National Library of Energy BETA

Sample records for forecast date actual

  1. DATE:

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

    DATE: February 1, 2012 TO: Procurement Directors FROM: Director, Office of Procurement and Assistance Policy Office of Procurement and Assistance Management SUBJECT: Acquisition...

  2. DATE:

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

    38 DATE: May 03, 2012 TO: Procurement Directors FROM: Director, Contract and Financial Assistance Policy Division Office of Policy Office of Procurement and Assistance Management...

  3. DATE:

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

    61 DATE: June 19, 2013 TO: Procurement Directors FROM: Director Policy Division Office of Procurement and Assistance Policy Office of Acquisition and Project Management SUBJECT: ...

  4. DATE:

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

    3-12 DATE: December 7, 2012 TO: Procurement Directors FROM: Director Contract and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management ...

  5. DATE:

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

    4-35 DATE: July 09, 2014 TO: Procurement Directors FROM: Director Contract and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management ...

  6. DATE:

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

    36 DATE: April 23, 2012 TO: Procurement Directors FROM: Director, Policy Division Office of Procurement and Assistance Policy Office of Procurement and Assistance Management...

  7. DATE:

    Office of Legacy Management (LM)

    -RL5- DATE: September 13, 1990 TO: Alexander Williams (w 39 fusrap6 I FROM: Ed Mitchellzm SUBJECT: Elimination Recommendation for American Machine and Foundry in New York City The...

  8. Date

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

    Template Revised: 6/12/2014 Template Reviewed: 6/12/2014 Operated for the U.S. Department of Energy by Sandia Corporation P.O. Box 5800 MS-1461 Albuquerque, New Mexico 87185-1461 Date Contractor Name Address Attention: Based on our earlier discussions, the Contract Audit Department at Sandia Corporation, which operates Sandia National Laboratories (Sandia) will audit costs incurred through your fiscal year ending XXXXXX on the following contracts placed with your company: Contract(s) Type of

  9. Dated:

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

    cause appearing, IT IS HEREBY ORDERED: 1. The Schedule Scheduling Order is stayed pending execution of a settlement agreement and stipulated final order. Dated: ~ /,/ .,2015 Christopher T. Saucedo Hearing Officer 3 Complainant, v. UNITED STATES DEPARTMENT OF ENERGY, and NUCLEAR WASTE PARTNERSHIP, LLC, Respondents. No. HWB 14-21 (CO) CERTIFICATE OF SERVICE I hereby certify that a copy of the STIPULATED JOINT MOTION TO STAY THE SCHEDULING ORDER has been sent electronically to the following on May

  10. DATE:

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

    POLICY FLASH 2013-45 DATE: April 16, 2013 TO: Procurement Directors FROM: Director Contract and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management SUBJECT: DOE Acquisition Guide Chapter 15.1 Source Selection Guide SUMMARY: Attached is a revised Source Selection Guide. The Guide has been updated to reflect changes to DOE policies and practices and includes new topics such as Flow of the Source Selection Process, Source Selection Official

  11. DATE:

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

    53 DATE: May 15, 2013 TO: Procurement Directors FROM: Director Contract and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management SUBJECT: Implementation of Division F, Title I, Title II, and Title III and Division G, Consolidated and Further Continuing Appropriations Act, 2013, Pub. L. No.113-6 SUMMARY: Acquisition Letter (AL) 2013-06 and Financial Assistance Letter (FAL) 2013-04 provides implementing instructions and guidance for Division F, Title

  12. DATE:

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

    61 DATE: June 19, 2013 TO: Procurement Directors FROM: Director Policy Division Office of Procurement and Assistance Policy Office of Acquisition and Project Management SUBJECT: The Whistleblower Protection Enhancement Act of 2012 and How It Affects Federal Employee Non-Disclosure Policies, Forms, Certificates, Agreements and Acknowledgments SUMMARY: Acquisition Letter (AL) 2013-08 and Financial Assistance Letter (FAL) 2013-05 provide Contracting Officers with notice of the recently passed,

  13. DATE:

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

    1 DATE: March 10, 2014 TO: Procurement Directors FROM: Director Contract and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management SUBJECT: Implementation of Division D, Titles III and V, and Division E, Title VII of the Consolidated Appropriations Act, 2014, Pub. L. No. 113-76. SUMMARY: Acquisition Letter (AL) 2014-04 and Financial Assistance Letter (FAL) 2014-01 provides implementing instructions and guidance for Division D, Titles III and V, and

  14. DATE:

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

    5 DATE: April 10, 2014 TO: Procurement Directors FROM: Director Contract and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management SUBJECT: Revision to the Procurement Strategy Panel (PSP) Briefing Process SUMMARY: This flash and the attached Acquisition Guide 7.1 revises the PSP process, which is an alternate to a written acquisition plan for procurementsexpected to exceed $100M. This flash and its attachments will be available online at the

  15. DATE:

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

    7 DATE: May 7, 2014 TO: Procurement Directors FROM: Director Contract and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management SUBJECT: Implementation of Division D, Titles III and V, and Division E, Title VII of the Consolidated Appropriations Act, 2014, Pub. L. No. 113-76. SUMMARY: Acquisition Letter (AL) 2014-04 and Financial Assistance Letter (FAL) 2014-01 have been revised to remove language from Section 502 that was not carried forward from

  16. DATE:

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

    4-35 DATE: July 09, 2014 TO: Procurement Directors FROM: Director Contract and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management SUBJECT: Rescission of American Recovery and Reinvestment Act Reporting Requirements. SUMMARY: Financial Assistance Letter (FAL) 2014-xx provides COs with: 1) notice of the recession of the reporting requirements for recipients of ARRA funds in accordance with the recently passed P.L. 113- 76, Consolidated Appropriations

  17. DATE:

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

    3-12 DATE: December 7, 2012 TO: Procurement Directors FROM: Director Contract and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management SUBJECT: Section 301(b) Congressional Notification of Multi-year Contract Award Report Revision for Fiscal Year 2013 SUMMARY: With reference to Acquisition Letter (AL) 2012-08 and Financial Assistance Letter (FAL) 2012-02 regarding Section 301(b) Congressional Notification of Multi-year Contract Award, the spreadsheet

  18. DATE:

    Office of Legacy Management (LM)

    DATE: AUG 12 1991 REPLY TO ATTN OF: EM-421 (J. Wagoner, 3-8147) SUBIECT: Elimination of the Duriron Company Site TO: The File I have reviewed the attached site summary and elimination recommendation for the Duriron Company Site in Dayton, Ohio. I have determined that there is little likelihood of radioactive contamination at this site. Based on the above, the Ouriron Company Site is hereby eliminated from further consideration under the Formerly Utilized Sites Remedial Action Program. W.

