margulis, M.; Mcreavy, D.

    2015-02-01

    This report summarizes an assessment of improved short-term wind power forecasting in the California Independent System Operator (CAISO) market and provides a quantification of its potential value.

  8. Summer gasoline price forecast slightly higher, but drivers still...

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

    In its new monthly forecast, the U.S. Energy Information Administration said the retail price for regular grade gasoline will average 2.21 per gallon this summer. While that's 17 ...

  9. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

    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.

  10. Radar Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    1) To provide profiles of the horizontal wind to be used to test and validate short-term cloud advection forecasts for solar-energy applications and 2) to provide vertical ...

  11. PBL FY 2002 Second Quarter Review Forecast of Generation Accumulated...

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

    Slice true-ups, and actual expense levels. Any variation of these can change the net revenue situation. FY 2002 Forecasted Second Quarter Results 170 (418) FY 2002 Unaudited...

  12. Forecasting the oil-gasoline price relationship: should we care...

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

    (2007, EE) obtain similar results on a panel of 15 OECD countries, with annual data ... Results Point forecasts of the N.Y. gasoline price 26 Panel (a): daily data Model MSFE ...

  13. New Forecasting Tools Enhance Wind Energy Integration In Idaho...

    Office of Environmental Management (EM)

    New Forecasting Tools Enhance Wind Energy Integration in Idaho and Oregon Page 1 Under the ... (RIT) that enables grid operators to use wind energy more cost-effectively to serve ...

  14. Modeling and forecasting the distribution of Vibrio vulnificus in

    Office of Scientific and Technical Information (OSTI)

    Chesapeake Bay (Journal Article) | SciTech Connect Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay Citation Details In-Document Search Title: Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters

  15. Forecasting neutrino masses from combining KATRIN and the CMB observations:

    Office of Scientific and Technical Information (OSTI)

    Frequentist and Bayesian analyses (Journal Article) | SciTech Connect SciTech Connect Search Results Journal Article: Forecasting neutrino masses from combining KATRIN and the CMB observations: Frequentist and Bayesian analyses Citation Details In-Document Search Title: Forecasting neutrino masses from combining KATRIN and the CMB observations: Frequentist and Bayesian analyses We present a showcase for deriving bounds on the neutrino masses from laboratory experiments and cosmological

  16. Expert Panel: Forecast Future Demand for Medical Isotopes | Department of

    Energy Savers [EERE]

    Energy Expert Panel: Forecast Future Demand for Medical Isotopes Expert Panel: Forecast Future Demand for Medical Isotopes The Expert Panel has concluded that the Department of Energy and National Institutes of Health must develop the capability to produce a diverse supply of radioisotopes for medical use in quantities sufficient to support research and clinical activities. Such a capability would prevent shortages of isotopes, reduce American dependence on foreign radionuclide sources and

  17. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National

    Office of Scientific and Technical Information (OSTI)

    Laboratory (Technical Report) | SciTech Connect 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory Citation Details In-Document Search Title: 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory When considering the amount of shortwave radiation incident on a photovoltaic solar array and, therefore, the amount and stability of the energy output from the system, clouds represent the greatest source of short-term (i.e., scale of minutes to

  18. Study forecasts disappearance of conifers due to climate change

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

    Study forecasts disappearance of conifers due to climate change Study forecasts disappearance of conifers due to climate change New results, reported in a paper released today in the journal Nature Climate Change, suggest that global models may underestimate predictions of forest death. December 21, 2015 Los Alamos scientist Nate McDowell discusses how climate change is killing trees with PBS NewsHour reporter Miles O'Brien. Los Alamos scientist Nate McDowell discusses how climate change is

  19. National Oceanic and Atmospheric Administration Provides Forecasting Support for CLASIC and CHAPS 2007

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

    NOAA Provides Forecasting Support for CLASIC and CHAPS 2007 Forecasting Challenge While weather experiments in the heart of Tornado Alley typically focus on severe weather, the CLASIC and CHAPS programs will have different emphases. Forecasters from the National Oceanic and Atmospheric Administration in Norman, Okla. will provide weather forecasting support to these two Department of Energy experiments based in the state. Forecasting support for meteorological research field programs usually

