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)]

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

  2. 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...

  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

    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

  8. 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

  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

    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

  12. 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

  13. 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

  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

    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...

  2. 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...

  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

    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.

  20. 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

  1. 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...

  2. 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...

  3. 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...

  4. 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)...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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,...

  10. 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...

  11. 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...

  12. 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...

  13. 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,...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  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. 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 ...

  3. 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...

  4. 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. ...

  5. 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...

  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

    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

  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

    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.

  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. 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 ...

  20. 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)

  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. 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:...

  4. 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.

  5. 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 ...

  6. 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 ...

  7. 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...

  8. 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...

  9. 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 ...

  10. 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 ...

  11. 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 ...

  12. 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 ...

  13. 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 ...

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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 -...

  6. 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 -...

  7. 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 ...

  8. 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 ...

  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. 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 ...

  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. 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.

  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. 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

  16. 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

  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. 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 ...

  6. 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...

  7. 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...

  8. 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 ...

  9. 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 ...

  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. 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, ...

  13. 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 ...

  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. 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 ...

  16. 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

  17. 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

  18. 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 ...

  19. 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.

  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. 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...

  7. 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....

  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, 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.

  11. 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.

  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. 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 ...

  14. 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 ...

  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. 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.

  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. 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

  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. 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 ...

  5. 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.

  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, 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.

  8. 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.

  9. 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.

  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. 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

  19. 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...

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

    SciTech Connect (OSTI)

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

    2010-04-01

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

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

    SciTech Connect (OSTI)

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

    2010-04-15

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

  2. 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. Alignment reference device

    DOE Patents [OSTI]

    Patton, Gail Y.; Torgerson, Darrel D.

    1987-01-01

    An alignment reference device provides a collimated laser beam that minimizes angular deviations therein. A laser beam source outputs the beam into a single mode optical fiber. The output end of the optical fiber acts as a source of radiant energy and is positioned at the focal point of a lens system where the focal point is positioned within the lens. The output beam reflects off a mirror back to the lens that produces a collimated beam.

  11. 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

  12. Chapter 6 - References

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

    6-1 CHAPTER 6 REFERENCES BLS (Bureau of Labor Statistics), 2002. Bureau of Labor Statistics Data, <http://www.bls.gov/data>, accessed January 25. CAIRS (Computerized Accident/Incident Reporting System), 2002. Statistics, <http://www.eh.doe.gov/cairs/stats.html>, accessed January 30. CEMRC (Carlsbad Environmental Monitoring & Research Center), 2000. Actinide Chemistry and Repository Science Laboratory Initiative, New Mexico State University, Carlsbad, New Mexico, December 15. CEQ

  13. Forecasting hotspots using predictive visual analytics approach

    SciTech Connect (OSTI)

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

    2014-12-30

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

  14. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

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

    2011-02-23

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

  15. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

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

    2014-11-13

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

  16. Global disease monitoring and forecasting with Wikipedia

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

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

    2014-11-13

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

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

    SciTech Connect (OSTI)

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

    2015-08-05

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

  18. Coal Data: A reference

    SciTech Connect (OSTI)

    Not Available

    1991-11-26

    The purpose of Coal Data: A Reference is to provide basic information on the mining and use of coal, an important source of energy in the United States. The report is written for a general audience. The goal is to cover basic material and strike a reasonable compromise between overly generalized statements and detailed analyses. The section ``Coal Terminology and Related Information`` provides additional information about terms mentioned in the text and introduces new terms. Topics covered are US coal deposits, resources and reserves, mining, production, employment and productivity, health and safety, preparation, transportation, supply and stocks, use, coal, the environment, and more. (VC)

  19. STEP Intern Reference Check Sheet

    Broader source: Energy.gov [DOE]

    STEP Intern Reference Check Sheet, from the Tool Kit Framework: Small Town University Energy Program (STEP).

  20. Headquarters Security Quick Reference Book

    Office of Energy Efficiency and Renewable Energy (EERE)

    This quick reference book provides an overview of Department of Energy (DOE) Headquarters (HQ) security programs.

  1. Coal data: A reference

    SciTech Connect (OSTI)

    Not Available

    1995-02-01

    This report, Coal Data: A Reference, summarizes basic information on the mining and use of coal, an important source of energy in the US. This report is written for a general audience. The goal is to cover basic material and strike a reasonable compromise between overly generalized statements and detailed analyses. The section ``Supplemental Figures and Tables`` contains statistics, graphs, maps, and other illustrations that show trends, patterns, geographic locations, and similar coal-related information. The section ``Coal Terminology and Related Information`` provides additional information about terms mentioned in the text and introduces some new terms. The last edition of Coal Data: A Reference was published in 1991. The present edition contains updated data as well as expanded reviews and additional information. Added to the text are discussions of coal quality, coal prices, unions, and strikes. The appendix has been expanded to provide statistics on a variety of additional topics, such as: trends in coal production and royalties from Federal and Indian coal leases, hours worked and earnings for coal mine employment, railroad coal shipments and revenues, waterborne coal traffic, coal export loading terminals, utility coal combustion byproducts, and trace elements in coal. The information in this report has been gleaned mainly from the sources in the bibliography. The reader interested in going beyond the scope of this report should consult these sources. The statistics are largely from reports published by the Energy Information Administration.

  2. Nuclear Science References Database

    SciTech Connect (OSTI)

    Pritychenko, B.; Běták, E.; Singh, B.; Totans, J.

    2014-06-15

    The Nuclear Science References (NSR) database together with its associated Web interface, is the world's only comprehensive source of easily accessible low- and intermediate-energy nuclear physics bibliographic information for more than 210,000 articles since the beginning of nuclear science. The weekly-updated NSR database provides essential support for nuclear data evaluation, compilation and research activities. The principles of the database and Web application development and maintenance are described. Examples of nuclear structure, reaction and decay applications are specifically included. The complete NSR database is freely available at the websites of the National Nuclear Data Center (http://www.nndc.bnl.gov/nsr) and the International Atomic Energy Agency (http://www-nds.iaea.org/nsr)

  3. Long life reference electrode

    DOE Patents [OSTI]

    Yonco, R.M.; Nagy, Z.

    1987-07-30

    An external, reference electrode is provided for long term use with a high temperature, high pressure system. The electrode is arranged in a vertical, electrically insulative tube with an upper portion serving as an electrolyte reservoir and a lower portion in electrolytic communication with the system to be monitored. The lower end portion includes a flow restriction such as a porous plug to limit the electrolyte release into the system. A piston equalized to the system pressure is fitted into the upper portion of the tube to impart a small incremental pressure to the electrolyte. The piston is selected of suitable size and weight to cause only a slight flow of electrolyte through the porous plug into the high pressure system. This prevents contamination of the electrolyte but is of such small flow rate that operating intervals of a month or more can be achieved. 2 figs.

  4. Long life reference electrode

    DOE Patents [OSTI]

    Yonco, Robert M.; Nagy, Zoltan

    1989-01-01

    An external, reference electrode is provided for long term use with a high temperature, high pressure system. The electrode is arranged in a vertical, electrically insulative tube with an upper portion serving as an electrolyte reservior and a lower portion in electrolytic communication with the system to be monitored. The lower end portion includes a flow restriction such as a porous plug to limit the electrolyte release into the system. A piston equalized to the system pressure is fitted into the upper portion of the tube to impart a small incremental pressure to the electrolyte. The piston is selected of suitable size and weight to cause only a slight flow of electrolyte through the porous plug into the high pressure system. This prevents contamination of the electrolyte but is of such small flow rate that operating intervals of a month or more can be achieved.

  5. Long life reference electrode

    DOE Patents [OSTI]

    Yonco, R.M.; Nagy, Z.

    1989-04-04

    An external, reference electrode is provided for long term use with a high temperature, high pressure system. The electrode is arranged in a vertical, electrically insulative tube with an upper portion serving as an electrolyte reservoir and a lower portion in electrolytic communication with the system to be monitored. The lower end portion includes a flow restriction such as a porous plug to limit the electrolyte release into the system. A piston equalized to the system pressure is fitted into the upper portion of the tube to impart a small incremental pressure to the electrolyte. The piston is selected of suitable size and weight to cause only a slight flow of electrolyte through the porous plug into the high pressure system. This prevents contamination of the electrolyte but is of such small flow rate that operating intervals of a month or more can be achieved. 2 figs.

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  7. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

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

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

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

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

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

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

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

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

    Energy Savers [EERE]

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

  11. NREL: Resource Assessment and Forecasting - Data and Resources

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

    Data and Resources National Solar Radiation Database NREL resource assessment and forecasting research information is available from the following sources. Renewable Resource Data ...

  12. Roel Neggers European Centre for Medium-range Weather Forecasts

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

    transition from shallow to deep convection using a dual mass flux boundary layer scheme Roel Neggers European Centre for Medium-range Weather Forecasts Introduction " " % % &...

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

    Office of Scientific and Technical Information (OSTI)

    forecasts for solar-energy applications and 2) to provide vertical profiling capabilities for the study of dynamics (i.e., vertical velocity) and hydrometeors in winter storms. ...

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

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

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

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

    SciTech Connect (OSTI)

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

    2015-12-08

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

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

    Office of Energy Efficiency and Renewable Energy (EERE)

    A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts.

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

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

    ... RIT forecasting is saving costs and improving operational practices for IPC and helping integrate wind power more efficiently and cost effectively. Figure 3 shows how the ...

  18. A Review of Variable Generation Forecasting in the West: July...

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

    ... Cost Assignment - Only a few respondents partly or fully recover forecasting costs from variable generators. Many simply absorb the costs, possibly viewing them as relatively ...