  19. DATE:

    Office of Legacy Management (LM)

    a? ,itbd States Government memorandum Department of Energy DATE: APR 15 893 REPLY TO EM-421 (W. Williams, 903-8149) ATTN OF: Authorization for Remedial Action at the Former Associate Aircraft Site in SUBJECT: Fairfield, Ohio TO: W. Seay, DOE Oak Ridge Field Office The former Associate Aircraft Tool and Manufacturing, Inc., site at 3660 Dixie Highway, Fairfield, Ohio, is designated for remedial action under the Formerly Utilized Sites Remedial Action Program (FUSRAP). Force Control Industries is

  20. DATE:

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

    JDA 1/31/13 Jan 31, 2013 DATE: 01/31/2013 x Aardal, Janis D Y-Public, See below. Approved for Public Release; Further Dissemination Unlimited By Janis D. Aardal at 1:25 pm, Jan 31, 2013 DOE/RL-2001-41 Revision 6 SITEWIDE INSTITUTIONAL CONTROLS PLAN FOR HANFORD CERCLA RESPONSE ACTIONS AND RCRA CORRECTIVE ACTIONS Prepared for the U.S. Department of Energy Assistant Secretary for Environmental Management P.O. Box 550 Richland, Washington 99352 Approved for Public Release; Further Dissemination

  1. Date:

    Office of Legacy Management (LM)

    Tetra Tech 3801 Automation Way, Suite 100, Fort Collins, CO 80525 Tel 970.223.9600 Fax 970.223.7171 www. tetratech.com Technical Memorandum To: Rick DiSalvo, Stephen Pitton, Mel Madril From: Jackie Blumberg, PE Company: U.S. Department of Energy Date: December 19, 2013 CC: Tom Chapel, PE; Amber Kauffman, PE Project No.: 114-181750 Re: OLF Berm Height Evaluation Using Site-Specific Data INTRODUCTION Tetra Tech performed statistical analyses on rainfall data collected at the Rocky Flats site over

  2. DATE:

    Office of Legacy Management (LM)

    -RL5- DATE: September 13, 1990 TO: Alexander Williams (w 39 fusrap6 I FROM: Ed Mitchellzm SUBJECT: Elimination Recommendation for American Machine and Foundry in New York City The purpose of this note is to provide the following with respect to the former American Machine and Foundry Company (AMF) in New York City, New York--FUSRAP Considered Site Recommendation (g/13/90). 1 he recommendation is to eliminate the AMF New York City sites. If you agree, then please return an "approved"

  3. DATE:

    Office of Legacy Management (LM)

    OOE F 1325.3 m e m o randum DATE: SEP 23 1988 Department of Energy IL_. 9 REPLY TO AlTN OF, NE-23 SUElJECT. Owner Searches for Potential Sites in Chicago IL, (7 TO: W . Cottrell, ORNL 0. Kozlouski, OTS W h ile in Chicago, Illinois, on September 13, 14, and 15, 1988, I drove to the suspected addresses of several potential FUSRAP sites. No owners were contacted during this activity because most of the work was done after normal working hours or while on the way to the airport when tim e would not

  4. Forecasting Flu

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

    Forecasting Flu March 6, 2016 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 Valle and her team from Los Alamos National Laboratory have developed a global disease-forecasting system that will improve the way we respond to epidemics. Using this model, individuals and public health officials can monitor

  5. RACORO Forecasting

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

    Hartsock CIMMS, University of Oklahoma  ARM AAF Wiki page  Weather Briefings  Observed Weather  Cloud forecasting models  BUFKIT forecast soundings + guidance from Norman NWS enhanced pages and discussions NAM-WRF updated twice/day (12Z and 00Z) Forecast out to 84-hours RUC (updated every 3 hours) Operational RUC forecast only goes out 12 hours (developmental out 24 hours)

  6. Acquisition Forecast

    Broader source: Energy.gov [DOE]

    It is the policy of the Department of Energy (DOE) and the National Nuclear Security Administration (NNSA) to provide timely information to the public regarding DOE/NNSA’s forecast of future prime contracting opportunities and subcontracting opportunities which are available via the Department’s major site and facilities management contractors.

  7. Posting Date: July 16, 2015 Posting Close Date: TBD

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

    July 16, 2015 Posting Close Date: TBD North American Industry Classification System (NAICS) code for the request: 812332 Estimated Subcontract/PO Value TBD Estimated Period of Performance 8-03-15 Estimated RFP/RFQ Release Date: TBD Estimated Award Date: FY 2018 Competition Type: Open Buyer Contact Email: pbeauparlant@lanl.gov Title: Radioactive Laundry and Respirator Services Description of Product or Service Required Radioactive Laundry and Respirator Services * Current forecasted bid

  8. Posting Date: 28 May, 2015 Posting Close Date: TBD

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

    7 Estimated Award Date: TBD Competition Type: TBD Buyer Contact Email: Itmartinez@lanl.gov Title: QA Support Description of Product or Service Required QA Support (Current subcontracts expires 2018) * Current forecasted bid opportunities are subject to change or cancellation due to scope, mission, or funding requirements. * Some procurements are reserved for small businesses. Note the competition type on the forecast matrix to determine if a procurement has been set aside or is open to fair and

  9. Posting Date: 28 May, 2015 Posting Close Date: TBD

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

    5 Estimated Award Date: TBD Competition Type: TBD Buyer Contact Email: m_armijo@lanl.gov Title: Crowdsourcing Description of Product or Service Required Crowdsourcing * Current forecasted bid opportunities are subject to change or cancellation due to scope, mission, or funding requirements. * Some procurements are reserved for small businesses. Note the competition type on the forecast matrix to determine if a procurement has been set aside or is open to fair and reasonable competition. * LANL

  10. Posting Date: 28 May, 2015 Posting Close Date: TBD

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

    300M Estimated Period of Performance: 5 Years Estimated RFP/RFQ Release Date: 2 nd QTR 2018 Estimated Award Date: TBD Competition Type: TBD Buyer Contact Email: pia@lanl.gov Title: Staff Augmentation Services Description of Product or Service Required Staff Augmentation Services (Current subcontract expires 2019) * Current forecasted bid opportunities are subject to change or cancellation due to scope, mission, or funding requirements. * Some procurements are reserved for small businesses. Note

  11. Posting Date: 28 May, 2015 Posting Close Date: TBD

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

    700K Estimated Period of Performance: TBD Estimated RFP/RFQ Release Date: FY 2018 Estimated Award Date: TBD Competition Type: TBD Buyer Contact Email: m_armijo@lanl.gov Title: Poly Com Phones Description of Product or Service Required Poly Com Phones (Current subcontracts expires 2019) * Current forecasted bid opportunities are subject to change or cancellation due to scope, mission, or funding requirements. * Some procurements are reserved for small businesses. Note the competition type on the

  12. Posting Date: 28 May, 2015 Posting Close Date: TBD

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

    238210 Estimated Subcontract/PO Value: TBD Estimated Period of Performance: TBD Estimated RFP/RFQ Release Date: FY 2016 Estimated Award Date: TBD Competition Type: TBD Buyer Contact Email: brianhornung@lanl.gov Title: Fire Alarm Project Support Description of Product or Service Required Fire Alarm Project Support * Current forecasted bid opportunities are subject to change or cancellation due to scope, mission, or funding requirements. * Some procurements are reserved for small businesses. Note

  13. 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...

