National Library of Energy BETA

Sample records for forecasting wa id

  1. 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

  2. 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

  3. 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.

  4. 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

  5. 4-ID beamline layout

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

    Sector 4 beamline layout Overview Sector 4 uses a canted undulator straight section to operate two beamlines The 4-ID-C beamline operates between 500 and 3000 eV while the 4-ID-D...

  6. Badging, Real ID

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

    Office » Badging, Real ID Badging, Real ID Effective Nov. 3, 2014, the Lab will implement requirements of the REAL ID Act. Contact Badge Office (505) 667-6901 Email Badge requirements US citizen employees must present a photo ID and proof of US citizenship. See Security Smart on Proof of United States Citizenship for the Badge Office (pdf). Foreign national guests and employees must have an approved visit and present a valid passport and documentation of US legal status and work authorizations.

  7. ID@Work

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

    ID@Work ID@Work ID@Work is a video feature that introduces DOE-ID employees and the jobs they perform. These videos are created in Windows Media Video (wmv) format and have no scripts are available. 2013, January Morris Hall is the Radiological Controls Manager for the Idaho Operations Office 2 minutes, (18 MB) 2012, December Mark Arenaz, Director of ID's Office of Project Management Support 2 minutes, (14 MB) 2012, January Carol Henning, Safety Team Lead for Quality and Safety Division 2

  8. 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....

  9. 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...

  10. Beamline 29-ID

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

    & Milestones IEX Advisory Committees FDR Beamline Information RSXS ARPES APS Ring Status Current APS Schedule Intermediate Energy X-Rays (29-ID): The Intermediate Energy...

  11. 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...

  12. AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT 1.CNTAT ID CODE PAGE "OF PAGES

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

    CNTAT ID CODE PAGE "OF PAGES 1 11 3 2. AMEN DME NT/MO0D IFICATION NO. 3. EFFECTIVE DATE 4. REOUISITION/PURCHASE REQ, NO. 5. PROJECT NO. (if applicable) 6. SSED Y ODE00037. ADMINISTERED BY (If'other than Item 6) CODE 00603 Office of River Protection Office of River Protection U.S. Department of Energy U.S. Department of Energy Office of River Protection Office of River Protection P.O. Box 450 P.O. Box 450 Richiand WA 99352 MS: H16-60 ____________________________________Richland WA 99352 8

  13. AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT 1.CONTRACT ID CODE PAGE OF PAGES

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

    CONTRACT ID CODE PAGE OF PAGES T 1 1 13 2 AMENDIMENT/MODIFICATION NO 3. EFFECTIVE DATE 4 -REGUISITION/PURCHASE RED. NO 5. PROJECT NO. (If epplicable) 032 04/14/2011 11EM002244 6 ISSUED BY CODE 00603 7 ADMINISTERED BY (Iftherthan temrt6) CODE J00603 Office of River Protection Office of River Protection U.S. Department of Energy U.S. Department of Energy Office of River Protection office of River Protection P.O. Box 450 P.O. Box 450 Richland WA 99352 Richland WA 99352 8 NAME AND ADDRESS OF

  14. AMENDMENT OF SOLICITATIONIMODIFICATION OF CONTRACT 1. CONTRACT ID CODE P AE

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

    OF CONTRACT 1. CONTRACT ID CODE P AE 2. AMEN DMENT/MODIF ICATION NO. 3. EFFECTIVE DATE 4. REQUISITION/PURCHASE RED. NO. 5. PROJECT NO. (If applicable) 073 See Block 16C 12EM002951/12EM003004 6. ISSUED BY CODE 100603 7. ADMINISTERED BY (If other than Item 6) CODE 100603 Office of River Protection Office of River Protection U.S. Department of Energy U.S. Department of Energy Office of River Protection Office of River Protection P.O. Box 450 P.O. Box 450 Richland WA 99352 Richland WA 99352 8. NAME

  15. AMENDMENT OF SOLICITATIONIMODIFICATION OF CONTRACT I CONTRACT ID CODE PAGE OF PAGES

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

    I CONTRACT ID CODE PAGE OF PAGES 1 14 2. AMENDMENT/MODIFICATION NO. 3 EFFECTIVE DATE 4. REQUISITION/PURCHASE RED. NO 5. PRtOJECT NO. (if pplicable) 186 See Block 16CL 6. ISSUED BY CODE j 0603 7. ADMINISTERED BY (If other than Item 6) CODE 00603 office of River Protection Office of River Protection U.S. Department of Energy U.S. Department of Energy office of River Protection office of River Protection P.O. Box 450 P.O. Box 450 Richland WA 99352 MS: H6-60 Richland WA 99352 6. NAME AND ADDRESS OF

  16. 4-ID-D optics

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

    4-ID-D Beamline Optics A schetch of the major optical components for beam line 4-ID-D are shown above. All these components located in the B-station upstream from the D...

  17. Real ID Act in brief

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

    Real Estate Approvals Real Estate Approvals Real Estate Approvals Policy Flash 2011-61, Acquisition Guide Chapter 17.3, Acquisition, Use, and Disposal of Real Estate (attachment)

    Visitors » Badging, Badge Office » Real ID Act in brief Real ID Act in brief Effective Nov. 3, 2014, the Lab will implement requirements of the REAL ID Act. Contact Badge Office (505) 667-6901 Email REAL ID Act in brief REAL ID is a coordinated effort by the states and the Federal Government to improve the

  18. Blind Modal ID

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

    Research Projects » Blind Modal ID Blind separation of high-resolution vibration modes High-resolution video camera measurement of the structural vibration (the top video) could be separated into individual, monotone, vibration modes, which enable high-resolution visualization and analysis of structural dynamics. Contact Yongchao Yang (832) 335-3003 Email David Mascarenas dmascarenas@lanl.gov (505) 665-0881 Original video = Mode 1 - 6.34 Hz + Mode 2 - 17.96 Hz + Mode 3 - 25.89 Hz (higher

  19. Data ID Service

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

    ID Service First DOI for a DOE dataset was minted by OSTI and registered with DataCite on 8/10/2011 from the DOE Atmospheric Radiation Measurement (ARM) Climate Research Facility at Oak Ridge National Laboratory http://dx.doi.org/10.5439/1021460 Disseminate Our Results: "Our success should be measured not when a project is completed or an experiment concluded, but when scientifc and technical information is disseminated. Beyond broad availability of technical reports, e-prints and

  20. T ID CODE I

    National Nuclear Security Administration (NNSA)

    T ID CODE I DE- , I AC52- AMENDMENT OF SOLICITATION/MODIFICATlON OF CONTRACT I. CONTRAC I 06NA25396 I Los Alamos National Security, LLC 4200 West Jernez Road Suite 400 Los Alamos, NM 87544 PAGE 1 OF 1 PAGES 2. AMENDMENTIMODIFICATION NO. A029 U.S. Department of Energy National Nuclear Security Administration Manager, Los Alamos Site Office 528 3sth Street Los Alamos, NM 87544 I 9B. DATED (SEE ITEM 11) 8. NAME AND ADDRESS OF CONTRACTOR (No., street, county, state, ZIP Code) 10A. MODIFICATION OF

  1. DHSIsotopeID

    Energy Science and Technology Software Center (OSTI)

    2007-12-18

    DHSIsotopeID is an application designed to read and analyze radiation measurement files taken by radiation measurement files taken by radiation portal monitors, and in particular, by the advanced spectroscopic portals. It requires that the data files be in the N42 file format, compliant with the interface control documents for DNDO radiation measurement files. It carries out an automated analysis to determine which isotopes are present in the spectra, and then presents the results in graphicalmore » form to the user. It also enables further post-processing and analysis, for example by performing further analysis on selected regions of interest of the spectrum, as designated by the user via the graphical interface.« less

  2. 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....

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. APS Beamline 6-ID-B,C

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

    6-ID-B,C Home Recent Publications Beamline Info Optics Instrumentation Software User Info Beamline 6-ID-B,C Beamline 6-ID-B,C is operated by the Magnetic Materials Group in the...

  9. APS Beamline 6-ID-D

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

    MM-Group Home MMG Advisory Committees 6-ID-D Home Recent Publications Beamline Info Optics Instrumentation Software User Info Beamline 6-ID-D Beamline 6-ID-D is operated by the...

  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. DOE-ID Operations Summary

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

    June 5, 2013 DOE-ID Operations Summary For the Period May 16, through May 30, 2013 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory, managed by DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC - Shannon Brennan, DOE-ID, (208) 526-3993.

  12. DOE-ID Operations Summary

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

    24, 2013 DOE-ID Operations Summary For the Period May 30, 2013 through June 12, 2013 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory, managed by DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC - Shannon Brennan, DOE-ID, (208) 526-3993.

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. DOE-ID Twitter Site

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

    Bradley Bugger doeidbug Bradley Bugger Want to know what's going on at DOE-Idaho? Follow DOE-ID public affairs supervisor Brad Bugger on Twitter at doeidbug. https://twitter.com/#!/doeidbug Editorial Date May 9, 2911 By Brad Bugger

  6. AMENDMENT OF SOUCITATIONIMODIFICATION OF CONTRACT 1. CONTRACT ID CODE PAGE OF PAGES

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

    1. CONTRACT ID CODE PAGE OF PAGES II 11 9 2. AMEN DMENTIMODIFICATION NO. 3. EFFECTIVE DATE 4. REOUISITIONIPURCHASE REQ. NO. 5. PROJECT NO. (If elpicable) 169 See Block 16C 12EM0020631 6. ISSUED BY CODE 00603 7. ADMINISTERED BY (If otherthan Item 6) CODE 100603 Office of River Protection Office of River Protection U.S. Department of Energy U.S. Department of Energy Office of River Protection Office of River Protection P.O. Box 450 P.O. Box 450 Richland WA 99352 MS: H6-60

  7. 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

  8. DOE-ID Operations Summary

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

    07, 2013 DOE-ID Operations Summary For the Period July 8, 2013 through July 28, 2013 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory, managed by DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC -Danielle Miller, (208) 526-5709. Advanced

  9. DOE-ID Operations Summary

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

    6, 2013 DOE-ID Operations Summary For the Period July 29, 2013 through August 12, 2013 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory, managed by DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC -Danielle Miller, (208) 526-5709. Advanced

  10. DOE-ID Operations Summary

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

    8, 2013 DOE-ID Operations Summary For the Period September 30, 2013 through October 31, 2013 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory, managed by DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC -Danielle Miller, (208) 526-5709.

  11. DOE-ID Operations Summary

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

    6, 2014 DOE-ID Operations Summary For the Period November 01, 2013 through November 30, 2013 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory, managed by DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC -Danielle Miller, (208) 526-5709.

  12. DOE-ID Operations Summary

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

    27, 2014 DOE-ID Operations Summary For the Period December 01, 2013 through January 15, 2014 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory, managed by DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC -Danielle Miller, (208) 526-5709.

  13. DOE-ID Operations Summary

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

    3, 2015 Updated on April 28, 2015 DOE-ID Operations Summary For the Period September 30, 2014 through November 1, 2014 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory, managed by DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC -Danielle

  14. DOE-ID Operations Summary

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

    7, 2015 DOE-ID Operations Summary For the Period January 1, 2015 - January 31, 2015 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory Site, managed by the DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC: Danielle Miller, (208) 526-5709.

  15. DOE-ID Operations Summary

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

    6, 2015 DOE-ID Operations Summary For the Period February 1, 2015 - February 28, 2015 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory Site, managed by the DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC: Danielle Miller, (208) 526-5709.

  16. DOE-ID Operations Summary

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

    23, 2015 DOE-ID Operations Summary For the Period March 1, 2015 -March 31, 2015 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory Site, managed by the DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC: Danielle Miller, (208) 526-5709.

  17. DOE-ID Operations Summary

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

    1, 2015 DOE-ID Operations Summary For the Period April 1, 2015 - April 30, 2015 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory Site, managed by the DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information about health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC: Danielle Miller, (208) 526-5709.

  18. DOE-ID Operations Summary

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

    4, 2015 DOE-ID Operations Summary For the Period May 1, 2015 - May 31, 2015 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory Site, managed by the DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC: Danielle Miller, (208) 526-5709. Advanced

  19. DOE-ID Operations Summary

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

    25, 2015 DOE-ID Operations Summary For the Period June 1, 2015 - June 30, 2015 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory Site, managed by the DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC: Danielle Miller, (208) 526-5709. Advanced

  20. DOE-ID Operations Summary

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

    December 2, 2015 DOE-ID Operations Summary For the Period September 1, 2015 - September 30, 2015 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory Site, managed by the DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC: Danielle Miller, (208)

  1. DOE-ID Operations Summary

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

    7, 2015 DOE-ID Operations Summary For the Period August 1, 2015 - August 31, 2015 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory Site, managed by the DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC: Danielle Miller, (208) 526-5709.

