National Library of Energy BETA

Sample records for reference case forecast

  1. Appendix A: Reference case

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

    4 Reference case Table A2. Energy consumption by sector and source (quadrillion Btu per year, unless otherwise noted) Energy Information Administration Annual Energy Outlook 2014...

  2. Appendix A: Reference case

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

    Reference case Energy Information Administration Annual Energy Outlook 2014 Table A17. Renewable energy consumption by sector and source (quadrillion Btu) Sector and source...

  3. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    I Reference case projections for natural gas production This page inTenTionally lefT blank 121 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for natural gas production Table I1. World total natural gas production by region, Reference case, 2012-40 (trillion cubic feet) Region/country Projections Average annual percent change, 2012-40 2012 2020 2025 2030 2035 2040 OECD OECD Americas 31.8 35.7 38.6 42.1 44.6 47.3 1.4 United States a 24.0 28.7

  4. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections Table A14. World population by region, Reference case, 2011-40 (millions) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 484 489 523 544 564 581 597 0.7 United States a 312 315 334 347 359 370 380 0.7 Canada 34 35 38 39 41 43 44 0.8 Mexico and Chile 137 139 151 158 164 169 173 0.8 OECD Europe 548 550 565 571 576 579 581

  5. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    3 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections Table A8. World nuclear energy consumption by region, Reference case, 2011-40 (billion kilowatthours) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 888 867 902 891 901 900 924 0.2 United States a 790 769 804 808 808 812 833 0.3 Canada 88 89 86 72 72 67 62 -1.3 Mexico and Chile 9 8 12 12 20 20 29 4.5 OECD Europe 861 837

  6. Appendix A: Reference case projections

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

    U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections Table A1. World total primary energy consumption by region, Reference case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 120.6 118.1 125.7 128.1 130.7 133.8 138.1 0.6 United States a 96.8 94.4 100.8 102.0 102.9 103.8 105.7 0.4 Canada 14.5 14.5 15.1 15.6 16.3 17.1 18.1 0.8 Mexico and Chile 9.3

  7. Appendix A: Reference case projections

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

    International Energy Outlook 2016 Reference case projections Table A4. World gross domestic product (GDP) by region expressed in market exchange rates, Reference case, 2011-40 (billion 2010 dollars) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 18,006 18,440 22,566 25,585 28,757 32,166 36,120 2.4 United States a 15,021 15,369 18,801 21,295 23,894 26,659 29,898 2.4 Canada 1,662 1,694 2,024 2,240 2,470 2,730 3,012 2.1 Mexico

  8. Appendix A: Reference case projections

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

    U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections Table A6. World natural gas consumption by region, Reference case, 2011-40 (trillion cubic feet) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 30.8 31.8 32.8 34.3 36.5 38.2 40.1 0.8 United States a 24.5 25.5 26.1 26.9 28.1 28.8 29.7 0.5 Canada 3.7 3.7 3.9 4.2 4.7 5.2 5.6 1.5 Mexico and Chile 2.6 2.6 2.8 3.2 3.6 4.2 4.8

  9. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    1 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for natural gas production Table I1. World total natural gas production by region, Reference case, 2012-40 (trillion cubic feet) Region/country Projections Average annual percent change, 2012-40 2012 2020 2025 2030 2035 2040 OECD OECD Americas 31.8 35.7 38.6 42.1 44.6 47.3 1.4 United States a 24.0 28.7 30.4 32.9 34.0 35.3 1.4 Canada 6.1 5.8 6.6 7.2 7.9 8.6 1.2 Mexico 1.7 1.2 1.5 2.0 2.6 3.3

  10. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    3 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for natural gas production Table I3. World other natural gas production by region, Reference case, 2012-40 (trillion cubic feet) Region/country Projections Average annual percent change, 2012-40 2012 2020 2025 2030 2035 2040 OECD OECD Americas 12.0 9.8 9.5 10.7 10.3 10.3 -0.5 United States a 7.5 6.6 6.5 7.8 7.5 7.5 0.0 Canada 2.8 2.0 1.8 1.7 1.6 1.5 -2.2 Mexico 1.7 1.2 1.2 1.2 1.2 1.2 -1.2

  11. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    5 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections Table A10. World carbon dioxide emissions by region, Reference case, 2011-40 (million metric tons carbon dioxide) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 6,558 6,343 6,569 6,620 6,675 6,769 6,887 0.3 United States a 5,483 5,272 5,499 5,511 5,514 5,521 5,549 0.2 Canada 562 563 557 577 587 621 647 0.5 Mexico and

  12. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    Reference case projections Table A12. World carbon dioxide emissions from natural gas use by region, Reference case, 2011-40 (million metric tons carbon dioxide) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 1,666 1,715 1,766 1,849 1,965 2,063 2,167 0.8 United States a 1,305 1,363 1,394 1,432 1,497 1,538 1,586 0.5 Canada 205 205 213 234 261 287 310 1.5 Mexico and Chile 156 147 158 184 207 238 271 2.2 OECD Europe 1,016 970

  13. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    5 U.S. Energy Information Administration | International Energy Outlook 2016 Projections of petroleum and other liquid fuels production in three cases Table G1. World petroleum and other liquids production by region and country, Reference case, 2011-40 (million barrels per day, unless otherwise noted) Region/country History (estimates) Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OPEC a 36.0 37.4 39.2 41.4 44.6 48.7 52.2 1.2 Middle East 26.2 26.6 29.8

  14. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | International Energy Outlook 2016 Projections of petroleum and other liquid fuels production in three cases Table G3. International other liquid fuels a production by region and country, Reference case, 2011-40 (million barrels per day, unless otherwise noted) Region/country History (estimates) Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OPEC b 3.7 3.8 4.3 4.6 4.8 5.2 5.6 1.3 Natural gas plant liquids 3.6 3.7

  15. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | International Energy Outlook 2016 Kaya Identity factor projections Table J3. World gross domestic product (GDP) per capita by region expressed in purchasing power parity, Reference case, 2011-40 (2010 dollars per person) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 38,441 39,055 44,716 48,842 53,114 57,747 63,278 1.7 United States a 48,094 48,865 56,285 61,453 66,639 72,107

  16. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for electricity capacity and generation by fuel Table H1. World total installed generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 1,258 1,278 1,330 1,371 1,436 1,517 1,622 0.9 United States a 1,046 1,063 1,079 1,091 1,133 1,187 1,261 0.6 Canada 133 135

  17. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for electricity capacity and generation by fuel Table H11. World installed other renewable generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 41 42 45 49 52 57 59 1.2 United States a 36 37 39 39 39 40 41 0.4 Canada 4 4 5 8 12 15 16 4.9 Mexico and Chile 1 1

  18. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for electricity capacity and generation by fuel Table H13. World net liquids-fred electricity generation by region and country, 2011-40 (billion kilowatthours) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 88 88 66 37 36 35 35 -3.3 United States a 30 23 18 18 18 18 18 -0.9 Canada 6 7 6 6 6 5 5 -1.0 Mexico and

  19. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    1 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for electricity capacity and generation by fuel Table H15. World net coal-fred electricity generation by region and country, 2011-40 (billion kilowatthours) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 1,857 1,630 1,808 1,820 1,786 1,778 1,769 0.3 United States a 1,733 1,514 1,709 1,724 1,713 1,704 1,702 0.4

  20. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    Reference case projections for electricity capacity and generation by fuel Table H17. World net hydroelectric and other renewable electricity generation by region and country, 2011-40 (billion kilowatthours) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 1,004 987 1,278 1,376 1,472 1,598 1,763 2.1 United States a 535 520 704 741 781 848 934 2.1 Canada 398 397 459 491 524 557 606 1.5 Mexico and Chile 71 69 115 144

  1. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    5 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for electricity capacity and generation by fuel Table H19. World net wind-powered electricity generation by region and country, 2011-40 (billion kilowatthours) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 142 156 295 327 354 404 460 3.9 United States a 120 141 232 235 245 278 319 3.0 Canada 20 11 39 46 53 60 66

  2. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for electricity capacity and generation by fuel Table H21. World net solar electricity generation by region and country, 2011-40 (billion kilowatthours) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 6 12 57 65 79 96 120 8.7 United States a 6 11 51 59 71 88 110 8.5 Canada 0 0 3 3 4 5 5 10.3 Mexico and Chile 0 0 3

  3. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for electricity capacity and generation by fuel Table H3. World installed natural-gas-fred generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 410 420 455 488 534 584 640 1.5 United States a 358 367 393 409 444 481 525 1.3 Canada 20 20 25 30 36 41 46 3.0

  4. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    1 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for electricity capacity and generation by fuel Table H5. World installed nuclear generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 115 117 115 113 115 114 118 0.0 United States a 102 102 101 101 102 102 105 0.1 Canada 13 14 12 10 10 10 9 -1.5 Mexico and

  5. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    3 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for electricity capacity and generation by fuel Table H7. World installed hydroelectric generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 171 171 183 187 192 198 210 0.7 United States a 78 78 80 80 80 80 80 0.1 Canada 75 75 83 85 88 90 99 1.0 Mexico and

  6. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    5 U.S. Energy Information Administration | International Energy Outlook 2016 Reference case projections for electricity capacity and generation by fuel Table H9. World installed geothermal generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 3 3 5 7 9 10 11 4.3 United States a 3 3 4 5 7 8 9 4.6 Canada 0 0 0 0 0 0 0 - Mexico and Chile 1 1 1 1 2 2 2 3.3 OECD

  7. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | International Energy Outlook 2016 Kaya Identity factor projections Table J1. World carbon dioxide intensity of energy use by region, Reference case, 2011-40 (metric tons per billion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 53.6 53.0 52.3 51.7 51.1 50.6 49.9 -0.2 United States a 55.7 55.0 54.5 54.0 53.6 53.2 52.5 -0.2 Canada 38.8 38.9 37.0 37.0 36.1 36.2 35.8 -0.3 Mexico

  8. Appendix A: Reference case projections

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

    8 Appendix A Table A3. World gross domestic product (GDP) by region expressed in purchasing power parity, Reference case, 2011-40 (billion 2010 dollars) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 18,616 19,080 23,390 26,577 29,942 33,569 37,770 2.5 United States a 15,021 15,369 18,801 21,295 23,894 26,659 29,898 2.4 Canada 1,396 1,422 1,700 1,881 2,074 2,293 2,529 2.1 Mexico and Chile 2,200 2,288 2,890 3,400 3,974 4,618

  9. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    6 Appendix A Table A11. World carbon dioxide emissions from liquids use by region, Reference case, 2011-40 (million metric tons carbon dioxide) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 2,881 2,838 2,861 2,812 2,785 2,794 2,812 0.0 United States a 2,291 2,240 2,269 2,227 2,182 2,163 2,147 -0.2 Canada 289 291 291 289 290 295 304 0.2 Mexico and Chile 301 307 301 296 313 335 361 0.6 OECD Europe 1,969 1,903 1,823 1,804

