National Library of Energy BETA

Sample records for forecast tables annual

  1. Annual Coal Distribution Tables

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969 1.979Coal Consumers4.32Elements)Grossc. Real73 Table

  2. 2011 Annual Report Table of Contents

    E-Print Network [OSTI]

    ) ...................12 Smart Grid Cyber Security.....................................................13 ICT Supply ChainComputer Security Division 2011 Annual Report #12;Table of Contents Welcome ................................................................. 1 Division Organization .................................................2 The Computer Security

  3. 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.

  4. Annual Energy Outlook (AEO) 2006 - Supplemental Tables - All Tables

    SciTech Connect (OSTI)

    None

    2009-01-18

    Tables describing regional energy consumption and prices by sector; residential, commercial, and industrial demand sector data; transportation demand sector; electricity and renewable fuel; and petroleum, natural gas, and coal data.

  5. CENTER FOR RADIOLOGICAL RESEARCH ANNUAL REPORT 2004 RARAF -Table of Contents

    E-Print Network [OSTI]

    RADIOLOGICAL RESEARCH ACCELERATOR FACILITY The Radiological Research Accelerator Facility AN NIHCENTER FOR RADIOLOGICAL RESEARCH · ANNUAL REPORT 2004 RARAF - Table of Contents RARAF Staff ...................................................................................................................................................67 Development of Facilities

  6. Exploring the Forecasting Potential of Company Annual Reports Xin Ying Qiu

    E-Print Network [OSTI]

    Street, Nick

    Exploring the Forecasting Potential of Company Annual Reports Xin Ying Qiu Management Sciences reports can be used to assist in assessing the company's short-term financial prospects. However, not much effort has been made to systematically and automatically assess the predictive potential of such reports

  7. 1Annual Report AY 2013 Department of Medicine Table of Contents Department of Medicine

    E-Print Network [OSTI]

    Zapletal, Jindrich

    #12;1Annual Report AY 2013 Department of Medicine Table of Contents Department of Medicine TABLE. Internal Medicine Residency Training Program b. Subspecialty Fellowship Programs c. Student Education and Metabolism c. Gastroenterology d. General Internal Medicine e. Hematology and Medical Oncology f. Infectious

  8. "Table 2. Real Average Annual Coal Transportation Costs, By Primary...

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

    Real Average Annual Coal Transportation Costs, By Primary Transport Mode and Supply Region" "(2013 dollars per ton)" "Coal Supply Region",2008,2009,2010,2011,2012,2013 "Railroad"...

  9. CNS EOC Annual Report 2 Table of Contents

    E-Print Network [OSTI]

    Hardy, Darel

    . On the Cover High school students learn about clean energy as they build a rechargeable battery and a solar cell from scratch using our new Get Energized! science kit. #12; CNS EOC Annual Report ­ 3

  10. 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.

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural GasNatural Gas UsageDiesel pricesDieselAnnual Energy Outlook

  12. 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.

  13. Financial Forecasting using Character N-Gram Analysis and Readability Scores of Annual

    E-Print Network [OSTI]

    Keselj, Vlado

    for each annual report, and then labeled based on the CNG classification. The second method draws on a more-grams, CNG, readability scores, support vector machines 1 Introduction The Securities and Exchange Commission

  14. Consensus Coal Production Forecast for

    E-Print Network [OSTI]

    Mohaghegh, Shahab

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

  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. Consensus Coal Production And Price Forecast For

    E-Print Network [OSTI]

    Mohaghegh, Shahab

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

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

    SciTech Connect (OSTI)

    Poyer, D.A.; Allison, T.

    1998-03-01

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

  18. Annual Report School of Engineering

    E-Print Network [OSTI]

    Alpay, S. Pamir

    Annual Report 1999-2000 School of Engineering University of Connecticut #12;#12;University of Connecticut School of Engineering Annual Report 1999-2000 Table of Contents School of Engineering Annual Departments Chemical Engineering Annual Report Summary

  19. INTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev

    E-Print Network [OSTI]

    , discourse and semantic. They are based on a conceptual model underlying weather forecasts as well situations represented in the form of texts in NL, weather maps, data tables or combined information objectsINTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev I n s t i t u t e of Mathematics Acad

  20. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    income 7 Figure 1.14: United States inflation Rate 8 Figure 1.15: Select United States interest Rates 8 2014 TABLE OF CONTENTS EXECUTiVE SUMMARY 1 CHAPTER 1: THE UNiTED STATES ECONOMY 3 Recent Trends Forecast Summary 2 CHAPTER 1: THE UNiTED STATES ECONOMY Figure 1.1: United States Real GDP Growth 3 Figure

  1. Annual Spring Experiments aim to accelerate the transfer of promising new concepts and tools from research to operations through intensive real-time forecasts and evaluations.

    E-Print Network [OSTI]

    Xue, Ming

    research to operations through intensive real-time forecasts and evaluations. B ackground. Each spring research to operations, while inspiring new initiatives for operationally relevant research, through a combined forecast and research area situated between the SPC and OUN operations rooms (Fig. 1

  2. Annual Coal Distribution Tables

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969 1.979Coal Consumers4.32Elements)Grossc. Real73

  3. Annual Coal Distribution Tables

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969 1.979Coal Consumers4.32Elements)Grossc. Real73and Foreign

  4. 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....

  5. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

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

    of table. 134 Energy Information AdministrationPetroleum Marketing Annual 1999 Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per...

  6. Table Search (or Ranking Tables)

    E-Print Network [OSTI]

    Halevy, Alon

    ;Table Search #3 #12;Outline · Goals of table search · Table search #1: Deep Web · Table search #3 search Table search #1: Deep Web · Table search #3: (setup): Fusion Tables · Table search #2: WebTables ­Version 1: modify document search ­Version 2: recover table semantics #12;Searching the Deep Web store

  7. 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.

  8. 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.

  9. SFU LIBRARY ANNUAL REPORT

    E-Print Network [OSTI]

    SFU LIBRARY ANNUAL REPORT 2006/07 #12;22 TABLE OF CONTENTS Message from the University Librarian................................................... ....................................... 7 WAC Bennett Library.................................................................. ....................................... 8 Samuel and Frances Belzberg Library

  10. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

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

  11. 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.

  12. The Western Water Assessment Annual RISA Report

    E-Print Network [OSTI]

    Neff, Jason

    ;Western Water Assessment 2007 Annual Report 2 Table of Contents I. Areas of FocusThe Western Water Assessment Annual RISA Report Reporting Period: January 2007-December 2007 #12-30 #12;Western Water Assessment 2007 Annual Report 3

  13. Fiscal Year 2004 Annual Report

    E-Print Network [OSTI]

    Salvaggio, Carl

    NTID Fiscal Year 2004 Annual Report (Click here to jump to the Table of Contents) #12;#12;-1- FY ................... 17 Assessment Information on Entering Class

  14. Annual energy outlook 1997 with projections to 2015

    SciTech Connect (OSTI)

    NONE

    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.

  15. 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.

  16. Using Building Simulation and Optimization to Calculate Lookup Tables for Control

    E-Print Network [OSTI]

    Coffey, Brian

    2012-01-01

    solar (W/m2) Table 13: Base case annual energy consumptionlighting energy consumption. Figure 11: Solar shading and

  17. Engineering Faculty's Annual Report 2010

    E-Print Network [OSTI]

    Toronto, University of

    Engineering Faculty's Annual Report 2010: Performance Indicators #12;ii | Table of Contents | Annual Report 2010 | Faculty of Applied Science & Engineering Table of Contents Introduction 2 ­ Message from the Dean ­ 2009­2010 Faculty Leadership ­ Comparison of U of T Engineering with Ontario and Canada

  18. Table 21. Domestic Crude Oil First Purchase Prices

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

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

  19. Table 21. Domestic Crude Oil First Purchase Prices

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

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

  20. Crude Oil Prices Table 21. Domestic Crude Oil First Purchase...

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

    Information Administration Petroleum Marketing Annual 1995 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

  1. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

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

    Information AdministrationPetroleum Marketing Annual 1998 Table 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and Selected States (Cents per...

  2. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    Petroleum Marketing Annual 1998 Table 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State (Thousand Gallons per Day) -...

  3. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

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

    Information AdministrationPetroleum Marketing Annual 1998 Table 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  4. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

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

    250 Energy Information AdministrationPetroleum Marketing Annual 1998 Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State (Thousand Gallons...

  5. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

    Gasoline and Diesel Fuel Update (EIA)

    Information AdministrationPetroleum Marketing Annual 1999 Table 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and Selected States (Cents per...

  6. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

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

    Marketing Annual 1998 Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State (Thousand Gallons per Day) -...

  7. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

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

    Marketing Annual 1999 Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State (Thousand Gallons per Day) -...

  8. Petroleum Products Table 31. Motor Gasoline Prices by Grade...

    Gasoline and Diesel Fuel Update (EIA)

    Information AdministrationPetroleum Marketing Annual 2000 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) -...

  9. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

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

    AdministrationPetroleum Marketing Annual 1998 Table 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) -...

  10. Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils...

    Gasoline and Diesel Fuel Update (EIA)

    Marketing Annual 1999 359 Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils and Kerosene by PAD District and State (Thousand Gallons per Day) - Continued...

  11. Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils...

    Gasoline and Diesel Fuel Update (EIA)

    Marketing Annual 1998 359 Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils and Kerosene by PAD District and State (Thousand Gallons per Day) - Continued...

  12. Data Management Group Annual Report

    E-Print Network [OSTI]

    Toronto, University of

    Data Management Group Annual Report 1997 #12;Data Management Group Annual Report 1997 A co-operative project that is jointly funded by members of the Toronto Area Transportation Planning Data Collection: (416) 978-3941 #12;Data Management Group 1997 Annual Report Table of Contents 1 INTRODUCTION

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

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

  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 Platform Review Principle Investigator: Dr. Henriette I. Jager Organization: Oak Ridge National...

  19. U.S. Energy Information Administration / Annual Energy Review 2011 341 Table E1. Estimated Primary Energy Consumption in the United States, Selected Years, 1635-1945

    E-Print Network [OSTI]

    Hansen, James E.

    Renewable Energy Electricity Net Imports TotalCoal Natural Gas Petroleum Total Conventional Hydroelectric in the American Economy, 1850-1975, Table VII. Conventional Hydroelectric Power: Energy in the American Economy as the difference between hydroelectric consumption and hydroelectric production times 3,412 Btu per kilowatthour

  20. Annual energy outlook 2005 with projections to 2025

    SciTech Connect (OSTI)

    NONE

    2005-02-01

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

  1. Annual Energy Review 1999

    SciTech Connect (OSTI)

    Seiferlein, Katherine E.

    2000-07-01

    A generation ago the Ford Foundation convened a group of experts to explore and assess the Nation’s energy future, and published their conclusions in A Time To Choose: America’s Energy Future (Cambridge, MA: Ballinger, 1974). The Energy Policy Project developed scenarios of U.S. potential energy use in 1985 and 2000. Now, with 1985 well behind us and 2000 nearly on the record books, it may be of interest to take a look back to see what actually happened and consider what it means for our future. The study group sketched three primary scenarios with differing assumptions about the growth of energy use. The Historical Growth scenario assumed that U.S. energy consumption would continue to expand by 3.4 percent per year, the average rate from 1950 to 1970. This scenario assumed no intentional efforts to change the pattern of consumption, only efforts to encourage development of our energy supply. The Technical Fix scenario anticipated a “conscious national effort to use energy more efficiently through engineering know-how." The Zero Energy Growth scenario, while not clamping down on the economy or calling for austerity, incorporated the Technical Fix efficiencies plus additional efficiencies. This third path anticipated that economic growth would depend less on energy-intensive industries and more on those that require less energy, i.e., the service sector. In 2000, total energy consumption was projected to be 187 quadrillion British thermal units (Btu) in the Historical Growth case, 124 quadrillion Btu in the Technical Fix case, and 100 quadrillion Btu in the Zero Energy Growth case. The Annual Energy Review 1999 reports a preliminary total consumption for 1999 of 97 quadrillion Btu (see Table 1.1), and the Energy Information Administration’s Short-Term Energy Outlook (April 2000) forecasts total energy consumption of 98 quadrillion Btu in 2000. What energy consumption path did the United States actually travel to get from 1974, when the scenarios were drawn, to the end of the century? What happened to the relationship between growth and energy consumption? How did the fuel mix change over this period? What are the effects of energy usage on our environment? What level of consumption will the United States—and the world—record in the Annual Energy Review 2025? We present this edition of the Annual Energy Review to help investigate these important questions and to stimulate and inform our thinking about what the future holds.

  2. Fuel Price Forecasts INTRODUCTION

    E-Print Network [OSTI]

    Fuel Price Forecasts INTRODUCTION Fuel prices affect electricity planning in two primary ways and water heating, and other end-uses as well. Fuel prices also influence electricity supply and price turbines. This second effect is the primary use of the fuel price forecast for the Council's Fifth Power

  3. Weather Forecasting Spring 2014

    E-Print Network [OSTI]

    Hennon, Christopher C.

    ATMS 350 Weather Forecasting Spring 2014 Professor : Dr. Chris Hennon Office : RRO 236C Phone : 232 of atmospheric physics and the ability to include this understanding into modern numerical weather prediction agencies, forecast tools, numerical weather prediction models, model output statistics, ensemble

  4. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    ....................................................................................................1-16 Energy Consumption Data...............................................1-15 Data Sources for Energy Demand Forecasting ModelsCALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report

  5. Assessing forecast uncertainties in a VECX model for Switzerland: an exercise in forecast combination across models and observation windows

    E-Print Network [OSTI]

    Assenmacher-Wesche, Katrin; Pesaran, M. Hashem

    horizons of up to eight quarters ahead since this is the rele- vant time horizon for central banks when setting interest rates. Table 6 shows the RMSFE, the bias and the hit rate of forecasts based on the VECX*(2,2) model for the longest estimation window...

  6. C:\\ANNUAL\\Vol2chps.v8\\ANNUAL2.VP

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

    Administration Historical Natural Gas Annual 1930 Through 2000 13. Natural Gas Production, Transmission, and Consumption by State, 1967-2000 (Million Cubic Feet) Table...

  7. C:\\ANNUAL\\Vol2chps.v8\\ANNUAL2.VP

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

    3 Energy Information Administration Historical Natural Gas Annual 1930 Through 2000 25. Natural Gas Delivered to Consumers by Census Division, 1967-2000 Table Census Division...

  8. Solar Forecast Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE)

    For the Solar Forecast Improvement Project (SFIP), the Earth System Research Laboratory (ESRL) is partnering with the National Center for Atmospheric Research (NCAR) and IBM to develop more...

  9. Natural gas annual 1995

    SciTech Connect (OSTI)

    1996-11-01

    The Natural Gas Annual provides information on the supply and disposition of natural gas to a wide audience including industry, consumers, Federal and State agencies, and educational institutions. The 1995 data are presented in a sequence that follows natural gas (including supplemental supplies) from its production to its end use. This is followed by tables summarizing natural gas supply and disposition from 1991 to 1995 for each Census Division and each State. Annual historical data are shown at the national level.

  10. Natural gas annual 1994

    SciTech Connect (OSTI)

    NONE

    1995-11-17

    The Natural Gas Annual provides information on the supply and disposition of natural gas to a wide audience including industry, consumers, Federal and State agencies, and educational institutions. The 1994 data are presented in a sequence that follows natural gas (including supplemental supplies) from its production to its end use. This is followed by tables summarizing natural gas supply and disposition from 1990 to 1994 for each Census Division and each State. Annual historical data are shown at the national level.

  11. Weather-based forecasts of California crop yields

    SciTech Connect (OSTI)

    Lobell, D B; Cahill, K N; Field, C B

    2005-09-26

    Crop yield forecasts provide useful information to a range of users. Yields for several crops in California are currently forecast based on field surveys and farmer interviews, while for many crops official forecasts do not exist. As broad-scale crop yields are largely dependent on weather, measurements from existing meteorological stations have the potential to provide a reliable, timely, and cost-effective means to anticipate crop yields. We developed weather-based models of state-wide yields for 12 major California crops (wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios), and tested their accuracy using cross-validation over the 1980-2003 period. Many crops were forecast with high accuracy, as judged by the percent of yield variation explained by the forecast, the number of yields with correctly predicted direction of yield change, or the number of yields with correctly predicted extreme yields. The most successfully modeled crop was almonds, with 81% of yield variance captured by the forecast. Predictions for most crops relied on weather measurements well before harvest time, allowing for lead times that were longer than existing procedures in many cases.

  12. 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.

