National Library of Energy BETA

Sample records for forecasting ak wa

  1. Category:Seattle, WA | Open Energy Information

    Open Energy Info (EERE)

    Seattle, WA Jump to: navigation, search Go Back to PV Economics By Location Media in category "Seattle, WA" The following 16 files are in this category, out of 16 total....

  2. BayWa Group | Open Energy Information

    Open Energy Info (EERE)

    BayWa Group Jump to: navigation, search Name: BayWa Group Place: Munich, Germany Zip: 81925 Sector: Services, Solar Product: Germany-based company with international operations...

  3. Advance Patent Waiver W(A)2011-006 | Department of Energy

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

    WA05022DOWCHEMICALCOMPANYWaiverofdomesticandForeig.pdf WA04033CARGILLWaiverofPatentRightstoCARGILLDOWNL.pdf WA00022CARGILLDOWPOLYMERSLLCWaiverofDomest...

  4. Solar Forecasting

    Broader source: Energy.gov [DOE]

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

  5. Advance Patent Waiver W(A)2002-023 | Department of Energy

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

    2-023 Advance Patent Waiver W(A)2002-023 PDF icon Advance Patent Waiver W(A)2002-023 More Documents & Publications Advance Patent Waiver W(A)2006-028 WA05056IBMWATSONRESEARCH...

  6. WA_00_022_CARGILL_DOW_POLYMERS_LLC_Waiver_of_Domestic_and_Fo...

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

    22CARGILLDOWPOLYMERSLLCWaiverofDomesticandFo.pdf WA00022CARGILLDOWPOLYMERSLLCWaiverofDomesticandFo.pdf PDF icon WA00022CARGILLDOWPOLYMERSLLCWaiverofDom...

  7. WA_98_001_REYNOLDS_METALS_COMPANY_Waiver_of_Domestic_and_For...

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

    8001REYNOLDSMETALSCOMPANYWaiverofDomesticandFor.pdf WA98001REYNOLDSMETALSCOMPANYWaiverofDomesticandFor.pdf PDF icon WA98001REYNOLDSMETALSCOMPANYWaiverofD...

  8. WA_02_035_BP_SOLAR_INTERNATIONAL_Waiver_of_Domestic_and_Fore...

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

    INTERNATIONALWaiverofDomesticandFore.pdf More Documents & Publications WA06016BPSOLARINTERNATIONALWaiverofPatentRightsUnd.pdf WA02034BPSOLARINTERNATIONALLLCW...

  9. WA_03_010_SHELL_SOLAR_INDUSTRIES_Waiver_of_Domestic_and_Fore...

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

    INDUSTRIESWaiverofDomesticandFore.pdf More Documents & Publications WA02039SHELLSOLARSYSTEMSWaiverofPatentRightsUnder.pdf WA05059SHELLSOLARINDUSTRIESLPWaive...

  10. Forecast Change

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

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

  11. RAPID/Roadmap/19-WA-e | Open Energy Information

    Open Energy Info (EERE)

    Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Water Well Notice of Intent for New Well (19-WA-e) A...

  12. RAPID/Roadmap/11-WA-b | Open Energy Information

    Open Energy Info (EERE)

    Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Human Remains Process (11-WA-b) This flowchart...

  13. RAPID/Roadmap/5-WA-a | Open Energy Information

    Open Energy Info (EERE)

    Geothermal Hydropower Solar Tools Contribute Contact Us Drilling and Well Development (5-WA-a) In Washington geothermal drilling and well development are regulated by the...

  14. RAPID/Roadmap/14-WA-c | Open Energy Information

    Open Energy Info (EERE)

    Geothermal Hydropower Solar Tools Contribute Contact Us Underground Injection Control Permit (14-WA-c) The Safe Drinking Water Act requires Washington to implement...

  15. RAPID/Roadmap/18-WA-b | Open Energy Information

    Open Energy Info (EERE)

    Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Dangerous Solid Waste Permit (18-WA-b) The Washington State Department of Ecology (WSDE) oversees the...

  16. RAPID/Roadmap/14-WA-b | Open Energy Information

    Open Energy Info (EERE)

    RAPIDRoadmap14-WA-b < RAPID | Roadmap Jump to: navigation, search RAPID Regulatory and Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal...

  17. RAPID/Roadmap/15-WA-a | Open Energy Information

    Open Energy Info (EERE)

    BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Air Quality Permit - Notice of Construction Permit (15-WA-a) This flowchart illustrates...

  18. RAPID/Roadmap/15-WA-b | Open Energy Information

    Open Energy Info (EERE)

    BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Air Quality Permit - Operating Permit (15-WA-b) This flowchart illustrates the process for...

  19. RAPID/Roadmap/12-WA-b | Open Energy Information

    Open Energy Info (EERE)

    Geothermal Hydropower Solar Tools Contribute Contact Us State Trust Lands Habitat Conservation Plan Compliance (12-WA-b) The State of Washington has a Habitat Conservation Plan...

  20. RAPID/Roadmap/19-WA-d | Open Energy Information

    Open Energy Info (EERE)

    BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Water Conservancy Board Transfer or Change of Water Right (19-WA-d) In 1997, the Washington...

  1. RAPID/Roadmap/19-WA-c | Open Energy Information

    Open Energy Info (EERE)

    Geothermal Hydropower Solar Tools Contribute Contact Us Transfer or Change of Water Right (19-WA-c) Much of Washington's public waters have been accounted for through...

  2. RAPID/Roadmap/19-WA-b | Open Energy Information

    Open Energy Info (EERE)

    About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us New Water Right Permit Process (19-WA-b) Washington uses a prior appropriation system for the...

  3. Measurement of Fukushima Aerosol Debris in Sequim and Richland, WA and Ketchikan, AK

    SciTech Connect (OSTI)

    Miley, Harry S.; Bowyer, Ted W.; Engelmann, Mark D.; Eslinger, Paul W.; Friese, Judah I.; Greenwood, Lawrence R.; Haas, Derek A.; Hayes, James C.; Keillor, Martin E.; Kiddy, Robert A.; Kirkham, Randy R.; Landen, Jonathan W.; Lepel, Elwood A.; Lidey, Lance S.; Litke, Kevin E.; Morris, Scott J.; Olsen, Khris B.; Thompson, Robert C.; Valenzuela, Blandina R.; Woods, Vincent T.; Biegalski, Steven R.

    2013-05-01

    Aerosol collections were initiated at several locations by PNNL shortly after the Great East Japan Earthquake of May 2011. Aerosol samples were transferred to laboratory high-resolution gamma spectrometers for analysis. Similar to treaty monitoring stations operating across the Northern hemisphere, iodine and other isotopes which could be volatilized at high temperature were detected. Though these locations are not far apart, they have significant variations with respect to water, mountain-range placement, and local topography. Variation in computed source terms will be shown to bound the variability of this approach to source estimation.

  4. DOE - Office of Legacy Management -- Hanford Engineer Works - WA 01

    Office of Legacy Management (LM)

    Hanford Engineer Works - WA 01 FUSRAP Considered Sites Site: Hanford Engineer Works (WA.01 ) Designated Name: Alternate Name: Location: Evaluation Year: Site Operations: Site Disposition: Radioactive Materials Handled: Primary Radioactive Materials Handled: Radiological Survey(s): Site Status: Also see http://www.hanford.gov/ Documents Related to Hanford Engineer Works

  5. WA_06_016_BP_SOLAR_INTERNATIONAL_Waiver_of_Patent_Rights_Und...

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

    06016BPSOLARINTERNATIONALWaiverofPatentRightsUnd.pdf WA06016BPSOLARINTERNATIONALWaiverofPatentRightsUnd.pdf PDF icon WA06016BPSOLARINTERNATIONALWaiverofP...

  6. WA_04_033_CARGILL_Waiver_of_Patent_Rights_to_CARGILL_DOWN_L.pdf...

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

    33CARGILLWaiverofPatentRightstoCARGILLDOWNL.pdf WA04033CARGILLWaiverofPatentRightstoCARGILLDOWNL.pdf PDF icon WA04033CARGILLWaiverofPatentRightstoCARGI...

  7. WA_02_034_BP_SOLAR_INTERNATIONAL_LLC_Waiver_of_Domestic_and_...

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

    verofDomesticand.pdf More Documents & Publications WA02035BPSOLARINTERNATIONALWaiverofDomesticandFore.pdf WA06016BPSOLARINTERNATIONALWaiverofPatentRightsUnd...

  8. Ak Chin Indian Community- 2004 Project

    Broader source: Energy.gov [DOE]

    The Ak-Chin Indian Community will study the feasibility of siting a biopower installation on community lands.

  9. RAPID/Roadmap/6-WA-a | Open Energy Information

    Open Energy Info (EERE)

    in the Washington Administrative Code. 6-WA-a - Oversize-Overweight Load Permit.pdf Error creating thumbnail: Page number not in range. Error creating thumbnail: Page number...

  10. RAPID/Roadmap/3-WA-b | Open Energy Information

    Open Energy Info (EERE)

    the Washington State Department of Natural Resources. 3-WA-b - Land Access Overview.pdf Error creating thumbnail: Page number not in range. Error creating thumbnail: Page number...

  11. Hanford, WA Selected as Plutonium Production Facility | National...

    National Nuclear Security Administration (NNSA)

    Production Facility Hanford, WA Groves selects Hanford, Washington, as site for full-scale plutonium production and separation facilities. Three reactors--B, D, and F--are built....

  12. BayWa Sunways JV | Open Energy Information

    Open Energy Info (EERE)

    JV that specialises in developing, planning and realizing medium-sized to large photovoltaic systems and solar plants. References: BayWa & Sunways JV1 This article is a stub....

  13. RAPID/Roadmap/19-WA-a | Open Energy Information

    Open Energy Info (EERE)

    BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Water Access and Water Rights Overview (19-WA-a) Pursuant to RCW 78.60.060, developers that...

  14. WA_1994_003_GOLDEN_PHOTOCON_INC_Waiver_of_Domestic_and_Forei.pdf |

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

    Department of Energy WA_1994_003_GOLDEN_PHOTOCON_INC_Waiver_of_Domestic_and_Forei.pdf WA_1994_003_GOLDEN_PHOTOCON_INC_Waiver_of_Domestic_and_Forei.pdf PDF icon WA_1994_003_GOLDEN_PHOTOCON_INC_Waiver_of_Domestic_and_Forei.pdf More Documents & Publications WA_1995_030_GOLDEN_PHOTON_INC_Waiver_of_Domestic_and_Foreign.pdf WA_1993_033_GOLDEN_PHOTON_INC_Waiver_of_Domestic_and_Foreign.pdf WA_03_010_SHELL_SOLAR_INDUSTRIES_Waiver_of_Domestic_and_Fore.pdf

  15. Sumas, WA Liquefied Natural Gas Imports (Million Cubic Feet)

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

    (Million Cubic Feet) Sumas, WA Liquefied Natural Gas Imports (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2014 5 2015 4 4 2 1 2016 1 2 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: U.S. Liquefied Natural Gas Imports by Point of Entry Sumas, WA LNG Imports from All Countries

  16. Climate Action Champions: Seattle, WA | Department of Energy

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

    Seattle, WA Climate Action Champions: Seattle, WA The City of Seattle has long been at the leading edge of environmental innovation. Seattle has been recycling for over 25 years and today has one of the highest recycling and composting rates nationwide. In 2005, Seattle City Light became the first electric utility in the nation to be carbon neutral. Recently, Seattle was recognized as the “most sustainable city in the nation” by STAR communities with a 5-STAR rating and the highest

  17. Microsoft Word - WA Parish_MAP_Final.docx

    Energy Savers [EERE]

    W.A. Parish Post-Combustion CO 2 Capture and Sequestration Project U. S. Department of Energy National Energy Technology Laboratory June 2013 INTRODUCTION: The United States (U.S.) Department of Energy (DOE) issued a final environmental impact statement (EIS; DOE/EIS-0473) for the W.A. Parish Post-Combustion CO 2 Capture and Sequestration Project (Parish PCCS Project) in March 2013. DOE announced its decision to provide $167 million in cost-shared funding to NRG Energy, Inc. (NRG) for the

  18. Port Nikiski, AK Liquefied Natural Gas Exports to Japan (Dollars...

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

    Port Nikiski, AK Liquefied Natural Gas Exports to Japan (Dollars per Thousand Cubic Feet) Port Nikiski, AK Liquefied Natural Gas Exports to Japan (Dollars per Thousand Cubic Feet)...

  19. File:06-WA-b - Washington Construction Storm Water Permit.pdf...

    Open Energy Info (EERE)

    6-WA-b - Washington Construction Storm Water Permit.pdf Jump to: navigation, search File File history File usage Metadata File:06-WA-b - Washington Construction Storm Water...

  20. Mechanism of somatic hypermutation at the WA motif by human DNA...

    Office of Scientific and Technical Information (OSTI)

    at the WA motif by human DNA polymerase eta Citation Details In-Document Search Title: Mechanism of somatic hypermutation at the WA motif by human DNA polymerase eta Authors: ...

  1. 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 ...

  2. Wind Power Forecasting Data

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

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

  3. Forecasting Water Quality & Biodiversity

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

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

  4. Wind Power Forecasting

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

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

  5. EIS-0397: Lyle Falls Fish Passage Project, WA

    Broader source: Energy.gov [DOE]

    This EIS analyzes BPA's decision to modify funding to the existing Lyle Falls Fishway on the lower Klickitat River in Klickitat County, WA. The proposed project would help BPA meet its off-site mitigation responsibilities for anadromous fish affected by the development of the Federal Columbia River Power System and increase overall fish production in the Columbia Basin.

  6. Using Wikipedia to forecast disease

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

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

  7. WA_01_018_IBM_Waiver_of_Governement_US_and_Foreign_Patent_Ri.pdf |

    Energy Savers [EERE]

    Department of Energy 1_018_IBM_Waiver_of_Governement_US_and_Foreign_Patent_Ri.pdf WA_01_018_IBM_Waiver_of_Governement_US_and_Foreign_Patent_Ri.pdf PDF icon WA_01_018_IBM_Waiver_of_Governement_US_and_Foreign_Patent_Ri.pdf More Documents & Publications WA_04_053_IBM_CORP_Waiver_of_the_Government_U.S._and_Foreign.pdf WA_00_015_COMPAQ_FEDERAL_LLC_Waiver_Domestic_and_Foreign_Pat.pdf Advance Patent Waiver W(A)2002-023

  8. WA_04_047_CATERPILLAR_INC_Waiver_of_Patent_Rights_to_Inventi.pdf |

    Energy Savers [EERE]

    Department of Energy 47_CATERPILLAR_INC_Waiver_of_Patent_Rights_to_Inventi.pdf WA_04_047_CATERPILLAR_INC_Waiver_of_Patent_Rights_to_Inventi.pdf PDF icon WA_04_047_CATERPILLAR_INC_Waiver_of_Patent_Rights_to_Inventi.pdf More Documents & Publications WA_04_046_CATERPILLAR_INC_Waiver_of_Patent_Rights_to_Inventi.pdf WA_04_071_CATERPILLAR_INC_Waiver_of_Patent_Rights_to_Inventi.pdf Advance Patent Waiver W(A)2005-052

  9. WA_04_069__EATON_CORPORATION_Waiver_of_Domestic_and_Foreign_.pdf |

    Energy Savers [EERE]

    Department of Energy 69__EATON_CORPORATION_Waiver_of_Domestic_and_Foreign_.pdf WA_04_069__EATON_CORPORATION_Waiver_of_Domestic_and_Foreign_.pdf PDF icon WA_04_069__EATON_CORPORATION_Waiver_of_Domestic_and_Foreign_.pdf More Documents & Publications WA_04_059_EATON_CORPORATION_Waiver_of_Patent_Rights_Under_a_.pdf WA_02_048_EATON_CORPORATION_Waviver_of_Patent_Rights_Under_A.pdf WA_04_074_EATON_CORPORATION_Waiver_of_Domestic_and_Foreign_I.pdf

  10. 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 ...

  11. ERSUG Meeting: January 12 - 13, 1995 (Richland, WA)

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

    ERSUG Meeting: January 12 - 13, 1995 (Richland, WA) Dates January 12th & 13th, 1995 Location Pacific Northwest Laboratory Richland, Washington Presentations Summary of ERSUG Meeting January 12 - 13, 1995, Richland, Washington The latest Energy Research Supercomputer Users Group (ERSUG) meeting was held at Pacific Northwest Laboratory in Richland, Washington, on January 12 - 13, 1995. Some of the talks are summarized below. The View from Washington (Tom Kitchens) Tom Kitchens presented the

  12. 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

  13. The forecast calls for flu

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

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

  14. WA_97_027_GENERAL_ATOMICS__CORPORATION_Waiver_of_Domestic_an.pdf |

    Energy Savers [EERE]

    Department of Energy 97_027_GENERAL_ATOMICS__CORPORATION_Waiver_of_Domestic_an.pdf WA_97_027_GENERAL_ATOMICS__CORPORATION_Waiver_of_Domestic_an.pdf PDF icon WA_97_027_GENERAL_ATOMICS__CORPORATION_Waiver_of_Domestic_an.pdf More Documents & Publications WA_99_014_UNITED_SOLAR_SYSTEMS_CORP_Waiver_of_Domestic_and_F.pdf Class Patent Waiver W(C)2004-001 WA_97_006_MOTOROLA_MANUFACTURING_SYSTEMS_Waiver_of_Patent_Ri

  15. DOE Zero Energy Ready Home Case Study: TC Legend Homes, Bellingham, WA |

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

    Department of Energy Bellingham, WA DOE Zero Energy Ready Home Case Study: TC Legend Homes, Bellingham, WA DOE Zero Energy Ready Home Case Study: TC Legend Homes, Bellingham, WA Case study of a DOE Zero Energy Ready home in Bellingham, WA, that achieves HERS 43 without PV or HERS 13 with 3.2 kW of PV. The 1,055-ft2 two-story production home has 6-in. SIP walls, a 10-in. SIP roof, and ICF foundation walls with R-20 high-density rigid EPS foam under the slab. A single ductless heat pump heats

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

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - February 2009 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin...