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

  20. ANL Software Improves Wind Power Forecasting | Department of...

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

    ... The licensing arrangement helps to facilitate transfer of the statistical learning algorithms developed in the project to industry use. A leading forecast provider in the United ...

  1. Selected papers on fuel forecasting and analysis

    SciTech Connect (OSTI)

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

    1983-05-01

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

  2. Sensor Characteristics Reference Guide

    SciTech Connect (OSTI)

    Cree, Johnathan V.; Dansu, A.; Fuhr, P.; Lanzisera, Steven M.; McIntyre, T.; Muehleisen, Ralph T.; Starke, M.; Banerjee, Pranab; Kuruganti, T.; Castello, C.

    2013-04-01

    The Buildings Technologies Office (BTO), within the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), is initiating a new program in Sensor and Controls. The vision of this program is: • Buildings operating automatically and continuously at peak energy efficiency over their lifetimes and interoperating effectively with the electric power grid. • Buildings that are self-configuring, self-commissioning, self-learning, self-diagnosing, self-healing, and self-transacting to enable continuous peak performance. • Lower overall building operating costs and higher asset valuation. The overarching goal is to capture 30% energy savings by enhanced management of energy consuming assets and systems through development of cost-effective sensors and controls. One step in achieving this vision is the publication of this Sensor Characteristics Reference Guide. The purpose of the guide is to inform building owners and operators of the current status, capabilities, and limitations of sensor technologies. It is hoped that this guide will aid in the design and procurement process and result in successful implementation of building sensor and control systems. DOE will also use this guide to identify research priorities, develop future specifications for potential market adoption, and provide market clarity through unbiased information

  3. Capillary reference half-cell

    DOE Patents [OSTI]

    Hall, S.H.

    1996-02-13

    The present invention is a reference half-cell electrode wherein intermingling of test fluid with reference fluid does not affect the performance of the reference half-cell over a long time. This intermingling reference half-cell may be used as a single or double junction submersible or surface reference electrode. The intermingling reference half-cell relies on a capillary tube having a first end open to reference fluid and a second end open to test fluid wherein the small diameter of the capillary tube limits free motion of fluid within the capillary to diffusion. The electrode is placed near the first end of the capillary in contact with the reference fluid. The method of operation of the present invention begins with filling the capillary tube with a reference solution. After closing the first end of the capillary, the capillary tube may be fully submerged or partially submerged with the second open end inserted into test fluid. Since the electrode is placed near the first end of the capillary, and since the test fluid may intermingle with the reference fluid through the second open end only by diffusion, this intermingling capillary reference half-cell provides a stable voltage potential for long time periods. 11 figs.

  4. Capillary reference half-cell

    DOE Patents [OSTI]

    Hall, Stephen H.

    1996-01-01

    The present invention is a reference half-cell electrode wherein intermingling of test fluid with reference fluid does not affect the performance of the reference half-cell over a long time. This intermingling reference half-cell may be used as a single or double junction submersible or surface reference electrode. The intermingling reference half-cell relies on a capillary tube having a first end open to reference fluid and a second end open to test fluid wherein the small diameter of the capillary tube limits free motion of fluid within the capillary to diffusion. The electrode is placed near the first end of the capillary in contact with the reference fluid. The method of operation of the present invention begins with filling the capillary tube with a reference solution. After closing the first end of the capillary, the capillary tube may be fully submerged or partially submerged with the second open end inserted into test fluid. Since the electrode is placed near the first end of the capillary, and since the test fluid may intermingle with the reference fluid through the second open end only by diffusion, this intermingling capillary reference half-cell provides a stable voltage potential for long time periods.

  5. Technical analysis in short-term uranium price forecasting

    SciTech Connect (OSTI)

    Schramm, D.S.

    1990-03-01

    As market participants anticipate the end of the current uranium price decline and its subsequent reversal, increased attention will be focused upon forecasting future price movements. Although uranium is economically similar to other mineral commodities, it is questionable whether methodologies used to forecast price movements of such commodities may be successfully applied to uranium.

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

    SciTech Connect (OSTI)

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

    2012-07-01

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

  7. 3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information

    Open Energy Info (EERE)

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

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

    Reports and Publications (EIA)

    2010-01-01

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

  9. Application of Ensemble Sensitivity Analysis to Observation Targeting for Short-term Wind Speed Forecasting

    SciTech Connect (OSTI)

    Zack, J; Natenberg, E; Young, S; Manobianco, J; Kamath, C

    2010-02-21

    The operators of electrical grids, sometimes referred to as Balancing Authorities (BA), typically make critical decisions on how to most reliably and economically balance electrical load and generation in time frames ranging from a few minutes to six hours ahead. At higher levels of wind power generation, there is an increasing need to improve the accuracy of 0- to 6-hour ahead wind power forecasts. Forecasts on this time scale have typically been strongly dependent on short-term trends indicated by the time series of power production and meteorological data from a wind farm. Additional input information is often available from the output of Numerical Weather Prediction (NWP) models and occasionally from off-site meteorological towers in the region surrounding the wind generation facility. A widely proposed approach to improve short-term forecasts is the deployment of off-site meteorological towers at locations upstream from the wind generation facility in order to sense approaching wind perturbations. While conceptually appealing, it turns out that, in practice, it is often very difficult to derive significant benefit in forecast performance from this approach. The difficulty is rooted in the fact that the type, scale, and amplitude of the processes controlling wind variability at a site change from day to day if not from hour to hour. Thus, a location that provides some useful forecast information for one time may not be a useful predictor a few hours later. Indeed, some processes that cause significant changes in wind power production operate predominantly in the vertical direction and thus cannot be monitored by employing a network of sensors at off-site locations. Hence, it is very challenging to determine the type of sensors and deployment locations to get the most benefit for a specific short-term forecast application. Two tools recently developed in the meteorological research community have the potential to help determine the locations and parameters to

  10. Incorporating Forecast Uncertainty in Utility Control Center

    SciTech Connect (OSTI)

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

    2014-07-09

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

  11. Reference Documents | Department of Energy

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

    Reference Documents Reference Documents The following are reference documents utilized by CNS staff to perform its functions. Understanding Process Plant Schedule Slippage and Startup Costs A Review of Cost Estimation in New Technologies - Implications for Energy Process Plants Understanding Cost Growth and Performance Shortfalls in Pioneer Process Plants Pioneer Plants Study User's Manual The Formation of Pioneer Plant Projects in Chemical Processing Firms Industry Information Practices and the

  12. Optical probe with reference fiber

    DOE Patents [OSTI]

    Da Silva, Luiz B.; Chase, Charles L.

    2006-03-14

    A system for characterizing tissue includes the steps of generating an emission signal, generating a reference signal, directing the emission signal to and from the tissue, directing the reference signal in a predetermined manner relative to the emission signal, and using the reference signal to compensate the emission signal. In one embodiment compensation is provided for fluctuations in light delivery to the tip of the probe due to cable motion.

  13. FAQS Reference Guide- Chemical Processing

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide addresses the competency statements in the February 2010 edition of DOE-STD-1176-2010, Chemical Processing Functional Area Qualification Standard.

  14. FAQS Reference Guide- Aviation Manager

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the January 2010 edition of DOE-STD-1164-2003 Chg 1, Aviation Safety Officer Functional Area Qualification Standard.

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

    SciTech Connect (OSTI)

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

    2005-07-01

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

  16. Archived Reference Building Type: Hospital

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  17. Archived Reference Building Type: Hospital

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  18. Archived Reference Building Type: Warehouse

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  19. Archived Reference Building Type: Warehouse

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  20. Archived Reference Building Type: Supermarket

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  1. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

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

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

    SciTech Connect (OSTI)

    Templeton, K.J.

    1996-05-23

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

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

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

    SciTech Connect (OSTI)

    Lantz, E.; Hand, M.

    2010-05-01

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

  5. World oil inventories forecast to grow significantly in 2016...

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

    World oil inventories forecast to grow significantly in 2016 and 2017 Global oil inventories are expected to continue strong growth over the next two years which should keep oil ...

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

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

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

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

    Reports and Publications (EIA)

    2003-01-01

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

  8. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    U.S. DEPARTMENT OF HP IENERGY Office of Science DOESC-ARM-15-024 915-MHz Wind Profiler ... M Jensen et al., March 2016, DOESC-ARM-15-024 915-MHz Wind Profiler for Cloud Forecasting ...

  9. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

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

  10. DOE Publishes New Forecast of Energy Savings from LED Lighting

    Broader source: Energy.gov [DOE]

    The U.S. Department of Energy has just published the latest edition of its biannual report, Energy Savings Forecast of Solid-State Lighting in General Illumination Applications, which models the...

  11. Value of Improved Short-Term Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2015-02-01

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

  12. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

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

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

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

    The Wind Forecast Improvement Project (WFIP) is a U. S. Department of Energy (DOE) sponsored research project whose overarching goals are to improve the accuracy of short-term wind ...