  20. Microsoft PowerPoint - ARM_STM_2007_Neggers.ppt [Compatibility Mode]

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

    ARM data in improving the ECMWF boundary layer scheme Roel Neggers Sylvain Cheinet Martin Köhler Anton Beljaars Contents Various ways to evaluate an operational forecast model Issues concerning the model physics A new boundary layer scheme Improvements Outlook How to evaluate an operational forecast model? GCM: resolved & unresolved (sub-grid) scales Physical process evaluation can be done in two modes: 3D Forecasts and climate runs Process is interactive with the larger scales (dynamics)

  1. Iran`s petroleum policy: Current trends and the future outlook

    SciTech Connect (OSTI)

    Pezeshki, S.; Fesharaki, F.

    1994-12-01

    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.

  2. 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

    2008-05-15

    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.

  3. Modeling renewable portfolio standards for the annual energy outlook 1998 - electricity market module

    SciTech Connect (OSTI)

    NONE

    1998-02-01

    The Electricity Market Module (EMM) is the electricity supply component of the National Energy Modeling System (NEMS). The EMM represents the generation, transmission, and pricing of electricity. It consists of four submodules: the Electricity Capacity Planning (ECP) Submodule, the Electricity Fuel Dispatch (EFD) Submodule, the Electricity Finance and Pricing (EFP) Submodule, and the Load and Demand-Side Management (LDSM) Submodule. For the Annual Energy Outlook 1998 (AEO98), the EMM has been modified to represent Renewable Portfolio Standards (RPS), which are included in many of the Federal and state proposals for deregulating the electric power industry. A RPS specifies that electricity suppliers must produce a minimum level of generation using renewable technologies. Producers with insufficient renewable generating capacity can either build new plants or purchase {open_quotes}credits{close_quotes} from other suppliers with excess renewable generation. The representation of a RPS involves revisions to the ECP, EFD, and the EFP. The ECP projects capacity additions required to meet the minimum renewable generation levels in future years. The EFD determines the sales and purchases of renewable credits for the current year. The EFP incorporates the cost of building capacity and trading credits into the price of electricity.

  4. AVLIS: a technical and economic forecast

    SciTech Connect (OSTI)

    Davis, J.I.; Spaeth, M.L.

    1986-01-01

    The AVLIS process has intrinsically large isotopic selectivity and hence high separative capacity per module. The critical components essential to achieving the high production rates represent a small fraction (approx.10%) of the total capital cost of a production facility, and the reference production designs are based on frequent replacement of these components. The specifications for replacement frequencies in a plant are conservative with respect to our expectations; it is reasonable to expect that, as the plant is operated, the specifications will be exceeded and production costs will continue to fall. Major improvements in separator production rates and laser system efficiencies (approx.power) are expected to occur as a natural evolution in component improvements. With respect to the reference design, such improvements have only marginal economic value, but given the exigencies of moving from engineering demonstration to production operations, we continue to pursue these improvements in order to offset any unforeseen cost increases. Thus, our technical and economic forecasts for the AVLIS process remain very positive. The near-term challenge is to obtain stable funding and a commitment to bring the process to full production conditions within the next five years. If the funding and commitment are not maintained, the team will disperse and the know-how will be lost before it can be translated into production operations. The motivation to preserve the option for low-cost AVLIS SWU production is integrally tied to the motivation to maintain a competitive nuclear option. The US industry can certainly survive without AVLIS, but our tradition as technology leader in the industry will certainly be lost.