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

    Open Energy Info (EERE)

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - January 2009 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin...

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

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

  6. Project Reports for Ak Chin Indian Community- 2004 Project

    Broader source: Energy.gov [DOE]

    The Ak-Chin Indian Community will study the feasibility of siting a biopower installation on community lands.

  7. Advance Patent Waiver W(A)2006-028 | Department of Energy

    Energy Savers [EERE]

    6-028 Advance Patent Waiver W(A)2006-028 This document waives certain patent rights the Department of Energy (DOE) has to inventions conceived or first actually reduced to practice by COLONY PROJECT under agreement SUBC-B555909, as the DOE has determined that granting such a waiver best serves the interests of the United States and the general public. PDF icon Advance Patent Waiver W(A)2006-028 More Documents & Publications Advance Patent Waiver W(A)2005-048 2011_INCITE_Fact_Sheets.pdf

  8. Advance Patent Waiver W(A)2012-021 | Department of Energy

    Energy Savers [EERE]

    2-021 Advance Patent Waiver W(A)2012-021 This document waives certain patent rights the Department of Energy (DOE) has to inventions conceived or first actually reduced to practice by USEC, INC. under agreement DE-NE0000488, as the DOE has determined that granting such a waiver best serves the interests of the United States and the general public. PDF icon Advance Patent Waiver W(A)2012-021 More Documents & Publications WA_1993_042_UNITED_TECHNOLOGIES_CORPORATION_Waiver_of_the_Go.pdf

  9. DOE Zero Energy Ready Home Case Study: Clifton View Homes, Coupeville, WA,

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

    Systems Home | Department of Energy Coupeville, WA, Systems Home DOE Zero Energy Ready Home Case Study: Clifton View Homes, Coupeville, WA, Systems Home Case study of a DOE Zero Energy Ready Home on Whidbey Island, WA, that scored HERS 45 without PV. This 2,908-square-foot custom/system home has a SIP roof and walls, R-20 rigid foam under slab, triple-pane windows, ground source heat pump for radiant floor heat, and a unique balanced ventilation system using separate exhaust fans to bring

  10. DOE Zero Energy Ready Home Case Study: Dwell Development, Seattle, WA,

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

    Systems Home | Department of Energy Dwell Development, Seattle, WA, Systems Home DOE Zero Energy Ready Home Case Study: Dwell Development, Seattle, WA, Systems Home Case study of a DOE Zero Energy Ready Home in Seattle, WA, that scored HERS 34 without PV. This 2,000-square-foot system home has R-45 double-stud walls, an unvented flat roof with 2 inches of spray foam plus 18 inches blown cellulose, R-42 XPS under slab, triple-pane windows, and a ductless mini-split heat pump. PDF icon Dwell

  11. Fisher & Paykel Appliances: ENERGY STAR Referral (WA42T26GW1) | Department

    Energy Savers [EERE]

    of Energy Fisher & Paykel Appliances: ENERGY STAR Referral (WA42T26GW1) Fisher & Paykel Appliances: ENERGY STAR Referral (WA42T26GW1) June 12, 2013 DOE referred the matter of Fisher & Paykel Appliances residential clothes washer, model WA42T26GW1, to the U.S. Environmental Protection Agency, brand manager for the ENERGY STAR Program, for appropriate action after DOE testing showed that the model does not meet the ENERGY STAR specification. PDF icon Fisher & Paykel Appliances:

  12. 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)

  13. Supply Forecast and Analysis (SFA)

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

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

  14. 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.

  15. 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:...

  16. Advance Patent Waiver W(A)2010-006 | Department of Energy

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

    Advance Patent Waiver W(A)2010-006 This document waives certain patent rights the Department of Energy (DOE) has to inventions conceived or first actually reduced to practice by ...

  17. Best Practices Case Study: Devoted Builders, LLC, Mediterrtanean Villas, Pasco,WA

    SciTech Connect (OSTI)

    2010-12-01

    Devoted Builders of Kennewick, WA worked with Building America's BIRA team to achieve the 50% Federal tax credit level energy savings on 81 homes at its Mediterranean Villas community in eastern Washington.

  18. DOE Zero Energy Ready Home Case Study: TC Legend Homes, Bellingham, WA

    Broader source: Energy.gov [DOE]

    Case study of a DOE Zero Energy Ready home in Bellingham, WA, that achieves HERS 43 without PV or HERS 13 with 3.2 kW of PV.

  19. Advance Patent Waiver W(A)2008-006 | Department of Energy

    Energy Savers [EERE]

    8-006 Advance Patent Waiver W(A)2008-006 This document waives certain patent rights the Department of Energy (DOE) has to inventions conceived or first actually reduced to practice by CATERPILLAR, INC under agreement DE-FC26-00AL67017, as the DOE has determined that granting such a waiver best serves the interests of the United States and the general public. PDF icon Advance Patent Waiver W(A)2008-006 More Documents & Publications

  20. Advance Patent Waiver W(A)2010-037 | Department of Energy

    Energy Savers [EERE]

    7 Advance Patent Waiver W(A)2010-037 This document waives certain patent rights the Department of Energy (DOE) has to inventions conceived or first actually reduced to practice by ALCATEL-LUCENT USA INC. under agreement DE-EE0002895, as the DOE has determined that granting such a waiver best serves the interests of the United States and the general public. PDF icon Advance Patent Waiver W(A)2010-037 More Documents & Publications A

  1. Advance Patent Waiver W(A)2010-038 | Department of Energy

    Energy Savers [EERE]

    8 Advance Patent Waiver W(A)2010-038 This document waives certain patent rights the Department of Energy (DOE) has to inventions conceived or first actually reduced to practice by ALCATEL-LUCENT USA INC. under agreement DE-EE0002887, as the DOE has determined that granting such a waiver best serves the interests of the United States and the general public. PDF icon Advance Patent Waiver W(A)2010-038 More Documents & Publications A

  2. RAPID/Roadmap/6-AK-b | Open Energy Information

    Open Energy Info (EERE)

    Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Construction Storm Water Permit (6-AK-b) From DEC...

  3. RAPID/Roadmap/14-AK-d | Open Energy Information

    Open Energy Info (EERE)

    Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us 401 Water Quality Certification (14-AK-d) In accordance...

  4. RAPID/Roadmap/18-AK-a | Open Energy Information

    Open Energy Info (EERE)

    Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Underground Storage Tank Permit (18-AK-a) 18AKA - StorageTankRegistration (1).pdf Error creating...

  5. RAPID/Roadmap/14-AK-c | Open Energy Information

    Open Energy Info (EERE)

    Geothermal Hydropower Solar Tools Contribute Contact Us Underground Injection Control Permit (14-AK-c) 14AKCAlaskaUICPermit.pdf Error creating thumbnail: Page number not...

  6. RAPID/Roadmap/18-AK-b | Open Energy Information

    Open Energy Info (EERE)

    Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Hazardous Waste Permit (18-AK-b) The Alaska Department of Environmental Conservation defers to the...

  7. RAPID/Roadmap/14-AK-b | Open Energy Information

    Open Energy Info (EERE)

    RAPIDRoadmap14-AK-b < RAPID | Roadmap Jump to: navigation, search RAPID Regulatory and Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal...

  8. RAPID/Roadmap/3-AK-a | Open Energy Information

    Open Energy Info (EERE)

    RAPIDRoadmap3-AK-a < RAPID | Roadmap Jump to: navigation, search RAPID Regulatory and Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower...

  9. RAPID/Roadmap/17-AK-a | Open Energy Information

    Open Energy Info (EERE)

    RAPIDRoadmap17-AK-a < RAPID | Roadmap Jump to: navigation, search RAPID Regulatory and Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal...

  10. RAPID/Roadmap/8-AK-c | Open Energy Information

    Open Energy Info (EERE)

    8-AK-c < RAPID | Roadmap Jump to: navigation, search RAPID Regulatory and Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools...

  11. RAPID/Roadmap/3-AK-c | Open Energy Information

    Open Energy Info (EERE)

    AK-c < RAPID | Roadmap Jump to: navigation, search RAPID Regulatory and Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools...

  12. RAPID/Roadmap/15-AK-c | Open Energy Information

    Open Energy Info (EERE)

    BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Air Quality Permit - Title V Operating Permit (15-AK-c) One of the major initiatives...

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

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

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

  15. 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:...

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

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

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

  17. 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.

  18. Really Off the Grid: Hooper Bay, AK

    Energy Savers [EERE]

    Really Off the Grid - Hooper Bay, AK Old Housing - Energy Efficiency Vintage Hooper Bay Renewable Energy - Before & After DOE Tribal Energy Grant * $200,000 - Energy Efficiency Feasibility Study * Hire & train 2-5 local energy assessors * Energy audits of 24 homes with blower doors, etc. - Reduce energy consumption from air leakage - Moisture/mold issues - Reduce drafts * $7/gallon heating fuel * ~ $0.55/kWh - electricity (over half of households behind on utility payments) Is your house

  19. 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

  20. Acquisition Forecast Download | Department of Energy

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

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

  1. 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.

  2. Sumas, WA Liquefied Natural Gas Imports from Canada (Million Cubic Feet)

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

    from Canada (Million Cubic Feet) Sumas, WA Liquefied Natural Gas Imports from Canada (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2014 5 2015 4 4 2 1 2016 1 2 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: U.S. Liquefied Natural Gas Imports by Point of Entry Sumas, WA Natural Gas Imports by Pipeline from Canada

  3. W.A. Parish Post-Combustion CO{sub 2} Capture and Sequestration Project

    Office of Scientific and Technical Information (OSTI)

    Phase 1 Definition (Technical Report) | SciTech Connect SciTech Connect Search Results Technical Report: W.A. Parish Post-Combustion CO{sub 2} Capture and Sequestration Project Phase 1 Definition Citation Details In-Document Search Title: W.A. Parish Post-Combustion CO{sub 2} Capture and Sequestration Project Phase 1 Definition For a secure and sustainable energy future, the United States (U.S.) must reduce its dependence on imported oil and reduce its emissions of carbon dioxide (CO{sub 2})

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

  6. 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

  7. DOE Zero Energy Ready Home Case Study: Clifton View Homes, Whidbey Island, WA

    Broader source: Energy.gov [DOE]

    Case study of a DOE Zero Energy Ready home on Whidbey Island, WA, that scores HERS 37 without PV or HERS -13 with 10 kW PV, enough to power the home and an electric car. The two-story custom home...

  8. EIA lowers forecast for summer gasoline prices

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

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

  9. Kenai, AK Liquefied Natural Gas Exports to Taiwan (Dollars per...

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

    Liquefied Natural Gas Exports to Taiwan (Dollars per Thousand Cubic Feet) Kenai, AK Liquefied Natural Gas Exports to Taiwan (Dollars per Thousand Cubic Feet) Year Jan Feb Mar Apr...

  10. Kenai, AK Liquefied Natural Gas Exports to China (Million Cubic...

    Gasoline and Diesel Fuel Update (EIA)

    to China (Million Cubic Feet) Kenai, AK Liquefied Natural Gas Exports to China (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2011 1,127 - No Data ...

  11. RAPID/Roadmap/7-AK-a | Open Energy Information

    Open Energy Info (EERE)

    Us Power Plant Siting Process (7-AK-a) Add text. 07AKAPowerPlantSitingConstruction.pdf Error creating thumbnail: Page number not in range. Error creating thumbnail: Page number...

  12. RAPID/Roadmap/3-AK-h | Open Energy Information

    Open Energy Info (EERE)

    Settlement Lands Leasing (3-AK-h) 03AKHAlaskaNativeClaimsSettlementLandsLeasing.pdf Error creating thumbnail: Page number not in range. Error creating thumbnail: Page number...

  13. RAPID/Roadmap/13-AK-a | Open Energy Information

    Open Energy Info (EERE)

    Contribute Contact Us State Land Use Assessment (13-AK-a) 13AKALandUseAssessment.pdf Error creating thumbnail: Page number not in range. Error creating thumbnail: Page number...

  14. RAPID/Roadmap/6-AK-a | Open Energy Information

    Open Energy Info (EERE)

    of a load upon a highway. Examples of such vehicles are self-propelled cranes, pump trucks, off-road construction equipment or other road maintenance equipment. 6-AK-a.3 -...

  15. RAPID/Roadmap/15-AK-a | Open Energy Information

    Open Energy Info (EERE)

    BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Air Quality Assessment Process (15-AK-a) The Clean Air Act is the law that defines the...

  16. RAPID/Roadmap/15-AK-b | Open Energy Information

    Open Energy Info (EERE)

    BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Air Quality Permit - Minor Permit (15-AK-b) The mission of the Air Permit Program is to...

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

    Open Energy Info (EERE)

    March 2009 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin Electric Utility Authority for March 2009. Monthly Electric Utility Sales and...

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

    Open Energy Info (EERE)

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

  19. RAPID/Roadmap/12-AK-a | Open Energy Information

    Open Energy Info (EERE)

    12-AK-a.1 - Will the Project Affect Streams or Other Bodies of Water? The Anadromous Fish Act (AS 16.05.871-.901) requires that an individual or government agency provide prior...

  20. 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

  1. AK-CHIN INDIAN COMMUNITY BIOMASS FEASIBILITY STUDY

    Energy Savers [EERE]

    4 Program Review Meeting Feasibility Study for Renewable Energy Development on Community Lands Solicitation # DE-PS36-02GO92006 October 20, 2004 © 2004 L. S. Gold & Associates, Inc. Page 2 October 20, 2004 AK-CHIN INDIAN COMMUNITY BIOMASS FEASIBILITY STUDY Topics * Ak-Chin Indian Community * Project Background and Objectives * Project Description and Diagram * Project Team * Proposed Project Schedule * Items To Be Reviewed * Resource Assessment * Digester Technology * Decision Factors *

  2. NREL: Resource Assessment and Forecasting Home Page

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

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

  3. DOE Zero Energy Ready Home Case Study: TC Legend, Seattle, WA, Custom Home

    Broader source: Energy.gov [DOE]

    Case study of a DOE Zero Energy Ready Home in Seattle, WA, that scored HERS 37 without PV, HERS -1 with PV. This 1,915-square-foot custom home has SIP walls and roof, R-20 XPS under the slab, triple-pane windows, an air to water heat pump for radiant heat, and balanced ventilation with timer-controlled fans to bring in and exhaust air.

  4. 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

  5. Solar Forecast Improvement Project | Department of Energy

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

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

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

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

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

  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. 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...

  9. 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 ...

  10. 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 ...

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

  14. Ak-Chin Indian Community Biomass Feasiiblity Study

    SciTech Connect (OSTI)

    Mark A. Moser, RCM Digesters, Inc.; Mark Randall, Daystar Consulting, LLC; Leonard S. Gold, Ak-Chin Energy Services & Utility Strategies Consulting Group

    2005-12-31

    Study of the conversion of chicken litter to biogas for the production of energy. There was an additional requirement that after extracting the energy from the chicken litter the nutrient value of the raw chicken litter had to be returned to the Ak-Chin Farms for use as fertilizer in a form and delivery method acceptable to the Farm.

  15. Kenai, AK Liquefied Natural Gas Exports to Japan (Million Cubic...

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

    Million Cubic Feet) Kenai, AK Liquefied Natural Gas Exports to Japan (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2011 1,856 1,908 1,915 1,913 1,915...

  16. 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.

  17. 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.

  18. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  19. 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.

  20. 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...

  1. 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....

  2. 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...

  3. NREL: Resource Assessment and Forecasting - Research Staff

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

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

  4. 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.

  5. Recovery Act: Waste Energy Project at AK Steel Corporation Middletown

    SciTech Connect (OSTI)

    Joyce, Jeffrey

    2012-06-30

    In 2008, Air Products and Chemicals, Inc. (Air Products) began development of a project to beneficially utilize waste blast furnace topgas generated in the course of the iron-making process at AK Steel Corporations Middletown, Ohio works. In early 2010, Air Products was awarded DOE Assistance Agreement DE-EE002736 to further develop and build the combined-cycle power generation facility. In June 2012, Air Products and AK Steel Corporation terminated work when it was determined that the project would not be economically viable at that time nor in the foreseeable future. The project would have achieved the FOA-0000044 Statement of Project Objectives by demonstrating, at a commercial scale, the technology to capture, treat, and convert blast furnace topgas into electric power and thermal energy.

  6. 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.

  7. 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.

  8. EIS-0473: W.A. Parish Post-Combustion CO2 Capture and Sequestration Project (PCCS), Fort Bend County, TX

    Broader source: Energy.gov [DOE]

    This EIS evaluates the environmental impacts of a proposal to provide financial assistance for a project proposed by NRG Energy, Inc (NRG). DOE selected NRG’s proposed W.A. Parish Post-Combustion CO2 Capture and Sequestration Project for a financial assistance award through a competitive process under the Clean Coal Power Initiative Program. NRG would design, construct and operate a commercial-scale carbon dioxide (CO2) capture facility at its existing W.A. Parish Generating Station in Fort Bend County, Texas; deliver the CO2 via a new pipeline to the existing West Ranch oil field in Jackson County, Texas, for use in enhanced oil recovery operations; and demonstrate monitoring techniques to verify the permanence of geologic CO2 storage.

  9. 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 ...

  10. 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...