  14. Solar Trackers Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

  16. Recently released EIA report presents international forecasting data

    SciTech Connect (OSTI)

    1995-05-01

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

  17. REFERENCES

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

    CATEGORY Name of Awardee Recovery Act Funding Awarded Participant Cost Share Total Project Value Including Cost Share Headquarters Location for Lead Applicant Brief Project Description Map of Coverage Area CenterPoint Energy $200,000,000 $439,187,435 $639,187,435 Houston, TX Complete the installation of 2.2 million smart meters and further strengthen the reliability and self-healing properties of the grid by installing more than 550 sensors and automated switches that will help protect against

  18. New Climate Research Centers Forecast Changes and Challenges | Department

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

    of Energy Climate Research Centers Forecast Changes and Challenges New Climate Research Centers Forecast Changes and Challenges October 25, 2013 - 12:24pm Addthis This artist's rendering illustrates the full site installation, including a new aerosol observing system (far left) and a precipitation radar (far right, with 20-ft tower). The site is located near the Graciosa Island aiport terminal, hidden by the image inset. | Image courtesy of ARM Climate Research Facility. This artist's

  19. Energy Department Forecasts Geothermal Achievements in 2015 | Department of

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

    Energy Forecasts Geothermal Achievements in 2015 Energy Department Forecasts Geothermal Achievements in 2015 The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector, including Jay Nathwani, Acting Director of the Energy Department's Geothermal Technologies Office. Nathwani shared achievements and challenges in the program's technical portfolio. The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector,

  20. Study forecasts disappearance of conifers due to climate change

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

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

  1. Safeguards and Security Program References

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2005-08-26

    The manual establishes definitions for terms related to the Department of Energy Safeguards and Security (S&S) Program and includes lists of references and acronyms/abbreviations applicable to S&S Program directives. Cancels the Safeguards and Security Glossary of Terms, dated 12-18-95. Current Safeguards and Security Program References can also be found at Safeguards and Security Policy Information Resource (http://pir.pnl.gov/)

  2. NPS Quick Reference Guide | Open Energy Information

    Open Energy Info (EERE)

    Quick Reference Guide Jump to: navigation, search OpenEI Reference LibraryAdd to library Legal Document- OtherOther: NPS Quick Reference GuideLegal Abstract NPS Quick Reference...

  3. A 24-h forecast of solar irradiance using artificial neural network: Application for performance prediction of a grid-connected PV plant at Trieste, Italy

    SciTech Connect (OSTI)

    Mellit, Adel; Pavan, Alessandro Massi

    2010-05-15

    Forecasting of solar irradiance is in general significant for planning the operations of power plants which convert renewable energies into electricity. In particular, the possibility to predict the solar irradiance (up to 24 h or even more) can became - with reference to the Grid Connected Photovoltaic Plants (GCPV) - fundamental in making power dispatching plans and - with reference to stand alone and hybrid systems - also a useful reference for improving the control algorithms of charge controllers. In this paper, a practical method for solar irradiance forecast using artificial neural network (ANN) is presented. The proposed Multilayer Perceptron MLP-model makes it possible to forecast the solar irradiance on a base of 24 h using the present values of the mean daily solar irradiance and air temperature. An experimental database of solar irradiance and air temperature data (from July 1st 2008 to May 23rd 2009 and from November 23rd 2009 to January 24th 2010) has been used. The database has been collected in Trieste (latitude 45 40'N, longitude 13 46'E), Italy. In order to check the generalization capability of the MLP-forecaster, a K-fold cross-validation was carried out. The results indicate that the proposed model performs well, while the correlation coefficient is in the range 98-99% for sunny days and 94-96% for cloudy days. As an application, the comparison between the forecasted one and the energy produced by the GCPV plant installed on the rooftop of the municipality of Trieste shows the goodness of the proposed model. (author)

  4. Climatic Forecasting of Net Infiltration at Yucca Montain Using Analogue Meteororological Data

    SciTech Connect (OSTI)

    B. Faybishenko

    2006-09-11

    At Yucca Mountain, Nevada, future changes in climatic conditions will most likely alter net infiltration, or the drainage below the bottom of the evapotranspiration zone within the soil profile or flow across the interface between soil and the densely welded part of the Tiva Canyon Tuff. The objectives of this paper are to: (a) develop a semi-empirical model and forecast average net infiltration rates, using the limited meteorological data from analogue meteorological stations, for interglacial (present day), and future monsoon, glacial transition, and glacial climates over the Yucca Mountain region, and (b) corroborate the computed net-infiltration rates by comparing them with the empirically and numerically determined groundwater recharge and percolation rates through the unsaturated zone from published data. In this paper, the author presents an approach for calculations of net infiltration, aridity, and precipitation-effectiveness indices, using a modified Budyko's water-balance model, with reference-surface potential evapotranspiration determined from the radiation-based Penman (1948) formula. Results of calculations show that net infiltration rates are expected to generally increase from the present-day climate to monsoon climate, to glacial transition climate, and then to the glacial climate. The forecasting results indicate the overlap between the ranges of net infiltration for different climates. For example, the mean glacial net-infiltration rate corresponds to the upper-bound glacial transition net infiltration, and the lower-bound glacial net infiltration corresponds to the glacial transition mean net infiltration. Forecasting of net infiltration for different climate states is subject to numerous uncertainties-associated with selecting climate analogue sites, using relatively short analogue meteorological records, neglecting the effects of vegetation and surface runoff and runon on a local scale, as well as possible anthropogenic climate changes.

  5. CASE Design/Remodeling | Open Energy Information

    Open Energy Info (EERE)

    DesignRemodeling Jump to: navigation, search Name: CASE DesignRemodeling Place: Bethesda, MD Website: www.casedesignremodeling.com References: CASE DesignRemodeling1...

  6. Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs

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

    Pelletier, Jon D.; Murray, A. Brad; Pierce, Jennifer L.; Bierman, Paul R.; Breshears, David D.; Crosby, Benjamin T.; Ellis, Michael; Foufoula-Georgiou, Efi; Heimsath, Arjun M.; Houser, Chris; et al

    2015-07-14

    In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we havemore » the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.« less

  7. Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs

    SciTech Connect (OSTI)

    Pelletier, Jon D.; Murray, A. Brad; Pierce, Jennifer L.; Bierman, Paul R.; Breshears, David D.; Crosby, Benjamin T.; Ellis, Michael; Foufoula-Georgiou, Efi; Heimsath, Arjun M.; Houser, Chris; Lancaster, Nick; Marani, Marco; Merritts, Dorothy J.; Moore, Laura J.; Pederson, Joel L.; Poulos, Michael J.; Rittenour, Tammy M.; Rowland, Joel C.; Ruggiero, Peter; Ward, Dylan J.; Wickert, Andrew D.; Yager, Elowyn M.

    2015-07-14

    In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we have the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.

  8. FY 1996 solid waste integrated life-cycle forecast container summary volume 1 and 2

    SciTech Connect (OSTI)

    Valero, O.J.

    1996-04-23

    For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the containers expected to be used for these waste shipments from 1996 through the remaining life cycle of the Hanford Site. In previous years, forecast data have been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to the more detailed report on waste volumes: WHC-EP0900, FY 1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary. Both of these documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on the types of containers that will be used for packaging low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major waste generators for each waste category and container type are also discussed. Containers used for low-level waste (LLW) are described in Appendix A, since LLW requires minimal treatment and storage prior to onsite disposal in the LLW burial grounds. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste are expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters.

  9. A comparison of water vapor quantities from model short-range forecasts and ARM observations

    SciTech Connect (OSTI)

    Hnilo, J J

    2006-03-17

    Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the 'Merged-sounding' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.

  10. A comparison of model short-range forecasts and the ARM Microbase data

    SciTech Connect (OSTI)

    Hnilo, J J

    2006-09-22

    For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the 'Microbase' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both TWP and NSA. The Microbase data have been averaged to 35 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3hourly data for direct comparison to our model output.

  11. A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations

    SciTech Connect (OSTI)

    Hnilo, J.

    2006-03-17

    Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the “Mergedsounding” value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01

    This report surveyed Western Interconnection Balancing Authorities regarding their implementation of variable generation forecasting, the lessons learned to date, and recommendations they would offer to other Balancing Authorities who are considering variable generation forecasting. Our survey found that variable generation forecasting is at an early implementation stage in the West. Eight of the eleven Balancing Authorities interviewed began forecasting in 2008 or later. It also appears that less than one-half of the Balancing Authorities in the West are currently utilizing variable generation forecasting, suggesting that more Balancing Authorities in the West will engage in variable generation forecasting should more variable generation capacity be added.

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

    SciTech Connect (OSTI)

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

    2011-09-13

    The overall goal of this multi-phased research project known as WindSENSE is to develop an observation system deployment strategy that would improve wind power generation forecasts. The objective of the deployment strategy is to produce the maximum benefit for 1- to 6-hour ahead forecasts of wind speed at hub-height ({approx}80 m). In this phase of the project the focus is on the Mid-Columbia Basin region which encompasses the Bonneville Power Administration (BPA) wind generation area shown in Figure 1 that includes Klondike, Stateline, and Hopkins Ridge wind plants. The Ensemble Sensitivity Analysis (ESA) approach uses data generated by a set (ensemble) of perturbed numerical weather prediction (NWP) simulations for a sample time period to statistically diagnose the sensitivity of a specified forecast variable (metric) for a target location to parameters at other locations and prior times referred to as the initial condition (IC) or state variables. The ESA approach was tested on the large-scale atmospheric prediction problem by Ancell and Hakim 2007 and Torn and Hakim 2008. ESA was adapted and applied at the mesoscale by Zack et al. (2010a, b, and c) to the Tehachapi Pass, CA (warm and cools seasons) and Mid-Colombia Basin (warm season only) wind generation regions. In order to apply the ESA approach at the resolution needed at the mesoscale, Zack et al. (2010a, b, and c) developed the Multiple Observation Optimization Algorithm (MOOA). MOOA uses a multivariate regression on a few select IC parameters at one location to determine the incremental improvement of measuring multiple variables (representative of the IC parameters) at various locations. MOOA also determines how much information from each IC parameter contributes to the change in the metric variable at the target location. The Zack et al. studies (2010a, b, and c), demonstrated that forecast sensitivity can be characterized by well-defined, localized patterns for a number of IC variables such as 80-m

  14. 1980 annual report to Congress: Volume three, Forecasts: Summary

    SciTech Connect (OSTI)

    Not Available

    1981-05-27

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

  15. Draft SPD Supplemental EIS Master Reference List | National Nuclear

    National Nuclear Security Administration (NNSA)

    Security Administration | (NNSA) Draft SPD Supplemental EIS Master Reference List References for Chapters 1 - 5 References for Appendix A References for Appendix B References for Appendix C References for Appendix D References for Appendix E References for Appendix F References for Appendix G References for Appendix H References for Appendix I References for Appendix J References for Summary Learn More SPD SEIS References for Appendix C SPD SEIS References for Appendix D SPD SEIS References

  16. Annual Energy Outlook 2013 Early Release Reference Case

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

    price per barrel (real 2010 dollars) Sources: U.S. Energy Information Administration, Thomson Reuters Prices shown are quarterly averages: dashed lines are EIA projections...