  14. MEMORANDUM DATE

    Office of Legacy Management (LM)

    DATE :;++, -m--s B-w- -w---m-- SUBJECT: , ::;:: JLLiucd ALTERN&TE e---e---- --------------------------- CITY&da NCIME: ---------------------- - --------------------- J&f STATE: OWNER ( S 1 -----m-e Past 0 Current: ------------------------ Owner contacted 0 -------------------------- 0 yes no; if ye=, date contacted ------w---s-- TYPE OF OPERATION ----w------------ F Research & Development 0 Facility Type 0 Production scale testing F Pilot Scale 0 Manufacturing 0 Bench Scale

  15. MEMORANDUfl DATE

    Office of Legacy Management (LM)

    DATE cl e-w --we-- SUBJECT: __------------------------ _ OWNER (S) -----w-e Pamt a __---------------------- current: -------------------_______ Owner contacted 0 yes 0 no; if yes, date contacted --------w-w-- TYPE OF OPERATION ------------- erearch & Development a Facility Typr Praduction scale trstinq Pilot Scale Bench Seal e Process Theoretical Studies Sample & Analysis n Production 0 Disposal/Storage TYPE OF CONTRACT ---------------- 0 Prim* 7z Subcontract& Purchase Order . Mmuf l

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

    SciTech Connect (OSTI)

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

    2014-05-01

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

  17. 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.

  18. 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...

  19. 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...

  20. NREL: Transmission Grid Integration - Forecasting

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

    generation output by using forecasts that incorporate meteorological data to predict production. Such systems typically provide forecasts at a number of timescales, ranging from...

  1. LED Lighting Forecast | Department of Energy

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

    Publications Market Studies LED Lighting Forecast LED Lighting Forecast The DOE report Energy Savings Forecast of Solid-State Lighting in General Illumination Applications ...

  2. Date | Open Energy Information

    Open Energy Info (EERE)

    Date Jump to: navigation, search Properties of type "Date" Showing 48 properties using this type. A Property:ASHRAE 169 End Date Property:ASHRAE 169 Start Date B Property:Building...

  3. The forecast calls for flu

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

    Laboratory found a way to forecast the flu season and even next week's sickness trends. ... Laboratory found a way to forecast the flu season and even next week's sickness trends. ...

  4. Solar Forecasting | Department of Energy

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

    Systems Integration » Solar Forecasting Solar Forecasting 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. solar energy plants. Part of the SunShot Systems Integration efforts, the Solar Forecasting projects will allow power system operators to integrate more solar energy into the electricity grid, and ensure the economic and reliable delivery of

  5. DATE: | Department of Energy

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

    DATE: DATE: PDF icon DATE: More Documents & Publications Policy Flash 2013-2 Policy Flash 2013-51 311 Notice Aquisition Letter 2013-05 Financial Assistance Letter 2013-03 Acquisition Letter No. AL 2013-03

  6. probabilistic energy production forecasts

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

    probabilistic energy production forecasts - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel Cycle Defense Waste Management

  7. How People Actually Use Thermostats

    SciTech Connect (OSTI)

    Meier, Alan; Aragon, Cecilia; Hurwitz, Becky; Mujumdar, Dhawal; Peffer, Therese; Perry, Daniel; Pritoni, Marco

    2010-08-15

    Residential thermostats have been a key element in controlling heating and cooling systems for over sixty years. However, today's modern programmable thermostats (PTs) are complicated and difficult for users to understand, leading to errors in operation and wasted energy. Four separate tests of usability were conducted in preparation for a larger study. These tests included personal interviews, an on-line survey, photographing actual thermostat settings, and measurements of ability to accomplish four tasks related to effective use of a PT. The interviews revealed that many occupants used the PT as an on-off switch and most demonstrated little knowledge of how to operate it. The on-line survey found that 89% of the respondents rarely or never used the PT to set a weekday or weekend program. The photographic survey (in low income homes) found that only 30% of the PTs were actually programmed. In the usability test, we found that we could quantify the difference in usability of two PTs as measured in time to accomplish tasks. Users accomplished the tasks in consistently shorter times with the touchscreen unit than with buttons. None of these studies are representative of the entire population of users but, together, they illustrate the importance of improving user interfaces in PTs.

  8. 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.

  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. 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:...

  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. Using Wikipedia to forecast diseases

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

    based on today's forecast." Del Valle and her team were able to successfully monitor influenza in the United States, Poland, Japan and Thailand, dengue fever in Brazil and...

  13. 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.

  14. 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

  15. 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.

  16. Solar Energy Market Forecast | Open Energy Information

    Open Energy Info (EERE)

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

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

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

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

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

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

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

  19. Science on Tap - Forecasting illness

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

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

  20. 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.

  1. Solar Forecast Improvement Project | Department of Energy

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

    Solar Forecast Improvement Project Solar Forecast Improvement Project NOAA.png For the Solar Forecast Improvement Project (SFIP), the Earth System Research Laboratory (ESRL) is partnering with the National Center for Atmospheric Research (NCAR) and IBM to develop more accurate methods for solar forecasts using their state-of-the-art weather models. APPROACH NOAA solar.png SFIP has three main goals: 1) to develop solar forecasting metrics tailored to the utility sector; 2) to improve solar

  2. 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.

  3. DATE SUBMITTED: GRADE LEVEL:

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

    two total hours per visit. For more students than that, please plan a visit on another date. To make a request, please complete the form below and submit it to...

  4. Dating the Vinland Map

    ScienceCinema (OSTI)

    None

    2013-07-17

    Scientists from Brookhaven National Laboratory, the University of Arizona, and the Smithsonian Institution used carbon-dating technology to determine the age of a controversial parchment that might be the first-ever map of North America.

  5. TO: FILE DATE

    Office of Legacy Management (LM)

    tlEi?ORANDUH TO: FILE DATE FFtOil: c ----'- Y '%d 6- ----_----_ SUBJECT: SITE NAME: ----------STATE: Owner contacted 0 yes qno; if yes, date contacted ---------__-- TYPE OF OPERATION ----~_--_--~----_ &Research & Development @ Praduction scale testing. 0 Pilat Scale 0 Bench Scale Process a Theoretical Studies 0 Sample & Analysis tin Facility Type R Manufacturing IJ University 0 Research Organization IJ Gavernment Sponsored Facility 0 Other ----------------' --~- 0 Production E

  6. TO: FILE DATE------

    Office of Legacy Management (LM)

    DATE------ la Fp7 ---------__ OWNER(.=) m-----z- Past: -----_------------------ Current: ------------i----------- Owner c:nntacted q ye' s y "0; !' L-----J if yea, date contacted TYPE OF OPERATION -------_------___ 0 Research & Development cl Facility Type 0 Production scale testins 0 Pilot Scale 0 Bench Scale Process E Theoretical Studies Sample SI Analysis [7 Manufacturing i University $ Resear.& Organization Government Sponsored Facility 0 Other -~------------------- 0 Production