  2. DOE-ID Operations Summary

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

    February 11, 2016 DOE-ID Operations Summary For the Period November 1, 2015 - November 30, 2015 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory Site, managed by the DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC: Danielle Miller, (208)

  3. DOE-ID Operations Summary

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

    December 1, 2015 -December 31, 2015 EDITOR'S NOTE: The following is a summary of contractor operations at the Idaho National Laboratory Site, managed by the DOE- Idaho Operations Office. It has been compiled in response to a request from stakeholders for more information on health, safety and environmental incidents at DOE facilities in Idaho. It also includes a brief summary of accomplishments at the Site. POC: Danielle Miller, (208) 526-5709. Idaho Operations Office (DOE-ID) December 17: The

  4. APS Beamline 6-ID-B,C

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

    B,C Home Recent Publications Beamline Info Optics Instrumentation Software User Info Beamline 6-ID-B,C Beamline 6-ID-B,C is operated by the Magnetic Materials Group in the X-ray...

  5. APS Beamline 6-ID-D

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

    D Home Recent Publications Beamline Info Optics Instrumentation Software User Info Beamline 6-ID-D Beamline 6-ID-D is operated by the Magnetic Materials Group in the X-ray Science...

  6. 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...

  7. 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...

  8. 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...

  9. DOE-ID Mission and Vision

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

    ID Mission and Vision You are here: DOE-ID Home > Inside ID > Our Mission and Vision The Idaho Operations Office (DOE-ID)/INL mission is: To develop and deliver cost-effective solutions to both fundamental and advanced challenges in nuclear energy and other energy resources, national security, and environmental management. The Department's expectations of its operations offices and laboratories are: to advance the national, economic and energy security of the United States; to promote

  10. II.CONTRACT ID CODE

    National Nuclear Security Administration (NNSA)

    1 II.CONTRACT ID CODE ~AGE 1 of AMENDMENT OF SOLICITATIONIMODIFICATION OF CONTRACT PAGES AC 5. PROJECT NO. (If applicable) 3. EFFECTNE DATE 2. AMENDMENTfMODIFICA TION NO. 4. REQUISITIONIPURCHASE REQ. NO. See Block 16c. NOPR 7. ADMINISTERED BY (If other than Item 6) CODE 05008 6. ISSUED BY CODE 05008 U.S. Department of Energy National Nuclear Security Administration U.S. Department of Energy National Nuclear Security Administration P.O. Box 2050 Oak Ridge, TN 37831 P.O. Box 2050 Oak Ridge, TN

  11. Department of Energy Idaho - Inside DOE-ID

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

    Inside ID Inside Idaho Operations Office (DOE-ID) DOE-ID Mission and Vision Brief History of the Idaho National Laboratory (INL) DOE-ID Agreement in Principle Organization Chart...

  12. DOEDataID_24X30poster112515

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

    osti.gov/home/doe-data-id-service

  13. 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...

  14. 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...

  15. 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....

  16. 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....

  17. 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...

  18. VA VT CT RI MT WY CO ID UT OR NV CA AZ NM WA TN WV NC AR OK

    Energy Savers [EERE]

    08: Debian Security Advisory V-008: Debian Security Advisory October 23, 2012 - 6:00am Addthis PROBLEM: Debian Security Advisory PLATFORM: Debian GNU/Linux 6.0 ABSTRACT: Debian update for bind9 REFERENCE LINKS: Debian Security Advisory DSA-2560-1 Debian bugtracking system: Bug 690118 ISC Reference Number: AA-00801 Secunia Advisory SA51054 CVE-2012-5166 IMPACT ASSESSMENT: Medium DISCUSSION: was discovered that BIND, a DNS server, hangs while constructing the additional section of a DNS reply,

  19. VA VT CT RI MT WY CO ID UT OR NV CA AZ NM WA TN WV NC AR OK

    Energy Savers [EERE]

    2 1 Smart Grid Demonstration Project Locations NH MA 16 Awards Support Projects in 21 States

  20. VA VT CT RI MT WY CO ID UT OR NV CA AZ NM WA TN WV NC AR OK

    Energy Savers [EERE]

    7 2 1 Energy Storage Demonstration Project Locations NH 16 Awards Support Projects in 9 States MA

  1. VA VT CT RI MT WY CO ID UT OR NV CA AZ NM WA TN WV NC AR OK

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

    2 1 Locations of Smart Grid Demonstration and Large-Scale Energy Storage Projects NH 32 Awards Support Projects in 24 States 6 11 MA

  2. 1. CON'I'AC'r ID CODE PAGE OF PAGES AMENDMENT OF SOLICITATIONIMODIFICATION OF CONTRACT II 11 3

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

    CON'I'AC'r ID CODE PAGE OF PAGES AMENDMENT OF SOLICITATIONIMODIFICATION OF CONTRACT II 11 3 2. AMENDMENT/MODIFICATION NO. 3. EFFECTIVE DATE (M/D.'F) 4. REQUISITION/PURCHASE RE-Q. NO. S. PROJECT1 NO. t7fapplieoble) 27See Block 16C 12EM001839 6. ISUED13Y ODE7. ADMINISTER.ED BY (If uI/wr ius /tem 6) CODE U.S. Department of Energy Office or River Protection P. 0. Box 450, MS 146-60 Richland, WA 99352 1. NAME AND ADDRESS OF CONTRACTOR (No.,stree, county State and Z11' code) 9A, AMENDMEN f

  3. 1. CONTRACT ID CODE PAGE OF PAGES AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT I11 5

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

    Ap5,sval 2700042 1. CONTRACT ID CODE PAGE OF PAGES AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT I11 5 2. AMENDMENT/MOOIFICATION NO. 3. EFFECTIVE DATE 4. REQUISITION/PURCHASE REQ. NO.5 PROJECT NO. (If applicable) A077 See 16C 06-08RL-14383.O1 1 6. ISSUED BY CODE 7. ADMINISTERED BY (If other than Item 6) CODEJ US. Department of Energy Same as item 6. Richland Operations Office DOE Contracting POC: Richard Stimmrrel P. 0. Box 550, MSIN A7-80 (509) 376-2882 Richland, WA 99352 8 NAME AND

  4. 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

  5. Advance Patent Waiver W(A)2005-027

    Broader source: Energy.gov [DOE]

    This is a request by WESTINGHOUSE ELECTRIC CORPORATION for a DOE waiver of domestic and foreign patent rights under agreement DE-FC07-05ID14636.

  6. 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

  7. 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

  8. 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

  9. Origin State>> CA CA ID ID ID IL KY MD MO NM NM NY NY OH SC

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

    MO NM NM NY NY OH SC TN TN TN, WA, CA TN TN TN TN Total Shipments by Route Lawrence Livermore National Laboratory General Atomics Batelle Energy Alliance Idaho National Laboratory Advanced Mixed Waste Treatment Project Argonne National Laboratory Paducah Gaseous Diffusion Plant Aberdeen Proving Grounds National Security Technologies Sandia National Laboratory Los Alamos National Laboratory Brookhaven National Laboratory CH2M Hill B&W West Valley, LLC Portsmouth Gaseous Diffusion Plant

  10. Origin State>> CA CA ID ID ID IL KY MD NM NM NV NY NY OH TN

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

    NM NM NV NY NY OH TN TN TN, WA, CA TN TN TN TN TX Total Shipments by Route Lawrence Livermore National Laboratory General Atomics Advanced Mixed Waste Treatment Project Batelle Energy Alliance Idaho National Laboratory Argonne National Laboratory Paducah Gaseous Diffusion Plant Aberdeen Proving Ground Los Alamos National Laboratory Sandia National Laboratory National Security Technologies Brookhaven National Laboratory West Valley Environmental Services Portsmouth Gaseous Diffusion Plant

  11. Origin State>> CA ID ID ID IL KY MD NM NM NY NY OH SC TN TN

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

    MD NM NM NY NY OH SC 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 Aberdeen Proving Ground Los Alamos National Laboratory Sandia National Laboratory Brookhaven National Laboratory West Valley Environmental Services Portsmouth Gaseous Diffusion Plant Savannah River Site Duratek/Energy Solutions Babcox

  12. Origin State>> CA ID ID ID IL MD NM NM NV NY NY OH SC TN TN

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

    NV NY NY OH SC TN TN TN, WA, CA TN TN TN 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 National Security Technologies Brookhaven National Laboratory West Valley Environmental Services Portsmouth Gaseous Diffusion Plant Savannah River Site Duratek/Energy Solutions Babcox & Wilcox

  13. 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...

  14. 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: ...

  15. Mo Year Report Period: EIA ID NUMBER:

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

    Mo Year Report Period: EIA ID NUMBER: http:www.eia.govsurveyformeia14instructions.pdf Mailing Address: Secure File Transfer option available at: (e.g., PO Box, RR) https:...

  16. 1-ID Home Page | Advanced Photon Source

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

    1-ID Home Infrastructure Techniques Data Analysis Publications X-ray Resources Materials Physics and Engineering Group Useful Links Current APS status ESAF System GUP System X-Ray...

  17. Page 1, About DOE-ID

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

    1 of 11 Previous Page About the U.S. Department of Energy, Idaho Operations Office (DOE-ID) As a new employee of the Department of Energy (DOE), you are entering a Cabinet-Level Executive Branch Agency with a long history of achievement. The Idaho Operations Office (DOE-ID)/INL mission is to develop and deliver cost-effective solutions to both fundamental and advanced challenges in nuclear energy and other energy resources, national security, and environmental management. The Department's

  18. IDS Climate Change and Development Centre Resources | Open Energy...

    Open Energy Info (EERE)

    IDS Climate Change and Development Centre Resources Jump to: navigation, search Tool Summary Name: IDS Climate Change and Development Centre Resources AgencyCompany Organization:...

  19. 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 ...

  20. 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...

  1. 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. ...

  2. 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...

  3. 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.

  4. Id-1 and Id-2 genes and products as markers of epithelial cancer

    DOE Patents [OSTI]

    Desprez, Pierre-Yves; Campisi, Judith

    2008-09-30

    A method for detection and prognosis of breast cancer and other types of cancer. The method comprises detecting expression, if any, for both an Id-1 and an Id-2 genes, or the ratio thereof, of gene products in samples of breast tissue obtained from a patient. When expressed, Id-1 gene is a prognostic indicator that breast cancer cells are invasive and metastatic, whereas Id-2 gene is a prognostic indicator that breast cancer cells are localized and noninvasive in the breast tissue.

  5. Id-1 and Id-2 genes and products as markers of epithelial cancer

    DOE Patents [OSTI]

    Desprez, Pierre-Yves; Campisi, Judith

    2011-10-04

    A method for detection and prognosis of breast cancer and other types of cancer. The method comprises detecting expression, if any, for both an Id-1 and an Id-2 genes, or the ratio thereof, of gene products in samples of breast tissue obtained from a patient. When expressed, Id-1 gene is a prognostic indicator that breast cancer cells are invasive and metastatic, whereas Id-2 gene is a prognostic indicator that breast cancer cells are localized and noninvasive in the breast tissue.

  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. Employee Assistance Self-ID Form | Department of Energy

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

    Employee Assistance Self-ID Form Employee Assistance Self-ID Form Request Emergency Assistance Self-ID Form-HQ PDF icon Employee Assistance Self-ID Form More Documents & Publications DOE HQ Special Needs Assistance in an Emergency DOE Emergency Special Needs Self-Identification Form DOE Emergency Exercise Feedback Form

  12. 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

  13. I.D I VI Figure

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

    ~press - ,~,.--;~ 3.1 ,,~-.::;:.--- ~ ( 3.1 ( ;-; t\ I.D I VI Figure 9-1. Location of the original Cypress Grove Set-Aside and the Stave Island and Georgia Power replacement Areas. Set-Aside 9: Cypress Grove, Stave Island, and Georgia Power

  14. 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

  15. 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

  16. 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

  17. 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

  18. Facility Representative Program Outstanding at ID

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

    June 19, 2007 Facility Representative Program Outstanding at ID Idaho's three DOE Complex-wide Facility Representative of the Year (FROTY) recipients at this year's conference pose for a photo shoot with Elvis. L to R: Dary Newbry 2005 FROTY, Bob Seal 2006 FROTY, Bob Knighten 2004 FROTY Facility representatives (FRs) are the eyes and ears of the federal government at the Idaho National Laboratory. They oversee the people, processes, facilities and systems that ensure safety at INL facilities.

  19. CHANGE IN ACCEPTABLE ID DOCUMENTS FOR JLAB ACCESS:

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

    JLAB ACCESS: The REAL ID Act (Public Law 109-13) now determines which state driver's license can be presented and accepted as a valid ID document for access to Jefferson Lab. The...