  13. Office of Classroom Management 2011 Annual Report

    E-Print Network [OSTI]

    Ciocan-Fontanine, Ionut

    Office of Classroom Management 2011 Annual Report Office of Classroom Management · Academic Support Director, Office of Classroom Management Charts/graphs Table of Contents 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Office of Classroom Management 2011 Annual Report #12;1 2011 OCM Annual Report OCM's functions Scheduling

  14. UNIVERSITY OF CONNECTICUT SCHOOL OF ENGINEERING ANNUAL REPORT

    E-Print Network [OSTI]

    Alpay, S. Pamir

    #12;1 UNIVERSITY OF CONNECTICUT SCHOOL OF ENGINEERING ANNUAL REPORT 2009-2010 TABLE OF CONTENTS...................................................... 244 CONNECTICUT TRANSPORTATION INSTITUTE......................................................250

  15. UNIVERSITY OF CONNECTICUT SCHOOL OF ENGINEERING ANNUAL REPORT

    E-Print Network [OSTI]

    Alpay, S. Pamir

    #12;1 UNIVERSITY OF CONNECTICUT SCHOOL OF ENGINEERING ANNUAL REPORT 2010-2011 TABLE OF CONTENTS CENTER FOR CLEAN ENERGY ENGINEERING...................................................... 252 CONNECTICUT

  16. Table 6. U.S. Refiner Motor Gasoline Prices by Grade and Sales...

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

    Energy Information AdministrationPetroleum Marketing Annual 1998 Table 6. U.S. Refiner Motor Gasoline Prices by Grade and Sales Type (Cents per Gallon Excluding Taxes) - Continued...

  17. Table 10. U.S. Refiner Oxygenated Motor Gasoline Prices by...

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

    AdministrationPetroleum Marketing Annual 1999 Table 10. U.S. Refiner Oxygenated Motor Gasoline Prices by Grade and Sales Type (Cents per Gallon Excluding Taxes) Year Month...

  18. Table 6. U.S. Refiner Motor Gasoline Prices by Grade and Sales...

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

    Energy Information AdministrationPetroleum Marketing Annual 1999 Table 6. U.S. Refiner Motor Gasoline Prices by Grade and Sales Type (Cents per Gallon Excluding Taxes) - Continued...

  19. Table 7. U.S. Refiner Motor Gasoline Volumes by Grade and Sales...

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

    Energy Information AdministrationPetroleum Marketing Annual 1998 Table 7. U.S. Refiner Motor Gasoline Volumes by Grade and Sales Type (Million Gallons per Day) - Continued Year...

  20. Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District...

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

    Information AdministrationPetroleum Marketing Annual 1999 191 Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District, and Selected States (Cents per Gallon Excluding...

  1. Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District...

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

    Information AdministrationPetroleum Marketing Annual 1998 191 Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District, and Selected States (Cents per Gallon Excluding...

  2. Table 41. No. 2 Diesel Fuel Prices by Sulfur Content, Sales...

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

    Information AdministrationPetroleum Marketing Annual 1998 Table 41. No. 2 Diesel Fuel Prices by Sulfur Content, Sales Type, and PAD District (Cents per Gallon Excluding...

  3. Table 41. No. 2 Diesel Fuel Prices by Sulfur Content, Sales...

    Gasoline and Diesel Fuel Update (EIA)

    Information AdministrationPetroleum Marketing Annual 1999 Table 41. No. 2 Diesel Fuel Prices by Sulfur Content, Sales Type, and PAD District (Cents per Gallon Excluding...

  4. Table 30. Landed Costs of Imported Crude Oil for Selected Crude...

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

    Energy Information Administration Petroleum Marketing Annual 1995 53 Table 30. Landed Costs of Imported Crude Oil for Selected Crude Streams (Dollars per Barrel) - Continued Year...

  5. Table 30. Landed Costs of Imported Crude Oil for Selected Crude...

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

    Energy Information AdministrationPetroleum Marketing Annual 1999 53 Table 30. Landed Costs of Imported Crude Oil for Selected Crude Streams (Dollars per Barrel) - Continued Year...

  6. Table 30. Landed Costs of Imported Crude Oil for Selected Crude...

    Gasoline and Diesel Fuel Update (EIA)

    Energy Information AdministrationPetroleum Marketing Annual 1998 53 Table 30. Landed Costs of Imported Crude Oil for Selected Crude Streams (Dollars per Barrel) - Continued Year...

  7. Table A3. Refiner/Reseller Prices of Distillate and Residual...

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

    AdministrationPetroleum Marketing Annual 1999 441 Table A3. RefinerReseller Prices of Distillate and Residual Fuel Oils, by PAD District, 1983-Present (Cents per Gallon...

  8. Table A1. Refiner/Reseller Motor Gasoline Prices by Grade, PAD...

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

    Petroleum Marketing Annual 1999 401 Table A1. RefinerReseller Motor Gasoline Prices by Grade, PAD District and State, 1984-Present (Cents per Gallon Excluding Taxes) -...

  9. Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District...

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

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

  10. Table A2. Refiner/Reseller Prices of Aviation Fuels, Propane...

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

    AdministrationPetroleum Marketing Annual 1999 421 Table A2. RefinerReseller Prices of Aviation Fuels, Propane, and Kerosene, by PAD District, 1983-Present (Cents per...

  11. Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District...

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

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

  12. Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil...

    Gasoline and Diesel Fuel Update (EIA)

    Petroleum Marketing Annual 1998 295 Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil Volumes by PAD District and State (Thousand Gallons per Day) - Continued...

  13. Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil...

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

    Petroleum Marketing Annual 1999 295 Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil Volumes by PAD District and State (Thousand Gallons per Day) - Continued...

  14. Table 42. Residual Fuel Oil Prices by PAD District and State

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

    Information AdministrationPetroleum Marketing Annual 1999 203 Table 42. Residual Fuel Oil Prices by PAD District and State (Cents per Gallon Excluding Taxes) - Continued...

  15. Table 42. Residual Fuel Oil Prices by PAD District and State

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

    Information AdministrationPetroleum Marketing Annual 1998 203 Table 42. Residual Fuel Oil Prices by PAD District and State (Cents per Gallon Excluding Taxes) - Continued...

  16. Improving automotive battery sales forecast

    E-Print Network [OSTI]

    Bulusu, Vinod

    2015-01-01

    Improvement in sales forecasting allows firms not only to respond quickly to customers' needs but also to reduce inventory costs, ultimately increasing their profits. Sales forecasts have been studied extensively to improve ...

  17. "Annual Electric Power Industry Report (EIA-861 data file)

    Gasoline and Diesel Fuel Update (EIA)

    Electric Sales, Revenue, and Average Price CorrectionUpdate Annual data revisions: June 17 2015 Annual survey form EIA-861 data for 2013 re-released: June 17, 2015 Tables T5.a,...

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

    E-Print Network [OSTI]

    Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts ............................................................................................................................ 5 U.S. Natural Gas Commodity Prices

  19. General Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformation Current HABFESOpportunities NuclearlongGeneral Tables The General Tables for

  20. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required in electricity demand is, of course, crucial to determining the need for new electricity resources and helping of any forecast of electricity demand and developing ways to reduce the risk of planning errors

  1. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Rutledge, Steven

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary microbursts than in many previously documented microbursts. Alignment of Doppler radar data to reports of wind-related damage to electrical power infrastructure in Phoenix allowed a comparison of microburst wind damage

  2. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

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

  3. Hawaii demand-side management resource assessment. Final report, Reference Volume 5: The DOETRAN user`s manual; The DOE-2/DBEDT DSM forecasting model interface

    SciTech Connect (OSTI)

    1995-04-01

    The DOETRAN model is a DSM database manager, developed to act as an intermediary between the whole building energy simulation model, DOE-2, and the DBEDT DSM Forecasting Model. DOETRAN accepts output data from DOE-2 and TRANslates that into the format required by the forecasting model. DOETRAN operates in the Windows environment and was developed using the relational database management software, Paradox 5.0 for Windows. It is not necessary to have any knowledge of Paradox to use DOETRAN. DOETRAN utilizes the powerful database manager capabilities of Paradox through a series of customized user-friendly windows displaying buttons and menus with simple and clear functions. The DOETRAN model performs three basic functions, with an optional fourth. The first function is to configure the user`s computer for DOETRAN. The second function is to import DOE-2 files with energy and loadshape data for each building type. The third main function is to then process the data into the forecasting model format. As DOETRAN processes the DOE-2 data, graphs of the total electric monthly impacts for each DSM measure appear, providing the user with a visual means of inspecting DOE-2 data, as well as following program execution. DOETRAN provides three tables for each building type for the forecasting model, one for electric measures, gas measures, and basecases. The optional fourth function provided by DOETRAN is to view graphs of total electric annual impacts by measure. This last option allows a comparative view of how one measure rates against another. A section in this manual is devoted to each of the four functions mentioned above, as well as computer requirements and exiting DOETRAN.

  4. 2003 CBECS RSE Tables

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

    of the Excel tables (access from main detailed tables page) or in PDF format here: Building Characteristics for All Buildings (Tables A1-A8) RSE Tables: PDF, 16 pages, 312KB...

  5. 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.

  6. THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY RARAF Table of Contents

    E-Print Network [OSTI]

    THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY 118 RARAF Table of Contents RARAF Professional ANNUAL REPORT 2008 119 The Radiological Research Accelerator Facility AN NIH-SUPPORTED RESOURCE CENTER................................................................................................................................................119 Development of Facilities

  7. THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY RARAF -Table of Contents

    E-Print Network [OSTI]

    THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY 113 RARAF - Table of Contents RARAF Professional · ANNUAL REPORT 2007 114 The Radiological Research Accelerator Facility AN NIH-SUPPORTED RESOURCE CENTER................................................................................................................................................114 Development of Facilities

  8. THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY RARAF -Table of Contents

    E-Print Network [OSTI]

    THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY 117 RARAF - Table of Contents RARAF Professional RESEARCH · ANNUAL REPORT 2010 118 The Radiological Research Accelerator Facility AN NIH-SUPPORTED RESOURCE................................................................................................................................................117 Development of Facilities

  9. THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY RARAF Table of Contents

    E-Print Network [OSTI]

    THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY RARAF Table of Contents RARAF Professional Staff RESEARCH ANNUAL REPORT 2009 The Radiological Research Accelerator Facility AN NIH-SUPPORTED RESOURCE................................................................................................................................................101 Development of Facilities

  10. THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY RARAF -Table of Contents

    E-Print Network [OSTI]

    THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY 75 RARAF - Table of Contents RARAF Professional FOR RADIOLOGICAL RESEARCH · ANNUAL REPORT 2005 76 The Radiological Research Accelerator Facility AN NIH .................................................................................................................................................72 Development of Facilities

  11. THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY RARAF -Table of Contents

    E-Print Network [OSTI]

    THE RADIOLOGICAL RESEARCH ACCELERATOR FACILITY 65 RARAF - Table of Contents RARAF Professional FOR RADIOLOGICAL RESEARCH · ANNUAL REPORT 2006 66 The Radiological Research Accelerator Facility AN NIH..................................................................................................................................................66 Development of facilities

  12. 2001 annual report 2001 annual report

    E-Print Network [OSTI]

    New Mexico, University of

    2001 annual report 2001 annual report 2001 annual report 2001 annual report 2001 annual report 2001 annual report 2001 annual report 2001 annual reportelectrical & computer engineering 2001 annual report the university of new mexico department of 2001 annual report 2001 annual report 2001 annual report 2001 annual

  13. 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.

  14. Wind Power Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentricNCubicthe FOIA?ResourceMeasurement BuoyForecasting Sign

  15. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    s economy. Demand Forecasts The three energy futures wereto meet the forecast demand in each energy futurE2. e e1£~energy saved through improved appliance efficiencies. Also icit in our demand forecasts

  16. Natural gas annual 1997

    SciTech Connect (OSTI)

    1998-10-01

    The Natural Gas Annual provides information on the supply and disposition of natural gas to a wide audience including industry, consumers, Federal and State agencies, and educational institutions. The 1997 data are presented in a sequence that follows natural gas (including supplemental supplies) from its production to its end use. This is followed by tables summarizing natural gas supply and disposition from 1993 to 1997 for each Census Division and each State. Annual historical data are shown at the national level. 27 figs., 109 tabs.

  17. Price forecasting for notebook computers 

    E-Print Network [OSTI]

    Rutherford, Derek Paul

    1997-01-01

    of individual features are estimated. A time series analysis is used to forecast and can be used, for example, to forecast (1) notebook computer price at introduction, and (2) rate of price erosion for a notebook's life cycle. Results indicate that this approach...

  18. Multivariate Forecast Evaluation And Rationality Testing

    E-Print Network [OSTI]

    Komunjer, Ivana; OWYANG, MICHAEL

    2007-01-01

    Economy, 95(5), 1062—1088. MULTIVARIATE FORECASTS Chaudhuri,Notion of Quantiles for Multivariate Data,” Journal of thePress, United Kingdom. MULTIVARIATE FORECASTS Kirchgässner,

  19. C:\\ANNUAL\\Vol2chps.v8\\ANNUAL2.VP

    Gasoline and Diesel Fuel Update (EIA)

    Natural Gas Annual 1930 Through 2000 36. Prices of Natural Gas Deliveries to Electric Utilities by State, 1993-1998 (Dollars per Thousand Cubic Feet) Table State Firm Interruptible...

  20. PAGE 12013 -2014 ANNUAL REPORT 2013-2014 ANNUAL REPORT

    E-Print Network [OSTI]

    Doty, Sharon Lafferty

    #12;PAGE 4 UW ENTERPRISE RISK MANAGEMENT Executive Summary 1 Top 10 Strategic Issues for Boards 2013 Management (UW-ERM) #12;PAGE 2 UW ENTERPRISE RISK MANAGEMENT #12;PAGE 32013 - 2014 ANNUAL REPORT Table............................................................................................................. 4 II. About Enterprise Risk Management

  1. Security Division 2007 Annual Report

    E-Print Network [OSTI]

    research programs. These programs, which include Cyber Security, Pervasive Information TechnologiesComputer Security Division 2007 Annual Report #12;TAble of ConTenTS Welcome Division Organization The Computer Security Division Responds to the Federal Information Security Management Act of 2002 Security

  2. Analysis of Emissions Calculators for the National Center of Excellence on Displaced Emission Reductions (CEDER): Annual Report 

    E-Print Network [OSTI]

    Yazdani, Bahman; Culp, Charles; Haberl, Jeff; Baltazar, Juan-Carlos; Do, Sung Lok

    2010-01-01

    Calculators According to Annual CO2 Emissions from N.G. Use ................................................................................................................................................ 15 Figure 5. Annual NOx Emissions from the N.G.... Use of a Residential Building ........................ 16 Figure 6. Annual SOx Emissions from the N.G. Use of a Residential Building ......................... 16 LIST OF TABLES Page Table 1. Review of Emissions Calculators in the 2008...

  3. 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.

  4. Downscaling Extended Weather Forecasts for Hydrologic Prediction

    SciTech Connect (OSTI)

    Leung, Lai-Yung R.; Qian, Yun

    2005-03-01

    Weather and climate forecasts are critical inputs to hydrologic forecasting systems. The National Center for Environmental Prediction (NCEP) issues 8-15 days outlook daily for the U.S. based on the Medium Range Forecast (MRF) model, which is a global model applied at about 2? spatial resolution. Because of the relatively coarse spatial resolution, weather forecasts produced by the MRF model cannot be applied directly to hydrologic forecasting models that require high spatial resolution to represent land surface hydrology. A mesoscale atmospheric model was used to dynamically downscale the 1-8 day extended global weather forecasts to test the feasibility of hydrologic forecasting through this model nesting approach. Atmospheric conditions of each 8-day forecast during the period 1990-2000 were used to provide initial and boundary conditions for the mesoscale model to produce an 8-day atmospheric forecast for the western U.S. at 30 km spatial resolution. To examine the impact of initialization of the land surface state on forecast skill, two sets of simulations were performed with the land surface state initialized based on the global forecasts versus land surface conditions from a continuous mesoscale simulation driven by the NCEP reanalysis. Comparison of the skill of the global and downscaled precipitation forecasts in the western U.S. showed higher skill for the downscaled forecasts at all precipitation thresholds and increasingly larger differences at the larger thresholds. Analyses of the surface temperature forecasts show that the mesoscale forecasts generally reduced the root-mean-square error by about 1.5 C compared to the global forecasts, because of the much better resolved topography at 30 km spatial resolution. In addition, initialization of the land surface states has large impacts on the temperature forecasts, but not the precipitation forecasts. The improvements in forecast skill using downscaling could be potentially significant for improving hydrologic forecasts for managing river basins.

  5. 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.

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

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01

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

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

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

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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    weather prediction solar irradiance forecasts in the US.2013: Review of solar irradiance forecasting methods and asatellite-derived irradiances: Description and validation.