  11. Origin State>> CA ID ID ID IL KY NV NY NY OH TN TN TN, WA, CA

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

    NV NY NY OH TN TN TN, WA, CA TN TN TN TN TX Total Shipments by Route Lawrence Livermore National Laboratory Advanced Mixed Waste Treatment Project Batelle Energy Alliance Idaho National Laboratory Argonne National Laboratory Paducah Gaseous Diffusion Plant National Security Technologies Brookhaven National Laboratory West Valley Environmental Services Portsmouth Gaseous Diffusion Plant Duratek/Energy Solutions Babcox & Wilcox Technical Services Y-12 Plant Materials & Energy Corporation

  12. Origin State>> CA ID ID ID IL MD NM NM NY OH TN TN TN, WA, CA

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

    NY OH TN TN TN, WA, CA TN TN TN TX Total Shipments by Route Lawrence Livermore National Laboratory Batelle Energy Alliance Idaho National Laboratory Advanced Mixed Waste Treatment Project Argonne National Laboratory Aberdeen Proving Ground Sandia National Laboratory Los Alamos National Laboratory Brookhaven National Laboratory Portsmouth Gaseous Diffusion Plant Duratek/Energy Solutions Babcox & Wilcox Technical Services Y-12 Plant Materials & Energy Corporation (M&EC) Perma-Fix

  13. Origin State>> CA ID ID ID IL NM NM OH TN TN TN, WA, CA TN TN

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

    NM NM OH TN TN TN, WA, CA TN TN TN TN TX Total Shipments by Route Lawrence Livermore National Laboratory Batelle Energy Alliance Idaho National Laboratory Advanced Mixed Waste Treatment Project Argonne National Laboratory Sandia National Laboratory Los Alamos National Laboratory Portsmouth Gaseous Diffusion Plant Duratek/Energy Solutions Babcox & Wilcox Technical Services Y-12 Plant Materials & Energy Corporation (M&EC) Perma-Fix Nuclear Fuels Services Wastren Advantage, Inc.

  14. Origin State>> CA ID ID IL IL KY NM NM NV NY OH TN TN TN, WA,

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

    IL IL KY NM NM NV NY OH TN TN TN, WA, CA TN TN TN TN Total Shipments by Route Lawrence Livermore National Laboratory Batelle Energy Alliance Idaho National Laboratory Energx Argonne National Laboratory Argonne National Laboratory Paducah Gaseous Diffusion Plant Sandia National Laboratory Los Alamos National Laboratory National Security Technologies West Valley Environmental Services Portsmouth Gaseous Diffusion Plant Duratek/Energy Solutions Babcox & Wilcox Technical Services Y-12 Plant

  15. 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...

  16. 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

  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. 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.

  19. 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)

  20. Uncertainty Reduction in Power Generation Forecast Using Coupled

    Office of Scientific and Technical Information (OSTI)

    Wavelet-ARIMA (Conference) | SciTech Connect Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA Citation Details In-Document Search Title: Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of

  1. 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.

  2. 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.

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

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

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

  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. 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.

  6. 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.

  7. File:NREL-ak-50m.pdf | Open Energy Information

    Open Energy Info (EERE)

    Help Apps Datasets Community Login | Sign Up Search File Edit with form History File:NREL-ak-50m.pdf Jump to: navigation, search File File history File usage Alaska Mainland...

  8. File:NREL-ak2-50m.pdf | Open Energy Information

    Open Energy Info (EERE)

    File Edit with form History File:NREL-ak2-50m.pdf Jump to: navigation, search File File history File usage Alaska Panhandle Annual Average Wind Speed at 50 Meters (PDF) Size of...

  9. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

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

    2014-12-30

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

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. Results from ORNL Characterization of Zr02-500-AK2 - Surrogate TRISO Material

    SciTech Connect (OSTI)

    Hunn, John D; Kercher, Andrew K

    2005-06-01

    This document is a compilation of the characterization data for the TRISO-coated surrogate particle batch designated ZrO2-500-AK2 that was produced at Oak Ridge National Laboratory (ORNL) as part of the Advanced Gas Reactor Fuel Development and Qualification (AGR) program. The ZrO2-500-AK2 material contains nominally 500 {micro}m kernels of yttria-stabilized zirconia (YSZ) coated with all TRISO layers (buffer, inner pyrocarbon, silicon carbide, and outer pyrocarbon). The ZrO2-500-AK2 material was created for: (1) irradiation testing in the High Flux Isotope Reactor (HFIR) and (2) limited dissemination to laboratories as deemed appropriate to the AGR program. This material was created midway into a TRISO fuel development program to accommodate a sudden opportunity to perform irradiation testing on surrogate material. While the layer deposition processes were chosen based on the best technical understanding at the time, technical progress at ORNL has led to an evolution in the perceived optimal deposition conditions since the createion of ZrO2-500-AK2. Thus, ZrO2-500-AK2 contains a reasonable TRISO microstructure, but does differ significanly from currently produced TRISO surrogates and fuel at ORNL. In this document, characterization data of the ZrO2-500-AK2 surrogate includes: size, shape, coating thickness, and density.

  15. Results from ORNL characterization of ZrO2-500-AK2 - surrogate TRISO material

    SciTech Connect (OSTI)

    Kercher, Andrew K; Hunn, John D

    2005-06-01

    This document is a compilation of the characterization data for the TRISO-coated surrogate particles designated ZrO2-500-AK2 that was produced at Oak Ridge National Laboratory (ORNL) as part of the Advanced Gas Reactor Fuel Development and Qualification (AGR) program. The ZrO2-500-AK2 material contains nominally 500 {micro}m kernels of yttria-stabilized zirconia (YSZ) coated with all TRISO layers (buffer, inner pyrocarbon, silicon carbide, and outer pyrocarbon). The ZrO2-500-AK2 material was created for: (1) irradiation testing in the High Flux Isotope Reactor (HFIR) and (2) limited dissemination to laboratories as deemed appropriate to the AGR program. This material was created midway into a TRISO fuel development program to accommodate a sudden opportunity to perform irradiation testing on surrogate material. While the layer deposition processes were chosen based on the best technical understanding at the time, technical progress at ORNL has led to an evolution in the perceived optimal deposition conditions since the creation of ZrO2-500-AK2. Thus, ZrO2-500-AK2 contains a reasonable TRISO microstructure, but does differ significantly from currently produced TRISO surrogates and fuel at ORNL. In this document, characterization data of the ZrO2-500-AK2 surrogate includes: size, shape, coating thickness, and density.

  16. HIA 2015 DOE Zero Energy Ready Home Case Study: TC Legend Homes, Bellingham Power House, Bellingham, WA

    Energy Savers [EERE]

    Bellingham Power House Bellingham, WA DOE ZERO ENERGY READY HOME(tm) The U.S. Department of Energy invites home builders across the country to meet the extraordinary levels of excellence and quality specified in DOE's Zero Energy Ready Home program (formerly known as Challenge Home). Every DOE Zero Energy Ready Home starts with ENERGY STAR Certified Homes Version 3.0 for an energy-efficient home built on a solid foundation of building science research. Advanced technologies are designed in to

  17. Analyses of soils at commercial radioactive-waste-disposal sites. [Barnwell, SC; Richland, WA

    SciTech Connect (OSTI)

    Piciulo, P.L.; Shea, C.E.; Barletta, R.E.

    1982-01-01

    Brookhaven National Laboratory, in order to provide technical assistance to the NRC, has measured a number of physical and chemical characteristics of soils from two currently operating commercial radioactive waste disposal sites; one at Barnwell, SC, and the other near Richland, WA. Soil samples believed to be representative of the soil that will contact the buried waste were collected and analyzed. Earth resistivities (field measurements), from both sites, supply information to identify variations in subsurface material. Barnwell soil resistivities (laboratory measurements) range from 3.6 x 10/sup 5/ ohm-cm to 8.9 x 10/sup 4/ ohm-cm. Soil resistivities of the Hanford sample vary from 3.0 x 10/sup 5/ ohm-cm to 6.6 x 10/sup 3/ ohm-cm. The Barnwell and Hanford soil pH ranges from 4.8 to 5.4 and from 4.0 to 7.2 respectively. The pH of a 1:2 mixture of soil to 0.01 M CaCl/sub 2/ resulted in a pH for the Barnwell samples of 3.9 +- 0.1 and for the Hanford samples of 7.4 +- 0.2. These values are comparable to the pH measurements of the water extract of the soils used for the analyses of soluble ion content of the soils. The exchange acidity of the soils was found to be approximately 7 mg-eq per 100 g of dry soil for clay material from Barnwell, whereas the Hanford soils showed an alkaline reaction. Aqueous extracts of saturated pastes were used to determine the concentrations of the following ions: Ca/sup 2 +/, Mg/sup 2 +/, K/sup +/, Na/sup +/, HCO/sub 3//sup -/, SO/sub 4//sup =/, and Cl/sup -/. The sulfide content of each of the soils was measured in a 1:2.5 mixture of soil to an antioxidant buffer solution. The concentrations of soluble ions found in the soils from both sites are consistent with the high resistivities.

  18. 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.

  19. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

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

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

  4. 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.

  5. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

  8. 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.

  9. 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, ...

  10. 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...

  11. 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...

  12. 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.

  13. HIA 2015 DOE Zero Energy Ready Home Case Study: Clifton View Homes, Marine Drive and Port Hadlcok, Coupeville and Port Hadlock WA

    Energy Savers [EERE]

    Homes Marine Drive and Port Hadlock Coupeville, WA Port Hadlock, WA DOE ZERO ENERGY READY HOME(tm) The U.S. Department of Energy invites home builders across the country to meet the extraordinary levels of excellence and quality specified in DOE's Zero Energy Ready Home program (formerly known as Challenge Home). Every DOE Zero Energy Ready Home starts with ENERGY STAR Certified Homes Version 3.0 for an energy-efficient home built on a solid foundation of building science research. Advanced

  14. 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.

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

    SciTech Connect (OSTI)

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

    2012-07-01

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

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

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

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

  17. 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.

  18. 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...

  19. Evaluation of contaminant flux rates from sediments of Sinclair Inlet, WA, using a benthic flux sampling device. Final report

    SciTech Connect (OSTI)

    Chadwick, D.B.; Lieberman, S.H.; Reimers, C.E.; Young, D.

    1993-02-01

    A Benthic Flux Sampling Device (BFSD) was demonstrated on site to determine the mobility of contaminants in sediments off the Puget Sound Naval Shipyard (PSNS) in Sinclair Inlet, WA. Quantification of toxicant flux from the sediments will support ongoing assessment studies and facilitate the design of appropriate remediation strategies, if required. In general, where release of contaminants was found, the measured rates do not represent a significant source relative to other major inputs such as sewer discharges, nonpoint source runoff, and marinas. They may, however, represent an exposure pathway for benthic biota with a subsequent potential for toxicological effects and/or bioaccumulation. Environmental assessment, CIVAPP:Toxicity, CIVAPP:Marine chemistry, Hazardous waste.

  20. Kenai, AK Exports to Taiwan Liquefied Natural Gas (Million Cubic Feet)

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

    Exports to Taiwan Liquefied Natural Gas (Million Cubic Feet) Kenai, AK Exports to Taiwan Liquefied Natural Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2015 2,748 2,754 2,755 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 04/29/2016 Next Release Date: 05/31/2016 Referring Pages: U.S. Liquefied Natural Gas Exports by Point of Exit Kenai, AK Liquefied Natural Gas Exports to

  1. Kenai, AK Liquefied Natural Gas Exports to Russia (Dollars per Thousand

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

    Cubic Feet) Kenai, AK Liquefied Natural Gas Exports to Russia (Dollars per Thousand Cubic Feet) Kenai, AK Liquefied Natural Gas Exports to Russia (Dollars per Thousand Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's -- 12.12 -- -- 2010's -- - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 04/29/2016 Next Release Date: 05/31/2016 Referring Pages: U.S. Price

  2. ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-ATM NSAC1 V4)

    Office of Scientific and Technical Information (OSTI)

    (Dataset) | Data Explorer Data Explorer Search Results ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-ATM NSAC1 V4) Title: ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-ATM NSAC1 V4) The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data. Authors: McCoy, Renata ; Xie, Shaocheng Publication Date: 2013-12-26 OSTI Identifier: 1039932 DOE Contract Number: DE-AC05-00OR22725

  3. ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-ATM NSAC1 V4)

    Office of Scientific and Technical Information (OSTI)

    (Dataset) | Data Explorer Barrow, AK (ARMBE-ATM NSAC1 V4) Title: ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-ATM NSAC1 V4) The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data. Authors: McCoy, Renata ; Xie, Shaocheng Publication Date: 2013-12-26 OSTI Identifier: 1111572 DOE Contract Number: DE-AC05-00OR22725 Resource Type: Dataset Data Type: Numeric Data Research Org:

  4. 2013,1,"AK",3522,"Chugach Electric Assn Inc",0,,,,0,0,,,,0,0...

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

    ...034,15248,226,1,0,15475 2013,1,"VT",7601,"Green Mountain Power Corp",39.65,10.83,0,0,50.48... 2013,1,"WA",15500,"Puget Sound Energy Inc",334.185,64.655,0,0,398.84,26734.802,...

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

    SciTech Connect (OSTI)

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

    2011-12-06

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

  6. 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.

  7. 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.

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

    Broader source: Energy.gov [DOE]

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

  9. ORISE "AK RlDGE lNSTlT"TE FOR SCIENCE AND EDUCATION

    Office of Legacy Management (LM)

    ti,;;; il.,. (' . d ORISE "AK RlDGE lNSTlT"TE FOR SCIENCE AND EDUCATION August 1,200l Robert Atkin U.S. Department of Energy Oak Ridge Operations Office P.O. Box 2001 Oak Ridge, ...

  10. 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,...

  11. 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....

  12. 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.

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

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

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

  14. 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.

  15. 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.

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

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

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

  17. 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.

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

    Office of Scientific and Technical Information (OSTI)

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

  19. 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...

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

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

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

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

    Office of Environmental Management (EM)

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

  2. Modeling and forecasting the distribution of Vibrio vulnificus in

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Energy Savers [EERE]

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

  5. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National

    Office of Scientific and Technical Information (OSTI)

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

  6. 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

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

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

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

  8. 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.

  9. Wa s h i n g t o n U n i v e r s i t y i n S t . L o...

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

    Wa s h i n g t o n U n i v e r s i t y i n S t . L o u i s - - P A R C ' s H o s t & A d mi n s t r a t i v e H o me - B o b B l a n k e n s h i p , P A R C D i r e c t o r - D e ...

  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. 1990,"AK","Total Electric Power Industry","All Sources",4208809,18741,12562

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

    State","Producer Type","Energy Source","CO2 (Metric Tons)","SO2 (Metric Tons)","NOx (Metric Tons)" 1990,"AK","Commercial Cogen","All Sources",824004,13198,3011 1990,"AK","Commercial Cogen","Coal",821929,13191,3009 1990,"AK","Commercial Cogen","Petroleum",2075,6,2 1990,"AK","Commercial Non-Cogen","All Sources",0,149,42

  13. 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.

  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. 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).

  16. 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).

  17. 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...

  18. 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.

  19. 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.

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

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

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

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

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

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

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

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

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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

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

    2011-11-29

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

  8. 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.

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

    Broader source: Energy.gov [DOE]

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

  10. 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.

  11. Franklin PUD, Pasco WA

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

    have been replaced by Hans Berg (State of Washington, Wid Ritchie (Idaho Falls) and Shawn Collins (The Energy Project). A few participants reported new LIEE activities, due at...

  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 ! " #" $ % % & # % " " " ' % ' ( ) * + " % ( , - . / 0 / " 0 . * 0 . * . . " 0 References A short model description Sensitivity tests Results Tropospheric humidity # " humidity 1 % 2 % ' 3 " % + 1 % 2 % % 3 % Updraft entrainment ' + % " 3 % 4 # " + %' 5 6)( . % ' 1 % .7

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

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

    Data and Resources National Solar Radiation Database NREL resource assessment and forecasting research information is available from the following sources. Renewable Resource Data Center (RReDC) Provides information about biomass, geothermal, solar, and wind energy resources. Measurement and Instrumentation Data Center Provides irradiance and meteorological data from stations throughout the United States. Baseline Measurement System (BMS) Provides live solar radiation data from approximately 70

  14. NREL: Energy Analysis - Energy Forecasting and Modeling Staff

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

    Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Elizabeth Torres Clayton Barrows Dave Bielen Aaron Bloom Greg Brinkman Brian W Bush Stuart Cohen Wesley Cole Paul Denholm Nicholas DiOrio Aron Dobos Kelly Eurek Janine Freeman Bethany Frew Pieter Gagnon Elaine Hale

  15. 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.

  16. 3AK RIDGE NATIONAL LABORATORY OPERAiEO BY MARTIN MARIE,TA ENERGY SYSTEMS, INC.

    Office of Legacy Management (LM)

    .I Y. ,J,.- i - 3AK RIDGE NATIONAL LABORATORY OPERAiEO BY MARTIN MARIE,TA ENERGY SYSTEMS, INC. POST OFFICE BOX X OAK RIOGE. TENNESSEE 37631 July 20, 1984 Ms. Gale P. Turi Division of Remedial Action Projects Office of Nuclear Energy U.S. Department of Energy MS - NE24 Washington, D.C. 20545 Dear Ms. Turi: Radfoloafcal Survey of the Guterl Steel Fad1 ftya 1 o&a As requested, a visit was made to the Guterl Steel facility (formerly Simonds Saw and Steel) on July 9, 1984 to determine if there

  17. Albany, OR * Archorage, AK * Morgantown, WV * Pittsburgh, PA * Sugar Land, TX

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

    Archorage, AK * Morgantown, WV * Pittsburgh, PA * Sugar Land, TX Website: www.netl.doe.gov Customer Service: 1-800-553-7681 R& D FAC T S Geological & Environmental Sciences CONTACTS OFFICE OF RESEARCH AND DEVELOPMENT Kelly Rose Principal Investigator Research Physical Scientist 541-967-5883 kelly.rose@netl.doe.gov Jennifer Bauer Geospatial Researcher 541-918-4507 jennifer.bauer@contr.netl.doe.gov Cynthia Powell Acting Focus Area Lead 541-967-5803 cynthia.powell@netl.doe.gov RESEARCH

  18. 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

  19. 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.

  20. 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.

  1. 1990,"AK","Combined Heat and Power, Commercial Power","All Sources",,4,85.9,80.09

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

    State Code","Producer Type","Fuel Source","Generators","Facilities","Nameplate Capacity (Megawatts)","Summer Capacity (Megawatts)" 1990,"AK","Combined Heat and Power, Commercial Power","All Sources",,4,85.9,80.09 1990,"AK","Combined Heat and Power, Commercial Power","Coal",,3,65.5,61.1 1990,"AK","Combined Heat and Power, Commercial

  2. 2014,"AK","Total Electric Power Industry","All Sources",10,6,59.1,52.9

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

    "Planned Year","State Code","Producer Type","Fuel Source","Generators","Facilities","Nameplate Capacity (Megawatts)","Summer Capacity (Megawatts)" 2014,"AK","Total Electric Power Industry","All Sources",10,6,59.1,52.9 2014,"AK","Total Electric Power Industry","Hydroelectric",2,1,4.8,4.8 2014,"AK","Total Electric Power

  3. 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.