  20. Facility Representative Program ID Selects FR of the Year

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

    Facility Representative Program ID Selects FR of the Year John Martin DOE-ID Facility Representative John Martin DOE-ID Facility Representative of the Year. John Martin was selected as DOE-ID's Facility Representative of the Year and the office's nominee for the 2007 DOE Facility Representative of the Year Award. John was selected from an exceptional field of candidates to represent DOE-ID at the Facility Representative Annual Workshop in Las Vegas this May. Each year the Department of Energy

  1. CHANGE IN ACCEPTABLE ID DOCUMENTS FOR JLAB ACCESS:

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

    CHANGE IN ACCEPTABLE ID DOCUMENTS FOR JLAB ACCESS: The REAL ID Act (Public Law 109-13) now determines which state driver's license can be presented and accepted as a valid ID document for access to Jefferson Lab. The following states/US territories have been determined by the U.S. Department of Homeland Security to have failed to comply with the REAL ID Act: American Samoa, Illinois, Minnesota, Missouri, and Washington. As of March 2, 2015, Jefferson Lab will begin using the REAL ID Act

  2. SLAC Dosimeter / ID Request Form A

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

    Feb 2009 (updated 13 May 2010) SLAC-I-760-0A07J-006-R010 1 of 2 SLAC Dosimeter / ID Request Form A (For applicants who have completed SLAC Environment, Safety, and Health Training) Sections 1-5 completed by applicant. Section 1: Contact Information Last name: First name: MI: Male Female Birth year (yyyy): Job title: Contact information/mailing address: City: State: Zip code: Country: Dept/Group: Phone number: Mail stop: Users or non-SLAC employees only: List employer, company, or university :

  3. Airless drying -- Developments since IDS'94

    SciTech Connect (OSTI)

    Stubbing, T.J.

    1999-09-01

    Since its introduction to IDS'94 delegates, significant progress has been made with the development of airless drying technology. The ceramic industry internationally is beginning to benefit from both the energy use and drying time reductions it achieves, while on the basis of further theoretical work carried out since 1993 other industries, including the bioenergy sector, should also soon begin to exploit its advantages. As global warming becomes a reality and oil reserves decline, superheated steam drying and gasification of biomass will contribute to the mitigation of those problems.

  4. RAPID/Roadmap/14-ID-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-ID-d) IDEQ is...

  5. RAPID/Roadmap/3-ID-b | Open Energy Information

    Open Energy Info (EERE)

    Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us State Land Access Overview (3-ID-b) If a project is...

  6. RAPID/Roadmap/14-ID-f | Open Energy Information

    Open Energy Info (EERE)

    Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us 401 NPDES Water Quality Certification (14-ID-f) Idaho...

  7. RAPID/Roadmap/4-ID-a | Open Energy Information

    Open Energy Info (EERE)

    Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us State Exploration Process (4-ID-a) 04IDAStateExploration...

  8. 2011 Annual Planning Summary for Idaho Operations Office (ID...

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

    The ongoing and projected Environmental Assessments and Environmental Impact Statements for 2011 and 2012 within the Idaho Operations Office (ID) (See Environmental Management). ...

  9. RAPID/Roadmap/11-ID-a | Open Energy Information

    Open Energy Info (EERE)

    Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us State Cultural Considerations (11-ID-a) Idaho has a statute that provides state...

  10. RAPID/Roadmap/5-ID-a | Open Energy Information

    Open Energy Info (EERE)

    Geothermal Hydropower Solar Tools Contribute Contact Us Drilling and Well Development (5-ID-a) 05IDADrillingWellDevelopment.pdf Error creating thumbnail: Page number not in...

  11. RAPID/Roadmap/17-ID-a | Open Energy Information

    Open Energy Info (EERE)

    Contact Us Aesthetic Resource Assessment (17-ID-a) 17IDAAestheticResourceAssessment.pdf Error creating thumbnail: Page number not in range. Error creating thumbnail: Page number...

  12. RAPID/Roadmap/9-ID-a | Open Energy Information

    Open Energy Info (EERE)

    Environmental Review Process (9-ID-a) Add overview. 09IDAStateEnvironmentalProcess.pdf Error creating thumbnail: Page number not in range. Error creating thumbnail: Page number...

  13. DOE - Office of Legacy Management -- Lowman Mill Site - ID 01

    Office of Legacy Management (LM)

    Mill Site (ID.01) Designated Name: Alternate Name: Location: Evaluation Year: Site Operations: Site Disposition: Radioactive Materials Handled: Primary Radioactive Materials...

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

    Open Energy Info (EERE)

    Geothermal Hydropower Solar Tools Contribute Contact Us Underground Injection Control Permit (14-ID-c) Rule 40 of the Idaho Department of Water Resources' Drilling for...

  15. Temporary EPA ID Number Request | Open Energy Information

    Open Energy Info (EERE)

    Temporary EPA ID Number RequestLegal Abstract A developer that may "generate hazardous waste only from an episodic event" may instead apply for a temporary hazardous waste...

  16. RAPID/Roadmap/8-ID-e | Open Energy Information

    Open Energy Info (EERE)

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

  17. RAPID/Roadmap/3-ID-e | Open Energy Information

    Open Energy Info (EERE)

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

  18. RAPID/Roadmap/14-ID-b | Open Energy Information

    Open Energy Info (EERE)

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

  19. RAPID/Roadmap/8-ID-a | Open Energy Information

    Open Energy Info (EERE)

    RAPIDRoadmap8-ID-a < RAPID | Roadmap Jump to: navigation, search RAPID Regulatory and Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower...

  20. RAPID/Roadmap/6-ID-b | Open Energy Information

    Open Energy Info (EERE)

    RAPIDRoadmap6-ID-b < RAPID | Roadmap Jump to: navigation, search RAPID Regulatory and Permitting Information Desktop Toolkit BETA About Bulk Transmission Geothermal Hydropower...

  1. RAPID/Roadmap/15-ID-b | Open Energy Information

    Open Energy Info (EERE)

    BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Air Quality Permit - Tier II Operating Permit (15-ID-b) Tier II Operating Permits are...

  2. RAPID/Roadmap/15-ID-a | Open Energy Information

    Open Energy Info (EERE)

    BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Air Quality Permit - Permit to Construct (15-ID-a) The Idaho Department of Environmental...

  3. RAPID/Roadmap/12-ID-a | Open Energy Information

    Open Energy Info (EERE)

    Contact Us State Biological Resource Considerations (12-ID-a) The Idaho Department of Fish & Game preserves wildlife against any direct take, including wild animals, birds, and...

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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:

  9. 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)

  10. 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 ...

  11. 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.

  12. 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:...

  13. 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 ...

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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:...

  20. 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 ...

  1. 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.

  2. Id-1 and Id-2 genes and products as therapeutic targets for treatment of breast cancer and other types of carcinoma

    DOE Patents [OSTI]

    Desprez, Pierre-Yves; Campisi, Judith

    2014-09-30

    A method for treatment and amelioration of breast, cervical, ovarian, endometrial, squamous cells, prostate cancer and melanoma in a patient comprising targeting Id-1 or Id-2 gene expression with a delivery vehicle comprising a product which modulates Id-1 or Id-2 expression.

  3. JLab Registration/International Services - Researcher/Visitor ID

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

    Requirements Researcher/Visitor ID Requirements CHANGE IN ACCEPTABLE ID DOCUMENTS FOR JLAB ACCESS U.S. Citizens must bring a valid Government issued ID card that contains a photo such as a passport or valid driver's license. Non-driver photo identification cards issued by the Department of Motor Vehicles can be used as proof of identification. Lawful Permanent Resident of the United States must bring their Green Card or passport with valid I-551 stamp AND a valid government issued

  4. 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

  5. Beamline 4-ID-C | Advanced Photon Source

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

    C 4-ID-C Home Recent Publications XSD-MM Home MM Advisory Committees FAQs Beamline Info Instrumentation Magnet Materials Internal Useful Links Current APS status ESAF System GUP...

  6. Microsoft Word - DOE-ID-INL-15-070.docx

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

    DOE-ID-INL-15-070 excluded petroleum and natural gas products that pre-exist in the environment such that there would be uncontrolled or unpermitted releases; (4) have the...

  7. RAPID/Roadmap/3-ID-d | Open Energy Information

    Open Energy Info (EERE)

    Toolkit BETA About Bulk Transmission Geothermal Hydropower Solar Tools Contribute Contact Us Land Use Permit (3-ID-d) The Idaho Department of Lands issues Land Use Permits for...

  8. RAPID/Roadmap/6-ID-c | Open Energy Information

    Open Energy Info (EERE)

    Tools Contribute Contact Us Drinking Water Permit (6-ID-c) 06IDCDrinkingWaterPermit.pdf Error creating thumbnail: Page number not in range. Error creating thumbnail: Page number...

  9. RAPID/Roadmap/7-ID-a | Open Energy Information

    Open Energy Info (EERE)

    Contact Us Power Plant Siting Process (7-ID-a) 07IDAPowerPlantSitingConstruction.pdf Error creating thumbnail: Page number not in range. Error creating thumbnail: Page number...

  10. RAPID/Roadmap/13-ID-a | Open Energy Information

    Open Energy Info (EERE)

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

  11. Microsoft Word - DOE-ID-INL-14-034.docx

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

    No.: DOE-ID-INL-14-034 pollutants, contaminants, or CERCLA-excluded petroleum and natural gas products that pre-exist in the environment such that there would be uncontrolled...

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

    Open Energy Info (EERE)

    to 19-ID-a.5 - Is a Change in Point of Diversion, Place of Use, Period of Use, or Nature of Use Needed for an Existing Water Right If the proposed activity will require a...

  13. RAPID/Roadmap/6-ID-a | Open Energy Information

    Open Energy Info (EERE)

    load A load is overlegal if the load is: width over 8'6"; Over 14' tall; Truck and trailer combined are over 75' long; or The load weighs over 80,000 pounds. 6-ID-a.2 - Meet...

  14. RAPID/Roadmap/18-ID-b | Open Energy Information

    Open Energy Info (EERE)

    demonstrate insurance coverage that would protect the community from incurring clean-up costs in the event of the developer's insolvency. 18-ID-b.5 - Facility siting license...

  15. Vermont Hazardous Waste Handler Site ID Form | Open Energy Information

    Open Energy Info (EERE)

    to library Legal Document- Permit ApplicationPermit Application: Vermont Hazardous Waste Handler Site ID FormLegal Abstract This form is used to notify the Vermont Agency of...

  16. RAPID/Roadmap/3-ID-a | Open Energy Information

    Open Energy Info (EERE)

    the IDL becomes involved only if they are notified and the Land Board requests their involvement. 3-ID-a.3 - Consultation (optional) IDL may meet with any other state agency to...

  17. T-642: RSA SecurID update to Customers

    Broader source: Energy.gov [DOE]

    RSA investigation has revealed that the attack resulted in certain information being extracted from RSA's systems. Some of that information is related to RSA's SecurID two-factor authentication products

  18. 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

  19. 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.

  20. NERSC Helps Physicists ID New Molecules With Unique Features

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

    NERSC Helps Physicists ID New Molecules With Unique Features NERSC Helps Physicists ID New Molecules With Unique Features Hollow magnetic cage molecules may have applications in technology, healthcare August 10, 2013 NERSC supercomputing resources helped Virginia Commonwealth University (VCU) researchers determine it may be possible to create large, hollow magnetic cage molecules that could be used in medicine as a drug delivery system to noninvasively treat tumors and in other emerging

  1. Physicists ID Mechanism that Stabilizes Plasma in Tokamaks

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

    Physicists ID Mechanism that Stabilizes Plasma in Tokamaks Physicists ID Mechanism that Stabilizes Plasma in Tokamaks Calculations Run at NERSC Create 3D Simulations of Fusion Plasmas January 4, 2016 Contact: Kathy Kincade, kkincade@lbl.gov, +1 510 495 2124 jardinfusion A cross-section of the virtual plasma showing where the magnetic field lines intersect the plane. The central section has field lines that rotate exactly once. Image: Stephen Jardin A team of physicists led by Stephen Jardin of

  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. 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

  10. 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

  11. 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.

  12. DOE-ID FOIA Electronic Reading Room Documents

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

    Electronic Reading Room Documents Electronic Reading Room Documents The information contained here represents DOE-ID's responses to FOIA requests that have been or are likely to be of broad public interest, as stipulated under the Electronic Freedom of Information Act Amendments of 1996. As required by the Act, documents created after November 1997, which meet the criteria for electronic presentation, will be made available here. Other documents requested under the FOIA will also be made

  13. Poster - DOE Data ID Service | OSTI, US Dept of Energy, Office of

    Office of Scientific and Technical Information (OSTI)

    Scientific and Technical Information ID Service Document Files and References Available Downloads for this Document: application/pdf icon Poster DOE Data ID Service Last updated on Tuesday 22 December

  14. DOI-BLM-ID-T020-2012-0003-CX | Open Energy Information

    Open Energy Info (EERE)

    ID-T020-2012-0003-CX Jump to: navigation, search NEPA Document Collection for: DOI-BLM-ID-T020-2012-0003-CX CX for GeothermalExploration CX for Seismic Survey at ?? Geothermal...

  15. Finding Utility Companies Under a Given Utility ID | OpenEI Community

    Open Energy Info (EERE)

    utility company pages under a given utility id. From the Special Ask page, in the query box enter the following: Category:Utility CompaniesEiaUtilityId::15248 substituting...

  16. EIS-0471: Areva Eagle Rock Enrichment Facility in Bonneville County, ID |

    Energy Savers [EERE]

    Department of Energy 1: Areva Eagle Rock Enrichment Facility in Bonneville County, ID EIS-0471: Areva Eagle Rock Enrichment Facility in Bonneville County, ID May 20, 2011 delete me old download page duplicate

  17. 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

  18. 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. ...