  9. Hot cell examination table

    DOE Patents [OSTI]

    Gaal, Peter S. (Monroeville, PA); Ebejer, Lino P. (Weston, MA); Kareis, James H. (Slickville, PA); Schlegel, Gary L. (McKeesport, PA)

    1991-01-01

    A table for use in a hot cell or similar controlled environment for use in examining specimens. The table has a movable table top that can be moved relative to a table frame. A shaft is fixedly mounted to the frame for axial rotation. A shaft traveler having a plurality of tilted rollers biased against the shaft is connected to the table top such that rotation of the shaft causes the shaft traveler to roll along the shaft. An electromagnetic drive is connected to the shaft and the frame for controllably rotating the shaft.

  10. Massachusetts state airport system plan forecasts.

    E-Print Network [OSTI]

    Mathaisel, Dennis F. X.

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

  11. Management Forecast Quality and Capital Investment Decisions

    E-Print Network [OSTI]

    Goodman, Theodore H.

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

  12. Forecasting consumer products using prediction markets

    E-Print Network [OSTI]

    Trepte, Kai

    2009-01-01

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

  13. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    FORECASTING THE ROLE OF RENEWABLES IN HAWAII Jayant SathayeFORECASTING THE ROLF OF RENEWABLES IN HAWAII J Sa and Henrythe Conservation Role of Renewables November 18, 1980 Page 2

  14. UNIVERSITY OF CONNECTICUT SCHOOL OF ENGINEERING ANNUAL REPORT

    E-Print Network [OSTI]

    Alpay, S. Pamir

    #12;1 UNIVERSITY OF CONNECTICUT SCHOOL OF ENGINEERING ANNUAL REPORT 2011-2012 TABLE OF CONTENTS FOR CLEAN ENERGY ENGINEERING...................................................... 24 CONNECTICUT Energy Engineering (C2E2). The installation was funded by a federal stimulus grant from Connecticut

  15. UNIVERSITY OF CONNECTICUT SCHOOL OF ENGINEERING ANNUAL REPORT

    E-Print Network [OSTI]

    Alpay, S. Pamir

    #12;1 UNIVERSITY OF CONNECTICUT SCHOOL OF ENGINEERING ANNUAL REPORT 2007-08 TABLE OF CONTENTS Center for Advanced Technology.................................. 217 Connecticut Global Fuel Cell Center......................................................219 Connecticut Transportation Institute...................................................... 223

  16. Using Building Simulation and Optimization to Calculate Lookup Tables for Control

    E-Print Network [OSTI]

    Coffey, Brian

    2011-01-01

    solar (W/m2) Table 13: Base case annual energy consumptionsolar gain on window (W/m2) Figure 25: Total energy consumptionlighting energy consumption. Figure 11: Solar shading and

  17. Modeling and Forecasting Electric Daily Peak Loads

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    for the same data. Two methods are described for forecasting daily peak loads up to one week ahead through, including generator unit commitment, hydro-thermal coordination, short-term maintenance, fuel allocation forecasting accuracies. STLF forecasting covers the daily peak load, total daily energy, and daily load curve

  18. 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.

  19. Forecasting phenology under global warming

    E-Print Network [OSTI]

    Silander Jr., John A.

    Forecasting phenology under global warming Ine´s Iba´n~ez1,*, Richard B. Primack2, Abraham J in phenology. Keywords: climate change; East Asia, global warming; growing season, hierarchical Bayes; plant is shifting, and these shifts have been linked to recent global warming (Parmesan & Yohe 2003; Root et al

  20. LOAD FORECASTING Eugene A. Feinberg

    E-Print Network [OSTI]

    Feinberg, Eugene A.

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

  1. Annual Energy Review 2007

    SciTech Connect (OSTI)

    Seiferlein, Katherine E.

    2008-06-01

    The Annual Energy Review (AER) is the Energy Information Administration's (EIA) primary report of annual historical energy statistics. For many series, data begin with the year 1949. Included are data on total energy production, consumption, and trade; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, international energy, as well as financial and environment indicators; and data unit conversion tables. Publication of this report is required under Public Law 95–91 (Department of Energy Organization Act), Section 205(c), and is in keeping with responsibilities given to the EIA under Section 205(a)(2), which states: “The Administrator shall be responsible for carrying out a central, comprehensive, and unified energy data and information program which will collect, evaluate, assemble, analyze, and disseminate data and information....”

  2. Table of contents www.q2s.ntnu.no 1 Centre for Quantifiable Quality

    E-Print Network [OSTI]

    Nørvåg, Kjetil

    Table of contents www.q2s.ntnu.no 1 Q2S Centre for Quantifiable Quality of Service in Communication Systems AnnualReport2008 #12;www.q2s.ntnu.no Table of contents2 The sixth year of Q2S Telefax: +47 73 59 27 90 Email: secretary@q2s.ntnu.no Internet: www.q2s.ntnu.no Table of contents #12;3The

  3. CALIFORNIA ENERGY COMMISSION0 Annual Update to the Forecasted

    E-Print Network [OSTI]

    Additional Rooftop PV 6 Additional Combined Heat and Power 7 Adjusted Statewide Retail Sales for RPS 7.5 12.6 5 AdditionalRooftop PV - 0.4 0.7 6 AdditionalCombined Heatand Power 20.8 11.6 9.9 7 Adjusted Adjustments CED 2011 ­ Form 1.1c - CDWR, MWD, WAPA - pumping loads ­ Small LSEs (

  4. Table 1.-Statlsllcal dala on Argentina's major fishery slacks, 1980. Foreign Fishery Developments

    E-Print Network [OSTI]

    Table 1.-Statlsllcal dala on Argentina's major fishery slacks, 1980. Foreign Fishery Developments Argentina Revises Marine Resources Forecast squid one of the country's major fish- eries. INIDEP indicated- ly. Argentina signed a cooperative research agreement in 1980 with the Soviet Union to study

  5. SEP Program Transition Tables

    Broader source: Energy.gov [DOE]

    The Program Transition Tables provide information concerning the level of effort required to move from a traditional, industrial incentive program to Strategic Energy Management, ISO 50001, or SEP.

  6. Description of Detailed Tables

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

    for the 1999 Commercial Buildings Energy Consumption Survey (CBECS) consists of building characteristics tables B1 through B39, which contain the number of buildings and...

  7. SCHOOLOFSCIENCE Table of Contents

    E-Print Network [OSTI]

    Varela, Carlos

    SCHOOLOFSCIENCE Table of Contents Degrees Offered and Associated Departments 330 Overview Environmental Science 403 Interdisciplinary Science 407 Multidisciplinary Science 409 The Darrin Fresh Water

  8. Environmental Justice Tables

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

    ... H-1 Table H-1. Poverty Thresholds in 1999 by Size of Family and Number of Related Children Under 18 Years...

  9. 1995 CECS C&E Tables

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

    Fuel Oil Tables (10 pages, 58 kb) CONTENTS PAGES Table 26. Total Fuel Oil Consumption and Expenditures, 1995 Table 27. Fuel Oil Consumption and Expenditure Intensities, 1995 Table...

  10. Forecasting wind speed financial return

    E-Print Network [OSTI]

    D'Amico, Guglielmo; Prattico, Flavio

    2013-01-01

    The prediction of wind speed is very important when dealing with the production of energy through wind turbines. In this paper, we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model that has been shown to be able to reproduce accurately the statistical behavior of wind speed. The model is used to forecast, one step ahead, wind speed. In order to check the validity of the model we show, as indicator of goodness, the root mean square error and mean absolute error between real data and predicted ones. We also compare our forecasting results with those of a persistence model. At last, we show an application of the model to predict financial indicators like the Internal Rate of Return, Duration and Convexity.

  11. 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.

  12. Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia

    E-Print Network [OSTI]

    Evans, Jason

    Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south, Australia. D Corresponding author. Email: h.clarke@student.unsw.edu.au Abstract. The fire weather of south of the McArthur Forest Fire Danger Index (FFDI) using probability density function skill scores, annual

  13. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16

    and encouragement. I am very grateful to Lucille and Michael Hobbs for their friendship, understanding and financial support. Finally, thank you to Tom Decker, Pat Jackson and Brian Zellar for all their contributions and hard work on this project... below: 1. Na?ve 2. Linear Regression 3. Moving Average 4. Exponential 5. Double exponential The na?ve forecasting method assumes that more recent data values are the best predictors of future values. The model is ? t+1 = Y t . Where ? t...

  14. TABLE OF NUCLIDES

    E-Print Network [OSTI]

    Shirley, V.S.

    2008-01-01

    1980) RECEIVED TABLE OF NUCLIDES V. S. Shirley and C. M.Office of Standard Reference Data. -ii- TABLE OF NUCLIDESNuclide Z EI 0 n I H A B B Abundance or t 1 / 2 10.6 m 12.33

  15. Petroleum supply annual 1994. Volume 1

    SciTech Connect (OSTI)

    1995-05-22

    The Petroleum Supply Annual (PSA) contains information on the supply and disposition of crude oil and petroleum products. The publication reflects data that were collected from the petroleum industry during 1994 through annual and monthly surveys. The PSA is divided into two volumes. This first volume contains four sections: Summary Statistics, Detailed Statistics, Refinery Capacity, and Oxygenate Capacity each with final annual data. The second volume contains final statistics for each month of 1994, and replaces data previously published in the Petroleum Supply Monthly (PSM). The tables in Volumes 1 and 2 are similarly numbered to facilitate comparison between them. Below is a description of each section in Volume 1 of the PSA.

  16. Petroleum supply annual, 1997. Volume 1

    SciTech Connect (OSTI)

    1998-06-01

    The Petroleum Supply Annual (PSA) contains information on the supply and disposition of crude oil and petroleum products. The publication reflects data that were collected from the petroleum industry during 1997 through annual and monthly surveys. The PSA is divided into two volumes. This first volume contains three sections: Summary Statistics, Detailed Statistics, and Refinery Statistics; each with final annual data. The second volume contains final statistics for each month of 1997, and replaces data previously published in the Petroleum Supply Monthly (PSM). The tables in Volumes 1 and 2 are similarly numbered to facilitate comparison between them. 16 figs., 48 tabs.

  17. Petroleum supply annual 1993. Volume 1

    SciTech Connect (OSTI)

    Not Available

    1994-06-01

    The Petroleum Supply Annual (PSA) contains information on the supply and disposition of crude oil and petroleum products. The publication reflects data that were collected from the petroleum industry during 1993 through annual and monthly surveys. The PSA is divided into two volumes. This first volume contains four sections: Summary Statistics, Detailed Statistics, Refinery Capacity, and Oxygenate Capacity each with final annual data. The second volume contains final statistics for each month of 1993, and replaces data previously published in the Petroleum Supply Monthly (PSM). The tables in Volumes 1 and 2 are similarly numbered to facilitate comparison between them. Below is a description of each section in Volume 1 of the PSA.

  18. Petroleum supply annual 1998: Volume 1

    SciTech Connect (OSTI)

    1999-06-01

    The ``Petroleum Supply Annual`` (PSA) contains information on the supply and disposition of crude oil and petroleum products. The publication reflects data that were collected from the petroleum industry during 1998 through annual and monthly surveys. The PSA is divided into two volumes. This first volume contains three sections: Summary Statistics, Detailed Statistics, and Refinery Statistics; each with final annual data. The second volume contains final statistics for each month of 1998, and replaces data previously published in the PSA. The tables in Volumes 1 and 2 are similarly numbered to facilitate comparison between them. 16 figs., 59 tabs.

  19. 2003 CBECS Detailed Tables: Summary

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

    Tables 2003 CBECS Detailed Tables most recent available Released: September 2008 Building Characteristics | Consumption & Expenditures | End-Use Consumption In the 2003 CBECS,...

  20. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

    Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens to the Klim wind farm using three WPPT forecasts based on different weather forecasting systems. It is shown of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

  1. Weather Forecasts are for Wimps: Why Water Resource Managers Do Not Use Climate Forecasts

    E-Print Network [OSTI]

    Rayner, Steve; Lach, Denise; Ingram, Helen

    2005-01-01

    and Winter, S. G. : 1960, Weather Information and EconomicThe ENSO Signal 7, 4–6. WEATHER FORECASTS ARE FOR WIMPSWEATHER FORECASTS ARE FOR WIMPS ? : WHY WATER RESOURCE

  2. Memo 2005-044 Annual report 2004

    E-Print Network [OSTI]

    report 2004 Sociological Investigation of the Reception of Nysted Offshore Wind Farm Table of Contents: 1 Offshore Wind Farm 1 Introduction This annual report presents the work related to the sociological part wind farms: Horns Rev Offshore Wind Farm, west of Blaavands Huk in Jutland, and Nysted Offshore Wind

  3. Computer Security Division 2009 Annual Report

    E-Print Network [OSTI]

    Security 12 Smart Grid Cyber Security 13 Supply Chain Risk Management 13 Cryptographic Validation Programs Computing Project 36 Policy Machine 36 Security for Grid and Pervasive Systems 38 Security OntologiesComputer Security Division 2009 Annual Report #12;Table of Contents Welcome 1 Division

  4. Computer Security Division 2008 Annual Report

    E-Print Network [OSTI]

    played an active role in implementation planning for the Comprehensive National Cyber Security InitiativeComputer Security Division 2008 Annual Report #12;TAble of ConTenTS Welcome 1 Division Organization 2 The Computer Security Division Responds to the Federal Information Security Management Act

  5. AEGEAN DENDROCHRONOLOGY 1992 ANNUAL PROGRESS REPORT

    E-Print Network [OSTI]

    Manning, Sturt

    1 AEGEAN DENDROCHRONOLOGY PROJECT 1992 ANNUAL PROGRESS REPORT ÇATAL HÜYÜK The Neolithic settlement. The sophisticated architecture (Fig.1), the unexpected and sensational wall-paintings, the bizarre religious-of-the-pants estimates of the dates, and the table of dates shown in Fig.2 left was a real breakthrough. Note that all

  6. The Preservation of Physical Fashion Forecasts

    E-Print Network [OSTI]

    Kosztowny, Alexander John

    2015-01-01

    schools and their libraries, which use trend forecastingin archives and libraries would be that the trend forecastsin a library or archive, not exclusively to trend forecasts.

  7. Project Profile: Forecasting and Influencing Technological Progress...

    Energy Savers [EERE]

    R&D translates into improved performance and reduced costs for energy technologies. Motivation Technological forecasts, which plot the anticipated performance and costs of...

  8. Promotional forecasting in the grocery retail business

    E-Print Network [OSTI]

    Koottatep, Pakawkul

    2006-01-01

    Predicting customer demand in the highly competitive grocery retail business has become extremely difficult, especially for promotional items. The difficulty in promotional forecasting has resulted from numerous internal ...

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

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

    that take place in complex terrain, this funding opportunity will improve foundational weather models by developing short-term wind forecasts for use by industry professionals,...

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

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

    processes that take place in complex terrain, this funding would improve foundational weather models by developing short-term wind forecasts for use by industry professionals,...

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

    E-Print Network [OSTI]

    to the electricity price forecast. This resource mix is used to forecast the fuel consumption and carbon dioxide (CO2Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price forecast of the Fifth Northwest Power Plan. This forecast is an estimate of the future price of electricity

  12. 1Bureau of Meteorology | Water Information > INFORMATION SHEET 6 > Flood Forecasting and Warning Services Flood Forecasting

    E-Print Network [OSTI]

    Greenslade, Diana

    SHEET 6 1Bureau of Meteorology | Water Information > INFORMATION SHEET 6 > Flood Forecasting and Warning Services Flood Forecasting and Warning Services The Bureau of Meteorology (the Bureau) is responsible for providing an effective flood forecasting and warning service in each Australian state

  13. Annual energy review 1997

    SciTech Connect (OSTI)

    1998-07-01

    The Annual Energy Review (AER) is a historical data report that tells many stories. It describes, in numbers, the changes that have occurred in US energy markets since the midpoint of the 20th century. In many cases, those markets differ vastly from those of a half-century ago. By studying the graphs and data tables presented in this report, readers can learn about past energy supply and usage in the United States and gain an understanding of the issues in energy and the environment now before use. While most of this year`s report content is similar to last year`s, there are some noteworthy developments. Table 1.1 has been restructured into more summarized groupings -- fossil fuels, nuclear electric power, and renewable energy -- to aid analysts in their examination of the basic trends in those broad categories. Readers` attention is also directed to the electricity section, where considerable reformatting of the tables and graphs has been carried out to help clarify past and recent trends in the electric power industry as it enters a period of radical restructuring. Table 9.1, which summarizes US nuclear generating units, has been redeveloped to cover the entire history of the industry in this country and to provide categories relevant in assessing the future of the industry, such as the numbers of ordered generating units that have been canceled and those that were built and later shut down. In general, the AER emphasizes domestic energy statistics. Sections 1 through 10 and Section 12 are devoted mostly to US data; Section 11 reports on international statistics and world totals. 140 figs., 141 tabs.