  4. 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.

  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. 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.

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

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

    The Value of Improved Short- Term Wind Power Forecasting B.-M. Hodge and A. Florita National Renewable Energy Laboratory J. Sharp Sharply Focused, LLC M. Margulis and D. Mcreavy Lockheed Martin Technical Report NREL/TP-5D00-63175 February 2015 NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency & Renewable Energy Operated by the Alliance for Sustainable Energy, LLC This report is available at no cost from the National Renewable Energy Laboratory (NREL)

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

    SciTech Connect (OSTI)

    Finley, Cathy

    2014-04-30

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

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. Albany, OR * Anchorage, AK * Morgantown, WV * Pittsburgh, PA * Sugar Land, TX

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

    Performance in High-Pressure, High-Temperature, and Ultra-Deep Drilling Environments Background Oil and natural gas fuel America's economy and account for more than 60 percent of the energy consumed in the United States. Most forecasts indicate that these resources will continue to play a vital role in the U.S. energy portfolio for the next several decades. Increasingly, however, the domestic oil and gas industry must search for hydrocarbons in geologically challenging and operationally complex

  16. 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.

  17. 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.

  18. World oil inventories forecast to grow significantly in 2016 and 2017

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

    World oil inventories forecast to grow significantly in 2016 and 2017 Global oil inventories are expected to continue strong growth over the next two years which should keep oil prices low. In its new monthly forecast, the U.S. Energy Information Administration said world oil stocks are likely to increase by 1.6 million barrels per day this year and by 600,000 barrels per day next year. The higher forecast for inventory builds are the result of both higher global oil production and less oil

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

    Broader source: Energy.gov [DOE]

    This project will address the need for a more accurate approach to forecasting net utility load by taking into consideration the contribution of customer-sited PV energy generation. Tasks within...

  20. Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain

    Broader source: Energy.gov [DOE]

    On April 4, 2014 the U.S. Department of Energy announced a $2.5 million funding opportunity entitled “Wind Forecasting Improvement Project in Complex Terrain.” By researching the physical processes...

  1. Ramping Effect on Forecast Use: Integrated Ramping as a Mitigation Strategy; NREL (National Renewable Energy Laboratory)

    SciTech Connect (OSTI)

    Diakov, Victor; Barrows, Clayton; Brinkman, Gregory; Bloom, Aaron; Denholm, Paul

    2015-06-23

    Power generation ramping between forecasted (net) load set-points shift the generation (MWh) from its scheduled values. The Integrated Ramping is described as a method that mitigates this problem.

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

    Broader source: Energy.gov [DOE]

    As part of this project, new solar forecasting technology will be developed that leverages big data processing, deep machine learning, and cloud modeling integrated in a universal platform with an...

  3. U.S. diesel fuel price forecast to be 1 penny lower this summer...

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

    That's down 12 percent from last summer's record exports. Biodiesel production, which averaged 68,000 barrels a day last summer, is forecast to jump to 82,000 barrels a day this ...

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

    Office of Scientific and Technical Information (OSTI)

    the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. ...

  5. 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.

  6. Examining Information Entropy Approaches as Wind Power Forecasting Performance Metrics: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Orwig, K.; Milligan, M.

    2012-06-01

    In this paper, we examine the parameters associated with the calculation of the Renyi entropy in order to further the understanding of its application to assessing wind power forecasting errors.

  7. U.S. oil production forecast update reflects lower rig count

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

    U.S. oil production forecast update reflects lower rig count Lower oil prices and fewer rigs drilling for crude oil are expected to slow U.S. oil production growth this year and in ...

  8. Analysis and Synthesis of Load Forecasting Data for Renewable Integration Studies: Preprint

    SciTech Connect (OSTI)

    Steckler, N.; Florita, A.; Zhang, J.; Hodge, B. M.

    2013-11-01

    As renewable energy constitutes greater portions of the generation fleet, the importance of modeling uncertainty as part of integration studies also increases. In pursuit of optimal system operations, it is important to capture not only the definitive behavior of power plants, but also the risks associated with systemwide interactions. This research examines the dependence of load forecast errors on external predictor variables such as temperature, day type, and time of day. The analysis was utilized to create statistically relevant instances of sequential load forecasts with only a time series of historic, measured load available. The creation of such load forecasts relies on Bayesian techniques for informing and updating the model, thus providing a basis for networked and adaptive load forecast models in future operational applications.

  9. 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.

  10. 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....

  11. Photometric analysis of overcontact binaries AK Her, HI Dra, V1128 Tau, and V2612 Oph

    SciTech Connect (OSTI)

    al??kan, ?.; zavc?, ?.; Ba?trk, .; ?enavc?, H. V.; K?l?o?lu, T.; Y?lmaz, M.; Selam, S. O.; Latkovi?, O.; Djuraevi?, G.; Cski, A. E-mail: ozavci@science.ankara.edu.tr E-mail: hvsenavci@ankara.edu.tr E-mail: mesutyilmaz@ankara.edu.tr E-mail: olivia@aob.rs E-mail: attila@aob.rs

    2014-12-01

    We analyze new, high quality multicolor light curves of four overcontact binaries: AK Her, HI Dra, V1128 Tau, and V2612 Oph, and determine their orbital and physical parameters using the modeling program of G. Djurasevic and recently published results of radial velocity studies. The achieved precision in absolute masses is between 10% and 20%, and the precision in absolute radii is between 5% and 10%. All four systems are W UMa-type binaries with bright or dark spots indicative of mass and energy transfer or surface activity. We estimate the distances and the ages of the systems using the luminosities computed through our analysis, and perform an O C study for V1128 Tau, which reveals a complex period variation that can be interpreted in terms of mass loss/exchange and either the presence of the third body, or the magnetic activity on one of the components. We conclude that further observations of these systems are needed to deepen our understanding of their nature and variability.

  12. U.S. Department of Energy Workshop Report: Solar Resources and Forecasting

    SciTech Connect (OSTI)

    Stoffel, T.

    2012-06-01

    This report summarizes the technical presentations, outlines the core research recommendations, and augments the information of the Solar Resources and Forecasting Workshop held June 20-22, 2011, in Golden, Colorado. The workshop brought together notable specialists in atmospheric science, solar resource assessment, solar energy conversion, and various stakeholders from industry and academia to review recent developments and provide input for planning future research in solar resource characterization, including measurement, modeling, and forecasting.

  13. A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and

    Office of Scientific and Technical Information (OSTI)

    ARM Observations (Technical Report) | SciTech Connect Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations Citation Details In-Document Search Title: A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations (in English; Croatian) 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

  14. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE (Presentation)

    SciTech Connect (OSTI)

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B.M.

    2014-11-01

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This presentation is an overview of a study that examines the value of improved solar forecasts on Bulk Power System Operations.

  15. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE: Preprint

    SciTech Connect (OSTI)

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B. M.

    2014-09-01

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This study examines the value of improved solar power forecasting for the Independent System Operator-New England system. The results show how 25% solar power penetration reduces net electricity generation costs by 22.9%.

  16. Forecasting Wind and Solar Generation: Improving System Operations, Greening the Grid

    SciTech Connect (OSTI)

    Tian; Tian; Chernyakhovskiy, Ilya

    2016-01-01

    This document discusses improving system operations with forecasting and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.

  17. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect (OSTI)

    Not Available

    1993-12-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

  18. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect (OSTI)

    1995-01-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

  19. Investigating the Correlation Between Wind and Solar Power Forecast Errors in the Western Interconnection: Preprint

    SciTech Connect (OSTI)

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

    2013-05-01

    Wind and solar power generations differ from conventional energy generation because of the variable and uncertain nature of their power output. This variability and uncertainty can have significant impacts on grid operations. Thus, short-term forecasting of wind and solar generation is uniquely helpful for power system operations to balance supply and demand in an electricity system. This paper investigates the correlation between wind and solar power forecasting errors.

  20. Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint

    SciTech Connect (OSTI)

    Florita, A.; Hodge, B. M.; Milligan, M.

    2012-08-01

    The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites and for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.

  1. Wind power forecasting : state-of-the-art 2009.

    SciTech Connect (OSTI)

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

    2009-11-20

    Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and uncertainty in wind power and to more efficiently operate power systems with large wind power penetrations. Moreover, in a market environment, the wind power contribution to the generation portofolio becomes important in determining the daily and hourly prices, as variations in the estimated wind power will influence the clearing prices for both energy and operating reserves. With the increasing penetration of wind power, WPF is quickly becoming an important topic for the electric power industry. System operators (SOs), generating companies (GENCOs), and regulators all support efforts to develop better, more reliable and accurate forecasting models. Wind farm owners and operators also benefit from better wind power prediction to support competitive participation in electricity markets against more stable and dispatchable energy sources. In general, WPF can be used for a number of purposes, such as: generation and transmission maintenance planning, determination of operating reserve requirements, unit commitment, economic dispatch, energy storage optimization (e.g., pumped hydro storage), and energy trading. The objective of this report is to review and analyze state-of-the-art WPF models and their application to power systems operations. We first give a detailed description of the methodologies underlying state-of-the-art WPF models. We then look at how WPF can be integrated into power system operations, with specific focus on the unit commitment problem.

  2. The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations. The Southern Study Area, Final Report

    SciTech Connect (OSTI)

    Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

    2014-04-30

    This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP) -- Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute - 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 - 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 - 3 hours.

  3. The Value of Improved Wind Power Forecasting in the Western Interconnection (Poster), NREL (National Renewable Energy Laboratory)

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

    outcome 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 interest are: 1. Correlated behavior among variables (e.g., changes in dispatch stacks, production costs, or generation by type as a function of forecasting accuracy); 2. The relative reduction in wind curtailment with improved forecasting accuracy; and 3. The value of information (e.g., which subset of

  4. Optimization Based Data Mining Approah for Forecasting Real-Time Energy Demand

    SciTech Connect (OSTI)

    Omitaomu, Olufemi A; Li, Xueping; Zhou, Shengchao

    2015-01-01

    The worldwide concern over environmental degradation, increasing pressure on electric utility companies to meet peak energy demand, and the requirement to avoid purchasing power from the real-time energy market are motivating the utility companies to explore new approaches for forecasting energy demand. Until now, most approaches for forecasting energy demand rely on monthly electrical consumption data. The emergence of smart meters data is changing the data space for electric utility companies, and creating opportunities for utility companies to collect and analyze energy consumption data at a much finer temporal resolution of at least 15-minutes interval. While the data granularity provided by smart meters is important, there are still other challenges in forecasting energy demand; these challenges include lack of information about appliances usage and occupants behavior. Consequently, in this paper, we develop an optimization based data mining approach for forecasting real-time energy demand using smart meters data. The objective of our approach is to develop a robust estimation of energy demand without access to these other building and behavior data. Specifically, the forecasting problem is formulated as a quadratic programming problem and solved using the so-called support vector machine (SVM) technique in an online setting. The parameters of the SVM technique are optimized using simulated annealing approach. The proposed approach is applied to hourly smart meters data for several residential customers over several days.

  5. Climate Leadership Conference (Seattle, WA)

    Broader source: Energy.gov [DOE]

    Sustainability leaders from the private, public, academic, and non-profit communities meet to explore market transformation, carbon management, and building climate resilience on an annual basis.

  6. Baseline data for the residential sector and development of a residential forecasting database

    SciTech Connect (OSTI)

    Hanford, J.W.; Koomey, J.G.; Stewart, L.E.; Lecar, M.E.; Brown, R.E.; Johnson, F.X.; Hwang, R.J.; Price, L.K.

    1994-05-01

    This report describes the Lawrence Berkeley Laboratory (LBL) residential forecasting database. It provides a description of the methodology used to develop the database and describes the data used for heating and cooling end-uses as well as for typical household appliances. This report provides information on end-use unit energy consumption (UEC) values of appliances and equipment historical and current appliance and equipment market shares, appliance and equipment efficiency and sales trends, cost vs efficiency data for appliances and equipment, product lifetime estimates, thermal shell characteristics of buildings, heating and cooling loads, shell measure cost data for new and retrofit buildings, baseline housing stocks, forecasts of housing starts, and forecasts of energy prices and other economic drivers. Model inputs and outputs, as well as all other information in the database, are fully documented with the source and an explanation of how they were derived.

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

    SciTech Connect (OSTI)

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

    2014-08-15

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

  8. Gasoline price forecast to stay below 3 dollar a gallon in 2015

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

    Gasoline price forecast to stay below $3 a gallon in 2015 The national average pump price of gasoline is expected to stay below $3 per gallon during 2015. In its new monthly forecast, the U.S. Energy Information Administration said the retail price for regular gasoline should average $2.33 per gallon this year. The price of gasoline increased in early February after falling for 17 weeks in a row. But gasoline prices will continue to remain low in 2015 when compared with pump prices in recent

  9. A Comparison of Model Short-Range Forecasts and the ARM Microbase Data

    Office of Scientific and Technical Information (OSTI)

    Fourth Quarter ARM Science Metric (Technical Report) | SciTech Connect Model Short-Range Forecasts and the ARM Microbase Data Fourth Quarter ARM Science Metric Citation Details In-Document Search Title: A Comparison of Model Short-Range Forecasts and the ARM Microbase Data Fourth Quarter ARM Science Metric 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

  10. EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy

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

    Improved by 30% | Department of Energy Forecasting Gets a Boost from Watson, Accuracy Improved by 30% EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM Youtube Video | Courtesy of IBM Remember when IBM's super computer Watson defeated Jeopardy! champions Ken Jennings and Brad Rutter? With funding from the U.S. Department of Energy SunShot Initiative, IBM researchers are using Watson-like technology to improve solar

  11. 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.

  12. SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2003 THRU FY2046 VERSION 2003.1 VOLUME 2 [SEC 1 & 2

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2003-12-01

    This report includes data requested on September 10, 2002 and includes radioactive solid waste forecasting updates through December 31, 2002. The FY2003.0 request is the primary forecast for fiscal year FY 2003.

  13. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach

    SciTech Connect (OSTI)

    Brown, C. W.; Hood, Raleigh R.; Long, Wen; Jacobs, John M.; Ramers, D. L.; Wazniak, C.; Wiggert, J. D.; Wood, R.; Xu, J.

    2013-09-01

    The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the concentrations of chlorophyll, nitrate, and dissolved oxygen, and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens, for the purpose of monitoring the Bay's ecosystem. While the physical and biogeochemical variables are forecast mechanistically using the Regional Ocean Modeling System configured for the Chesapeake Bay, the species predictions are generated using a novel mechanistic empirical approach, whereby real-time output from the coupled physical biogeochemical model drives multivariate empirical habitat models of the target species. The predictions, in the form of digital images, are available via the World Wide Web to interested groups to guide recreational, management, and research activities. Though full validation of the integrated forecasts for all species is still a work in progress, we argue that the mechanisticempirical approach can be used to generate a wide variety of short-term ecological forecasts, and that it can be applied in any marine system where sufficient data exist to develop empirical habitat models. This paper provides an overview of this system, its predictions, and the approach taken.

  14. Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Clark, C.; Cline, J.; Benjamin, S.; Wilczak, J.; Marquis, M.; Finley, C.; Stern, A.; Freedman, J.

    2012-09-01

    The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis.

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

    SciTech Connect (OSTI)

    Tutt, T.; Flory, J.

    1995-05-01

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

  16. 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.

  17. A Distributed Modeling System for Short-Term to Seasonal Ensemble Streamflow Forecasting in Snowmelt Dominated Basins

    SciTech Connect (OSTI)

    Wigmosta, Mark S.; Gill, Muhammad K.; Coleman, Andre M.; Prasad, Rajiv; Vail, Lance W.

    2007-12-01

    This paper describes a distributed modeling system for short-term to seasonal water supply forecasts with the ability to utilize remotely-sensed snow cover products and real-time streamflow measurements. Spatial variability in basin characteristics and meteorology is represented using a raster-based computational grid. Canopy interception, snow accumulation and melt, and simplified soil water movement are simulated in each computational unit. The model is run at a daily time step with surface runoff and subsurface flow aggregated at the basin scale. This approach allows the model to be updated with spatial snow cover and measured streamflow using an Ensemble Kalman-based data assimilation strategy that accounts for uncertainty in weather forecasts, model parameters, and observations used for updating. Model inflow forecasts for the Dworshak Reservoir in northern Idaho are compared to observations and to April-July volumetric forecasts issued by the Natural Resource Conservation Service (NRCS) for Water Years 2000 2006. October 1 volumetric forecasts are superior to those issued by the NRCS, while March 1 forecasts are comparable. The ensemble spread brackets the observed April-July volumetric inflows in all years. Short-term (one and three day) forecasts also show excellent agreement with observations.

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

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

    Reports and Publications (EIA)

    1998-01-01

    The blending of oxygenates, such as fuel ethanol and methyl tertiary butyl ether (MTBE), into motor gasoline has increased dramatically in the last few years because of the oxygenated and reformulated gasoline programs. Because of the significant role oxygenates now have in petroleum product markets, the Short-Term Integrated Forecasting System (STIFS) was revised to include supply and demand balances for fuel ethanol and MTBE. The STIFS model is used for producing forecasts in the Short-Term Energy Outlook. A review of the historical data sources and forecasting methodology for oxygenate production, imports, inventories, and demand is presented in this report.

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

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

    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 Administration revised upward its projection for crude oil output in 2013 by 70,000 barrels per day and for next year by 190,000 barrels per day. U.S. oil production is now on track to average 7.5 million barrels per day this year and rise to 8.4 million barrels per day in 2014, according to EIA's latest monthly forecast.

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

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

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

  2. Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.

    SciTech Connect (OSTI)

    Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M.

    2009-10-09

    We present a computational framework for integrating the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.

  3. 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.

