Sample records for forecast period eia

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

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01T23:59:59.000Z

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

  2. Recently released EIA report presents international forecasting data

    SciTech Connect (OSTI)

    NONE

    1995-05-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

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

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01T23:59:59.000Z

    the Energy Information Administration’s (EIA) web site. Wein the past, compared the EIA’s reference case long-termgas price forecasts from the EIA. As such, we have concluded

  6. Report Period: EIA ID NUMBER: Appendix A: Mailing Address: Appendix B:

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS FRecord U.S.

  7. Report Period: EIA ID NUMBER: Instructions: (e.g., Street Address, Bldg, Floor, Suite)

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS FRecord U.S.Report

  8. EIA revises up forecast for U.S. 2013 crude oil production by 70,000 barrels per day

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA revises up

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01T23:59:59.000Z

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

  11. EIA Publications Directory 1993

    SciTech Connect (OSTI)

    Not Available

    1994-07-18T23:59:59.000Z

    This directory contains abstracts and ordering information for EIA publications released in the above time period. The abstracts are arranged by broad subject category such as coal, petroleum, natural gas, and electric power. A comprehensive subject index, a title index, and a report number index are included. Each entry gives the title, report number, publication frequency, date, number of pages, and ordering information.

  12. Energy Links Page - EIA

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

    being provided consistent with the intended purpose of the EIA Web site. EIA does not control or guarantee the accuracy, relevance, timeliness, or completeness of this outside...

  13. EIA-912 Instructions

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

    OMB No. 1905-0175 Expiration Date: 12312017 EIA-912 WEEKLY UNDERGROUND NATURAL GAS STORAGE REPORT INSTRUCTIONS PURPOSE The Energy Information Administration (EIA) Form...

  14. Current practice and shortcomings of EIA in Lithuania

    SciTech Connect (OSTI)

    Kruopiene, Jolita, E-mail: Jolita.Kruopiene@ktu.l [Kaunas University of Technology, Institute of Environmental Engineering, K. Donelaicio str. 20-412, LT-44239 Kaunas (Lithuania); Zidoniene, Sigita, E-mail: sigitazi@gmail.co [Kaunas University of Technology, Institute of Environmental Engineering, K. Donelaicio str. 20-413, LT-Q1 44239 Kaunas (Lithuania); Dvarioniene, Jolanta, E-mail: Jolanta.dvarioniene@ktu.l [Kaunas University of Technology, Institute of Environmental Engineering, K. Donelaicio str. 20-412, LT-44239 Kaunas (Lithuania)

    2009-09-15T23:59:59.000Z

    The paper provides an overview of EIA system applications and assesses its effectiveness in Lithuania. A combination of archival research and quantitative/qualitative analysis was used to identify the main shortcomings of the EIA process in Lithuania: subjectivity in forecasting environmental effects, insufficient consideration of alternatives, politicisation of the process and incompetence of authorities involved. The research revealed that a thorough knowledge of EIA procedures and legal requirements may be a solution to these problems, especially when the stages related to forecasting the effects and evaluating the results are strictly reserved for recognized experts. The work concludes on the suggestions to involve in EIA process relevant authorities and to increase the competence of EIA practitioners.

  15. U.S. Energy Information Administration (EIA) - Topics

    Gasoline and Diesel Fuel Update (EIA)

    Mkt trends Market Trends EIA's International Energy Outlook shows world marketed energy consumption increasing strongly over the projection period, -rising by nearly 50...

  16. EIA-14,

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA revises

  17. EIA-757

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA12 (2003)

  18. EIA-800

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA121.

  19. EIA-800

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuaryEmail:FORM EIA-805

  20. EIA-820

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal2,7, MonthlyEIA ID NUMBER:

  1. EIA-820

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal2,7, MonthlyEIA ID

  2. Causal networks in EIA

    SciTech Connect (OSTI)

    Perdicoulis, Anastassios [Departamento de Engenharia Biologica e Ambiental, Universidade de Tras-os-Montes e Alto Douro, Apartado 1013, 5001-801 Vila Real (Portugal)]. E-mail: tasso@utad.pt; Glasson, John [Oxford Brookes University, Oxford Institute for Sustainable Development, School of the Built Environment, Headington Campus, Gipsy Lane, Oxford OX3 0BP (United Kingdom)]. E-mail: jglasson@brookes.ac.uk

    2006-08-15T23:59:59.000Z

    Causal networks have been used in Environmental Impact Assessment (EIA) since its early days, but they appear to have a minimal use in modern practice. This article reviews the typology of causal networks in EIA as well as in other academic and professional fields, verifies their contribution to EIA against the principles and requirements of the process, and discusses alternative scenarios for their future in EIA.

  3. EIA-906 & EIA-920, and EIA-923 Database Notes

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site. If youEIA-906 & EIA-920, and EIA-923 Database Notes"

  4. Assessment and Suggestions to Improve the Commercial Building Module of EIA-NEMS

    E-Print Network [OSTI]

    O'Neal, D. L.; Reddy, T. A.; Sucher, B.

    1996-01-01T23:59:59.000Z

    The National Energy Modeling System (NEMS) is a comprehensive, computer-based, energy-economy modeling system developed and maintained by the Department of Energy's Energy Information Administration (EIA). NEMS forecasts the national production...

  5. EIA Energy Information Administration

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

    Electric utilities that have coal conservation plans in place have increased their natural gas consumption. EIA data for September indicate that more than 126 Bcf of gas was...

  6. EIA - State Nuclear Profiles

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

    municipal solid waste, landfill gas, sludge waste, agriculture byproducts, other biomass, geothermal, solar thermal, photovoltaic energy, and wind. Sources: Form EIA-860, "Annual...

  7. EIA - State Nuclear Profiles

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

    municipal solid waste, landfill gas, sludge waste, agriculture byproducts, other biomass, geothermal, solar thermal, photovoltaic energy, and wind. Source: Form EIA-860, "Annual...

  8. EIA - State Nuclear Profiles

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

    municipal solid waste, landfill gas, sludge waste, agriculture byproducts, other biomass, geothermal, solar thermal, photovoltaic energy, and wind. Source:Form EIA-860, "Annual...

  9. DOE/EIA-0306

    Gasoline and Diesel Fuel Update (EIA)

    (EIA), Office of Energy Markets and End Use under the directorship of Wray Smith (202633-8544). General supervision of the report was provided by Kenneth A. Vagts,...

  10. 2009 Revisions EIA-914

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

    Revisions Quantifying the Change to the New Methodology EIA-914 Monthly Gas Production Report April 2010 This month the 2009 gas production estimates are revised. The previously...

  11. Sources: Energy Information Administration, Form EIA-182,

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

    Sources: Energy Information Administration, Form EIA-182, "Domestic Crude Oil First Purchase Report"; Form EIA-856, "Monthly Foreign Crude Oil Acquisition Report"; and Form EIA-14,...

  12. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    NONE

    1998-07-01T23:59:59.000Z

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

  13. EIA lowers forecast for summer gasoline prices

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,

  14. EIA Energy Information Administration

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

    of 3,190 Bcf. In a special report on underground storage in the September issue of the Natural Gas Monthly, EIA puts the nation&20;s working gas capacity at the beginning of 1997 at...

  15. EIA Energy Information Administration

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

    end-of-September estimate of 2,691 Bcf, which will appear in the September 1997 Natural Gas Monthly. According to EIA data, October injections were just over 200 Bcf in both 1995...

  16. EIA Energy Information Administration

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

    working gas in storage is about 5 percent greater than last year at the same time (2,128 vs. 2,028 Bcf). The August issue of EIA&20;s Natural Gas Monthly estimates that net injections...

  17. Transboundary EIA: Iberian experiences

    SciTech Connect (OSTI)

    Albergaria, Rita [Department of Environment and Planning, University of Aveiro, University Campus, 3810-193 Aveiro (Portugal)]. E-mail: ritaalbergaria@yahoo.com; Fidelis, Teresa [Department of Environment and Planning, University of Aveiro, University Campus, 3810-193 Aveiro (Portugal)]. E-mail: Fidelis@dao.ua.pt

    2006-10-15T23:59:59.000Z

    The 1314 km border shared by Portugal and Spain is simultaneously a conflict generator, due to joint access to common resources such as water, and a motive for transboundary cooperation in terms of development projects based on common concerns. Transboundary cooperation associated with Environment Impact Assessment (EIA) has been encouraged through the enactment of the Espoo Convention (1997). The European Union has adopted a Directive (97/11/CE Directive) under which taking transboundary impacts into consideration during EIA processes has become mandatory for member states. As a consequence, Portugal and Spain have approved related provisions. This paper aims to critically analyse the legal and procedural features of bilateral cooperation through the comparison of two case studies related to water management projects (the Sela and Alqueva dams). The paper highlights procedural weaknesses and puts forward a 'Good Practice Model' for cooperation under transboundary EIA processes. The model focuses on the ways in which EIA-based bilateral cooperation should proceed through the specification of phases and procedures for collaboration between Portugal and Spain in the identification and evaluation of transboundary impacts, as well in the public participation procedures.

  18. EIA publications directory, 1992

    SciTech Connect (OSTI)

    Not Available

    1993-06-24T23:59:59.000Z

    This directory contains abstracts and ordering information for EIA publications. The abstracts are arranged by broad subject category such as coal, petroleum, natural gas, and electric power. A comprehensive subject index, a title index, and a report number index are included. Each entry gives the title, report number, publication frequency, date, number of pages, and ordering information. Publication began with the 1979 edition.

  19. DOE/EIA-0340(98)/2 Distribution Category UC-950 Petroleum Supply

    Gasoline and Diesel Fuel Update (EIA)

    Administration (EIA) Forms EIA-810, "Monthly Refinery Report," EIA-811, "Monthly Bulk Terminal Report," EIA-812, "Monthly Product Pipeline Report," EIA-813, "Monthly Crude Oil...

  20. U.S. Energy Information Administration (EIA)

    Gasoline and Diesel Fuel Update (EIA)

    (PDF) | EIA-7A SSO Registration Guide | EIA-7A Users Guide | Frequently Asked Questions New form for collection starting January 2015: Form (includes instructions) + See more...

  1. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    4, 2000 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  2. EIA Energy Information Administration

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

    8, 2000 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  3. EIA Energy Information Administration

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

    , 2000 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  4. EIA Energy Information Administration

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

    0, 1999 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  5. EIA Energy Information Administration

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

    6, 2000 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  6. EIA Energy Information Administration

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

    3, 1999 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  7. EIA Energy Information Administration

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

    7, 2000 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  8. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    2, 1999 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  9. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    2000 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 . 3...

  10. EIA Energy Information Administration

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

    , 1999 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  11. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    3, 2000 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3...

  12. EIA Energy Information Administration

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

    4, 2000 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e P r i c e , H e n r y H u b S p o t P r i c e , a n d W e s t T e x a s I n t e r m e d i a t e C r u d e O...

  13. EIA Energy Information Administration

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

    03, 2000 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3...

  14. EIA Energy Information Administration

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

    , 1997 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 3 . 2 5 3 . 5 0 3 ....

  15. EIA Energy Information Administration

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

    5, 1997 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 3 . 2 5 3 . 5 0 3 ....

  16. EIA Energy Information Administration

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

    5, 1999 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  17. EIA Energy Information Administration

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

    7, 1998 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 Dollars Per Million...

  18. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    0, 2000 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  19. EIA Energy Information Administration

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

    6, 2000 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e P r i c e , H e n r y H u b S p o t P r i c e , a n d W e s t T e x a s I n t e r m e d i a t e C r u d e O...

  20. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    4, 1997 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 3 . 2 5 3 . 5 0 3 ....

  1. EIA Energy Information Administration

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

    6, 1999 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  2. EIA Energy Information Administration

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

    0, 2000 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3...

  3. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    31, 2000 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3...

  4. EIA Energy Information Administration

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

    8, 1999 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  5. EIA Energy Information Administration

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

    7, 1997 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 3 . 2 5 3 . 5 0 3 ....

  6. EIA Energy Information Administration

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

    8, 1997 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 3 . 2 5 3 . 5 0 3 ....

  7. EIA Energy Information Administration

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

    8, 2000 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e P r i c e , H e n r y H u b S p o t P r i c e , a n d W e s t T e x a s I n t e r m e d i a t e C r u d e O...

  8. EIA Energy Information Administration

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

    4, 1997 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 3 . 2 5 3 . 5 0...

  9. EIA Energy Information Administration

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

    3, 2000 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e P r i c e , H e n r y H u b S p o t P r i c e , a n d W e s t T e x a s I n t e r m e d i a t e C r u d e O...

  10. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    9, 1999 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 0 1 . 9 0 2 . 1 0 2 . 3 0 2 . 5 0 2 . 7 0 2 . 9 0 3 . 1 0 3 ....

  11. EIA Energy Information Administration

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

    7, 2000 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e P r i c e , H e n r y H u b S p o t P r i c e , a n d W e s t T e x a s I n t e r m e d i a t e C r u d e O...

  12. EIA Energy Information Administration

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

    0, 2000 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e P r i c e , H e n r y H u b S p o t P r i c e , a n d W e s t T e x a s I n t e r m e d i a t e C r u d e O...

  13. EIA Energy Information Administration

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

    8, 1997 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 Dollars Per Million...

  14. EIA Energy Information Administration

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

    9, 1997 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 Dollars Per Million...

  15. EIA Energy Information Administration

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

    , 2001 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e s N e a r - M o n t h C o n t r a c t S e t t l e m e n t P r i c e , H e n r y H u b S p o t P r i c e , a...

  16. EIA Energy Information Administration

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

    7, 1997 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 Dollars Per Million...

  17. EIA Energy Information Administration

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

    2, 2001 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e s N e a r - M o n t h C o n t r a c t S e t t l e m e n t P r i c e , H e n r y H u b S p o t P r i c e , a...

  18. EIA Energy Information Administration

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

    5, 2001 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e s N e a r - M o n t h C o n t r a c t S e t t l e m e n t P r i c e , H e n r y H u b S p o t P r i c e , a...

  19. EIA Energy Information Administration

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

    , 1997 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 Dollars Per Million...

  20. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    6, 2000 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e s N e a r - M o n t h C o n t r a c t S e t t l e m e n t P r i c e , H e n r y H u b S p o t P r i c e , a...

  1. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    6, 2001 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e s N e a r - M o n t h C o n t r a c t S e t t l e m e n t P r i c e , H e n r y H u b S p o t P r i c e , a...

  2. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    9, 2001 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e s N e a r - M o n t h C o n t r a c t S e t t l e m e n t P r i c e , H e n r y H u b S p o t P r i c e , a...

  3. EIA Energy Information Administration

    Gasoline and Diesel Fuel Update (EIA)

    19, 2001 http:www.eia.doe.gov N Y M E X N a t u r a l G a s F u t u r e s N e a r - M o n t h C o n t r a c t S e t t l e m e n t P r i c e , H e n r y H u b S p o t P r i c e ,...

  4. EIA Energy Information Administration

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

    4, 1997 http:www.eia.doe.gov N Y M E X F u t u r e P r i c e s v s H e n r y H u b S p o t P r i c e s 1 . 5 0 1 . 7 5 2 . 0 0 2 . 2 5 2 . 5 0 2 . 7 5 3 . 0 0 Dollars Per Million...