  14. NREL: Transmission Grid Integration - Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines lightGeospatial ToolkitSMARTS -BeingFuture forForecasting NREL researchers

  15. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar2-0057-EA Jump to:ofEnia SpAFlex Fuels Energy JumpVyncke Jump to:Forecast

  16. Forecasting Market Demand for New Telecommunications Services: An Introduction

    E-Print Network [OSTI]

    Parsons, Simon

    Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc in demand forecasting for new communication services. Acknowledgments: The writing of this paper commenced employers or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica- tions

  17. Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting

    E-Print Network [OSTI]

    Plale, Beth

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

  18. Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts

    E-Print Network [OSTI]

    Raftery, Adrian

    Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts VERONICA ensembles that generates calibrated probabilistic forecast products for weather quantities at indi- vidual perturbation (GOP) method, and extends BMA to generate calibrated probabilistic forecasts of whole weather

  19. SCHOOLOFSCIENCE Table of Contents

    E-Print Network [OSTI]

    Varela, Carlos

    SCHOOLOFSCIENCE Table of Contents Degrees Offered and Associated Departments 324 Overview The Darrin Fresh Water Institute 401 New York Center for Studies on the Origins of Life 402 New York State

  20. Petroleum supply annual 1994, Volume 2

    SciTech Connect (OSTI)

    1995-06-01

    The Petroleum Supply Annual (PSA) contains information on the supply and disposition of crude oil and petroleum products. The publication reflects data that were collected from the petroleum industry during 1994 through annual and monthly surveys. The PSA is divided into two volumes. This first volume contains four sections: Summary Statistics, Detailed Statistics, Refinery Capacity, and Oxygenate Capacity each with final annual data. The second volume contains final statistics for each month of 1994, and replaces data previously published in the Petroleum Supply Monthly (PSM). The tables in Volumes 1 and 2 are similarly numbered to facilitate comparison between them. Explanatory Notes, located at the end of this publication, present information describing data collection, sources, estimation methodology, data quality control procedures, modifications to reporting requirements and interpretation of tables. Industry terminology and product definitions are listed alphabetically in the Glossary.

  1. Nonparametric models for electricity load forecasting

    E-Print Network [OSTI]

    Genève, Université de

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

  2. Smooth Calibration, Leaky Forecasts, and Finite Recall

    E-Print Network [OSTI]

    Hart, Sergiu

    Smooth Calibration, Leaky Forecasts, and Finite Recall Sergiu Hart October 2015 SERGIU HART c 2015 ­ p. #12;Smooth Calibration, Leaky Forecasts, and Finite Recall Sergiu Hart Center for the Study of Rationality Dept of Mathematics Dept of Economics The Hebrew University of Jerusalem hart@huji.ac.il http://www.ma.huji.ac.il/hart

  3. Multivariate Time Series Forecasting in Incomplete Environments

    E-Print Network [OSTI]

    Roberts, Stephen

    Multivariate Time Series Forecasting in Incomplete Environments Technical Report PARG 08-03 Seung of Oxford December 2008 #12;Seung Min Lee and Stephen J. Roberts Technical Report PARG 08-03 Multivariate missing observations and forecasting future values in incomplete multivariate time series data. We study

  4. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary PDF of the author, Guangzhou 510301, China9 2. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological10, China20 21 22 23 24 Submitted to Weather and Forecasting25 2014. 12. 2826 27 Corresponding author: Dr

  5. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Johnson, Richard H.

    Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary PDF of the author Fort Collins, Colorado7 October 20128 (submitted to Weather and Forecasting)9 1 Corresponding author address: Rebecca D. Adams-Selin, HQ Air Force Weather Agency 16th Weather Squadron, 101 Nelson Dr., Offutt

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

    Office of Environmental Management (EM)

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

  7. 2012 NISE Awards Summary Table

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

    refcst 1,675,000 BER Climate Research A multi-decadal reforecast data set to improve weather forecasts for renewable energy applications Yosuke Kanai, University of North...

  8. Earthquake Forecast via Neutrino Tomography

    E-Print Network [OSTI]

    Bin Wang; Ya-Zheng Chen; Xue-Qian Li

    2011-03-29

    We discuss the possibility of forecasting earthquakes by means of (anti)neutrino tomography. Antineutrinos emitted from reactors are used as a probe. As the antineutrinos traverse through a region prone to earthquakes, observable variations in the matter effect on the antineutrino oscillation would provide a tomography of the vicinity of the region. In this preliminary work, we adopt a simplified model for the geometrical profile and matter density in a fault zone. We calculate the survival probability of electron antineutrinos for cases without and with an anomalous accumulation of electrons which can be considered as a clear signal of the coming earthquake, at the geological region with a fault zone, and find that the variation may reach as much as 3% for $\\bar \

  9. 1997 Housing Characteristics Tables Housing Unit Tables

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1 Table 1.10 CoolingNotes &* j o n p o J d

  10. 1997 Housing Characteristics Tables Housing Unit Tables

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1 Table 1.10 CoolingNotes &* j o n p o J dPercent

  11. FY 2013 Laboratory Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuelsof Energy Services » Program ManagementAct FAQsAnnualAnnualHawaii 13

  12. FY 2013 State Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuelsof Energy Services » Program ManagementAct FAQsAnnualAnnualHawaii

  13. FY 2013 Statistical Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuelsof Energy Services » Program ManagementAct FAQsAnnualAnnualHawaiiStatistical

  14. 1995 CECS C&E Tables

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

    Electricity Tables (35 pages, 218 kb) CONTENTS PAGES Table 9. Total Electricity Consumption and Expenditures, 1995 Table 10. Electricity Consumption and Expenditure Intensities,...

  15. 1995 CECS C&E Tables

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

    kb) CONTENTS PAGES Table 1. Total Energy Consumption by Major Fuel, 1995 Table 9. Total Electricity Consumption and Expenditures, 1995 Table 20. Total Natural Gas Consumption and...

  16. 1995 CECS C&E Tables

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

    pages, 95 kb) CONTENTS PAGES Table 3. Consumption for Sum of Major Fuels, 1995 Table 10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas...

  17. 1995 CECS C&E Tables

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

    kb) CONTENTS PAGES Table 2. Total Energy Expenditures by Major Fuel, 1995 Table 9. Total Electricity Consumption and Expenditures, 1995 Table 20. Total Natural Gas Consumption and...

  18. 1995 CECS C&E Tables

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

    pages, 95 kb) CONTENTS PAGES Table 4. Expenditures for Sum of Major Fuels, 1995 Table10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas...

  19. Forecasting Random Walks Under Drift Instability

    E-Print Network [OSTI]

    Pesaran, M Hashem; Pick, Andreas

    will yield a biased forecast but will continue to have the least variance. On the other hand a forecast based on the sub-sample {yTi , yTi+1, . . . , yT }, where Ti > 1 is likely to have a lower bias but could be inefficient due to a higher variance... approach considered in Pesaran and Timmermann (2007) is to use different sub-windows to forecast and then average the outcomes, either by means of cross-validated weights or by simply using equal weights. To this end consider the sample {yTi , yTi+1...

  20. 1993 Solid Waste Reference Forecast Summary

    SciTech Connect (OSTI)

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

    1993-08-01

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

  1. 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.

  2. Wind-Wave Probabilistic Forecasting based on Ensemble

    E-Print Network [OSTI]

    Wind-Wave Probabilistic Forecasting based on Ensemble Predictions Maxime FORTIN Kongens Lyngby 2012.imm.dtu.dk IMM-PhD-2012-86 #12;Summary Wind and wave forecasts are of a crucial importance for a number weather forecasts and do not take any possible correlation into ac- count. Since wind and wave forecasts

  3. 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.

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

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural networks, Neural networks, Modeling, Forecasting, Energy demand, Time series forecasting, Power system demand time series based only on data for six years to forecast the demand for the seventh year. Both

  5. Annual Energy Review 2004

    SciTech Connect (OSTI)

    Seiferlein, Katherine E.

    2005-08-01

    The Annual Energy Review (AER) is the Energy Information Administration's (EIA) primary report of annual historical energy statistics. For many series, data begin with the year 1949. Included are data on total energy production, consumption, and trade; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, international energy, as well as financial and environment indicators; and data unit conversion tables. Publication of this report is required under Public Law 95–91 (Department of Energy Organization Act), Section 205(c), and is in keeping with responsibilities given to the EIA under Section 205(a)(2), which states: “The Administrator shall be responsible for carrying out a central, comprehensive, and unified energy data and information program which will collect, evaluate, assemble, analyze, and disseminate data and information....” The AER is intended for use by Members of Congress, Federal and State agencies energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the AER and in other EIA publications.

  6. Annual Energy Review 2005

    SciTech Connect (OSTI)

    Seiferlein, Katherine E.

    2006-07-01

    The Annual Energy Review (AER) is the Energy Information Administration's (EIA) primary report of annual historical energy statistics. For many series, data begin with the year 1949. Included are data on total energy production, consumption, and trade; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, international energy, as well as financial and environment indicators; and data unit conversion tables. Publication of this report is required under Public Law 95–91 (Department of Energy Organization Act), Section 205(c), and is in keeping with responsibilities given to the EIA under Section 205(a)(2), which states: “The Administrator shall be responsible for carrying out a central, comprehensive, and unified energy data and information program which will collect, evaluate, assemble, analyze, and disseminate data and information....” The AER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the AER and in other EIA publications.

  7. Annual Energy Review 2006

    SciTech Connect (OSTI)

    Seiferlein, Katherine E.

    2007-06-01

    The Annual Energy Review (AER) is the Energy Information Administration's (EIA) primary report of annual historical energy statistics. For many series, data begin with the year 1949. Included are data on total energy production, consumption, and trade; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, international energy, as well as financial and environment indicators; and data unit conversion tables. Publication of this report is required under Public Law 95–91 (Department of Energy Organization Act), Section 205(c), and is in keeping with responsibilities given to the EIA under Section 205(a)(2), which states: “The Administrator shall be responsible for carrying out a central, comprehensive, and unified energy data and information program which will collect, evaluate, assemble, analyze, and disseminate data and information....” The AER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the AER and in other EIA publications.

  8. Electric power annual 1992

    SciTech Connect (OSTI)

    Not Available

    1994-01-06

    The Electric Power Annual presents a summary of electric utility statistics at national, regional and State levels. The objective of the publication is to provide industry decisionmakers, government policymakers, analysts and the general public with historical data that may be used in understanding US electricity markets. The Electric Power Annual is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels; Energy Information Administration (EIA); US Department of Energy. ``The US Electric Power Industry at a Glance`` section presents a profile of the electric power industry ownership and performance, and a review of key statistics for the year. Subsequent sections present data on generating capability, including proposed capability additions; net generation; fossil-fuel statistics; retail sales; revenue; financial statistics; environmental statistics; electric power transactions; demand-side management; and nonutility power producers. In addition, the appendices provide supplemental data on major disturbances and unusual occurrences in US electricity power systems. Each section contains related text and tables and refers the reader to the appropriate publication that contains more detailed data on the subject matter. Monetary values in this publication are expressed in nominal terms.

  9. STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES

    E-Print Network [OSTI]

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

  10. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand Bill Junker Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS

  11. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P

  12. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    /demographic growth, relatively low electricity and natural gas rates, and relatively low efficiency program CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity Manager Bill Junker Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY

  13. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    incorporates relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P. Oglesby Executive

  14. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    high economic/demographic growth, relatively low electricity and natural gas rates, and relatively low CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION

  15. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    incorporates relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P

  16. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand Gough Office Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS

  17. Text-Alternative Version LED Lighting Forecast

    Broader source: Energy.gov [DOE]

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

  18. Load Forecast For use in Resource Adequacy

    E-Print Network [OSTI]

    forecast of 4) Calculate Hourly Load Allocation Factor s for each day for 2019 For use in RA analysis as a function ofthe load for electricity in the region as a function of cyclical, weather and economic variables

  19. Wind Speed Forecasting for Power System Operation 

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22

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

  20. Testing Competing High-Resolution Precipitation Forecasts

    E-Print Network [OSTI]

    Gilleland, Eric

    Testing Competing High-Resolution Precipitation Forecasts Eric Gilleland Research Prediction Comparison Test D1 D2 D = D1 ­ D2 copyright NCAR 2013 Loss Differential Field #12;Spatial Prediction Comparison Test Introduced by Hering and Genton

  1. New product forecasting in volatile markets

    E-Print Network [OSTI]

    Baldwin, Alexander (Alexander Lee)

    2014-01-01

    Forecasting demand for limited-life cycle products is essentially projecting an arc trend of demand growth and decline over a relatively short time horizon. When planning for a new limited-life product, many marketing and ...

  2. Potential Economic Value of Seasonal Hurricane Forecasts

    E-Print Network [OSTI]

    Emanuel, Kerry Andrew

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

  3. "Annual Coal Report

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1 Table 1.10 CoolingNotes & Sources1) JuneAnnual

  4. ISSUE TABLE OF CONTENTS

    E-Print Network [OSTI]

    SPECTRA HOME CURRENT ISSUE TABLE OF CONTENTS TECHNOLOGY BUSINESS PRESSTIME BULLETIN ARTICLE Thomas Young's classic setup for the demonstration of interference features light from one source incident on two vertical slits because the phenomenon occurs only if the light from the slits has a well

  5. Table of Contents Introduction

    E-Print Network [OSTI]

    Nagy, Eric Sándor

    include nitrogen oxides (NOx = NO + NO2 ), nitric acid (HNO3 ), nitrous oxide (N2 O, a greenhouse gas.TheHaber-BoschprocessalsosuppliesNH3 for industrial processes. Anthropogenic sources of nitrogen are twice as large as natural terDRAFT - 1 #12;2 - DRAFT Table of Contents Introduction What is Reactive Nitrogen and Why

  6. TABLE OF CONTENTS ABSTRACT . . .. . . .. . . . . . . . . . . . . . . . . . . . . . v

    E-Print Network [OSTI]

    Oak Ridge National Laboratory

    ........................................................ 2 City Selection ................................................ 2 Weather Data and Building Loads. MONTHLY HEAT GAIN/LOSS FACTORS ........................... 5 TABLE 2. BASE TEMPERATURES

  7. Energy.gov Data Tables

    Broader source: Energy.gov [DOE]

    Follow these guidelines for creating Section 508-compliant data tables in the Energy.gov Drupal environment.

  8. Secretary's annual report to Congress

    SciTech Connect (OSTI)

    None

    1980-01-01

    This second annual report of the DOE covers activities of all elements of the department except the independent FERC, which issues its own annual report. Individual chapters concern a posture statement, conservation, solar and other renewable energy, fossil energy, electric energy, nuclear energy, the environment, defense programs, international programs, general science programs, energy information, economic regulation, energy production, and support operations. The following appendixes are also included: foreign direct investments in US energy sources and supplies, exports of energy resources by foreign companies, major recipients of DOE funding, actions taken regarding disclosure of energy assets by DOE employees, financial assistance programs for alternative fuel demonstration facilities, and 1978 budget summary. 16 figures, 56 tables. (RWR)

  9. World Oils`s 1995 coiled tubing tables

    SciTech Connect (OSTI)

    1995-03-01

    Increasingly in demand in almost every aspect of today`s E and P market because of flexibility, versatility and economy, coiled tubing is being used for a variety of drilling, completion and production operations that previously required conventional jointed pipe, workover and snubbing units, or rotary drilling rigs. For 1995 the popular coiled tubing tables have been reformatted, expanded and improved to give industry engineering and field personnel additional, more specific selection, operational and installation information. Traditional specifications and dimensions have been augmented by addition of calculated performance properties for downhole workover and well servicing applications. For the first time the authors are presenting this information as a stand-alone feature, separate from conventional jointed tubing connection design tables, which are published annually in the January issue. With almost seven times as much usable data as previous listings, the authors hope that their new coiled tubing tables are even more practical and useful to their readers.

  10. 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.

  11. Annual Reports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L O O D S TAPropaneandAn319 125 U.S.812AnnualFinalAnnual

  12. Annual Report

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on DeliciousMathematics And StatisticsProgram ManagerCorridor Designations inEnergy 4 Report AnnualAnnual Planning09

  13. Annual Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i p a l De p u t yWaste |4 2014 Annual Planning Summary for the2011 Annual

  14. Intra-hour Direct Normal Irradiance solar forecasting using genetic programming

    E-Print Network [OSTI]

    Queener, Benjamin Daniel

    2012-01-01

    guideline for Solar Power Forecasting Performance . . 46 viof forecasting techniques for solar power production with noand A. Pavlovski, “Solar power forecasting performance

  15. A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of the WRF model solar irradiance forecasts in Andalusia (Beyer, H. , 2009.    Irradiance forecasting for the power dependent probabilistic irradiance  forecasts for coastal 

  16. ENERGY & ENVIRONMENT DIVISION. ANNUAL REPORT FY 1980

    E-Print Network [OSTI]

    Authors, Various

    2010-01-01

    The results of the energy demand forecasts are presented inthe "low-growth" energy-demand forecasts that have recentlyprovide detailed forecasts of energy demand for the state's

  17. Mathematics Of Ice To Aid Global Warming Forecasts Mathematics Of Ice To Aid Global Warming Forecasts

    E-Print Network [OSTI]

    Golden, Kenneth M.