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

    SciTech Connect (OSTI)

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

    2010-04-20

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

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

    SciTech Connect (OSTI)

    Eisenberg, Joel F.

    2005-10-31

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

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

  9. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

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

    4 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen MJ Bartholomew S Giangrande March 2016 DISCLAIMER This report was prepared as an account of work sponsored by the U.S. Government. Neither the United States nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or

  10. Validation of Global Weather Forecast and Climate Models Over the North

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

    Slope of Alaska Validation of Global Weather Forecast and Climate Models Over the North Slope of Alaska Xie, Shaocheng Lawrence Livermore National Laboratory Klein, Stephen Lawrence Livermore National Laboratory Boyle, Jim Lawrence Livermore National Laboratory Fiorino, Michael DOE/Lawrence Livermore National Laboratory Hnilo, Justin DOE/Lawrence Livermore National Laboratory Phillips, Thomas PCMDI/LLNL Potter, Gerald Lawrence Livermore National Laboratory Beljaars, Anton ECMWF Category:

  11. Are there Gains from Pooling Real-Time Oil Price Forecasts?

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

    Are there Gains from Pooling Real- Time Oil Price Forecasts? Christiane Baumeister, Bank of Canada Lutz Kilian, University of Michigan Thomas K. Lee, U.S. Energy Information Administration February 12, 2014 Independent Statistics & Analysis www.eia.gov U.S. Energy Information Administration Washington, DC 20585 This paper is released to encourage discussion and critical comment. The analysis and conclusions expressed here are those of the authors and not necessarily those of the U.S. Energy

  12. doe sc arm 16 025 The Radar Wind Profiler for Cloud Forecasting at BNL_formatted

    Office of Scientific and Technical Information (OSTI)

    5 Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report MP Jensen SE Giangrande MJ Bartholomew April 2016 CLIMATE RESEARCH FACILITY DISCLAIMER This report was prepared as an account of work sponsored by the U.S. Government. Neither the United States nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any

  13. Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

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

    Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

    2015-02-14

    Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equationsmore » at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.« less

  14. National forecast for geothermal resource exploration and development with techniques for policy analysis and resource assessment

    SciTech Connect (OSTI)

    Cassel, T.A.V.; Shimamoto, G.T.; Amundsen, C.B.; Blair, P.D.; Finan, W.F.; Smith, M.R.; Edeistein, R.H.

    1982-03-31

    The backgrund, structure and use of modern forecasting methods for estimating the future development of geothermal energy in the United States are documented. The forecasting instrument may be divided into two sequential submodels. The first predicts the timing and quality of future geothermal resource discoveries from an underlying resource base. This resource base represents an expansion of the widely-publicized USGS Circular 790. The second submodel forecasts the rate and extent of utilization of geothermal resource discoveries. It is based on the joint investment behavior of resource developers and potential users as statistically determined from extensive industry interviews. It is concluded that geothermal resource development, especially for electric power development, will play an increasingly significant role in meeting US energy demands over the next 2 decades. Depending on the extent of R and D achievements in related areas of geosciences and technology, expected geothermal power development will reach between 7700 and 17300 Mwe by the year 2000. This represents between 8 and 18% of the expected electric energy demand (GWh) in western and northwestern states.

  15. Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

    SciTech Connect (OSTI)

    Jacobs, John M.; Rhodes, M.; Brown, C. W.; Hood, Raleigh R.; Leight, A.; Long, Wen; Wood, R.

    2014-11-01

    The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.

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

    SciTech Connect (OSTI)

    Graham, Robin Lambert

    2007-01-01

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

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

    SciTech Connect (OSTI)

    McNamara, Laura A.

    2010-08-01

    The title of this paper, Why Models Don't Forecast, has a deceptively simple answer: models don't forecast because people forecast. Yet this statement has significant implications for computational social modeling and simulation in national security decision making. Specifically, it points to the need for robust approaches to the problem of how people and organizations develop, deploy, and use computational modeling and simulation technologies. In the next twenty or so pages, I argue that the challenge of evaluating computational social modeling and simulation technologies extends far beyond verification and validation, and should include the relationship between a simulation technology and the people and organizations using it. This challenge of evaluation is not just one of usability and usefulness for technologies, but extends to the assessment of how new modeling and simulation technologies shape human and organizational judgment. The robust and systematic evaluation of organizational decision making processes, and the role of computational modeling and simulation technologies therein, is a critical problem for the organizations who promote, fund, develop, and seek to use computational social science tools, methods, and techniques in high-consequence decision making.

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

    SciTech Connect (OSTI)

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

    2008-01-24

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

  19. Turbulence-driven coronal heating and improvements to empirical forecasting of the solar wind

    SciTech Connect (OSTI)

    Woolsey, Lauren N.; Cranmer, Steven R.

    2014-06-01

    Forecasting models of the solar wind often rely on simple parameterizations of the magnetic field that ignore the effects of the full magnetic field geometry. In this paper, we present the results of two solar wind prediction models that consider the full magnetic field profile and include the effects of Alfvn waves on coronal heating and wind acceleration. The one-dimensional magnetohydrodynamic code ZEPHYR self-consistently finds solar wind solutions without the need for empirical heating functions. Another one-dimensional code, introduced in this paper (The Efficient Modified-Parker-Equation-Solving Tool, TEMPEST), can act as a smaller, stand-alone code for use in forecasting pipelines. TEMPEST is written in Python and will become a publicly available library of functions that is easy to adapt and expand. We discuss important relations between the magnetic field profile and properties of the solar wind that can be used to independently validate prediction models. ZEPHYR provides the foundation and calibration for TEMPEST, and ultimately we will use these models to predict observations and explain space weather created by the bulk solar wind. We are able to reproduce with both models the general anticorrelation seen in comparisons of observed wind speed at 1 AU and the flux tube expansion factor. There is significantly less spread than comparing the results of the two models than between ZEPHYR and a traditional flux tube expansion relation. We suggest that the new code, TEMPEST, will become a valuable tool in the forecasting of space weather.

  20. Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

    SciTech Connect (OSTI)

    Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

    2015-02-14

    Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equations at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.

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

    SciTech Connect (OSTI)

    Templeton, K.J.

    1996-05-23

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

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

    SciTech Connect (OSTI)

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

    2011-09-13

    The overall goal of this multi-phased research project known as WindSENSE is to develop an observation system deployment strategy that would improve wind power generation forecasts. The objective of the deployment strategy is to produce the maximum benefit for 1- to 6-hour ahead forecasts of wind speed at hub-height ({approx}80 m). In this phase of the project the focus is on the Mid-Columbia Basin region which encompasses the Bonneville Power Administration (BPA) wind generation area shown in Figure 1 that includes Klondike, Stateline, and Hopkins Ridge wind plants. The Ensemble Sensitivity Analysis (ESA) approach uses data generated by a set (ensemble) of perturbed numerical weather prediction (NWP) simulations for a sample time period to statistically diagnose the sensitivity of a specified forecast variable (metric) for a target location to parameters at other locations and prior times referred to as the initial condition (IC) or state variables. The ESA approach was tested on the large-scale atmospheric prediction problem by Ancell and Hakim 2007 and Torn and Hakim 2008. ESA was adapted and applied at the mesoscale by Zack et al. (2010a, b, and c) to the Tehachapi Pass, CA (warm and cools seasons) and Mid-Colombia Basin (warm season only) wind generation regions. In order to apply the ESA approach at the resolution needed at the mesoscale, Zack et al. (2010a, b, and c) developed the Multiple Observation Optimization Algorithm (MOOA). MOOA uses a multivariate regression on a few select IC parameters at one location to determine the incremental improvement of measuring multiple variables (representative of the IC parameters) at various locations. MOOA also determines how much information from each IC parameter contributes to the change in the metric variable at the target location. The Zack et al. studies (2010a, b, and c), demonstrated that forecast sensitivity can be characterized by well-defined, localized patterns for a number of IC variables such as 80-m wind speed and vertical temperature difference. Ideally, the data assimilation scheme used in the experiments would have been based upon an ensemble Kalman filter (EnKF) that was similar to the ESA method used to diagnose the Mid-Colombia Basin sensitivity patterns in the previous studies. However, the use of an EnKF system at high resolution is impractical because of the very high computational cost. Thus, it was decided to use the three-dimensional variational analysis data assimilation that is less computationally intensive and more economically practical for generating operational forecasts. There are two tasks in the current project effort designed to validate the ESA observational system deployment approach in order to move closer to the overall goal: (1) Perform an Observing System Experiment (OSE) using a data denial approach which is the focus of this task and report; and (2) Conduct a set of Observing System Simulation Experiments (OSSE) for the Mid-Colombia basin region. The results of this task are presented in a separate report. The objective of the OSE task involves validating the ESA-MOOA results from the previous sensitivity studies for the Mid-Columbia Basin by testing the impact of existing meteorological tower measurements on the 0- to 6-hour ahead 80-m wind forecasts at the target locations. The testing of the ESA-MOOA method used a combination of data assimilation techniques and data denial experiments to accomplish the task objective.

  3. Validation of a 20-year forecast of US childhood lead poisoning: Updated prospects for 2010

    SciTech Connect (OSTI)

    Jacobs, David E. . E-mail: dejacobs@starpower.net; Nevin, Rick

    2006-11-15

    We forecast childhood lead poisoning and residential lead paint hazard prevalence for 1990-2010, based on a previously unvalidated model that combines national blood lead data with three different housing data sets. The housing data sets, which describe trends in housing demolition, rehabilitation, window replacement, and lead paint, are the American Housing Survey, the Residential Energy Consumption Survey, and the National Lead Paint Survey. Blood lead data are principally from the National Health and Nutrition Examination Survey. New data now make it possible to validate the midpoint of the forecast time period. For the year 2000, the model predicted 23.3 million pre-1960 housing units with lead paint hazards, compared to an empirical HUD estimate of 20.6 million units. Further, the model predicted 498,000 children with elevated blood lead levels (EBL) in 2000, compared to a CDC empirical estimate of 434,000. The model predictions were well within 95% confidence intervals of empirical estimates for both residential lead paint hazard and blood lead outcome measures. The model shows that window replacement explains a large part of the dramatic reduction in lead poisoning that occurred from 1990 to 2000. Here, the construction of the model is described and updated through 2010 using new data. Further declines in childhood lead poisoning are achievable, but the goal of eliminating children's blood lead levels {>=}10 {mu}g/dL by 2010 is unlikely to be achieved without additional action. A window replacement policy will yield multiple benefits of lead poisoning prevention, increased home energy efficiency, decreased power plant emissions, improved housing affordability, and other previously unrecognized benefits. Finally, combining housing and health data could be applied to forecasting other housing-related diseases and injuries.

  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. 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.

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

    SciTech Connect (OSTI)

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

    2013-06-15

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

  7. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

    Office of Scientific and Technical Information (OSTI)

    U.S. DEPARTMENT OF HP IENERGY Office of Science DOE/SC-ARM-15-024 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen MJ Bartholomew S Giangrande March 2016 CLIMATE RESEARCH FACILITY DISCLAIMER This report was prepared as an account of work sponsored by the U.S. Government. Neither the United States nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy,

  8. Energy Savings Forecast of Solid-State Lighting in General Illumination Applications

    SciTech Connect (OSTI)

    none,

    2014-08-29

    With declining production costs and increasing technical capabilities, LED adoption has recently gained momentum in general illumination applications. This is a positive development for our energy infrastructure, as LEDs use significantly less electricity per lumen produced than many traditional lighting technologies. The U.S. Department of Energy’s Energy Savings Forecast of Solid-State Lighting in General Illumination Applications examines the expected market penetration and resulting energy savings of light-emitting diode, or LED, lamps and luminaires from today through 2030.

  9. RACORO Forecasting

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

    7a. Space Heating by Census Region and Climate Zone, Million U.S. Households, 1993 Space Heating Characteristics RSE Column Factor: Total Census Region Climate Zone RSE Row Factors Northeast Midwest South West Fewer than 2,000 CDD and -- More than 2,000 CDD and Few- er than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Few- er than 4,000 HDD 0.5 0.9 1.1 0.8 0.8 1.6 1.3 1.2 1.2 1.1 Total ................................................. 96.6 19.5 23.3 33.5 20.4 8.7 26.5

  10. Forecasting Flu

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

    introduction in 1992 of an American-made truck with a fully factory-installed/war- ranted liquefied petroleum gas (LPG) engine represents another "Ford first" in the alternative fuel arena. Now the company has introduced an LPG- powered F-700, a medium/heavy- duty truck. According to Tom Steckel, Ford's medium-duty marketing man- ager, Ford's latest sales figures already prove the alternative fuel F-700's popularity. With a little more than 10 months of the model year finished, Ford

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

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

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

  12. Crude oil and alternate energy production forecasts for the twenty-first century: The end of the hydrocarbon era

    SciTech Connect (OSTI)

    Edwards, J.D.

    1997-08-01

    Predictions of production rates and ultimate recovery of crude oil are needed for intelligent planning and timely action to ensure the continuous flow of energy required by the world`s increasing population and expanding economies. Crude oil will be able to supply increasing demand until peak world production is reached. The energy gap caused by declining conventional oil production must then be filled by expanding production of coal, heavy oil and oil shales, nuclear and hydroelectric power, and renewable energy sources (solar, wind, and geothermal). Declining oil production forecasts are based on current estimated ultimate recoverable conventional crude oil resources of 329 billion barrels for the United States and close to 3 trillion barrels for the world. Peak world crude oil production is forecast to occur in 2020 at 90 million barrels per day. Conventional crude oil production in the United States is forecast to terminate by about 2090, and world production will be close to exhaustion by 2100.

  13. Solid waste integrated forecast technical (SWIFT) report: FY1997 to FY 2070, Revision 1

    SciTech Connect (OSTI)

    Valero, O.J.; Templeton, K.J.; Morgan, J.

    1997-01-07

    This web site provides an up-to-date report on the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the WM Project; program-level and waste class-specific estimates; background information on waste sources; and comparisons with previous forecasts and with other national data sources. This web site does not include: liquid waste (current or future generation); waste to be managed by the Environmental Restoration (EM-40) contractor (i.e., waste that will be disposed of at the Environmental Restoration Disposal Facility (ERDF)); or waste that has been received by the WM Project to date (i.e., inventory waste). The focus of this web site is on low-level mixed waste (LLMW), and transuranic waste (both non-mixed and mixed) (TRU(M)). Some details on low-level waste and hazardous waste are also provided. Currently, this web site is reporting data th at was requested on 10/14/96 and submitted on 10/25/96. The data represent a life cycle forecast covering all reported activities from FY97 through the end of each program's life cycle. Therefore, these data represent revisions from the previous FY97.0 Data Version, due primarily to revised estimates from PNNL. There is some useful information about the structure of this report in the SWIFT Report Web Site Overview.

  14. Department of Energy award DE-SC0004164 Climate and National Security: Securing Better Forecasts

    SciTech Connect (OSTI)

    Reno Harnish

    2011-08-16

    The Climate and National Security: Securing Better Forecasts symposium was attended by senior policy makers and distinguished scientists. The juxtaposition of these communities was creative and fruitful. They acknowledged they were speaking past each other. Scientists were urged to tell policy makers about even improbable outcomes while articulating clearly the uncertainties around the outcomes. As one policy maker put it, we are accustomed to making these types of decisions. These points were captured clearly in an article that appeared on the New York Times website and can be found with other conference materials most easily on our website, www.scripps.ucsd.edu/cens/. The symposium, generously supported by the NOAA/JIMO, benefitted the public by promoting scientifically informed decision making and by the transmission of objective information regarding climate change and national security.

  15. Solid Waste Integrated Forecast Technical (SWIFT) Report FY2001 to FY2046 Volume 1

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2000-08-31

    This report provides up-to-date life cycle information about the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the WM Project; program-level and waste class-specific estimates; background information on waste sources; and comparisons to previous forecasts and other national data sources. This report does not include: waste to be managed by the Environmental Restoration (EM-40) contractor (i.e., waste that will be disposed of at the Environmental Restoration Disposal Facility (ERDF)); waste that has been received by the WM Project to date (i.e., inventory waste); mixed low-level waste that will be processed and disposed by the River Protection Program; and liquid waste (current or future generation). Although this report currently does not include liquid wastes, they may be added as information becomes available.

  16. Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012

    SciTech Connect (OSTI)

    Pennock, K.

    2012-10-01

    AWS Truepower, LLC (AWST) was retained by the National Renewable Energy Laboratory (NREL) to update wind resource, plant output, and wind power forecasts originally produced by the Eastern Wind Integration and Transmission Study (EWITS). The new data set was to incorporate AWST's updated 200-m wind speed map, additional tall towers that were not included in the original study, and new turbine power curves. Additionally, a primary objective of this new study was to employ new data synthesis techniques developed for the PJM Renewable Integration Study (PRIS) to eliminate diurnal discontinuities resulting from the assimilation of observations into mesoscale model runs. The updated data set covers the same geographic area, 10-minute time resolution, and 2004?2006 study period for the same onshore and offshore (Great Lakes and Atlantic coast) sites as the original EWITS data set.