  19. 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 ...

  20. 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...

  1. 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...

  2. Material Safety Data Sheet MSDS ID NO.: 0137SPE012

    Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

    Material Safety Data Sheet MSDS ID NO.: 0137SPE012 Revision date: 05/25/2011 1. CHEMICAL PRODUCT AND COMPANY INFORMATION Product name: Speedway E85 Synonym: Speedway ED75/ED85; E-75; E75; E-85; E85; Ethanol/Gasoline Fuel Blend; Fuel Ethanol ED75/ED85 Chemical Family: Gasoline/Ethanol Formula: Mixture Manufacturer: Speedway LLC P.O. Box 1500 Enon, OH 45501 Other information: 419-421-3070 Emergency telephone number: 877-627-5463 2. COMPOSITION/INFORMATION ON INGREDIENTS E85 is a mixture of ethyl

  3. DOE-ID Procurement Services � the action team

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

    DOE-ID Procurement Services � the action team Passage of the American Recovery and Reinvestment Act of 2009 included billions of dollars in additional funding for energy efficiency improvements to U.S. homes and businesses. By early July, the U.S. Department of Energy was hard pressed to get that funding to the communities who needed it to reduce their power bills. That�s when DOE�s Office of Energy Efficiency asked the department�s Idaho Operations Office for support from DOE-ID�s

  4. IdJOO2 UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

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

    6/2004 13:39 FAX IdJOO2 UNITED STATES ENVIRONMENTAL PROTECTION AGENCY WASHINGTON, D.C. 20460 MAR 26 2004 OFFICE OF AIR AND RADIATION R. Paul Detwiler, Acting Manager Carlsbad Field Office U.S. Department of Energy P.O. Box 3090 Carlsbad, NM 88221-3090 Dear Dr. Detwiler: This letter announces the U.S. Environmental Protection Agency's (EPA's) final decision to approve the Department of Energy's (DOE's) remote handled (RH) transuranic (TRU) Waste Characterization Program Implementation Plan

  5. Microsoft Word - DOE-ID-INL-10-017.doc

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

    DOE-ID-INL-10-017 SECTION A. Project Title: ATR Complex Dial Room. SECTION B. Project Description: The proposed project is to construct and operate a new dial room at the Advanced Test Reactor Complex (ATR Complex) (formerly known as the Test Reactor Area [TRA]) in order to meet the U.S. Department of Energy Office of Nuclear Energy programmatic needs and to provide ongoing critical support at the Idaho National Laboratory (INL). The existing telecommunication and data systems located at the

  6. Microsoft Word - DOE-ID-INL-12-016.doc

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

    No.: DOE-ID-INL-12-016 SECTION A. Project Title: Reverse Osmosis System Removal SECTION B. Project Description: The project will remove a reverse osmosis water treatment system (FU-HA-101) from TAN 681 room 182. The system is out-of-service, with no intent of future use. Work will involve removal of the reverse osmosis system, and associated plumbing/piping and electrical lines and conduit. The project will clear the area of obstacles and tripping hazards associated with unused/unnecessary

  7. AMENDMENT OF SOLICITATIONIMODIFICATION OF CONTRACT I '. CONTRACT ID CODE

    National Nuclear Security Administration (NNSA)

    SOLICITATIONIMODIFICATION OF CONTRACT I '. CONTRACT ID CODE BWXT Pantex, LLC Route 726, Mt. Athos Road Lynchburg, VA 24506 PAGE I OF 12 PAGES Albuquerque, NM 871 85-5400 I Amarillo, TX 79120 I I 90. DATED (SEE ITEM 1 1 ) 8. NAME AND ADDRESS OF CONTRACTOR (No., street, county, state, ZIP Code) I 10A. MODIFICATION OF CONTRACTIORDER NO. 2. AMENDMENT/MODIFICATION NO. MI67 9A. AMENDMENT OF SOLICITATION NO. I 1 DE-AC04-00AL66620 100. DATED (SEE ITEM 13) 3. EFFECTIVE DATE See Block 16C Offers must

  8. UNITED STATES OF AMERICA FEDERAL ENERGY REGULATORY COMMISSION

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

    (WA), Sen. Maria Cantwell (OR), Rep. Norman Dicks (WA), Rep. Rick Larsen (WA), Rep. Adam Smith (WA), Rep. Greg Walden (OR), Rep. Mike Simpson (ID), Rep. David Reichert (WA),...

  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. Underground Storage Tank Integrated Demonstration (UST-ID). Technology summary

    SciTech Connect (OSTI)

    Not Available

    1994-02-01

    The DOE complex currently has 332 underground storage tanks (USTs) that have been used to process and store radioactive and chemical mixed waste generated from weapon materials production. Very little of the over 100 million gallons of high-level and low-level radioactive liquid waste has been treated and disposed of in final form. Two waste storage tank design types are prevalent across the DOE complex: single-shell wall and double-shell wall designs. They are made of stainless steel, concrete, and concrete with carbon steel liners, and their capacities vary from 5000 gallons (19 m{sup 3}) to 10{sup 6} gallons (3785 m{sup 3}). The tanks have an overburden layer of soil ranging from a few feet to tens of feet. Responding to the need for remediation of tank waste, driven by Federal Facility Compliance Agreements (FFCAs) at all participating sites, the Underground Storage Tank Integrated Demonstration (UST-ID) Program was created by the US DOE Office of Technology Development in February 1991. Its mission is to focus the development, testing, and evaluation of remediation technologies within a system architecture to characterize, retrieve, treat to concentrate, and dispose of radioactive waste stored in USTs at DOE facilities. The ultimate goal is to provide safe and cost-effective solutions that are acceptable to the public and the regulators. The UST-ID has focused on five DOE locations: the Hanford Site, which is the host site, in Richland, Washington; the Fernald Site in Fernald, Ohio; the Idaho National Engineering Laboratory near Idaho Falls, Idaho; the Oak Ridge Reservation in Oak Ridge, Tennessee, and the Savannah River Site in Savannah River, South Carolina.

  15. 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.

  16. IDS-NF Impact of Neutrino Cross Section Impact of Neutrino Cross Section

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

    IDS-NF Impact of Neutrino Cross Section Impact of Neutrino Cross Section Knowledge on Oscillation Knowledge on Oscillation Measurements Measurements M. Sorel, IFIC (CSIC and U. of Valencia) IDS-NF, RAL, Jan 16-17 2008 M. Sorel - IFIC (Valencia U. & CSIC) 2 IDS-NF Neutrino Cross Sections: At What Energies Needed? Superbeams: Solid: T2K Dashed: NovA M. Sorel - IFIC (Valencia U. & CSIC) 3 IDS-NF Neutrino Cross Sections: At What Energies Needed? Superbeams: Solid: T2K Dashed: NovA Beta

  17. DOE Data ID Service | OSTI, US Dept of Energy, Office of Scientific...

    Office of Scientific and Technical Information (OSTI)

    increase access to digital data from DOE-funded scientific research. Through the DOE Data ID Service, OSTI assigns persistent identifiers, known as Digital Object Identifiers ...

  18. 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.

  19. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  20. 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.

  1. Coal Fired Power Generation Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  2. 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....

  3. 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...

  4. 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

  5. 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.

  6. Femtosecond dark-field imaging with an X-ray free electron laser (CXIDB ID 19)

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

    Martin, A. V.

    2012-08-25

    This data was collected as part of the same experiment as the data deposited in [ID16](id-16.html). Experiment details are given in [Loh, N.D. et al.](http://dx.doi.org/10.1038/nature11222)

  7. Femtosecond dark-field imaging with an X-ray free electron laser (CXIDB ID 19)

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

    Martin, A. V.

    This data was collected as part of the same experiment as the data deposited in [ID16](id-16.html). Experiment details are given in [Loh, N.D. et al.](http://dx.doi.org/10.1038/nature11222)

  8. 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.

  9. 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.

  10. A short Id2 protein fragment containing the nuclear export signal forms amyloid-like fibrils

    SciTech Connect (OSTI)

    Colombo, Noemi [Fakultaet fuer Chemie und Pharmazie, Universitaet Regensburg, Universitaetsstrasse 31, 93053 Regensburg (Germany); Schroeder, Josef [Institut fuer Pathologie, Zentrales EM-Labor, Fakultaet fuer Medizin, Universitaet Regensburg, Franz-Josef-Strauss-Allee 11, 93053 Regensburg (Germany); Cabrele, Chiara [Fakultaet fuer Chemie und Pharmazie, Universitaet Regensburg, Universitaetsstrasse 31, 93053 Regensburg (Germany)]. E-mail: chiara.cabrele@chemie.uni-regensburg.de

    2006-07-21

    The negative regulator of DNA-binding/cell-differentiation Id2 is a small protein containing a central helix-loop-helix (HLH) motif and a C-terminal nuclear export signal (NES). Whereas the former is essential for Id2 dimerization and nuclear localization, the latter is responsible for the transport of Id2 from the nucleus to the cytoplasm. Whereas the isolated Id2 HLH motif is highly helical, large C-terminal Id2 fragments including the NES sequence are either unordered or aggregation-prone. To study the conformational properties of the isolated NES region, we synthesized the Id2 segment 103-124. The latter was insoluble in water and only temporarily soluble in water/alcohol mixtures, where it formed quickly precipitating {beta}-sheets. Introduction of a positively charged N-terminal tail prevented aggressive precipitation and led to aggregates consisting of long fibrils that bound thioflavin T. These results show an interesting structural aspect of the Id2 NES region, which might be of significance for both protein folding and function.

  11. Id-1 gene and gene products as therapeutic targets for treatment of breast cancer and other types of carcinoma

    DOE Patents [OSTI]

    Desprez, Pierre-Yves; Campisi, Judith

    2014-08-19

    A method for treatment of breast cancer and other types of cancer. The method comprises targeting and modulating Id-1 gene expression, if any, for the Id-1 gene, or gene products in breast or other epithelial cancers in a patient by delivering products that modulate Id-1 gene expression. When expressed, Id-1 gene is a prognostic indicator that cancer cells are invasive and metastatic.

  12. 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.

  13. YEAR","UTILITY_ID","UTILITY_NAME","PLANT_ID","PLANT_NAME","SCHEDULE","LINENO","A

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

    UTILITY_ID","UTILITY_NAME","PLANT_ID","PLANT_NAME","SCHEDULE","LINENO","AMOUNTS","DESCRIPTION" 2001,298,"Alexandria City of",6558,"DG Hunter",9,"Line 1","STEAM","Kind of Plant" 2001,298,"Alexandria City of",6558,"DG Hunter",9,"Line 2",1956,"Year Originally Constructed" 2001,298,"Alexandria City of",6558,"DG

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

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

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

  15. 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...

  16. 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...

  17. 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

  18. 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.

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

    SciTech Connect (OSTI)

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

    2010-04-01

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

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

    SciTech Connect (OSTI)

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

    2010-04-15

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

  1. 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

  2. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    1996-08-01

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

  3. 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.

  4. File:08-ID-c - Certificate of Public Convenience and Necessity...

    Open Energy Info (EERE)

    modified from its original state, some details may not fully reflect the modified file. Image title Lucidchart Author None Short title 08-ID-c - Certificate of Public Convenience...

  5. File:USDA-CE-Production-GIFmaps-ID.pdf | Open Energy Information

    Open Energy Info (EERE)

    ID.pdf Jump to: navigation, search File File history File usage Idaho Ethanol Plant Locations Size of this preview: 776 600 pixels. Full resolution (1,650 1,275 pixels,...

  6. DOI-BLM-ID-B010-2010-0083-CX | Open Energy Information

    Open Energy Info (EERE)

    0083-CX Jump to: navigation, search NEPA Document Collection for: DOI-BLM-ID-B010-2010-0083-CX CX for GeothermalExploration, CX for Thermal Gradient Holes for Geothermal...

  7. DOI-BLM-ID-I020-2012-0017-CX | Open Energy Information

    Open Energy Info (EERE)

    I020-2012-0017-CX Jump to: navigation, search NEPA Document Collection for: DOI-BLM-ID-I020-2012-0017-CX CX at Bingham-Caribou Geothermal Area for GeothermalExploration CX for...

  8. DOI-BLM-ID-B010-2010-??-CX | Open Energy Information

    Open Energy Info (EERE)

    ??-CX Jump to: navigation, search NEPA Document Collection for: DOI-BLM-ID-B010-2010-??-CX CX at Weiser Geothermal Area for GeothermalExploration CX at Weiser Geothermal Area for...

  9. DOI-BLM-ID-110-2009-3825-CE | Open Energy Information

    Open Energy Info (EERE)

    110-2009-3825-CE Jump to: navigation, search NEPA Document Collection for: DOI-BLM-ID-110-2009-3825-CE CX at Crane Creek Geothermal Area for GeothermalExploration Crane Creek...