  10. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    8 Appendix A Table A13. World carbon dioxide emissions from coal use by region, Reference case, 2011-40 (million metric tons carbon dioxide) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 2,000 1,779 1,931 1,947 1,912 1,901 1,896 0.2 United States a 1,876 1,657 1,824 1,840 1,822 1,808 1,804 0.3 Canada 68 68 53 54 36 38 33 -2.5 Mexico and Chile 56 54 53 53 54 55 58 0.3 OECD Europe 1,208 1,251 1,228 1,244 1,219 1,195 1,178

  11. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    8 Appendix J Table J2. World energy intensity by region, Reference case, 2011-40 (thousand Btu per 2010 dollar of GDP) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 6.5 6.2 5.4 4.8 4.4 4.0 3.7 -1.9 United States a 6.4 6.1 5.4 4.8 4.3 3.9 3.5 -2.0 Canada 10.4 10.2 8.9 8.3 7.8 7.5 7.1 -1.3 Mexico and Chile 4.2 4.0 3.4 3.1 2.9 2.8 2.7 -1.4 OECD Europe 4.4 4.4 3.9 3.7 3.5 3.3 3.2 -1.1 OECD Asia 5.7 5.5 5.4 5.3 5.1 4.9 4.8 -0.5

  12. Appendix A: Reference case projections

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

    6 Appendix A Table A2. World total energy consumption by region and fuel, Reference case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas Liquids 45.3 44.6 46.4 46.1 46.0 46.2 46.7 0.2 Natural gas 31.8 32.8 33.9 35.5 37.7 39.5 41.4 0.8 Coal 21.0 18.7 20.3 20.5 20.1 20.0 20.0 0.2 Nuclear 9.4 9.2 9.5 9.4 9.5 9.5 9.7 0.2 Other 13.1 12.9 15.6 16.6 17.5 18.6 20.3 1.6 Total 120.6 118.1 125.7 128.1 130.7

  13. Appendix A: Reference case projections

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

    30 Appendix A Table A5. World liquids consumption by region, Reference case, 2011-40 (million barrels per day) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 23.6 23.2 24.4 24.4 24.3 24.4 24.6 0.2 United States a 18.9 18.5 19.6 19.6 19.4 19.3 19.3 0.2 Canada 2.3 2.4 2.4 2.4 2.4 2.4 2.5 0.2 Mexico and Chile 2.4 2.4 2.4 2.4 2.5 2.7 2.9 0.6 OECD Europe 14.5 14.1 13.7 13.6 13.7 13.8 14.0 0.0 OECD Asia 7.9 8.2 7.7 7.5 7.5 7.5

  14. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    86 Appendix G Table G2. World crude oil a production by region and country, Reference case, 2011-40 (million barrels per day, unless otherwise noted) Region/country History (estimates) Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OPEC b 32.2 33.4 34.9 36.8 39.7 43.4 46.6 1.2 Middle East 22.9 23.2 26.2 27.9 30.3 33.4 35.6 1.5 North Africa 2.0 2.9 1.6 1.7 1.8 2.0 2.2 -1.0 West Africa 4.3 4.3 4.3 4.3 4.5 4.7 5.1 0.6 South America 3.0 3.0 2.8 2.9 3.1 3.4 3.6

  15. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    2 Appendix I Table I2. World tight gas, shale gas and coalbed methane production by region, Reference case, 2012-40 (trillion cubic feet) Region/country Projections Average annual percent change, 2012-40 2012 2020 2025 2030 2035 2040 OECD OECD Americas 19.8 26.0 29.0 31.4 34.3 37.0 2.3 United States a 16.6 22.1 23.9 25.1 26.5 27.8 1.9 Canada 3.3 3.8 4.9 5.5 6.3 7.0 2.8 Mexico 0.0 0.1 0.3 0.8 1.4 2.2 - Chile 0.0 0.0 0.0 0.0 0.0 0.0 - OECD Europe 0.0 0.5 1.7 3.3 4.6 5.5 21.8 North Europe 0.0 0.5

  16. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    4 Appendix I Table I4. World net trade in natural gas by region, Reference case, 2012-40 (trillion cubic feet) Region/country Projections Average annual percent change, 2012-40 2012 2020 2025 2030 2035 2040 OECD OECD Americas 0.3 -2.6 -4.0 -5.4 -6.2 -6.9 - United States a 1.5 -2.6 -3.5 -4.8 -5.2 -5.6 - Canada -2.3 -1.9 -2.3 -2.4 -2.7 -2.8 0.7 Mexico 1.0 1.7 1.7 1.6 1.5 1.3 1.1 Chile 0.1 0.1 0.1 0.2 0.2 0.2 1.7 OECD Europe 7.8 10.9 11.9 12.7 13.0 14.0 2.1 North Europe 2.4 5.2 5.9 6.1 6.1 6.3 3.5

  17. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    2 Appendix A Table A7. World coal consumption by region, Reference case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 21.0 18.7 20.3 20.5 20.1 20.0 20.0 0.2 United States a 19.6 17.3 19.2 19.3 19.2 19.0 19.0 0.3 Canada 0.7 0.7 0.6 0.6 0.4 0.4 0.4 -2.5 Mexico and Chile 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.3 OECD Europe 12.9 13.4 13.2 13.3 13.1 12.8 12.6 -0.2 OECD Asia 9.7 9.7 10.2 10.1 10.1 10.1 10.1 0.1

  18. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    4 Appendix A Table A9. World consumption of hydroelectricity and other renewable energy by region, Reference case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 13.1 12.9 15.6 16.6 17.5 18.6 20.3 1.6 United States a 7.9 7.7 9.3 9.7 9.9 10.4 11.3 1.4 Canada 4.3 4.2 4.8 5.1 5.5 5.8 6.3 1.4 Mexico and Chile 0.9 1.0 1.5 1.8 2.1 2.4 2.7 3.7 OECD Europe 10.7 11.5 15.7 16.7 17.3 18.5 19.6 1.9 OECD Asia

  19. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    C Low Economic Growth case projections This page inTenTionally lefT blank 47 U.S. Energy Information Administration | International Energy Outlook 2016 Low Economic Growth case projections Table C1. World total primary energy consumption by region, Low Economic Growth case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 120.6 118.1 123.3 123.9 124.7 126.3 128.8 0.3 United States a 96.8 94.4 98.7

  20. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    D High Oil Price case projections This page inTenTionally lefT blank 51 U.S. Energy Information Administration | International Energy Outlook 2016 High Oil Price case projections Table D1. World total primary energy consumption by region, High Oil Price case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 120.6 118.1 125.3 127.9 130.8 135.5 142.1 0.7 United States a 96.8 94.4 100.8 102.2 103.3

  1. Appendix A. Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    by region and country, Low Oil Price case, 2009-40 (million barrels per day) Region History Projections Average annual percent change, 2010-40 2009 2010 2011 2020 2025 2030...

  2. Appendix A. Reference case projections

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

    by region and end-use sector, High Oil Price case, 2010-40 (quadrillion Btu) Region History Projections Average annual percent change, 2010-40 2010 2020 2025 2030 2035 2040 OECD...

  3. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    E Low Oil Price case projections This page inTenTionally lefT blank 57 U.S. Energy Information Administration | International Energy Outlook 2016 Low Oil Price case projections Table E1. World total primary energy consumption by region, Low Oil Price case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-s40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 120.6 118.1 126.5 129.2 131.8 135.0 138.9 0.6 United States a 96.8 94.4 101.2 102.7 103.6 104.6

  4. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    1 U.S. Energy Information Administration | International Energy Outlook 2016 Projections of petroleum and other liquid fuels production in three cases Table G7. World petroleum and other liquids production by region and country, Low Oil Price case, 2011-40 (million barrels per day, unless otherwise noted) Region/country History (estimates) Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OPEC a 36.0 37.4 43.2 45.6 49.9 54.7 59.4 1.7 Middle East 26.2 26.6 31.1

  5. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    3 U.S. Energy Information Administration | International Energy Outlook 2016 Projections of petroleum and other liquid fuels production in three cases Table G9. World other liquid fuels a production by region and country, Low Oil Price case, 2011-40 (million barrels per day, unless otherwise noted) Region/country History (estimates) Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OPEC b 3.7 3.8 4.3 4.5 4.5 4.9 4.8 0.8 Natural gas plant liquids 3.6 3.7 4.0

  6. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | International Energy Outlook 2016 Low Oil Price case projections Table E1. World total primary energy consumption by region, Low Oil Price case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-s40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 120.6 118.1 126.5 129.2 131.8 135.0 138.9 0.6 United States a 96.8 94.4 101.2 102.7 103.6 104.6 106.1 0.4 Canada 14.5 14.5 15.3 15.8 16.5 17.4 18.3 0.8 Mexico and

  7. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | International Energy Outlook 2016 Low Oil Price case projections Table E3. World liquids consumption by region, Low Oil Price case, 2011-40 (million barrels per day) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 23.6 23.2 24.9 25.0 25.2 25.5 26.1 0.4 United States a 18.9 18.5 20.0 20.1 20.1 20.2 20.4 0.4 Canada 2.3 2.4 2.4 2.4 2.5 2.6 2.6 0.4 Mexico and Chile 2.4 2.4 2.5 2.5 2.6

  8. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    7 U.S. Energy Information Administration | International Energy Outlook 2016 Low Economic Growth case projections Table C1. World total primary energy consumption by region, Low Economic Growth case, 2011-40 (quadrillion Btu) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 120.6 118.1 123.3 123.9 124.7 126.3 128.8 0.3 United States a 96.8 94.4 98.7 98.1 97.5 97.4 98.0 0.1 Canada 14.5 14.5 15.0 15.4 15.9 16.6 17.3 0.6 Mexico

  9. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    9 U.S. Energy Information Administration | International Energy Outlook 2016 Projections of petroleum and other liquid fuels production in three cases Table G5. World crude oil a production by region and country, High Oil Price case, 2011-40 (million barrels per day, unless otherwise noted) Region/country History (estimates) Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OPEC b 32.2 33.4 30.7 30.9 32.4 33.4 34.4 0.1 Middle East 22.9 23.2 22.7 23.0 24.4 25.2

  10. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    58 Appendix E Table E2. World gross domestic product (GDP) by region expressed in purchasing power parity, Low Oil Price case, 2011-40 (billion 2010 dollars) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 18,616 19,080 23,330 26,574 29,998 33,626 37,702 2.5 United States a 15,021 15,369 18,742 21,299 23,963 26,735 29,885 2.4 Canada 1,396 1,422 1,700 1,881 2,073 2,290 2,521 2.1 Mexico and Chile 2,200 2,288 2,889 3,394 3,962