  7. MEMORANDUM TO: FILE DATE-

    Office of Legacy Management (LM)

    MEMORANDUM TO: FILE DATE- SUBJECT:' g 1, .,;,A 5 ti ~I' ow, Y. ; + SITE NAME: CITY: ---@h---f&- -________ STATE: -' -;L- 9kE%;f' 4N; -' . PlrrrGj current: ------------------------ ------------- Owner contacted 0' yes if yes, date contacted TYPE OF OPERATION ---_----------_-- q Research & Development .o Production scale testing a Pilot scale 0 Bench Scale Process 0 Thearetical Studies 0 Sample 84 Analysis IJ Production Cl Disposal/Storage Q Prime 0 Subcontract& 0 Purchase Order 0

  8. 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

  9. Forecasting Water Quality & Biodiversity

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

    Forecasting Water Quality & Biodiversity March 25, 2015 Cross-cutting Sustainability Platform Review Principle Investigator: Dr. Henriette I. Jager Organization: Oak Ridge National Laboratory This presentation does not contain any proprietary, confidential, or otherwise restricted information 2015 DOE Bioenergy Technologies Office (BETO) Project Peer Review Goal Statement Addresses the following MYPP BETO goals:  Advance scientific methods and models for measuring and understanding

  10. 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

  11. HEMORANDUH TO: FILE DATE

    Office of Legacy Management (LM)

    HEMORANDUH TO: FILE DATE 1123 lLjl ---WV-------------- FROM: P. s&w+ -------v-----s-- SUBJECT: lJ+ - e;& SITE NAME: LJo"zL - /L,' de Cd -J--h=- ALTERNATE l --e-e-- ------w------- ---,,,' ,m--, NAME: ---------------------- CITY: LL-pL~ ------------ ------------- STATE3 e--w-- OWNER tS) -----w-- Past I --k-!!.l~ -pa L . -v-----w------- Current: Owner contac?-ed 0 yes 0 no; if yes, I+Lff A zid;&m - -------------------------- date contacted ------B--m--- TYPE OF OPERATION

  12. MEMORANDUfl J: FILE DATE

    Office of Legacy Management (LM)

    J: FILE DATE // //r /so -----------w------m FROM: 9. 34oyc -w--------v----- SUBJECT: D3 Bo;s CL&;C J mL-;+J; - Rcc cap 049 /'A :j$: &336;s L-.fh~ w-f L-1 ALE"nirTE __ ------------- --- ---_------------------ CITY: &u+M- - &. -w---v------ ---B-------w STATE: 0 h' -a---- OWNER(S) --pi::;- l>cl, b af.5 CA.-*>J CD Current: Gr;W i- ~U~&;P~ -------------,,' ,-,,,,-, Owner contacted 0 yes jg no; -------------------------- if yes, date contacted ------m------ TYPE OF

  13. DATE: TO: FROM:

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

    POLICY FLASH 2015-30 DATE: TO: FROM: June 18, 2015 Procurement Directors/Contracting Officers ~~-- Chief Contract and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management SUBJECT: Clarification on the Drug Testing Custody and Control Form for Department of Energy Contractors SUMMARY: Effective immediately, please ensure that all DOE contractors use the Forensic Drug Testing Custody and Control Form for their drug testing programs to comply with the

  14. MEMORANDUM TO: FILE DATE

    Office of Legacy Management (LM)

    -.. 37qg: MEMORANDUM TO: FILE DATE =b-- FROM: ---L- _------__ u . SUBJECT: SITE ACl= ALTERNATE NAME: -_______-~-----------------NA~E:__( CITY:--~---------_-STATE:-~~ (2 OWNE!sI_SL f Past- L&cl= w ------------------- ----- Current- w buL.r - ------------ ownq cm-ltacted 0 yes @ "no; if yes, data cnntacte TYPE OF OPERATION -------------_~-~ q Research & Development 0 Production %.cale testing 0 Pilot Scale 0 Bench Scale Process 0 Theoretical Studies 0 Sample 84 Analysis 0 Production

  15. MEtlORANDUM DATE

    Office of Legacy Management (LM)

    iM: iy&j> -------------- MEtlORANDUM DATE .----w-w-- SUBJECTS ALTERNCITE . NAMEr CITY8 -~~i_c;cF_g-~ ___- -----STfiTE~ --------------------- -EL OWNER(S) -------- Past x ------------------------ Currrnt: -------------------------- Owner contacted 0 yes 0 no; if yes, datr contacted ----------B-B TYPE OF OPERATION we s- ------------- Research & Development E Facility Type 0 Production scale testing 0 Pilot Scale ti Bench Seal e Process 0 Theoretical Studies 0 Sample & CInalyris

  16. 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.

  17. Supply Forecast and Analysis (SFA)

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

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

  18. United States Government DATE:

    Office of Legacy Management (LM)

    5oE(E;,8 ' 0 H .2+ L-1 United States Government DATE: MAR 0 8 1994 REPLY TO AlTN OF: EM-421 (W. A. Williams, 903-8149) SUBJECT: Authority Determination -- Former Herring-Hall-Marvin Safe Co., Hamilton, Ohio TO: The File The attached review documents the basis for determining whether the Department of Energy (DOE) has authority for taking remedial action at the former Herring-Hall-Marvin Safe Co. facility in Hamilton, Ohio, under the Formerly Utilized Sites Remedial Action Program (FUSRAP). The

  19. Issuance Date:: February

    Office of Legacy Management (LM)

    Issuance Date:: February 11, 1966 POST-SHOT HYDROLOGI C SAFETY 68296 VUF-1014 FINAL REPORT FALLON, NEVADA OCTOBER 26, 1963 Hazleton-Nuclear Science Corporation October 30, 1965 SPONSORED BY THE ADVANCED RESEARCH PROJECTS AGENCY OF THE DEPARTMENT OF DEFENSE AND THE U. S.ATOMIC ENERGY COMMISSION VELA UNIFORM PROJECT LEG A L NOTICE This report was prepared as an account of Government sponsored work. Neither the United States, nor the Commission, nor any person acting on behalf of the Commission: A.