  10. High-resolution x-ray diffraction microscopy of specifically labeled yeast cells (CXIDB ID 6)

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

    Nelson, Johanna

    2011-07-22

    This is the third of five exposures of the same sample at different tilts. This one is at +30 degrees tilt. Check CXI IDs 4 to 8 for the complete set.

  11. High-resolution x-ray diffraction microscopy of specifically labeled yeast cells (CXIDB ID 5)

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

    Nelson, Johanna

    2011-07-22

    This is the second of five exposures of the same sample at different tilts. This one is at +15 degrees tilt. Check CXI IDs 4 to 8 for the complete set.

  12. High-resolution x-ray diffraction microscopy of specifically labeled yeast cells (CXIDB ID 8)

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

    Nelson, Johanna

    2011-07-22

    This is the fifth of five exposures of the same sample at different tilts. This one is at -30 degrees tilt. Check CXI IDs 4 to 8 for the complete set.

  13. High-resolution x-ray diffraction microscopy of specifically labeled yeast cells (CXIDB ID 4)

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

    Nelson, Johanna

    2011-07-22

    This is the first of five exposures of the same sample at different tilts. This one is at +0 degrees tilt. Check CXI IDs 4 to 8 for the complete set.

  14. High-resolution x-ray diffraction microscopy of specifically labeled yeast cells (CXIDB ID 7)

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

    Nelson, Johanna

    2011-07-22

    This is the fourth of five exposures of the same sample at different tilts. This one is at -15 degrees tilt. Check CXI IDs 4 to 8 for the complete set.

  15. 11. CONTRACT ID CODE PAGE OF PAGES I AMENDMENT OF SOLICITATION...

    National Nuclear Security Administration (NNSA)

    11. CONTRACT ID CODE PAGE OF PAGES I AMENDMENT OF SOLICITATIONMODIFICATION OF CONTRACT 1 I 2. AMENDMENTIMODIFICATION NO. 258 6. ISSUED BY CODE 3. EFFECTIVE DATE See Block 16C ...

  16. 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,

  17. 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.

  18. How the DOE Data ID Service Works | OSTI, US Dept of Energy, Office of

    Office of Scientific and Technical Information (OSTI)

    Scientific and Technical Information the DOE Data ID Service Works DataCite | Contact DOE Data ID Service A DOE researcher, organization, or grantee determines that important datasets exist which need to be announced in DOE's scientific and technical databases and assigned DOIs. DOE Order 241.1B instructs that bibliographic information for these datasets be submitted to OSTI. First time submitters may contact OSTI at 865-576-6784 for help in deciding what submittal method will be used,

  19. PERSONAL PROPERTY TRANSFER MEMORANDUM OF UNDERSTANDING DE..GM07..04ID11457

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

    PERSONAL PROPERTY TRANSFER MEMORANDUM OF UNDERSTANDING DE..GM07..04ID11457 BETWEEN THE DEPARTMENT OF ENERGY IDAHO OPERATIONS OFFICE AND THE COMMUNITY REUSE ORGANIZATION, INC. I. INTRODUCTION This plan establishes conditions under which personal property may be transferred from the United States Department of Energy, Idaho Operations Office (DOE-ID), an agency of the United States Government, to the Community Reuse Organization, Inc. (CRO), an Idaho Corporation. A. Background Section 3] 55 of

  20. Microsoft Word - DOE-ID-INL-12-028-1.doc

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

    EC Document No.: DOE-ID-INL-12-028 SECTION A. Project Title: National Oceanic and Atmospheric Administration (NOAA) Birch Creek Canyon Wind Study SECTION B. Project Description: The National Oceanic and Atmospheric Administration (NOAA) Birch Creek Valley Wind Study would be conducted under the umbrella of the NOAA/Idaho National Laboratory (INL) Meteorological Research Partnership Memorandum of Agreement between NOAA and the Idaho Office of the U.S. Department of Energy (DOE-ID). The project

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. DOE Data ID Service Benefits | OSTI, US Dept of Energy, Office of

    Office of Scientific and Technical Information (OSTI)

    Scientific and Technical Information Benefits DataCite | Contact DOE Data ID Service When you submit metadata to OSTI about a dataset, you are basically "announcing" that it exists and you are describing it. That's why you will see the name of the basic submittal tool for data referred to as "Announcement Notice 241.6." Note that the DOE Data ID Service does not accept the dataset itself; only the metadata is submitted. The metadata loads into the OSTI processing system

  12. How to Use the DOE Data ID Service: For Data Centers and High Volume/High

    Office of Scientific and Technical Information (OSTI)

    Frequency Submitters | OSTI, US Dept of Energy, Office of Scientific and Technical Information Data Centers and High Volume/High Frequency Submitters DataCite | Contact DOE Data ID Service Call or email your organization's Scientific and Technical Information (STI) Manager. Your STI Manager will refer you to the correct contact at OSTI. Or, if someone else has suggested you contact OSTI directly, you may do so through the DOE Data ID Service email. OSTI will work with you to discover your

  13. Comments on Docket ID: DOE-HQ-2011-0014 | Department of Energy

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

    on Docket ID: DOE-HQ-2011-0014 Comments on Docket ID: DOE-HQ-2011-0014 This letter comprises the comments of the Pacific Gas and Electric Company (PG&E), Southern California Gas Company (SCGC), San Diego Gas and Electric (SDG&E), and Southern California Edison (SCE) in response to the U.S. Department of Energy's (DOE) Request for Information on Regulatory Burden. The signatories of this letter, collectively referred to herein as the California Investor Owned Utilities (CA IOUs) represent

  14. Idaho National Lab Contract DE-AC07-05ID14517

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

    Contract No. DE-AC07-05ID14517 Modifications You are here: DOE-ID Home > Contracts, Financial Assistance & Solicitations > INL Contract > INL Basic Contract Blue Line Free Acrobat Reader Link The documents listed below represent an electronic copy of modifications to the contract for the Management and Operation of the INL awarded to Battelle Energy Alliance, LLC. These documents are in PDF format. The Adobe Reader is required to access them. If you do not currently have the Acrobat

  15. A Better Way to ID Extreme Weather Events in Climate Models

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

    A Better Way to ID Extreme Weather Events in Climate Models A Better Way to ID Extreme Weather Events in Climate Models Berkeley Lab scientists help automate the search for hurricanes and other storms in huge datasets December 7, 2011 Dan Krotz, dakrotz@lbl.gov, +1 510-486-4019 You'd think that spotting a category 5 hurricane would never be difficult. But when the hurricane is in a global climate model that spans several decades, it becomes a fleeting wisp among mountains of data. That's a

  16. 1. CONTRACT ID CODE PAGE OF PAGES AMENDMENT OF SOLICITATIONIMODIFICATION OF CONTRACT I11 5

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

    SOLICITATIONIMODIFICATION OF CONTRACT I11 5 2 AMENDMENT/MODIFICATION NO 3. EFFECTIVE DATE (MD Y) 4. REQUISITION/PURCHASE REQ. NO SPROJECT NO. (If applicable) 273 See Block 16C 6 ISSUED BY CODE 7 ADMINISTERED BY (If olher than Item 6,, CODE U.S. Department of Energy Office of River Protection P. 0. Box 450, MIS 116-60 Richland, WA 99352 8. NAME AND ADDRESS OF CONTRACTOR (No., street, county, Stale and ZIP code) 9A. AMENDMENT OF SOLICITATION NO. ED Bechtel National, Inc. 9B. DATED (SEE ITEM I])

  17. 1. CONTRACT ID CODE PAGE OF PAGES AMENDMENT OF SOLICITATIONIMODIFICATION OF CONTRACT I111 5

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

    AMENDMENT OF SOLICITATIONIMODIFICATION OF CONTRACT I111 5 2. AMENDMENT/MODIFICATION NO. 3. EFFECTIVE DATE 4. REQUISITION/PURCHASE REQ. NO. 5. PROJECT NO. (If applica ble) A078 See 16C 06-08RL14383.012 6. ISSUED BY CODE1 7. ADMINISTERED BY (If other than Item ) CODEJ U.S. Department of Energy Same as item 6. Richland Operations Office DOE Contracting POC: Richard Stimmel P. 0. Box 550, MSIN A7-80 (509) 376-2882 Richland, WA 99352 8. NAME AND ADDRESS OF CONTRACTOR (No. Street, county, Stale and

  18. 1. CONTRACT ID CODE PAGE OF PAGES AMENDMENT OF SOLICITATIONIMODIFICATION OF CONTRACT II11 5

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

    AMENDMENT OF SOLICITATIONIMODIFICATION OF CONTRACT II11 5 2. AMEN DMENT/MODIFICATION NO. 3. EFFECTIVE DATE 4. REOUISITIONIPURCHASE REQ. NO. 5. PROJECT NO. (if applicable) A07 I ee 6C06-08RL143 83 .013 6.ISE YCDJ7. ADMINISTERED BY If lother than Item 6) CODEJ U.S. Department of Energy Same as item 6. Richland Operations Office DOE Contracting POC: Richard Stimmel P. 0. Box 550, MSTN A7-80 (509) 376-2882 Richland, WA 99352 _________ 8. NAME AND ADDRESS OF CONTRACTOR (No. Street, county, State and

  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. Single mimivirus particles intercepted and imaged with an X-ray laser (CXIDB ID 1)

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

    Seibert, M. Marvin; Ekeberg, Tomas; Maia, Filipe R.N.C.

    2011-02-02

    These are the files used to reconstruct the images in the paper "Single Mimivirus particles intercepted and imaged with an X-ray laser". Besides the diffracted intensities, the Hawk configuration files used for the reconstructions are also provided. The files from CXIDB ID 1 are the pattern and configuration files for the pattern showed in Figure 2a in the paper.

  15. Single mimivirus particles intercepted and imaged with an X-ray laser (CXIDB ID 2)

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

    Seibert, M. Marvin; Ekeberg, Tomas

    2011-02-02

    These are the files used to reconstruct the images in the paper "Single Mimivirus particles intercepted and imaged with an X-ray laser". Besides the diffracted intensities, the Hawk configuration files used for the reconstructions are also provided. The files from CXIDB ID 2 are the pattern and configuration files for the pattern showed in Figure 2b in the paper.

  16. Single mimivirus particles intercepted and imaged with an X-ray laser (CXIDB ID 1)

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

    Seibert, M. Marvin; Ekeberg, Tomas; Maia, Filipe R.N.C.

    These are the files used to reconstruct the images in the paper "Single Mimivirus particles intercepted and imaged with an X-ray laser". Besides the diffracted intensities, the Hawk configuration files used for the reconstructions are also provided. The files from CXIDB ID 1 are the pattern and configuration files for the pattern showed in Figure 2a in the paper.

  17. 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.

  18. Id1 expression promotes peripheral CD4{sup +} T cell proliferation and survival upon TCR activation without co-stimulation

    SciTech Connect (OSTI)

    Liu, Chen; Jin, Rong; Wang, Hong-Cheng; Tang, Hui; Liu, Yuan-Feng; Qian, Xiao-Ping; Sun, Xiu-Yuan; Ge, Qing; Sun, Xiao-Hong; Zhang, Yu

    2013-06-21

    Highlights: •Id1 expression enables naïve T cell proliferation without anti-CD28 co-stimulation. •Id1 expression facilitates T cells survival when stimulated with anti-CD3. •Elevation of IL-2 production by Id1 contributes increased proliferation and survival. •Id1 potentiates NF-κB activation by anti-CD3 stimulation. -- Abstract: Although the role of E proteins in the thymocyte development is well documented, much less is known about their function in peripheral T cells. Here we demonstrated that CD4 promoter-driven transgenic expression of Id1, a naturally occurring dominant-negative inhibitor of E proteins, can substitute for the co-stimulatory signal delivered by CD28 to facilitate the proliferation and survival of naïve CD4{sup +} cells upon anti-CD3 stimulation. We next discovered that IL-2 production and NF-κB activity after anti-CD3 stimulation were significantly elevated in Id1-expressing cells, which may be, at least in part, responsible for the augmentation of their proliferation and survival. Taken together, results from this study suggest an important role of E and Id proteins in peripheral T cell activation. The ability of Id proteins to by-pass co-stimulatory signals to enable T cell activation has significant implications in regulating T cell immunity.

  19. 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.

  20. 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

  1. 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.

  2. 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...

  3. 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.

  4. 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.