  17. Annual Energy Outlook 2013 Early Release Reference Case

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

    (CO, WY) Haynesville Utica (OH, PA & WV) Marcellus (PA,WV,OH & NY) Woodford (OK) Granite Wash (OK & TX) Austin Chalk (LA & TX) Monterey (CA) U.S. tight oil production...

  18. Annual Energy Outlook 2013 Early Release Reference Case

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

    : Focus on the Electricity Supply Mix for Natural Gas Power Generation US May 18, 2015 | Philadelphia, Pennsylvania by Howard Gruenspecht, Deputy Administrator U.S. Energy...

  19. Annual Energy Outlook 2013 Early Release Reference Case

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

    resource and technology scenario (a key driver of domestic gas prices); global energy market prices (which along with domestic prices defines the "gap" that determines the...

  20. Annual Energy Outlook 2013 Early Release Reference Case

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

    Flex-Fuel Vehicle Modeling in the Annual Energy Outlook John Maples Office of Energy Consumption and Energy Analysis March 20, 2013 | Washington, DC Light duty vehicle technology ...

  1. Annual Energy Outlook 2014 Early Release Reference Case

    Gasoline and Diesel Fuel Update (EIA)

    Annual Coal Distribution Report Release Date: April 8, 2016 | Next Release Date: December 2016 | full report The Annual Coal Distribution Report (ACDR) provides detailed information on domestic coal distribution by origin state, destination state, consumer category, and method of transportation. Also provided is a summary of foreign coal distribution by coal-producing state. All data for 2014 are final and this report supersedes the 2014 quarterly coal distribution reports. Highlights for 2014:

  2. Annual Energy Outlook 2013 Early Release Reference Case

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

    Gov't deficits, high reliance on oil revenue, and asset coverage of gov't spending are indicators of geopolitical stress exposure more risk less risk more risk less risk 7...

  3. Annual Energy Outlook 2013 Early Release Reference Case

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

    energy markets For Cheung Kong Graduate School of Business July 29, 2015 | Beijing, China by Adam Sieminski, Administrator U.S. Energy Information Administration International...

  4. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

  5. Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts |

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

    Department of Energy Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts May 11, 2016 - 6:48pm Addthis Balancing the power grid is an art-or at least a scientific study in chaos-and the Energy Department is hoping wind energy can take a greater role in the act. Yet, the intermittency of wind-sometimes it's blowing, sometimes it's not-makes adding it smoothly to the nation's electrical grid a challenge.

  6. Forecast of contracting and subcontracting opportunities. Fiscal year 1996

    SciTech Connect (OSTI)

    1996-02-01

    This forecast of prime and subcontracting opportunities with the U.S. Department of Energy and its MAO contractors and environmental restoration and waste management contractors, is the Department`s best estimate of small, small disadvantaged and women-owned small business procurement opportunities for fiscal year 1996. The information contained in the forecast is published in accordance with Public Law 100-656. It is not an invitation for bids, a request for proposals, or a commitment by DOE to purchase products or services. Each procurement opportunity is based on the best information available at the time of publication and may be revised or cancelled.

  7. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    2008-01-15

    Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

  8. Category:Buildings References | Open Energy Information

    Open Energy Info (EERE)

    Buildings References Jump to: navigation, search Add a new Reference Pages in category "Buildings References" The following 16 pages are in this category, out of 16 total. B Bureau...

  9. Category:Water References | Open Energy Information

    Open Energy Info (EERE)

    Water References Jump to: navigation, search Add a new Reference Pages in category "Water References" The following 22 pages are in this category, out of 22 total. A Alaska AS...

  10. Category:Hydrogen References | Open Energy Information

    Open Energy Info (EERE)

    Hydrogen References Jump to: navigation, search Add a new Reference Pages in category "Hydrogen References" The following 6 pages are in this category, out of 6 total. F FERC Order...

  11. Appendix E References | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    E References Crosswalk of Appendix E References to Main DSEIS Reference File name (Main DSEIS) or file name in Appendix E folder DOE (U.S. Department of Energy) 1999. Final ...

  12. HANFORD WASTE MINERALOGY REFERENCE REPORT

    SciTech Connect (OSTI)

    DISSELKAMP RS

    2010-06-29

    This report lists the observed mineral phases present in the Hanford tanks. This task was accomplished by performing a review of numerous reports that used experimental techniques including, but not limited to: x-ray diffraction, polarized light microscopy, scanning electron microscopy, transmission electron microscopy, energy dispersive spectroscopy, electron energy loss spectroscopy, and particle size distribution analyses. This report contains tables that can be used as a quick reference to identify the crystal phases observed in Hanford waste.

  13. HANFORD WASTE MINEROLOGY REFERENCE REPORT

    SciTech Connect (OSTI)

    DISSELKAMP RS

    2010-06-18

    This report lists the observed mineral phase phases present in the Hanford tanks. This task was accomplished by performing a review of numerous reports using experimental techniques including, but not limited to: x-ray diffraction, polarized light microscopy, scanning electron microscopy, transmission electron microscopy, energy dispersive spectroscopy, electron energy loss spectroscopy, and particle size distribution analyses. This report contains tables that can be used as a quick reference to identify the crystal phases present observed in Hanford waste.

  14. Microgrid cyber security reference architecture.

    SciTech Connect (OSTI)

    Veitch, Cynthia K.; Henry, Jordan M.; Richardson, Bryan T.; Hart, Derek H.

    2013-07-01

    This document describes a microgrid cyber security reference architecture. First, we present a high-level concept of operations for a microgrid, including operational modes, necessary power actors, and the communication protocols typically employed. We then describe our motivation for designing a secure microgrid; in particular, we provide general network and industrial control system (ICS)-speci c vulnerabilities, a threat model, information assurance compliance concerns, and design criteria for a microgrid control system network. Our design approach addresses these concerns by segmenting the microgrid control system network into enclaves, grouping enclaves into functional domains, and describing actor communication using data exchange attributes. We describe cyber actors that can help mitigate potential vulnerabilities, in addition to performance bene ts and vulnerability mitigation that may be realized using this reference architecture. To illustrate our design approach, we present a notional a microgrid control system network implementation, including types of communica- tion occurring on that network, example data exchange attributes for actors in the network, an example of how the network can be segmented to create enclaves and functional domains, and how cyber actors can be used to enforce network segmentation and provide the neces- sary level of security. Finally, we describe areas of focus for the further development of the reference architecture.

  15. Reference Inflow Characterization for River Resource Reference Model (RM2)

    SciTech Connect (OSTI)

    Neary, Vincent S

    2011-12-01

    Sandia National Laboratory (SNL) is leading an effort to develop reference models for marine and hydrokinetic technologies and wave and current energy resources. This effort will allow the refinement of technology design tools, accurate estimates of a baseline levelized cost of energy (LCoE), and the identification of the main cost drivers that need to be addressed to achieve a competitive LCoE. As part of this effort, Oak Ridge National Laboratory was charged with examining and reporting reference river inflow characteristics for reference model 2 (RM2). Published turbulent flow data from large rivers, a water supply canal and laboratory flumes, are reviewed to determine the range of velocities, turbulence intensities and turbulent stresses acting on hydrokinetic technologies, and also to evaluate the validity of classical models that describe the depth variation of the time-mean velocity and turbulent normal Reynolds stresses. The classical models are found to generally perform well in describing river inflow characteristics. A potential challenge in river inflow characterization, however, is the high variability of depth and flow over the design life of a hydrokinetic device. This variation can have significant effects on the inflow mean velocity and turbulence intensity experienced by stationary and bottom mounted hydrokinetic energy conversion devices, which requires further investigation, but are expected to have minimal effects on surface mounted devices like the vertical axis turbine device designed for RM2. A simple methodology for obtaining an approximate inflow characterization for surface deployed devices is developed using the relation umax=(7/6)V where V is the bulk velocity and umax is assumed to be the near-surface velocity. The application of this expression is recommended for deriving the local inflow velocity acting on the energy extraction planes of the RM2 vertical axis rotors, where V=Q/A can be calculated given a USGS gage flow time

  16. Template:ReferenceMaterial | Open Energy Information

    Open Energy Info (EERE)

    - The type of reference material (allowable values include: Journal article, Book, Report, etc.) Documentnumber - The reference material document number or DOI...

  17. Existing Commercial Reference Buildings Constructed Before 1980...

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

    Existing Commercial Reference Buildings Constructed Before 1980 The files on this page ... These U.S. Department of Energy (DOE) reference buildings are complete descriptions for ...

  18. A New Solar Irradiance Reference Spectrum

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

    A New Solar Irradiance Reference Spectrum Pilewskie, Peter University of Colorado ... We describe the development of a new solar reference spectrum for radiation and climate ...