    Mathematics Of Ice To Aid Global Warming Forecasts Mathematics Of Ice To Aid Global Warming forecasts of how global warming will affect polar icepacks. See also: Earth & Climate q Global Warming q the effects of climate warming, and its presence greatly reduces solar heating of the polar oceans." "Sea ice

  18. 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.

  19. Forecasting Prices andForecasting Prices and Congestion forCongestion for

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    Goal: Design nodal price and grid congestion forecasting tools for market operators and market Traders To facilitate scenario-conditioned planning Price forecasting for Market Participants (MPs) To manage short for portfolio management by power market participants Conclusion #12;Project OverviewProject Overview Project

  20. Petroleum supply annual 1995: Volume 2

    SciTech Connect (OSTI)

    1996-06-01

    The Petroleum Supply Annual (PSA) contains information on the supply and disposition of crude oil and petroleum products. The publication reflects data that were collected from the petroleum industry during 1995 through monthly surveys. The PSA is divided into two volumes. This first volume contains three sections: Summary Statistics, Detailed Statistics, and selected Refinery Statistics each with final annual data. The second volume contains final statistics for each month of 1995, and replaces data previously published in the Petroleum Supply Monthly (PSM). The tables in Volumes 1 and 2 are similarly numbered to facilitate comparison between them. Explanatory Notes, located at the end of this publication, present information describing data collection, sources, estimation methodology, data quality control procedures, modifications to reporting requirements and interpretation of tables. Industry terminology and product definitions are listed alphabetically in the Glossary.

  1. Petroleum supply annual, 1997. Volume 2

    SciTech Connect (OSTI)

    1998-06-01

    The Petroleum Supply Annual (PSA) contains information on the supply and disposition of crude oil and petroleum products. The publication reflects data that were collected from the petroleum industry during 1997 through monthly surveys. The PSA is divided into two volumes. The first volume contains three sections: Summary Statistics, Detailed Statistics, and Refinery Statistics; each with final annual data. The second volume contains final statistics for each month of 1997, and replaces data previously published in the Petroleum Supply Monthly (PSM). The tables in Volumes 1 and 2 are similarly numbered to facilitate comparison between them. Explanatory Notes, located at the end of this publication, present information describing data collection, sources, estimation methodology, data quality control procedures, modifications to reporting requirements and interpretation of tables. Industry terminology and product definitions are listed alphabetically in the Glossary. 35 tabs.

  2. Petroleum supply annual 1998: Volume 2

    SciTech Connect (OSTI)

    1999-06-01

    The Petroleum Supply Annual (PSA) contains information on the supply and disposition of crude oil and petroleum products. The publication reflects data that were collected from the petroleum industry during 1998 through monthly surveys. The PSA is divided into two volumes. The first volume contains three sections: Summary Statistics, Detailed Statistics, and Refinery Statistics; each with final annual data. This second volume contains final statistics for each month of 1998, and replaces data previously published in the Petroleum Supply Monthly (PSM). The tables in Volumes 1 and 2 are similarly numbered to facilitate comparison between them. Explanatory Notes, located at the end of this publication, present information describing data collection, sources, estimation methodology, data quality control procedures, modifications to reporting requirements and interpretation of tables. Industry terminology and product definitions are listed alphabetically in the Glossary. 35 tabs.

  3. Petroleum supply annual 1996: Volume 2

    SciTech Connect (OSTI)

    1997-06-01

    The Petroleum Supply Annual (PSA) contains information on the supply and disposition of crude oil and petroleum products. The publication reflects data that were collected from the petroleum industry during 1996 through monthly surveys. The PSA is divided into two volumes. The first volume contains three sections: Summary Statistics, Detailed Statistics, and Refinery Capacity; each with final annual data. The second volume contains final statistics for each month of 1996, and replaces data previously published in the Petroleum Supply Monthly (PSM). The tables in Volumes 1 and 2 are similarly numbered to facilitate comparison between them. Explanatory Notes, located at the end of this publication, present information describing data collection, sources, estimation methodology, data quality control procedures, modifications to reporting requirements and interpretation of tables. Industry terminology and product definitions are listed alphabetically in the Glossary. 35 tabs.

  4. 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.

  5. Waste generation forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1995-FY 2002, September 1994 revision

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

    A comprehensive waste-forecasting task was initiated in FY 1991 to provide a consistent, documented estimate of the volumes of waste expected to be generated as a result of U.S. Department of Energy-Oak Ridge Operations (DOE-ORO) Environmental Restoration (ER) OR-1 Project activities. Continual changes in the scope and schedules for remedial action (RA) and decontamination and decommissioning (D&D) activities have required that an integrated data base system be developed that can be easily revised to keep pace with changes and provide appropriate tabular and graphical output. The output can then be analyzed and used to drive planning assumptions for treatment, storage, and disposal (TSD) facilities. The results of this forecasting effort and a description of the data base developed to support it are provided herein. The initial waste-generation forecast results were compiled in November 1991. Since the initial forecast report, the forecast data have been revised annually. This report reflects revisions as of September 1994.

  6. NREL Annual Environmental Performance Reports (Annual Site Environment...

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

    NREL Annual Environmental Performance Reports (Annual Site Environmental Reports) NREL Annual Environmental Performance Reports (Annual Site Environmental Reports) Every year NREL...

  7. LANL JOWOG 31 2012 Forecast

    SciTech Connect (OSTI)

    Vidlak, Anton J. II [Los Alamos National Laboratory

    2012-08-08

    Joint Working Group (JOWOG) 31, Nuclear Weapons Engineering, has a particularly broad scope of activities within its charter which emphasizes systems engineering. JOWOG 31 brings together experts from AWE and the national laboratories to address engineering issues associated with warhead design and certification. Some of the key areas of interaction, as addressed by the HOCWOGs are: (1) Engineering Analysis, (2) Hydrodynamic Testing, (3) Environmental Testing, and (4) Model Based Integrated Toolkit (MBIT). Gas Transfer Systems and Condition Monitoring interaction has been moved back to JOWOG 31. The regularly scheduled JOWOG 31 activities are the General Sessions, Executive Sessions, Focused Exchanges and HOCWOGs. General Sessions are scheduled every 12-18 months and are supported by the four design laboratories (AWE, LANL, LLNL, and SNL). Beneficial in educating the next generation of weapons engineers and establishing contacts between AWE and the US laboratory personnel. General Sessions are based on a blend of presentations and workshops centered on various themed subjects directly related to Stockpile Stewardship. HOCWOG meetings are more narrowly focused than the General Sessions. They feature presentations by experts in the field with a greater emphasis on round table discussions. Typically about 20 people attend. Focused exchanges are generally the result of interactions within JOWOG general sessions or HOCWOG meetings. They generally span a very specific topic of current interest within the US and UK.

  8. 2010 ANNUAL RESEARCH REPORT 2010 ANNUAL RESEARCH REPORT 2010 ANNUAL RESEARCH REPORT RESEARCH REPORT2010ANNUAL RESEARCH REPORT2010ANNUAL RESEARCH REPORT

    E-Print Network [OSTI]

    Hill, Jeffrey E.

    2010 ANNUAL RESEARCH REPORT 2010 ANNUAL RESEARCH REPORT 2010 ANNUAL RESEARCH REPORT RESEARCH REPORT2010ANNUAL RESEARCH REPORT2010ANNUAL RESEARCH REPORT 2010 ANNUAL RESEARCH REPORT 2010 ANNUAL RESEARCH REPORT 2010 ANNUAL RESEARCH REPORT RESEARCH REPORT2010ANNUAL RESEARCH REPORT2010ANNUAL RESEARCH REPORT

  9. Annual Report 2009-2010 Table of Contents

    E-Print Network [OSTI]

    Laval, Université

    title of "Sustainable Campus." But sustainable development at Université Laval is about much more than the impetus behind the University Council's decision in April 2010 to approve the new sustainable development programs. Another important aspect of Université Laval's sustainable development approach in 2009

  10. 2008-2009Annual Report Table of Contents

    E-Print Network [OSTI]

    Laval, Université

    of sustainable development. After advocating the adoption of a university-wide sustainable development policy undergraduate programs must introduce students to sustainable development issues.After reviewing the favorable conclusions of a feasibility study on the project, the council also recommended that a sustainable development

  11. Annual Report2011-2012 Table of Contents

    E-Print Network [OSTI]

    Laval, Université

    , and reaffirmed our commitment to responsible and sustainable development. In addition, we added six new: a certificate in sustainable tourism, a DESS in ergonomics and another one in innovation, a new bachelor at Université Laval, as shown by the creation of the School of Design in the Faculty of Architecture, Arts

  12. 2CCSI Annual Report 2014 Table of Contents

    E-Print Network [OSTI]

    to Gulf Coast energy 16 Protecting US hydropower through climate modeling 17 Data Integration with major, next-generation climate model 9 New Initiatives for 2015 NGEE-Tropics: A decade of tropical the influence of climate on economies and energy futures 15 Impacts, Adaptation, and Vulnerability Science

  13. Annual Report2012-2013 Table of Contents

    E-Print Network [OSTI]

    Laval, Université

    , all from a sustainable development perspective. To learn more about the energy and creativity tribute to those among us who serve as models: new recipients of honorary doctorates from Université Laval

  14. Table 3a. Real Average Annual Coal Transportation Costs from...

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

    a","W","-","-","-","-","-" "Uinta Basin","Alabama","W","-","-","-","-","-" "Uinta Basin","California","-","W","-","-","-","-" "Uinta Basin","Colorado","W","W","W","W","-","-"...

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul AugAdditions1--Electronic860‹ Analysis

  16. Table 3. Annual commercial spent fuel discharges and burnup

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969 1.979 1.988 1.996Deutsche Bank AGTotal96 Created on:

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

    E-Print Network [OSTI]

    Raftery, Adrian

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

  18. New directions for forecasting air travel passenger demand

    E-Print Network [OSTI]

    Garvett, Donald Stephen

    1974-01-01

    While few will disagree that sound forecasts are an essential prerequisite to rational transportation planning and analysis, the making of these forecasts has become a complex problem with the broadening of the scope and ...

  19. Generalized Cost Function Based Forecasting for Periodically Measured Nonstationary Traffic

    E-Print Network [OSTI]

    Zeng, Yong - Department of Mathematics and Statistics, University of Missouri

    1 Generalized Cost Function Based Forecasting for Periodically Measured Nonstationary Traffic true value. However, such a forecast- ing function is not directly applicable for applications potentially result in insufficient allocation of bandwidth leading to short term data loss. To facilitate

  20. The effect of multinationality on management earnings forecasts 

    E-Print Network [OSTI]

    Runyan, Bruce Wayne

    2005-08-29

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

  1. Market perceptions of efficiency and news in analyst forecast errors 

    E-Print Network [OSTI]

    Chevis, Gia Marie

    2004-11-15

    Financial analysts are considered inefficient when they do not fully incorporate relevant information into their forecasts. In this dissertation, I investigate differences in the observable efficiency of analysts' earnings forecasts between firms...

  2. DOE Releases Latest Report on Energy Savings Forecast of Solid...

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

    Latest Report on Energy Savings Forecast of Solid-State Lighting DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting September 12, 2014 - 2:06pm Addthis...

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

    E-Print Network [OSTI]

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

    2005-01-01

    Forecasts Using NEMS and GIS National Climatic Data Center.with Changing Boundaries." Use of GIS to Understand Socio-Forecasts Using NEMS and GIS Appendix A. Map Results Gallery

  4. OPERATIONAL EARTHQUAKE FORECASTING State of Knowledge and Guidelines for Utilization

    E-Print Network [OSTI]

    .................................................................................................................................... 323 II. SCIENCE OF EARTHQUAKE FORECASTING AND PREDICTION 325 A. Definitions and Concepts....................................................................................................................................... 325 B. Research on Earthquake PredictabilityOPERATIONAL EARTHQUAKE FORECASTING State of Knowledge and Guidelines for Utilization Report

  5. A=19 Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve Lithium-Ion1AJ01)72AJ02) (See Energy1959AJ76) (See95TI07)Tables for

  6. A=20 Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach HomeA Better Anode Design to Improve Lithium-Ion1AJ01)72AJ02) (See72AJ02)1959AJ76)83AJ01)Tables for A =

  7. 9He General Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-InspiredAtmosphericdevicesPPONeApril351APPLICATION OFsaferHe General Table The

  8. 9Li General Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-InspiredAtmosphericdevicesPPONeApril351APPLICATION OFsaferHe General Table

  9. A = 10 General Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-InspiredAtmosphericdevicesPPONeApril351APPLICATIONPostdoctoral10 General Tables

  10. TABLE OF CONTENTS

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-Inspired Solar Fuel Production 1:PhysicsSyndicated Contentwo2 TABLE OF

  11. TABLE OF CONTENTS

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-Inspired Solar Fuel Production 1:PhysicsSyndicated Contentwo2 TABLE OF

  12. TABLE OF CONTENTS

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-Inspired Solar Fuel Production 1:PhysicsSyndicated Contentwo2 TABLE OF

  13. FY 2005 Statistical Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergy A plug-inPPLforLDRD Report to Congress More Documents & PublicationsTable of

  14. compare_tables.xlsx

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1 Table 1.10 Cooling Degree-Days by038.2Natural

  15. Microsoft Word - table_11

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1Markets See(STEO) Highlights1199,0,26,27 Table 11

  16. Microsoft Word - table_13

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1Markets See(STEO) Highlights1199,0,26,27 Table 11

  17. ENERGY AND ENVIRONMENT DIVISION ANNUAL REPORT 1978

    E-Print Network [OSTI]

    Cairns, E.L.

    2011-01-01

    be incorporated in future energy demand forecasts and supplyshows two sets of energy demand forecasts for residential

  18. Health Care Buildings: Subcategories Table

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

    Subcategories Table Selected Data by Type of Health Care Building Number of Buildings (thousand) Percent of Buildings Floorspace (million square feet) Percent of Floorspace Square...

  19. Health Care Buildings: Equipment Table

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

    Equipment Table Buildings, Size and Age Data by Equipment Types for Health Care Buildings Number of Buildings (thousand) Percent of Buildings Floorspace (million square feet)...

  20. 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.

  1. 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)

  2. 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.

  3. Department of Civil, Environmental and Geomatic Engineering Annual Report 2005

    E-Print Network [OSTI]

    Department of Civil, Environmental and Geomatic Engineering Annual Report 2005 D-BAUGDepartment of Civil, Environmental and Geomatic Engineering #12;2 Table of Contents Preface Central Points Fires departments of civil and environmen- tal engineering (D-BAUM) and geodetic sciences (D-GEOD) as well

  4. Department of Civil, Environmental and Geomatic Engineering Annual Report 2006

    E-Print Network [OSTI]

    Department of Civil, Environmental and Geomatic Engineering Annual Report 2006 D-BAUGDepartment of Civil, Environmental and Geomatic Engineering #12;#12;#12;Table of Contents Preface Central Points Ultra-Tech Measuring Systems Studying at the Department of Civil, Environ- mental and Geomatic Engineering Facts

  5. 1999 Commercial Building Characteristics--Detailed Tables--Principal...

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

    Principal Building Activities > Detailed Tables-Principal Building Activities Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Principal Building Activities Table B1....

  6. 1999 Commercial Building Characteristics--Detailed Tables--Year...

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

    Year Constructed > Detailed Tables-Year Constructed Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Year Constructed Table B8. Year Constructed, Number of Buildings...