  11. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    8 Appendix C Table C2. World gross domestic product (GDP) by region expressed in purchasing power parity, Low Economic Growth case, 2011-40 (billion 2010 dollars) Region History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 18,616 19,080 22,285 24,599 27,041 29,850 33,088 2.0 United States a 15,021 15,369 17,747 19,441 21,224 23,305 25,763 1.9 Canada 1,396 1,422 1,682 1,841 2,005 2,186 2,375 1.8 Mexico and Chile 2,200 2,288 2,856 3,317

  12. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    8 Appendix G Table G4. World petroleum and other liquids production by region and country, High Oil Price case, 2011-40 (million barrels per day, unless otherwise noted) Region/country History (estimates) Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OPEC a 36.0 37.4 35.3 35.8 37.7 39.3 40.4 0.3 Middle East 26.2 26.6 26.5 27.0 28.6 29.8 30.6 0.5 North Africa 2.4 3.3 2.1 1.9 2.1 2.2 2.3 -1.4 West Africa 4.3 4.3 4.0 4.0 4.0 4.0 4.0 -0.2 South America 3.2 3.2

  13. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    0 Appendix G Table G6. World other liquid fuels a production by region and country, High Oil Price case, 2011-40 (million barrels per day, unless otherwise noted) Region/country History (estimates) Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OPEC b 3.7 3.8 4.6 4.9 5.3 5.8 5.9 1.6 Natural gas plant liquids 3.6 3.7 4.3 4.6 4.9 5.3 5.3 1.3 Liquids from renewable sources c 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - Liquids from coal 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - Liquids

  14. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    2 Appendix G Table G8. World crude oil a production by region and country, Low Oil Price case, 2011-40 (million barrels per day, unless otherwise noted) Region/country History (estimates) Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OPEC b 32.2 33.4 38.9 41.1 45.3 49.7 54.5 1.8 Middle East 22.9 23.2 27.8 28.9 32.2 35.6 38.5 1.8 North Africa 2.0 2.9 2.9 3.0 3.0 3.0 3.3 0.5 West Africa 4.3 4.3 4.4 4.5 4.9 5.5 6.3 1.3 South America 3.0 3.0 3.8 4.7 5.1 5.6

  15. Generic Argillite/Shale Disposal Reference Case

    SciTech Connect (OSTI)

    Zheng, Liange; Colon, Carlos Jové; Bianchi, Marco; Birkholzer, Jens

    2014-08-08

    properties (parameters) used in these models are different, which not only make inter-model comparisons difficult, but also compromise the applicability of the lessons learned from one model to another model. The establishment of a reference case would therefore be helpful to set up a baseline for model development. A generic salt repository reference case was developed in Freeze et al. (2013) and the generic argillite repository reference case is presented in this report. The definition of a reference case requires the characterization of the waste inventory, waste form, waste package, repository layout, EBS backfill, host rock, and biosphere. This report mainly documents the processes in EBS bentonite and host rock that are potentially important for performance assessment and properties that are needed to describe these processes, with brief description other components such as waste inventory, waste form, waste package, repository layout, aquifer, and biosphere. A thorough description of the generic argillite repository reference case will be given in Jové Colon et al. (2014).

  16. Annual Energy Outlook 2011 Reference Case

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

    ... Case CO 2 Fee 10ton CO 2 Fee 25ton Coal plant retirements 8 gigawatts Source: EIA, ... gas combined-cycle plants to coal-fired steam turbines in five cases, 2008-2040 9 ...

  17. Annual Energy Outlook 2013 Early Release Reference Case

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

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

  18. REFERENCE CASES FOR USE IN THE CEMENTITOUS PARTNERSHIP PROJECT

    SciTech Connect (OSTI)

    Langton, C.; Kosson, D.; Garrabrants, A.

    2010-08-31

    The Cementitious Barriers Partnership Project (CBP) is a multi-disciplinary, multi-institution cross cutting collaborative effort supported by the US Department of Energy (DOE) to develop a reasonable and credible set of tools to improve understanding and prediction of the structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. The period of performance is >100 years for operating facilities and > 1000 years for waste management. The CBP has defined a set of reference cases to provide the following functions: (i) a common set of system configurations to illustrate the methods and tools developed by the CBP, (ii) a common basis for evaluating methodology for uncertainty characterization, (iii) a common set of cases to develop a complete set of parameter and changes in parameters as a function of time and changing conditions, (iv) a basis for experiments and model validation, and (v) a basis for improving conceptual models and reducing model uncertainties. These reference cases include the following two reference disposal units and a reference storage unit: (i) a cementitious low activity waste form in a reinforced concrete disposal vault, (ii) a concrete vault containing a steel high-level waste tank filled with grout (closed high-level waste tank), and (iii) a spent nuclear fuel basin during operation. Each case provides a different set of desired performance characteristics and interfaces between materials and with the environment. Examples of concretes, grout fills and a cementitious waste form are identified for the relevant reference case configurations.

  19. REFERENCE CASES FOR USE IN THE CEMENTITIOUS BARRIERS PARTNERSHIP

    SciTech Connect (OSTI)

    Langton, C

    2009-01-06

    The Cementitious Barriers Project (CBP) is a multidisciplinary cross cutting project initiated by the US Department of Energy (DOE) to develop a reasonable and credible set of tools to improve understanding and prediction of the structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. The period of performance is >100 years for operating facilities and > 1000 years for waste management. The CBP has defined a set of reference cases to provide the following functions: (1) a common set of system configurations to illustrate the methods and tools developed by the CBP, (2) a common basis for evaluating methodology for uncertainty characterization, (3) a common set of cases to develop a complete set of parameter and changes in parameters as a function of time and changing conditions, and (4) a basis for experiments and model validation, and (5) a basis for improving conceptual models and reducing model uncertainties. These reference cases include the following two reference disposal units and a reference storage unit: (1) a cementitious low activity waste form in a reinforced concrete disposal vault, (2) a concrete vault containing a steel high-level waste tank filled with grout (closed high-level waste tank), and (3) a spent nuclear fuel basin during operation. Each case provides a different set of desired performance characteristics and interfaces between materials and with the environment. Examples of concretes, grout fills and a cementitious waste form are identified for the relevant reference case configurations.

  20. Preliminary Reference Case Results for Oil and Natural Gas

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

    Preliminary Reference Case Results for Oil and Natural Gas AEO2014 Oil and Gas Supply Working Group Meeting Office of Petroleum, Gas, and Biofuels Analysis September 26, 2013 | Washington, DC WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE AEO2014P uses ref2014.d092413a AEO2013 uses ref2013.d102312a Changes for AEO2014 2 * Revised shale & tight play resources (EURs, type curves) * Updated classification of shale gas, tight gas, &

  1. Coal-by-Rail: A Business-as-Usual Reference Case | Argonne National...

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

    Coal-by-Rail: A Business-as-Usual Reference Case Title Coal-by-Rail: A Business-as-Usual Reference Case Publication Type Report Year of Publication 2015 Authors Mintz, MM, Saricks,...

  2. Coal-by-Rail Business-as-Usual Reference Case

    Broader source: Energy.gov [DOE]

    As proposed carbon emission standards reduce domestic coal use, the role of coal in the U.S. energy mix may be expected to decline. If such a decline were to occur, how would it affect rail traffic? Today, coal represents a major share of rail tonnage and gross revenue. While growth in other traffic―most notably, crude oil―may offset some of any potential decline in coal shipments, would it be sufficient? This paper explores trends in coal production volumes and use, rail tonnage and revenue, and the distribution of traffic origins and destinations in order to consider the impact of potential changes in future coal traffic. Rather than modeling discrete flows, it draws on historical data and forecasts maintained by the U.S. Department of Energy’s Energy Information Administration (EIA), industry studies and analyses, and background knowledge of the rail industry, specific routes and service territories, and commodity-level traffic volumes.

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

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

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

  4. Expectations models of electric utilities' forecasts: a case study of econometric estimation with influential data points

    SciTech Connect (OSTI)

    Vellutini, R. de A.S.; Mount, T.D.

    1983-01-01

    This study develops an econometric model for explaining how electric utilities revise their forecasts of future electricity demand each year. The model specification is developed from the adaptive expectations hypothesis and it relates forecasted growth rates to actual lagged growth rates of electricity demand. Unlike other studies of the expectation phenomenon, expectations of future demand levels constitute an observable variable and thus can be incorporated explicitly into the model. The data used for the analysis were derived from the published forecasts of the nine National Electric Reliability Councils in the US for the years 1974 to 1980. Three alternative statistical methods are used for estimation purposes: ordinary least-squares, robust regression and a diagnostic analysis to identify influential observations. The results obtained with the first two methods are very similar, but are both inconsistent with the underlying economic logic of the model. The estimated model obtained from the diagnostics approach after deleting two aberrant observations is consistent with economic logic, and supports the hypothesis that the low growth demand experienced immediately following the oil embargo in 1973 were disregarded by the industry for forecasting purposes. The model includes transitory effects associated with the oil embargo that gradually disappear over time, the estimated coefficients for the lagged values of actual growth approach a structure with declining positive weights. The general shape of this asymptotic structure is similar to the findings in many economic applications using distributed lag models.

  5. 2007 Wholesale Power Rate Case Final Proposal : Market Price Forecast Study.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    2006-07-01

    This study presents BPA's market price forecasts for the Final Proposal, which are based on AURORA modeling. AURORA calculates the variable cost of the marginal resource in a competitively priced energy market. In competitive market pricing, the marginal cost of production is equivalent to the market-clearing price. Market-clearing prices are important factors for informing BPA's power rates. AURORA was used as the primary tool for (a) estimating the forward price for the IOU REP Settlement benefits calculation for fiscal years (FY) 2008 and 2009, (b) estimating the uncertainty surrounding DSI payments and IOU REP Settlements benefits, (c) informing the secondary revenue forecast and (d) providing a price input used for the risk analysis. For information about the calculation of the secondary revenues, uncertainty regarding the IOU REP Settlement benefits and DSI payment uncertainty, and the risk run, see Risk Analysis Study WP-07-FS-BPA-04.

  6. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1994-02-01

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

  7. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04

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

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

    SciTech Connect (OSTI)

    1995-04-01

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

  10. Simulations of Clouds and Sensitivity Study by Weather Research and Forecast Model for Atmospheric Radiation Measurement Case 4

    SciTech Connect (OSTI)

    Wu, J.; Zhang, M.