  5. EIA guidelines - are they doing the job?

    SciTech Connect (OSTI)

    Lawrence, D.P. [Lawrence Environmental, Langley, British Columbia (Canada)

    1997-08-01T23:59:59.000Z

    There is a tendency to evaluate the merits of the direction provided by the regulatory level to EIA practitioners by focusing exclusively on the contents of EIA requirements as expressed through legislation and regulations. However, much more substantive guidance is provided through general and project-specific EIA guidelines. EIA guidelines in Canada provide a useful case in point to EIA regulators and practitioners in the United States and elsewhere. The Federal government in Canada and in the ten Canadian provinces each has separate and distinctly different EIA legislation, regulations and guidelines. A review of the contents of EIA guidelines across these eleven jurisdictions can provide many insights regarding the role that EIA regulators can and should assume in shaping the contents of EIA documents and the conduct of the EIA planning process.

  6. EIA and CHP: What is going on?

    SciTech Connect (OSTI)

    Balducci, Patrick J.; Roop, Joseph M.; Fowler, Richard A.

    2003-08-01T23:59:59.000Z

    In December, 2002, the Energy Information Administration (EIA) released its Annual Energy Review, 2001 (hereafter AER01; the document is available at: http://www.eia.doe.gov/emeu/aer/contents.html), with extensive revisions to both the electricity data and the categories under which the data are reported. The basics of these revisions are explained in Appendix H of AER01, ''Estimating and Presenting Power Sector Fuel Use in EIA Publications and Analyses'' (which can be downloaded from the ''Appendices and Glossary'' link). This revision was timely and eliminated the growing ''adjustments'' that reconciled the discrepancy between the sum of fuels consumed by the four end-use sectors and the electricity sector with the total energy consumed by the four end-use sectors (i.e., with electricity losses allocated back to the four end-use sectors). This adjustment jumped from almost nothing in 1988 to 128 trillion Btu (TBtu) in 1989 and grew to a half-quadrillion British thermal unit (quad) by 199 8. In 1999 it was -3.2 quad and in 2000, as reported in the AER 2000, it was -4.3 quad. After revisions, the adjustment nearly disappears, with the largest adjustment over the period 1989-2001 at 10 trillion Btu (TBtu). Even with these revisions, however, there are still some very strange numbers. This paper explains these revisions and accounting techniques, and tries to reconcile some of the data via an appeal to the detailed Independent Power Producer survey, EIA Form 860b, for 1998 and 1999.

  7. EIA Winter Fuels Outlook

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877SouthwestWisconsin profile Wisconsin8,ElectricEIA

  8. EIA-411 Data File

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877SouthwestWisconsin profileDatabase Form EIA-411 -

  9. EIA-411 Data File

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877SouthwestWisconsin profileDatabase Form EIA-411

  10. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5, 19972, 19979,

  11. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5, 19972,

  12. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5, 19972,, 1997

  13. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5, 19972,,

  14. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5, 19972,,6,

  15. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5, 19972,,6,3,

  16. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5, 19972,,6,3,4,

  17. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,

  18. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8, 1997

  19. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8, 19974, 1997

  20. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8, 19974,

  1. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8, 19974,5,

  2. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8, 19974,5,,

  3. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8, 19974,5,,5,

  4. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8,

  5. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8,9, 1997

  6. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8,9, 19976,

  7. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8,9, 19976,4,

  8. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8,9,

  9. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8,9,7, 1997

  10. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8,9,7, 1997,

  11. EIA Energy Information Administration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.Major NaturalMontanaTexasTinker, 2015 EIA5,8,9,7, 1997,7,

  12. EIA April 2008

    Gasoline and Diesel Fuel Update (EIA)

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

  13. EIA-176 Form

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA revises1 7 6

  14. EIA-176 Instructions

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA revises1 7

  15. EIA-191 Instructions

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA revises1 1

  16. EIA-757 Instructions

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA12 (2003)

  17. EIA-782C,

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA12

  18. FORM EIA-28

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal2,7,7,of2014FORM EIA-28 -

  19. Form EIA-411 2011

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site. If youEIA-906 &Stocks 2009 2010 2011YearYearper

  20. Form EIA-411 2011

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site. If youEIA-906 &Stocks 2009 2010 2011YearYearper2013"

  1. EIA Energy Information Administration

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

    normal. Prices also seemed to derive strength from forecasts for a huge, frigid Arctic air mass-termed a "Polar Pig"-to move into the lower 48 states beginning early this week....

  2. Mo Year Report Period: EIA ID NUMBER:

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name:24,High824 2.839 2.8352.747 2.759 2.699Mo

  3. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA0 EIA2 EIA

  4. EIA-914 Monthly Natural Gas Production Report Data Analysis...

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

    EIA-914: Monthly Natural Gas Production Report Data Analysis October 2006 Page 1 of 38 EIA-914 Monthly Natural...

  5. An assessment of EIA system in India

    SciTech Connect (OSTI)

    Panigrahi, Jitendra K., E-mail: Jitu@scientist.com [Department of Marine Sciences, Berhampur University, Berhampur-760007 (India); Amirapu, Susruta, E-mail: susrutaa@gmail.com [EIA Department, L and T-RAMBOLL, Hyderabad-500029 (India)

    2012-07-15T23:59:59.000Z

    Environmental impact assessment (EIA) was first introduced in India based on the Environmental Protection Act (EPA), 1986. But formally it came in to effect, when Ministry of Environment and Forest (MoEF) has passed a major legislative measure under EPA in January 1994 for Environmental Clearance (EC) known as EIA Notification, 1994. Subsequently, EIA processes have been strengthened by MoEF by a series of amendments. The current practice is adhering to EIA Notification, 2006 and its amendments. The pieces of evidence collected and analysis in the present assessment suggest that, despite a sound legislative, administrative and procedural set-up EIA has not yet evolved satisfactorily in India. An appraisal of the EIA system against systematic evaluation criteria, based on discussions with various stakeholders, EIA expert committee members, approval authorities, project proponents, NGOs and consulting professionals, reveals various drawbacks of the EIA system. These mainly include; inadequate capacity of EIA approval authorities, deficiencies in screening and scoping, poor quality EIA reports, inadequate public participation and weak monitoring. Overall, EIA is used presently as a project justification tool rather than as a project planning tool to contribute to achieving sustainable development. While shortcomings are challenging, Government of India is showing a high degree of commitment. The EIA system in the country is undergoing progressive refinements by steadily removing the constraints. The paper identifies opportunities for taking advantage of the current circumstances for strengthening the EIA process. - Highlights: Black-Right-Pointing-Pointer An assessment has been carried out on Environmental Clearance under EIA Notification, 2006, MoEF, Government of India. Black-Right-Pointing-Pointer EIA system is appraised against systematic evaluation criteria proposed by Ahmad and Wood (2002), Wood (2003), Fuller (1999). Black-Right-Pointing-Pointer The analysis reveals reveals various drawbacks of the EIA system. Black-Right-Pointing-Pointer The paper identifies opportunities to enhance the effectiveness of the EIA system in India.

  6. About EIA - Policies - U.S. Energy Information Administration (EIA)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 34 44Year199873.4DecemberDecember Form EIA-411 for 2005bAbout EIA

  7. EIA - Energy Conferences & Presentations.

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877 951,322 1,381,127byForms What'sAnnual2 EIA3 EIA

  8. EIA - Energy Conferences & Presentations.

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877 951,322 1,381,127byForms What'sAnnual2 EIA3 EIA4

  9. EIA - Energy Conferences & Presentations.

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877 951,322 1,381,127byForms What'sAnnual2 EIA3 EIA45

  10. EIA - Energy Conferences & Presentations.

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877 951,322 1,381,127byForms What'sAnnual2 EIA37 EIA

  11. EIA - Energy Conferences & Presentations.

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877 951,322 1,381,127byForms What'sAnnual2 EIA37 EIA8

  12. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA0 EIA

  13. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA0 EIA2

  14. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA0 EIA24

  15. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA0 EIA245

  16. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA0 EIA2456

  17. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA0 EIA24567

  18. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA09 EIA

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

    SciTech Connect (OSTI)

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04T23:59:59.000Z

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

  20. "EIA-914 Production Weighted Response Rates, Percent"

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

    EIA-914 Production Weighted Response Rates, Percent" "Areas",38353,38384,38412,38443,38473,38504,38534,38565,38596,38626,38657,38687,38718,38749,38777,"application...

  1. U.S. Energy Information Administration (EIA)

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

    EIA's regional petroleum balances by reducing regional crude oil adjustments (unaccounted for crude oil). Petroleum Supply Monthly tables affected are tables 5-27 and 57. A...

  2. U.S. Energy Information Administration (EIA)

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

    OPEC Organization of the Petroleum Exporting Countries CSAPR Cross-State Air Pollution Rule RFS Renewable Fuels Standard EIA U.S. Energy Information Administration RPS...

  3. EIA - Annual Energy Outlook 2013 Early Release

    Gasoline and Diesel Fuel Update (EIA)

    OECD Organization for Economic Cooperation and Development CSAPR Cross-State Air Pollution Rule OPEC Organization of the Petroleum Exporting Countries EIA U.S. Energy...

  4. Auditing and control programs: putting EIA recommendations for ecological impacts prevention in practice

    E-Print Network [OSTI]

    Arce-Ruiz, Rosa M.

    2003-01-01T23:59:59.000Z

    Morrison-Saunders, A. (1996) “EIA Auditing to determinesu importancia en el proceso de EIA”. En El Transporte en elCONTROL PROGRAMS: PUTTING EIA RECOMMENDATIONS FOR ECOLOGICAL

  5. Danish experiences on EIA of livestock projects

    SciTech Connect (OSTI)

    Christensen, Per [Department of Development and Planning, Aalborg University, Fibigerstraede 13, DK-9220 Aalborg O (Denmark)]. E-mail: pc@plan.aau.dk

    2006-07-15T23:59:59.000Z

    Since its introduction into Danish planning in 1989, Environmental Impact Assessment (EIA) has been widely discussed. At the centre of the debate has been the question of whether EIA actually offered anything new and there has been a great deal of scepticism about the efficacy of the instrument, especially when it comes to livestock projects. In an evaluation of the Danish EIA experience, we have looked more closely at how the EIA instruments function regarding livestock projects. This article addresses both the EIA process as well as the EIA screening. It is demonstrated that the EIA screening in its own right is a kind of regulatory instrument. Examining the assessments made during screening more closely, we conclude that there is still some way to go in order to make the assessment broader and more holistic in accordance with the ambitions set out in the EIA directive to contribute to a more sustainable development. Although the provisions laid down are the same the praxis related to the field has developed at a considerable speed. In order to understand this development we have closely examined how the decisions made by the Nature Protection Board of Appeal (NPBA) have been changed and conclude that these changes definitely address some of the shortcomings found in the evaluation.

  6. About EIA - Organization - U.S. Energy Information Administration (EIA)

    Gasoline and Diesel Fuel Update (EIA)

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

  7. About EIA - Organization - U.S. Energy Information Administration (EIA)

    Gasoline and Diesel Fuel Update (EIA)

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

  8. About EIA - Organization - U.S. Energy Information Administration (EIA)

    Gasoline and Diesel Fuel Update (EIA)

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

  9. About EIA - Policies - U.S. Energy Information Administration (EIA)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWP TWP Related LinksATHENA could reduceCustomerEIA's 2015 Writing Style

  10. About EIA - Website - U.S. Energy Information Administration (EIA)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWP TWP Related LinksATHENA could reduceCustomerEIA's 2015 Writing

  11. About EIA - Website - U.S. Energy Information Administration (EIA)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWP TWP Related LinksATHENA could reduceCustomerEIA's 2015 WritingHelp

  12. About EIA - Policies - U.S. Energy Information Administration (EIA)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 34 44Year199873.4DecemberDecember Form EIA-411 for 2005b A-ZWebsite

  13. About EIA - Policies - U.S. Energy Information Administration (EIA)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 34 44Year199873.4DecemberDecember Form EIA-411 for 2005b

  14. About EIA - Policies - U.S. Energy Information Administration (EIA)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1 U.S. Department of Energygasoline4Residential17.KeepingAbout EIA

  15. EIA - Energy Conferences & Presentations.

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877 951,322 1,381,127byForms What'sAnnual2 EIA

  16. EIA - Energy Conferences & Presentations.

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877 951,322 1,381,127byForms What'sAnnual2 EIA3

  17. EIA - Energy Conferences & Presentations.

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877 951,322 1,381,127byForms What'sAnnual2 EIA37

  18. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA

  19. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA0

  20. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA09

  1. EIA | OpenEI Community

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluating A Potential MicrohydroDistrict ofDongjinDynetek42 EIA officially recognizes

  2. EIA-412 Form and Instructions

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA

  3. EIA-412 Form and Instructions

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA12 (2003)

  4. EIA-803_20150504.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal Control EIA-802, Weekly3,

  5. EIA-809_20150504.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal Control EIA-802,Expiration

  6. Form EIA-411 for 2011

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site. If youEIA-906 &Stocks 2009 2010

  7. X1£/EIA-0512(88)

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

    X1EIA-0512(88) f-tf- 7? day 1991 AO? Manufacturing Energy Consumption Survey Consump tion of Energy 1988 Energy Information Administration This publication is available from the...

  8. An evaluation of EIA system performance in eight EU countries

    SciTech Connect (OSTI)

    Barker, A. [Univ. of Aberdeen (United Kingdom)] [Univ. of Aberdeen (United Kingdom); Wood, C. [Univ. of Manchester (United Kingdom). EIA Centre] [Univ. of Manchester (United Kingdom). EIA Centre

    1999-07-01T23:59:59.000Z

    An evaluation of the quality of environmental impact assessment (EIA) reports, modifications to projects as a result of EIA, and the influence of changes to EIA procedures in the United Kingdom, Germany, Spain, Belgium, Denmark, Greece, Ireland, and Portugal is reported. The overall proportion of satisfactory EIA reports sampled increased from 50% to 71% between 1990--1991 and 1994--1996. Several modifications to projects occurred as a result of the EIA process, but there was no apparent trend over time relating to the number or significance of modifications. All the eight Member States had taken major or minor measures to modify EIA procedures and these either have already improved the quality of EIA practice or are expected to do so. A series of recommendations to improve the performance of the EIA process is presented.

  9. EIA Practice Examples of Cumulative Effects and Final Disposal of

    E-Print Network [OSTI]

    EIA Practice Examples of Cumulative Effects and Final Disposal of Spent Nuclear Fuel Antoienette: SLU Service/Repro, Uppsala 2012 #12;EIA Practice. Examples of Cumulative Effects and Final Disposal of Spent Nuclear Fuel Abstract This thesis is about Environmental Impact Assessment (EIA) practice

  10. End-use taxes: Current EIA practices

    SciTech Connect (OSTI)

    Not Available

    1994-08-17T23:59:59.000Z

    There are inconsistencies in the EIA published end-use price data with respect to Federal, state, and local government sales and excise taxes; some publications include end-use taxes and others do not. The reason for including these taxes in end-use energy prices is to provide consistent and accurate information on the total cost of energy purchased by the final consumer. Preliminary estimates are made of the effect on prices (bias) reported in SEPER (State Energy Price and Expenditure Report) resulting from the inconsistent treatment of taxes. EIA has undertaken several actions to enhance the reporting of end-use energy prices.