  19. Manufacturing Energy and Carbon Footprint References | Department...

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

    Manufacturing Energy and Carbon Footprint References footprintreferences.pdf (309.04 KB) More Documents & Publications 2010 Manufacturing Energy and Carbon Footprints: References ...

  20. Final Report - Integration of Behind-the-Meter PV Fleet Forecasts...

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

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

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

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01

    This study analyzed the potential benefits of improving the accuracy (reducing the error) of day-ahead wind forecasts on power system operations, assuming that wind forecasts were used for day ahead security constrained unit commitment.

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

    Broader source: Energy.gov [DOE]

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01

    Report surveys grid wind power forecasts for all wind generators, which are administered by utilities or regional transmission organizations (RTOs), typically with the assistance of one or more wind power forecasting companies.

  4. EIA revises up forecast for U.S. 2013 crude oil production by...

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

    EIA revises up forecast for U.S. 2013 crude oil production by 70,000 barrels per day The forecast for U.S. crude oil production keeps going higher. The U.S. Energy Information ...

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

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

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01

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

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

    SciTech Connect (OSTI)

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

    2011-03-28

    Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

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

    Energy Science and Technology Software Center (OSTI)

    2012-05-01

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

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

    SciTech Connect (OSTI)

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

    2009-03-01

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

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

    SciTech Connect (OSTI)

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

    2013-06-15

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

  11. Incorporating Uncertainty of Wind Power Generation Forecast into Power System Operation, Dispatch, and Unit Commitment Procedures

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian; Huang, Zhenyu; Subbarao, Krishnappa

    2011-06-23

    An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures). A new method called the 'flying-brick' technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through EMS integration illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems in control rooms.

  12. Incorporating Wind Generation Forecast Uncertainty into Power System Operation, Dispatch, and Unit Commitment Procedures

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Subbarao, Krishnappa

    2010-10-19

    In this paper, an approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the "flying-brick" technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through integration with an EMS system illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems from other vendors.

  13. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

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

    2011-11-29

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

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  15. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.; Gomez-Lazaro, E.; Lovholm, A. L.; Berge, E.; Miettinen, J.; Holttinen, H.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Dobschinski, J.

    2013-10-01

    One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

  16. Navy mobility fuels forecasting system report: World petroleum trade forecasts for the year 2000

    SciTech Connect (OSTI)

    Das, S.

    1991-12-01

    The Middle East will continue to play the dominant role of a petroleum supplier in the world oil market in the year 2000, according to business-as-usual forecasts published by the US Department of Energy. However, interesting trade patterns will emerge as a result of the democratization in the Soviet Union and Eastern Europe. US petroleum imports will increase from 46% in 1989 to 49% in 2000. A significantly higher level of US petroleum imports (principally products) will be coming from Japan, the Soviet Union, and Eastern Europe. Several regions, the Far East, Japan, Latin American, and Africa will import more petroleum. Much uncertainty remains about of the level future Soviet crude oil production. USSR net petroleum exports will decrease; however, the United States and Canada will receive some of their imports from the Soviet Union due to changes in the world trade patterns. The Soviet Union can avoid becoming a net petroleum importer as long as it (1) maintains enough crude oil production to meet its own consumption and (2) maintains its existing refining capacities. Eastern Europe will import approximately 50% of its crude oil from the Middle East.

  17. PVWatts Version 1 Technical Reference

    SciTech Connect (OSTI)

    Dobos, A. P.

    2013-10-01

    The NREL PVWatts(TM) calculator is a web application developed by the National Renewable Energy Laboratory (NREL) that estimates the electricity production of a grid-connected photovoltaic system based on a few simple inputs. PVWatts combines a number of sub-models to predict overall system performance, and makes several hidden assumptions about performance parameters. This technical reference details the individual sub-models, documents assumptions and hidden parameters, and explains the sequence of calculations that yield the final system performance estimation.

  18. Reference electrode for electrolytic cell

    DOE Patents [OSTI]

    Kessie, R.W.

    1988-07-28

    A reference electrode device is provided for a high temperature electrolytic cell used to electrolytically recover uranium from spent reactor fuel dissolved in an anode pool, the device having a glass tube to enclose the electrode and electrolyte and serve as a conductive membrane with the cell electrolyte, and an outer metal tube about the glass tube to serve as a shield and basket for any glass sections broken by handling of the tube to prevent their contact with the anode pool, the metal tube having perforations to provide access between the bulk of the cell electrolyte and glass membrane. 4 figs.

  19. Emergency Responder Radioactive Material Quick Reference Sheet

    Broader source: Energy.gov [DOE]

    Transportation Emergency Preparedness Program (TEPP) Emergency Responder Radioactive Material Quick Reference Sheet

  20. Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect (OSTI)

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

    2010-01-01

    unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the “flying brick” technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.

  1. High stability wavefront reference source

    DOE Patents [OSTI]

    Feldman, M.; Mockler, D.J.

    1994-05-03

    A thermally and mechanically stable wavefront reference source which produces a collimated output laser beam is disclosed. The output beam comprises substantially planar reference wavefronts which are useful for aligning and testing optical interferometers. The invention receives coherent radiation from an input optical fiber, directs a diverging input beam of the coherent radiation to a beam folding mirror (to produce a reflected diverging beam), and collimates the reflected diverging beam using a collimating lens. In a class of preferred embodiments, the invention includes a thermally and mechanically stable frame comprising rod members connected between a front end plate and a back end plate. The beam folding mirror is mounted on the back end plate, and the collimating lens mounted to the rods between the end plates. The end plates and rods are preferably made of thermally stable metal alloy. Preferably, the input optical fiber is a single mode fiber coupled to an input end of a second single mode optical fiber that is wound around a mandrel fixedly attached to the frame of the apparatus. The output end of the second fiber is cleaved so as to be optically flat, so that the input beam emerging therefrom is a nearly perfect diverging spherical wave. 7 figures.

  2. High stability wavefront reference source

    DOE Patents [OSTI]

    Feldman, Mark; Mockler, Daniel J.

    1994-01-01

    A thermally and mechanically stable wavefront reference source which produces a collimated output laser beam. The output beam comprises substantially planar reference wavefronts which are useful for aligning and testing optical interferometers. The invention receives coherent radiation from an input optical fiber, directs a diverging input beam of the coherent radiation to a beam folding mirror (to produce a reflected diverging beam), and collimates the reflected diverging beam using a collimating lens. In a class of preferred embodiments, the invention includes a thermally and mechanically stable frame comprising rod members connected between a front end plate and a back end plate. The beam folding mirror is mounted on the back end plate, and the collimating lens mounted to the rods between the end plates. The end plates and rods are preferably made of thermally stable metal alloy. Preferably, the input optical fiber is a single mode fiber coupled to an input end of a second single mode optical fiber that is wound around a mandrel fixedly attached to the frame of the apparatus. The output end of the second fiber is cleaved so as to be optically flat, so that the input beam emerging therefrom is a nearly perfect diverging spherical wave.

  3. Forecast of transportation energy demand through the year 2010

    SciTech Connect (OSTI)

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

    1991-04-01

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

  4. Microsoft Word - Documentation - Price Forecast Uncertainty.doc

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

    October 2009 1 October 2009 Short-Term Energy Outlook Supplement: Energy Price Volatility and Forecast Uncertainty 1 Summary It is often noted that energy prices are quite volatile, reflecting market participants' adjustments to new information from physical energy markets and/or markets in energy- related financial derivatives. Price volatility is an indication of the level of uncertainty, or risk, in the market. This paper describes how markets price risk and how the market- clearing process

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

    SciTech Connect (OSTI)

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

    2000-01-07

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

  6. Assessment of the possibility of forecasting future natural gas curtailments

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

    This study provides a preliminary assessment of the potential for determining probabilities of future natural-gas-supply interruptions by combining long-range weather forecasts and natural-gas supply/demand projections. An illustrative example which measures the probability of occurrence of heating-season natural-gas curtailments for industrial users in the southeastern US is analyzed. Based on the information on existing long-range weather forecasting techniques and natural gas supply/demand projections enumerated above, especially the high uncertainties involved in weather forecasting and the unavailability of adequate, reliable natural-gas projections that take account of seasonal weather variations and uncertainties in the nation's energy-economic system, it must be concluded that there is little possibility, at the present time, of combining the two to yield useful, believable probabilities of heating-season gas curtailments in a form useful for corporate and government decision makers and planners. Possible remedial actions are suggested that might render such data more useful for the desired purpose in the future. The task may simply require the adequate incorporation of uncertainty and seasonal weather trends into modeling systems and the courage to report projected data, so that realistic natural gas supply/demand scenarios and the probabilities of their occurrence will be available to decision makers during a time when such information is greatly needed.

  7. Towards a Science of Tumor Forecast for Clinical Oncology

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

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoplymore » of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.« less

  8. Toward a science of tumor forecasting for clinical oncology

    SciTech Connect (OSTI)

    Yankeelov, Thomas E.; Quaranta, Vito; Evans, Katherine J.; Rericha, Erin C.

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.

  9. Toward a science of tumor forecasting for clinical oncology

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

    Yankeelov, Thomas E.; Quaranta, Vito; Evans, Katherine J.; Rericha, Erin C.

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapiesmore » is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.« less

  10. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.