    2005-03-18

    One of the large errors in general circulation models (GCMs) cloud simulations is from the mid-latitude, synoptic-scale frontal cloud systems. Now, with the availability of the cloud observations from Atmospheric Radiation Measurement (ARM) 2000 cloud Intensive Operational Period (IOP) and other observational datasets, the community is able to document the model biases in comparison with the observations and make progress in development of better cloud schemes in models. Xie et al. (2004) documented the errors in midlatitude frontal cloud simulations for ARM Case 4 by single-column models (SCMs) and cloud resolving models (CRMs). According to them, the errors in the model simulated cloud field might be caused by following reasons: (1) lacking of sub-grid scale variability; (2) lacking of organized mesoscale cyclonic advection of hydrometeors behind a moving cyclone which may play important role to generate the clouds there. Mesoscale model, however, can be used to better under stand these controls on the subgrid variability of clouds. Few studies have focused on applying mesoscale models to the forecasting of cloud properties. Weaver et al. (2004) used a mesoscale model RAMS to study the frontal clouds for ARM Case 4 and documented the dynamical controls on the sub-GCM-grid-scale cloud variability.

  11. Solar Forecasting

    Broader source: Energy.gov [DOE]

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

  12. Developing an industrial end-use forecast: A case study at the Los Angeles department of water and power

    SciTech Connect (OSTI)

    Mureau, T.H.; Francis, D.M.

    1995-05-01

    The Los Angeles Department of Water and Power (LADWP) uses INFORM 1.0 to forecast industrial sector energy. INFORM 1.0 provides an end-use framework that can be used to forecast electricity, natural gas or other fuels consumption. Included with INFORM 1.0 is a default date set including the input data and equations necessary to solve each model. LADWP has substituted service area specific data for the default data wherever possible. This paper briefly describes the steps LADWP follows in developing those inputs and application in INFORM 1.0.

  13. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Advanced Scientific Computing Research January 5-6, 2011 Official DOE Invitation Workshop Invitation Letter from DOE Associate Directors NERSC Documents NERSC science requirements home page NERSC science requirements workshop page NERSC science requirements case study FAQ Previous NERSC Requirements Workshops Biological and Environmental Research (BER) Basic Energy Sciences (BES) Fusion Energy Sciences

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

    Reports and Publications (EIA)

    2009-01-01

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

  15. Technical basis for cases N-629 and N-631 as an alternative for RTNDT reference temperature

    SciTech Connect (OSTI)

    Merkle, John Graham; Server, W. L.

    2007-01-01

    ASME Code Cases N-629/N-631, published in 1999, provided an important new approach to allow material specific, measured fracture toughness curves for ferritic steels in the code applications. This has enabled some of the nuclear power plants whose reactor pressure vessel materials reached a certain threshold level based on overly conservative rules to use an alternative RTNDT to justify continued operation of their plants. These code cases have been approved by the US Nuclear Regulatory Commission and these have been proposed to be codified in Appendix A and Appendix G of the ASME Boiler and Pressure Vessel Code. This paper summarizes the basis of this approach for the record.

  16. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Fusion Energy Sciences August 3-4, 2010 Official DOE Invitation Workshop Invitation Letter from DOE Associate Directors [not available] NERSC Documents NERSC science requirements home page NERSC science requirements workshop page NERSC science requirements case study FAQ Workshop Agenda Previous NERSC Requirements Workshops Biological and Environmental Research (BER) Basic Energy Sciences (BES) Fusion

  17. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for High Energy Physics November 12-13, 2009 Official DOE Invitation Workshop Invitation Letter from DOE Associate Directors NERSC Documents NERSC science requirements home page NERSC science requirements workshop page NERSC science requirements case study FAQ Workshop Agenda Previous NERSC Requirements Workshops Biological and Environmental Research (BER) Basic Energy Sciences (BES) Fusion Energy Sciences

  18. Forecast Change

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

    Forecast Change 2011 2012 2013 2014 2015 2016 from 2015 United States Usage (kWh) 3,444 3,354 3,129 3,037 3,151 3,302 4.8% Price (cents/kWh) 12.06 12.09 12.58 13.04 12.95 12.84 -0.9% Expenditures $415 $405 $393 $396 $408 $424 3.9% New England Usage (kWh) 2,122 2,188 2,173 1,930 1,992 2,082 4.5% Price (cents/kWh) 15.85 15.50 16.04 17.63 18.64 18.37 -1.5% Expenditures $336 $339 $348 $340 $371 $382 3.0% Mid-Atlantic Usage (kWh) 2,531 2,548 2,447 2,234 2,371 2,497 5.3% Price (cents/kWh) 16.39 15.63

  19. Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels

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

    Niemeyer, Kyle E.; Sung, Chih-Jen

    2014-11-01

    Strategies and recommendations for performing skeletal reductions of multicomponent surrogate fuels are presented, through the generation and validation of skeletal mechanisms for a three-component toluene reference fuel. Using the directed relation graph with error propagation and sensitivity analysis method followed by a further unimportant reaction elimination stage, skeletal mechanisms valid over comprehensive and high-temperature ranges of conditions were developed at varying levels of detail. These skeletal mechanisms were generated based on autoignition simulations, and validation using ignition delay predictions showed good agreement with the detailed mechanism in the target range of conditions. When validated using phenomena other than autoignition, suchmore » as perfectly stirred reactor and laminar flame propagation, tight error control or more restrictions on the reduction during the sensitivity analysis stage were needed to ensure good agreement. In addition, tight error limits were needed for close prediction of ignition delay when varying the mixture composition away from that used for the reduction. In homogeneous compression-ignition engine simulations, the skeletal mechanisms closely matched the point of ignition and accurately predicted species profiles for lean to stoichiometric conditions. Furthermore, the efficacy of generating a multicomponent skeletal mechanism was compared to combining skeletal mechanisms produced separately for neat fuel components; using the same error limits, the latter resulted in a larger skeletal mechanism size that also lacked important cross reactions between fuel components. Based on the present results, general guidelines for reducing detailed mechanisms for multicomponent fuels are discussed.« less

  20. Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels

    SciTech Connect (OSTI)

    Niemeyer, Kyle E.; Sung, Chih-Jen

    2014-11-01

    Strategies and recommendations for performing skeletal reductions of multicomponent surrogate fuels are presented, through the generation and validation of skeletal mechanisms for a three-component toluene reference fuel. Using the directed relation graph with error propagation and sensitivity analysis method followed by a further unimportant reaction elimination stage, skeletal mechanisms valid over comprehensive and high-temperature ranges of conditions were developed at varying levels of detail. These skeletal mechanisms were generated based on autoignition simulations, and validation using ignition delay predictions showed good agreement with the detailed mechanism in the target range of conditions. When validated using phenomena other than autoignition, such as perfectly stirred reactor and laminar flame propagation, tight error control or more restrictions on the reduction during the sensitivity analysis stage were needed to ensure good agreement. In addition, tight error limits were needed for close prediction of ignition delay when varying the mixture composition away from that used for the reduction. In homogeneous compression-ignition engine simulations, the skeletal mechanisms closely matched the point of ignition and accurately predicted species profiles for lean to stoichiometric conditions. Furthermore, the efficacy of generating a multicomponent skeletal mechanism was compared to combining skeletal mechanisms produced separately for neat fuel components; using the same error limits, the latter resulted in a larger skeletal mechanism size that also lacked important cross reactions between fuel components. Based on the present results, general guidelines for reducing detailed mechanisms for multicomponent fuels are discussed.

  1. Appendix A: Reference case

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

    and related equipment 2 ... 0.33 0.33 0.33 0.33 0.35 0.37 0.39 0.5% Computers and related equipment 3 ... 0.13 0.12 0.10 0.08 0.07 0.06 0.05...

  2. Appendix A: Reference case

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

    district services. 2 Includes (but is not limited to) miscellaneous uses such as transformers, medical imaging and other medical equipment, elevators, escalators, off-road...

  3. Appendix A: Reference case

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

    ... 1,096 1,016 1,077 1,114 1,127 1,126 1,121 0.3% Waste coal supplied 2 ... 13 11 14 14 15 17 19...

  4. Appendix A: Reference case

    Gasoline and Diesel Fuel Update (EIA)

    Sources: 2011 and 2012 interregional firm electricity trade data: 2012 seasonal reliability assessments from North American Electric Reliability Council regional entities and...

  5. Appendix A: Reference case

    Gasoline and Diesel Fuel Update (EIA)

    ... 29.52 28.85 29.72 29.67 30.56 31.49 32.63 0.4% Non-renewable energy expenditures by sector (billion 2012 dollars) Residential...

  6. Appendix A: Reference case

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

    523.3 1.5% 1 Does not include water heating portion of load. 2 Includes televisions, set-top boxes, home theater systems, DVD players, and video game consoles. 3 Includes desktop...

  7. Appendix A: Reference case

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

    12.92 12.90 13.09 -0.2% 1 Commercial trucks 8,501 to 10,000 pounds gross vehicle weight rating. 2 CAFE standard based on projected new vehicle sales. 3 Includes CAFE credits for...

  8. Appendix A: Reference case

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

    Information Administration Annual Energy Outlook 2014 Table A18. Energy-related carbon dioxide emissions by sector and source (million metric tons, unless otherwise noted)...

  9. Appendix A: Reference case

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

    2012-2040 (percent) 2011 2012 2020 2025 2030 2035 2040 Energy consumption Residential Propane ... 0.51 0.51 0.42 0.40...

  10. Appendix A: Reference case

    Gasoline and Diesel Fuel Update (EIA)

    ... 4,370 4,525 5,735 6,467 7,148 7,784 8,443 2.3% Agriculture, mining, and construction ... 1,556 1,623 2,226 2,311 2,389 2,457...

  11. Appendix A: Reference case

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

    supplies. 2 Includes lease condensate. 3 Tight oil represents resources in low-permeability reservoirs, including shale and chalk formations. The specific plays included in...

  12. Appendix A: Reference case

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

    DC, September 2013). 2011 and 2012 natural gas spot price at Henry Hub: Thomson Reuters. 2011 and 2012 electric power prices: EIA, Electric Power Monthly, DOEEIA-0226,...

  13. Appendix A: Reference case

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

    2011 and 2012 Brent and West Texas Intermediate crude oil spot prices: Thomson Reuters. 2011 and 2012 average imported crude oil cost: U.S. Energy Information...

  14. Appendix A: Reference case

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

    ... 9,429 9,603 11,592 12,773 14,220 15,828 17,635 2.2% Real investment ... 1,744 1,914 2,876 3,269 3,740...

  15. Appendix A: Reference case

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

    road oil, still gas, special naphthas, petroleum coke, crude oil product supplied, methanol, and miscellaneous petroleum products. 14 Includes energy for combined heat and...

  16. Appendix A: Reference case

    Gasoline and Diesel Fuel Update (EIA)

    energy. See Table A17 for selected nonmarketed residential and commercial renewable energy data. 5 Includes non-biogenic municipal waste, liquid hydrogen, methanol, and some...

  17. Appendix A: Reference case

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

    Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, and the United Kingdom. 3 Other Europe and Eurasia Albania, Armenia, Azerbaijan,...