  7. Managerial Career Concerns and Earnings Forecasts SARAH SHAIKH

    E-Print Network [OSTI]

    Tipple, Brett

    's aversion to risk, I find that a CEO is less likely to issue an earnings forecast in periods of stricter non is more pronounced for a CEO who has greater concern for his reputation, faces more risk in forecasting the provision of earnings forecasts. Literature has long recognized that the labor market provides distinct

  8. Forecasting Market Demand for New Telecommunications Services: An Introduction

    E-Print Network [OSTI]

    McBurney, Peter

    Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc to redress this situation by presenting a discussion of the issues involved in demand forecasting for new or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica­ tions Services. 1 #12

  9. Neural Network forecasts of the tropical Pacific sea surface temperatures

    E-Print Network [OSTI]

    Hsieh, William

    Neural Network forecasts of the tropical Pacific sea surface temperatures Aiming Wu, William W Tang Jet Propulsion Laboratory, Pasadena, CA, USA Neural Networks (in press) December 11, 2005 title: Forecast of sea surface temperature 1 #12;Neural Network forecasts of the tropical Pacific sea

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

    E-Print Network [OSTI]

    i Managing Wind Power Forecast Uncertainty in Electric Grids Brandon Keith Mauch Co Paulina Jaramillo Doctor Paul Fischbeck 2012 #12;ii #12;iii Managing Wind Power Forecast Uncertainty generated from wind power is both variable and uncertain. Wind forecasts provide valuable information

  11. Forecasting Uncertainty Related to Ramps of Wind Power Production

    E-Print Network [OSTI]

    Boyer, Edmond

    Forecasting Uncertainty Related to Ramps of Wind Power Production Arthur Bossavy, Robin Girard - The continuous improvement of the accuracy of wind power forecasts is motivated by the increasing wind power. This paper presents two methods focusing on forecasting large and sharp variations in power output of a wind

  12. SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS

    E-Print Network [OSTI]

    Heinemann, Detlev

    SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS Detlev Heinemann Oldenburg in irradiance forecasting have been presented more than twenty years ago (Jensenius and Cotton, 1981), when or progress with respect to the development of solar irradiance forecasting methods. Heck and Takle (1987

  13. Choosing Words in Computer-Generated Weather Forecasts

    E-Print Network [OSTI]

    Reiter, Ehud

    to communicate numeric weather data. A corpus-based analysis of how humans write forecasts showed that there wereTime- Mousam weather-forecast generator to use consistent data-to-word rules, which avoided words which were weather forecast texts from numerical weather pre- diction data (SumTime-Mousam in fact is used

  14. Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging J. MCLEAN 2011, in final form 26 May 2012) ABSTRACT Probabilistic forecasts of wind vectors are becoming critical with univariate quantities, statistical approaches to wind vector forecasting must be based on bivariate

  15. Accuracy of near real time updates in wind power forecasting

    E-Print Network [OSTI]

    Heinemann, Detlev

    Accuracy of near real time updates in wind power forecasting with regard to different weather October 2007 #12;EMS/ECAM 2007 ­ Nadja Saleck Outline · Study site · Wind power forecasting - method #12;EMS/ECAM 2007 ­ Nadja Saleck Wind power forecast data observed wind power input (2004 ­ 2006

  16. Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging J. Mc in the context of wind power, where under- forecasting and overforecasting carry different financial penal- ties, calibrated and sharp probabilistic forecasts can help to make wind power a more financially competitive alter

  17. Forecasting Building Occupancy Using Sensor Network James Howard

    E-Print Network [OSTI]

    Hoff, William A.

    Forecasting Building Occupancy Using Sensor Network Data James Howard Colorado School of Mines@mines.edu ABSTRACT Forecasting the occupancy of buildings can lead to signif- icant improvement of smart heating throughout a building, we perform data mining to forecast occupancy a short time (i.e., up to 60 minutes

  18. Weather Forecasting -Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting - Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, "weather forecasts" are created such that selected wireless LAN performance indicators might be used to evaluate the effec- tiveness of individual weather forecasts. The paper evaluates six distinct weather

  19. Weather Forecasting Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting ­ Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, ``weather forecasts'' are created such that selected wireless LAN performance indicators might be used to evaluate the e#ec­ tiveness of individual weather forecasts. The paper evaluates six distinct weather

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

    E-Print Network [OSTI]

    Povinelli, Richard J.

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

  1. Preprints, 15th AMS Conference on Weather Analysis and Forecasting

    E-Print Network [OSTI]

    Doswell III, Charles A.

    ) models have substantially improved forecast skill. Recent and planned changes along these lines (e to delivering two kinds of weather products. The first is a day-to-day forecast of weather elements, e by the private sector. Improvements in automated techniques for the forecasting of basic weather elements

  2. Influences of soil moisture and vegetation on convective precipitation forecasts

    E-Print Network [OSTI]

    Robock, Alan

    Influences of soil moisture and vegetation on convective precipitation forecasts over the United and vegetation on 30 h convective precipitation forecasts using the Weather Research and Forecasting model over, the complete removal of vegetation produced substantially less precipitation, while conversion to forest led

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    of Solar 2011, American Solar Energy Society, Raleigh, NC.Description and validation. Solar Energy, 73 (5), 307-317.forecast database. Solar Energy, Perez, R. , S. Kivalov, J.

  4. Online short-term solar power forecasting

    SciTech Connect (OSTI)

    Bacher, Peder; Madsen, Henrik [Informatics and Mathematical Modelling, Richard Pedersens Plads, Technical University of Denmark, Building 321, DK-2800 Lyngby (Denmark); Nielsen, Henrik Aalborg [ENFOR A/S, Lyngsoe Alle 3, DK-2970 Hoersholm (Denmark)

    2009-10-15

    This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model. (author)

  5. Forecasting Hot Water Consumption in Residential Houses

    E-Print Network [OSTI]

    MacDonald, Mark

    and technological advancement in energy-intensive applications are causing fast electric energy consumption growth and consumption of electricity [8], as long as there is no significant correlation between intermittent energyArticle Forecasting Hot Water Consumption in Residential Houses Linas Gelazanskas * and Kelum A

  6. GENETIC ALGORITHM FORECASTING FOR TELECOMMUNICATIONS PRODUCTS

    E-Print Network [OSTI]

    Havlicek, Joebob

    available economic indicators such as Disposable Personal Income and New Housing Starts as independent exhibiting maximal fitness achieved RMS forecast errors below the the average two-week sales figure. 1 (Holland, 1975), (Packard, 1990), (Koza, 1992), (Bäck, et al., 1997), (Mitchell, 1998). For example, Meyer

  7. GOES Aviation Products Aviation Weather Forecasting

    E-Print Network [OSTI]

    Kuligowski, Bob

    GOES Aviation Products · The GOES aviation forecast products are based on energy measured in different characteristics #12;GOES Aviation Products Quiz · What is a geostationary satellite? · What generates energy received by the satellite in the visible band? · What generates energy received by the satellite

  8. Solar Forecasting System and Irradiance Variability Characterization

    E-Print Network [OSTI]

    solar forecasting system based on numerical weather prediction plus satellite and ground-based data.1 Photovoltaic Systems: Report 3 Development of data base allowing managed access to statewide PV and insolation Based Data 13 Summary 14 References 14 #12;List of Figures Figure Number and Title Page # 1. Topography

  9. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Reiter, Ehud

    summarisation. We found three alternative ways in which we could model data summarisation. One approach is based turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP) models is summarised as weather forecast texts. In the domain of gas turbines, sensor data from

  10. "FLIGHT PLAN" FORECASTS SEATTLE/TACOMA AND

    E-Print Network [OSTI]

    ASSESSMENT OF THE "FLIGHT PLAN" FORECASTS FOR SEATTLE/TACOMA AND REGIONAL AIRPORTS TOGETHER 1. Introduction 5 2. Airport Planning Process 7 Traditional Master Planning Application to Seattle/Tacoma. Uncertainty about Capacity 27 A Fuzzy Concept Assessment Factors Application to Seattle/Tacoma 7. Assessment

  11. Forecast Technical Document Felling and Removals

    E-Print Network [OSTI]

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

  12. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27

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

  13. Stochastic Weather Generator Based Ensemble Streamflow Forecasting

    E-Print Network [OSTI]

    Stochastic Weather Generator Based Ensemble Streamflow Forecasting by Nina Marie Caraway B of Civil Engineering 2012 #12;This thesis entitled: Stochastic Weather Generator Based Ensemble Streamflow mentioned discipline. #12;iii Caraway, Nina Marie (M.S., Civil Engineering) Stochastic Weather Generator

  14. Annual satellite imaging of the world's glaciers Assessment of glacier extent and change

    E-Print Network [OSTI]

    GLIMS HIGH ICE Annual satellite imaging of the world's glaciers Assessment of glacier extent is an international consortium of 23 regional centers ·Coordinated by U.S. Geological Survey - Flagstaff #12.S. National Research Applications: · Energy Forecasting: Energy for U.S. Northwest derived partly from

  15. A 110-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe Floods of 200307*

    E-Print Network [OSTI]

    Webster, Peter J.

    A 1­10-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe of the Brahmaputra and Ganges Rivers as they flow into Bangladesh; it has been operational since 2003. The Bangladesh points of the Ganges and Brahmaputra into Bangladesh. Forecasts with 1­10-day horizons are presented

  16. Annual Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L O O D S TAPropaneandAn319 125 U.S.812Annual ProgressANNUALY

  17. Annual Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 OutreachProductswsicloudwsiclouddenDVA N C E D B L O O D S TAPropaneandAn319 125 U.S.812Annual

  18. Annual Reports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTechtail.Theory of raregovAboutRecovery ActTools to someone by AllocationAnnual Energy

  19. Annual Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i p a l De p u t yWaste |4 2014 Annual Planning Summary for the2011

  20. 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.

  1. Table of Contents Executive Summary

    E-Print Network [OSTI]

    McDonald, Kirk

    Table of Contents Page Executive Summary I. Introduction 1 Neutrino Oscillation Results from Solar and Atmospheric Neutrino Data 1 Tables 7 References 5 Figures 9 II. Overview of the Long Baseline Experiment 17 Magnetic Moment, Charge Radius, and Extra Z-bosons 261 VII. Cost and Schedule 265 Project schedule 267 Work

  2. Supplemental Material Table of Contents

    E-Print Network [OSTI]

    Kuchta, Shawn R.

    1 Supplemental Material Table of Contents Text on the multiple individuals per population phylogeny: pg 4 Supplemental Figure 1: Phylogram of U. stansburiana populations from the complete data set that included multiple individuals per population. pg 5 Supplemental Table 1: Population locations and years

  3. A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China

    SciTech Connect (OSTI)

    Xu, Lilai; Gao, Peiqing; Cui, Shenghui; Liu, Chun

    2013-06-15

    Highlights: ? We propose a hybrid model that combines seasonal SARIMA model and grey system theory. ? The model is robust at multiple time scales with the anticipated accuracy. ? At month-scale, the SARIMA model shows good representation for monthly MSW generation. ? At medium-term time scale, grey relational analysis could yield the MSW generation. ? At long-term time scale, GM (1, 1) provides a basic scenario of MSW generation. - Abstract: Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 – 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 – 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to develop integrated policies and measures for waste management over the long term.

  4. Annual Reports | Department of Energy

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

    in PDF and will require Adobe Reader for viewing. Freedom of Information Act Annual Reports Annual Report for 2014 Annual Report for 2013 Annual Report for 2012 Annual Report...

  5. 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.

  6. Combinatorial Evolution and Forecasting of Communication Protocol ZigBee

    E-Print Network [OSTI]

    Levin, Mark Sh; Kistler, Rolf; Klapproth, Alexander

    2012-01-01

    The article addresses combinatorial evolution and forecasting of communication protocol for wireless sensor networks (ZigBee). Morphological tree structure (a version of and-or tree) is used as a hierarchical model for the protocol. Three generations of ZigBee protocol are examined. A set of protocol change operations is generated and described. The change operations are used as items for forecasting based on combinatorial problems (e.g., clustering, knapsack problem, multiple choice knapsack problem). Two kinds of preliminary forecasts for the examined communication protocol are considered: (i) direct expert (expert judgment) based forecast, (ii) computation of the forecast(s) (usage of multicriteria decision making and combinatorial optimization problems). Finally, aggregation of the obtained preliminary forecasts is considered (two aggregation strategies are used).

  7. 1995 CECS C&E Tables

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

    Building Level Intensities (percentile) (6 pages, 39 kb) CONTENTS PAGES Table 10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas Consumption and...

  8. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Census Region for Sum of Major Fuels, 1995 Table 11. Electricity Consumption and Conditional Energy Intensity by Census Region, 1995 Table 22....

  9. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Year Constructed for Sum of Major Fuels, 1995 Table 14. Electricity Consumption and Conditional Energy Intensity by Year Constructed, 1995 Table...

  10. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Building Size for Sum of Major Fuels, 1995 Table13. Electricity Consumption and Conditional Energy Intensity by Building Size, 1995 Table 24....

  11. Appendix B: Technical Projection Tables, Bioenergy Technologies...

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

    Tables B-2 Last updated: November 2014 Table B-2: Terrestrial Feedstock Supply and Logistics Costs to Supply Feedstock to a Pyrolysis Conversion Process Processing Area Cost...

  12. 1995 CECS C&E Tables

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

    Category (6 pages, 36 kb) CONTENTS PAGES Table 17. Peak Electricity Demand Category, Number of Buildings, 1995 Table 18. Peak Electricity Demand Category, Floorspace, 1995 These...

  13. Commercial Small Fruit Table of Contents

    E-Print Network [OSTI]

    Liskiewicz, Maciej

    ........................................................................................................................................ 2-1 Strawberries.................................................................................................................................................... 2-2 Table 2.1a - Strawberry Diseases, At Planting......................................................................................... 2-2 Table 2.1b - Strawberry Diseases, Post

  14. Commerial Buildings Characteristics, 1995 (Table of Contents...

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

    Number of Buildings and Relative Standard Errors, 1995 Table I.2. Participation in Energy Conservation Programs, Floorspace and Relative Standard Errors, 1995 Table J.1....

  15. Trends in Commercial Buildings--Table

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

    Home > Trends in Commercial Buildings > Energy Consumption - Part 1> Site Energy Consumption Tables Table 1. Total site energy consumption, relative standard errors, and 95%...

  16. 2008 Annual Report

    SciTech Connect (OSTI)

    none,

    2008-01-01

    This annual report includes: a brief overview of Western; FY 2008 operational highlights; and financial data.

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  18. 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.

  19. Two techniques for forecasting clear air turbulence 

    E-Print Network [OSTI]

    Arbeiter, Randolph George

    1977-01-01

    result in only mild annoyance or discomfort (air sickness) to crew and passengers. As it becomes moderate, difficulty may be experienced in moving about inside the airplane and the crew may momentarily lose control. Severe CAT can result in injury... successfully used by the Air Force Clobal Heather Central (Barnett, 1970) for oper" tional forecasting on a day-to-day basis. Furthermore, its usefulness 1' or supersonic aircraft in the stratosphere v;as successfully demonstrated by Scoggins et H. (1975...

  20. 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.

  1. Table of tables: A database design tool for SYBASE

    SciTech Connect (OSTI)

    Brown, B.C.; Coulter, K.; Glass, H.D.; Glosson, R.; Hanft, R.W.; Harding, D.J.; Trombly-Freytag, K.; Walbridge, D.G.C.; Wallis, D.B. ); Allen, M.E. )

    1991-01-04

    The Table of Tables' application system captures in a set of SYBASE tables the basic design specification for a database schema. Specification of tables, columns (including the related defaults and rules for the stored values) and keys is provided. The feature which makes this application specifically useful for SYBASE is the ability to automatically generate SYBASE triggers. A description field is provided for each database object. Based on the data stored, SQL scripts for creating complete schema including the tables, their defaults and rules, their indexes, and their SYBASE triggers, are written by TOT. Insert, update and delete triggers are generated from TOT to guarantee integrity of data relations when tables are connected by single column foreign keys. The application is written in SYBASE's APT-SQL and includes a forms based data entry system. Using the features of TOT we can create a complete database schema for which the data integrity specified by our design is guaranteed by the SYBASE triggers generated by TOT. 3 refs.

  2. Solar Wind Forecasting with Coronal Holes

    E-Print Network [OSTI]

    S. Robbins; C. J. Henney; J. W. Harvey

    2007-01-09

    An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. Health Care Buildings: Consumption Tables

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

    Consumption Tables Sum of Major Fuel Consumption by Size and Type of Health Care Building Total (trillion Btu) per Building (million Btu) per Square Foot (thousand Btu) Dollars per...

  8. Table of Contents Deschutes Subbasin Plan

    E-Print Network [OSTI]

    Table of Contents Deschutes Subbasin Plan Table of Contents Executive Summary 1. Purpose and Scope.1. Physical, Natural and Human Landscape ................................................2.1 2.2. Water, Table of Contents Page 1 #12;Table of Contents 7. Limiting Factors and Conditions .........

  9. Regulations and Basic Information Table of Contents

    E-Print Network [OSTI]

    Liskiewicz, Maciej

    Regulations and Basic Information Table of Contents Safe and Effective Use.) for Various Quantities of Water

  10. TABLE OF CONTENTS Content Page

    E-Print Network [OSTI]

    Li, Jiuyong "John"

    #12;TABLE OF CONTENTS Content Page Version 5.1 iii September 2012 Contents 1 INTRODUCTION 1-1 1;TABLE OF CONTENTS Content Page Version 5.1 iv September 2012 3 PLANNING AND DESIGN GUIDELINES 3-1 3 Noise 3-25 3.3.15 Optimise Light 3-25 3.3.16 Save Water 3-25 3.3.17 Minimise Waste 3-25 3.4 Green Star

  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. Radioactive decay data tables

    SciTech Connect (OSTI)

    Kocher, D.C.