  5. Assumptions and Expectations for Annual Energy Outlook 2015: Oil and Gas Working Group

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

    5: Oil and Gas Working Group AEO2015 Oil and Gas Supply Working Group Meeting Office of Petroleum, Gas, and Biofuels Analysis August 7, 2014 | Washington, DC http://www.eia.gov/forecasts/aeo/workinggroup/ WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE Changes in release cycles for EIA's AEO and IEO * To focus more resources on rapidly changing energy markets and how they might evolve over the next few years, the U.S. Energy Information

  6. Survey of Variable Generation Forecasting in the West: August 2011 - June 2012

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01

    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. 1980 annual report to Congress: Volume three, Forecasts: Summary

    SciTech Connect (OSTI)

    Not Available

    1981-05-27

    This report presents an overview of forecasts of domestic energy consumption, production, and prices for the year 1990. These results are selected from more detailed projections prepared and published in Volume 3 of the Energy Information Administration 1980 Annual Report to Congress. This report focuses specifically upon the 1980's and concentrates upon similarities and differences in the domestic energy system, as forecast, compared to the national experience in the years immediately following the 1973--1974 oil embargo. Interest in the 1980's stems not only from its immediacy in time, but also from its importance as a time in which certain adjustments to higher energy prices are expected to take place. The forecasts presented do not attempt to account for all of this wide range of potentially important forces that could conceivably alter the energy situation. Instead, the projections are based on a particular set of assumptions that seems reasonable in light of what is currently known. 9 figs., 25 tabs.

  8. The Growth of U.S. Natural Gas: An Uncertain Outlook for U.S. and World Supply

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

    The Growth of U.S. Natural Gas: An Uncertain Outlook for U.S. and World Supply For 2015 EIA Energy Conference June 15, 2015 | Washington, D.C. By John Staub, Team Lead, Exploration and Production Analysis Outline * Changes in U.S. natural gas - Why resource estimates change * Why resource estimates produced with different methods should be different and are valuable * What we need to know about a play to get a fairly accurate estimate - Intersection of geology, technology & above-ground

  9. Annual Energy Outlook 2014 projects reduced need for U.S. oil imports due to tight oil production growth

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

    7, 2014 Annual Energy Outlook 2014 projects reduced need for U.S. oil imports due to tight oil production growth U.S. production of tight crude oil is expected to make up a larger share of total U.S. oil output in the years ahead, and help lower imports share of total U.S. oil consumption. In its annual long-term projections, the U.S. Energy Information Administration (EIA) expects total U.S. crude oil production to reach a record 9.6 million barrels per day (bbl/d) in 2019, under its baseline

  10. Short-Term Energy Outlook Supplement: Status of Libyan Loading Ports and Oil and Natural Gas Fields

    Gasoline and Diesel Fuel Update (EIA)

    Short-Term Energy Outlook Supplement: Status of Libyan Loading Ports and Oil and Natural Gas Fields Tuesday, September 10, 2013, 10:00AM EST Overview During July and August 2013, protests at major oil loading ports in the central-eastern region of Libya forced the complete or partial shut-in of oil fields linked to the ports. As a result of protests at ports and at some oil fields, crude oil production fell to 1.0 million barrels per day (bbl/d) in July and 600,000 bbl/d in August, although the

  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. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    2008-01-15

    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).

  13. Waste Treatment Plant Liquid Effluent Treatability Evaluation

    SciTech Connect (OSTI)

    LUECK, K.J.

    2001-06-07

    Bechtel National, Inc. (BNI) provided a forecast of the radioactive, dangerous liquid effluents expected to be generated by the Waste Treatment Plant (WTP). The forecast represents the liquid effluents generated from the processing of 25 distinct batches of tank waste through the WTP. The WTP liquid effluents will be stored, treated, and disposed of in the Liquid Effluent Retention Facility (LERF) and the Effluent Treatment Facility (ETF). Fluor Hanford, Inc. (FH) evaluated the treatability of the WTP liquid effluents in the LERFIETF. The evaluation was conducted by comparing the forecast to the LERFIETF treatability envelope, which provides information on the items that determine if a liquid effluent is acceptable for receipt and treatment at the LERFIETF. The WTP liquid effluent forecast is outside the current LERFlETF treatability envelope. There are several concerns that must be addressed before the WTP liquid effluents can be accepted at the LERFIETF.