  18. Appendix A: Reference case

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

    ... 133.0 147.6 173.1 175.0 178.2 184.2 199.2 1.1% Distributed generation (natural gas) 7 ... 0.0 0.0 1.6 3.3 4.6 6.2 8.9 - -...

  19. Appendix A: Reference case

    Gasoline and Diesel Fuel Update (EIA)

    sources 5 ... 476 459 600 634 660 686 735 1.7% Distributed generation (natural gas) ... 0 0 1 2 2 3 4 - - Total...

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

    On December 12, 2005, the reference case projections from ''Annual Energy Outlook 2006'' (AEO 2006) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past five AEO releases (AEO 2001-AEO

  2. Wind Power Forecasting Data

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

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

  3. probabilistic energy production forecasts

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

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

  4. Wind Power Forecasting

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

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

  5. Forecasting Water Quality & Biodiversity

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

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

    On December 5, 2006, the reference case projections from 'Annual Energy Outlook 2007' (AEO 2007) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past six years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past six years at least, levelized cost comparisons of fixed-price renewable generation with variable-price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are 'biased' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2007. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past six AEO releases (AEO 2001-AEO 2006), we

  7. NREL: Transmission Grid Integration - Forecasting

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

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

  8. 2016 Solar Forecasting Workshop

    Office of Energy Efficiency and Renewable Energy (EERE)

    On August 3, 2016, the SunShot Initiative's systems integration subprogram hosted the Solar Forecasting Workshop to convene experts in the areas of bulk power system operations, distribution system operations, weather and solar irradiance forecasting, and photovoltaic system operation and modeling. The goal was to identify the technical challenges and opportunities in solar forecasting as a capability that can significantly reduce the integration cost of high levels of solar energy into the electricity grid. This will help SunShot to assess current technology and practices in this field and identify the gaps and needs for further research.

  9. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Biological and Environmental Research May 7-8, 2009 Invitation Workshop Invitation Letter...

  10. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Basic Energy Sciences February 9-10, 2010 Official DOE Invitation Workshop Invitation...

  11. Today's Forecast: Improved Wind Predictions

    Broader source: Energy.gov [DOE]

    Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable.

  12. Solar Forecast Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  13. Acquisition Forecast | Department of Energy

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

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

  14. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Basic Energy Sciences February 9-10, 2010 Official DOE Invitation Workshop Invitation Letter from DOE Associate Directors Last edited: 2016-04-29 11:35:05

  15. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 1. Wind and Turbulence

    SciTech Connect (OSTI)

    Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott

    2015-09-25

    We found that numerical-weather-prediction models are often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense horizontally- and vertically-resolved geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City and the simulated fields important to transport and dispersion models were compared to measurements from a number of sodars, tower-based sonic anemometers, and balloon soundings located in the greater metropolitan area. Time histories of computed wind speed, wind direction, turbulent kinetic energy (e), friction velocity (u* ), and reciprocal Obukhov length (1 / L) were compared to measurements over the 1-month field campaign. Vertical profiles of wind speed, potential temperature (θ ), and e were compared during short intensive operating periods. The WRF model was typically able to replicate the measured diurnal variation of the wind fields, but with an average absolute wind direction and speed difference of 35° and 1.9 m s-1 , respectively. Then, using the Mellor-Yamada-Janjic (MYJ) surface-layer scheme, the WRF model was found to generally underpredict surface-layer TKE but overpredict u* that was observed above a suburban region of Oklahoma City. The TKE-threshold method used by the WRF model’s MYJ surface-layer scheme to compute the boundary-layer height (h) consistently overestimated h derived from a θ gradient method whether using observed or modelled θ profiles.

  16. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 1. Wind and Turbulence

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

    Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott

    2015-09-25

    We found that numerical-weather-prediction models are often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense horizontally- and vertically-resolved geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City and the simulated fields important to transport and dispersion models were compared to measurements from a number of sodars, tower-based sonic anemometers, and balloon soundings located in the greater metropolitan area. Time histories of computed windmore » speed, wind direction, turbulent kinetic energy (e), friction velocity (u* ), and reciprocal Obukhov length (1 / L) were compared to measurements over the 1-month field campaign. Vertical profiles of wind speed, potential temperature (θ ), and e were compared during short intensive operating periods. The WRF model was typically able to replicate the measured diurnal variation of the wind fields, but with an average absolute wind direction and speed difference of 35° and 1.9 m s-1 , respectively. Then, using the Mellor-Yamada-Janjic (MYJ) surface-layer scheme, the WRF model was found to generally underpredict surface-layer TKE but overpredict u* that was observed above a suburban region of Oklahoma City. The TKE-threshold method used by the WRF model’s MYJ surface-layer scheme to compute the boundary-layer height (h) consistently overestimated h derived from a θ gradient method whether using observed or modelled θ profiles.« less

  17. Reference Materials

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

    Reference Materials Reference Materials Large Scale Computing and Storage Requirements for Biological and Environmental Research May 7-8, 2009 Invitation Workshop Invitation Letter from DOE Associate Directors Workshop Invitation Letter from DOE ASCR Program Manager Yukiko Sekine Last edited: 2016-04-29 11:34:54

  18. Quick Reference

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

    Reference 2015 Annual Planning Summary (APS) User's Guide 1, 2 PART 1 OFFICE Enter the office preparing this APS. NEPA REVIEWS Select one of two responses. SITE-WIDE EISs Select...

  19. Using Wikipedia to forecast diseases

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

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

  20. Baseline and Target Values for PV Forecasts: Toward Improved...

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

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

  1. Reference Material

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

    Reference Materials There are a variety of reference materials the NSSAB utilizes and have been made available on its website. Documents Fact Sheets - links to Department of Energy Nevada Field Office webpage Public Reading Room NTA Public Reading Facility Open Monday through Friday, 7:30 am to 4:30 pm (except holidays) 755C East Flamingo Road Las Vegas, Nevada 89119 Phone (702) 794-5106 http://www.nv.doe.gov/library/testingarchive.aspx DOE Electronic Database Also available to the public is an

  2. The NEPA reference guide

    SciTech Connect (OSTI)

    Swartz, L.L.; Reinke, D.C.

    1999-10-01

    The NEPA Reference Guide conveniently organizes and indexes National Environmental Policy Act (NEPA) and Council on Environmental Quality (CEQ) regulations and guidance, along with relevant federal case law, all in one place. It allows the user to quickly learn the statutory, regulatory, and case law authority for a large number of NEPA subjects. A unique feature of The NEPA Reference Guide is its detailed index that includes a large number of diverse NEPA subjects. The index enables users to find and compile any statutory, regulatory (including CEQ guidance), and case law original source material and references on virtually any NEPA subject. This will be an especially useful tool for new NEPA practitioners who need to become immersed in a particular subject quickly.

  3. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01

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

  4. The forecast calls for flu

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

    Science on the Hill: The forecast calls for flu Using mathematics, computer programs, ... We're getting close. Using mathematics, computer programs, statistics and information ...

  5. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

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

  6. Appendix A. Reference case projections

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

    4.3 4.5 4.8 5.1 5.0 1.4 Natural gas plant liquids 3.1 3.3 3.4 4.0 4.2 4.4 4.8 4.7 1.2 Biofuels c 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - Coal-to-liquids 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -...

  7. Appendix A. Reference case projections

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

    4.6 4.9 5.3 5.8 5.9 1.9 Natural gas plant liquids 3.1 3.3 3.4 4.3 4.6 4.9 5.3 5.3 1.6 Biofuels c 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - Coal-to-liquids 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -...

  8. Appendix A: Reference case projections

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

    Table F1. Total world delivered energy consumption by end-use sector and fuel, 2011-40 ... 4.7 4.8 4.5 4.3 4.1 4.1 4.0 -0.6 Electricity 18.0 18.4 22.5 25.5 28.6 32.0 35.8 ...

  9. Appendix A. Reference case projections

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

    9.7 15.3 15.2 14.2 13.8 13.5 1.2 Canada 3.4 3.6 3.7 5.4 6.4 7.3 7.8 8.0 2.7 Mexico and Chile 3.0 3.0 3.0 3.1 3.4 3.7 3.9 4.2 1.1 OECD Europe 4.9 4.6 4.3 3.3 3.2 3.2 3.2 3.4 -1.0...

  10. Appendix A. Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    9.7 13.6 12.9 11.7 11.2 10.6 0.4 Canada 3.4 3.6 3.7 4.7 5.1 5.5 5.7 5.8 1.6 Mexico and Chile 3.0 3.0 3.0 2.4 2.0 2.0 2.1 2.2 -1.0 OECD Europe 4.9 4.6 4.3 3.1 2.9 2.5 2.4 2.5 -2.0...

  11. Appendix A. Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    Persian Gulf Share of World Production 29% 29% 31% 32% 35% 38% 40% 42% a Crude and lease condensate includes tight oil, shale oil, extra-heavy oil, field condensate, and bitumen. b ...

  12. Appendix A. Reference case projections

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

    Persian Gulf Share of World Production 29% 29% 31% 24% 24% 26% 27% 28% a Crude and lease condensate includes tight oil, shale oil, extra-heavy oil, field condensate, and bitumen. b ...

  13. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    Non-OECD Asia 168.2 175.9 222.7 246.4 269.9 295.1 322.1 2.2 China 109.4 115.0 147.3 159.4 ... Non-OECD Asia 26,261 27,914 44,139 56,222 69,542 84,680 102,015 4.7 China 13,286 14,309 ...

  14. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    1,708 2,383 2,612 2,840 3,079 3,332 2.4 China 1,065 1,153 1,657 1,808 1,937 2,066 2,194 ... Non-OECD Asia 56 56 55 53 50 48 46 -0.7 China 8 8 8 7 7 7 6 -0.9 India 8 7 7 7 7 7 6 ...

  15. Appendix A: Reference case projections

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

    Asia 8.2 8.3 8.9 9.1 9.2 9.6 9.9 0.6 China 4.4 4.4 4.9 5.2 5.5 6.0 6.3 1.2 India 1.0 ... Asia 7.2 7.2 7.4 7.2 7.0 7.1 6.9 -0.2 China 4.1 4.1 4.3 4.5 4.4 4.7 4.7 0.5 India 0.8 ...

  16. Appendix A: Reference case projections

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

    ... OECD Asia 5.7 5.5 5.4 5.3 5.1 4.9 4.8 -0.5 Japan 4.9 4.7 4.7 4.6 4.4 4.3 4.1 -0.5 South ... Non-OECD Asia 6.4 6.3 5.0 4.4 3.9 3.5 3.2 -2.4 China 8.2 8.0 6.4 5.4 4.7 4.1 3.7 -2.8 ...

  17. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    OECD Asia 203 204 207 208 208 207 206 0.0 Japan 127 127 125 123 120 117 114 -0.4 South ... Non-OECD Asia 3,691 3,730 4,013 4,159 4,278 4,373 4,443 0.6 China 1,373 1,381 1,435 1,450 ...