  11. Research Notes and Information References

    Energy Science and Technology Software Center (OSTI)

    1994-12-01

    The RNS (Research Notes System) is a set of programs and databases designed to aid the research worker in gathering, maintaining, and using notes taken from the literature. The sources for the notes can be books, journal articles, reports, private conversations, conference papers, audiovisuals, etc. The system ties the databases together in a relational structure, thus eliminating data redundancy while providing full access to all the information. The programs provide the means for access andmore » data entry in a way that reduces the key-entry burden for the user. Each note has several data fields. Included are the text of the note, the subject classification (for retrieval), and the reference identification data. These data are divided into four databases: Document data - title, author, publisher, etc., fields to identify the article within the document; Note data - text and page of the note; Sublect data - subject categories to ensure uniform spelling for searches. Additionally, there are subsidiary files used by the system, including database index and temporary work files. The system provides multiple access routes to the notes, both structurally (access method) and topically (through cross-indexing). Output may be directed to a printer or saved as a file for input to word processing software.« less

  12. Analysis of Restricted Natural Gas Supply Cases

    Reports and Publications (EIA)

    2004-01-01

    The four cases examined in this study have progressively greater impacts on overall natural gas consumption, prices, and supply. Compared to the Annual Energy Outlook 2004 reference case, the no Alaska pipeline case has the least impact; the low liquefied natural gas case has more impact; the low unconventional gas recovery case has even more impact; and the combined case has the most impact.

  13. Form:Reference | Open Energy Information

    Open Energy Info (EERE)

    The reference title should match the book title. e.g.- Where the Wild Things Are Book Review Used when citing a review of a book. The reference title should include "Review of the...

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

    Broader source: Energy.gov [DOE]

    The Wind Forecast Improvement Project (WFIP) is a U. S. Department of Energy (DOE) sponsored research project whose overarching goals are to improve the accuracy of short-term wind energy forecasts, and to demonstrate the economic value of these improvements.

  15. Functional Area Qualification Standard Reference Guides

    Broader source: Energy.gov [DOE]

    The reference guides have been developed to address the competency statements in DOE Functional Area Qualification Standard.

  16. Commercial Reference Buildings | Department of Energy

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

    Reference Buildings Commercial Reference Buildings The U.S. Department of Energy (DOE), in conjunction with three of its national laboratories, developed commercial reference buildings, formerly known as commercial building benchmark models. These reference buildings play a critical role in the program's energy modeling software research by providing complete descriptions for whole building energy analysis using EnergyPlus simulation software. There are 16 building types that represent

  17. OSTIblog Articles in the reference linking Topic | OSTI, US Dept...

    Office of Scientific and Technical Information (OSTI)

    reference linking Topic OSTI and Reference Linking by Daphne Evans 13 May, 2008 in Technology OSTI actively supports the practice of Reference Linking. Also referred to as citation ...

  18. World Business Council for Sustainable Development-Case Studies...

    Open Energy Info (EERE)

    Efficiency, Renewable Energy, Buildings, Industry Topics Implementation Resource Type Lessons learnedbest practices Website http:www.wbcsd.orgtemplates References Case...

  19. Geothermal Exploration Techniques a Case Study. Final Report...

    Open Energy Info (EERE)

    Techniques a Case Study. Final Report Jump to: navigation, search OpenEI Reference LibraryAdd to library Report: Geothermal Exploration Techniques a Case Study. Final Report...

  20. Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting

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

    Technology | Department of Energy Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting Technology Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting Technology IBM logo.png As part of this project, new solar forecasting technology will be developed that leverages big data processing, deep machine learning, and cloud modeling integrated in a universal platform with an open architecture. Similar to the Watson computer system, this proposed technology

  1. Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System

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

    Operations | Department of Energy Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Clean Power Research logo.jpg This project will address the need for a more accurate approach to forecasting net utility load by taking into consideration the contribution of customer-sited PV energy generation. Tasks within the project are designed to integrate novel PV power

  2. Central Wind Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities: Revised Edition

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01

    The report and accompanying table addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America. The first part of the table focuses on electric utilities and regional transmission organizations that have central wind power forecasting in place; the second part focuses on electric utilities and regional transmission organizations that plan to adopt central wind power forecasting in 2010. This is an update of the December 2009 report, NREL/SR-550-46763.

  3. ARM - PI Product - CCPP-ARM Parameterization Testbed Model Forecast Data

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

    ProductsCCPP-ARM Parameterization Testbed Model Forecast Data ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : CCPP-ARM Parameterization Testbed Model Forecast Data Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are

  4. The Value of Improved Wind Power Forecasting in the Western Interconne...

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

    of this research will facilitate a better functional understanding of wind forecasting accuracy and power system operations at various spatial and temporal scales.* Of particular ...

  5. Report of the external expert peer review panel: DOE benefits forecasts

    SciTech Connect (OSTI)

    None, None

    2006-12-20

    A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts.

  6. Integration of Behind-the-Meter PV Fleet Forecasts into Utility...

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

    Forecasting behind-the-meter distributed PV generation power production within a region ... This project is expected to reduce the costs of integrating higher penetrations of PV into ...

  7. Energy Department Announces $2.5 Million to Improve Wind Forecasting...

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

    turbines operate closer to maximum capacity, leading to lower energy costs for consumers. ... for the Weather Research and Forecasting model, a widely used weather prediction system. ...

  8. Value of Improved Wind Power Forecasting in the Western Interconnection (Poster)

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01

    Wind power forecasting is a necessary and important technology for incorporating wind power into the unit commitment and dispatch process. It is expected to become increasingly important with higher renewable energy penetration rates and progress toward the smart grid. There is consensus that wind power forecasting can help utility operations with increasing wind power penetration; however, there is far from a consensus about the economic value of improved forecasts. This work explores the value of improved wind power forecasting in the Western Interconnection of the United States.

  9. EERE Success Story-Solar Forecasting Gets a Boost from Watson...

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

    electric system operators, and solar project owners better predict when and how much ... production varies, an accurate solar forecast is needed in order to maintain an ...

  10. A Comparison of Model Short-Range Forecasts and the ARM Microbase Data Fourth Quarter ARM Science Metric

    SciTech Connect (OSTI)

    Hnilo, J.

    2006-09-19

    For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the “Microbase” value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both TWP and NSA. The Microbase data have been averaged to 35 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3hourly data for direct comparison to our model output.

  11. NREL: Measurements and Characterization - Reference Cell Calibration

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

    Reference Cell Calibration The National Renewable Energy Laboratory (NREL) calibrates primary reference cells for in-house use and for use by other national laboratories. We also do so to provide our clients and partners with a path for traceability to standards. Our laboratory is one of only four facilities in the world certified to calibrate reference cells in accordance with the world photovoltaic scale, and these measurements are accredited to International Organization for Standardization

  12. References | National Nuclear Security Administration | (NNSA)

    National Nuclear Security Administration (NNSA)

    References U.S. Department of Energy / U.S. Nuclear Regulatory Commission Nuclear Materials Management & Safeguards System References Additional information related to the NMMSS may be located in the publications listed below. By referencing these documents, a more extensive understanding of the system may be gained. Other references extracted from DOE M 470.4-6 and used within the industry have also been included. "Agreement between the United States of America and the IAEA for the

  13. Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1994--FY 2001. Environmental Restoration Program, September 1993 Revision

    SciTech Connect (OSTI)

    Not Available

    1993-12-01

    This Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project. FY 1994--FY 2001 is the third in a series of documents that report current estimates of the waste volumes expected to be generated as a result of Environmental Restoration activities at Department of Energy, Oak Ridge Operations Office (DOE-ORO), sites. Considered in the scope of this document are volumes of waste expected to be generated as a result of remedial action and decontamination and decommissioning activities taking place at these sites. Sites contributing to the total estimates make up the DOE-ORO Environmental Restoration OR-1 Project: the Oak Ridge K-25 Site, the Oak Ridge National Laboratory, the Y-12 Plant, the Paducah Gaseous Diffusion Plant, the Portsmouth Gaseous Diffusion Plant, and the off-site contaminated areas adjacent to the Oak Ridge facilities (collectively referred to as the Oak Ridge Reservation Off-Site area). Estimates are available for the entire fife of all waste generating activities. This document summarizes waste estimates forecasted for the 8-year period of FY 1994-FY 2001. Updates with varying degrees of change are expected throughout the refinement of restoration strategies currently in progress at each of the sites. Waste forecast data are relatively fluid, and this document represents remediation plans only as reported through September 1993.

  14. ORISE: Radiological Terms Quick Reference Guide

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

    Type text Type text Type text Radiation Emergency Assistance CenterTraining Site ... 2015 Quick Reference Information - Radiation Activity: Radioactive materials aren't ...

  15. FAQS Reference Guide – Mechanical Systems

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide addresses the competency statements in the June 2008 edition of DOE-STD-1161-2008, Mechanical Systems Functional Area Qualification Standard.

  16. AVIATION MANAGER QUALIFICATION STANDARD REFERENCE GUIDE

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

    Manager Qualification Standard Reference Guide MARCH 2010 i This page is intentionally blank. Table of Contents ii LIST OF FIGURES ..................................................................................................................... iii LIST OF TABLES ....................................................................................................................... iii ACRONYMS

  17. AVIATION SAFETY OFFICER QUALIFICATION STANDARD REFERENCE GUIDE

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

    Safety Officer Qualification Standard Reference Guide MARCH 2010 i This page is intentionally blank. Table of Contents ii LIST OF FIGURES ..................................................................................................................... iii LIST OF TABLES ....................................................................................................................... iii ACRONYMS

  18. FAQS Reference Guide – Weapon Quality Assurance

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the August 2008 edition of DOE-STD-1025-2008, Weapon Quality Assurance Functional Area Qualification Standard.

  19. FAQS Reference Guide – Technical Training

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the February 2004 edition of DOE-STD-1179-2004, Technical Training Functional Area Qualification Standard.