  5. DOE Data ID Service Background | OSTI, US Dept of Energy, Office of

    Office of Scientific and Technical Information (OSTI)

    Scientific and Technical Information Background DataCite | Contact DOE Data ID Service In 2011, the DOE Office of Scientific and Technical Information (OSTI) joined DataCite to facilitate citing, accessing, and reusing publicly available scientific research datasets produced by DOE-funded researchers. DataCite is an international organization that supports data visibility, ease of data citation in scholarly publications, data preservation and future re-use, and data access and

  6. How to Use the DOE Data ID Service: For Grantees | OSTI, US Dept of Energy,

    Office of Scientific and Technical Information (OSTI)

    Office of Scientific and Technical Information Grantees DataCite | Contact DOE Data ID Service Grantees who are not stationed at one of DOE's laboratories may access the E-Link website at https://www.osti.gov/elink/. Select the link for Financial Assistance Recipients. Choose Scientific Research Datasets (AN 241.6) from the menu and begin entering the metadata that is asked for. Ensure all required fields are completed with the appropriate information. Required fields are: Dataset Type,

  7. Microsoft PowerPoint - ID 876 TourBooklet_revb_Geology [Compatibility Mode]

    Office of Environmental Management (EM)

    Energy, National Nuclear Security Administration Nevada Field Office Bob Andrews Navarro-Intera December 10, 2014 Nevada National Security Site Underground Test Area (UGTA) Tour Page 2 Page 2Title ID 876 Tour Booklet 12/10/2014 - Page 2 Log No. 2014-xxx Nevada National Security Site (NNSS) * NNSS has many diverse roles to support the U.S. nuclear weapons stockpile stewardship missions and also supports other U.S. Department of Energy (DOE), Department of Defense, and Department of Homeland

  8. 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.

  9. 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.

  10. 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

  11. 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,...

  12. 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....

  13. 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.

  14. 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...

  15. 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.

  16. 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.

  17. 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 ...

  18. 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.

  19. 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 ...

  20. 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...

  1. 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 ...

  2. 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 ...

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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 ...

  11. How to Use the DOE Data ID Service: For Individual Lab Researchers | OSTI,

    Office of Scientific and Technical Information (OSTI)

    US Dept of Energy, Office of Scientific and Technical Information Individual Lab Researchers DataCite | Contact DOE Data ID Service Call or email your organization's Scientific and Technical Information (STI) Manager. Explain your need to submit a dataset to support a publication and/or to receive a DOI. Ask if your lab has been assigned a unique DOI prefix. The answer should be "yes." If it is not, the STI Manager will need to contact OSTI to obtain a prefix and then get back to

  12. AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT 11. CONTRACT ID CODE

    National Nuclear Security Administration (NNSA)

    -------------------------------------------------------- AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT 11. CONTRACT ID CODE I PAGE OF PAGES 1 I 2 2. AMENDMENT/MODIFICATION NO. 3. EFFECTIVE DATE 4. REQUISITION/PURCHASE REQ. NO. 15. PROJECT NO. (If applicable) 0246 See Block 16C 6. ISSUED BY CODE 05003 7. ADMINISTERED BY (If other than Item 6) CODE 105003 NNSA/Los Alamos Site Office NNSA/Los Alamos Site Office U.S. Department of Energy U.S. Department of Energy NNSA/Los Alamos Site Office Los

  13. Microsoft Word - DOE-ID-INL-12-007_INL-12-033_.doc

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

    Page 1 of 2 CX Posting No.: DOE-ID-INL-12-007 SECTION A. Project Title: Geotechnical Core Drilling for USGS 138 SECTION B. Project Description: . The U.S. Geological Survey (USGS) proposes to drill a 1,000-foot deep geotechnical corehole (USGS 138) into the eastern Snake River Plain aquifer. The location of the corehole will be about 4.0 mile(s) east of the city Howe and about 8.5 mile(s) north of the Naval Reactors Facility at the Southeast Quarter of the Southwest Quarter, Section 7, Township

  14. Microsoft Word - DOE-ID-13-044 Idaho EC B3-6.doc

    Office of Environmental Management (EM)

    10-2008 CONCLUDING MATERIAL Review Activity: Preparing Activity: DOE Operations Offices Field Offices DOE-HS-11 NA NNSA Service Center HS CH OH Project Number: EM ID GFO FSC 6910-0069 NE NV SC OR RL OAK SR RP National Laboratories Area Offices BNL Pantex Site Office LLNL Ashtabula Area Office LANL Carlsbad Area Office PNNL Columbus Area Office Sandia Fernald Area Office FNL Los Alamos Area Office West Valley Area Office Kirtland Area Office Pinellas Area Office Kansas City Area Office Miamisburg

  15. 11. CONTRACT ID CODE PAGE OF PAGES I AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT

    National Nuclear Security Administration (NNSA)

    11. CONTRACT ID CODE PAGE OF PAGES I AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT 1 I 2. AMENDMENTIMODIFICATION NO. 258 6. ISSUED BY CODE 3. EFFECTIVE DATE See Block 16C 05008 4. REQUISITION/PURCHASE REQ. NO. 7. ADMINISTERED BY (If other than Item 6) 15. PROJECT NO. (If applicable) CODE 1 0 5 0 0 8 NNSA/Oakridge Site Office NNSA/Oakridge Site Office U.S. Department of Energy U. S. Department of Energy NNSA/Y-12 Site Office NNSA/Y-12 Site Office P.O. Box 2050 P.O. Box 2050 Building 9704-2

  16. AMENDMENT OF SOLICITATIONIMODIFICATlON OF CONTRACT ( I- CONTRACT ID CODE PAGE I OF 2

    National Nuclear Security Administration (NNSA)

    ( I- CONTRACT ID CODE PAGE I OF 2 PAGES I . . Babcock & Wilcox Technical Services Pantex, LLC PO Box 30020 Amarillo, TX 79120 2. AMENDMENTIMODIFICATION NO. M I 51 Albuquerque, NM 87185-5400 I Amarillo, TX 79120 90. DATED (SEE ITEM 11) 8. NAME AND ADDRESS OF CONTRACTOR (No., street, county, state, ZIP Code) 3. EFFECTIVE DATE See Block 16C 9A. AMENDMENT OF SOLICITATION NO. extended. 6 . ISSUED BY CODE U.S. Department of Energy National Nuclear Security Administration Service Center Property

  17. AMENDMENT OF SOLlClTATlONlMODlFlCATlON OF CONTRACT ( I. ID CODE

    National Nuclear Security Administration (NNSA)

    ( I. ID CODE / DE-ACO4-OOAL6662O ' 10s. DATED (SEE ITEM 13) PAGE I OF 2 PAGES Babcock & W ~ ~ C O X Technical Services Pantex, LLC 800 Main Street Lynchburg, VA 24505 9B. DATED (SEE ITEM 11) 10A. MODIFICATION OF CONTRACTIORDER NO. Offers must acknowledge receipt of this amendment prior to the hour and date specified in the solicitation as amended, by one of the following methods: (a) By completing Items 8 and 15, and returning - copies of the amendment; (b) By acknowledging receipt of this

  18. AMENDMENT OF SOlLICITATION/MODIFICATlON OF CONTRACT I I. CONTRACr ID CODE

    National Nuclear Security Administration (NNSA)

    SOlLICITATION/MODIFICATlON OF CONTRACT I I. CONTRACr ID CODE BWXT Pantex, LLC Route 726, Mt. Athos Road Lynchburg, VA 24506 PAGE I OF 2 PAGES Albuquerque, NM 871 85-5400 I Amarillo, TX 79120 9B. DATED (SEE ITEM 1 1 ) 8. NAME AND ADDRESS OF CONTRACTOR (No., street, county, state, ZIP Code) DE-AC04-00AL66620 I I IOB. DATED (SEE ITEM 13) 2. AMENDMENTIMODIFICATION NO. MI41 9A. AMENDMENT OF Sol-ICITATION NO. CODE I ~ H L I L I I Y L U U ~ I I - 11. THlS ITEM ONLY APPLIES TO AMENDMENTS OF

  19. AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT /1. CONTRACT ID CODE

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

    SOLICITATION/MODIFICATION OF CONTRACT /1. CONTRACT ID CODE I PAGE OF PAGES 1 I 2 2. AMENDMENT/MODIFICATION NO 3. EFFECTIVE DATE 4 REQUISITION/PURCHASE REQ. NO 1 5 PROJECT NO. (If applicable) 342 See Block 16C 12SCOO1256 Item 0001 6. ISSUED BY CODE 00518 7. ADMINISTERED BY (If other than Item 6) CODE 1 0 0518 Oak 'Ridge Oak Ridge U.S. Department of Energy U.S. Department of Energy P.O. Box 2001 P.O. Box 2001 Oak Ridge TN 37831 Oak Ridge TN 37831 8. NAME AND ADDRESS OF CONTRACTOR (No .. street.

  20. AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT 1. CONTRACT ID CODE PAGE OF PAGES

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

    AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT 1. CONTRACT ID CODE PAGE OF PAGES 1 20 2. AMENDMENT/MODIFICATION NO. A001 3. EFFECTIVE DATE See Block 16C 4. REQUISITION/PURCHASE REQ. NO. 5. PROJECT NO. (If applicable) 6. ISSUED BY CODE 7. ADMINISTERED BY (If other than Item 6) CODE U.S. Department of Energy National Energy Technology Laboratory PO Box 880, 3610 Collins Ferry Road Morgantown, WV 26507-0880 Attn: Amanda Lopez 8. NAME AND ADDRESS OF CONTRACTOR (No., street, county, State, and

  1. AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT \1. CONTRACT ID CODE

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

    ID CODE I PAGE OF PAGES 1 I 2 2. AMENDMENTIMODIFICATION NO. 3. EFFECTIVE DATE 4. REOUISITIONIPURCHASE REO. NO. r' PROJECT NO. (If applicable) 356 See Block 16C 12SC001876 Item 7 6. ISSUED BY CODE 00518 7. ADMINISTERED BY (If other than Item 6) CODE \00518 Oak Ridge Oak Ridge U.S. Department of Energy U.S. Department of Energy P.O. Box 2001 P.O. Box 2001 Oak Ridge TN 37831 Oak Ridge TN 37831 8. NAME AND ADDRESS OF CONTRACTOR (No., stroot, county, State and ZIP Code) J1 SA. AMENDMENT OF

  2. 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

  3. 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.

  4. An interactive version of PropID for the aerodynamic design of horizontal axis wind turbines

    SciTech Connect (OSTI)

    Ninham, C.P.; Selig, M.S.

    1997-12-31

    The original PROP code developed by AeroVironment, Inc. and its various versions have been in use for wind turbine performance predictions for over ten years. Due to its simplicity, rapid execution times and relatively accurate predictions, it has become an industry standard in the US. The Europeans have similar blade-element/momentum methods in use for design. Over the years, PROP has continued to be improved (in its accuracy and capability), e.g., PROPSH, PROPPC, PROP93, and PropID. The latter version incorporates a unique inverse design capability that allows the user to specify the desired aerodynamic characteristics from which the corresponding blade geometry is determined. Through this approach, tedious efforts related to manually adjusting the chord, twist, pitch and rpm to achieve desired aerodynamic/performance characteristics can be avoided, thereby making it possible to perform more extensive trade studies in an effort to optimize performance. Past versions of PropID did not have supporting graphics software. The more current version to be discussed includes a Matlab-based graphical user interface (GUI) and additional features that will be discussed in this paper.

  5. 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.

  6. 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.

  7. 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).

  8. 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).

  9. North Portal Fuel Storage System Fire Hazard Analysis-ESF Surface Design Package ID

    SciTech Connect (OSTI)

    N.M. Ruonavaara

    1995-01-18

    The purpose of the fire hazard analysis is to comprehensively assess the risk from fire within the individual fire areas. This document will only assess the fire hazard analysis within the Exploratory Studies Facility (ESF) Design Package ID, which includes the fuel storage system area of the North Portal facility, and evaluate whether the following objectives are met: 1.1.1--This analysis, performed in accordance with the requirements of this document, will satisfy the requirements for a fire hazard analysis in accordance with U.S. Department of Energy (DOE) Order 5480.7A. 1.1.2--Ensure that property damage from fire and related perils does not exceed an acceptable level. 1.1.3--Provide input to the ESF Basis For Design (BFD) Document. 1.1.4 Provide input to the facility Safety Analysis Report (SAR) (Paragraph 3.8).

  10. Eastport, ID Natural Gas Pipeline Imports From Canada (Dollars per Thousand

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

    Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 1.22 1.60 1.60 2.04 2000's 3.79 4.71 2.83 4.72 5.30 7.13 6.22 6.31 7.88 3.86 2010's 4.19 3.90 2.59 3.34 4.14 2.34 - = 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. Price of Natural Gas Pipeline Imports by Point of Entry Eastport, ID Natural Gas

  11. Yucca Mountain Project Integrated Data System (IDS); Final report, October 1, 1989--December 31, 1990

    SciTech Connect (OSTI)

    1991-05-23

    This final report for LANL Subcontract 9-XS8-2604-1 includes copies of all formal letters, memorandums, and reports provided by CAG to support the IDS effort in the LANL Test Managers Office, Las Vegas, Nevada from October 1, 1989 through the end of the contract on December 31, 1990. The material is divided into two sections; the Functional Requirements Document (FRD) and other reports, letters, and memorandums. All documents are arranged in chronological order with most recent last. Numerous draft copies of the FRD were prepared and cover sheets for all drafts are included. The complete text of only the last version supplied (July 27, 1990) is included in this document.

  12. 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...

  13. 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.

  14. 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.