  14. DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting

    Broader source: Energy.gov [DOE]

    DOE has published a new report forecasting the energy savings of LED white-light sources compared with conventional white-light sources. The sixth iteration of the Energy Savings Forecast of Solid...

  15. Impacts of Improved Day-Ahead Wind Forecasts on Power Grid Operations: September 2011

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01

    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. Status of Centralized Wind Power Forecasting in North America: May 2009-May 2010

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01

    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.

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

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

    Beyond "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast December 7, 2012 - 10:00am Addthis The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during

  18. A Public-Private-Academic Partnership to Advance Solar Power Forecasting |

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

    Department of Energy A Public-Private-Academic Partnership to Advance Solar Power Forecasting A Public-Private-Academic Partnership to Advance Solar Power Forecasting UCAR logo2.jpg The University Corporation for Atmospheric Research (UCAR) will develop a solar power forecasting system that advances the state of the science through cutting-edge research. APPROACH UCAR value chain.png The team will develop a solar power forecasting system that advances the state of the science through

  19. Data Collection and Comparison with Forecasted Unit Sales of Five Lamp

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

    Types | Department of Energy Collection and Comparison with Forecasted Unit Sales of Five Lamp Types Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types PDF icon Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types More Documents & Publications Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability CX-100584 Categorical Exclusion Determination ISSUANCE

  20. Central Wind Power Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01

    The report addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America.

  1. Weather forecast-based optimization of integrated energy systems.

    SciTech Connect (OSTI)

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

    2009-03-01

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

  2. Weather Research and Forecasting Model with the Immersed Boundary Method

    Energy Science and Technology Software Center (OSTI)

    2012-05-01

    The Weather Research and Forecasting (WRF) Model with the immersed boundary method is an extension of the open-source WRF Model available for wwww.wrf-model.org. The new code modifies the gridding procedure and boundary conditions in the WRF model to improve WRF's ability to simutate the atmosphere in environments with steep terrain and additionally at high-resolutions.

  3. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

    Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V.

    2011-11-29

    The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help efficiently address this challenge, and significant efforts have been invested in developing more accurate wind power forecasts. In this report, we document our work on the use of wind power forecasting in operational decisions.

  4. 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.

    2010-01-01

    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.

  5. Navy mobility fuels forecasting system report: World petroleum trade forecasts for the year 2000

    SciTech Connect (OSTI)

    Das, S.

    1991-12-01

    The Middle East will continue to play the dominant role of a petroleum supplier in the world oil market in the year 2000, according to business-as-usual forecasts published by the US Department of Energy. However, interesting trade patterns will emerge as a result of the democratization in the Soviet Union and Eastern Europe. US petroleum imports will increase from 46% in 1989 to 49% in 2000. A significantly higher level of US petroleum imports (principally products) will be coming from Japan, the Soviet Union, and Eastern Europe. Several regions, the Far East, Japan, Latin American, and Africa will import more petroleum. Much uncertainty remains about of the level future Soviet crude oil production. USSR net petroleum exports will decrease; however, the United States and Canada will receive some of their imports from the Soviet Union due to changes in the world trade patterns. The Soviet Union can avoid becoming a net petroleum importer as long as it (1) maintains enough crude oil production to meet its own consumption and (2) maintains its existing refining capacities. Eastern Europe will import approximately 50% of its crude oil from the Middle East.

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  7. Outlook for Non-OPEC Oil Supply Growth in 2008-2009 (Released in the STEO February 2008)

    Reports and Publications (EIA)

    2008-01-01

    In 2008-2009, the Energy Information Administration expects that non-OPEC (Organization of the Petroleum Exporting Countries) petroleum supply growth will surpass that in recent years because of the large number of new oil projects scheduled to come online during the forecast period.