  20. FAQS Reference Guide – Environmental Compliance

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide addresses the competency statements in the June 2011 edition of DOE-STD-1156-2011, Environmental Compliance Functional Area Qualification Standard.

  1. Template:Reference | Open Energy Information

    Open Energy Info (EERE)

    for references that may not require listed authors such as technical reports or web referenced material (Report & Web Site) GraphicAuthor - List of authors or map...

  2. Commercial Reference Buildings | Open Energy Information

    Open Energy Info (EERE)

    Reference Building Types1 , which represent approximately 70% of the commercial buildings in the U.S. 2. Whole building energy analysis data (developed using EnergyPlus...

  3. Reference Form | SREL REU in Radioecology

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

    to highlight specific examples that illustrate the candidate's strengths or suitability to the program. Therefore, we also require references to also upload a letter of...

  4. FAQS Reference Guide – Construction Management

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide addresses the competency statements in the March 2004 edition of DOE-STD-1180-2004, Construction Management Functional Area Qualification Standard.

  5. FAQS Reference Guide – Emergency Management

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide addresses the competency statements in the January 2004 edition of DOE-STD-1177-2004, Emergency Management Functional Area Qualification Standard.

  6. FAQS Reference Guide – Industrial Hygiene

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the November 2007 edition of DOE-STD-1138-2007, Industrial Hygiene Functional Area Qualification Standard.

  7. FAQS Reference Guide – Fire Protection Engineering

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide addresses the competency statements in the December 2007 edition of DOE-STD-1137-2007, Fire Protection Engineering Functional Area Qualification Standard.

  8. Reference Designs for Hydrogen Fueling Stations Webinar

    Office of Energy Efficiency and Renewable Energy (EERE)

    Access the recording and download the presentation slides from the Fuel Cell Technologies Office webinar "Reference Designs for Hydrogen Fueling Stations" held on October 13, 2015.

  9. EERE Program Management Quick Reference Guide

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

    a companion to the Office of Energy Efficiency and Renewable Energy (EERE) Program Management Reference Guide. It provides an overall description of the EERE program management ...

  10. IBM References | Argonne Leadership Computing Facility

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

    Feedback Form IBM References Contents IBM Redbooks A2 Processor Manual QPX Vector Instruction Set Architecture XL Compiler Documentation MASS Documentation Back to top IBM...

  11. FAQS Reference Guide – Environmental Restoration

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the November 2002 edition of DOE-STD-1157-2002, Environmental Restoration Functional Area Qualification Standard.

  12. Floating Oscillating Water Column Reference Model Completed

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

    Floating Oscillating Water Column Reference Model Completed - Sandia Energy Energy Search ... Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 ...

  13. FAQS Reference Guide – Facility Representative

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide addresses the competency statements in the October 2010 edition of DOE-STD-1151-2010, Facility Representative Functional Area Qualification Standard.

  14. FAQS Reference Guide – Criticality Safety

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide addresses the competency statements in the April 2009 edition of DOE-STD-1173-2009, Criticality Safety Functional Area Qualification Standard.

  15. FAQS Reference Guide – Safeguards and Security

    Broader source: Energy.gov [DOE]

    This reference guide addresses the competency statements in the May 2009 edition of DOE-STD-1171-2009, Safeguards and Security Functional Area Qualification Standard.

  16. Property:ReferenceGenre | Open Energy Information

    Open Energy Info (EERE)

    Property Type Text Description The genre or subcategory label of reference material. Allows Values Buildings;Bulk Transmission;Geothermal;Hydrogen;Hydropower;Smart...

  17. FAQS Reference Guide – Criticality Safety (NNSA)

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide has been developed to address the competency statements in DOE-STD-1173-2009, Criticality Safety Functional Area Qualification Standard.

  18. Archived Reference Climate Zone: 8 Fairbanks, Alaska

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zonesis available for reference.Current versionsare also available.

  19. Archived Reference Climate Zone: 8 Fairbanks, Alaska

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  20. References - DOE Directives, Delegations, and Requirements

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

    References by Website Administrator This page provides information and links to references. Technical Standards Technical Standards Program Technical Standards Home RevCom for Technical Standards Technical Standards Crosswalk NNSA Directives National Nuclear Security Administration (NNSA) Supplemental Directives NNSA Policies (NAPs) FAR Federal Acquisition Regulations Federal Acquisition Regulations (FAR) DOE Acquisition Regulations (DEAR) CFR Code of Federal Regulations CFR (annual edition) 10

  1. Archived Reference Building Type: Medium office

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  2. Archived Reference Building Type: Medium office

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  3. Archived Reference Building Type: Small Hotel

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  4. Archived Reference Building Type: Large Hotel

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  5. Archived Reference Building Type: Small Hotel

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  6. Archived Reference Building Type: Primary school

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  7. Archived Reference Building Type: Primary school

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  8. Archived Reference Building Type: Outpatient health care

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  9. Archived Reference Building Type: Outpatient health care

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  10. Archived Reference Building Type: Strip mall

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zonesis available for reference.Current versionsare also available.

  11. Archived Reference Building Type: Strip mall

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  12. Archived Reference Building Type: Secondary school

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  13. Archived Reference Building Type: Secondary school

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  14. Archived Reference Climate Zone: 7 Duluth, Minnesota

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  15. Archived Reference Climate Zone: 7 Duluth, Minnesota

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  16. Archived Reference Building Type: Large Hotel

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  17. Archived Reference Building Type: Quick service restaurant

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  18. Archived Reference Building Type: Quick service restaurant

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  19. Archived Reference Building Type: Full service restaurant

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

  20. Archived Reference Building Type: Full service restaurant

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zones is available for reference. Current versions are also available.

  1. Archived Reference Building Type: Midrise Apartment

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed before 1980, organized by building type and location. A summary ofbuilding types and climate zonesis available for reference.Current versionsare also available.

  2. Archived Reference Building Type: Midrise Apartment

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the commercial reference building models for existing buildings constructed in or after 1980, organized by building type and location. A summary of building types and climate zones is available for reference. Current versions are also available.

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

    SciTech Connect (OSTI)

    Finley, Cathy

    2014-04-30

    This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the

  4. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect (OSTI)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the systems ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  5. Recent Trends in Variable Generation Forecasting and Its Value to the Power System

    SciTech Connect (OSTI)

    Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; Sharp, Justin; Wilczak, James M.; Freedman, Jeffrey; Haupt, Sue Ellen; Cline, Joel; Bartholomy, Obadiah; Hamann, Hendrik F.; Hodge, Bri-Mathias; Finley, Catherine; Nakafuji, Dora; Peterson, Jack L.; Maggio, David; Marquis, Melinda

    2014-12-23

    We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value of adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.

  6. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect (OSTI)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  7. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison (Presentation)

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B.; Miettinen, J.; Holttinen, H.; Gomez-Lozaro, E.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Lovholm, A.; Berge, E.; Dobschinski, J.

    2013-10-01

    This presentation summarizes the work to investigate the uncertainty in wind forecasting at different times of year and compare wind forecast errors in different power systems using large-scale wind power prediction data from six countries: the United States, Finland, Spain, Denmark, Norway, and Germany.

  8. Recent Trends in Variable Generation Forecasting and Its Value to the Power System

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

    Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; Sharp, Justin; Wilczak, James M.; Freedman, Jeffrey; Haupt, Sue Ellen; Cline, Joel; Bartholomy, Obadiah; Hamann, Hendrik F.; et al

    2014-12-23

    We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value ofmore » adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.« less

  9. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

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

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  10. FAQS Reference Guide - Aviation Manager | Department of Energy

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

    FAQS Reference Guide - Aviation Manager FAQS Reference Guide - Aviation Manager This reference guide addresses the competency statements in the January 2010 edition of...

  11. Microsoft Word - Cross Reference Matrix Introduction.doc | Department...

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

    Cross Reference Matrix Introduction.doc Microsoft Word - Cross Reference Matrix Introduction.doc PDF icon Microsoft Word - Cross Reference Matrix Introduction.doc More Documents & ...

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

    SciTech Connect (OSTI)

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

    2005-02-09

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

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

    SciTech Connect (OSTI)

    Thomas, L.C.

    1994-10-01

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

  14. Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

    Broader source: Energy.gov [DOE]

    Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

  15. Excepted Service EJ and EK Desk Reference

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

    1] U.S. DEPARTMENT OF ENERGY Office of the Chief Human Capital Officer 2012 Excepted Service EJ and EK Desk Reference E X E C U T I V E R E S O U R C E S D I V I S I O N [2] Executive Summary The Excepted Service EJ and EK Desk Reference is designed to provide the framework, in conjunction, with the DOE O 329.1 (Excepted Service Authorities for EJ and EK Pay Plans). Specifically, the desk reference addresses the requirements for the Excepted Service EJ and EK positions, to include: * Description

  16. Weather Research and Forecasting Model with Vertical Nesting Capability

    Energy Science and Technology Software Center (OSTI)

    2014-08-01

    The Weather Research and Forecasting (WRF) model with vertical nesting capability is an extension of the WRF model, which is available in the public domain, from www.wrf-model.org. The new code modifies the nesting procedure, which passes lateral boundary conditions between computational domains in the WRF model. Previously, the same vertical grid was required on all domains, while the new code allows different vertical grids to be used on concurrently run domains. This new functionality improvesmore » WRF's ability to produce high-resolution simulations of the atmosphere by allowing a wider range of scales to be efficiently resolved and more accurate lateral boundary conditions to be provided through the nesting procedure.« less

  17. Emergency Responder Radioactive Material Quick Reference Sheet

    Broader source: Energy.gov [DOE]

    This job aid is a quick reference to assist emergency responders in identifying preliminary safety precautions that should be taken during the initial response phase after arrival at the scene of...