  11. Mandated monitoring of post-project impacts in the Czech EIA

    SciTech Connect (OSTI)

    Branis, Martin [Institute for Environmental Studies, Faculty of Science, Charles University in Prague, Albertov 6, 128 43 Prague 2 (Czech Republic)]. E-mail: branis@natur.cuni.cz; Christopoulos, Stamatios [Institute for Environmental Studies, Faculty of Science, Charles University in Prague, Albertov 6, 128 43 Prague 2 (Czech Republic)

    2005-04-15T23:59:59.000Z

    Altogether, 801 documents of consent (50% of all) issued under the EIA Act No. 244/1992 by the competent authorities in the Czech Republic between 1993 and 2001 were studied. The aim of the analysis was to find and characterize conditions prescribing to the developer to perform ex-ante and ex-post monitoring of potential impacts of projects submitted for approval. It was found that each of the studied documents (standpoints) contained on average three to four conditions prescribing to collect data on various environmental factors during the preparation, implementation and/or operation phase of the development in question. The number of monitoring conditions contained in the standpoints issued by the Ministry of Environment as well as by the District Offices increased during the period studied from about two to five per project indicating a growing interest in and/or need to obtaining such data. Even though there is a good legal background for collecting monitoring data from implementation and operation phase of new developments, the Czech EIA Act (similarly as EIA acts in other countries) does not provide any practical background for this activity. Without relevant institutional, personal and financial support the possibility to impose post-project monitoring to the developer remains rather a challenge to, not advantage of the Czech EIA Act.

  12. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

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

  13. EIA new releases: EIA examines the growing importance of longwall mining

    SciTech Connect (OSTI)

    NONE

    1995-05-17T23:59:59.000Z

    This publication disseminates information on progress in various DOE research areas. This issues contains information on Longwall mining; electric fleet utility survey; electronic publishing system; other publications of the EIA; and places from which to purchase publications.

  14. 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....

  15. DOE/EIA-0484(2008) International

    E-Print Network [OSTI]

    Laughlin, Robert B.

    position of the Department of Energy or of any other organization. This publication is on the WEB at: www-586-1398) Transportation Sector Energy Use . . . . . . Barry Kapilow-Cohen (bcohen@eia.doe.gov, 202-586-5359) Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Outlook for World Energy Consumption by Source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

  16. EIA and green procurement: Opportunities for strengthening their coordination

    SciTech Connect (OSTI)

    Uttam, Kedar, E-mail: kedar@kth.se [Department of Land and Water Resources Engineering, Royal Institute of Technology, Stockholm (Sweden); Faith-Ell, Charlotta, E-mail: charlotta.faith-ell@WSPGroup.se [WSP Sweden (Sweden); Balfors, Berit, E-mail: balfors@kth.se [Department of Land and Water Resources Engineering, Royal Institute of Technology, Stockholm (Sweden)

    2012-02-15T23:59:59.000Z

    EIA plays an important role in enhancing the environmental performance of the construction sector. In recent years, the construction sector has been developing green procurement practices. Green procurement is a process that involves the incorporation of environmental requirements during the procurement of services and products. However, discussion on green procurement is rarely seen during the EIA phase. This paper addresses possible opportunities for improving the coordination between EIA and green procurement within the construction sector. The linking of EIA and green procurement has been postulated in the paper as an aid to strengthen the coordination between project planning and implementation. The paper is based on a literature review and is an outcome of an on-going research project concerning EIA and green procurement. This study indicated that it would be appropriate to introduce green procurement during the pre-decision phase of an EIA. In the present study, the opportunities for integrating green procurement at the stage of EIA are associated with the integration of project planning and EIA. Future research should investigate the mechanism through which the link can be established. - Highlights: Black-Right-Pointing-Pointer This paper identifies opportunities to link EIA and green procurement. Black-Right-Pointing-Pointer Pre-decision phase of EIA could be appropriate for planning green procurement. Black-Right-Pointing-Pointer Future research should investigate the mechanism for establishing the link.

  17. The impact of forecasted energy price increases on low-income consumers

    SciTech Connect (OSTI)

    Eisenberg, Joel F. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2005-10-31T23:59:59.000Z

    The Department of Energy’s Energy Information Administration (EIA) recently released its short term forecast for residential energy prices for the winter of 2005-2006. The forecast indicates significant increases in fuel costs, particularly for natural gas, propane, and home heating oil, for the year ahead. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation’s low-income households by primary heating fuel type, nationally and by Census Region. The statistics are intended for the use of policymakers in the Department of Energy’s Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2006 fiscal year.

  18. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    Open Energy Info (EERE)

    Sales (MWh) 1889 Total Consumers 417 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  19. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 89442.402 Total Consumers 30374 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  20. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 93116.915 Total Consumers 30297 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  1. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 90111.278 Total Consumers 30445 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  2. 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 97102 Total Consumers 44394 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  3. 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 77157 Total Consumers 43869 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  4. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    Open Energy Info (EERE)

    Sales (MWh) 1777 Total Consumers 417 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  5. 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 69154 Total Consumers 43876 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  6. 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 77543 Total Consumers 44730 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  7. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 89735.352 Total Consumers 30544 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  8. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 107731.895 Total Consumers 30210 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  9. 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 92113 Total Consumers 44586 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  10. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 89390.873 Total Consumers 30381 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  11. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 95905.285 Total Consumers 30205 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  12. 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 64724 Total Consumers 44708 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  13. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    Open Energy Info (EERE)

    Sales (MWh) 1656 Total Consumers 417 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  14. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    Open Energy Info (EERE)

    Sales (MWh) 1588 Total Consumers 416 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  15. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 110168.666 Total Consumers 30225 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  16. Central Illinois Pub Serv Co (Illinois) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 723681 Total Consumers 388107 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  17. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 97302.646 Total Consumers 30310 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  18. Central Illinois Pub Serv Co (Illinois) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 635952 Total Consumers 375832 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  19. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    Open Energy Info (EERE)

    Sales (MWh) 2604 Total Consumers 416 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  20. 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 87721 Total Consumers 43779 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  1. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    Open Energy Info (EERE)

    Sales (MWh) 1786 Total Consumers 416 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  2. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 106052.325 Total Consumers 30249 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  3. 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 88236 Total Consumers 44787 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  4. Central Illinois Pub Serv Co (Illinois) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 458221 Total Consumers 378624 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  5. 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 73805 Total Consumers 44830 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  6. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 86664.25 Total Consumers 30409 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  7. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 103478.845 Total Consumers 30233 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  8. 4-County Electric Power Assn (Mississippi) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 93756 Total Consumers 43814 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  9. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    Open Energy Info (EERE)

    Sales (MWh) 2434 Total Consumers 416 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  10. Anchorage Municipal Light and Power (Alaska) EIA Revenue and...

    Open Energy Info (EERE)

    (MWh) 90071.242 Total Consumers 30468 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  11. U.S. Energy Information Administration (EIA) - Pub

    Gasoline and Diesel Fuel Update (EIA)

    EIA's regional petroleum balances by reducing regional crude oil adjustments (unaccounted for crude oil). Petroleum Supply Monthly tables affected are tables 5-27 and 57. A...

  12. 2-26-09_Final_Testimony_(Gruenspect)EIA.pdf

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

    electricity generation in the Energy Information Administration's (EIA) Annual Energy Outlook 2009 (AEO2009) projections, provides a brief overview of the renewable...

  13. DOE/EIA-0487(98) Petroleum Marketing Annual

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

    "Monthly For-eign Crude Oil Acquisition Report"; and Form EIA-14, "Re - finers' Monthly Cost Report." The statistics on petroleum product sales prices and volumes are derived...

  14. Revision Policy for EIA Weekly Underground Natural Gas Storage...

    Weekly Natural Gas Storage Report (EIA)

    April 26, 2005 This report consists of the following sections: General EIA Weekly Natural Gas Storage Report Revisions Policy - a description of how revisions to the Weekly Natural...

  15. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    Open Energy Info (EERE)

    August 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin Electric Utility Authority for August 2008. Monthly Electric Utility Sales...

  16. 1993 Solid Waste Reference Forecast Summary

    SciTech Connect (OSTI)

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

    1993-08-01T23:59:59.000Z

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

  17. About EIA - U.S. Energy Information Administration (EIA) - U.S. Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, Weekly Refinery andInformation Administration (EIA) EIA

  18. Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price.................................................................................................................................. 27 INTRODUCTION The Council prepares and periodically updates a 20-year forecast of wholesale to forecast wholesale power prices. AURORAxmp® provides the ability to inco

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

    E-Print Network [OSTI]

    Hicks, Geoff Cody

    1997-01-01T23:59:59.000Z

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

  20. EIA - Greenhouse Gas Emissions - Carbon Dioxide Emissions

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877 951,322 1,381,127byForms What'sAnnual2 EIA372.

  1. EIA - Gulf of Mexico Energy Data

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2YonthlyEnergy Markets EIA09Isaac

  2. HOW TO OBTAIN EIA PRODUCTS AND SERVICES

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803 Table A1.GasYearperHOW TO OBTAIN EIA PRODUCTS AND

  3. EIA-782A Exclusionary list instructions

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA12 (2003)A

  4. EIA-782B EXCLUSIONARY LIST INSTRUCTIONS

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA12 (2003)AB

  5. EIA-782C Exclusionary list instructions

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA12 (2003)ABC

  6. EIA-804, Weekly Imports Report Page 1

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal Control EIA-802, Weekly3,

  7. EIA-809, Weekly Oxygenate Report Page 1

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal Control EIA-802,

  8. Energy Information Administration (EIA)- Commercial Buildings Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal2,7,7,of2014 EIA-64A

  9. EIA-176 Electronic Filing System (EFS)

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0 Year-1InformationDieselAnnual EnergyAlabamaEIA-176 Electronic

  10. U.S. Energy Information Administration (EIA)

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oilAllDiesel Fuel Price ContinuesA Day at EIA

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

    E-Print Network [OSTI]

    Hansens, Jim

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

  12. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

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

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

    Gasoline and Diesel Fuel Update (EIA)

    FILES Electric power sales, revenue, and energy efficiency Form EIA-861 detailed data files Release Date for 2013: February 19, 2015 Next Release date: October 2015 Annual data for...

  14. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    Open Energy Info (EERE)

    8 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin Electric Utility Authority for March 2008. Monthly Electric Utility Sales and Revenue...

  15. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    Open Energy Info (EERE)

    April 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin Electric Utility Authority for April 2008. Monthly Electric Utility Sales and...

  16. Risk assessment for improved treatment of health considerations in EIA

    SciTech Connect (OSTI)

    Demidova, Olga [Ecoline Environmental Assessment Center, PO Box 7 125047, Moscow (Russian Federation)]. E-mail: odemidova@eac-ecoline.ru; Cherp, Aleg [Department of Environmental Sciences and Policy, Central European University (CEU), Nador u. 9, 1051, Budapest (Hungary)]. E-mail: cherpa@ceu.hu

    2005-05-15T23:59:59.000Z

    Environmental Impact Assessment (EIA) and Risk Assessment (RA) processes are rarely used to complement each other despite potential benefits of such integration. This paper proposes a model for procedural and methodological integration of EIA and RA based on reported best practice approaches. The proposed model stipulates 'embedding' RA into EIA and is organized in accordance with the generic stages of the EIA process. The model forms the basis for the proposed Evaluation Package which can be used as a benchmarking tool for evaluating the effectiveness of integration of RA within particular EIAs. The current paper uses the package for evaluating seven Environmental Impact Statements (EISs) of waste incineration facilities in the UK produced between 1990 and 2000. Though RA was found to be an element of these EIAs, its prominence varied considerably from case to case. Systematic application of RA in accordance with the best practice was not observed. Particular omissions were demonstrated in assessing health impacts not directly associated with air emissions, identifying the receptors of health impacts (affected population), interpreting health impacts as health risks, dealing with uncertainties, and risk communications.

  17. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

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

    1994-09-01T23:59:59.000Z

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

  18. Technology Forecasting Scenario Development

    E-Print Network [OSTI]

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

  19. Rainfall-River Forecasting

    E-Print Network [OSTI]

    US Army Corps of Engineers

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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    the Energy Information Administration’s (EIA) web site. Wein the past, compared the EIA’s reference-case long-termfuel price projection from the EIA or some other long-term

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01T23:59:59.000Z

    the Energy Information Administration’s (EIA) web site. Wein the past, compared the EIA’s reference-case long-termfuel price projection from the EIA or some other long-term

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    the Energy Information Administration’s (EIA) web site. Wein the past, compared the EIA’s reference-case long-termfuel price projection from the EIA or some other long-term

  3. EIA-An Updated Annual Energy Outlook 2009 Reference Case - Preface...

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

    about the report can be directed to the following analysts: Macroeconomic Analysis Kay Smith (kay.smith@eia.doe.gov, 202586-1132) Buildings John Cymbalsky (john.cymbalsky@eia.doe...

  4. Request for an Update of EIA's January 2012 Study of Liquefied...

    Office of Environmental Management (EM)

    Request for an Update of EIA's January 2012 Study of Liquefied Natural Gas Export Scenarios Request for an Update of EIA's January 2012 Study of Liquefied Natural Gas Export...

  5. Summary of Feedback Collected for the EIA Program (February June, 2011)

    E-Print Network [OSTI]

    Rau, Don C.

    1 Summary of Feedback Collected for the EIA Program (February ­ June, 2011) August 12, 2011 ......................................................................... 12 CUSTOMER SATISFACTION SURVEY FOR APPLICANTS (JUNIOR SCIENTISTS) ....... 13 Major Highlights for Improving the EIA Program............................................................................ 17

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19T23:59:59.000Z

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

  9. The Canadian EIA Process: The Purpose, The Process, The Players and The Pitfalls

    E-Print Network [OSTI]

    Boisvert, Jeff

    ? · As the Keystone Pipeline and Prosperity Gold-Copper Mine Project have indicated until an EIA has been concluded, design criteria, operating parameters and monitoring are the EIA report and recommendations EI, EI, EIA to be addressed, from the beginning to the end, should not be limited to problems of engineering and construction

  10. EIA-22M, Monthly Biodiesel Production Survey Page 1 EIA-22M

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA revises1

  11. Probabilistic manpower forecasting

    E-Print Network [OSTI]

    Koonce, James Fitzhugh

    1966-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    Dubin, Rivers Associates. EIA. 1989. Housing CharacteristicsU.S. Dept. of Energy, Washington, DC. DOE/EIA- 0314(87).May. EIA. 1990. Energy Consumption and Conservation

  13. UPF Forecast | Y-12 National Security Complex

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

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

  14. Long Term Forecast ofLong Term Forecast of TsunamisTsunamis

    E-Print Network [OSTI]

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

  15. Steam System Forecasting and Management

    E-Print Network [OSTI]

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

    1982-01-01T23:59:59.000Z

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

  16. Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill

    SciTech Connect (OSTI)

    Shukla, Shraddhanand; Voisin, Nathalie; Lettenmaier, D. P.