  20. DATE: REPLY TO

    Office of Legacy Management (LM)

    DOE F 1325.8 (NW ed States Governhent ilmemorandum DATE: REPLY TO ' bPfl29 1993 Al-fN OF: EM-421 (W. W illiams, 903-8149) SUBJECT: Authorization for Remedial Action at the Former Associate Aircraft Site, Fairfield, Ohio TO: Manager, DOE Oak Ridge Field Office This is to notify you that the Former Associated Aircraft Site in Fairfield, Ohio, is designated,for remedial action under the Formerly Utilized Sites Remedial Action Program (FUSRAP). This notification does not constitute a FUSRAP baseline

  1. MEMORANDUM TO: FILE DATE

    Office of Legacy Management (LM)

    FROt+: --L---L---- 3 Lev' vl/\e SUBJECT:' cl; vul;v\q+; 011\ ' ;peco~yyadh--i~o~ :j$E:, CkGme C "TEz!?% ------------- ~' ~~~~f"-___--_-~~-_------- ----------------- CITY: Ch' 1 c-440 ST&TE- I: L - ------ Curr=ntr__--___-__--______________ Owner contacted 0 yes 9 no; if yes, date contacted TYPE OF OPERATION -------------_--- ~Research & Development .m val\/e Qppl p 4' q Facility Type 0 Hlemll s=tii es 0 Production eta e testing L-h Ic~o*/vl 0 Pilot Scale' q Manufacturing 0 Bench

  2. MEMORANDUM TO: FILE DATE

    Office of Legacy Management (LM)

    FROH: ~+dL :fi:k ALTERNATE F~-5~iM-~~IcRe-C~f~-~----NAME: -------.e-- ____ OWNER(S) ------__ past: ~~-~Y~~~~-~~~~~Current: --x+-!!xh)- ___________ l- Owner c:nntacted q yes xno; if yea, date contacted TYPE OF OPERATION -------------____ BR~+earch & Development -a Facility Type @?..Pdtt. r'o UC Ion scale testing 0 Pilot Scale @ Manufacturing 0 Bench Scale Process q University a Theoretical Studies 0 Research Organization 0 Sample & Analysis 0 Government Sponsored Facility 0 Other

  3. MEMORANDUM TO: FILE DATE

    Office of Legacy Management (LM)

    /I // /s 3 ------------------- FROM: D. I&+ ---------------- SUBJECT: 5;le r 3-&-F.. SITE /+yNJs l3 ALTERNATE NAME: -w---- -SF ------------------------------ NAME: CITY: c ;A< ;,+,ZJ+ ------------,-L-----,,,,,, STATE: OH --w-w- OWNER(S) -w---s-- past: /" ' A--F5 ---w-m- -e----v-------- Current: 0~. A-+A.~~ -------------------------- Owner contacted 0 yes 0 no; if yes, date contacted ------------- TYPE OF OPERATION -------e--------w 0 Research & Development 0 Facility Type 0

  4. MEMORANDUM TO: FILE DATE

    Office of Legacy Management (LM)

    5/22/w ------..------------- FROM: D- f&u+ ---------------- SUBJECT: E/;-+&o.. ReC*-C.AB&;O* +L /z&J; &DC,, /Ptrr; CLonr z-r. SITE NAME: _ ALTERNATE ----------WV-- --------------------- NAME: EAT ---- ------------------ CAY: r-led 4' or k -------------------------- STATE: ti Y VW---- OWNER tS) -------- Past: ---Cl&zt.t.r-----~-~- ---- =urr=nt: ti& LPdA Owner cnntacted 0 yes mo; i+ ye8, -------------------------- date contacted ------------- TYPE OF OPERATION

  5. J. C. Fulton

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

    ... sludge from the K West Reactor fuel storage basin. ... Number Title Type Due Date Actual Date Forecast Date Status ... Project Manager for Decommissioning, Waste, Fuels, and ...

  6. 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

  7. UPF Forecast | Y-12 National Security Complex

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

    UPF Forecast UPF Forecast UPF Procurement provides the following forecast of subcontracting opportunities. Keep in mind that these requirements may be revised or cancelled, depending on program budget funding or departmental needs. If you have questions or would like to express an interest in any of the opportunities listed below, contact UPF Procurement. Descriptiona Methodb NAICS Est. Dollar Range RFP release/ Award datec Buyer/ Phone Commodities Equipment Rental FOC 238910 TBD 3Q FY15/ 3Q

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

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

    Influencing Technological Progress in Solar Energy Project Profile: Forecasting and ... energy technologies based on estimates of future rates of progress and adoption. ...

  9. NREL: Resource Assessment and Forecasting Home Page

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

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

  10. 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...

  11. Date Times Group Speakers

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

    Meetings - Spring 2014 Date Times Group Speakers Tues, 1-13 2:30-3:30pm Faculty Meeting Fri, 1-24 12:30-1:30pm Group Research Meeting Emmanuel Giannelis Fri, 1-31 12:30-1:30pm Student & Postdoc Mtg Apostolos Enotiadis; Nikki Ritzert & Megan Holtz Fri, 2-7 12:30-1:30pm Group Research Meeting CHESS Mon, 2-10 2:30-3:30pm Faculty Meeting Will Dichtel Fri, 2-14 12:30-1:30pm Student & Postdoc Mtg Frank DiSalvo Fri, 2-21 12:30-1:30pm Group Research Meeting Lynden Archer Fri, 2-28

  12. FY 2013 Real Property Deferred, Actual, and Required Maintenance...

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

    Real Property Deferred, Actual, and Required Maintenance Reporting Requirement FY 2013 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement PDF icon FY ...

  13. FY 2012 Real Property Deferred, Actual, and Required Maintenance...

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

    Real Property Deferred, Actual, and Required Maintenance Reporting Requirement FY 2012 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement PDF icon FY ...

  14. Table 13. Coal Production, Projected vs. Actual

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

    Coal Production, Projected vs. Actual" "Projected" " (million short tons)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",999,1021,1041,1051,1056,1066,1073,1081,1087,1098,1107,1122,1121,1128,1143,1173,1201,1223 "AEO 1995",,1006,1010,1011,1016,1017,1021,1027,1033,1040,1051,1066,1076,1083,1090,1108,1122,1137 "AEO

  15. Table 22. Energy Intensity, Projected vs. Actual

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

    Energy Intensity, Projected vs. Actual" "Projected" " (quadrillion Btu / $Billion 2005 Chained GDP)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",10.89145253,10.73335719,10.63428655,10.48440125,10.33479508,10.20669515,10.06546105,9.94541493,9.822393757,9.707148466,9.595465524,9.499032573,9.390723436,9.29474735,9.185496812,9.096176848,9.007677565,8.928276581 "AEO

  16. Posting Date: July 16, 2015 Posting Close Date: TBD

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

    July 16, 2015 Posting Close Date: TBD North American Industry Classification System (NAICS) code for the request: 812332 Estimated SubcontractPO Value TBD Estimated Period of...

  17. Caustic-Side Solvent Extraction: Prediction of Cesium Extraction for Actual Wastes and Actual Waste Simulants

    SciTech Connect (OSTI)

    Delmau, L.H.; Haverlock, T.J.; Sloop, F.V., Jr.; Moyer, B.A.