  17. HONEYWELL - KANSAS CITY PLANT FISCAL YEARS 2009 THRU 2015 SMALL BUSINESS PROGRAM RESULTS & FORECAST

    National Nuclear Security Administration (NNSA)

    HONEYWELL - KANSAS CITY PLANT FISCAL YEARS 2009 THRU 2015 SMALL BUSINESS PROGRAM RESULTS & FORECAST CATEGORY Total Procurement Total SB Small Disad. Bus Woman-Owned SB Hub-Zone SB Veteran-Owned SB Service Disabled Vet. SB FY 2009 Dollars Goal (projected) $183,949,920 $82,690,000 $4,550,000 $8,829,596 $3,370,000 $5,025,000 $460,000 FY 2009 Dollars Accomplished $143,846,731 $68,174,398 $9,247,214 $11,333,905 $4,979,858 $6,713,791 $1,612,136 FY 2009 % Goal 45.0% 2.5% 4.8% 1.8% 2.7% 0.25% FY

  18. Radioactive Waste Characterization Strategies; Comparisons Between AK/PK, Dose to Curie Modeling, Gamma Spectroscopy, and Laboratory Analysis Methods- 12194

    SciTech Connect (OSTI)

    Singledecker, Steven J.; Jones, Scotty W.; Dorries, Alison M.; Henckel, George; Gruetzmacher, Kathleen M. [Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States)

    2012-07-01

    In the coming fiscal years of potentially declining budgets, Department of Energy facilities such as the Los Alamos National Laboratory (LANL) will be looking to reduce the cost of radioactive waste characterization, management, and disposal processes. At the core of this cost reduction process will be choosing the most cost effective, efficient, and accurate methods of radioactive waste characterization. Central to every radioactive waste management program is an effective and accurate waste characterization program. Choosing between methods can determine what is classified as low level radioactive waste (LLRW), transuranic waste (TRU), waste that can be disposed of under an Authorized Release Limit (ARL), industrial waste, and waste that can be disposed of in municipal landfills. The cost benefits of an accurate radioactive waste characterization program cannot be overstated. In addition, inaccurate radioactive waste characterization of radioactive waste can result in the incorrect classification of radioactive waste leading to higher disposal costs, Department of Transportation (DOT) violations, Notice of Violations (NOVs) from Federal and State regulatory agencies, waste rejection from disposal facilities, loss of operational capabilities, and loss of disposal options. Any one of these events could result in the program that mischaracterized the waste losing its ability to perform it primary operational mission. Generators that produce radioactive waste have four characterization strategies at their disposal: - Acceptable Knowledge/Process Knowledge (AK/PK); - Indirect characterization using a software application or other dose to curie methodologies; - Non-Destructive Analysis (NDA) tools such as gamma spectroscopy; - Direct sampling (e.g. grab samples or Surface Contaminated Object smears) and laboratory analytical; Each method has specific advantages and disadvantages. This paper will evaluate each method detailing those advantages and disadvantages including; - Cost benefit analysis (basic materials costs, overall program operations costs, man-hours per sample analyzed, etc.); - Radiation Exposure As Low As Reasonably Achievable (ALARA) program considerations; - Industrial Health and Safety risks; - Overall Analytical Confidence Level. The concepts in this paper apply to any organization with significant radioactive waste characterization and management activities working to within budget constraints and seeking to optimize their waste characterization strategies while reducing analytical costs. (authors)

  19. 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

  20. 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.

  1. XMM-NEWTON MONITORING OF THE CLOSE PRE-MAIN-SEQUENCE BINARY AK SCO. EVIDENCE OF TIDE-DRIVEN FILLING OF THE INNER GAP IN THE CIRCUMBINARY DISK

    SciTech Connect (OSTI)

    Gomez de Castro, Ana Ines; Lopez-Santiago, Javier; Talavera, Antonio; Sytov, A. Yu.; Bisikalo, D.

    2013-03-20

    AK Sco stands out among pre-main-sequence binaries because of its prominent ultraviolet excess, the high eccentricity of its orbit, and the strong tides driven by it. AK Sco consists of two F5-type stars that get as close as 11 R{sub *} at periastron passage. The presence of a dense (n{sub e} {approx} 10{sup 11} cm{sup -3}) extended envelope has been unveiled recently. In this article, we report the results from an XMM-Newton-based monitoring of the system. We show that at periastron, X-ray and UV fluxes are enhanced by a factor of {approx}3 with respect to the apastron values. The X-ray radiation is produced in an optically thin plasma with T {approx} 6.4 Multiplication-Sign 10{sup 6} K and it is found that the N{sub H} column density rises from 0.35 Multiplication-Sign 10{sup 21} cm{sup -2} at periastron to 1.11 Multiplication-Sign 10{sup 21} cm{sup -2} at apastron, in good agreement with previous polarimetric observations. The UV emission detected in the Optical Monitor band seems to be caused by the reprocessing of the high-energy magnetospheric radiation on the circumstellar material. Further evidence of the strong magnetospheric disturbances is provided by the detection of line broadening of 278.7 km s{sup -1} in the N V line with Hubble Space Telescope/Space Telescope Imaging Spectrograph. Numerical simulations of the mass flow from the circumbinary disk to the components have been carried out. They provide a consistent scenario with which to interpret AK Sco observations. We show that the eccentric orbit acts like a gravitational piston. At apastron, matter is dragged efficiently from the inner disk border, filling the inner gap and producing accretion streams that end as ring-like structures around each component of the system. At periastron, the ring-like structures come into contact, leading to angular momentum loss, and thus producing an accretion outburst.

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

    SciTech Connect (OSTI)

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

    2010-01-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the flying brick technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28

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

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

    SciTech Connect (OSTI)

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

    2008-01-07

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

  5. EIS-0346: Salmon Creek Project, WA

    Broader source: Energy.gov [DOE]

    This EIS analyzes BPA's proposal to fund activities that would restore sufficient water flows to Salmon Creek and rehabilitate its streambed as necessary to provide adequate passage for summer steelhead (Oncorhynchus mykiss) and possibly spring chinook (O. tshawytscha).

  6. DOE Climate Change Adaptation Training (Richland, WA)

    Broader source: Energy.gov [DOE]

    This free training is a primer on climate science, identifying climate hazards, conducting vulnerability assessments, leveraging climate change data and tools and understanding the energy-water-food nexus.

  7. 2715-WA_Carpenter's_Shop_Refurbishment.pdf

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

  8. Sumas, WA LNG Imports from Canada

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

    12,530 7,769 9,768 6,016 10,409 3,547 1996-2014 Pipeline Prices 5.55 4.81 4.47 3.87 4.02 5.05 1996...

  9. Navy Mobility Fuels Forecasting System report: Navy fuel production in the year 2000

    SciTech Connect (OSTI)

    Hadder, G.R.; Davis, R.M.

    1991-09-01

    The Refinery Yield Model of the Navy Mobility Fuels Forecasting System has been used to study the feasibility and quality of Navy JP-5 jet fuel and F-76 marine diesel fuel for two scenarios in the year 2000. Both scenarios account for environmental regulations for fuels produced in the US and assume that Eastern Europe, the USSR, and the People`s Republic of China have free market economies. One scenario is based on business-as-usual market conditions for the year 2000. The second scenario is similar to first except that USSR crude oil production is 24 percent lower. During lower oil production in the USSR., there are no adverse effects on Navy fuel availability, but JP-5 is generally a poorer quality fuel relative to business-as-usual in the year 2000. In comparison with 1990, there are two potential problems areas for future Navy fuel quality. The first problem is increased aromaticity of domestically produced Navy fuels. Higher percentages of aromatics could have adverse effects on storage, handling, and combustion characteristics of both JP-5 and F-76. The second, and related, problem is that highly aromatic light cycle oils are blended into F-76 at percentages which promote fuel instability. It is recommended that the Navy continue to monitor the projected trend toward increased aromaticity in JP-5 and F-76 and high percentages of light cycle oils in F-76. These potential problems should be important considerations in research and development for future Navy engines.

  10. Navy Mobility Fuels Forecasting System report: Navy fuel production in the year 2000

    SciTech Connect (OSTI)

    Hadder, G.R.; Davis, R.M.

    1991-09-01

    The Refinery Yield Model of the Navy Mobility Fuels Forecasting System has been used to study the feasibility and quality of Navy JP-5 jet fuel and F-76 marine diesel fuel for two scenarios in the year 2000. Both scenarios account for environmental regulations for fuels produced in the US and assume that Eastern Europe, the USSR, and the People's Republic of China have free market economies. One scenario is based on business-as-usual market conditions for the year 2000. The second scenario is similar to first except that USSR crude oil production is 24 percent lower. During lower oil production in the USSR., there are no adverse effects on Navy fuel availability, but JP-5 is generally a poorer quality fuel relative to business-as-usual in the year 2000. In comparison with 1990, there are two potential problems areas for future Navy fuel quality. The first problem is increased aromaticity of domestically produced Navy fuels. Higher percentages of aromatics could have adverse effects on storage, handling, and combustion characteristics of both JP-5 and F-76. The second, and related, problem is that highly aromatic light cycle oils are blended into F-76 at percentages which promote fuel instability. It is recommended that the Navy continue to monitor the projected trend toward increased aromaticity in JP-5 and F-76 and high percentages of light cycle oils in F-76. These potential problems should be important considerations in research and development for future Navy engines.

  11. Material World: Forecasting Household Appliance Ownership in a Growing Global Economy

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

    Over the past years the Lawrence Berkeley National Laboratory (LBNL) has developed an econometric model that predicts appliance ownership at the household level based on macroeconomic variables such as household income (corrected for purchase power parity), electrification, urbanization and climate variables. Hundreds of data points from around the world were collected in order to understand trends in acquisition of new appliances by households, especially in developing countries. The appliances covered by this model are refrigerators, lighting fixtures, air conditioners, washing machines and televisions. The approach followed allows the modeler to construct a bottom-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residential sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time. This serves two important functions with regard to evaluation of the impact of energy efficiency policies. First, it provides insight into which end uses will be responsible for the largest share of demand growth, and therefore should be policy priorities. Second, it provides a characterization of the rate at which policies affecting new equipment penetrate the appliance stock. Over the past 3 years, this method has been used to support the development of energy demand forecasts at the country, region or global level.

  12. Demand forecasting and revenue requirements, with implications for consideration in British Columbia

    SciTech Connect (OSTI)

    Acton, J.P.

    1983-05-01

    This paper was filed as an exhibit on behalf of The Consumers' Association of Canada (B.C. Branch), The Federated Anti-Poverty Groups of B.C., The Sierra Club of Western Canada, and the B.C. Old Age Pensioners' Organization. It was subjected to cross-examination on October 29, 1982, during Phase I of the hearings. The Utilities Commission had designated Phase I for consideration of (1) demand, (2) assets in service, (3) revenue requirements excluding return, and (4) financing and capital requirements. This paper presents a general discussion of the elements of a rate structure and their relationship to the demand for electricity, a systematic review of some 50 empirical studies of the demand for electricity as a function of price and other factors by the three principal classes of customers, and a discussion of the notion of revenue requirements. The paper should be of interest to utility regulators, rate specialists, and forecasters for its review of demand models and to academics concerned with the study of energy demand.

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

    SciTech Connect (OSTI)

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

    2005-06-30

    The purpose of this article is to compare the accuracy of forecasts for natural gas prices as reported by the Energy Information Administration's Short-Term Energy Outlook (STEO) and the futures market for the period from 1998 to 2003. The analysis tabulates the existing data and develops a statistical comparison of the error between STEO and U.S. wellhead natural gas prices and between Henry Hub and U.S. wellhead spot prices. The results indicate that, on average, Henry Hub is a better predictor of natural gas prices with an average error of 0.23 and a standard deviation of 1.22 than STEO with an average error of -0.52 and a standard deviation of 1.36. This analysis suggests that as the futures market continues to report longer forward prices (currently out to five years), it may be of interest to economic modelers to compare the accuracy of their models to the futures market. The authors would especially like to thank Doug Hale of the Energy Information Administration for supporting and reviewing this work.

  14. Combining multi-objective optimization and bayesian model averaging to calibrate forecast ensembles of soil hydraulic models

    SciTech Connect (OSTI)

    Vrugt, Jasper A; Wohling, Thomas

    2008-01-01

    Most studies in vadose zone hydrology use a single conceptual model for predictive inference and analysis. Focusing on the outcome of a single model is prone to statistical bias and underestimation of uncertainty. In this study, we combine multi-objective optimization and Bayesian Model Averaging (BMA) to generate forecast ensembles of soil hydraulic models. To illustrate our method, we use observed tensiometric pressure head data at three different depths in a layered vadose zone of volcanic origin in New Zealand. A set of seven different soil hydraulic models is calibrated using a multi-objective formulation with three different objective functions that each measure the mismatch between observed and predicted soil water pressure head at one specific depth. The Pareto solution space corresponding to these three objectives is estimated with AMALGAM, and used to generate four different model ensembles. These ensembles are post-processed with BMA and used for predictive analysis and uncertainty estimation. Our most important conclusions for the vadose zone under consideration are: (1) the mean BMA forecast exhibits similar predictive capabilities as the best individual performing soil hydraulic model, (2) the size of the BMA uncertainty ranges increase with increasing depth and dryness in the soil profile, (3) the best performing ensemble corresponds to the compromise (or balanced) solution of the three-objective Pareto surface, and (4) the combined multi-objective optimization and BMA framework proposed in this paper is very useful to generate forecast ensembles of soil hydraulic models.

  15. Residential sector end-use forecasting with EPRI-Reeps 2.1: Summary input assumptions and results

    SciTech Connect (OSTI)

    Koomey, J.G.; Brown, R.E.; Richey, R.

    1995-12-01

    This paper describes current and projected future energy use by end-use and fuel for the U.S. residential sector, and assesses which end-uses are growing most rapidly over time. The inputs to this forecast are based on a multi-year data compilation effort funded by the U.S. Department of Energy. We use the Electric Power Research Institute`s (EPRI`s) REEPS model, as reconfigured to reflect the latest end-use technology data. Residential primary energy use is expected to grow 0.3% per year between 1995 and 2010, while electricity demand is projected to grow at about 0.7% per year over this period. The number of households is expected to grow at about 0.8% per year, which implies that the overall primary energy intensity per household of the residential sector is declining, and the electricity intensity per household is remaining roughly constant over the forecast period. These relatively low growth rates are dependent on the assumed growth rate for miscellaneous electricity, which is the single largest contributor to demand growth in many recent forecasts.

  16. The Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE (Presentation), NREL (National Renewable Energy Laboratory)

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

    Improved Solar Forecasts on Bulk Power System Operations in ISO-NE 4 th Solar Integration Workshop Carlo Brancucci Martinez-Anido, Anthony Florita, and Bri-Mathias Hodge Berlin, Germany November 10, 2014 NREL/PR-5000-63082 2 Motivation and Scope * The economic benefits from renewable energy forecasting are largely unquantified in the power community o Current renewable energy penetration levels in the United States are often too low to appreciably quantify the value of improving renewable energy

  17. Technology data characterizing water heating in commercial buildings: Application to end-use forecasting

    SciTech Connect (OSTI)

    Sezgen, O.; Koomey, J.G.

    1995-12-01

    Commercial-sector conservation analyses have traditionally focused on lighting and space conditioning because of their relatively-large shares of electricity and fuel consumption in commercial buildings. In this report we focus on water heating, which is one of the neglected end uses in the commercial sector. The share of the water-heating end use in commercial-sector electricity consumption is 3%, which corresponds to 0.3 quadrillion Btu (quads) of primary energy consumption. Water heating accounts for 15% of commercial-sector fuel use, which corresponds to 1.6 quads of primary energy consumption. Although smaller in absolute size than the savings associated with lighting and space conditioning, the potential cost-effective energy savings from water heaters are large enough in percentage terms to warrant closer attention. In addition, water heating is much more important in particular building types than in the commercial sector as a whole. Fuel consumption for water heating is highest in lodging establishments, hospitals, and restaurants (0.27, 0.22, and 0.19 quads, respectively); water heating`s share of fuel consumption for these building types is 35%, 18% and 32%, respectively. At the Lawrence Berkeley National Laboratory, we have developed and refined a base-year data set characterizing water heating technologies in commercial buildings as well as a modeling framework. We present the data and modeling framework in this report. The present commercial floorstock is characterized in terms of water heating requirements and technology saturations. Cost-efficiency data for water heating technologies are also developed. These data are intended to support models used for forecasting energy use of water heating in the commercial sector.

  18. Residential applliance data, assumptions and methodology for end-use forecasting with EPRI-REEPS 2.1

    SciTech Connect (OSTI)

    Hwang, R.J,; Johnson, F.X.; Brown, R.E.; Hanford, J.W.; Kommey, J.G.

    1994-05-01

    This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the US residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute. In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70% of electricity consumption and 30% of natural gas consumption in the US residential sector. Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific technologies within those end-uses, developing cost data for the various technologies, and specifying decision models to forecast future purchase decisions by households. Our implementation of the REEPS 2.1 modeling framework draws on the extensive technology, cost and market data assembled by LBL for the purpose of analyzing federal energy conservation standards. The resulting residential appliance forecasting model offers a flexible and accurate tool for analyzing the effect of policies at the national level.

  19. ON THE IMPACT OF SUPER RESOLUTION WSR-88D DOPPLER RADAR DATA ASSIMILATION ON HIGH RESOLUTION NUMERICAL MODEL FORECASTS

    SciTech Connect (OSTI)

    Chiswell, S

    2009-01-11

    Assimilation of radar velocity and precipitation fields into high-resolution model simulations can improve precipitation forecasts with decreased 'spin-up' time and improve short-term simulation of boundary layer winds (Benjamin, 2004 & 2007; Xiao, 2008) which is critical to improving plume transport forecasts. Accurate description of wind and turbulence fields is essential to useful atmospheric transport and dispersion results, and any improvement in the accuracy of these fields will make consequence assessment more valuable during both routine operation as well as potential emergency situations. During 2008, the United States National Weather Service (NWS) radars implemented a significant upgrade which increased the real-time level II data resolution to 8 times their previous 'legacy' resolution, from 1 km range gate and 1.0 degree azimuthal resolution to 'super resolution' 250 m range gate and 0.5 degree azimuthal resolution (Fig 1). These radar observations provide reflectivity, velocity and returned power spectra measurements at a range of up to 300 km (460 km for reflectivity) at a frequency of 4-5 minutes and yield up to 13.5 million point observations per level in super-resolution mode. The migration of National Weather Service (NWS) WSR-88D radars to super resolution is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current operational mesoscale model domains utilize grid spacing several times larger than the legacy data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of super resolution reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution is investigated here to determine the impact of the improved data resolution on model predictions.

  20. 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.