    2012-08-15T23:59:59.000Z

    We investigated the contribution of medium range weather forecasts with lead times up to 14 days to seasonal hydrologic prediction skill over the Conterminous United States (CONUS). Three different Ensemble Streamflow Prediction (ESP)-based experiments were performed for the period 1980-2003 using the Variable Infiltration Capacity (VIC) hydrology model to generate forecasts of monthly runoff and soil moisture (SM) at lead-1 (first month of the forecast period) to lead-3. The first experiment (ESP) used a resampling from the retrospective period 1980-2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast) or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts, for runoff (SM) forecasts generally varies from 0 to 0.8 (0 to 0.5) as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

  17. Comparing GIS-based habitat models for applications in EIA and SEA

    SciTech Connect (OSTI)

    Gontier, Mikael, E-mail: gontier@kth.s [Department of Land and Water Resources Engineering, Royal Institute of Technology, SE-100 44 Stockholm (Sweden); Moertberg, Ulla, E-mail: mortberg@kth.s [Department of Land and Water Resources Engineering, Royal Institute of Technology, SE-100 44 Stockholm (Sweden); Balfors, Berit, E-mail: balfors@kth.s [Department of Land and Water Resources Engineering, Royal Institute of Technology, SE-100 44 Stockholm (Sweden)

    2010-01-15T23:59:59.000Z

    Land use changes, urbanisation and infrastructure developments in particular, cause fragmentation of natural habitats and threaten biodiversity. Tools and measures must be adapted to assess and remedy the potential effects on biodiversity caused by human activities and developments. Within physical planning, environmental impact assessment (EIA) and strategic environmental assessment (SEA) play important roles in the prediction and assessment of biodiversity-related impacts from planned developments. However, adapted prediction tools to forecast and quantify potential impacts on biodiversity components are lacking. This study tested and compared four different GIS-based habitat models and assessed their relevance for applications in environmental assessment. The models were implemented in the Stockholm region in central Sweden and applied to data on the crested tit (Parus cristatus), a sedentary bird species of coniferous forest. All four models performed well and allowed the distribution of suitable habitats for the crested tit in the Stockholm region to be predicted. The models were also used to predict and quantify habitat loss for two regional development scenarios. The study highlighted the importance of model selection in impact prediction. Criteria that are relevant for the choice of model for predicting impacts on biodiversity were identified and discussed. Finally, the importance of environmental assessment for the preservation of biodiversity within the general frame of biodiversity conservation is emphasised.

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

    E-Print Network [OSTI]

    Laughlin, Robert B.

    2009-01-01T23:59:59.000Z

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

  19. 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

  20. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16T23:59:59.000Z

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

  1. timber quality Modelling and forecasting

    E-Print Network [OSTI]

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

  2. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

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

  3. An evaluation framework for effective public participation in EIA in Pakistan

    SciTech Connect (OSTI)

    Nadeem, Obaidullah, E-mail: obaidnadeem@yahoo.co [Department of City and Regional Planning, University of Engineering and Technology, Lahore (Pakistan); Fischer, Thomas B., E-mail: fischer@liverpool.ac.u [Department of Civic Design, the University of Liverpool, Liverpool (United Kingdom)

    2011-01-15T23:59:59.000Z

    Evaluating the effectiveness of public participation in EIA related decisions is of crucial importance for developing a better understanding of overall EIA effectiveness. This paper aims to contribute to the professional debate by establishing a country specific evaluation framework for Pakistan, which, it is suggested, could also potentially be used in other developing countries. The framework is used to evaluate performance of public participation in EIA in terms of 40 attributes for four selected projects from the province of Punjab. The evaluation is based on interviews with stakeholders, review of EIA reports as well as public hearing proceedings and environmental approval conditions. The evaluation of the selected projects revealed an overall weak influence of public participation on substantive quality of EIA and on the final decision. Overall, EIA public participation has succeeded in providing a more egalitarian environment. Furthermore, it appears fair to say that sufficient time for submitting written comments on EIA reports as well as for raising concerns during public hearings had been given. Also, public consultation was significantly contributing to educating participants. Despite some impediments, it is argued that public participation in EIA is gradually gaining ground in Pakistan. Recommendations to enhance EIA public participation effectiveness in Pakistan include applying a more proactive approach which should take place before EIA is conducted and before site selection for development projects is happening.

  4. Does enhanced regulation improve EIA report quality? Lessons from South Africa

    SciTech Connect (OSTI)

    Sandham, L.A., E-mail: luke.sandham@nwu.ac.za [Environmental Assessment Research Group, School of Geo and Spatial Sciences, North-West University, Private Bag X6001, Potchefstroom, 2520 (South Africa); Heerden, A.J. van [Environmental Assessment Research Group, School of Geo and Spatial Sciences, North-West University, Private Bag X6001, Potchefstroom, 2520 (South Africa); Jones, C.E. [School of Environment and Development, University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom); Retief, F.P.; Morrison-Saunders, A.N. [Environmental Assessment Research Group, School of Geo and Spatial Sciences, North-West University, Private Bag X6001, Potchefstroom, 2520 (South Africa)

    2013-01-15T23:59:59.000Z

    Recently, various EIA systems have been subjected to system review processes with a view to improve performance. Many of these reviews resulted in some form of legislative reform. The South African Environmental Impact Assessment (EIA) regulations were modified in 2006 with the express intent to improve EIA effectiveness. In order to evaluate to what extent the desired outcome was achieved, the quality of EIA reports produced under the 2006 regulations was investigated for comparative analysis with the preceding regime. A sample of EIA reports from the two legislative regimes was reviewed using an adapted version of a well established method known colloquially as the 'Lee and Colley' review package. Despite some improvements in certain aspects, overall report quality has decreased slightly from the 1997 EIA regime. It therefore appears that the modifications to the regulations, often heralded as the solution to improvements in performance have not resulted in improved quality of EIA reports. - Highlights: Black-Right-Pointing-Pointer EIA regulations in South Africa were revised and became more comprehensive in 2006. Black-Right-Pointing-Pointer The report quality of a sample of EIAs was reviewed using the Lee and Colley review package. Black-Right-Pointing-Pointer Report quality showed a slight decline from the previous regulatory regime. Black-Right-Pointing-Pointer EIA good practice needs flexibility rather than over-detailed regulation.

  5. Verification of hourly forecasts of wind turbine power output

    SciTech Connect (OSTI)

    Wegley, H.L.

    1984-08-01T23:59:59.000Z

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

  6. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

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

  7. Fuel Price Forecasts INTRODUCTION

    E-Print Network [OSTI]

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

  8. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

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

  10. Walking the sustainability assessment talk - Progressing the practice of environmental impact assessment (EIA)

    SciTech Connect (OSTI)

    Morrison-Saunders, Angus, E-mail: a.morrison-saunders@murdoch.edu.au [School of Environmental Sciences and Development, North West University (South Africa); School of Environmental Science, Murdoch University (Australia); Retief, Francois [School of Environmental Sciences and Development, North West University (South Africa)

    2012-09-15T23:59:59.000Z

    Internationally there is a growing demand for environmental impact assessment (EIA) to move away from its traditional focus towards delivering more sustainable outcomes. South Africa is an example of a country where the EIA system seems to have embraced the concept of sustainability. In this paper we test the existing objectives for EIA in South Africa against sustainability principles and then critique the effectiveness of EIA practice in delivering these objectives. The outcome of the research suggests that notwithstanding a strong and explicit sustainability mandate through policy and legislation, the effectiveness of EIA practice falls far short of what is mandated. This shows that further legislative reform is not required to improve effectiveness but rather a focus on changing the behaviour of individual professionals. We conclude by inviting further debate on what exactly practitioners can do to give effect to sustainability in EIA practice.

  11. Cumulative effects in Swedish EIA practice - difficulties and obstacles

    SciTech Connect (OSTI)

    Waernbaeck, Antoienette [Swedish EIA Centre, Department of Urban and Rural Development, Swedish University of Agricultural Sciences, Uppsala (Sweden)], E-mail: antoienette.warnback@sol.slu.se; Hilding-Rydevik, Tuija [Swedish EIA Centre, Department of Urban and Rural Development, Swedish University of Agricultural Sciences, Uppsala (Sweden)

    2009-02-15T23:59:59.000Z

    The importance of considering cumulative effects (CE) in the context of environmental assessment is manifested in the EU regulations. The demands on the contents of Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) documents explicitly ask for CE to be described. In Swedish environmental assessment documents CE are rarely described or included. The aim of this paper is to look into the reasons behind this fact in the Swedish context. The paper describes and analyse how actors implementing the EIA and SEA legislation in Sweden perceive the current situation in relation to the legislative demands and the inclusion of cumulative effects. Through semi-structured interviews the following questions have been explored: Is the phenomenon of CE discussed and included in the EIA/SEA process? What do the actors include in and what is their knowledge of the term and concept of CE? Which difficulties and obstacles do these actors experience and what possibilities for inclusion of CE do they see in the EIA/SEA process? A large number of obstacles and hindrances emerged from the interviews conducted. It can be concluded from the analysis that the will to act does seem to exist. A lack of knowledge in respect of how to include cumulative effects and a lack of clear regulations concerning how this should be done seem to be perceived as the main obstacles. The knowledge of the term and the phenomenon is furthermore quite narrow and not all encompassing. They experience that there is a lack of procedures in place. They also seem to lack knowledge of methods in relation to how to actually work, in practice, with CE and how to include CE in the EIA/SEA process. It can be stated that the existence of this poor picture in relation to practice concerning CE in the context of impact assessment mirrors the existing and so far rather vague demands in respect of the inclusion and assessment of CE in Swedish EIA and SEA legislation, regulations, guidelines and handbooks.

  12. Alaska Electric Light&Power Co (Alaska) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 27165 Total Consumers 15955 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  13. Alaska Electric Light&Power Co (Alaska) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 18050 Total Consumers 15886 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  14. Alaska Electric Light&Power Co (Alaska) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 30637 Total Consumers 15914 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  15. Alaska Electric Light&Power Co (Alaska) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 23039 Total Consumers 15910 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  16. Alaska Electric Light&Power Co (Alaska) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 19019 Total Consumers 15891 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  17. Alaska Electric Light&Power Co (Alaska) EIA Revenue and Sales...

    Open Energy Info (EERE)

    (MWh) 27724.952 Total Consumers 15949 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  18. Alaska Electric Light&Power Co (Alaska) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 26729 Total Consumers 15898 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  19. Alaska Electric Light&Power Co (Alaska) EIA Revenue and Sales...

    Open Energy Info (EERE)

    (MWh) 27020.525 Total Consumers 15945 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  20. Alaska Electric Light&Power Co (Alaska) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 28400 Total Consumers 15946 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  1. Alaska Electric Light&Power Co (Alaska) EIA Revenue and Sales...

    Open Energy Info (EERE)

    Sales (MWh) 28597 Total Consumers 15902 Source: Energy Information Administration. Form EIA-826 Database Monthly Electric Utility Sales and Revenue Data 1 Previous | Next...

  2. Microsoft Word - EIA_WNGSR_PFEI-Evalution--06-29-11 _2_.docx

    Weekly Natural Gas Storage Report (EIA)

    Natural Gas Storage Report (WNGSR) (June 2011 for 2008 through 2010) Introduction The Energy Information Administration (EIA) is the statistical and analytical agency within the...

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

    SciTech Connect (OSTI)

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

    2005-07-01T23:59:59.000Z

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

  4. Forecasting oilfield economic performance

    SciTech Connect (OSTI)

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

    1994-11-01T23:59:59.000Z

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

  5. Model bias correction for dust storm forecast using ensemble Kalman filter

    E-Print Network [OSTI]

    Model bias correction for dust storm forecast using ensemble Kalman filter Caiyan Lin,1,2 Jiang Zhu Kalman filter (EnKF) assimilation targeting heavy dust episodes during the period of 15­24 March 2002. Wang (2008), Model bias correction for dust storm forecast using ensemble Kalman filter, J. Geophys

  6. Assessing environmental vulnerability in EIA-The content and context of the vulnerability concept in an alternative approach to standard EIA procedure

    SciTech Connect (OSTI)

    Kvaerner, Jens [Bioforsk-Norwegian Institute for Agricultural and Environmental Research, Soil and Environmental Division, Frederik A. Dahls vei 20, N-1432 As (Norway)]. E-mail: jens.kvarner@bioforsk.no; Swensen, Grete [NIKU, Norwegian Institute for Cultural Heritage Research, Storgata 2, P.O. Box 736, Sentrum, N-0105 Oslo (Norway)]. E-mail: grete.swensen@niku.no; Erikstad, Lars [NINA, Norwegian Institute for Nature Research, Dronningens gt. 13., P.O. Box 736, Sentrum, N-0105 Oslo (Norway)]. E-mail: lars.erikstad@nina.no

    2006-07-15T23:59:59.000Z

    In the traditional EIA procedure environmental vulnerability is only considered to a minor extent in the early stages when project alternatives are worked out. In Norway, an alternative approach to EIA, an integrated vulnerability model (IVM), emphasising environmental vulnerability and alternatives development in the early stages of EIA, has been tried out in a few pilot cases. This paper examines the content and use of the vulnerability concept in the IVM approach, and discusses the concept in an EIA context. The vulnerability concept is best suited to overview analyses and large scale spatial considerations. The concept is particularly useful in the early stages of EIA when alternatives are designed and screened. By introducing analyses of environmental vulnerability at the start of the EIA process, the environment can be a more decisive issue for the creation of project alternatives as well as improving the basis for scoping. Vulnerability and value aspects should be considered as separate dimensions. There is a need to operate with a specification between general and specific vulnerability. The concept of environmental vulnerability has proven useful in a wide range of disciplines. Different disciplines have different lengths of experience regarding vulnerability. In disciplines such as landscape planning and hydrogeology we find elements suitable as cornerstones in the further development of an interdisciplinary methodology. Further development of vulnerability criteria in different disciplines and increased public involvement in the early stages of EIA are recommended.

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

    SciTech Connect (OSTI)

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

    2011-12-06T23:59:59.000Z

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

  8. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01T23:59:59.000Z

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

  9. ELECTRICITY DEMAND FORECAST COMPARISON REPORT

    E-Print Network [OSTI]

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

  10. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

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

  11. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

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

  12. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

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

  13. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

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

  14. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

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

  15. Conservation The Northwest ForecastThe Northwest Forecast

    E-Print Network [OSTI]

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

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

    SciTech Connect (OSTI)

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

    2005-02-09T23:59:59.000Z

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

  17. The need for subjectivity in EIA: discourse as a tool for sustainable development

    SciTech Connect (OSTI)

    Wilkins, Hugh

    2003-07-01T23:59:59.000Z

    Subjectivity is often viewed as one of the shortcomings of environmental impact assessment (EIA). Politicized evaluations, narrow boundary setting, data gaps and simplified assumptions are frequently seen as problems in EIA that must be addressed. This paper takes a different approach to the issue. It views subjectivity as one of the positive attributes of the process that should be encouraged in order to promote sustainability and to inspire confidence in EIA. A satisfactory decision at the end of a specific EIA is not the only goal of the process. As a forum in which the public, proponents and regulators deliberate on the design and implementation of development plans, the creation of discourse around the pertinent issues at stake is also an important result. EIA promotes the development of values that foster greater social responsibility and has the capacity to increase the importance of long-term environmental considerations in decision-making.

  18. EIA models and capacity building in Viet Nam: an analysis of development aid programs

    SciTech Connect (OSTI)

    Doberstein, Brent

    2004-04-01T23:59:59.000Z

    There has been a decided lack of empirical research examining development aid agencies as 'agents of change' in environmental impact assessment (EIA) systems in developing countries, particularly research examining the model of environmental planning practice promoted by aid agencies as part of capacity building. This paper briefly traces a conceptual framework of EIA, then introduces the concept of 'EIA capacity building'. Using Viet Nam as a case study, the paper then outlines the empirical results of the research, focusing on the extent to which aid agency capacity-building programs promoted a Technical vs. Planning Model of EIA and on the coherence of capacity-building efforts across all aid programs. A discussion follows, where research results are interpreted within the Vietnamese context, and implications of research results are identified for three main groups of actors. The paper concludes by calling for development aid agencies to reconceptualise EIA capacity building as an opportunity to transform developing countries' development planning processes.