    1981-01-01

    The estimation of radiation dose to man from either external or internal exposure to radionuclides requires a knowledge of the energies and intensities of the atomic and nuclear radiations emitted during the radioactive decay process. The availability of evaluated decay data for the large number of radionuclides of interest is thus of fundamental importance for radiation dosimetry. This handbook contains a compilation of decay data for approximately 500 radionuclides. These data constitute an evaluated data file constructed for use in the radiological assessment activities of the Technology Assessments Section of the Health and Safety Research Division at Oak Ridge National Laboratory. The radionuclides selected for this handbook include those occurring naturally in the environment, those of potential importance in routine or accidental releases from the nuclear fuel cycle, those of current interest in nuclear medicine and fusion reactor technology, and some of those of interest to Committee 2 of the International Commission on Radiological Protection for the estimation of annual limits on intake via inhalation and ingestion for occupationally exposed individuals.

  13. The Commission Forecast 1992 Report: Important Resource Planning Issues 

    E-Print Network [OSTI]

    Adib, P.

    1992-01-01

    FORECAST 1992 REPORT: IMPORTANT RESOURCE PLANNING ISSUES PARVIZ ADIB MANAGER, ECONOMIC ANALYSIS SECTION ELECTRIC DIVISION PUBLIC UTILITY COMMISSION OF TEXAS ABSTRACT There is a general agreement among experts in the electric utility industry... there are many important issues in the preparation of a utility's electric resource plan, the Commission staff will address a few important ones in the next Commission Forecast Report (Forecast '92). In particular, the Commission staff will insure...

  14. 2008 Annual Report MISSION STATEMENT

    E-Print Network [OSTI]

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Forecasting the Fight Against Famine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Understanding the "Body Electric" to Better Fight Disease. . . . . . . . . . . . . . 31 33

  15. 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.

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

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01

    function. The forecasts of oil, coal and gas prices as wellforecasts for natural gas consumption, electricity sales, coal and electricity prices,

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

    E-Print Network [OSTI]

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

    2011-01-01

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

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

    E-Print Network [OSTI]

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

    2005-01-01

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

  19. Electric Grid - Forecasting system licensed | ornl.gov

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

    Electric Grid - Forecasting system licensed Location Based Technologies has signed an agreement to integrate and market an Oak Ridge National Laboratory technology that provides...

  20. Ramping Effect on Forecast Use: Integrated Ramping (Presentation...

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

    the shift from ramping. * the benefits - better use of forecast values (load or net load) - reduce the amount of variability that the regulation reserve must accommodate...

  1. 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.

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

    E-Print Network [OSTI]

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

    2006-01-01

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

  3. Nuclear Theory Helps Forecast Neutron Star Temperatures | U.S...

    Office of Science (SC) Website

    Nuclear Theory Helps Forecast Neutron Star Temperatures Nuclear Physics (NP) NP Home About Research Facilities Science Highlights Benefits of NP Funding Opportunities Nuclear...

  4. The Exvessel Price table is an index of 1982 (the base year). That number was then divided changes in the relative dockside value of fish and by the 1982 value to obtain the final index

    E-Print Network [OSTI]

    PRICES The Exvessel Price table is an index of 1982 (the base year). That number was then divided sold by fishing vessels. The table indexes the average annual exvessel value (price per pound) received for each species or group to the average price per pound received for the same species or group in the base

  5. 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.

  6. 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.

  7. 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.

  8. Natural gas annual 1992: Volume 1

    SciTech Connect (OSTI)

    Not Available

    1993-11-22

    This document provides information on the supply and disposition of natural gas to a wide audience including industry, consumers, Federal and State agencies, and education institutions. The 1992 data are presented in a sequence that follows natural gas (including supplemental supplies) from its production top its end use. Tables summarizing natural gas supply and disposition from 1988 to 1992 are given for each Census Division and each State. Annual historical data are shown at the national level. Volume 2 of this report presents State-level historical data.

  9. FY 1996 solid waste integrated life-cycle forecast characteristics summary. Volumes 1 and 2

    SciTech Connect (OSTI)

    Templeton, K.J.

    1996-05-23

    For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the physical waste forms, hazardous waste constituents, and radionuclides of the waste expected to be shipped to the CWC from 1996 through the remaining life cycle of the Hanford Site (assumed to extend to 2070). In previous years, forecast data has been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to two previous reports: the more detailed report on waste volumes, WHC-EP-0900, FY1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary and the report on expected containers, WHC-EP-0903, FY1996 Solid Waste Integrated Life-Cycle Forecast Container Summary. All three documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on two main characteristics: the physical waste forms and hazardous waste constituents of low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major generators for each waste category and waste characteristic are also discussed. The characteristics of low-level waste (LLW) are described in Appendix A. In addition, information on radionuclides present in the waste is provided in Appendix B. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste is expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters. The range is primarily due to uncertainties associated with the Tank Waste Remediation System (TWRS) program, including uncertainties regarding retrieval of long-length equipment, scheduling, and tank retrieval technologies.

  10. EIA lowers forecast for summer gasoline prices

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural GasNatural GasEIA lowers forecast for summer gasoline prices

  11. Motivation Methods Model configuration Results Forecasting Summary & Outlook Retrieving direct and diffuse radiation with the

    E-Print Network [OSTI]

    Heinemann, Detlev

    Motivation Methods Model configuration Results Forecasting Summary & Outlook 1/ 14 Retrieving. 17, 2015 #12;Motivation Methods Model configuration Results Forecasting Summary & Outlook 2/ 14 Motivation Sky Imager based shortest-term solar irradiance forecasts for local solar energy applications

  12. ECMWF analyses and forecasts of 500 mb synoptic-scale activity during wintertime blocking 

    E-Print Network [OSTI]

    Matson, David Michael

    1993-01-01

    An observational study of 500 mb atmospheric blocking is conducted based on an European Centre for Medium-Range Weather Forecasts (ECMWF) wintertime analysis and forecast dataset during dynamic extended range forecasting ...

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

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

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

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

    revisions to the EIA’s natural gas price forecasts in AEOon the AEO 2005 natural gas price forecasts will likely onceComparison of AEO 2005 Natural Gas Price Forecast to NYMEX

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

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

  18. HOW ACCURATE ARE WEATHER MODELS IN ASSISTING AVALANCHE FORECASTERS? M. Schirmer, B. Jamieson

    E-Print Network [OSTI]

    Jamieson, Bruce

    HOW ACCURATE ARE WEATHER MODELS IN ASSISTING AVALANCHE FORECASTERS? M. Schirmer, B. Jamieson and decision makers strongly rely on Numerical Weather Prediction (NWP) models, for example on the forecasted on forecasted precipitation. KEYWORDS: Numerical weather prediction models, validation, precipitation 1

  19. ENERGY & ENVIRONMENT DIVISION ANNUAL REPORT 1979

    E-Print Network [OSTI]

    Cairns, E.J.

    2010-01-01

    of 25 years energy demand forecasts, and for a preliminaryIn addition, energy demand forecasts will be revised to takedemand forecasts as well as severly limiting their utility in assessing impacts of energy

  20. Annual Report Outline (IDIQ Attachment J-10) | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based Fuels Research at 1 Table ofDepartmentEnergy Annual1 Annual1Report

  1. Annual Report 2001 Annual Report 2001

    E-Print Network [OSTI]

    Habib, Ayman

    The Arctic Institute of North America Annual Report 2001 The Arctic Institute of North America Annual Report 2001 #12;2000 Board of Directors · James Raffan,Seeley's Bay,Ontario (Chair until September 2001) · Murray B. Todd, Calgary,Alberta (Chair as of September 2001) · Luc Bouthillier,Québec City

  2. Library Annual Report Library Annual Report

    E-Print Network [OSTI]

    Tobar, Michael

    Library Annual Report 2007 Library Annual Report 2007 #12;www.library.uwa.edu.au Our mission: By delivering excellent information resources and services the Library is integral to the University's mission of advancing, transmitting and sustaining knowledge. Our vision: The Library will continue to be at the heart

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

    E-Print Network [OSTI]

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

  4. Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence

    E-Print Network [OSTI]

    Lawrence, Ramon

    Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence Department of Computer Science on the application of neural networks in forecasting stock market prices. With their ability to discover patterns in nonlinear and chaotic systems, neural networks offer the ability to predict market directions more

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Impact of PV forecasts uncertainty in batteries management in microgrids Andrea Michiorri Arthur-based battery schedule optimisation in microgrids in presence of network constraints. We examine a specific case production forecast algorithm is used in combination with a battery schedule optimisation algorithm. The size

  6. Forecasting Hot Water Consumption in Dwellings Using Artifitial Neural Networks

    E-Print Network [OSTI]

    MacDonald, Mark

    electricity consumption in time. This paper investigates the ability on Artificial Neural Networks to predict shift electric energy. Keywords--Hot Water Consumption; Forecasting; Artifitial Neural Networks; SmartForecasting Hot Water Consumption in Dwellings Using Artifitial Neural Networks Linas Gelazanskas

  7. Draft for Public Comment Appendix A. Demand Forecast

    E-Print Network [OSTI]

    in the forecast of electricity consumption for those years has been less than one half of a percent. Figure A-1 forecast of electricity demand is a required component of the Council's Northwest Regional Conservation and Electric Power Plan.1 Understanding growth in electricity demand is, of course, crucial to determining

  8. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    of transportation fuel and crude oil import requirements. The transportation energy demand forecasts make. The transportation fuel and crude oil import requirement assessments build on assumptions about California crude oil forecasts, transportation energy, gasoline, diesel, jet fuel, crude oil production, fuel imports, crude oil

  9. A Deep Hybrid Model for Weather Forecasting Aditya Grover

    E-Print Network [OSTI]

    Horvitz, Eric

    @microsoft.com ABSTRACT Weather forecasting is a canonical predictive challenge that has depended primarily on model-based methods. We ex- plore new directions with forecasting weather as a data- intensive challenge that involves the joint statistics of a set of weather-related vari- ables. We show how the base model can be enhanced

  10. Hydrological Forecasting Improvements Primary Investigator: Thomas Croley -NOAA GLERL (Emeritus)

    E-Print Network [OSTI]

    multiple data streams in a near-real-time manner and incorporate them into the AHPS data base, run for matching weather forecasts with historical data, and prepare extensive forecasts of hydrology probabilities maximum use of all available information and be based on efficient and true hydrological process models

  11. DEEP COMPREHENSION, GENERATION AND TRANSLATION OF WEATHER FORECASTS (WEATHRA)

    E-Print Network [OSTI]

    in a data base and graphic representation with tile standard meteorological icons on a map, e.g. iconsDEEP COMPREHENSION, GENERATION AND TRANSLATION OF WEATHER FORECASTS (WEATHRA) by BENGT SIGURD, Sweden E-mail: linglund@gemini.ldc.lu.se FAX:46-(0)46 104210 Introduction and abstract Weather forecasts

  12. Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    markets could aid in the design of appropriate price forecasting tools for such markets. Scenario1 Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets Qun Zhou, restructured wholesale power markets, scenario generation, ARMA model, moment-matching method I. INTRODUCTION

  13. Probabilistic forecasting of solar flares from vector magnetogram data

    E-Print Network [OSTI]

    Barnes, Graham

    Probabilistic forecasting of solar flares from vector magnetogram data G. Barnes,1 K. D. Leka,1 E to solar flare forecasting, adapted to provide the probability that a measurement belongs to either group, the groups in this case being solar active regions which produced a flare within 24 hours and those

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

    E-Print Network [OSTI]

    Singhal, Gaurav

    2012-10-19

    Real-time wave forecasts are critical to a variety of coastal and offshore opera- tions. NOAA’s global wave forecasts, at present, do not extend into many coastal regions of interest. Even after more than two decades of the historical Exxon Valdez...

  15. Human Trajectory Forecasting In Indoor Environments Using Geometric Context

    E-Print Network [OSTI]

    . In addressing this problem, we have built a model to estimate the occupancy behavior of humans based enhancement in the accuracy of trajectory forecasting by incorporating the occupancy behavior model. Keywords Trajectory forecasting, human occupancy behavior, 3D ge- ometric context 1. INTRODUCTION Given a human

  16. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    . Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data Office. Andrea Gough ran the summary energy model and supervised data preparation. Glen Sharp prepared models. Both the staff revised energy consumption and peak forecasts are slightly higher than

  17. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center

    E-Print Network [OSTI]

    Washington at Seattle, University of

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

  18. MAINTENANCE, UPGRADE AND VERIFICATION OF OPERATIONAL FORECASTS OF

    E-Print Network [OSTI]

    MAINTENANCE, UPGRADE AND VERIFICATION OF OPERATIONAL FORECASTS OF CLOUD COVER AND WATER VAPOUR Purchase Order 58311/ODG/99/8362/GWI/LET #12;i PREFACE Starting in August 1998, operational forecasts satellite imagery from the Co-operative Institute for Research in the Atmosphere (CIRA) and upper

  19. Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids

    E-Print Network [OSTI]

    Hwang, Kai

    1 Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids Yogesh Simmhan. One of the characteristic applications of Smart Grids is demand response optimization (DR). The goal of DR is to use the power consumption time series data to reliable forecast the future consumption

  20. THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD

    E-Print Network [OSTI]

    THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD ENERGY SERVICES by Steven Groves BASc of Research Project: The Desire to Acquire: Forecasting the Evolution of Household Energy Services Report No, and gasoline. A fixed effects panel model was used to examine the relationship of demand for energy

  1. Airplanes Aloft as a Sensor Network for Wind Forecasting

    E-Print Network [OSTI]

    Horvitz, Eric

    Airplanes Aloft as a Sensor Network for Wind Forecasting Ashish Kapoor, Zachary Horvitz, Spencer for observing weather phenomena at a continental scale. We focus specifically on the problem of wind forecasting with the sensed winds. The experiments show the promise of using airplane in flight as a large-scale sensor

  2. Classification of Commodity Price Forecast With Random Forests and Bayesian

    E-Print Network [OSTI]

    Freitas, Nando de

    on the sentiment of price39 forecasts and reports for commodities such as gold, natural gas or most commonly oil or natural gas can impact everything from the21 critical business decisions made within nationsClassification of Commodity Price Forecast Sentiment With Random Forests and Bayesian Optimization

  3. Microsoft Word - table_15.doc

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential2, 2014 MEMORANDUMProvedFeet) U.S. Energy8 Table0 Table

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

    114 Solar Irradiance And Power Output Variabilityand L. Bangyin. Online 24-h solar power forecasting based onNielsen. Online short-term solar power forecasting. Solar

  5. A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of numerical weather prediction solar irradiance forecasts numerical weather prediction model for solar irradiance weather prediction for intra?day solar  forecasting in the 

  6. Building Electricity Load Forecasting via Stacking Ensemble Learning Method with Moving Horizon Optimization

    E-Print Network [OSTI]

    Burger, Eric M.; Moura, Scott J.

    2015-01-01

    K. W. Yau, “Predicting electricity energy con- sumption: Afor building-level electricity load forecasts,” Energy andannealing algorithms in electricity load forecasting,”

  7. Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts ............................................................................................................................ 5 U.S. Natural Gas Commodity Prices

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

    SciTech Connect (OSTI)

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

    2014-10-27

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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01

    Comparison of AEO 2009 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01

    Comparison of AEO 2008 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01

    Comparison of AEO 2006 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

    Comparison of AEO 2007 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

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

  14. ANNUAL REPORT RESEARCH PROGRAM

    E-Print Network [OSTI]

    Rock, Chris

    ;#12;i TABLE OF CONTENTS Page General Summary...........................................8 Water Resource Economics Initiative Economic Value of Soil Water Enhancement from Brush Removal on the Perdenales Water Shed

  15. 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.

  16. 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.

  17. Table Of Contents Section: Page

    E-Print Network [OSTI]

    US Army Corps of Engineers

    EM 385-1-1 XX Sep 13 i Section 2 SANITATION Table Of Contents Section: Page 02.A General Water......................................................... 2-1 02.D Non-Potable Water and openings. 02.C DRINKING WATER #12;EM 385-1-1 XX Sep 13 2-2 02.C.01 An adequate supply of potable water

  18. THINKING THESIS Table of Contents

    E-Print Network [OSTI]

    Massachusetts at Lowell, University of

    THINKING THESIS GUIDEBOOK #12;#12;Table of Contents Part One: Getting Started 1. What the Honors aides 5. Final Turn in of the Thesis Appendix I. Sample Title Page II. Honors Mentor Declaration Form on to better things. Theodore Roosevelt #12;#12;Honors College Thesis Requirements There are several forms

  19. OUTLOOK BYLAWS Table of Contents

    E-Print Network [OSTI]

    OUTLOOK BYLAWS Table of Contents Article I - Legal Authority to Operate Article II - Scope-in-Chief and Responsible Director Article VIII - Funding of Outlook Article IX - Unused Funds Article X - Composition The publication of Outlook is authorized under a license granted to AUB by decision No. 113 issued by the Lebanese

  20. Table of Contents INTRODUCTION 2

    E-Print Network [OSTI]

    O'Mahony, Donal E.