  1. Standardized Software for Wind Load Forecast Error Analyses and Predictions Based on Wavelet-ARIMA Models - Applications at Multiple Geographically Distributed Wind Farms

    SciTech Connect (OSTI)

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

    2013-03-19

    Given the multi-scale variability and uncertainty of wind generation and forecast errors, it is a natural choice to use time-frequency representation (TFR) as a view of the corresponding time series represented over both time and frequency. Here we use wavelet transform (WT) to expand the signal in terms of wavelet functions which are localized in both time and frequency. Each WT component is more stationary and has consistent auto-correlation pattern. We combined wavelet analyses with time series forecast approaches such as ARIMA, and tested the approach at three different wind farms located far away from each other. The prediction capability is satisfactory -- the day-ahead prediction of errors match the original error values very well, including the patterns. The observations are well located within the predictive intervals. Integrating our wavelet-ARIMA (stochastic) model with the weather forecast model (deterministic) will improve our ability significantly to predict wind power generation and reduce predictive uncertainty.

  2. SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2005 THRU FY2035 2005.0 VOLUME 2

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2005-08-17

    This report provides up-to-date life cycle information about the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: (1) an overview of Hanford-wide solid waste to be managed by the WM Project; (2) multi-level and waste class-specific estimates; (3) background information on waste sources; and (4) comparisons to previous forecasts and other national data sources. The focus of this report is low-level waste (LLW), mixed low-level waste (MLLW), and transuranic waste, both non-mixed and mixed (TRU(M)). Some details on hazardous waste are also provided, however, this information is not considered comprehensive. This report includes data requested in December, 2004 with updates through March 31,2005. The data represent a life cycle forecast covering all reported activities from FY2005 through the end of each program's life cycle and are an update of the previous FY2004.1 data version.

  3. Seismic energy data analysis of Merapi volcano to test the eruption time prediction using materials failure forecast method (FFM)

    SciTech Connect (OSTI)

    Anggraeni, Novia Antika

    2015-04-24

    The test of eruption time prediction is an effort to prepare volcanic disaster mitigation, especially in the volcano’s inhabited slope area, such as Merapi Volcano. The test can be conducted by observing the increase of volcanic activity, such as seismicity degree, deformation and SO2 gas emission. One of methods that can be used to predict the time of eruption is Materials Failure Forecast Method (FFM). Materials Failure Forecast Method (FFM) is a predictive method to determine the time of volcanic eruption which was introduced by Voight (1988). This method requires an increase in the rate of change, or acceleration of the observed volcanic activity parameters. The parameter used in this study is the seismic energy value of Merapi Volcano from 1990 – 2012. The data was plotted in form of graphs of seismic energy rate inverse versus time with FFM graphical technique approach uses simple linear regression. The data quality control used to increase the time precision employs the data correlation coefficient value of the seismic energy rate inverse versus time. From the results of graph analysis, the precision of prediction time toward the real time of eruption vary between −2.86 up to 5.49 days.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

    Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.

  5. Effects of the Financial Crisis on Photovoltaics: An Analysis of Changes in Market Forecasts from 2008 to 2009

    SciTech Connect (OSTI)

    Bartlett, J. E.; Margolis, R. M.; Jennings, C. E.

    2009-09-01

    To examine how the financial crisis has impacted expectations of photovoltaic production, demand and pricing over the next several years, we surveyed the market forecasts of industry analysts that had issued projections in 2008 and 2009. We find that the financial crisis has had a significant impact on the PV industry, primarily through increasing the cost and reducing the availability of investment into the sector. These effects have been more immediately experienced by PV installations than by production facilities, due to the different types and duration of investments, and thus PV demand has been reduced by a greater proportion than PV production. By reducing demand more than production, the financial crisis has accelerated previously expected PV overcapacity and resulting price declines.

  6. HOW TO DEAL WITH WASTE ACCEPTANCE UNCERTAINTY USING THE WASTE ACCEPTANCE CRITERIA FORECASTING AND ANALYSIS CAPABILITY SYSTEM (WACFACS)

    SciTech Connect (OSTI)

    Redus, K. S.; Hampshire, G. J.; Patterson, J. E.; Perkins, A. B.

    2002-02-25

    The Waste Acceptance Criteria Forecasting and Analysis Capability System (WACFACS) is used to plan for, evaluate, and control the supply of approximately 1.8 million yd3 of low-level radioactive, TSCA, and RCRA hazardous wastes from over 60 environmental restoration projects between FY02 through FY10 to the Oak Ridge Environmental Management Waste Management Facility (EMWMF). WACFACS is a validated decision support tool that propagates uncertainties inherent in site-related contaminant characterization data, disposition volumes during EMWMF operations, and project schedules to quantitatively determine the confidence that risk-based performance standards are met. Trade-offs in schedule, volumes of waste lots, and allowable concentrations of contaminants are performed to optimize project waste disposition, regulatory compliance, and disposal cell management.

  7. Enhancing Cloud Radiative Processes and Radiation Efficiency in the Advanced Research Weather Research and Forecasting (WRF) Model

    SciTech Connect (OSTI)

    Iacono, Michael J.

    2015-03-09

    The objective of this research has been to evaluate and implement enhancements to the computational performance of the RRTMG radiative transfer option in the Advanced Research version of the Weather Research and Forecasting (WRF) model. Efficiency is as essential as accuracy for effective numerical weather prediction, and radiative transfer is a relatively time-consuming component of dynamical models, taking up to 30-50 percent of the total model simulation time. To address this concern, this research has implemented and tested a version of RRTMG that utilizes graphics processing unit (GPU) technology (hereinafter RRTMGPU) to greatly improve its computational performance; thereby permitting either more frequent simulation of radiative effects or other model enhancements. During the early stages of this project the development of RRTMGPU was completed at AER under separate NASA funding to accelerate the code for use in the Goddard Space Flight Center (GSFC) Goddard Earth Observing System GEOS-5 global model. It should be noted that this final report describes results related to the funded portion of the originally proposed work concerning the acceleration of RRTMG with GPUs in WRF. As a k-distribution model, RRTMG is especially well suited to this modification due to its relatively large internal pseudo-spectral (g-point) dimension that, when combined with the horizontal grid vector in the dynamical model, can take great advantage of the GPU capability. Thorough testing under several model configurations has been performed to ensure that RRTMGPU improves WRF model run time while having no significant impact on calculated radiative fluxes and heating rates or on dynamical model fields relative to the RRTMG radiation. The RRTMGPU codes have been provided to NCAR for possible application to the next public release of the WRF forecast model.

  8. 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)

  9. Solid waste integrated forecast technical (SWEFT) report: FY1997 to FY 2070 - Document number changed to HNF-0918 at revision 1 - 1/7/97

    SciTech Connect (OSTI)

    Valero, O.J.

    1996-10-03

    This web site provides an up-to-date report on the radioactive solid waste expected to be managed at Hanford`s Solid Waste (SW) Program from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the SW Program; program- level and waste class-specific estimates; background information on waste sources; and Li comparisons with previous forecasts and with other national data sources. The focus of this web site is on low- level mixed waste (LLMW), and transuranic waste (both non-mixed and mixed) (TRU(M)). Some details on low-level waste and hazardous waste are also provided. Currently, this site is reporting data current as of 9/96. The data represent a life cycle forecast covering all reported activities from FY97 through the end of each program`s life cycle.

  10. F-1 U.S. Energy Information Administration | Annual Energy Outlook...

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

    Central West North Central East North Central Mountain AK WA MT WY ID NV UT CO AZ NM TX OK IA KS MO IL IN KY TN MS AL FL GA SC NC WV PA NJ MD DE NY CT VT ME RI MA NH VA WI MI OH...

  11. Microsoft Word - figure_03.doc

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

    IN OH TN WV VA KY MD PA NY VT NH MA CT ME RI DE DC NC SC GA FL NJ AL MS LA MO AR TX NM OK CO KS UT AZ WY NE IL IA MN WI ND SD ID MT WA OR NV CA HI AK MI Gulf of Mexico Volume

  12. Coal supply/demand, 1980 to 2000. Task 3. Resource applications industrialization system data base. Final review draft. [USA; forecasting 1980 to 2000; sector and regional analysis

    SciTech Connect (OSTI)

    Fournier, W.M.; Hasson, V.

    1980-10-10

    This report is a compilation of data and forecasts resulting from an analysis of the coal market and the factors influencing supply and demand. The analyses performed for the forecasts were made on an end-use-sector basis. The sectors analyzed are electric utility, industry demand for steam coal, industry demand for metallurgical coal, residential/commercial, coal demand for synfuel production, and exports. The purpose is to provide coal production and consumption forecasts that can be used to perform detailed, railroad company-specific coal transportation analyses. To make the data applicable for the subsequent transportation analyses, the forecasts have been made for each end-use sector on a regional basis. The supply regions are: Appalachia, East Interior, West Interior and Gulf, Northern Great Plains, and Mountain. The demand regions are the same as the nine Census Bureau regions. Coal production and consumption in the United States are projected to increase dramatically in the next 20 years due to increasing requirements for energy and the unavailability of other sources of energy to supply a substantial portion of this increase. Coal comprises 85 percent of the US recoverable fossil energy reserves and could be mined to supply the increasing energy demands of the US. The NTPSC study found that the additional traffic demands by 1985 may be met by the railways by the way of improved signalization, shorter block sections, centralized traffic control, and other modernization methods without providing for heavy line capacity works. But by 2000 the incremental traffic on some of the major corridors was projected to increase very significantly and is likely to call for special line capacity works involving heavy investment.

  13. 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.

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

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred

    2008-01-01

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

  15. 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.

  16. Final Report, 2011-2014. Forecasting Carbon Storage as Eastern Forests Age. Joining Experimental and Modeling Approaches at the UMBS AmeriFlux Site

    SciTech Connect (OSTI)

    Curtis, Peter; Bohrer, Gil; Gough, Christopher; Nadelhoffer, Knute

    2015-03-12

    At the University of Michigan Biological Station (UMBS) AmeriFlux sites (US-UMB and US-UMd), long-term C cycling measurements and a novel ecosystem-scale experiment are revealing physical, biological, and ecological mechanisms driving long-term trajectories of C cycling, providing new data for improving modeling forecasts of C storage in eastern forests. Our findings provide support for previously untested hypotheses that stand-level structural and biological properties constrain long-term trajectories of C storage, and that remotely sensed canopy structural parameters can substantially improve model forecasts of forest C storage. Through the Forest Accelerated Succession ExperimenT (FASET), we are directly testing the hypothesis that forest C storage will increase due to increasing structural and biological complexity of the emerging tree communities. Support from this project, 2011-2014, enabled us to incorporate novel physical and ecological mechanisms into ecological, meteorological, and hydrological models to improve forecasts of future forest C storage in response to disturbance, succession, and current and long-term climate variation

  17. 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.

  18. Summary of available waste forecast data for the Environmental Restoration Program at the Oak Ridge National Laboratory, Oak Ridge, Tennessee

    SciTech Connect (OSTI)

    Not Available

    1994-08-01

    This report identifies patterns of Oak Ridge National Laboratory (ORNL) Environmental Restoration (ER) waste generation that are predicted by the current ER Waste Generation Forecast data base. It compares the waste volumes to be generated with the waste management capabilities of current and proposed treatment, storage, or disposal (TSD) facilities. The scope of this report is limited to wastes generated during activities funded by the Office of the Deputy Assistant Secretary for Environmental Restoration (EM-40) and excludes wastes from the decontamination and decommissioning of facilities. Significant quantities of these wastes are expected to be generated during ER activities. This report has been developed as a management tool supporting communication and coordination of waste management activities at ORNL. It summarizes the available data for waste that will be generated as a result of remediation activities under the direction of the U.S. Department of Energy Oak Ridge Operations Office and identifies areas requiring continued waste management planning and coordination. Based on the available data, it is evident that most remedial action wastes leaving the area of contamination can be managed adequately with existing and planned ORR waste management facilities if attention is given to waste generation scheduling and the physical limitations of particular TSD facilities. Limited use of off-site commercial TSD facilities is anticipated, provided the affected waste streams can be shown to satisfy the requirements of the performance objective for certification of non-radioactive hazardous waste and the waste acceptance criteria of the off-site facilities. Ongoing waste characterization will be required to determine the most appropriate TSD facility for each waste stream.

  19. Albany, OR * Anchorage, AK * Morgantown...

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

    gained from RCSP large-scale field projects- particularly from the Southeast Regional Carbon Sequestration Partnership (SECARB) to address knowledge gaps in the design and...

  20. Albany, OR * Anchorage, AK * Morgantown...

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

    Enhanced Simulation Tools to Improve Predictions and Performance of Geologic Storage: Coupled Modeling of Fault Poromechanics, and High-Resolution Simulation of CO2 Migration and...

  1. Albany, OR * Anchorage, AK * Morgantown...

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

    Complexity and Choice of Model Approaches for Practical Simulations of CO2 Injection, Migration, Leakage, and Long-term Fate Introduction The overall goal of the Department of...

  2. Albany, OR * Anchorage, AK * Morgantown...

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

    Verification, Accounting (MVA) and Assessment, (3) CO 2 Use and Re-Use, (4) Regional Carbon Sequestration Partnerships (RCSP), and (5) Focus Area for Sequestration Science....

  3. Albany, OR * Anchorage, AK * Morgantown...

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

    Verification, Accounting (MVA) and Assessment, (3) CO2 Use and Re-Use, (4) Regional Carbon Sequestration Partnerships (RCSP), and (5) Focus Area for Sequestration Science....

  4. Albany, OR * Anchorage, AK * Morgantown...

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

    Simplified Predictive Models for CO2 Sequestration Performance Assessment Background The overall goal of the Department of Energy's (DOE) Carbon Storage Program is to develop and...

  5. Albany, OR * Anchorage, AK * Morgantown...

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

    routes responsible for the observed catalytic effects. Such efforts will allow for the optimization of plasma systems so that they may be incorporated into a broad range of...

  6. Albany, OR * Anchorage, AK * Morgantown...

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

    Assessing Reservoir Depositional Environments to Develop and Quantify Improvements in CO2 Storage Efficiency: A Reservoir Simulation Approach Background The overall goal of the...

  7. Albany, OR * Anchorage, AK * Morgantown...

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

    An Advanced Joint Inversion System for CO2 Storage Modeling with Large Date Sets for Characterization and Real- Time Monitoring - Enhancing Storage Performance and Reducing Failure...

  8. Albany, OR * Anchorage, AK * Morgantown...

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

    Reactive Transport Models with Geomechanics to Mitigate Risks of CO2 Utilization and Storage Background The overall goal of the Department of Energy's (DOE) Carbon Storage Program...

  9. Albany, OR * Anchorage, AK * Morgantown...

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

    Geomechanical Impacts of Shale Gas Activities Background During hydraulic fracturing of ... the likelihood of seismic events due to water disposal with shale gas is more prevalent. ...

  10. Albany, OR * Fairbanks, AK * Morgantown...

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

    run at the Eastman Chemical Company's Kingsport, TN, site; at Tampa Electric Company's Polk Power Station in Lakeland, FL; and at the Wabash River Power Station in Terre Haute,...

  11. WDR-PK-AK-018

    SciTech Connect (OSTI)

    Hollister, R

    2009-08-26

    Method - CES SOP-HW-P556 'Field and Bulk Gamma Analysis'. Detector - High-purity germanium, 40% relative efficiency. Calibration - The detector was calibrated on February 8, 2006 using a NIST-traceable sealed source, and the calibration was verified using an independent sealed source. Count Time and Geometry - The sample was counted for 20 minutes at 72 inches from the detector. A lead collimator was used to limit the field-of-view to the region of the sample. The drum was rotated 180 degrees halfway through the count time. Date and Location of Scans - June 1,2006 in Building 235 Room 1136. Spectral Analysis Spectra were analyzed with ORTEC GammaVision software. Matrix and geometry corrections were calculated using OR TEC Isotopic software. A background spectrum was measured at the counting location. No man-made radioactivity was observed in the background. Results were determined from the sample spectra without background subtraction. Minimum detectable activities were calculated by the Nureg 4.16 method. Results - Detected Pu-238, Pu-239, Am-241 and Am-243.

  12. Albany, OR * Anchorage, AK * Morgantown...

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

    educational topics include simulation and risk assessment; monitoring, verification, and accounting (MVA); geology-related analytical tools; site characterization, methods to...

  13. Albany, OR * Anchorage, AK * Morgantown...

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

    receive more than 8.4 million in funding to develop regional carbon storage technology training centers in the United States. The majority of this funding is provided by the...

  14. Albany, OR * Anchorage, AK * Morgantown...

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

    between formations through a pathway along the cementearth interface or within the well cement (Figure 1). This three-year project will explore the development of a low-cost...

  15. Albany, OR * Anchorage, AK * Morgantown...

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

    are an important target for studies seeking to positively affect both the efficiency and environmental impact of U.S. energy production. The diversity of available sources for...

  16. The use of real-time off-site observations as a methodology for increasing forecast skill in prediction of large wind power ramps one or more hours ahead of their impact on a wind plant.

    SciTech Connect (OSTI)

    Martin Wilde, Principal Investigator

    2012-12-31

    ABSTRACT Application of Real-Time Offsite Measurements in Improved Short-Term Wind Ramp Prediction Skill Improved forecasting performance immediately preceding wind ramp events is of preeminent concern to most wind energy companies, system operators, and balancing authorities. The value of near real-time hub height-level wind data and more general meteorological measurements to short-term wind power forecasting is well understood. For some sites, access to onsite measured wind data - even historical - can reduce forecast error in the short-range to medium-range horizons by as much as 50%. Unfortunately, valuable free-stream wind measurements at tall tower are not typically available at most wind plants, thereby forcing wind forecasters to rely upon wind measurements below hub height and/or turbine nacelle anemometry. Free-stream measurements can be appropriately scaled to hub-height levels, using existing empirically-derived relationships that account for surface roughness and turbulence. But there is large uncertainty in these relationships for a given time of day and state of the boundary layer. Alternatively, forecasts can rely entirely on turbine anemometry measurements, though such measurements are themselves subject to wake effects that are not stationary. The void in free-stream hub-height level measurements of wind can be filled by remote sensing (e.g., sodar, lidar, and radar). However, the expense of such equipment may not be sustainable. There is a growing market for traditional anemometry on tall tower networks, maintained by third parties to the forecasting process (i.e., independent of forecasters and the forecast users). This study examines the value of offsite tall-tower data from the WINDataNOW Technology network for short-horizon wind power predictions at a wind farm in northern Montana. The presentation shall describe successful physical and statistical techniques for its application and the practicality of its application in an operational setting. It shall be demonstrated that when used properly, the real-time offsite measurements materially improve wind ramp capture and prediction statistics, when compared to traditional wind forecasting techniques and to a simple persistence model.