  19. A review of EIA report quality in the North West province of South Africa

    SciTech Connect (OSTI)

    Sandham, Luke A. [Environmental Assessment Research Group, School of Environmental Sciences and Development, North-West University, Private Bag X6001, Potchefstroom (South Africa)], E-mail: luke.sandham@nwu.ac.za; Pretorius, Hester M. [P.O. Box 6859, Ansfrere, 1711 (South Africa)], E-mail: hpret@webmail.co.za

    2008-05-15T23:59:59.000Z

    The revised EIA regulations implemented on 3 July 2006 focused attention on the question of EIA effectiveness in South Africa. EIR quality review is one of the quality control functions contributing to EIA effectiveness within any EIA system, therefore the EIR quality review package developed by Lee and Colley was adapted and used to review the quality of a sample of 28 EIRs in the North West province of South Africa. Overall, 86% of the reports achieved satisfactory grades, with the descriptive and presentational elements of the EIRs more satisfactorily addressed, and the analytical components such as impact significance, addressed to a less satisfactory degree. EIR quality appears to be on par with international standards, but there are areas of distinct weakness. Further research is required to optimise quality review, and to reveal whether the new regulations have succeeded in addressing these weaknesses and made positive contributions to EIR quality, as a component of EIA effectiveness in South Africa.

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

    SciTech Connect (OSTI)

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

    2011-08-15T23:59:59.000Z

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

  1. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400. Hall Deputy Director Energy Efficiency and Demand Analysis Division Scott W. Matthews Acting Executive

  2. Mathematical Forecasting Donald I. Good

    E-Print Network [OSTI]

    Boyer, Robert Stephen

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

  3. Regional-seasonal weather forecasting

    SciTech Connect (OSTI)

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

    1980-08-01T23:59:59.000Z

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

  4. EIA - Greenhouse Gas Emissions - High-GWP gases

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877 951,322 1,381,127byForms What'sAnnual2 EIA372.5.

  5. EIA Energy Conferences & Presentations, April 8, 2009

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877SouthwestWisconsin profile Wisconsin8, 2009EIA

  6. EIA Energy Conferences & Presentations, April 8, 2009

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877SouthwestWisconsin profile Wisconsin8, 2009EIA9:

  7. Energy Information Administration (EIA)- About the Commercial Buildings

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power AdministrationField8, 2000 http://www.eia.doe.gov/oil_gas/natural_gas/nat_frame.htmlEnergy

  8. Revision Policy for EIA Weekly Underground Natural Gas Storage Estimates

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > TheNuclear Press ReleasesIn theTreatment in aRevision Policy for EIA

  9. Test Drive EIA's New Interactive Electricity Data Browser | Department of

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2, 2015 - JanuaryTank 48H TreatmentEnergy Test Drive EIA's New

  10. OMB No. 1905-0093 * EIA 457B

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC)Integrated CodesTransparencyDOE Project *1980-1981 U.S. Department of Energy093 * EIA

  11. EIA-22M, Monthly Biodiesel Production Survey Page 1

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA revises122M,

  12. FORM EIA-861 ANNUAL ELECTRIC POWER INDUSTRY REPORT INSTRUCTIONS

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal2,7,7,of2014FORM EIA-28861

  13. OHA EIA CASES ARCHIVE FILE | Department of Energy

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy China 2015of 2005 attheMohammed KhanDepartmentResponseNovemberAPP-00509EIA decisions,

  14. EIA-23L Reserves Information Gathering System (RIGS)

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0 Year-1InformationDieselAnnual EnergyAlabamaEIA-176182,

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J9 April 2015Events

  16. U.S. Energy Information Administration (EIA) - Ourwork

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oilAllDieselMarkets &FindWhat's New inEIA

  17. US EIA Country Energy Profiles | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlin Baxin HydropowerTrinityTurnbullGlobal Map-Annex 1EIA Country Energy

  18. US Energy Information Administration EIA | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlin Baxin HydropowerTrinityTurnbullGlobal Map-Annex 1EIA CountryUS

  19. Visualization of United States EIA SEDS data | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga,planningFlowmeterUtah: Energydba Vision Motor CorpEIA SEDS data Jump

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

    SciTech Connect (OSTI)

    Not Available

    1983-02-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Chen, Cliff; Wiser, Ryan; Bolinger, Mark

    2007-01-01T23:59:59.000Z

    EIA’s 2006 forecast for average natural gas prices deliveredsuch as the natural gas price forecast and the presumedNatural Gas Price Forecasts ..

  2. Comparative study of the transient evolution of Hanle EIT/EIA resonances

    E-Print Network [OSTI]

    P. Valente; H. Failache; A. Lezama

    2001-07-02T23:59:59.000Z

    The temporal evolutions of coherent resonances corresponding to electromagnetically induced transparency (EIT) and absorption (EIA) were observed in a Hanle absorption experiment carried on the $D_{2}$ lines of $% ^{87}$Rb vapor by suddenly turning the magnetic field on or off. The main features of the experimental observations are well reproduced by a theoretical model based on Bloch equation where the atomic level degeneracy has been fully accounted for. Similar (opposite phase) evolutions were observed at low optical field intensities for Hanle/EIT or Hanle/EIA resonances. Unlike the Hanle/EIA\\ transients which are increasingly shorter for driving field intensities approaching saturation, the $B\

  3. Comparative study of the transient evolution of Hanle EIT/EIA resonances

    E-Print Network [OSTI]

    Valente, P; Lezama, A

    2001-01-01T23:59:59.000Z

    The temporal evolutions of coherent resonances corresponding to electromagnetically induced transparency (EIT) and absorption (EIA) were observed in a Hanle absorption experiment carried on the $D_{2}$ lines of $% ^{87}$Rb vapor by suddenly turning the magnetic field on or off. The main features of the experimental observations are well reproduced by a theoretical model based on Bloch equation where the atomic level degeneracy has been fully accounted for. Similar (opposite phase) evolutions were observed at low optical field intensities for Hanle/EIT or Hanle/EIA resonances. Unlike the Hanle/EIA\\ transients which are increasingly shorter for driving field intensities approaching saturation, the $B\

  4. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

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

  5. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

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

  6. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01T23:59:59.000Z

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

  8. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

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

  9. Analysis quality report on the EIA Annual Report to Congress 1978, volume III : coal supply

    E-Print Network [OSTI]

    Wood, David O.

    1981-01-01T23:59:59.000Z

    The Energy Information Administration (EIA) is charged by Congress to prepare an Annual Report to Congress (ARC) which includes projections of energy supplies, consumption and prices, as well as the relation of energy to ...

  10. The importance of context in delivering effective EIA: Case studies from East Africa

    SciTech Connect (OSTI)

    Marara, Madeleine; Okello, Nick; Kuhanwa, Zainab; Douven, Wim; Beevers, Lindsay, E-mail: l.beevers@hw.ac.uk; Leentvaar, Jan

    2011-04-15T23:59:59.000Z

    This paper reviews and compares the condition of the environmental impact assessment (EIA) system in three countries in the East Africa region: Kenya, Rwanda and Tanzania. The criteria used for the evaluation and the comparison of each system are based on the elements of the legal, administrative and procedural frameworks, as well as the context in which they operate. These criteria are adapted from the evaluation and quality control criteria derived from a number of literature sources. The study reveals that the EIA systems of Kenya and Tanzania are at a similar stage in their development. The two countries, the first to introduce the EIA concept into their jurisdiction in this part of Africa, therefore have more experience than Rwanda in the practice of environmental impact assessment, where the legislation and process requires more time to mature both from the governmental and societal perspective. The analysis of the administrative and procedural frameworks highlights the weakness in the autonomy of the competent authority, in all three countries. Finally a major finding of this study is that the contextual set up i.e. the socio-economic and political situation plays an important role in the performance of an EIA system. The context in developing countries is very different from developed countries where the EIA concept originates. Interpreting EIA conditions in countries like Kenya, Rwanda and Tanzania requires that the analysis for determining the effectiveness of their systems should be undertaken within a relevant framework, taking into account the specific requirements of those countries.

  11. Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Lew, D.; Milligan, M.

    2013-01-01T23:59:59.000Z

    Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of the day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.

  12. Environmental Impact Assessment (EIA) Process of V1 NPP Decommissioning

    SciTech Connect (OSTI)

    Matejovic, Igor [DECOM A.S., Jana Bottu, 2. SK-91701 Trnava (Slovakia); Polak, Vincent [STM POWER, a.s., Jana Bottu 2, 917 01 Trnava (Slovakia)

    2007-07-01T23:59:59.000Z

    Through the adoption of Governmental Resolution No. 801/99 the Slovak Republic undertook a commitment to shutdown units 1 and 2 of Jaslovske Bohunice V 1 NPP (WWER 230 reactor type) in 2006 and 2008 respectively. Therefore the more intensive preparation of a decommissioning documentation has been commenced. Namely, the VI NPP Conceptual Decommissioning Plan and subsequently the Environmental Impact Assessment Report of VI NPP Decommissioning were developed. Thus, the standard environmental impact assessment process was performed and the most suitable alternative of V1 NPP decommissioning was selected as a basis for development of further decommissioning documents. The status and main results of the environmental impact assessment process and EIA report are discussed in more detail in this paper. (authors)

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

    E-Print Network [OSTI]

    Johnson, F.X.

    2010-01-01T23:59:59.000Z

    equipment (EIA 1993), and a compilation of utility surveySurvey (RECS) conducted by the Energy Information Administration (EIAMay. EIA. 1993. 1990 Residential Energy Consumption Survey (

  14. Environmental value assessment in a multidisciplinary EIA setting

    SciTech Connect (OSTI)

    Erikstad, Lars [Norwegian Institute for Nature Research (NINA), Gaustadalleen 21, NO-0349 Oslo (Norway)], E-mail: lars.erikstad@nina.no; Lindblom, Inge [Norwegian Institute for Cultural Heritage Research (NIKU), Box 736, Sentrum NO-0105 Oslo (Norway)], E-mail: inge.lindblom@niku.no; Jerpasen, Gro [Norwegian Institute for Cultural Heritage Research (NIKU), Box 736, Sentrum NO-0105 Oslo (Norway)], E-mail: gro.jerpasen@niku.no; Hanssen, Martin A. [Norwegian Institute for Urban and Regional Research (NIBR), Box 44 Blindern, NO-0313 Oslo (Norway)], E-mail: martin.hanssen@nibr.no; Bekkby, Trine [Norwegian Institute for Water Research (NIVA), Gaustadalleen 21, NO-0349 Oslo (Norway)], E-mail: trine.bekkby@niva.no; Stabbetorp, Odd [Norwegian Institute for Nature Research (NINA), Gaustadalleen 21, NO-0349 Oslo (Norway)], E-mail: odd.stabbetorp@nina.no; Bakkestuen, Vegar [Norwegian Institute for Nature Research (NINA), Gaustadalleen 21, NO-0349 Oslo (Norway); Department of Botany, Natural History Museum, University of Oslo P.O. Box 1172 Blindern, NO-0318 Oslo (Norway)], E-mail: vegar.bakkestuen@nina.no

    2008-02-15T23:59:59.000Z

    Value assessment is a central element in an EIA for the understanding of the impacts of specified projects. The value assessment contains subjective elements and this may cause errors and difficulties in numeric value assessment methods. There is a need for transparent common criteria to promote discussion and understanding. A common criteria base already exists, but lack of communication between different management systems and different disciplines, all with different traditions in value assessment, makes the situation complex. In this article we have looked into the basic understanding of value linked to the investigation themes of natural environment, cultural heritage and society. The investigation themes linked to social science is difficult to incorporate into a common system, basically because they have less focus on land use and contain different value types. Much of the relevant literature about value assessment is linked to the assessment of sites of special interest as candidates for legal protection or conservation. In an EIA a much broader range of areas is introduced, including the 'every day landscape' with a lower and more general level of value. Together with a focus on mitigation and adjustments of plans, this results in a need for a more detailed value assessment scale than is normally in use today. We have suggested a new scale to ease communication between different disciplines and management systems. How we understand value is not constant over time, nor is the level of knowledge. This makes it necessary to sustain an ongoing debate on value assessment. The need for a dynamic value assessment system increases with the increasing use of database modelling, digital analysis of map data (GIS) etc. Lack of a ongoing value debate will rapidly lead to misleading and biased results.

  15. Evaluation of the EIA system on the Island of Mauritius and development of an environmental monitoring plan framework

    SciTech Connect (OSTI)

    Ramjeawon, T.; Beedassy, R

    2004-07-01T23:59:59.000Z

    The Environment Protection Act (EPA) in Mauritius provides for the application of an EIA license in respect of undertakings listed in its first schedule. Following the promulgation of the Act in June 1993, the Department of Environment (DOE) is issuing an average of 125 EIA licenses yearly. In general, the review exercise of an environmental impact assessment (EIA) is terminated once the license has been granted. The aim of this project was to evaluate the EIA system in Mauritius and to identify its weaknesses and strengths. One of the main weaknesses, besides the lack of EIA audits, is the absence of EIA follow-up monitoring. It is necessary to distinguish between monitoring done for regulatory purposes (compliance monitoring) and environmental monitoring related to the EIA. With the growth of the tourism industry on the island, coastal development projects have the potential to cause significant environmental impacts . A sample of EIA reports pertaining to this sector was assessed for its quality and follow-up mechanisms. Proposals for the contents of EIA Prediction Audits, Environmental Monitoring Plans (EMP) and the format for an EMP report are made.

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

    SciTech Connect (OSTI)

    Finley, Cathy [WindLogics

    2014-04-30T23:59:59.000Z

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

  17. Forecasting consumer products using prediction markets

    E-Print Network [OSTI]

    Trepte, Kai

    2009-01-01T23:59:59.000Z

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

  18. 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 ...

  19. 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 ...

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

    E-Print Network [OSTI]

    Kemner, Ken

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

  1. 1995 shipment review & five year forecast

    SciTech Connect (OSTI)

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

    1996-01-01T23:59:59.000Z

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

  2. 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

  3. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

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

  4. Short and Long-Term Perspectives: The Impact on Low-Income Consumers of Forecasted Energy Price Increases in 2008 and A Cap & Trade Carbon Policy in 2030

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred [ORNL

    2008-01-01T23:59:59.000Z

    The Department of Energy's Energy Information Administration (EIA) recently released its short-term forecast for residential energy prices for the winter of 2007-2008. The forecast indicates increases in costs for low-income consumers in the year ahead, particularly for those using fuel oil to heat their homes. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation's low-income households by primary heating fuel type, nationally and by Census Region. The report provides an update of bill estimates provided in a previous study, "The Impact Of Forecasted Energy Price Increases On Low-Income Consumers" (Eisenberg, 2005). The statistics are intended for use by policymakers in the Department of Energy's Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2008 fiscal year. In addition to providing expenditure forecasts for the year immediately ahead, this analysis uses a similar methodology to give policy makers some insight into one of the major policy debates that will impact low-income energy expenditures well into the middle decades of this century and beyond. There is now considerable discussion of employing a cap-and-trade mechanism to first limit and then reduce U.S. emissions of carbon into the atmosphere in order to combat the long-range threat of human-induced climate change. The Energy Information Administration has provided an analysis of projected energy prices in the years 2020 and 2030 for one such cap-and-trade carbon reduction proposal that, when integrated with the RECS 2001 database, provides estimates of how low-income households will be impacted over the long term by such a carbon reduction policy.

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

    E-Print Network [OSTI]

    Lekov, Alex

    2011-01-01T23:59:59.000Z

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

  6. 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

  7. Calculator simplifies field production forecasting

    SciTech Connect (OSTI)

    Bixler, B.

    1982-05-01T23:59:59.000Z

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

  8. This research is partially supported by NSF under grant 9972883-EIA, 9974255-IIS, and 9983249-EIA, and by grants from IBM, NCR, Telcordia, and TAILOR: A Record Linkage Toolbox*

    E-Print Network [OSTI]

    Elmagarmid, Ahmed K.