    2003-02-01

    This report presents the work that followed the CSSX model development completed in FY2002. The developed cesium and potassium extraction model was based on extraction data obtained from simple aqueous media. It was tested to ensure the validity of the prediction for the cesium extraction from actual waste. Compositions of the actual tank waste were obtained from the Savannah River Site personnel and were used to prepare defined simulants and to predict cesium distribution ratios using the model. It was therefore possible to compare the cesium distribution ratios obtained from the actual waste, the simulant, and the predicted values. It was determined that the predicted values agree with the measured values for the simulants. Predicted values also agreed, with three exceptions, with measured values for the tank wastes. Discrepancies were attributed in part to the uncertainty in the cation/anion balance in the actual waste composition, but likely more so to the uncertainty in the potassium concentration in the waste, given the demonstrated large competing effect of this metal on cesium extraction. It was demonstrated that the upper limit for the potassium concentration in the feed ought to not exceed 0.05 M in order to maintain suitable cesium distribution ratios.

  18. Radiocarbon Dating, Memories, and Hopes

    DOE R&D Accomplishments [OSTI]

    Libby, W. F.

    1972-10-01

    The history of radiocarbon dating from 1939 to the present is reviewed. The basic principles of radiocarbon dating are that cosmic rays make living things radioactive with {sup 14}C to a certain level fixed by the environment and that at death the intake of food stops so no replenishment of the {sup 14}C steadily lost by the immutable decay occurs. Therefore measurement of the degree of decay gives the time lapse since death, i.e., the radiocarbon age. The equipment developed and experiments performed to measure the specific activity of specimens to be dated are described. The results obtained by world-wide experimenters are discussed. These showed that on simultaneity radiocarbon dating is apparently reliable but that absolute dates may be incorrect by as much as 600 to 700 y. The value of radiocarbon dating to archaeologists, geologists, climatologists, and historians is stressed. (LCL)

  19. Estimated Cost Description Determination Date:

    Office of Environmental Management (EM)

    Revised and posted 2/10/2011 *Title, Location Estimated Cost Description Determination Date: uncertain Transmittal to State: uncertain EA Approval: uncertain $50,000 FONSI: uncertain Determination Date: uncertain Transmittal to State: uncertain EA Approval: uncertain FONSI: uncertain Total Estimated Cost $70,000 Attachment: Memo, Moody to Marcinowski, III, SUBJECT: NEPA 2011 APS for DOE-SRS, Dated: Annual NEPA Planning Summary Environmental Assessments (EAs) Expected to be Initiated in the Next

  20. Dates Fact Sheet.cdr

    Office of Environmental Management (EM)

    DATES is a detection and security information/event management (SIEM) solution enabling asset owners to protect their energy control systems at the network, host, and device level from cyber attacks. DATES complements traditional, signature-based detection with multiple detection algorithms, including model- based and flow anomaly detection and cross-site attack correlation. The DATES detection and SIEM solution gives operators succinct and intuitive attack visualization, with attacks

  1. Dates Fact Sheet.cdr

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

    DATES is a detection and security informationevent management (SIEM) solution enabling asset owners to protect their energy control systems at the network, host, and device level ...

  2. EIA lowers forecast for summer gasoline prices

    Gasoline and Diesel Fuel Update (EIA)

    EIA lowers forecast for summer gasoline prices U.S. gasoline prices are expected to be lower this summer than previously thought. The price for regular gasoline this summer is now expected to average $3.53 a gallon, according to the new monthly forecast from the U.S. Energy Information Administration. That's down 10 cents from last month's forecast and 16 cents cheaper than last summer. After reaching a weekly peak of $3.78 a gallon in late February, pump prices fell nine weeks in a row to $3.52

  3. Text-Alternative Version LED Lighting Forecast

    Broader source: Energy.gov [DOE]

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

  4. 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...

  5. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  6. 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...

  7. 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.

  8. 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.

  9. Property:Deployment Date | Open Energy Information

    Open Energy Info (EERE)

    Deployment Date Jump to: navigation, search Property Name Deployment Date Property Type String Retrieved from "http:en.openei.orgwindex.php?titleProperty:DeploymentDate&oldid...

  10. Property:Achievement Date | Open Energy Information

    Open Energy Info (EERE)

    Achievement Date Jump to: navigation, search Property Name Achievement Date Property Type String Retrieved from "http:en.openei.orgwindex.php?titleProperty:AchievementDate&ol...

  11. Home Energy Score: Analysis & Improvements to Date

    Energy Savers [EERE]

    Home Energy Score: � Analysis & Improvements to Date � Joan Glickman Senior Advisor/Program Manager U.S. Department of Energy July 24, 2012 1 eere.energy.gov Presentation Overview 1) Background 2) Program Improvements 3) Analysis: Efficacy of Tool & Program - Asset Perturbations - Behavior Perturbations - Estimated Energy Use vs. Actual Energy Use (from utility bills) - Time Required for Assessment and Scoring - Blower Door Test Analysis 4) Next Steps & Ongoing Analysis 2

  12. FY 2012 Real Property Deferred, Actual, and Required Maintenance Reporting

    Office of Environmental Management (EM)

    Requirement | Department of Energy Real Property Deferred, Actual, and Required Maintenance Reporting Requirement FY 2012 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement PDF icon FY 2012 DARM Transmittal Letter and Attachment Final.pdf More Documents & Publications FY 2013 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement Real Property Maintenance Reporting Requirement Memorandum (July 13, 2010)

  13. 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.

  14. Hazard Communication Training - Upcoming Implementation Date...

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

    Hazard Communication Training - Upcoming Implementation Date for New Hazard Communication Standard Hazard Communication Training - Upcoming Implementation Date for New Hazard ...

  15. 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.

  16. MEMORANDUM I TO: FILE DATE

    Office of Legacy Management (LM)

    MEMORANDUM I TO: FILE DATE -----_-_- FaOM: ~~,~hkcid!,~- ' ALTERNATE CITY: I\ptw)a.yk --~---_--___-~--~---______ STATE: I current: ------------_------_-~~~~~ if yes, date contacted ____ TYPE OF OPERATION -_---_---------__ 0 Research & Development 6 Facility Type 0 Production scale testing 0 Pilat Scale 0 Bench Scale Process 0 Theoretical Studies Sample $ rraductian & Analysis a Manufacturing I 0 University I (1 Research Organization 0 Government Sponao&ed Facility 0 Cither I

  17. OTS NOTE DATE: TO: FROM:

    Office of Legacy Management (LM)

    TO: FROM: March 25, 1991 A. Williams D. stout P SUBJECT: Elimination Recommendation for the Star Cutter Corporation The .attached memorandum and supporting documents are the basis for our recommendation to eliminate the former Star Cutter Corporation site from further consideration under FUSRAP. The site is located in Farmington Hills, Michigan. Documents discovered to date which indicate use or handling of radioactive material by Star Cutter consist of two Analytical Data Sheets, dated June

  18. Dated:

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

    CERTIFICATE OF SERVICE I hereby certify that a copy of the STIPULATED JOINT MOTION TO STAY THE SCHEDULING ORDER has been sent electronically to the following on May 12, 2015:...

  19. DATE

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    CAES-061 292012 Rev. 04 CAES Microscopy & Characterization Suite (MaCS) Service Request Form Page 1 of 2 Contact Information: Requestor Name: *Researcher Name: Requestor Email:...