  8. Roel Neggers European Centre for Medium-range Weather Forecasts

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

    transition from shallow to deep convection using a dual mass flux boundary layer scheme Roel Neggers European Centre for Medium-range Weather Forecasts Introduction ! " #" $ % % & # % " " " ' % ' ( ) * + " % ( , - . / 0 / " 0 . * 0 . * . . " 0 References A short model description Sensitivity tests Results Tropospheric humidity # " humidity 1 % 2 % ' 3 " % + 1 % 2 % % 3 % Updraft entrainment ' + % " 3 % 4 # " + %' 5 6)( . % ' 1 % .7

  9. NREL: Resource Assessment and Forecasting - Data and Resources

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

    Data and Resources National Solar Radiation Database NREL resource assessment and forecasting research information is available from the following sources. Renewable Resource Data Center (RReDC) Provides information about biomass, geothermal, solar, and wind energy resources. Measurement and Instrumentation Data Center Provides irradiance and meteorological data from stations throughout the United States. Baseline Measurement System (BMS) Provides live solar radiation data from approximately 70

  10. NREL: Energy Analysis - Energy Forecasting and Modeling Staff

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

    Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Elizabeth Torres Clayton Barrows Dave Bielen Aaron Bloom Greg Brinkman Brian W Bush Stuart Cohen Wesley Cole Paul Denholm Nicholas DiOrio Aron Dobos Kelly Eurek Janine Freeman Bethany Frew Pieter Gagnon Elaine Hale

  11. Towards a Science of Tumor Forecast for Clinical Oncology

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

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoplymore » of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.« less

  12. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.

  13. Assessment of the possibility of forecasting future natural gas curtailments

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

    This study provides a preliminary assessment of the potential for determining probabilities of future natural-gas-supply interruptions by combining long-range weather forecasts and natural-gas supply/demand projections. An illustrative example which measures the probability of occurrence of heating-season natural-gas curtailments for industrial users in the southeastern US is analyzed. Based on the information on existing long-range weather forecasting techniques and natural gas supply/demand projections enumerated above, especially the high uncertainties involved in weather forecasting and the unavailability of adequate, reliable natural-gas projections that take account of seasonal weather variations and uncertainties in the nation's energy-economic system, it must be concluded that there is little possibility, at the present time, of combining the two to yield useful, believable probabilities of heating-season gas curtailments in a form useful for corporate and government decision makers and planners. Possible remedial actions are suggested that might render such data more useful for the desired purpose in the future. The task may simply require the adequate incorporation of uncertainty and seasonal weather trends into modeling systems and the courage to report projected data, so that realistic natural gas supply/demand scenarios and the probabilities of their occurrence will be available to decision makers during a time when such information is greatly needed.

  14. Central Wind Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities: Revised Edition

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01

    The report and accompanying table addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America. The first part of the table focuses on electric utilities and regional transmission organizations that have central wind power forecasting in place; the second part focuses on electric utilities and regional transmission organizations that plan to adopt central wind power forecasting in 2010. This is an update of the December 2009 report, NREL/SR-550-46763.

  15. Report of the external expert peer review panel: DOE benefits forecasts

    SciTech Connect (OSTI)

    None, None

    2006-12-20

    A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts.

  16. Value of Improved Wind Power Forecasting in the Western Interconnection (Poster)

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01

    Wind power forecasting is a necessary and important technology for incorporating wind power into the unit commitment and dispatch process. It is expected to become increasingly important with higher renewable energy penetration rates and progress toward the smart grid. There is consensus that wind power forecasting can help utility operations with increasing wind power penetration; however, there is far from a consensus about the economic value of improved forecasts. This work explores the value of improved wind power forecasting in the Western Interconnection of the United States.