    * This research is partially supported by NSF under grant 9972883-EIA, 9974255-IIS, and 9983249-EIA that ensures the quality of data stored in real-world databases. Data cleaning prob- lems are frequently encountered in many research areas, such as knowledge discovery in databases, data ware- housing, system

  9. A critique of the performance of EIA within the offshore oil and gas sector

    SciTech Connect (OSTI)

    Barker, Adam, E-mail: adam.barker@manchester.ac.uk; Jones, Carys, E-mail: carys.jones@manchester.ac.uk

    2013-11-15T23:59:59.000Z

    The oil and gas sector is a key driver of the offshore economy. Yet, it is also associated with a number of unwanted environmental impacts which potentially threaten the long term economic and environmental viability of marine ecosystems. Environmental Impact Assessment (EIA) can potentially make a significant contribution to the identification and management of adverse impacts through the promotion of evidence based decision making. However, the extent to which EIA has been embraced by key stakeholders is poorly understood. On this basis, this paper provides an initial evaluation of EIA performance within the oil and gas sector. The methodology adopted for the paper consisted of the structured review of 35 Environmental Statements (ESs) along with interviews with regulators, operators, consultants and advisory bodies. The findings reveal a mixed picture of EIA performance with a significant number of ESs falling short of satisfactory quality and a tendency for the process to be driven by compliance rather than best practice. -- Highlights: • Concerns identified relating to impacts of offshore oil and gas industry. • Research assesses performance of EIA in addressing impacts. • Findings highlight weak quality standards and procedural deficiencies. • Institutional reforms identified in order to improve practice.

  10. Reform of the EIA process in Indonesia: improving the role of public involvement

    SciTech Connect (OSTI)

    Purnama, Dadang

    2003-07-01T23:59:59.000Z

    The implementation of Environmental Impact Assessment (EIA) as a planning tool has been utilised for a relatively long time in Indonesia. It was introduced formally through the Act No. 4/1982. Supporting regulation was established in 1986 when Government Regulation No. 29 was enacted. After developing the EIA system for 14 years, Indonesia finally recognized the importance of emphasizing public involvement in the EIA guidelines of 2000. EIA in the previous Indonesian regulations, i.e. Regulation No. 29/1986 and No. 51/1993, did not have provisions for direct public involvement. The Indonesian Government Regulation No. 27/1999 is currently accommodating the above issue. Guidelines for public announcement and public involvement have been introduced in a decree issued by the Head of Indonesia's Environmental Impact Management Agency No. KepDal 08/2000. This was officially enacted on 7 November 2000 in response to the demand for more public involvement, an issue that was ambiguous in the previous legislation. This paper discusses: the implementation of the new guidelines; what has been achieved; and the challenges during implementation. While the paper focuses its review on the Indonesian EIA system, Indonesia's experience is relevant to many other developing countries that are starting to adopt public involvement in their decision-making processes.

  11. Environmental agreements, EIA follow-up and aboriginal participation in environmental management: The Canadian experience

    SciTech Connect (OSTI)

    O'Faircheallaigh, Ciaran [Department of Politics and Public Policy, Griffith Business School, Griffith University, Brisbane, Nathan, Queensland 4111 (Australia)]. E-mail: Ciaran.Ofaircheallaigh@griffith.edu.au

    2007-05-15T23:59:59.000Z

    During the last decade a number of environmental agreements (EAs) have been negotiated in Canada involving industry, government and Aboriginal peoples. This article draws on the Canadian experience to consider the potential of such negotiated agreements to address two issues widely recognised in academic and policy debates on environmental impact assessment (EIA) and environmental management. The first relates to the need to secure indigenous participation in environmental management of major projects that affect indigenous peoples. The second and broader issue involves the necessity for specific initiatives to ensure effective follow-up of EIA. The Canadian experience indicates that negotiated environmental agreements have considerable potential to address both issues. However, if this potential is to be realized, greater effort must be made to develop structures and processes specifically designed to encourage Aboriginal participation; and EAs must themselves provide the financial and other resource required to support EIA follow-up and Aboriginal participation.

  12. An assessment of the quality of selected EIA data series: Coal data, 1983--1988

    SciTech Connect (OSTI)

    Not Available

    1991-11-25T23:59:59.000Z

    The purpose of this report is to present information on the quality of some of the Energy Information Administration`s (EIA) coal data. This report contains discussions of data on production, direct labor hours, recoverable reserves, and prices from 1983 through 1988. Chapter 2 of this report presents a summary of the EIA coal data collection and identifies other sources providing similar data. Chapters 3 and 4 focus on data on coal production and direct labor hours, respectively. Detailed comparisons with data from the Mine Safety and Health Administration (MSHA) and State mining agencies are presented. Chapter 5 examines recoverable reserves. Included are internal comparisons as well as comparisons with other published reserve-related data, namely those of BXG, Inc. Chapter 6 describes how EIA obtains estimates of coal prices and discusses the variability in the prices caused by factors such as mine type, coal rank, and region. 5 figs., 5 tabs.

  13. A method for the assessment of changes in environmental perception during an EIA process

    SciTech Connect (OSTI)

    Peterlin, Monika [Institute for Water of the Republic of Slovenia, Hajdrihova 28c, Ljubljana (Slovenia)], E-mail: monika.peterlin@guest.arnes.si; Kross, Burton C. [Management Resources Network Inc., 6933 Sedgwick, Fort Collins, Colorado (United States); Kontic, Branko [Jozef Stefan Institute, Jamova 39, 1000 Ljubljana (Slovenia)

    2008-11-15T23:59:59.000Z

    Changes in environmental perception during an EIA process among the general population (the public) and employees of the Port of Koper were measured. The method of measurement addresses the statistical significance of the influence of the content, form, mode, providers of environmental information, institutional constraint and other factors. Opinions about environmental issues were collected in both groups prior to and after the provision of information in the EIA process. The difference formed the basis for an assessment of how environmental information provided during an EIA process contributes to environmental perception. The results show that difference in opinions about the impact of the Port between the two groups became smaller when comparing the first and second survey. In relation to the opinions of the employees, institutional constraint was recognised.

  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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible for Renewable Energy: Grid IntegrationReport AvailableForecasting NREL researchers use

  15. Quality of Cultural Heritage in EIA; twenty years of experience in Norway

    SciTech Connect (OSTI)

    Lindblom, Inge, E-mail: inge.lindblom@niku.no

    2012-04-15T23:59:59.000Z

    The aim of this paper is to clarify and discuss how quality, relevance, attitudes, beliefs and transfer value act as underlying driving forces in the development of the Cultural Heritage theme in EIAs. One purpose is to identify and discuss some conditions that can better environmental assessment in order to increase the significance of EIA in decision-making with regard to Cultural Heritage. The main tools used are different research methods designed for analyses of quality and quality changes, primarily based on the relevant opinions of 160 people occupied with Cultural Heritage in EIA in Norway. The study is based on a review of 40 types of EIAs from 1991 to 2000, an online questionnaire to 319 (160 responded) individuals from 14 different backgrounds, and interviews with three institutions in Sweden and Denmark. The study confirms a steadily increasing quality on EIRs over time, parallel with an improvement of the way in which Cultural Heritage is treated in EIA. This is supported by both the interviews and the qualitative comments regarding the survey. Potential for improvements is shown to be a need for more detailed background material as well as more use of adequate methods. The survey shows the existence of a wide variety of negative views, attitudes and beliefs, but the consequences of this are difficult to evaluate. However, most certainly, negative attitudes and beliefs have not been powerful enough to be detrimental to the quality of Cultural Heritage component, as nothing in the study indicates that negative attitudes and myths are undermining the system of EIA. The study shows the importance of having on-going discussions on quality and quality change over time by people involved in EIA, and how this is a necessary condition for successful implementation and acceptance. Beliefs and negative attitudes can also be a catalyst for developing better practice and advancing new methodology. In addition, new EIA countries must be prepared for several years of development and improvements after implementation. This is important in order to gain acceptance from the bureaucracy, especially from the Cultural Heritage authorities and local population.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, WeeklyElectricitylong Form EIA-7AEvents 2015 EIA EnergyApril

  17. Page 1 EIA-815, Monthly Bulk Terminal and Blender Report U. S. ENERGY INFORMATION ADMINISTRATION

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J uP2.EIA-815, Monthly

  18. EIA-0441: BLM Notice of Intent to Prepare an Environmental Impact Statement

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directed offOCHCO2: Final Environmental Assessment EA-1972:EERE EnergyStar StateAboutEIA Cases EIA Cases RSS|

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

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

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

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

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

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

  1. Solid low-level waste forecasting guide

    SciTech Connect (OSTI)

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

    1995-03-01T23:59:59.000Z

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

  2. Geothermal wells: a forecast of drilling activity

    SciTech Connect (OSTI)

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

    1981-07-01T23:59:59.000Z

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

  3. Online Forecast Combination for Dependent Heterogeneous Data

    E-Print Network [OSTI]

    Sancetta, Alessio

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

  4. The Value of Wind Power Forecasting

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

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

  5. The effectiveness of the Finnish EIA system - What works, what doesn't, and what could be improved?

    SciTech Connect (OSTI)

    Poeloenen, Ismo, E-mail: Ismo.Polonen@uef.f [University of Eastern Finland, Department of Law, P.O. Box 111, FIN-80101 Joensuu (Finland); Hokkanen, Pekka, E-mail: pekka.hokkanen@ely-keskus.f [Centre for Economic Development, Transport and the Environment for Central Finland, P.O. Box 250, FIN-40101 (Finland); Jalava, Kimmo, E-mail: kimmo.j.jalava@jyu.f [University of Jyvaeskylae, Department of Biological and Environmental Science, P.O. Box 35, FIN-40014 University of Jyvaeskylae (Finland)

    2011-03-15T23:59:59.000Z

    The article summarises the results of a multidisciplinary research project on the effectiveness of the Finnish EIA system. It examines the main strengths and weaknesses of EIA as a preventive and participatory environmental management tool. The study concludes that EIA has achieved a meaningful role in the environmental policy toolbox in Finland and has clearly enhanced the possibilities for high-quality environmental decision making. The research cites the liaison authority system as a clear strength of the Finnish EIA system in its enabling a single regional authority to specialise in and gain wide experience on EIA issues. In examining potential weaknesses of the regime, the article concludes that the key constraint on EIA effectiveness is inadequacy of the action-forcing mechanisms at the decision-making phase. The primary means to improve the effectiveness of EIA would be to strengthen the legal provisions on development consents. On the whole, the research indicates that the EU and Finnish legislation and guidance on environmental impact assessment provide a good framework for effective utilisation of the instrument.

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

    E-Print Network [OSTI]

    Kamat, Vineet R.

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

  7. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

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

  8. 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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-01-01T23:59:59.000Z

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

  10. A quantitative method to analyze the quality of EIA information in wind energy development and avian/bat assessments

    SciTech Connect (OSTI)

    Chang, Tony, E-mail: tc282@nau.edu [Environmental Science and Policy Program, School of Earth Science and Environmental Sustainability, Northern Arizona University, 602 S Humphreys P.O. Box 5694, Flagstaff, AZ, 86011 (United States); Nielsen, Erik, E-mail: erik.nielsen@nau.edu [Environmental Science and Policy Program, School of Earth Science and Environmental Sustainability, Northern Arizona University, 602 S Humphreys P.O. Box 5694, Flagstaff, AZ, 86011 (United States); Auberle, William, E-mail: william.auberle@nau.edu [Civil and Environmental Engineering Program, Department of Civil and Environmental Engineering, Northern Arizona University, 2112 S Huffer Ln P.O. Box 15600, Flagstaff, AZ, 860011 (United States); Solop, Frederic I., E-mail: fred.solop@nau.edu [Political Science Program, Department of Politics and International Affairs, Northern Arizona University, P.O. Box 15036, Flagstaff, AZ 86001 (United States)

    2013-01-15T23:59:59.000Z

    The environmental impact assessment (EIA) has been a tool for decision makers since the enactment of the National Environmental Policy Act (NEPA). Since that time, few analyses have been performed to verify the quality of information and content within EIAs. High quality information within assessments is vital in order for decision makers, stake holders, and the public to understand the potential impact of proposed actions on the ecosystem and wildlife species. Low quality information has been a major cause for litigation and economic loss. Since 1999, wind energy development has seen an exponential growth with unknown levels of impact on wildlife species, in particular bird and bat species. The purpose of this article is to: (1) develop, validate, and apply a quantitative index to review avian/bat assessment quality for wind energy EIAs; and (2) assess the trends and status of avian/bat assessment quality in a sample of wind energy EIAs. This research presents the development and testing of the Avian and Bat Assessment Quality Index (ABAQI), a new approach to quantify information quality of ecological assessments within wind energy development EIAs in relation to avian and bat species based on review areas and factors derived from 23 state wind/wildlife siting guidance documents. The ABAQI was tested through a review of 49 publicly available EIA documents and validated by identifying high variation in avian and bat assessments quality for wind energy developments. Of all the reviewed EIAs, 66% failed to provide high levels of preconstruction avian and bat survey information, compared to recommended factors from state guidelines. This suggests the need for greater consistency from recommended guidelines by state, and mandatory compliance by EIA preparers to avoid possible habitat and species loss, wind energy development shut down, and future lawsuits. - Highlights: Black-Right-Pointing-Pointer We developed, validated, and applied a quantitative index to review avian/bat assessment quality for wind energy EIAs. Black-Right-Pointing-Pointer We assessed the trends and status of avian/bat assessment quality in a sample of wind energy EIAs. Black-Right-Pointing-Pointer Applied index to 49 EIA documents and identified high variation in assessment quality for wind energy developments. Black-Right-Pointing-Pointer For the reviewed EIAs, 66% provided inadequate preconstruction avian and bat survey information.

  11. An adaptive neural network approach to one-week ahead load forecasting

    SciTech Connect (OSTI)

    Peng, T.M. (Pacific Gas and Electric Co., San Francisco, CA (United States)); Hubele, N.F.; Karady, G.G. (Arizona State Univ., Tempe, AZ (United States))

    1993-08-01T23:59:59.000Z

    A new neural network approach is applied to one-week ahead load forecasting. This approach uses a linear adaptive neuron or adaptive linear combiner called Adaline.'' An energy spectrum is used to analyze the periodic components in a load sequence. The load sequence mainly consists of three components: base load component, and low and high frequency load components. Each load component has a unique frequency range. Load decomposition is made for the load sequence using digital filters with different passband frequencies. After load decomposition, each load component can be forecasted by an Adaline. Each Adaline has an input sequence, an output sequence, and a desired response-signal sequence. It also has a set of adjustable parameters called the weight vector. In load forecasting, the weight vector is designed to make the output sequence, the forecasted load, follow the actual load sequence; it also has a minimized Least Mean Square error. This approach is useful in forecasting unit scheduling commitments. Mean absolute percentage errors of less than 3.4 percent are derived from five months of utility data, thus demonstrating the high degree of accuracy that can be obtained without dependence on weather forecasts.

  12. Show me the Data! EIA.gov Just Got Even Better

    Broader source: Energy.gov [DOE]

    The U.S. Energy Information Administration (EIA) launched a new website that includes new features, even more information, and improved navigation. This is the latest in a comprehensive initiative to improve the agency's capacity to achieve its mission -- collecting, analyzing, and disseminating independent and impartial energy information.