  15. 1. CONTRACT ID CODE PAGE of: PAGES AMENDM ENT OF SOLICITATION/MODIFICATION OF CONTRACT I -1 5

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

    of: PAGES AMENDM ENT OF SOLICITATION/MODIFICATION OF CONTRACT I -1 5 2. AMENDMENT/MODIFICATION NO. 3. EFFECTIVE DATE (0/1T 4. REQUISITION/PURCHASE REQ. NO. 5. PROJECT NO. (If applicable) 286 See Block 16C 12EM0014771 6. ISSUED BY CODE 7. AD)MINISTERED BY (If otherrtianItm 6) CODE U.S. Department of Energy Office of River Protection P. 0. Box 450, MIS 116-60 Richland, WA 99352 8. NAME AND ADDRESS OF CONTRACTOR (No., street. county.. State and ZIP code) 9A. AMENDMENT OF SOLICITATION NO. Bechtel

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. https://bluedart.phe.com/owa/?ae=Item&t=IPM.Note&id=RgAAAAA%2f3

    National Nuclear Security Administration (NNSA)

    Phyllis Radack Manager, Regulatory Services 702-295-6582 702-858-5587 (cell) 702-295-7699 ...idRgAAAAA%2f3mOqqZ%2bfSq... 702-858-5587 (cell) 702-295-7699 (fax) From: Morris, Patrick ...

  9. A 12-MW-scale pilot study of in-duct scrubbing (IDS) using a rotary atomizer

    SciTech Connect (OSTI)

    Samuel, E.A.; Murphy, K.R.; Demian, A.

    1989-11-01

    A low-cost, moderate-removal efficiency, flue gas desulfurization (FGD) technology was selected by the US Department of Energy for pilot demonstration in its Acid Rain Precursor Control Technology Initiative. The process, identified as In-Duct Scrubbing (IDS), applies rotary atomizer techniques developed for lime-based spray dryer FGD while utilizing existing flue gas ductwork and particulate collectors. IDS technology is anticipated to result in a dry desulfurization process with a moderate removal efficiency (50% or greater) for high-sulfur coal-fired boilers. The critical elements for successful application are: (1) adequate mixing of sorbent droplets with flue gas for efficient reaction contact, (2) sufficient residence time to produce a non-wetting product, and (3) appropriate ductwork cross-sectional area to prevent deposition of wet reaction products before particle drying is comple. The ductwork in many older plants, previously modified to meet 1970 Clean Air Act requirements for particulate control, usually meet these criteria. A 12 MW-scale IDS pilot plant was constructed at the Muskingum River Plant of the American Electric Power System. The pilot plant, which operates from a slipstrem attached to the air-preheater outlet duct from the Unit 5 boiler at the Muskingum River Plant (which burns about 4% sulfur coal), is equipped with three atomizer stations to test the IDS concept in vertical and horizontal configurations. In addition, the pilot plant is equipped to test the effect of injecting IDS off- product upstream of the atomizer, on SO{sub 2}and NO{sub x} removals.

  10. 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

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

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

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

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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)

  2. T-582: RSA systems has resulted in certain information being extracted from RSA systems that relates to RSA SecurID

    Broader source: Energy.gov [DOE]

    RSA investigation has revealed that the attack resulted in certain information being extracted from RSA's systems. Some of that information is related to RSA's SecurID two-factor authentication products.

  3. T-559: Stack-based buffer overflow in oninit in IBM Informix Dynamic Server (IDS) 11.50 allows remote execution

    Broader source: Energy.gov [DOE]

    Stack-based buffer overflow in oninit in IBM Informix Dynamic Server (IDS) 11.50 allows remote execution attackers to execute arbitrary code via crafted arguments in the USELASTCOMMITTED session environment option in a SQL SET ENVIRONMENT statement

  4. 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.

  5. 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.

  6. 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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  8. RESULTS OF RADIOLOGICAL I'IEASUREMENTS HIGHT{AYS 18 AI.ID IO4 IN NIAGARA

    Office of Legacy Management (LM)

    9s' RESULTS OF RADIOLOGICAL I'IEASUREMENTS HIGHT{AYS 18 AI.ID IO4 IN NIAGARA az76 rl//.ry' ORNL/RASA.85/ 40 TAKEN AT JUNCTION FALLS, NEH YORK Accesr to the information in thit rcport ir limiled to tho!' inOllateO on tho dl3tribution li3t and to OePartment ot Encrgy and Oepartmcnt ol Enotgy Gontracton This report was prepared as an account of work sponsored by an agency of the United States Government. Neitherth€ U nited StatesGovernment norany agency thereof, nor any of their employees, makes

  9. AMENDMENT OF SOLlClTATlONlMODlFlCATION OF CONTRACT 1 I . CONTR"CT ID CODE

    National Nuclear Security Administration (NNSA)

    SOLlClTATlONlMODlFlCATION OF CONTRACT 1 I . CONTR"CT ID CODE BWXT Pantex, LLC Route 726, Mt. Athos Road Lynchburg, VA 24506 PAGE 1 OF 2 PAGES Albuquerque, NM 8718Ii4400 I Amarillo, TX 79120 9B. DATED (SEE m M 11) 10A. MODIFICATION OF CONTRACTIORDER NO. 8. NAME AND ADDRESS OF CONTRACTOR (No., street, county, &ate, ZIP Code) I ( DE-ACOCOOAL66620 10B. DATED (SEE / E M 13) 2. AMENDMENT/MODIFICATION NO. M097 9A. AMENDMENT OF SOLICITATION NO. Offera must a d t n d e d p rsceipt of this m e n

  10. AMENDMENT OF SOLlClTATlONlMODlFlCATlON OF CONTRACT I ' CONTRACT ID CODE

    National Nuclear Security Administration (NNSA)

    ' CONTRACT ID CODE BWXT Pantex, LLC Route 726, Mt. Athos Road Lynchburg, VA 24506 PAGE 1 OF 12 PAGES 9B. DATED (SEE ITEM 11) 5. PROJECT NO. (If applicable) 4. REQUlSlTlONlPURCHASE REQ. NO. 2. AMENDMENTIMODIFICATION NO. MI39 extended. 6. ISSUED BY CODE U.S. Department of Energy National Nuclear Security Administration Service Center Property and M&O Contract Support Department P.O. Box 5400 Albuquerque, NM 871 85-5400 3. EFFECTIVE DATE See Block 16C CODE I FACILITY CODE Offers must

  11. AMENDMENT OF SOLlClTATlONlMODlFlCATlON OF CONTRACT I CONTRACT ID CODE

    National Nuclear Security Administration (NNSA)

    CONTRACT ID CODE Babcock & Wilcox Technical Services Pantex, LLC 9B. DATED (SEE ITEM 11) PO Box 30020 Amarillo, T X 79120 PAGE 1 OF 2 PAGES Albuquerque, NM 87185-5400 I Amarillo, TX 79120 I I DE-AC04-00AL66620 10B. DATED (SEE ITEM 13) 8. NAME AND ADDRESS OF CONTRACTOR (No., street, county, state, ZIP Code) 2. AMENDMENTIMODIFICATION NO. MI74 9A. AMENDMENT OF SOLICITATION NO. extended. CODE I FACILITY CODE Offers must acknowledge receipt of this amendment prior to the hour and date specified

  12. AMENDMENT OF SOLlClTATlONlMODlFlCATlON OF CONTRACT I I, CONTRACT ID CODE

    National Nuclear Security Administration (NNSA)

    I, CONTRACT ID CODE BWXT Pantex, LLC Route 726, Mt. Athos Road Lynchburg, V A 24506 PAGE I OF 2 PAGES Albuquerque, NM 87185-5400 I Amarillo, TX 79120 9B. DATED (SEE ITEM I I ) 8. NAME AND ADDRESS OF CONTRACTOR (No.. street, county, state, ZIP Code) I ( DE-AC04-00AL66620 10B. DATED (SEE ITEM 13) 2. AMENDMENTIMODIFICATION NO. M I 3 8 9A. AMENDMENT OF SOLICITATION NO. extended. 3. EFFECTIVE DATE See Block 16C CODE I FACILITY CODE Offers must acknowledge receipt of this amendment prior to the hour

  13. AMENDMENT OF SOLlClTATlONlMODlFlCATlON OF CONTRACT I I. CONT" ID CODE

    National Nuclear Security Administration (NNSA)

    CONT" ID CODE Babcock & Wilcox Technical Services Pantex, LLC I 1 98. DATED (SEE ITEM 11) PAGE I OF 2 PAGES Albuquerque, NM 87185-5400 I Amarillo, TX 79120 PO Box 30020 Amarillo, TX 79120 8. NAME AND ADDRESS OF CONTRACTOR (No., street, county, state, ZIP Code) 10A. MODIFICATION OF CONTRACTIORDER NO. 2. AMENDMENTIMODIFICATION NO. MI64 9A. AMENDMENT OF SOLICITATION NO. DE-AC04-00AL66620 1 I IOB. DATED (SEE ITEM 13) 3. EFFECTIVE DATE See Block 16C Offers must acknowledge receipt of this

  14. AMENDMENT OF SOLlClTATlONlMODlFlCATlON OF CONTRACT I I. CONTRA'T ID CODE

    National Nuclear Security Administration (NNSA)

    CONTRA'T ID CODE BWXT Pantex, LLC Route 726, Mt. Athos Road Lynchburg, V A 24506 PAGE I OF 2 PAGES Albuquerque, NM 871 85-5400 / Amarillo, TX 79120 I I 9B. DATED (SEE ITEM 11) 8. NAME AND ADDRESS OF CONTRACTOR (No., street, county, state, ZIP Code) I 10A. MODIFICATION OF CONTRACTIORDER NO. 2. AMENDMENTIMODIFICATION NO. M I 0 8 9A. AMENDMENT OF SOLICITATION NO. DE-AC04-00AL66620 1 1 108. DATED (SEE ITEM 13) 3. EFFECTIVE DATE See Block 16C Offers must acknowledge receipt of this amendment prior to

  15. AMENDMENT OF SOLlClTATlONlMODlFlCATlON OF CONTRACT ID PAGE I OF 2

    National Nuclear Security Administration (NNSA)

    / ' ID PAGE I OF 2 PAGES - . Albuquerque, NM 87185-5400 I Amarillo, TX 79120 I ( DE-AC04-00AL66620 10B. DATED (SEE ITEM 13) 8. NAME AND ADDRESS OF CONTRACTOR (No., street, county, state, ZIP Code) Babcock & W ~ ~ C O X Technical Services Pantex, LLC 800 Main Street Lynchburg, VA 24505 2 . AMENDMENTIMODIFICATION NO. MI50 9A. AMENDMENT OF SOLICITATION NO. 9B. DATED (SEE ITEM 11) 10A. MODIFICATION OF CONTRACTIORDER NO. Offers must acknowledge receipt of this amendment prior to the hour and date

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. AMENDMENT OF SOLIr ATI ON/MODIFI CATION OF CONTRACT 1. CONTRACT ID CODE PAGE OF PAGES

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

    SOLIr ATI ON/MODIFI CATION OF CONTRACT 1. CONTRACT ID CODE PAGE OF PAGES 2 AMENDMENT/lIVDDIFICATiON NC 3. EFFECTIVE DATE [4 REDUISITION/PURCHASE REC NO IE PR3JECT NC (if applicable) 09 ISoe Bloo , 16- - ISee Soheoule S ISSUED D> CODE 7 ~ ADMINISTERED BY (if otnertrian ItemS CO DE Of fice of Ri-.er PoDLecOLODn office of Riv'er P-oCQ-ec-.iQ .S. Cet:F O<men of E-nerov,, I.S. Deparo:merio c-' Enrgv P.O. Box 4'5C 0 ... Box 45C .io ao 1 31 W YS: (-876 B. NAME AND ADDRESS CF CONTRACTOR (No seve

  3. 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...

  4. 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...

  5. 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.

  6. 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...

  7. 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 ...

  8. 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. ...

  9. 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.

  10. 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.

  11. 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 ...

  12. 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.

  13. 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.

  14. 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....

  15. 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.

  16. 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

  17. 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.

  18. 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%.

  19. 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.

  20. 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.)

  1. 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.)

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. Search for: All records | SciTech Connect

    Office of Scientific and Technical Information (OSTI)

    Office of Classification Hanford Site (HNF), Richland, WA (United States) Idaho Chemical Processing Plant, Idaho Falls, ID (United States) Idaho National Engineering Laboratory,...

  10. Search for: All records | SciTech Connect

    Office of Scientific and Technical Information (OSTI)

    ... WA (United States) Idaho Chemical Processing Plant, Idaho Falls, ID (United States) ... CO (United States) Naval Petroleum and Oil Shale Reserves (United States) Navarro ...

  11. 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.

  12. 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.

  13. DOE/ID-Number

    Office of Environmental Management (EM)

    data from short-term tests. To collect the necessary data as part of the R&D program and engineering-scale demonstration, more effective monitoring systems must be developed to...

  14. ID-2011-01526

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

  15. DOE/ID-Number

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

    Prepared for US Department of Energy Used Fuel Disposition Campaign J.-A. Wang, H. Wang, and H. Jiang B. B. Bevard and R. L. Howard Oak Ridge National Laboratory September 2014 ...