  17. The Value of Improved Short-Term Wind Power Forecasting

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

    The Value of Improved Short- Term Wind Power Forecasting B.-M. Hodge and A. Florita National Renewable Energy Laboratory J. Sharp Sharply Focused, LLC M. Margulis and D. Mcreavy Lockheed Martin Technical Report NREL/TP-5D00-63175 February 2015 NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency & Renewable Energy Operated by the Alliance for Sustainable Energy, LLC This report is available at no cost from the National Renewable Energy Laboratory (NREL)

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

    Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.

  19. U.S. Energy Information Administration | Short-Term Energy...

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

    This edition of the Short-Term Energy Outlook is the first to include forecasts ... For renewables, the forecast share of total U.S. Energy Information Administration | ...

  20. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect (OSTI)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  1. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

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

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  3. Weather Research and Forecasting Model with Vertical Nesting Capability

    Energy Science and Technology Software Center (OSTI)

    2014-08-01

    The Weather Research and Forecasting (WRF) model with vertical nesting capability is an extension of the WRF model, which is available in the public domain, from www.wrf-model.org. The new code modifies the nesting procedure, which passes lateral boundary conditions between computational domains in the WRF model. Previously, the same vertical grid was required on all domains, while the new code allows different vertical grids to be used on concurrently run domains. This new functionality improvesmore » WRF's ability to produce high-resolution simulations of the atmosphere by allowing a wider range of scales to be efficiently resolved and more accurate lateral boundary conditions to be provided through the nesting procedure.« less

  4. Evaluation Framework and Tools for Distributed Energy Resources

    SciTech Connect (OSTI)

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

    2003-02-01

    The Energy Information Administration's (EIA) 2002 Annual Energy Outlook (AEO) forecast anticipates the need for 375 MW of new generating capacity (or about one new power plant) per week for the next 20 years, most of which is forecast to be fueled by natural gas. The Distributed Energy and Electric Reliability Program (DEER) of the Department of Energy (DOE), has set a national goal for DER to capture 20 percent of new electric generation capacity additions by 2020 (Office of Energy Efficiency and Renewable Energy 2000). Cumulatively, this amounts to about 40 GW of DER capacity additions from 2000-2020. Figure ES-1 below compares the EIA forecast and DEER's assumed goal for new DER by 2020 while applying the same definition of DER to both. This figure illustrates that the EIA forecast is consistent with the overall DEER DER goal. For the purposes of this study, Berkeley Lab needed a target level of small-scale DER penetration upon which to hinge consideration of benefits and costs. Because the AEO2002 forecasted only 3.1 GW of cumulative additions from small-scale DER in the residential and commercial sectors, another approach was needed to estimate the small-scale DER target. The focus here is on small-scale DER technologies under 500 kW. The technology size limit is somewhat arbitrary, but the key results of interest are marginal additional costs and benefits around an assumed level of penetration that existing programs might achieve. Berkeley Lab assumes that small-scale DER has the same growth potential as large scale DER in AEO2002, about 38 GW. This assumption makes the small-scale goal equivalent to 380,000 DER units of average size 100 kW. This report lays out a framework whereby the consequences of meeting this goal might be estimated and tallied up. The framework is built around a list of major benefits and a set of tools that might be applied to estimate them. This study lists some of the major effects of an emerging paradigm shift away from central station power and towards a more dispersed and heterogeneous power system. Seventeen societal effects of small-scale DER are briefly summarized. Each effect is rated as high, medium or low, on three different scales that will help determine the optimal social investment. The three scales are: the magnitude of the economic benefit; the likelihood that the benefit can be monetized in efficient markets, i.e. internalized; and how tractable it might be to quantify each benefit analytically. Some of the modeling tools that may be used to estimate these effects are described in the Appendix.

  5. An Optimized Autoregressive Forecast Error Generator for Wind and Load Uncertainty Study

    SciTech Connect (OSTI)

    De Mello, Phillip; Lu, Ning; Makarov, Yuri V.