  18. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    6 Appendix H Table H10. World installed solar generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 5 8 32 36 44 54 67 7.7 United States a 4 8 28 32 39 48 61 7.7 Canada 1 1 2 3 3 4 4 5.9 Mexico and Chile 0 0 2 2 2 2 3 14.4 OECD Europe 52 70 93 93 93 94 98 1.2 OECD Asia 7 9 45 51 57 59 60 6.9 Japan 5 7 38 43 48 49 49 7.4 South Korea 1 1 2 3 4 4 4 5.1 Australia

  19. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    8 Appendix H Table H12. World total net electricity generation by region and country, 2011-40 (billion kilowatthours) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 5,071 5,017 5,449 5,724 6,036 6,359 6,727 1.1 United States a 4,102 4,055 4,351 4,513 4,691 4,860 5,056 0.8 Canada 627 616 692 748 809 880 958 1.6 Mexico and Chile 342 346 406 463 535 618 713 2.6 OECD Europe 3,455 3,483 3,858 4,090 4,328 4,590 4,889 1.2

  20. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    0 Appendix H Table H14. World net natural gas-fred electricity generation by region and country, 2011-40 (billion kilowatthours) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 1,234 1,446 1,396 1,600 1,840 2,048 2,237 1.6 United States a 1,014 1,228 1,117 1,223 1,371 1,478 1,569 0.9 Canada 61 63 97 136 187 230 272 5.3 Mexico and Chile 160 154 182 240 282 340 396 3.4 OECD Europe 766 645 655 746 905 1,056 1,321 2.6

  1. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    2 Appendix H Table H16. World net nuclear electricity generation by region and country, 2011-40 (billion kilowatthours) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 888 867 902 891 901 900 924 0.2 United States a 790 769 804 808 808 812 833 0.3 Canada 88 89 86 72 72 67 62 -1.3 Mexico and Chile 9 8 12 12 20 20 29 4.5 OECD Europe 861 837 845 879 930 948 896 0.2 OECD Asia 304 161 381 437 457 450 427 3.5 Japan 156 17

  2. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    4 Appendix H Table H18. World net hydroelectric electricity generation by region and country, 2011-40 (billion kilowatthours) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 747 703 764 784 806 831 887 0.8 United States a 319 275 292 294 295 295 297 0.3 Canada 372 377 403 414 425 437 475 0.8 Mexico and Chile 57 51 68 76 86 99 114 2.9 OECD Europe 498 556 592 617 617 617 657 0.6 OECD Asia 128 115 127 131 135 143 153

  3. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    8 Appendix H Table H2. World installed liquids-fred generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 125 121 108 98 92 87 85 -1.2 United States a 105 101 89 80 75 71 70 -1.3 Canada 4 4 4 4 4 4 3 -1.0 Mexico and Chile 16 16 14 14 13 12 12 -1.0 OECD Europe 50 50 47 45 43 41 39 -0.9 OECD Asia 58 59 54 52 49 47 45 -1.0 Japan 52 52 49 46 44 42 40 -1.0 South

  4. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    6 Appendix H Table H20. World net geothermal electricity generation by region and country, 2011-40 (billion kilowatthours) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 22 21 37 49 64 75 85 5.0 United States a 15 16 27 39 52 62 70 5.5 Canada 0 0 0 0 0 0 0 - Mexico and Chile 7 6 10 10 11 13 15 3.5 OECD Europe 11 12 21 23 23 23 25 2.7 OECD Asia 9 9 17 18 20 22 25 3.9 Japan 3 3 3 3 3 3 3 0.1 South Korea 0 0 1 1 2 2 2

  5. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    8 Appendix H Table H22. World net other renewable electricity generation by region and country, 2011-40 (billion kilowatthours) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 87 94 125 151 169 191 210 2.9 United States a 75 77 103 115 119 125 138 2.1 Canada 6 9 14 28 41 55 60 7.0 Mexico and Chile 6 8 8 8 9 11 13 1.8 OECD Europe 155 149 201 210 210 210 224 1.5 OECD Asia 28 37 60 71 80 84 87 3.1 Japan 23 33 38 44 50

  6. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    0 Appendix H Table H4. World installed coal-fred generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 333 327 279 276 272 272 271 -0.7 United States a 314 308 263 260 260 260 260 -0.6 Canada 10 10 7 7 3 3 2 -5.2 Mexico and Chile 9 9 9 9 9 9 9 -0.2 OECD Europe 197 198 207 200 194 188 183 -0.3 OECD Asia 109 112 117 113 111 109 110 -0.1 Japan 50 50 49 47 46 44 43

  7. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    2 Appendix H Table H6. World installed hydroelectric and other renewable generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 273 293 372 396 424 460 507 2.0 United States a 168 185 233 240 252 273 301 1.8 Canada 85 87 106 114 123 132 144 1.8 Mexico and Chile 20 21 34 42 48 55 62 3.9 OECD Europe 337 372 514 534 553 594 626 1.9 OECD Asia 54 57 115 129 145 153

  8. Appendix A: Reference case projections

    Gasoline and Diesel Fuel Update (EIA)

    4 Appendix H Table H8. World installed wind-powered generating capacity by region and country, 2011-40 (gigawatts) Region/country History Projections Average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 OECD OECD Americas 53 67 107 117 127 141 159 3.1 United States a 47 59 83 84 87 97 110 2.2 Canada 5 6 15 18 20 22 24 5.0 Mexico and Chile 1 2 9 16 19 22 25 10.1 OECD Europe 94 107 189 203 222 263 277 3.5 OECD Asia 6 6 24 29 37 40 44 7.2 Japan 2 3 3 5 8 8 8 4.1 South Korea 0 0

  9. Poroelastic references

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

    Christina Morency

    This file contains a list of relevant references on the Biot theory (forward and inverse approaches), the double-porosity and dual-permeability theory, and seismic wave propagation in fracture porous media, in RIS format, to approach seismic monitoring in a complex fractured porous medium such as Brady?s Geothermal Field.

  10. Poroelastic references

    SciTech Connect (OSTI)

    Christina Morency

    2014-12-12

    This file contains a list of relevant references on the Biot theory (forward and inverse approaches), the double-porosity and dual-permeability theory, and seismic wave propagation in fracture porous media, in RIS format, to approach seismic monitoring in a complex fractured porous medium such as Brady?s Geothermal Field.

  11. Reference Materials

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

    home page NERSC science requirements workshop page NERSC science requirements case study FAQ Workshop Agenda Previous NERSC Requirements Workshops Biological and...

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

    SciTech Connect (OSTI)

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J.

    2011-12-06

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

  14. Reference Materials

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

    ID 412- 11/16/2012 - Page 1 Log No 2012-263 Reference Materials * Transporting Radioactive Waste to the Nevada National Security Site fact sheet (ww.nv.energy.gov/library/factsheets/DOENV_990.pdf) - Generators contract with commercial carriers - U.S. Department of Transportation regulations require carriers to select routes which minimize radiological risk * Drivers Route and Shipment Information Questionnaire completed by drivers to document routes taken to the NNSS upon entry into Nevada -

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

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

    Wind Forecasting Improvement Project in Complex Terrain Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain February 12, 2014 - 10:47am ...

  16. Solar Energy Market Forecast | Open Energy Information

    Open Energy Info (EERE)

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

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

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

    Soft Costs Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Project Profile: Forecasting and Influencing Technological Progress in Solar ...

  18. National Oceanic and Atmospheric Administration Provides Forecasting...

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

    ... will share their expertise with CLASIC and CHAPS forecasters and project leaders as they consult on the forecast that will determine the day's operations plan. -- Storm Prediction ...

  19. Intermediate future forecasting system

    SciTech Connect (OSTI)

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

    1983-12-01

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

  20. Quick Reference

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

    Quick Reference 2016 Annual Planning Summary (APS) User's Guide 1, 2 PART 1 OFFICE Enter the office preparing this APS. NEPA REVIEWS Select one of two responses. SITE-WIDE Select one of three responses. DOCUMENT NUMBER & TITLE Enter the DOE NEPA identification number if available, e.g., DOE/EIS-XXXX. If no document number has been assigned, enter N/A. Also enter the document title. Text is limited to 350 characters. PART 2 TYPE Select the type of document using the dropdown menu. STATUS

  1. Tracking stochastic resonance curves using an assisted reference model

    SciTech Connect (OSTI)

    Caldern Ramrez, Mario; Rico Martnez, Ramiro; Parmananda, P.

    2015-06-15

    The optimal noise amplitude for Stochastic Resonance (SR) is located employing an Artificial Neural Network (ANN) reference model with a nonlinear predictive capability. A modified Kalman Filter (KF) was coupled to this reference model in order to compensate for semi-quantitative forecast errors. Three manifestations of stochastic resonance, namely, Periodic Stochastic Resonance (PSR), Aperiodic Stochastic Resonance (ASR), and finally Coherence Resonance (CR) were considered. Using noise amplitude as the control parameter, for the case of PSR and ASR, the cross-correlation curve between the sub-threshold input signal and the system response is tracked. However, using the same parameter the Normalized Variance curve is tracked for the case of CR. The goal of the present work is to track these curves and converge to their respective extremal points. The ANN reference model strategy captures and subsequently predicts the nonlinear features of the model system while the KF compensates for the perturbations inherent to the superimposed noise. This technique, implemented in the FitzHugh-Nagumo model, enabled us to track the resonance curves and eventually locate their optimal (extremal) values. This would yield the optimal value of noise for the three manifestations of the SR phenomena.

  2. Science on Tap - Forecasting illness

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

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

  3. Aluminum reference electrode

    DOE Patents [OSTI]

    Sadoway, D.R.

    1988-08-16

    A stable reference electrode is described for use in monitoring and controlling the process of electrolytic reduction of a metal. In the case of Hall cell reduction of aluminum, the reference electrode comprises a pool of molten aluminum and a solution of molten cryolite, Na[sub 3]AlF[sub 6], wherein the electrical connection to the molten aluminum does not contact the highly corrosive molten salt solution. This is accomplished by altering the density of either the aluminum (decreasing the density) or the electrolyte (increasing the density) so that the aluminum floats on top of the molten salt solution. 1 fig.

  4. Aluminum reference electrode

    DOE Patents [OSTI]

    Sadoway, Donald R.

    1988-01-01

    A stable reference electrode for use in monitoring and controlling the process of electrolytic reduction of a metal. In the case of Hall cell reduction of aluminum, the reference electrode comprises a pool of molten aluminum and a solution of molten cryolite, Na.sub.3 AlF.sub.6, wherein the electrical connection to the molten aluminum does not contact the highly corrosive molten salt solution. This is accomplished by altering the density of either the aluminum (decreasing the density) or the electrolyte (increasing the density) so that the aluminum floats on top of the molten salt solution.