  13. Implementing the Espoo Convention in transboundary EIA between Germany and Poland

    SciTech Connect (OSTI)

    Albrecht, Eike [Brandenburg University of Technology of Cottbus (BTU) Centre for Law and Administration, Konrad-Wachsmann-Allee 1, D - 03046 Cottbus (Germany)], E-mail: albrecht@tu-cottbus.de

    2008-08-15T23:59:59.000Z

    Poland and Germany have a long common border which leads to the necessity to cooperate and consult each other in the case of large-scale projects or infrastructure measures likely to cause negative transboundary effects on the environment. There are already binding provisions for transboundary EIA. In the area of the UN Economic Commission for Europe (UNECE), transboundary EIA is intended to be legally binding for the Member States by the Espoo Convention which was ratified by Germany 8.8.2002 and by Poland 12.6.1997. Due to corresponding directives, the same is applicable in the context of the European Union. In German legislation, this issue is regulated by Art. 8 of the Federal EIA Act in regard to transboundary participation of administration and by Art. 9a in respect of transboundary public participation. However, these EIA regulations on transboundary participation do not surpass a certain detail level, as they have to be applied between Germany and all neighbouring states. Therefore both countries decided to agree on more detailed provisions in particular regarding procedural questions. During the 12th German-Polish Environmental Council, Germany and Poland reached an agreement on 11.4.2006 in Neuhardenberg/Brandenburg an agreement upon the implementation of the Espoo Convention, the so called Neuhardenberg Agreement. This article assesses the agreement under consideration of already existing law and discusses major improvements and problems.

  14. Birthday Forgery Attack on 128-EIA3(V ersion1.5) Raja Zeshan Haider

    E-Print Network [OSTI]

    on the Carter-Wegman family of universal hash functions [3].128-EIA3 is bit dif- ferent to Carter-Wegman family of universal hash functions in terms of genera- tion of it's masking value.In Carter-Wegman family of universal

  15. The Canadian EIA Process: The Purpose, The Process, The Players and The Pitfalls

    E-Print Network [OSTI]

    Boisvert, Jeff

    Need to Know This? · As the Keystone Pipeline and Prosperity Gold-Copper Mine Project have indicated approvals are given the basis for limits, design criteria, operating parameters and monitoring are the EIA to be addressed, from the beginning to the end, should not be limited to problems of engineering and construction

  16. Annual report of the origin of natural gas liquids production form EIA-64A

    SciTech Connect (OSTI)

    NONE

    1995-12-31T23:59:59.000Z

    The collection of basic, verifiable information on the Nation`s reserves and production of natural gas liquids (NGL) is mandated by the Federal Energy Administration Act of 1974 (FEAA) (Public Law 93-275) and the Department of Energy Organization Act of 1977 (Public Law 95-91). Gas shrinkage volumes reported on Form EIA-64A by natural gas processing plant operators are used with natural gas data collected on a {open_quotes}wet after lease separation{close_quotes} basis on Form EIA-23, Annual Survey of Domestic Oil and Gas Reserves, to estimate {open_quotes}dry{close_quotes} natural gas reserves and production volumes regionally and nationally. The shrinkage data are also used, along with the plant liquids production data reported on Form EIA-64A, and lease condensate data reported on Form EIA-23, to estimate regional and national gas liquids reserves and production volumes. This information is the only comprehensive source of credible natural gas liquids data, and is required by DOE to assist in the formulation of national energy policies.

  17. 1992 five year battery forecast

    SciTech Connect (OSTI)

    Amistadi, D.

    1992-12-01T23:59:59.000Z

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

  18. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2008-01-07T23:59:59.000Z

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

  1. 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...

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

    E-Print Network [OSTI]

    Heinemann, Detlev

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

  3. Alternative methods for forecasting GDP Dominique Gugan

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

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

  4. A NEW APPROACH FOR EVALUATING ECONOMIC FORECASTS

    E-Print Network [OSTI]

    Vertes, Akos

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

  5. 2013 Midyear Economic Forecast Sponsorship Opportunity

    E-Print Network [OSTI]

    de Lijser, Peter

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

  6. Dynamic Algorithm for Space Weather Forecasting System

    E-Print Network [OSTI]

    Fischer, Luke D.

    2011-08-08T23:59:59.000Z

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

  7. 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

  8. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

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

  9. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1994-02-01T23:59:59.000Z

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

  10. Ensemble Tropical Rainfall Potential (eTRaP) Forecasts ELIZABETH E. EBERT

    E-Print Network [OSTI]

    Ebert, Beth

    for more than 300 deaths in the United States during the period 1970­99, including 50 deaths related landfall in the United States between 2004 and 2008 shows that the eTRaP rain amounts are more accurate-h rain forecast based on estimated rain rates from microwave sensors aboard polar

  11. Forecasting electricity spot market prices with a k-factor GIGARCH process.

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Forecasting electricity spot market prices with a k-factor GIGARCH process. Abdou Kâ Diongue this method to the German electricity price market for the period August 15, 2000 - De- cember 31, 2002 and we, Pelacchi and Venturini (2002) investigate several markets. In addition, electricity spot prices exhibit

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

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

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

  13. U.S. Energy Information Administration (EIA) - Sector

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

    electricity production as relatively low prices make natural gas more competitive with coal. Over the projection period, the natural gas share of total power generation grows,...

  14. U.S. Energy Information Administration (EIA) - Source

    Gasoline and Diesel Fuel Update (EIA)

    Oil production, particulary from tight oil plays....Read full section Coal's share of electric power generation falls over the projected period ...Read full section With more...

  15. U.S. Energy Information Administration (EIA) - Source

    Gasoline and Diesel Fuel Update (EIA)

    expansions are built during the projection period besides those already under construction. Further, approximately 200,000 barrels per day of capacity is retired, beginning...

  16. U.S. Energy Information Administration (EIA) - Source

    Gasoline and Diesel Fuel Update (EIA)

    U.S. Energy Demand exec summary Executive Summary The rate of growth in energy use slows over the projection period, reflecting moderate population growth, an extended economic...

  17. U.S. Energy Information Administration (EIA) - Pub

    Gasoline and Diesel Fuel Update (EIA)

    period. The projected growth results largely from a significant increase in onshore crude oil production, particularly from shale and other tight formations, which has been spurred...

  18. LHCb Computing Resources: 2011 re-assessment, 2012 request and 2013 forecast

    E-Print Network [OSTI]

    Graciani, R

    2011-01-01T23:59:59.000Z

    This note covers the following aspects: re-assessment of computing resource usage estimates for 2011 data taking period, request of computing resource needs for 2012 data taking period and a first forecast of the 2013 needs, when no data taking is foreseen. Estimates are based on 2010 experienced and last updates from LHC schedule, as well as on a new implementation of the computing model simulation tool. Differences in the model and deviations in the estimates from previous presented results are stressed.

  19. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST

    E-Print Network [OSTI]

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

  20. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

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

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

    SciTech Connect (OSTI)

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

    2011-10-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Islam, M. Saif

    Page 1 Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will take a few moments to answer this short survey

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

    E-Print Network [OSTI]

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

  5. U.S. Energy Information Administration (EIA) - Source

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

    gas production increases throughout the projection period, allowing the United States to transition from a et importer to a net exporter of natural gas....Read full section Power...

  6. U.S. Energy Information Administration (EIA) - Source

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

    gas production increases throughout the projection period, allowing the United States to transition from a net importer to a net exporter of natural gas....Read full section Mkt...

  7. U.S. Energy Information Administration (EIA) - Data

    Gasoline and Diesel Fuel Update (EIA)

    projection period. The reduction occurs in response to the EPA's Cross- State Air Pollution Rule (CSAPR) and Mercury and Air Toxics Standards (MATS) 138. Although SO2 is not...

  8. U.S. Energy Information Administration (EIA) - Pub

    Gasoline and Diesel Fuel Update (EIA)

    than over a longer period, because the group of variables-such as population, productivity, and labor force growth-that influence long-run economic growth is smaller than the...

  9. U.S. Energy Information Administration (EIA) - Pub

    Gasoline and Diesel Fuel Update (EIA)

    than over a longer period, because the group of variables-such as population, productivity, and labor force growth-that are used to influence long-run economic growth is...

  10. Natural Gas Storage Report, Weekly EIA-AGA Comparison

    Reports and Publications (EIA)

    2002-01-01T23:59:59.000Z

    This report is intended to aid data users by examining differences between the Energy Information Administration and American Gas Association weekly surveys and comparing the results of the two surveys for the brief period of time in which they overlapped.

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

    SciTech Connect (OSTI)

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

    1985-01-01T23:59:59.000Z

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

  12. EIA model documentation: Petroleum Market Model of the National Energy Modeling System

    SciTech Connect (OSTI)

    NONE

    1994-12-30T23:59:59.000Z

    The purpose of this report is to define the objectives of the Petroleum Market Model (PMM), describe its basic approach, and provide detail on how it works. This report is intended as a reference document for model analysts, users, and the public. Documentation of the model is in accordance with EIA`s legal obligation to provide adequate documentation in support of its models (Public Law 94-385, section 57.b.2). The PMM models petroleum refining activities, the marketing of products, the production of natural gas liquids and domestic methanol, projects petroleum provides and sources of supplies for meeting demand. In addition, the PMM estimates domestic refinery capacity expansion and fuel consumption.

  13. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

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

  14. Wind Speed Forecasting for Power System Operation 

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

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

  15. 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

  16. Wind Speed Forecasting for Power System Operation

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

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

  17. 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 ...

  18. Essays in International Macroeconomics and Forecasting

    E-Print Network [OSTI]

    Bejarano Rojas, Jesus Antonio

    2012-10-19T23:59:59.000Z

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

  19. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01T23:59:59.000Z

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

  20. Uncovering the factors that can support and impede post-disaster EIA practice in developing countries: The case of Aceh Province, Indonesia

    SciTech Connect (OSTI)

    Gore, Tom; Fischer, Thomas B., E-mail: fischer@liverpool.ac.uk

    2014-01-15T23:59:59.000Z

    The close relationship between environmental degradation and the occurrence and severity of disaster events has in recent years raised the profile of environmental assessment (EA) in the disaster management field. EA has been identified as a potentially supportive tool in the global effort to reduce disaster risk. As a component of this, attention has been brought specifically to the importance of the application of EA in the aftermath of disaster events in order to help prevent recurrence and promote sustainability. At the same time, however, it has also been recognised that post-disaster environments may be unfavourable to such practices. Looking at the practice of environmental impact assessment (EIA), this paper reports on a study which sought to identify more specifically the factors which can both support and hinder such practice following disaster events in a developing country context. Analysing the situation in Aceh Province, Indonesia, after the impact of two tsunamigenic earthquakes in late 2004 and early 2005, it is concluded that if EIA is to have a central role in the post-disaster period, pre-disaster preparation could be a key. -- Highlights: • Close relationship between environmental degradation and occurrence/severity of disaster events has raised profile of EA. • EA as a potentially supportive tool in the global effort to reduce disaster risk • Application of EA in the aftermath of disaster events to help prevent recurrence and promote sustainability • The paper looks at factors which can both support and hinder EA following disaster events in a developing country context. • We analyse the situation in Aceh Province, Indonesia, after the impact of two tsunamigenic earthquakes in 2004 and 2005.

  1. Evolution of the U.S. Energy Service Company Industry: Market Size and Project Performance from 1990-2008

    E-Print Network [OSTI]

    Goldman, Charles A.

    2013-01-01T23:59:59.000Z

    EIA forecasts of future electricity and natural gas pricesand natural gas prices were escalated to 2030 using annual EIA price forecastand natural gas prices were escalated to 2030 using annual EIA price forecast

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01T23:59:59.000Z

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

  8. An analysis framework for characterizing and explaining development of EIA legislation in developing countries-Illustrated for Georgia, Ghana and Yemen

    SciTech Connect (OSTI)

    Kolhoff, Arend J., E-mail: akolhoff@eia.nl [Netherlands Commission for Environmental Assessment, P.O. Box 2345, 3500 GH Utrecht (Netherlands); Driessen, Peter P.J., E-mail: p.driessen@uu.nl [Copernicus Institute of Sustainable Development, Utrecht University, P.O. Box 80115, 3508 TC (Netherlands); Runhaar, Hens A.C., E-mail: h.a.c.runhaar@uu.nl [Copernicus Institute of Sustainable Development, Utrecht University, P.O. Box 80115, 3508 TC (Netherlands)

    2013-01-15T23:59:59.000Z

    Actors in the field of international development co-operation supporting the development of EIA legislation in developing countries often do not achieve the results envisaged. The performance of EIA in these countries often remains weak. One reason, we assume, is that often those actors support the establishment of overly ambitious EIA legislation that cannot achieve its objectives in the light of constraining contexts. To provide more effective support we need to better understand the enabling and constraining contextual factors that influence the development of EIA legislation and to which support actors should align itself. In this article a new analysis framework for classifying, characterizing and explaining the development of EIA legislation is described, measured in terms of ambition levels. Ambitions are defined as intentions the EIA authorities aim to fulfill, expressed in formal EIA legislation. Three country cases, Yemen, Georgia and Ghana are used to illustrate the usefulness of our framework and as a first test to refine the framework. We have formulated the following five hypotheses that complement and refine our analysis framework. One, EIA legislation may develop multilinearly in terms of ambition levels. Two, ambitions in EIA legislation seem to be influenced to a great extent by the power and capacity of, on the one hand, the environmental authorities supporting EIA and, on the other hand, the sector authorities hindering the development of EIA. Three, the political system is the most important context factor influencing the rules of policy-making and the power of the different actors involved. Four, the importance of context factors on the development of ambitions is dependent on the phase of EIA system development. Five, some ambitions seem to be influenced by particular factors; for instance the ambitions for the object of study seem to be influenced by the level of environmental awareness of the sector ministries and parliament. The analysis framework may also assist actors involved in the development of EIA legislation in setting ambitions for EIA legislation that are feasible within the context in which it will be developed and implemented. Application of a country-specific EIA model would seem to be the preferred model to develop EIA legislation because by taking capacities of actors and context factors as a starting point, it offers more potential to well-performing EIA systems. - Highlights: Black-Right-Pointing-Pointer EIA systems develop from less to high ambitious and sometimes vice versa. Black-Right-Pointing-Pointer Ambitions in EIA legislation are determined by the capacity of environment- and sector authority. Black-Right-Pointing-Pointer The political system is the most important context factor explaining the ambitions of an EIA system. Black-Right-Pointing-Pointer An analysis framework developed to measure EIA system ambitions might help to setambitions.