  20. DATE:

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    28 am, Mar 26, 2012 119 X X RPP-40149-VOL1, Rev. 2 Integrated Waste Feed Delivery Plan Volume 1 - Process Strategy E. B. West Washington River Protection Solutions, LLC P. J. Certa, T. M. Hohl, J. S. Ritari, B. R. Thompson Washington River Protection Solutions, LLC C. C. Haass Columbia Nuclear International, LLC Richland, WA 99352 U.S. Department of Energy Contract DE-AC27-08RV14800 EDT/ECN: UC: Cost Center: Charge Code: B&R Code: Total Pages: Key Words: Abstract: The Integrated Waste Feed

  1. DATE:

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

    7:53 am, Mar 26, 2012 X X 131 RPP-40149-VOL2, Rev. 2 Integrated Waste Feed Delivery Plan Volume 2 - Campaign Plan J. S. Ritari Washington River Protection Solutions, LLC P. J. Certa, T. M. Hohl, B. R. Thompson, E. B. West Washington River Protection Solutions, LLC C. C. Haass Columbia Nuclear International, LLC Richland, WA 99352 U.S. Department of Energy Contract DE-AC27-08RV14800 EDT/ECN: UC: Cost Center: Charge Code: B&R Code: Total Pages: Key Words: Abstract: The Integrated Waste Feed

  2. DATE:

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

    8:05 am, Mar 26, 2012 X X 189 RPP-40149-VOL3, Rev. 2 Integrated Waste Feed Delivery Plan Volume 3 - Project Plan J. S. Rodriguez Washington River Protection Solutions, LLC J. W. Kelly, D. C. Larsen Washington River Protection Solutions, LLC Richland, WA 99352 U.S. Department of Energy Contract DE-AC27-08RV14800 EDT/ECN: UC: Cost Center: Charge Code: B&R Code: Total Pages: Key Words: Abstract: The Integrated Waste Feed Delivery Plan (IWFDP) describes how waste feed will be delivered to the

  3. DATE

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

    CX Posting No.: DOE-ID-INL-10-008 SECTION A. Project Title: Maintenance and Modification of Well TRA-08 SECTION B. Project Description: TRA-08, a groundwater monitoring well...

  4. DATE

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    Subcontractor equipment such as generators, welders, etc. will be required to meet the opacity requirements established in the IDAPA regulations and INL Title V air permit....

  5. DATE

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    1 SECTION A. Project Title: Nuclear Fabrication Consortium SECTION B. Project Description The mission of the NFC will be accomplished through both public and private funding. The list below outlines the programs that have identified for initiation under the initial DOE funding. Additional programs are envisioned and will be proposed, subject to any applicable budget constraints, to DOE-NE as they become known to EWI, the NFC, and DOE. 1. Automation of Advanced Non-Destructive Evaluation (NDE)

  6. DATE

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    42 SECTION A. Project Title: Innovative Manufacturing Process for Improving the Erosion/Corrosion Resistance of Power Plant Components via Powder Metallurgy & Hot Isostatic Processing Methods - Electric Power Research Institute SECTION B. Project Description The objective of this project is to conduct the necessary design, processing, manufacturing, and validation studies to assess powder metallurgy/hot isostatic processing (PM/HIP) as a method to produce very large near-net shaped (NNS)

  7. DATE

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    4-006 SECTION A. Project Title: Design of SC Walls and Slabs for Impulsive Loading - Purdue University SECTION B. Project Description Purdue University proposes to analytically investigation the behavior and strength of modular steel-plate composite (SC) slabs and floor systems, analytically investigate the behavior and performance of SC structures subjected to impulsive loading including blast effects, experimentally verify the findings of analytical investigations, and develop design

  8. DATE

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    8 SECTION A. Project Title: Full-field Temperature and Strain Measurements at Extreme Temperatures - Utah State University SECTION B. Project Description Utah State University proposes to purchase and install a multi-camera system for recording simultaneous full-field temperature and strain measurements for thermos-mechanically loaded nuclear materials under extreme environments. SECTION C. Environmental Aspects / Potential Sources of Impact The action consists of purchasing equipment to be used

  9. DATE

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    09 SECTION A. Project Title: High Temperature Melt Solution Calorimeter: The Thermodynamic Characterization of Oxides n Nuclear Energy - Clemson University SECTION B. Project Description Clemson University proposes to purchase a High Temperature Melt Calorimeter that will support ongoing work to advance the fundamental understanding of high-temperature ceramic materials used in nuclear energy applications through the use of melt solution calorimetry resulting in uniquely determined experimental

  10. DATE

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    0 SECTION A. Project Title: Enhance Nuclear Education and Training at Aiken Technical College SECTION B. Project Description Aiken Technical College proposes to purchase and install a flow loop trainer to educate and train students for careers in the nuclear industry. SECTION C. Environmental Aspects / Potential Sources of Impact Chemical Use/Storage / Chemical Waste Disposal - No waste is generated during the manufacturing process, however each machine is equipped with a closed loop system

  11. DATE

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    1 SECTION A. Project Title: Nuclear Engineering and Science Equipment for Strategic Fuels Analysis Research in the Nuclear and Radiological Engineering Program at the Georgia Institute of Technology SECTION B. Project Description Georgia Tech proposes to purchase and install an imaging system to go with the existing x-ray source in a fully equipped irradiation laboratory, addition of spectroscopic instruments to perform energy resolution measurements in supplement of imaging, and tissue

  12. DATE

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    2 SECTION A. Project Title: Development of a Research and Education Facility for Evaluation of Environmental Degradation of Advanced Nuclear Materials in Simulated LWR Conditions - University of Idaho SECTION B. Project Description The University of Idaho proposes to a) upgrade the existing static autoclave system in order to simulate the light water reactor conditions without contaminating the high temperature waster with corrosion products; b) install a rotating a cylinder system in the

  13. DATE

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    4 SECTION A. Project Title: In situ Raman Spectroscopy to Enhance Nuclear Materials Research and Education - University of Nevada Reno SECTION B. Project Description The University of Nevada Reno proposes to purchase and install a Raman Spectrometer on the existing water loop for in situ analysis of materials to be used to characterize the surface chemistry of various alloys, understand the effect of mechanical stress on corrosion behavior of alloys, and improve nuclear education at UNR. SECTION

  14. DATE

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    5 SECTION A. Project Title: Nuclear Materials Science and Instrumentation Research Infrastructure Upgrade at Pennsylvania State University SECTION B. Project Description Pennsylvania State University proposes to purchase and install an inductively coupled plasma - atomic emission spectrometer (ICP- AES), glass melting furnace and crucible, and data acquisition system for use in research and education. SECTION C. Environmental Aspects / Potential Sources of Impact Chemical Use/Storage / Chemical

  15. DATE

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    6 SECTION A. Project Title: Equipment for Education, Training, and Research in Advanced Instrumentation for Fluoride Salt Cooled High-Temperature Reactors (FHRs) at The Ohio State University SECTION B. Project Description Ohio State University proposes to purchase and install the equipment necessary to develop and benchmark a non-invasive velocity measurement technique for salt based on short-lived activation products decay, a Fourier Transform Infrared spectrometer to measure the optical