  16. Beamline 29-ID

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

    sided bounce Mirror (M1) 31.3 m Heat-sink, side bounce Monochromater (M2, LEG, MEG, HEG) 39.7 m In-Focus VLS-PGM Exit Slit 59.7 m Both RSXS and ARPES branchlines Mirror...

  17. ID.pdf

    Energy Savers [EERE]

  18. DOE/ID-Number

    Office of Environmental Management (EM)

    INEELEXT-04-02423 ABB SCADAEMS System INEEL Baseline Summary Test Report J. R. Davidson ... SCADAEMS System INEEL Baseline Summary Test Report J. R. Davidson M. R. Permann B. L. ...

  19. DOE/ID-Number

    Office of Environmental Management (EM)

    in the energy sector NSTB National SCADA Test Bed Common Cyber Security Vulnerabilities ... of the National Supervisory Control and Data Acquisition (SCADA) Test Bed (NSTB) program. ...

  20. 2-ID-E

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

    General Users. For example, in collaboration with G. Woloschak et al, we have looked at TiO2-DNA nanocomposites in mammalian cells 1; B. Twining et al investigate trace elements...

  1. Badging, Real ID

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

    Foreign national guests and employees must have an approved visit and present a valid passport and documentation of US legal status and work authorizations. Official visitors are...

  2. DOE/ID-Number

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

    production of a range of liquid fuels and fuel blendstocks from lignocellulosic biomass feedstocks by funding fundamental and applied research that advances the state of...

  3. DOE/ID-Number

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

    non-industrial private forest land who wish to establish, produce, and deliver biomass feedstocks. It provides two categories of assistance: (1) Matching payments may be...

  4. DOE/ID-Number

    Energy Savers [EERE]

    ... 21, 2015 ACRONYMS ASME B&PVC American Society of Mechanical Engineers Boiler and Pressure Vessel Code ASTM American Society for Testing and Materials CISCC Chloride Induced ...

  5. DOE/ID-Number

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

    A Summary of Control System Security Standards Activities in the Energy Sector October 2005 National SCADA Test Bed A Summary of Control System Security Standards Activities in the Energy Sector October 2005 Sandia National Laboratories Idaho National Laboratory Argonne National Laboratory Pacific Northwest National Laboratory Prepared for the U.S. Department of Energy Office of Electricity Delivery and Energy Reliability 2 iii ABSTRACT This document is a compilation of the activities and

  6. Blind Modal ID

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

    high-resolution visualization and analysis of structural dynamics. Contact Yongchao Yang (832) 335-3003 Email David Mascarenas dmascarenas@lanl.gov (505) 665-0881 Original...

  7. DOE/ID-Number

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

    Signage and Posting Guidelines CAES is a destination point for world-renowned researchers, private industry partners, politicians, CAES patrons and other dignitaries. For this...

  8. DOE/ID-Number

    Energy Savers [EERE]

    ... greatest control on chemical and physical properties of both illite and smectite clays. ... U(VI) species predominant under these chemical solution conditions, as well as the ...

  9. Beamline 29-ID

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

    eV Energy resolution: 1.8 meV, Angular resolution: 0.01 6-axis cryomanipulator Polar Rotation: 180 Tilt Rotation:-10 to 35 Azimutal Rotation: 45 Temperature: 800-10K...

  10. DOE/ID-Number

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

    ... source term and decay heat with higher discharge burnup. ... that can challenge pressure boundaries and ... LWR core components * Melting temperature * Thermal conductivity ...

  11. Beamline 29-ID

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

    Resonant Soft X-ray Scattering (RSXS) Diffractometer: 7-axes "kappa" geometry 10 K closed-cycle cryostat Detectors: Microchannel plate, area detector Electron yield detector TES...

  12. DOE/ID-Number

    Office of Scientific and Technical Information (OSTI)

    M. J. Robinson Pacific Northwest National Laboratory September 2012 FCRD-SWF-2012-000214 DISCLAIMER This information was prepared as an account of work sponsored by an agency of...

  13. DOE/ID-Number

    Office of Scientific and Technical Information (OSTI)

    Microfluidic Sampling System for High Temperature Electrochemical MC&A September 26, 2013 II DISCLAIMER This information was prepared as an account of work sponsored by an agency...

  14. Beamline 29-ID

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

    component; implementation of beamline controls and safety systems (cleanroom, FOE progress, FOE progress2) Fall 2012 FDR approval (October 15) Installation of...

  15. DOE/ID-Number

    Office of Environmental Management (EM)

    for Spent Nuclear Fuel and High-Level Waste Prepared for U.S. Department of Energy ... management of spent nuclear fuel (SNF) a and high-level waste (HLW) for 54 years. ...

  16. acceptable-ID.pdf

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

  17. DOE/ID-Number

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

    Disposal in Crystalline Rocks 9262014 v Used Fuel Disposal in Crystalline Rocks: ... DEPTH AND DOSE RATE PROFILE USED IN MPM V2 287 9.6 INCORPORATION OF RADIOLYSIS MODEL ...

  18. DOE/ID-Number

    Energy Savers [EERE]

    Disposal Options for Research and Development for Spent Nuclear Fuel and High Basis for Identification of Disposal Options for Research and Development for Spent Nuclear Fuel and High-Level Waste Prepared for U.S. Department of Energy Used Fuel Disposition Campaign Rob P. Rechard Barry Goldstein Larry H. Brush Sandia National Laboratories James A. Blink Mark Sutton Lawrence Livermore National Laboratory Frank V. Perry Los Alamos National Laboratory March FCRD-USED-2011-0000 asis for

  19. DOE/ID-Number

    Energy Savers [EERE]

    INEEL/EXT-04-02423 ABB SCADA/EMS System INEEL Baseline Summary Test Report J. R. Davidson M. R. Permann B. L. Rolston S. J. Schaeffer November 2004 Prepared by: Idaho National Engineering and Environmental Laboratory INEEL/EXT-04-02423 ABB SCADA/EMS System INEEL Baseline Summary Test Report J. R. Davidson M. R. Permann B. L. Rolston S. J. Schaeffer November 2004 Idaho National Engineering and Environmental Laboratory INEEL National Security Division Idaho Falls, Idaho 83415 Prepared for the U.S.

  20. DOE/ID-Number

    Energy Savers [EERE]

    Public Preferences Related to Consent-Based Siting of Radioactive Waste Management Facilities for Storage and Disposal: Analyzing Variations over Time, Events, and Program Designs Prepared for US Department of Energy Nuclear Fuel Storage and Transportation Planning Project Hank C. Jenkins-Smith Carol L. Silva Kerry G. Herron Kuhika G. Ripberger Matthew Nowlin Joseph Ripberger Center for Risk and Crisis Management, University of Oklahoma Evaristo "Tito" Bonano Rob P. Rechard Sandia

  1. Beamline 29-ID

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

    Lab, APS) Christa Benson Dr. Jonathan Lang Dr. Jessica McChesney Dr. Mohan Ramanathan Dr. Ruben Reininger Dr. Richard Rosenberg Dr. George Srajer IEX - Advisory Committee Dr Dario...

  2. DOE/ID-Number

    Office of Environmental Management (EM)

    Planning Project Hank C. Jenkins-Smith Carol L. Silva Kerry G. Herron Kuhika G. ... in public support for nuclear technologies can occur (Jenkins-Smith et al. 2011). ...

  3. DOE/ID-Number

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

    storage, conveying systems and a pellet 110 pulverizer to insure that the appropriate recipe of material enters the throat of the conversion reactor in the appropriate blends and...

  4. DOE/ID-Number

    Office of Environmental Management (EM)

    Disposal Options for Research and Development for Spent Nuclear Fuel and High Basis for Identification of Disposal Options for Research and Development for Spent Nuclear Fuel and High-Level Waste Prepared for U.S. Department of Energy Used Fuel Disposition Campaign Rob P. Rechard Barry Goldstein Larry H. Brush Sandia National Laboratories James A. Blink Mark Sutton Lawrence Livermore National Laboratory Frank V. Perry Los Alamos National Laboratory March FCRD-USED-2011-0000 asis for

  5. DOE/ID-Number

    Office of Environmental Management (EM)

    Affecting Performance of a Salt Repository for Disposal of Heat-Generating Nuclear Waste Prepared for U.S. Department of Energy Used Nuclear Fuel S. David Sevougian, SNL Geoff...

  6. DOE/ID-Number

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

    76 Idaho National Laboratory Radiological Response Training Range Environmental Assessment Final October 2010 DOE/EA-1776 Idaho National Laboratory Radiological Response Training Range Environmental Assessment Final October 2010 Prepared for the U.S. Department of Energy Idaho Operations Office i CONTENTS GLOSSARY ................................................................................................................................................ iii EXECUTIVE SUMMARY

  7. DOE/ID-Number

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

    822 Idaho National Laboratory Stand-Off Experiment (SOX) Range Environmental Assessment Final March 2011 DOE/EA-1822 Idaho National Laboratory Stand-Off Experiment (SOX) Range Environmental Assessment Final March 2011 Prepared for the U.S. Department of Energy Idaho Operations Office i CONTENTS ACRONYMS ............................................................................................................................................... iii GLOSSARY

  8. DOE/ID-Number

    Energy Savers [EERE]

    ... automation industry is the Industrial Process Monitoring (IPM) profile, which is under development by ... recommended best practice to pre-load the keys into the ZigBee devices ...

  9. 11. CONTRACT ID CODE

    National Nuclear Security Administration (NNSA)

    1 PAGE 1 OF2 AMENDMENT OF SOLICITATION/MODIFICATION OF CONTRACT PAGES 2. AMENDMENT/MODIFICATION NO. I 3. EFFECTIVE DATE M191 See Block 16C 4. REQUISITION/PURCHASE I 5. PROJECT NO. (If applicable) REQ. NO. 6.ISSUED BY CODE U.S. Department of Energy National Nuclear Security Administration Service Center Property and M&O Contract Support Department P.O. Box 5400 Albuquerque, NM 87185-5400 7. ADMINISTERED BY (If other than Item 6) CODE U.S. Department of Energy National Nuclear Security

  10. 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

  11. 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

  12. 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

  13. 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.

  14. YEAR","MONTH","STATE","UTILITY_ID","UTILITY_NAME","RESIDENTIAL_GP REVENUES (Tho

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

    UTILITY_ID","UTILITY_NAME","RESIDENTIAL_GP REVENUES (Thousand $)","COMMERCIAL_GP REVENUES (Thousand $)","INDUSTRIAL_GP REVENUES (Thousand $)","TRANS_GP REVENUES (Thousand $)","TOTAL_GP REVENUES (Thousand $)","RESIDENTIAL_GP SALES (MWh)","COMMERCIAL_GP SALES (MWh)","INDUSTRIAL_GP SALES (MWh)","TRANS_GP SALES (MWh)","TOTAL_GP SALES (MWh)","RESIDENTIAL_GP

  15. 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.

  16. Priority Firm Exchange .

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

    OR 1953 21 MW Black Canyon Payette, ID 1925 10 MW Boise River Diversion Boise, ID 1912 3 MW Bonneville Columbia, ORWA 1938 1,225 MW Chandler Yakima, WA 1956 12 MW Chief...

  17. BLACKLEAF CANYON TWO MEDICINE CREEK POTSHOT PROSPECT GLACIER...

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

    Liquids Reserve Class No 2001 liquids reserves 0.1 - 10 Mbbl Basin Outline WY UT ID CO MT WA OR NV CANADA INDEX MAP ID Total Total Total Number Liquid Gas BOE of Reserves Reserves ...

  18. BLACKLEAF CANYON TWO MEDICINE CREEK POTSHOT PROSPECT GLACIER...

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

    BOE Reserve Class No 2001 Reserves 0.1 - 10 MBOE Basin Outline WY UT ID CO MT WA OR NV CANADA INDEX MAP ID Total Total Total Number Liquid Gas BOE of Reserves Reserves Reserves ...

  19. BLACKLEAF CANYON TWO MEDICINE CREEK POTSHOT PROSPECT GLACIER...

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

    Gas Reserve Class No 2001 gas reserves Basin Outline WY UT ID CO MT WA OR NV CANADA INDEX MAP ID Total Total Total Number Liquid Gas BOE of Reserves Reserves Reserves Fields (Mbbl) ...

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. AMENDMENT OF SOLlClTATlONlMODlFlCATlON OF CONTFWCT I 1 CONTRACT ID CODE PAGE I OF 2

    National Nuclear Security Administration (NNSA)

    CONTFWCT I 1 CONTRACT ID CODE PAGE I OF 2 PAGES MI10 I See Block 16C I REQ. NO. BWXT Pantex, LLC Route 726, Mt. Athos Road Lynchburg, VA 24506 2. AMENDMENTIMODIFICATION NO. 1 3. EFFECTIVE DATE 1 4. REQUISITIONIPURCHASE 1 5. PROJECT NO. (If a ~ ~ l i c a b l e l . a , U.S. Department of Energy National Nuclear Security Administration Service Center Property and M&O Contract Support Department P.O. Box 5400 Albuquerque, NM 871 85-5400 96. DATED (SEE ITEM 1 1 ) 6. ISSUED BY CODE 1 7.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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:

  19. 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

  20. 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