  5. Acquisition Forecast Download | Department of Energy

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

    Acquisition Forecast Download Acquisition Forecast Download Click on the link to download a copy of the DOE HQ Acquisition Forecast. Acquisition-Forecast-2016-07-20.xlsx (72.85 KB) More Documents & Publications Small Business Program Manager Directory EA-1900: Notice of Availability of a Draft Environmental Assessment Assessment Report: OAS-V-15-01

  6. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01

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

  7. Energy reference handbook. Third edition

    SciTech Connect (OSTI)

    Not Available

    1985-01-01

    The energy field has exploded since the OPEC oil embargo of 1973. Terms that did not even exist several years ago are now being used. In addition, many words have developed interpretations somewhat different from their commonly accepted meanings. The 3rd Edition of the Energy Reference Handbook records and standardizes these terms in a comprehensive glossary. Special emphasis is placed on providing terms and definitions in the area of alternative fuels-synthetics from coal and oil shale; solar; wind; biomass; geothermal; and more - as well as traditional fossil fuels. In total, more than 3,500 terms, key words, and phrases used daily in energy literature are referenced. In addition to these definitions, conversion tables, diagrams, maps, tables, and charts on various aspects of energy which forecast the reserves of fuel resources, plus other information relevant to energy resources and technologies are found in this reference.

  8. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01

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

  9. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect (OSTI)

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

    2015-05-14

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

  10. Forecasting the 2013–2014 influenza season using Wikipedia

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

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

    2015-05-14

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

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

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

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

  12. Picture of the Week: Forecasting Flu

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

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

  13. The Value of Wind Power Forecasting

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

    ... day-ahead wind generation forecasts yields an average of 195M savings in annual operating costs. Figure 6 shows how operating cost savings vary with improvements in forecasting. ...

  14. EIA lowers forecast for summer gasoline prices

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

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

  15. UPF Forecast | Y-12 National Security Complex

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

    Subcontracting / Subcontracting Forecasts / UPF Forecast UPF Forecast UPF Procurement provides the following forecast of subcontracting opportunities. Keep in mind that these requirements may be revised or cancelled, depending on program budget funding or departmental needs. If you have questions or would like to express an interest in any of the opportunities listed below, contact UPF Procurement. Descriptiona Methodb NAICS Est. Dollar Range RFP release/ Award datec Buyer/ Phone Commodities

  16. Wind Forecasting Improvement Project | Department of Energy

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

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

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

    SciTech Connect (OSTI)

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

    2008-01-07

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

    .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.

  20. Supply Forecast and Analysis (SFA)

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

    Matthew Langholtz Science Team Leader Oak Ridge National Laboratory DOE Bioenergy Technologies Office (BETO) 2015 Project Peer Review Supply Forecast and Analysis (SFA) 2 | Bioenergy Technologies Office Goal Statement * Provide timely and credible estimates of feedstock supplies and prices to support - the development of a bioeconomy; feedstock demand analysis of EISA, RFS2, and RPS mandates - the data and analysis of other projects in Analysis and Sustainability, Feedstock Supply and Logistics,

  1. Subsurface Knowledge Reference Page

    Broader source: Energy.gov [DOE]

    The below listing provides additional references related to Subsurface & Groundwater Remediation.  The references are categorized by documents types (e.g., Strategic Plans, Groundwater Plume...

  2. ARM - CARES - Tracer Forecast for CARES

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

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

  3. LED Lighting Forecast | Department of Energy

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

    Publications » Market Studies » LED Lighting Forecast LED Lighting Forecast 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. With declining costs and improving performance, LED products have been seeing increased adoption for general illumination applications. This is a positive development in terms of energy consumption, as LEDs use significantly

  4. NREL: Resource Assessment and Forecasting Home Page

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

    are used to plan and develop renewable energy technologies and support climate change research. Learn more about NREL's resource assessment and forecasting research:...

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

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

    There is no cost to participate and all applicants are encouraged to attend. To join the ... Related Articles Upcoming Funding Opportunity for Wind Forecasting Improvement Project in ...

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

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

    This module reviews metrics such as cost and schedule variance along with cost and schedule performance indices. In addition, this module will outline forecasting tools such as ...

  7. Forecast and Funding Arrangements - Hanford Site

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

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

  8. NREL: Resource Assessment and Forecasting - Webmaster

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

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

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

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

    and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices 63wateruseoptimizationprojectanlgasper.ppt (7.72 MB) More ...

  10. AVLIS: a technical and economic forecast

    SciTech Connect (OSTI)

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

    1986-01-01

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

  11. Sensing, Measurement, and Forecasting | Grid Modernization | NREL

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

    Sensing, Measurement, and Forecasting NREL measures weather resources and power systems, forecasts renewable resources and grid conditions, and converts measurements into operational intelligence to support a modern grid. Photo of solar resource monitoring equipment Modernizing the grid involves assessing its health in real time, predicting its behavior and potential disruptions, and quickly responding to events-which requires understanding vital parameters throughout the electric

  12. Study forecasts disappearance of conifers due to climate change

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

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

  13. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

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

    Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen MJ ... Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen, ...

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

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

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

  15. The case for unified linear reference system

    SciTech Connect (OSTI)

    Espinoza, J. Jr.; Mackoy, R.D.; Fletcher, D.R.

    1997-06-01

    The transportation industry distinguishes its activities and data into three functionally and institutionally distinct domains. Transportation infrastructure management activities make transport links (e.g., roads, rail lines, transit routes) available for travel. In contrast, civilian and military transport operations focus on finding and using the best transport links. Each of these three transportation interest groups - transportation facility operators, civilian and military transportation users - currently collects and maintains separate, often redundant or inconsistent information concerning the location and status of the transportation system, the vehicles using the system, and the passengers and freight (or material) being conveyed. Although there has been some progress made in integrating data within each domain, little emphasis has been placed on identifying and improving the flow of information between them. Because activities initiated in one domain affect conditions in the others, defining these flows is crucial to the next generation of planners, traffic managers and customers of transportation services. For example, construction and maintenance activities affect civilian and military route choices and travel times; large scale military movements disrupt civilian travel and have potentially major effects on the infrastructure and so on. This intertwined interest in the transportation system implies the need for data integration not only within each sphere of interest but among the spheres as well. Although recent policy statements by the U.S. Departments of Transportation and Defense and ITS America indicate a desire to combine and share information resources, there are enormous technical and institutional barriers that need to be overcome.

  16. Annual Energy Outlook 2011 Reference Case

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

    (RFS2, for example) * Prices of primary energy (crude oil, etc.) LP * Minimize cost to ... Biomass- based diesel FAME biodiesel Green Diesel Cellulosic Drop-in For use as motor ...

  17. Annual Energy Outlook 2011 Reference Case

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

    ... and engineering notes: - Fuel economy (Final Rule 2017-2025 and Lumped Parameter Model) - Cost (derived from Final Rule ... Gaseous and fuel cell AEO2013 Transportation ...

  18. Annual Energy Outlook 2011 Reference Case

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

    Liquid Fuels Markets Working Group Meeting Office of Petroleum, Natural Gas & Biofuels Analysis October 4, 2012 | Washington, DC Preliminary AEO2013: Biofuels and Petroleum WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE Overview 2 Office of Petroleum, Natural Gas, & Biofuels Analysis Working Group Presentation for Discussion Purposes Washington DC, October 4, 2012 DO NOT QUOTE OR CITE as results are subject to change * World oil

  19. Annual Energy Outlook 2011 Reference Case

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

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

  20. Annual Energy Outlook 2011 Reference Case

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

    of Clean Air Interstate Rule (CAIR) after U.S. Court of Appeals vacated Cross-State Air Pollution Rule (CSAPR) * Continued to coordinate with Survey Team and Statistics Group to: - ...

  1. Coal Fired Power Generation Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  2. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  5. Flood Forecasting in River System Using ANFIS

    SciTech Connect (OSTI)

    Ullah, Nazrin; Choudhury, P.

    2010-10-26

    The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.

  6. Text-Alternative Version LED Lighting Forecast

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  7. energy data + forecasting | OpenEI Community

    Open Energy Info (EERE)

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

  8. High frequency reference electrode

    DOE Patents [OSTI]

    Kronberg, J.W.

    1994-05-31

    A high frequency reference electrode for electrochemical experiments comprises a mercury-calomel or silver-silver chloride reference electrode with a layer of platinum around it and a layer of a chemically and electrically resistant material such as TEFLON around the platinum covering all but a small ring or halo' at the tip of the reference electrode, adjacent to the active portion of the reference electrode. The voltage output of the platinum layer, which serves as a redox electrode, and that of the reference electrode are coupled by a capacitor or a set of capacitors and the coupled output transmitted to a standard laboratory potentiostat. The platinum may be applied by thermal decomposition to the surface of the reference electrode. The electrode provides superior high-frequency response over conventional electrodes. 4 figs.

  9. High frequency reference electrode

    DOE Patents [OSTI]

    Kronberg, James W.

    1994-01-01

    A high frequency reference electrode for electrochemical experiments comprises a mercury-calomel or silver-silver chloride reference electrode with a layer of platinum around it and a layer of a chemically and electrically resistant material such as TEFLON around the platinum covering all but a small ring or "halo" at the tip of the reference electrode, adjacent to the active portion of the reference electrode. The voltage output of the platinum layer, which serves as a redox electrode, and that of the reference electrode are coupled by a capacitor or a set of capacitors and the coupled output transmitted to a standard laboratory potentiostat. The platinum may be applied by thermal decomposition to the surface of the reference electrode. The electrode provides superior high-frequency response over conventional electrodes.

  10. Optical voltage reference

    DOE Patents [OSTI]

    Rankin, Richard; Kotter, Dale

    1994-01-01

    An optical voltage reference for providing an alternative to a battery source. The optical reference apparatus provides a temperature stable, high precision, isolated voltage reference through the use of optical isolation techniques to eliminate current and impedance coupling errors. Pulse rate frequency modulation is employed to eliminate errors in the optical transmission link while phase-lock feedback is employed to stabilize the frequency to voltage transfer function.

  11. Optical voltage reference

    DOE Patents [OSTI]

    Rankin, R.; Kotter, D.

    1994-04-26

    An optical voltage reference for providing an alternative to a battery source is described. The optical reference apparatus provides a temperature stable, high precision, isolated voltage reference through the use of optical isolation techniques to eliminate current and impedance coupling errors. Pulse rate frequency modulation is employed to eliminate errors in the optical transmission link while phase-lock feedback is employed to stabilize the frequency to voltage transfer function. 2 figures.

  12. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01

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

  13. Reference Model Project (RMP)

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

    ... Reference Model 5: Oscillating Surge Wave Energy Converter. NRELTP-5000-62861. Golden, CO, National Renewable Energy Laboratory (NREL). January 2015. Power Conversion Chain Design ...