    #12;1 Table of Contents INTRODUCTION 2 SECTION ONE: PRINCIPLES OF GOOD PRACTICE 4 SECTION TWO, it offers a practical guide to staff and volunteers who work with children by outlining a number of fundamental principles of good practice, highlighting the key elements of each one and discussing the issues

  1. Student Handbook TABLE OF CONTENTS

    E-Print Network [OSTI]

    Horowitz, Leah S.

    1 Student Handbook 2014-2015 TABLE OF CONTENTS Comprehensive Nondiscrimination Statement 3 Sex Student Handbook Comprehensive Nondiscrimination Policy The provisions of this handbook of the services, programs or activities described in this handbook. The most up-to-date handbook can be found

  2. HOUSING POLICY Table of Contents

    E-Print Network [OSTI]

    HOUSING POLICY Table of Contents Housing Policy Housing Rules and Regulations Appendix I contact: policies@aub.edu.lb. Last updated on: August 14, 2014 #12;HOUSING POLICY Section 1 - Policy Section 2 - Housing Purchase Plan (HPP) Section 3 - Procedure for the Implementation of the Housing

  3. TABLE OF CONTENTS: Building Executive Definition.......................................................................3

    E-Print Network [OSTI]

    Capogna, Luca

    #12;TABLE OF CONTENTS: Building Executive Definition.......................................................................3 Building Executives Areas of Responsibilities ...................................................................................5 Building Safety and Security Issues

  4. Table Contents Page i 2013 Nonresidential Compliance Manual January 2014

    E-Print Network [OSTI]

    Table Contents Page i 2013 Nonresidential Compliance Manual January 2014 Table of Contents........................................................................5 Table F-1 Small Water Heater Test Methods ..................................................................................6 Table F-2 Large Water Heater Test Methods

  5. 1999 Commercial Building Characteristics--Detailed Tables--Census...

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

    Census Region > Detailed Tables-Census Region Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Census Region Table B3. Census Region, Number of Buildings and Floorspace...

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

    SciTech Connect (OSTI)

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

    2011-12-06

    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.

  7. Science and Engineering of an Operational Tsunami Forecasting System

    SciTech Connect (OSTI)

    Gonzalez, Frank

    2009-04-06

    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.

  8. 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.

  9. CloudCast: Cloud Computing for Short-term Mobile Weather Forecasts

    E-Print Network [OSTI]

    Shenoy, Prashant

    of Massachusetts Amherst Abstract--Since today's weather forecasts only cover large regions every few hours algorithm for generating accurate short-term weather forecasts. We study CloudCast's design space, which One useful application is mobile weather forecasting, which provides hour-to-hour forecasts

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

    E-Print Network [OSTI]

    Feinberg, Eugene A.

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

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

    Solar irradiance data . . . . . . . . . . . . .Irradiance . . . . . . . . . . . . . . . . . . . . . . . . . . .4 Forecasting Solar Irradiance With GOES-West Satellite

  12. Ensemble Kalman Filter Data Assimilation in a 1D Numerical Model Used for Fog Forecasting

    E-Print Network [OSTI]

    Ensemble Kalman Filter Data Assimilation in a 1D Numerical Model Used for Fog Forecasting SAMUEL RE, a need exists for accurate and updated fog and low-cloud forecasts. Couche Brouillard Eau Liquide (COBEL for the very short-term forecast of fog and low clouds. This forecast system assimilates local observations

  13. Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction

    E-Print Network [OSTI]

    Raftery, Adrian

    Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction LE proposes an effective bias correction technique for wind direction forecasts from numerical weather forecasts. These techniques are applied to 48-h forecasts of surface wind direction over the Pacific

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

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

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

    E-Print Network [OSTI]

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

  17. Improved forecasts of extreme weather events by future space borne Doppler wind lidar

    E-Print Network [OSTI]

    Marseille, Gert-Jan

    of forecast failures, in particular those with large socio economic impact. Forecast failures of high- impact on their ability to improve meteorological analyses and subsequently reduce the probability of forecast failures true atmospheric state. This was generated by the European Centre for Medium-Range Weather Forecasts

  18. Laboratory Directed Research and Development Program FY 2008 Annual Report

    E-Print Network [OSTI]

    editor, Todd C Hansen

    2009-01-01

    to study of energy demand forecasts for China, learningthat all major forecasts of energy demand after 2002 for

  19. Appears in Proceedings of the USENIX Annual Technical Conference, June 2004. Handling Churn in a DHT

    E-Print Network [OSTI]

    Kubiatowicz, John D.

    Appears in Proceedings of the USENIX Annual Technical Conference, June 2004. Handling Churn This paper addresses the problem of churn--the continu- ous process of node arrival and departure--in distributed hash tables (DHTs). We argue that DHTs should perform lookups quickly and consistently under churn

  20. Historical Natural Gas Annual

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

    Annual . 1996 Published October 1997 1997 Published October 1998 1998 Published October 1999 1999 Published October 2000 2000 Published December 2001...

  1. OPSI Annual Meeting

    Broader source: Energy.gov [DOE]

    The Organization of PJM States, Inc. (OPSI) is hosting its annual meeting in Chicago, IL, on October 13-14, 2014.

  2. EMSL 2009 Annual Report

    SciTech Connect (OSTI)

    Showalter, Mary Ann; Kathmann, Loel E.; Manke, Kristin L.; Wiley, Julie G.; Reed, Jennifer R.

    2010-02-26

    The EMSL 2009 Annual Report describes the science conducted at EMSL during 2009 as well as outreach activities and awards and honors received by users and staff.

  3. SPEER Third Annual Summit

    Broader source: Energy.gov [DOE]

    The South-Central Partnership for Energy Efficiency as a Resource (SPEER) is hosting their 3rd Annual Summit in Dallas, Texas.

  4. Required Annual Notices

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

    Annual Notices The Women's Health and Cancer Rights Act of 1998 (WHCRA) The medical programs sponsored by LANS will not restrict benefits if you or your dependent receives...

  5. Required Annual Notices

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

    Required Annual Notices The Women's Health and Cancer Rights Act of 1998 (WHCRA) The medical programs sponsored by LANS will not restrict benefits if you or your dependent...

  6. 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,...

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

    E-Print Network [OSTI]

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

    2015-03-29

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

  8. 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.

  9. Forecasting and Risk Analysis in Supply Chain Management

    E-Print Network [OSTI]

    Hilmola, Olli-Pekka

    Forecasting is an underestimated field of research in supply chain management. Recently advanced methods are coming into use. Initial results are encouraging, but often require changes in policies for collaboration and ...

  10. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

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

  11. PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022

    E-Print Network [OSTI]

    low electricity and natural gas rates, and relatively low efficiency program and self Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert Oglesby Executive Director DISCLAIMER Staff for electric vehicles. #12;ii #12;iii ABSTRACT The Preliminary California Energy Demand Forecast 2012

  12. Optimally Controlling Hybrid Electric Vehicles using Path Forecasting

    E-Print Network [OSTI]

    Kolmanovsky, Ilya V.

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

  13. Multidimensional approaches to performance evaluation of competing forecasting models 

    E-Print Network [OSTI]

    Xu, Bing

    2009-01-01

    The purpose of my research is to contribute to the field of forecasting from a methodological perspective as well as to the field of crude oil as an application area to test the performance of my methodological contributions ...

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

    E-Print Network [OSTI]

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

    2015-01-01

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

  15. Optimally controlling hybrid electric vehicles using path forecasting

    E-Print Network [OSTI]

    Katsargyri, Georgia-Evangelina

    2008-01-01

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

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

    E-Print Network [OSTI]

    Ham, Joy L

    2002-01-01

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

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

    E-Print Network [OSTI]

    Simmons, Joshua T. (Joshua Thomas)

    2007-01-01

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

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

    E-Print Network [OSTI]

    Adut, Davit

    2004-09-30

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

  19. Radiation fog forecasting using a 1-dimensional model 

    E-Print Network [OSTI]

    Peyraud, Lionel

    2001-01-01

    weather patterns known to be favorable for producing fog and once it has formed, to state that it will persist unless the pattern changes. Unfortunately, while such methods have shown some success, many times they have led weather forecasters astray...

  20. Pressure Normalization of Production Rates Improves Forecasting Results 

    E-Print Network [OSTI]

    Lacayo Ortiz, Juan Manuel

    2013-08-07

    reliable production forecasting technique suited to interpret unconventional wells in specific situations such as unstable operating conditions, limited availability of production data (short production history) and high-pressure, rate-restricted wells...

  1. Forecasting Stock Market Volatility: Evidence from Fourteen Countries. 

    E-Print Network [OSTI]

    Balaban, Ercan; Bayar, Asli; Faff, Robert

    2002-01-01

    This paper evaluates the out-of-sample forecasting accuracy of eleven models for weekly and monthly volatility in fourteen stock markets. Volatility is defined as within-week (within-month) standard deviation of continuously ...

  2. Adaptive sampling and forecasting with mobile sensor networks

    E-Print Network [OSTI]

    Choi, Han-Lim

    2009-01-01

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

  3. FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007

    E-Print Network [OSTI]

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

  4. Annual Performance Report FY 2004 Annual Performance Plan FY...

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

    I am pleased to present the Office of Inspector General's (OIG's) combined Fiscal Year 2004 Annual Performance Report and Fiscal Year 2005 Annual Performance Plan. In Fiscal Year...

  5. Forecasting the probability of forest fires in Northeast Texas 

    E-Print Network [OSTI]

    Wadleigh, Stuart Allen

    1972-01-01

    FORECASTING THE PROBABILITY OF FOREST FIRES IN NORTHEAST TEXAS A Thesis by STUART ALLEN WADLEIGH Submit ted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE... December 1972 Major Subject: Meteorology FORECASTING THE PROBABILITY OF FOREST FIRES IN NORTHEAST TEXAS A Thesis by STUART ALLEN WADLEIGH Approved as to style and content by: ( irman of ee) (Head of Depar nt) (Member) (Member) December 1972 c...

  6. Forecasting potential project risks through leading indicators to project outcome 

    E-Print Network [OSTI]

    Choi, Ji Won

    2007-09-17

    for the degree of MASTER OF SCIENCE May 2007 Major Subject: Civil Engineering FORECASTING POTENTIAL PROJECT RISKS THROUGH LEADING INDICATORS TO PROJECT OUTCOME A Thesis by JI WON CHOI... Guikema Head of Department, David Rosowsky May 2007 Major Subject: Civil Engineering iii ABSTRACT Forecasting Potential Project Risks through Leading Indicators to Project Outcome. (May 2007) Ji Won Choi, B.S., Han-Yang University...

  7. Tenth Annual Report: 2007State of Louisiana

    E-Print Network [OSTI]

    -filled Positions 2007 - Pie chart & Table ________________________________________________________14 Hospital

  8. Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use with the National Digital Forecast Database

    E-Print Network [OSTI]

    Douches, David S.

    Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use with the National Digital Forecast Database Kathleen Baker a, , Paul Roehsner a , Thomas Lake b , Douglas Rivet

  9. FITBIR Annual Report August 1, 2013

    E-Print Network [OSTI]

    .........................................................................................................9 NINDS Workflow for FITBIR for Newly Funded NINDS Grantees.............................................9 Table 2. NINDS grantees........................................................................................................12 Table 3. DOD grantees

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

    E-Print Network [OSTI]

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

    2000-01-01

    Comparisons are made of energy forecasts using results from the Industrial module of the National Energy Modeling System (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy Modeling System (ITEMS), a model...

  11. 1997 Housing Characteristics Tables Home Office Equipment Tables

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1 Table 1.10 CoolingNotes &* j o n p o J d VPercent

  12. Forest Research Annual Report

    E-Print Network [OSTI]

    Forest Research Annual Report and Accounts 2005­2006 The research agency of the Forestry Commission #12;Forest Research Annual Report and Accounts I 2005­2006 Together with the Comptroller and Auditor to be printed 24 July 2006 HC 1407 The research agency of the Forestry Commission Edinburgh: The Stationery

  13. Annual Energy Review, 2008

    SciTech Connect (OSTI)

    2009-06-01

    The Annual Energy Review (AER) is the Energy Information Administration's (EIA) primary report of annual historical energy statistics. For many series, data begin with the year 1949. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international energy; financial and environment indicators; and data unit conversions.

  14. Value of Probabilistic Weather Forecasts: Assessment by Real-Time Optimization of Irrigation Scheduling

    SciTech Connect (OSTI)

    Cai, Ximing; Hejazi, Mohamad I.; Wang, Dingbao

    2011-09-29

    This paper presents a modeling framework for real-time decision support for irrigation scheduling using the National Oceanic and Atmospheric Administration's (NOAA's) probabilistic rainfall forecasts. The forecasts and their probability distributions are incorporated into a simulation-optimization modeling framework. In this study, modeling irrigation is determined by a stochastic optimization program based on the simulated soil moisture and crop water-stress status and the forecasted rainfall for the next 1-7 days. The modeling framework is applied to irrigated corn in Mason County, Illinois. It is found that there is ample potential to improve current farmers practices by simply using the proposed simulation-optimization framework, which uses the present soil moisture and crop evapotranspiration information even without any forecasts. It is found that the values of the forecasts vary across dry, normal, and wet years. More significant economic gains are found in normal and wet years than in dry years under the various forecast horizons. To mitigate drought effect on crop yield through irrigation, medium- or long-term climate predictions likely play a more important role than short-term forecasts. NOAA's imperfect 1-week forecast is still valuable in terms of both profit gain and water saving. Compared with the no-rain forecast case, the short-term imperfect forecasts could lead to additional 2.4-8.5% gain in profit and 11.0-26.9% water saving. However, the performance of the imperfect forecast is only slightly better than the ensemble weather forecast based on historical data and slightly inferior to the perfect forecast. It seems that the 1-week forecast horizon is too limited to evaluate the role of the various forecast scenarios for irrigation scheduling, which is actually a seasonal decision issue. For irrigation scheduling, both the forecast quality and the length of forecast time horizon matter. Thus, longer forecasts might be necessary to evaluate the role of forecasts for irrigation scheduling in a more effective way.

  15. Results from the Second Forum on the Future Role of the Human in the Forecast Process. Part II: Cognitive Psychological Aspects of Expert Weather Forecasters

    E-Print Network [OSTI]

    Schultz, David

    : Cognitive Psychological Aspects of Expert Weather Forecasters NEIL A. STUART* NOAA/National Weather Service of Applied Research Associates, Fairborn, Ohio In Preparation for Submission to Forecasters Forum, Weather and Forecasting 30 June 2006 Corresponding author address: Neil A. Stuart, National Weather Service, 10009 General

  16. 18 Bureau of Meteorology Annual Report 201314 Hazards, warnings and forecasts

    E-Print Network [OSTI]

    Greenslade, Diana

    and tides, flood and short-term streamflow and space weather. The portfolio works closely with State of Foreign Affairs and Trade. Key stakeholders and users include: · the general public and local communities; · industry sectors such as aviation, finance and insurance, transport, mining and energy, marine

  17. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT OFEnergy-8,nTWISTUNITED STATES

  18. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT OFEnergy-8,nTWISTUNITED STATES4

  19. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT OFEnergy-8,nTWISTUNITED STATES48

  20. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT OFEnergy-8,nTWISTUNITED STATES4838

  1. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT OFEnergy-8,nTWISTUNITED

  2. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT OFEnergy-8,nTWISTUNITED5.4 from

  3. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT OFEnergy-8,nTWISTUNITED5.4 from6

  4. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT OFEnergy-8,nTWISTUNITED5.4

  5. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT OFEnergy-8,nTWISTUNITED5.47AJ02):

  6. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT

  7. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT0AJ01): Some electromagnetic

  8. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT0AJ01): Some electromagnetic1AJ01):

  9. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT0AJ01): Some

  10. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT0AJ01): Some2012KE01): Some

  11. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT0AJ01): Some2012KE01): Some5TI07):

  12. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT0AJ01): Some2012KE01):

  13. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With LivermoreSustainableDEPARTMENT0AJ01): Some2012KE01):2002TI10):

  14. Environmental regulatory update table, July 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-08-01

    This Environmental Regulatory Update Table (July 1991) provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  15. Environmental Regulatory Update Table, December 1989

    SciTech Connect (OSTI)

    Houlbert, L.M.; Langston, M.E. ); Nikbakht, A.; Salk, M.S. )

    1990-01-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  16. Environmental Regulatory Update Table, December 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1992-01-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  17. Environmental Regulatory Update Table, September 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-10-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  18. Environmental Regulatory Update Table, November 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-12-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  19. Environmental Regulatory Update Table, October 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-11-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  20. Environmental Regulatory Update Table, August 1991

    SciTech Connect (OSTI)

    Houlberg, L.M., Hawkins, G.T.; Salk, M.S.

    1991-09-01

    This Environmental Regulatory Update Table (August 1991) provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.