    2011-01-17

    This paper presents a first-order autoregressive algorithm to generate real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast errors. The methodology aims at producing random wind and load forecast time series reflecting the autocorrelation and cross-correlation of historical forecast data sets. Five statistical characteristics are considered: the means, standard deviations, autocorrelations, and cross-correlations. A stochastic optimization routine is developed to minimize the differences between the statistical characteristics of the generated time series and the targeted ones. An optimal set of parameters are obtained and used to produce the RT, HA, and DA forecasts in due order of succession. This method, although implemented as the first-order regressive random forecast error generator, can be extended to higher-order. Results show that the methodology produces random series with desired statistics derived from real data sets provided by the California Independent System Operator (CAISO). The wind and load forecast error generator is currently used in wind integration studies to generate wind and load inputs for stochastic planning processes. Our future studies will focus on reflecting the diurnal and seasonal differences of the wind and load statistics and implementing them in the random forecast generator.

  6. Review of Variable Generation Forecasting in the West: July 2013 - March 2014

    SciTech Connect (OSTI)

    Widiss, R.; Porter, K.

    2014-03-01

    This report interviews 13 operating entities (OEs) in the Western Interconnection about their implementation of wind and solar forecasting. The report updates and expands upon one issued by NREL in 2012. As in the 2012 report, the OEs interviewed vary in size and character; the group includes independent system operators, balancing authorities, utilities, and other entities. Respondents' advice for other utilities includes starting sooner rather than later as it can take time to plan, prepare, and train a forecast; setting realistic expectations; using multiple forecasts; and incorporating several performance metrics.

  7. World oil inventories forecast to grow significantly in 2016 and 2017

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

    World oil inventories forecast to grow significantly in 2016 and 2017 Global oil inventories are expected to continue strong growth over the next two years which should keep oil prices low. In its new monthly forecast, the U.S. Energy Information Administration said world oil stocks are likely to increase by 1.6 million barrels per day this year and by 600,000 barrels per day next year. The higher forecast for inventory builds are the result of both higher global oil production and less oil

  8. WASTE TREATMENT PLANT (WTP) LIQUID EFFLUENT TREATABILITY EVALUATION

    SciTech Connect (OSTI)

    LUECK, K.J.

    2004-10-18

    A forecast of the radioactive, dangerous liquid effluents expected to be produced by the Waste Treatment Plant (WTP) was provided by Bechtel National, Inc. (BNI 2004). The forecast represents the liquid effluents generated from the processing of Tank Farm waste through the end-of-mission for the WTP. The WTP forecast is provided in the Appendices. The WTP liquid effluents will be stored, treated, and disposed of in the Liquid Effluent Retention Facility (LERF) and the Effluent Treatment Facility (ETF). Both facilities are located in the 200 East Area and are operated by Fluor Hanford, Inc. (FH) for the US. Department of Energy (DOE). The treatability of the WTP liquid effluents in the LERF/ETF was evaluated. The evaluation was conducted by comparing the forecast to the LERF/ETF treatability envelope (Aromi 1997), which provides information on the items which determine if a liquid effluent is acceptable for receipt and treatment at the LERF/ETF. The format of the evaluation corresponds directly to the outline of the treatability envelope document. Except where noted, the maximum annual average concentrations over the range of the 27 year forecast was evaluated against the treatability envelope. This is an acceptable approach because the volume capacity in the LERF Basin will equalize the minimum and maximum peaks. Background information on the LERF/ETF design basis is provided in the treatability envelope document.