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

    SciTech Connect (OSTI)

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

    2014-05-01T23:59:59.000Z

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

  10. UK and Italian EIA systems: A comparative study on management practice and performance in the construction industry

    SciTech Connect (OSTI)

    Bassi, Andrea, E-mail: ab395@bath.co.uk [University of Bath, Faculty of Engineering and Design, Claverton Down, Bath BA2 7AY (United Kingdom); Howard, Robert, E-mail: robhoward@constcom.demon.co.uk [Construction Communications, 8 Cotton& #x27; s Field, Dry Drayton, Cambridge CB23 8DG (United Kingdom); Geneletti, Davide, E-mail: davide.geneletti@ing.unitn.it [Sustainability Science Program, Harvard University, 79 JFK Street, Cambridge, MA 02138 (United States); Dept. of Civil and Environmental Engineering, University of Trento, Via Mesiano, 77 38123 Trento (Italy); Ferrari, Simone, E-mail: simone.ferrari@polimi.it [Dept. BEST, Building Environment Science and Technology, Politecnico di Milano, Via Bonardi, 3 20133 Milano (Italy)

    2012-04-15T23:59:59.000Z

    This study evaluates and contrasts the management practice and the performance that characterise Environmental Impact Assessments (EIA) in Italy and in the UK. The methodology relies on the investigation of six carefully selected case studies, critically reviewed by referring to EIA and project design information, as well as collecting the opinion of key project participants. The study focuses on the construction industry and on specific key sectors like infrastructure for transport and renewable energy and commercial and tourism development. A main term of reference for the analyses has been established by critically reviewing international literature so as to outline common good practice, requirements for the enhancement of sustainability principles and typically incurred drawbacks. The proposed approach enhances transfer of knowledge and of experiences between the analyzed contexts and allows the provision of guidelines for practitioners. Distinctive differences between the UK and the Italian EIA systems have been detected for pivotal phases and elements of EIA, like screening, scoping, analysis of alternatives and of potential impacts, definition of mitigation strategies, review, decision making, public participation and follow up. - Highlights: Black-Right-Pointing-Pointer The Italian and the UK Environmental Impact Assessment systems are compared. Black-Right-Pointing-Pointer The research is centred on the construction industry. Black-Right-Pointing-Pointer Issues and shortcomings are analysed by investigating six case studies. Black-Right-Pointing-Pointer Integration of EIA with sustainability principles is appraised. Black-Right-Pointing-Pointer General guidelines are provided to assist practitioners in the two national contexts.

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    range of different plausible price projections, using eitherreference-case fuel price projection from the EIA or someprices and the AEO gas price projections over the past two

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

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Singhal, Gaurav

    2012-10-19T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Datta, Shoumen

    2008-07-31T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Washington at Seattle, University of

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

  16. The effect of multinationality on management earnings forecasts

    E-Print Network [OSTI]

    Runyan, Bruce Wayne

    2005-08-29T23:59:59.000Z

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

  17. Improved water allocation utilizing probabilistic climate forecasts: Short-term water contracts in a risk management framework

    E-Print Network [OSTI]

    Arumugam, Sankar

    . Thus, integrated supply and demand management can be achieved. In this paper, a single period multiuser, forecast consumers, water managers and reservoir operators, have difficulty interpreting such products in a risk management framework A. Sankarasubramanian,1 Upmanu Lall,2 Francisco Assis Souza Filho,3

  18. LHCb Computing Resources: 2012 re-assessment, 2013 request and 2014 forecast

    E-Print Network [OSTI]

    Graciani Diaz, Ricardo

    2012-01-01T23:59:59.000Z

    This note covers the following aspects: re-assessment of computing resource usage estimates for 2012 data-taking period, request of computing resource needs for 2013, and a first forecast of the 2014 needs, when restart of data-taking is foreseen. Estimates are based on 2011 experience, as well as on the results of a simulation of the computing model described in the document. Differences in the model and deviations in the estimates from previous presented results are stressed.

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

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Boyer, Edmond

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

  2. FORECASTING SOLAR RADIATION PRELIMINARY EVALUATION OF AN APPROACH

    E-Print Network [OSTI]

    Perez, Richard R.

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

  3. 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

  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 dedicated models to forecast the 12 individual months directly. Results indicate better performance is superior to naïve forecasts based on persistence and seasonality, and is better than results quoted

  5. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

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

  7. EIA Energy Efficiency-Iron and Steel Energy Intensity, 1998-2002

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at1,066,688 760,877SouthwestWisconsin profile Wisconsin8, 2009EIA9:

  8. Contact Us - U.S. Energy Information Administration (EIA) - U.S. Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting theCommercializationValidation andInformation Administration (EIA)

  9. EIA-914 Monthly Crude Oil, Lease Condensate, and Natural Gas Production Report Methodology

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.MajorMarkets 8, 3:00Markets 3,EIA-914 Monthly

  10. A Presentation for the DOE EIA 2013 Energy Conference, Washington, DC

    Gasoline and Diesel Fuel Update (EIA)

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

  11. www.eia.gov U.S. Energy Information Administration Independent Statistics & Analysis

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. Appliances by Climate6,1996 http://www.eia.doe.govEffects of

  12. EIA Report: U.S. Renewables Rise by 2040 | 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 DataDepartment of Energy Your Density Isn't Your Destiny:Revised Finding of98-F, Western22,EERE Solar SunShotAbsorption8, 2003SeptemberEIA

  13. 2014 EIA-821 SURVEY: LINE-BY-LINE REFERENCE GUIDE Kerosene

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAge Refining Air1, 2015 Financial4 EIA-821

  14. EIA-182, "Domestic Crude Oil First Purchase Report" Page 1

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment ActivitiesAgeDieselDieselJanuary 12,EIA revises1

  15. EIA-802, Weekly Product Pipeline Report Page 1 U. S. ENERGY INFORMATION ADMINISTRATION

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal Control EIA-802, Weekly

  16. EIA-803, Weekly Crude Oil Stocks Report Page 1 U. S. ENERGY INFORMATION ADMINISTRATION

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal Control EIA-802, Weekly3,

  17. EIA-820, Annual Refinery Report Page 1 U. S. DEPARTMENT OF ENERGY

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal2,7, MonthlyEIA

  18. FORM EIA-63B ANNUAL PHOTOVOLTAIC CELL/MODULE SHIPMENTS REPORT INSTRUCTIONS

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal2,7,7,of2014FORM EIA-28 -

  19. FORM EIA-860 ANNUAL ELECTRIC GENERATOR REPORT Approval: OMB No. 1905-0129

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal2,7,7,of2014FORM EIA-28

  20. FORM EIA-860M MONTHLY UPDATE TO ANNUAL ELECTRIC GENERATOR REPORT

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSite Name: Email: Terminal2,7,7,of2014FORM EIA-28

  1. Page 1 EIA-810, Monthly Refinery Report U. S. ENERGY INFORMATION ADMINISTRATION

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J uP2.

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J9 April

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J9 April18, 2015 New

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J9 April18, 2015 New0,

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J9 April18, 2015

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J9 April18, 2015April

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J9 April18,

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J9 April18,26, 2015

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J9 April18,26, 201515,

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

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) - HouseholdshortEIA-782A andS F J9 April18,26,

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13T23:59:59.000Z

    Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.

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

    E-Print Network [OSTI]

    Lang, K.

    1982-01-01T23:59:59.000Z

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

  13. EIA's role in the analysis of the Clean Air Act Amendments of 1990 and the development of the National Allowance Database

    SciTech Connect (OSTI)

    Beamon, J.A.; Linders, M.J. (Energy Information Administration, Washington, DC (United States))

    1993-01-01T23:59:59.000Z

    Throughout 1990 the Energy Information Administration (EIA) provided continuous data and analytic support to Congress during its deliberations on Title IV of the Clean Air Act Amendments of 1990 (CAA). Congress requested the Energy Information Administration (EIA) to review and analyze the sections that would affect electric utilities, specifically those relating to acid deposition (Title IV). By providing knowledgeable and impartial analysis, EIA clarified the likely effects of the various legislative proposals and helped Congress finalize the amendments. Even though the CAA is now law, EIA's efforts have not ended. During the analysis of the various proposals, EIA and EPA created a National Allowance Database (NAD). Now, under an agreement with the Environmental Protection Agency (EPA), a new version of the NAD is being developed to facilitate the implementation of the acid deposition provisions of the CAA. This article describes the analyses undertaken, points out where EIA's efforts led to improved understanding of the likely impacts of the CAA, and outlines EIA's continued efforts to assist EPA in the implementation of the amendments. 6 tabs.

  14. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

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

  15. Facebook IPO updated valuation and user forecasting

    E-Print Network [OSTI]

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

  16. Modeling of Uncertainty in Wind Energy Forecast

    E-Print Network [OSTI]

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

  17. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Sripada, Yaji

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

  18. Forecasting sudden changes in environmental pollution patterns

    E-Print Network [OSTI]

    Olascoaga, Maria Josefina

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

  19. New Concepts in Wind Power Forecasting Models

    E-Print Network [OSTI]

    Kemner, Ken

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

  20. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

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

  1. SIMULATION AND FORECASTING IN INTERMODAL CONTAINER TERMINAL

    E-Print Network [OSTI]

    Gambardella, Luca Maria

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

  2. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    NONE

    1996-08-01T23:59:59.000Z

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

  3. 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

  4. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27T23:59:59.000Z

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

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

    E-Print Network [OSTI]

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

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01T23:59:59.000Z

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

  8. From consultation to deliberation? Tracing deliberative norms in EIA frameworks in Swedish roads planning

    SciTech Connect (OSTI)

    Isaksson, Karolina, E-mail: karolina.isaksson@vti.s [Swedish National Road and Transport Research Institute, SE-581 95 Linkoeping (Sweden); Richardson, Tim, E-mail: tim@plan.aau.d [Department of Development and Planning, Aalborg University, Fibigerstraede 13, DK 9000, Aalborg (Denmark); Olsson, Krister, E-mail: kristero@infra.kth.s [Department of Planning and Environment, Royal Institute of Technology (KTH), 100 44 Stockholm (Sweden)

    2009-09-15T23:59:59.000Z

    This paper presents the results of an analysis of deliberative norms in the framework for Environmental Impact Assessment (EIA) in roads planning in Sweden. The more specific question is how this framework has responded to the shift towards more deliberative approaches to planning and decision making, advocated in planning theory and policy literature over the last decade. The analysis, which compares the current framework and guidance with an earlier iteration, identifies a shift towards deliberation; deliberative norms are present, and even dominate recent guidance. However, an instrumental norm permeates both the former and the current guidance, suggesting that even as a language of consultation is replaced by one of deliberation, the intention remains to secure and legitimise a smooth development pathway. Evidence from interviews with professionals working in the Swedish EIA system highlights the difficulties of navigating these uncertainties in practice. By opening up critical analysis of deliberative norms as they shape the conditions for practice, this study contributes to the continuous development of planning practice, by supporting a more normatively reflexive approach to framework-design.

  9. Steam System Forecasting and Management 

    E-Print Network [OSTI]

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

    1982-01-01T23:59:59.000Z

    process unit is not operating (down) is specified. If the process will be operating for the entire period, the word "LP" is displayed. PRODUCTION SCHEDULE 2/20/92 - 5/20/82 UNIT 1 A UP 2 B UP D 2./20-3./15 D 4.19. TO- 3 C D 2./20-3./15 D 4..../9. TO- 4 D 5 E D 4./15 TO- UP 6 F D 2./20-2./21 7 G UP 9 I UP 8 H D 2./20-3./13 D 3./27 TO- 10 J 11 K D 2./20 TO- 12 L UP 13 M UP UP 15 0 14 N UP D 2./20-2./24 D 3./7.-3./17 D 3./28 TO- 16 P 17 G D 4./1. TO- 19 R II 3...

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

    SciTech Connect (OSTI)

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

    1983-07-01T23:59:59.000Z

    The test application of the semi-objective (S-O) wind forecasting technique at three locations is described. The forecasting sites are described as well as site-specific forecasting procedures. Verification of the S-O wind forecasts is presented, and the observed verification results are interpreted. Comparisons are made between S-O wind forecasting accuracy and that of two previous forecasting efforts that used subjective wind forecasts and model output statistics. (LEW)

  11. Storm Water Analytical Period

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

    Protection Obeying Environmental Laws Individual Permit Storm Water Analytical Period Storm Water Analytical Period The Individual Permit authorizes the discharge of storm...

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

    SciTech Connect (OSTI)

    NONE

    1995-08-02T23:59:59.000Z

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

  13. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

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

    2014-12-30T23:59:59.000Z

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

  14. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

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

    2011-02-23T23:59:59.000Z

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

  15. 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.

    2011-10-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Not Available

    1984-03-01T23:59:59.000Z

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

  19. Road-corridor planning in the EIA procedure in Spain. A review of case studies

    SciTech Connect (OSTI)

    Loro, Manuel, E-mail: manuel.loro@upm.es [Department of Urban and Regional Planning and Environment, Civil Engineering School, Universidad Politécnica de Madrid, Prof. Aranguren s/n, 28040 Madrid (Spain) [Department of Urban and Regional Planning and Environment, Civil Engineering School, Universidad Politécnica de Madrid, Prof. Aranguren s/n, 28040 Madrid (Spain); Transport Research Centre (TRANSyT-UPM) Universidad Politécnica de Madrid, ETSI Caminos, Canales y Puertos, Prof. Aranguren s/n, 28040 Madrid (Spain); Centro de investigación del transporte, TRANSyT-UPM, ETSI Caminos, Canales y Puertos, Universidad Politécnica de Madrid, Prof. Aranguren s/n, 28040 Madrid (Spain); Arce, Rosa M., E-mail: rosa.arce.ruiz@upm.es [Department of Urban and Regional Planning and Environment, Civil Engineering School, Universidad Politécnica de Madrid, Prof. Aranguren s/n, 28040 Madrid (Spain); Transport Research Centre (TRANSyT-UPM) Universidad Politécnica de Madrid, ETSI Caminos, Canales y Puertos, Prof. Aranguren s/n, 28040 Madrid (Spain); Centro de investigación del transporte, TRANSyT-UPM, ETSI Caminos, Canales y Puertos, Universidad Politécnica de Madrid, Prof. Aranguren s/n, 28040 Madrid (Spain); Ortega, Emilio, E-mail: e.ortega@upm.es [Transport Research Centre (TRANSyT-UPM) Universidad Politécnica de Madrid, ETSI Caminos, Canales y Puertos, Prof. Aranguren s/n, 28040 Madrid (Spain) [Transport Research Centre (TRANSyT-UPM) Universidad Politécnica de Madrid, ETSI Caminos, Canales y Puertos, Prof. Aranguren s/n, 28040 Madrid (Spain); Centro de investigación del transporte, TRANSyT-UPM, ETSI Caminos, Canales y Puertos, Universidad Politécnica de Madrid, Prof. Aranguren s/n, 28040 Madrid (Spain); Department of Construction and Rural Roads, Forestry Engineering School, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid (Spain); and others

    2014-01-15T23:59:59.000Z

    The assessment of different alternatives in road-corridor planning must be based on a number of well-defined territorial variables that serve as decision making criteria, and this requires a high-quality preliminary environmental assessment study. In Spain the formal specifications for the technical requirements stipulate the constraints that must be considered in the early stages of defining road corridors, but not how they should be analyzed and ranked. As part of the feasibility study of a new road definition, the most common methodology is to establish different levels of Territorial Carrying Capacity (TCC) in the study area in order to summarize the territorial variables on thematic maps and to ease the tracing process of road-corridor layout alternatives. This paper explores the variables used in 22 road-construction projects conducted by the Ministry of Public Works that were subject to the Spanish EIA regulation and published between 2006 and 2008. The aim was to evaluate the quality of the methods applied and the homogeneity and suitability of the variables used for defining the TCC. The variables were clustered into physical, environmental, land-use and cultural constraints for the purpose of comparing the TCC values assigned in the studies reviewed. We found the average quality of the studies to be generally acceptable in terms of the justification of the methodology, the weighting and classification of the variables, and the creation of a synthesis map. Nevertheless, the methods for assessing the TCC are not sufficiently standardized; there is a lack of uniformity in the cartographic information sources and methodologies for the TCC valuation. -- Highlights: • We explore 22 road-corridor planning studies subjected to the Spanish EIA regulation. • We analyze the variables selected for defining territorial carrying capacity. • The quality of the studies is acceptable (methodology, variable weighting, mapping). • There is heterogeneity in the methods for territorial carrying capacity valuation.

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

    SciTech Connect (OSTI)

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

    2012-09-01T23:59:59.000Z

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