  14. EFRC Management Reference Document

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

    EFRC management reference document Energy Frontier Research Centers Acknowledgments of Support (v.1, October 2009) Office of Basic Energy Sciences Office of Science US Department ...

  15. Science on the Hill: The forecast calls for flu

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

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

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

    SciTech Connect (OSTI)

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

    2014-05-01

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

  17. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

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

    1994-09-01

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

  18. Reference Documents | National Nuclear Security Administration | (NNSA)

    National Nuclear Security Administration (NNSA)

    Reference Documents Summary References Main Draft SEIS References Additional SEIS References Appendix C References Appendix D References Appendix E References Appendix F References Learn More Summary References Main Draft SEIS References Appendix C References Appendix D References Appendix E References Appendix F References Additional SEIS references

  19. Sandia Energy - Reference Model Documents

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

    Documents Home Stationary Power Energy Conversion Efficiency Water Power Reference Model Project (RMP) Reference Model Documents Reference Model DocumentsTara Camacho-Lopez2015-05-...

  20. Multifunctional reference electrode (Patent) | DOEPatents

    Office of Scientific and Technical Information (OSTI)

    Multifunctional reference electrode Title: Multifunctional reference electrode A multifunctional, low mass reference electrode of a nickel tube, thermocouple means inside the ...

  1. reference | OpenEI Community

    Open Energy Info (EERE)

    reference Home Jweers's picture Submitted by Jweers(88) Contributor 7 August, 2013 - 18:23 New Robust References citation citing developer formatting reference Semantic Mediawiki...

  2. Uranium reference materials

    SciTech Connect (OSTI)

    Donivan, S.; Chessmore, R.

    1987-07-01

    The Technical Measurements Center has prepared uranium mill tailings reference materials for use by remedial action contractors and cognizant federal and state agencies. Four materials were prepared with varying concentrations of radionuclides, using three tailings materials and a river-bottom soil diluent. All materials were ground, dried, and blended thoroughly to ensure homogeneity. The analyses on which the recommended values for nuclides in the reference materials are based were performed, using independent methods, by the UNC Geotech (UNC) Chemistry Laboratory, Grand Junction, Colorado, and by C.W. Sill (Sill), Idaho National Engineering Laboratory, Idaho Falls, Idaho. Several statistical tests were performed on the analytical data to characterize the reference materials. Results of these tests reveal that the four reference materials are homogeneous and that no large systematic bias exists between the analytical methods used by Sill and those used by TMC. The average values for radionuclides of the two data sets, representing an unbiased estimate, were used as the recommended values for concentrations of nuclides in the reference materials. The recommended concentrations of radionuclides in the four reference materials are provided. Use of these reference materials will aid in providing uniform standardization among measurements made by remedial action contractors. 11 refs., 9 tabs.

  3. Fallout forecasting: 1945-1962

    SciTech Connect (OSTI)

    Kennedy, W.R. Jr.

    1986-03-01

    The delayed hazards of fallout from the detonations of nuclear devices in the atmosphere have always been the concern of those involved in the Test Program. Even before the Trinity Shot (TR-2) of July 16, 1945, many very competent, intelligent scientists and others from all fields of expertise tried their hand at the prediction problems. This resume and collection of parts from reports, memoranda, references, etc., endeavor to chronologically outline prediction methods used operationally in the field during Test Operations of nuclear devices fired into the atmosphere.

  4. Value of Information References

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

    Morency, Christina

    This file contains a list of relevant references on value of information (VOI) in RIS format. VOI provides a quantitative analysis to evaluate the outcome of the combined technologies (seismology, hydrology, geodesy) used to monitor Brady's Geothermal Field.

  5. REFERENCES Baines, W. D.

    Office of Scientific and Technical Information (OSTI)

    REFERENCES Baines, W. D. aud Peterson, E. G., 1951, "An Investigation of Flow Through ... D 50.8 m. A flow facility has been constructed for experiments with these screens. Air ...

  6. Value of Information References

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

    Morency, Christina

    2014-12-12

    This file contains a list of relevant references on value of information (VOI) in RIS format. VOI provides a quantitative analysis to evaluate the outcome of the combined technologies (seismology, hydrology, geodesy) used to monitor Brady's Geothermal Field.

  7. Membrane reference electrode

    DOE Patents [OSTI]

    Redey, Laszlo; Bloom, Ira D.

    1989-01-01

    A reference electrode utilizes a small thin, flat membrane of a highly conductive glass placed on a small diameter insulator tube having a reference material inside in contact with an internal voltage lead. When the sensor is placed in a non-aqueous ionic electrolytic solution, the concentration difference across the glass membrane generates a low voltage signal in precise relationship to the concentration of the species to be measured with high spatial resolution.

  8. Precision displacement reference system

    DOE Patents [OSTI]

    Bieg, Lothar F.; Dubois, Robert R.; Strother, Jerry D.

    2000-02-22

    A precision displacement reference system is described, which enables real time accountability over the applied displacement feedback system to precision machine tools, positioning mechanisms, motion devices, and related operations. As independent measurements of tool location is taken by a displacement feedback system, a rotating reference disk compares feedback counts with performed motion. These measurements are compared to characterize and analyze real time mechanical and control performance during operation.

  9. Membrane reference electrode

    DOE Patents [OSTI]

    Redey, L.; Bloom, I.D.

    1988-01-21

    A reference electrode utilizes a small thin, flat membrane of a highly conductive glass placed on a small diameter insulator tube having a reference material inside in contact with an internal voltage lead. When the sensor is placed in a non-aqueous ionic electrolytic solution, the concentration difference across the glass membrane generates a low voltage signal in precise relationship to the concentration of the species to be measured, with high spatial resolution. 2 figs.

  10. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

    SciTech Connect (OSTI)

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

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.

  11. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

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

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

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based onmore » state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.« less

  12. The Value of Improved Short-Term Wind Power Forecasting

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

    ... up-ramp reserves c down cost in MWh of down-ramp reserves R down MW range for ... power forecasting and the increased gas usage that comes with less-accurate forecasting. ...

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

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

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

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

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

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

  15. Multifunctional reference electrode

    DOE Patents [OSTI]

    Redey, Laszlo; Vissers, Donald R.

    1983-01-01

    A multifunctional, low mass reference electrode of a nickel tube, thermocouple means inside the nickel tube electrically insulated therefrom for measuring the temperature thereof, a housing surrounding the nickel tube, an electrolyte having a fixed sulfide ion activity between the housing and the outer surface of the nickel tube forming the nickel/nickel sulfide/sulfide half-cell. An ion diffusion barrier is associated with the housing in contact with the electrolyte. Also disclosed is a cell using the reference electrode to measure characteristics of a working electrode.

  16. Multifunctional reference electrode

    DOE Patents [OSTI]

    Redey, L.; Vissers, D.R.

    1981-12-30

    A multifunctional, low mass reference electrode of a nickel tube, thermocouple means inside the nickel tube electrically insulated therefrom for measuring the temperature thereof, a housing surrounding the nickel tube, an electrolyte having a fixed sulfide ion activity between the housing and the outer surface of the nickel tube forming the nickel/nickel sulfide/sulfide half-cell are described. An ion diffusion barrier is associated with the housing in contact with the electrolyte. Also disclosed is a cell using the reference electrode to measure characteristics of a working electrode.

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

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01

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

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

    Open Energy Info (EERE)

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

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

    SciTech Connect (OSTI)

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

    2010-04-01

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

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

    SciTech Connect (OSTI)

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

    2010-04-15

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

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

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

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

  2. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    1996-08-01

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

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

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

    Department of Energy Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report.pdf (15.76 MB) More Documents & Publications QER - Comment of Edison Electric Institute (EEI) 1 QER - Comment of Canadian Hydropower Association QER - Comment of Edison Electric Institute (EEI) 2

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

    SciTech Connect (OSTI)

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

    2015-10-30

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

  5. Reference Model Development

    SciTech Connect (OSTI)

    Jepsen, Richard

    2011-11-02

    Presentation from the 2011 Water Peer Review in which principal investigator discusses project progress to develop a representative set of Reference Models (RM) for the MHK industry to develop baseline cost of energy (COE) and evaluate key cost component/system reduction pathways.

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

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

  7. Regional four-dimensional variational data assimilation in a quasi-operational forecasting environment

    SciTech Connect (OSTI)

    Zupanski, M. )

    1993-08-01

    Four-dimensional variational data assimilation is applied to a regional forecast model as part of the development of a new data assimilation system at the National Meteorological Center (NMC). The assimilation employs an operational version of the NMC's new regional forecast model defined in eta vertical coordinates, and data used are operationally produced optimal interpolation (OI) analyses (using the first guess from the NMC's global spectral model), available every 3 h. Humidity and parameterized processes are not included in the adjoint model integration. The calculation of gradients by the adjoint model is approximate since the forecast model is used in its full-physics operational form. All experiments are over a 12-h assimilation period with subsequent 48-h forecast. Three different types of assimilation experiments are performed: (a) adjustment of initial conditions only (standard [open quotes]adjoint[close quotes] approach), (b) adjustment of a correction to the model equations only (variational continuous assimilation), and (c) simultaneous or sequential adjustment of both initial conditions and the correction term. Results indicate significantly better results when the correction term is included in the assimilation. It is shown, for a single case, that the new technique [experiment (c)] is able to produce a forecast better than the current conventional OI assimilation. It is very important to note that these results are obtained with an approximate gradient, calculated from a simplified adjoint model. Thus, it may be possible to perform an operational four-dimensional variational data assimilation of realistic forecast models, even before more complex adjoint models are developed. Also, the results suggest that it may be possible to reduce the large computational cost of assimilation by using only a few iterations of the minimization algorithm. This fast convergence is encouraging from the prospective of operational use. 37 refs., 10 figs., 1 tab.

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

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01

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

  9. OSH technical reference manual

    SciTech Connect (OSTI)

    Not Available

    1993-11-01

    In an evaluation of the Department of Energy (DOE) Occupational Safety and Health programs for government-owned contractor-operated (GOCO) activities, the Department of Labor`s Occupational Safety and Health Administration (OSHA) recommended a technical information exchange program. The intent was to share written safety and health programs, plans, training manuals, and materials within the entire DOE community. The OSH Technical Reference (OTR) helps support the secretary`s response to the OSHA finding by providing a one-stop resource and referral for technical information that relates to safe operations and practice. It also serves as a technical information exchange tool to reference DOE-wide materials pertinent to specific safety topics and, with some modification, as a training aid. The OTR bridges the gap between general safety documents and very specific requirements documents. It is tailored to the DOE community and incorporates DOE field experience.

  10. Reference Model Project (RMP)

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

    Reference Model Project (RMP) - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Energy Defense Waste Management Programs