  9. Microsoft Word - BL SP3 Table 11-03 v19 - final1.doc

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

    Are Product Spreads Useful for Forecasting Oil Prices? An Empirical Evaluation of the Verleger Hypothesis Christiane Baumeister Lutz Kilian Xiaoqing Zhou Bank of Canada University of Michigan University of Michigan CEPR EIA 2014 Workshop on Financial and Physical Oil Market Linkages October 6, 2014 The views expressed in this presentation, or in my remarks, are my own, and do not necessarily represent those of the Bank of Canada. Background  Oil price forecasts affect the economic outlook of

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

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

    Over the past years the Lawrence Berkeley National Laboratory (LBNL) has developed an econometric model that predicts appliance ownership at the household level based on macroeconomic variables such as household income (corrected for purchase power parity), electrification, urbanization and climate variables. Hundreds of data points from around the world were collected in order to understand trends in acquisition of new appliances by households, especially in developing countries. The appliances covered by this model are refrigerators, lighting fixtures, air conditioners, washing machines and televisions. The approach followed allows the modeler to construct a bottom-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residential sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time. This serves two important functions with regard to evaluation of the impact of energy efficiency policies. First, it provides insight into which end uses will be responsible for the largest share of demand growth, and therefore should be policy priorities. Second, it provides a characterization of the rate at which policies affecting new equipment penetrate the appliance stock. Over the past 3 years, this method has been used to support the development of energy demand forecasts at the country, region or global level.

  11. Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations

    Broader source: Energy.gov [DOE]

    This project will address the need for a more accurate approach to forecasting net utility load by taking into consideration the contribution of customer-sited PV energy generation. Tasks within...

  12. Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain

    Broader source: Energy.gov [DOE]

    On April 4, 2014 the U.S. Department of Energy announced a $2.5 million funding opportunity entitled “Wind Forecasting Improvement Project in Complex Terrain.” By researching the physical processes...

  13. Ramping Effect on Forecast Use: Integrated Ramping as a Mitigation Strategy; NREL (National Renewable Energy Laboratory)

    SciTech Connect (OSTI)

    Diakov, Victor; Barrows, Clayton; Brinkman, Gregory; Bloom, Aaron; Denholm, Paul

    2015-06-23

    Power generation ramping between forecasted (net) load set-points shift the generation (MWh) from its scheduled values. The Integrated Ramping is described as a method that mitigates this problem.

  14. Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting Technology

    Broader source: Energy.gov [DOE]

    As part of this project, new solar forecasting technology will be developed that leverages big data processing, deep machine learning, and cloud modeling integrated in a universal platform with an...

  15. U.S. diesel fuel price forecast to be 1 penny lower this summer...

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

    That's down 12 percent from last summer's record exports. Biodiesel production, which averaged 68,000 barrels a day last summer, is forecast to jump to 82,000 barrels a day this ...

  16. A comparison of model short-range forecasts and the ARM Microbase...

    Office of Scientific and Technical Information (OSTI)

    the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. ...

  17. Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Lew, D.; Milligan, M.

    2013-01-01

    Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of the day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.

  18. Examining Information Entropy Approaches as Wind Power Forecasting Performance Metrics: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Orwig, K.; Milligan, M.

    2012-06-01

    In this paper, we examine the parameters associated with the calculation of the Renyi entropy in order to further the understanding of its application to assessing wind power forecasting errors.

  19. U.S. oil production forecast update reflects lower rig count

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

    U.S. oil production forecast update reflects lower rig count Lower oil prices and fewer rigs drilling for crude oil are expected to slow U.S. oil production growth this year and in ...

  20. Analysis and Synthesis of Load Forecasting Data for Renewable Integration Studies: Preprint

    SciTech Connect (OSTI)

    Steckler, N.; Florita, A.; Zhang, J.; Hodge, B. M.

    2013-11-01

    As renewable energy constitutes greater portions of the generation fleet, the importance of modeling uncertainty as part of integration studies also increases. In pursuit of optimal system operations, it is important to capture not only the definitive behavior of power plants, but also the risks associated with systemwide interactions. This research examines the dependence of load forecast errors on external predictor variables such as temperature, day type, and time of day. The analysis was utilized to create statistically relevant instances of sequential load forecasts with only a time series of historic, measured load available. The creation of such load forecasts relies on Bayesian techniques for informing and updating the model, thus providing a basis for networked and adaptive load forecast models in future operational applications.