  17. Advance Patent Waiver W(A)2011-062

    Broader source: Energy.gov [DOE]

    This is a request by ABENGOA SOLAR INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-08GO18038.

  18. Advance Patent Waiver W(A)2011-056

    Broader source: Energy.gov [DOE]

    This is a request by ABENGOA SOLAR INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-08GO18036.

  19. Advance Patent Waiver W(A)2011-063

    Broader source: Energy.gov [DOE]

    This is a request by ABENGOA SOLAR INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-08GO18156.

  20. Advance Patent Waiver W(A)2008-010

    Broader source: Energy.gov [DOE]

    This is a request by XANTREX TECHNOLOGY, INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-07GO17043

  1. Advance Patent Waiver W(A)2007-021

    Broader source: Energy.gov [DOE]

    This is a request by SUN POWER CORPORATION for a DOE waiver of domestic and foreign patent rights under agreement DE-PS36-06GO96034

  2. Advance Patent Waiver W(A)2010-055

    Broader source: Energy.gov [DOE]

    This is a request by SUN POWER CORPORATIO for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0002066

  3. Advance Patent Waiver W(A)2006-032

    Broader source: Energy.gov [DOE]

    This is a request by HONEYWELL INTERNATIONAL, INC. for a DOE waiver of domestic and foreign patent rights under agreement UNKNOWN

  4. Advance Patent Waiver W(A)2012-003

    Broader source: Energy.gov [DOE]

    This is a request by CREE for a DOE Advance patent waiver of domestic and foreign patent rights under agreement DE-FOA-0000439.

  5. Advance Patent Waiver W(A)2005-031

    Broader source: Energy.gov [DOE]

    This is a request by OSRAM SYLVANIA PRODUCTS, INC for a DOE waiver of domestic and foreign patent rights under agreement DE-FG36-05GO85042.

  6. Advance Patent Waiver W(A)2005-043

    Broader source: Energy.gov [DOE]

    This is a request by GENERAL ELECTRIC COMPANY for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-05NT42451.

  7. Advance Patent Waiver W(A)2011-050

    Broader source: Energy.gov [DOE]

    This is a request by EMERSON ELECTRIC for a DOE waiver of domestic and foreign patent rights under agreement DE-FE0004000.

  8. Advance Patent Waiver W(A)2005-004

    Broader source: Energy.gov [DOE]

    This is a request by ALSTO for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-03NT41986.

  9. Advance Patent Waiver W(A)2012-024

    Broader source: Energy.gov [DOE]

    This is a request by SIEMENS ENERGY, INC. for a DOE Advance patent waiver of domestic and foreign patent rights under agreement DE-EE0005493.

  10. Advance Patent Waiver W(A)2010-061

    Broader source: Energy.gov [DOE]

    This is a request by PALTO ALTO RESEARCH CENTER, INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0002765

  11. Advance Patent Waiver W(A)2010-066

    Broader source: Energy.gov [DOE]

    This is a request by A.O. SMITH CORP. for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0003985

  12. EIS-0325: Schultz-Hanford Area Transmission Line Project, WA

    Broader source: Energy.gov [DOE]

    BPA proposes to construct a new 500-kilovolt (kV) transmission line in central Washington. This project would increase transmission system capacity north of Hanford.

  13. Advance Patent Waiver W(A)2008-015

    Broader source: Energy.gov [DOE]

    This is a request by BP SOLAR LTD. for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-GO17049

  14. Advance Patent Waiver W(A)2011-005

    Broader source: Energy.gov [DOE]

    This is a request by UNITED TECHNOLOGIES RESEARCH CENTER for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0003954.

  15. RAPID/Roadmap/6-WA-b | Open Energy Information

    Open Energy Info (EERE)

    water information; Location of discharge into surface waterbody; State Environmental Policy Act Requirements; Public notice requirements; and Certification of the developer...

  16. RAPID/Roadmap/4-WA-a | Open Energy Information

    Open Energy Info (EERE)

    Use Lease Developers interested in conducting non-drilling exploration activities must consult with the WSDNR and negotiate the terms of a Land Use License. As there is no formal...

  17. Advance Patent Waiver W(A)2008-017

    Office of Energy Efficiency and Renewable Energy (EERE)

    This is a request by UNITED TECHNOLOGIES CORP for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-07GO17030

  18. Advance Patent Waiver W(A)2009-019

    Broader source: Energy.gov [DOE]

    This is a request by DOW CORNING CORPORATION for a DOE waiver of domestic and foreign patent rights under agreement DE-FG36-08GO18068

  19. Advance Patent Waiver W(A)2009-011

    Broader source: Energy.gov [DOE]

    This is a request by BOEING COMPANY for a DOE waiver of domestic and foreign patent rights under agreement DE-FG36-08GO18135

  20. Advance Patent Waiver W(A)2009-032

    Broader source: Energy.gov [DOE]

    This is a request by GENERAL ATOMICS for a DOE waiver of domestic and foreign patent rights under agreement DE-FG36-08GO18145

  1. RAPID/Roadmap/19-WA-f | Open Energy Information

    Open Energy Info (EERE)

    Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Water Well NOI for Replacement or Additional Wells...

  2. Advance Patent Waiver W(A)2009-018

    Broader source: Energy.gov [DOE]

    This is a request by CATERPILLAR, INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-07NT43277

  3. Microsoft Word - WA Parish_MAP_Final.docx

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

    ... or working near Ecologically Significant Stream Segments during pipeline construction. ... If compensatory wetland mitigation becomes necessary as part of any USACE permit, NRG ...

  4. Advance Patent Waiver W(A)2012-027

    Broader source: Energy.gov [DOE]

    This is a request by DAIMIER TRUCKS NORTH AMERICA for a DOE Advance patent waiver of domestic and foreign patent rights under agreement DE-EE0003348.

  5. Advance Patent Waiver W(A)2012-029

    Broader source: Energy.gov [DOE]

    This is a request by ALCOA COMMERICAL WINDOWS, LLC for a DOE Advance patent waiver of domestic and foreign patent rights under agreement DE-EE0004012.

  6. Advance Patent Waiver W(A)2011-039

    Broader source: Energy.gov [DOE]

    This is a request by 3M COMPANY for a DOE waiver of domestic and foreign patent rights under agreement DE-FG36-08GO18134.

  7. Advance Patent Waiver W(A)2008-022

    Broader source: Energy.gov [DOE]

    This is a request by ABENGOA BIOENERGY BIOMASS OF KANSAS, LLC for a DOE waiver of domestic and foreign patent rights under agreement DE-FC3607017028

  8. Advance Patent Waiver W(A)2012-019

    Broader source: Energy.gov [DOE]

    This is a request by GE ENERGY for a DOE Advance patent waiver of domestic and foreign patent rights under agreement DE-FE0007902.

  9. Advance Patent Waiver W(A)2012-018

    Broader source: Energy.gov [DOE]

    This is a request by GE ENERGY for a DOE Advance patent waiver of domestic and foreign patent rights under agreement DE-FE0007859.

  10. Advance Patent Waiver W(A)2011-064

    Broader source: Energy.gov [DOE]

    This is a request by DELPHI AUTOMOTIVE SYSTEMS, LLC for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0005342.

  11. Advance Patent Waiver W(A)2009-048

    Office of Energy Efficiency and Renewable Energy (EERE)

    This is a request by GENERAL ELECTRIC COMPANY for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-08NT0005310

  12. Advance Patent Waiver W(A)2011-026

    Broader source: Energy.gov [DOE]

    This is a request by US SYNTHETIC CORPORATION for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0003633.

  13. Advance Patent Waiver W(A)2007-014

    Broader source: Energy.gov [DOE]

    This is a request by DONALDSON COMPANY for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-06NT42861

  14. Advance Patent Waiver W(A)2010-021

    Broader source: Energy.gov [DOE]

    This is a request by PHILIPS LUMILEDS for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0003249

  15. Advance Patent Waiver W(A)2010-047

    Broader source: Energy.gov [DOE]

    This is a request by APPLIED MATERIALS, INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0003331

  16. Sumas, WA Natural Gas Imports by Pipeline from Canada

    Gasoline and Diesel Fuel Update (EIA)

    332,358 313,922 312,236 333,050 359,343 429,642 1996-2015 Pipeline Prices 4.22 3.96 2.72 3.62 4.32 2.36 1996-2015 Liquefied Natural Gas Volumes 0 5 11 2013-2015 Liquefied Natural Gas Prices -- 8.42 6.22 2013

  17. Advance Patent Waiver W(A)2009-068

    Office of Energy Efficiency and Renewable Energy (EERE)

    This is a request by United Solar Systems Corp. for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-07GO17053

  18. Advance Patent Waiver W(A)2008-027

    Office of Energy Efficiency and Renewable Energy (EERE)

    This is a request by ALCOA, INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-08GO180278

  19. Advance Patent Waiver W(A)2011-059

    Office of Energy Efficiency and Renewable Energy (EERE)

    This is a request by CARLISLE CONSTRUCTION MATERIALS, INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0005435.

  20. Advance Patent Waiver W(A)2010-020

    Office of Energy Efficiency and Renewable Energy (EERE)

    This is a request by HALOTECHNICS, INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-08GO18144

  1. Advance Patent Waiver W(A)2007-012

    Office of Energy Efficiency and Renewable Energy (EERE)

    This is a request by BOEING for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-06GO17052

  2. Advance Patent Waiver W(A)2011-030

    Broader source: Energy.gov [DOE]

    This is a request by EATON CORPORATION for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0003911.

  3. Advance Patent Waiver W(A)2013-027

    Broader source: Energy.gov [DOE]

    This is a request by ELECTRICORE INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0005968

  4. Advance Patent Waiver W(A)2012-025

    Broader source: Energy.gov [DOE]

    This is a request by EATON CORPORATION for a DOE Advance patent waiver of domestic and foreign patent rights under agreement DE-OE0000592.

  5. Advance Patent Waiver W(A)2012-032

    Broader source: Energy.gov [DOE]

    This is a request by EATON CORPORATION for a DOE Advance patent waiver of domestic and foreign patent rights under agreement DE-EE0005665.

  6. Advance Patent Waiver W(A)2009-051

    Broader source: Energy.gov [DOE]

    This is a request by CATERPILLAR, INC. for a DOE waiver of domestic and foreign patent rights under agreement De-FC26-02AL67974

  7. Advance Patent Waiver W(A)2011-065

    Broader source: Energy.gov [DOE]

    This is a request by OWENS CORNING for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0005338.

  8. Advance Patent Waiver W(A)2009-007

    Broader source: Energy.gov [DOE]

    This is a request by UNITED TECHNOLOGIES CORP for a DOE waiver of domestic and foreign patent rights under agreement DE-AC02-05CH11231

  9. Advance Patent Waiver W(A)2011-038

    Broader source: Energy.gov [DOE]

    This is a request by A123 SYSTEMS, INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0001187.

  10. Advance Patent Waiver W(A)2008-035

    Broader source: Energy.gov [DOE]

    This is a request by POET RESEARCH, INC. for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-08GO88033

  11. Advance Patent Waiver W(A)2012-020

    Broader source: Energy.gov [DOE]

    This is a request by CLIPPER WINDPOWER LLC for a DOE Advance patent waiver of domestic and foreign patent rights under agreement DE-EE0005141.

  12. Advance Patent Waiver W(A)2010-034

    Office of Energy Efficiency and Renewable Energy (EERE)

    This is a request by LUMINATION, LLC for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0003232

  13. Advance Patent Waiver W(A)2005-061

    Broader source: Energy.gov [DOE]

    This is a request by CATERPILLAR for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-05NT42412.

  14. Advance Patent Waiver W(A)2005-052

    Broader source: Energy.gov [DOE]

    This is a request by CATERPILLAR, INC for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-05NT42423.

  15. Advance Patent Waiver W(A)2006-019

    Broader source: Energy.gov [DOE]

    This is a request by NALCO CHEMICAL CORPORATION for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-06FT42721

  16. Advance Patent Waiver W(A)2008-014

    Broader source: Energy.gov [DOE]

    This is a request by GENERAL MOTORS CORP for a DOE waiver of domestic and foreign patent rights under agreement DE-FG36-07GO17018

  17. Advance Patent Waiver W(A)2006-021

    Broader source: Energy.gov [DOE]

    This is a request by UTC FUEL CELLS, LLC for a DOE waiver of domestic and foreign patent rights under agreement DE-FG36-06GO86042

  18. Advance Patent Waiver W(A)2010-028

    Broader source: Energy.gov [DOE]

    This is a request by ARKEMA for a DOE waiver of domestic and foreign patent rights under agreement DE-PS36-08GO98009

  19. Advance Patent Waiver W(A)2010-049

    Broader source: Energy.gov [DOE]

    This is a request by PRAXAIR, INC for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-07NT43088

  20. Advance Patent Waiver W(A)2005-040

    Broader source: Energy.gov [DOE]

    This is a request by CORNING INCORPORATED for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-05NT42461.

  1. Advance Patent Waiver W(A)2010-024

    Broader source: Energy.gov [DOE]

    This is a request by EASTMAN CHEMICAL COMPANY for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-05NT42469

  2. Advance Patent Waiver W(A)2011-049

    Broader source: Energy.gov [DOE]

    This is a request by DOW CHEMICAL COMPANY for a DOE waiver of domestic and foreign patent rights under agreement DE-EE0003916.

  3. Advance Patent Waiver W(A)2012-016

    Broader source: Energy.gov [DOE]

    This is a request by LINDE, INC. for a DOE Advance patent waiver of domestic and foreign patent rights under agreement DE-FE0007453.

  4. EA-1949: Admiralty Inlet Pilot Tidal Project, Puget Sound, WA

    Broader source: Energy.gov [DOE]

    This EA analyzes the potential environmental effects of a proposal by the Public Utility District No. 1 of Snohomish County, Washington to construct and operate the Admiralty Inlet Tidal Project. The proposed 680-kilowatt project would be located on the east side of Admiralty Inlet in Puget Sound, Washington, about 1 kilometer west of Whidbey Island, entirely within Island County, Washington. The Federal Energy Regulatory Commission (FERC) is the lead agency. The DOE NEPA process for this project has been canceled.

  5. RAPID/Roadmap/14-WA-e | Open Energy Information

    Open Energy Info (EERE)

    wastewater pollutants to land must apply for a State Wastewater Discharge Permit. Industrial facilities that discharge wastewater to privately or publicly owned wastewater...

  6. Advance Patent Waiver W(A)2012-015

    Broader source: Energy.gov [DOE]

    This is a request by GENERAL ELECTRIC GLOBAL REARCH for a DOE Advance patent waiver of domestic and foreign patent rights under agreement DE-FE0005859.

  7. Advance Patent Waiver W(A)2005-048

    Broader source: Energy.gov [DOE]

    This is a request by IBM BLUEGENE/P DESIGN, PHASE III for a DOE waiver of domestic and foreign patent rights under agreement W-7405-ENG-48.

  8. Advance Patent Waiver W(A)2009-028

    Broader source: Energy.gov [DOE]

    This is a request by ARKEMA for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-08NT01582

  9. Advance Patent Waiver W(A)2005-053

    Broader source: Energy.gov [DOE]

    This is a request by ALLEGHENY TECHNLOGIES WAH CHANG DIVISION for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-05NT42513.

  10. Advance Patent Waiver W(A)2005-062

    Broader source: Energy.gov [DOE]

    This is a request by UNITED TECHNOLOGIES CORPORATION for a DOE waiver of domestic and foreign patent rights under agreement DE-FC26-05NT42626.

  11. Advance Patent Waiver W(A)2009-061

    Broader source: Energy.gov [DOE]

    This is a request by PPG INDUSTRIES for a DOE waiver of domestic and foreign patent rights under agreement DE-NT0003894

  12. Advance Patent Waiver W(A)2009-064

    Broader source: Energy.gov [DOE]

    This is a request by ROLLS ROYCE FUEL SYSTEMS for a DOE waiver of domestic and foreign patent rights under agreement DE-FE0000303

  13. Advance Patent Waiver W(A)2009-054

    Broader source: Energy.gov [DOE]

    This is a request by UNITED TECHNOLOGIES RESEARCH for a DOE waiver of domestic and foreign patent rights under agreement DE-PS36-08GO98010

  14. Advance Patent Waiver W(A)2009-010

    Broader source: Energy.gov [DOE]

    This is a request by SCHLUMBERGER TECHNOLOGY CORP for a DOE waiver of domestic and foreign patent rights under agreement DE-FG36-08GO18184

  15. Advance Patent Waiver W(A)2008-036

    Broader source: Energy.gov [DOE]

    This is a request by LIGNOL INNOVATIONS, LTD. for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-08GO18047

  16. Advance Patent Waiver W(A)2009-044

    Broader source: Energy.gov [DOE]

    This is a request by FORD MOTOR COMPANY for a DOE waiver of domestic and foreign patent rights under agreement DE-FC36-09GO19002

  17. Advance Patent Waiver W(A)2008-046

    Broader source: Energy.gov [DOE]

    This is a request by EATON CORPORATION for a DOE waiver of domestic and foreign patent rights under agreement DE-FG36-08GO18131

  18. Advance Patent Waiver W(A)2010-018

    Broader source: Energy.gov [DOE]

    This is a request by BOEING COMPANY for a DOE waiver of domestic and foreign patent rights under agreement DE-FG36-08GO18055

  19. Advance Patent Waiver W(A)2009-047

    Broader source: Energy.gov [DOE]

    This is a request by US SOLAR HOLDINGS LLP for a DOE waiver of domestic and foreign patent rights under agreement DE-FG36-08GO18155

  20. Advance Patent Waiver W(A)2011-031

    Broader source: Energy.gov [DOE]

    This is a request by PARKER HANNIFIN CORPORATION for a DOE waiver of domestic and foreign patent rights under agreement DE-FE0005508.