  18. FAQS Reference Guide – Occupational Safety

    Broader source: Energy.gov [DOE]

    This reference guide has been developed to address the competency statements in the July 2011 version of DOE-STD-1160-2011, Occupational Safety Functional Area Qualification Standard.

  19. New Construction Commercial Reference Buildings — Archive

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the reference buildings for new construction commercial buildings, organized by building type and location. A summary of building types and climate zones is...

  20. FAQS Reference Guide – Civil/ Structural Engineering

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide has been developed to address the competency statements in the March 2004 edition of DOE-STD-1182-2004, Civil/Structural Engineering Functional Area Qualification Standard.

  1. New Robust References! | OpenEI Community

    Open Energy Info (EERE)

    provided document type If I,Robot doesn't exist yet, the template will return a red link specially coded to open in the Reference form so that it can be easily added...

  2. FAQS Reference Guide – General Technical Base

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide has been developed to address the competency statements in the March 2015 reaffirmed edition of DOE Standard (STD)-1146-2007, General Technical Base Qualification Standard.

  3. FAQS Reference Guide – Quality Assurance

    Broader source: Energy.gov [DOE]

    This reference guide has been developed to address the competency statements in the April 2002 edition of DOE-Standard (STD)-1150-2002, Quality Assurance Functional Area Qualification Standard.

  4. Webinar: Reference Designs for Hydrogen Fueling Stations

    Broader source: Energy.gov [DOE]

    The Fuel Cell Technologies Office will present a live webinar titled "Reference Designs for Hydrogen Fueling Stations" on Tuesday, October 13, from 12 to 1 p.m. Eastern Daylight Time (EDT).

  5. Archive Reference Buildings by Building Type: Warehouse

    Broader source: Energy.gov [DOE]

    Here you will find past versions of the reference buildings for new construction commercial buildings, organized by building type and location. A summary of building types and climate zones is...

  6. Template:ReferenceHeader | Open Energy Information

    Open Energy Info (EERE)

    Reference Library banner, typically across the top of the page, which features a unique color scheme and simple menu. Parameters none Usage It should be called in the following...

  7. FAQS Reference Guide – Nuclear Safety Specialist

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide has been developed to address the competency statements in the November 2007 edition of DOE Standard DOE-STD-1183-2007, Nuclear Safety Specialist Functional Area Qualification Standard.

  8. FAQS Reference Guide – Instrumentation and Control

    Office of Energy Efficiency and Renewable Energy (EERE)

    This reference guide has been developed to address the competency statements in the June 2013 edition of DOE-Standard (STD)-1162-2013, Instrumentation and Control Functional Area Qualification Standard.

  9. "Analysis of SOFCs using reference electrodes?

    SciTech Connect (OSTI)

    Finklea, Harry; Chen,Xiaoke; Gerdes,Kirk; Pakalapati, Suryanarayana; Celik, Ismail

    2013-07-01

    Reference electrodes are frequently applied to isolate the performance of one electrode in a solid oxide fuel cell. However, reference electrode simulations raise doubt to veracity of data collected using reference electrodes. The simulations predict that the reported performance for the one electrode will frequently contain performance of both electrodes. Nonetheless, recent reports persistently treat data so collected as ideally isolated. This work confirms the predictions of the reference electrode simulations on two SOFC designs, and to provides a method of validating the data measured in the 3-electrode configuration. Validation is based on the assumption that a change in gas composition to one electrode does not affect the impedance of the other electrode at open circuit voltage. This assumption is supported by a full physics simulation of the SOFC. Three configurations of reference electrode and cell design are experimentally examined using various gas flows and two temperatures. Impedance data are subjected to deconvolution analysis and equivalent circuit fitting and approximate polarization resistances of the cathode and anode are determined. The results demonstrate that the utility of reference electrodes is limited and often wholly inappropriate. Reported impedances and single electrode polarization values must be scrutinized on this basis.

  10. References, Canceled-7 Section B- April 16 2010

    Broader source: Energy.gov [DOE]

    This Section contains S&S references arranged as general references and by topical S&S programmatic areas

  11. An Optimized Autoregressive Forecast Error Generator for Wind and Load Uncertainty Study

    SciTech Connect (OSTI)

    De Mello, Phillip; Lu, Ning; Makarov, Yuri V.

    2011-01-17

    This paper presents a first-order autoregressive algorithm to generate real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast errors. The methodology aims at producing random wind and load forecast time series reflecting the autocorrelation and cross-correlation of historical forecast data sets. Five statistical characteristics are considered: the means, standard deviations, autocorrelations, and cross-correlations. A stochastic optimization routine is developed to minimize the differences between the statistical characteristics of the generated time series and the targeted ones. An optimal set of parameters are obtained and used to produce the RT, HA, and DA forecasts in due order of succession. This method, although implemented as the first-order regressive random forecast error generator, can be extended to higher-order. Results show that the methodology produces random series with desired statistics derived from real data sets provided by the California Independent System Operator (CAISO). The wind and load forecast error generator is currently used in wind integration studies to generate wind and load inputs for stochastic planning processes. Our future studies will focus on reflecting the diurnal and seasonal differences of the wind and load statistics and implementing them in the random forecast generator.

  12. No Sunset and Extended Policies Cases (released in AEO2010)

    Reports and Publications (EIA)

    2010-01-01

    The Annual Energy Outlook 2010 Reference case is best described as a current laws and regulations case, because it generally assumes that existing laws and fully promulgated regulations will remain unchanged throughout the projection period, unless the legislation establishing them specifically calls for them to end or change. The Reference case often serves as a starting point for the analysis of proposed legislative or regulatory changes, a task that would be difficult if the Reference case included projected legislative or regulatory changes.

  13. Review of Variable Generation Forecasting in the West: July 2013 - March 2014

    SciTech Connect (OSTI)

    Widiss, R.; Porter, K.

    2014-03-01

    This report interviews 13 operating entities (OEs) in the Western Interconnection about their implementation of wind and solar forecasting. The report updates and expands upon one issued by NREL in 2012. As in the 2012 report, the OEs interviewed vary in size and character; the group includes independent system operators, balancing authorities, utilities, and other entities. Respondents' advice for other utilities includes starting sooner rather than later as it can take time to plan, prepare, and train a forecast; setting realistic expectations; using multiple forecasts; and incorporating several performance metrics.

  14. Development of solid radium-226 reference materials

    SciTech Connect (OSTI)

    Chessmore, R.B.; Engelder, P.R.; Sill, C.W.

    1983-11-01

    Radium-226 reference materials having a matrix similar to soil or tailings samples are not available in sufficient quantity for use by remedial-action contractors to calibrate their laboratory gamma-ray spectrometers. Such reference materials are needed to provide uniform standardization among measurements made by remedial-action contractors. A task, therefore, was undertaken to prepare about 200 pounds each of three different concentrations of radium-226 reference materials by diluting tailings with high-purity silica. Target values for radium-226 content were 50, 15, and 5 pCi/g. The radium-226 content of the reference materials was measured by C.W. Sill of EG and G Idaho, Inc., Idaho Falls, using a high- resolution alpha spectrometry technique standardized with National Bureau of Standards (NBS) standard 4961. A summary of this technique is provided in Appendix A of this report. An independent measurement of the radium-226 content was conducted by Bendix Field Engineering Corporation (Bendix), Grand Junction, Colorado, using a high-resolution Ge(Li) detector, which was calibrated using the New Brunswick Laboratory (NBL) 100-A Series standards. The Ge(Li) detector has also been used to determine the radium-226 content in the calibration models at the Grand Junction facility; these models are used by remedial-action contractors for calibration of borehole logging gamma-ray probes. 8 references, 12 tables.

  15. Ray Effect Mitigation Through Reference Frame Rotation

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

    Tencer, John

    2016-06-14

    The discrete ordinates method is a popular and versatile technique for solving the radiative transport equation, a major drawback of which is the presence of ray effects. Mitigation of ray effects can yield significantly more accurate results and enhanced numerical stability for combined mode codes. Moreover, when ray effects are present, the solution is seen to be highly dependent upon the relative orientation of the geometry and the global reference frame. It is an undesirable property. A novel ray effect mitigation technique of averaging the computed solution for various reference frame orientations is proposed.

  16. TriBITS Developers Guide and Reference

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

    TriBITS Developers Guide and Reference Ross Bartlett Oak Ridge National Laboratory March 31, 2014 CASL-U-2014-0075-000-E CASL-U-2014-0075-000-b TriBITS Developers Guide and Reference Author: Roscoe A. Bartlett (bartlettra@ornl.gov) Abstract This document describes the usage of TriBITS to build, test, and deploy complex software. The primary audience are those individuals who develop on a software project which uses TriBITS. The overall structure of a TriBITS project is described including all of

  17. U.S. Crude Oil Production Forecast-Analysis of Crude Types

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

    of Energy Washington, DC 20585 U.S. Energy Information Administration | U.S. Crude Oil Production Forecast-Analysis of Crude Types i This report was prepared by the U.S....

  18. Resource Information and Forecasting Group; Electricity, Resources, & Building Systems Integration (ERBSI) (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2009-11-01

    Researchers in the Resource Information and Forecasting group at NREL provide scientific, engineering, and analytical expertise to help characterize renewable energy resources and facilitate the integration of these clean energy sources into the electricity grid.

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

    Broader source: Energy.gov [DOE]

    The University Corporation for Atmospheric  Research (UCAR) will develop a solar power forecasting system that advances the state of the science through cutting-edge research.

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

    SciTech Connect (OSTI)

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

    2013-01-01

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