  16. DATE

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    7 SECTION A. Project Title: Impact Test Machine for Nuclear Containment Research - University of Houston SECTION B. Project Description The University of Houston proposes to upgrade the university's Universal Element Tester with an Impact Test Machine to advance the study on impact and shear behavior of the nuclear containment structure. SECTION C. Environmental Aspects / Potential Sources of Impact The action consists of purchasing equipment to be used in research and teaching. The action would

  17. DATE

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    8 SECTION A. Project Title: Integrated Approach to Fluoride High Temperature Reactor (FHR) Technology and Licensing Challenges - Georgia Tech SECTION B. Project Description Georgia Tech, in collaboration with Ohio State University, Texas A&M, Texas A&M - Kingsville, Oak Ridge National Laboratory and several industry and international partners, proposes to follow an integrated approach to address several key technology gaps associated with fluoride high temperature reactors, thereby

  18. DATE

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    3 SECTION A. Project Title: Design/Prototype Fabricate Rail Car for High Rad Mat Transport - Kasgro Rail Corp. SECTION B. Project Description The purpose of this proposal is to obtain a certification from the American Association of Railroads (AAR) on a fully constructed and tested railcar system for transporting spent nuclear fuel (SNF). The transport system will allow transporting SNF by rail to occur at normal rail speeds thus eliminating delays on rail lines and all more rapid transport of

  19. DATE

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    5-085 SECTION A. Project Title: Deep Borehole Field Test (DBFT) Characterization Borehole Drilling and Testing, Pierce County, N.D. - Battelle Memorial Institute SECTION B. Project Description The primary goal of the DBFT program is to drill a 5,000-meter-deep characterization borehole with a 3,000-meter open-hole section across crystalline bedrock, and to conduct scientific testing to characterize the hydrogeologic, geochemical, and geomechanical properties of the near-borehole host rock. The

  20. DATE

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    6-001 SECTION A. Project Title: Environmental Surveillance, Education, and Research Program - Wastren Advantage, Inc. SECTION B. Project Description Wastren Advantage, Inc. (WAI) proposes to continue the Environmental Surveillance, Education, and Research (ESER) program. Specific activities to be carried out may include, but are not limited to actions in the nature of sampling, collection, and characterization of air, water, soil, flora and fauna as well as measurement of ambient radiation

  1. DATE

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    6-002 SECTION A. Project Title: Experimental Verification of Post-Accident iPWR Aerosol Behavior - Electric Power Research Institute, Inc. SECTION B. Project Description EPRI proposes to perform a series of experiments to quantify the most influential decontamination factors and their effect on a class of integrated Pressurized Water Reactor (iPWR) containment designs. The experimental design and method includes development of a thermal hydraulic test loop with an integral reactor and

  2. DATE

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    02 SECTION A. Project Title: INL - Off-Road ATV Use In Support of Engineering Surveys SECTION B. Project Description The proposed action will allow for off-road ATV use near T-24 and T-25 at the Idaho National Laboratory Site. The ATV(s) will be used to survey in support of engineering design for a proposed upgraded haul road within the INL Site. Currently, an Environmental Assessment is being prepared to address upgrading either T-24 or T-25 to establish a site transportation route for the

  3. DATE

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    5 CX Posting No.: DOE-ID-ICP-12-002 SECTION A. Project Title: ICP Routine Maintenance SECTION B. Project Description The purpose of this document is to address actions that meet the intent of the categorical exclusion (CX) B1.3 as described in 10 CFR 1021, Appendix B to Subpart D. Both typical and non-typical types of actions, such as routine maintenance, minor modifications, and custodial services required to support safe and efficient plant operations even if performed on an infrequent basis

  4. DATE

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    2-003 SECTION A. Project Title: CPP-684 - Remote Analytical Laboratory Facility Modifications SECTION B. Project Description The proposed activities are intended to render CPP-684 Remote Analytical Laboratory (RAL) as a limited access area by removing existing operational functions that are currently performed in the facility. In general, the activities will involve (1) removing the need for building heat and overall reduction of power consumption; (2) converting the existing fire protection

  5. DATE

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    2-005 SECTION A. Project Title: INTEC - U-233 Waste Stream Disposition SECTION B. Project Description The proposed action will transfer 171 drums of U-233 waste from the Advanced Mixed Waste Treatment Project (AMWTP) to INTEC for verification, treatment, and repackaging for final disposition at the Nevada National Security Site (NNSS). The U233 drums are a portion of waste historically managed as transuranic as part of the 1995 Idaho Settlement Agreement.The waste management actions will be

  6. DATE

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    4-001 SECTION A. Project Title: INL - Idaho Completion Project Environmental and Regulatory Services Activities SECTION B. Project Description The proposed action addresses the site-wide sampling and monitoring and waste characterization sampling programs that support the Idaho Completion Project (ICP) operations. Actions include:  groundwater monitoring,  day-to-day monitoring activities (i.e., measurement of liquid or gaseous effluents for purposes of characterizing and quantifying

  7. DATE

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    1 SECTION A. Project Title: Spent Resin Removal and Addition of New Resin to Ion Exchange (IX) Columns Located at CPP- 666 SECTION B. Project Description The proposed action will transfer spent resins from hold tanks located inside CPP-666 to on-site vendor-owned and operated resin dewatering equipment (EnergySolutions), with off-site disposal of the dewatered resins at the Nevada National Security Site. This process is required to maintain water cleanliness and remove radionuclides and

  8. DATE

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    2 SECTION A. Project Title: Spent Resin Removal and Addition of New Resin to Ion Exchange (IX) Columns Located at CPP- 666 SECTION B. Project Description The proposed action will transfer spent resins from hold tanks located inside CPP-666 to on-site vendor-owned and operated resin dewatering equipment (EnergySolutions), with off-site disposal of the dewatered resins at the Nevada National Security Site. This process is required to maintain water cleanliness and remove radionuclides and

  9. DATE

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    3 SECTION A. Project Title: TAN - Monitoring Well Drilling Actions SECTION B. Project Description Two new monitoring wells will be drilled in the spring of 2015 within the Test Area North facility. Both wells will be drilled to a total depth of approximately 280 ft. and will be completed with two vapor ports, two pumps, and an inflatable isolation packer. Depending on location, the annular space will be filled with bentonite, silica sand, and bentonite associated with the vapor port filter pack

  10. DATE

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    4 SECTION A. Project Title: INTEC - CPP-603 Large Cask Adaptability SECTION B. Project Description DOE is responsible for the safe storage of Spent Nuclear Fuel (SNF) in its possession as well as obtaining data to verify the condition of SNF currently being stored in large storage casks at the INL Site. To meet this responsibility, DOE needs to open and examine the low-burnup SNF currently in long-term dry storage to verify the condition of the fuel and look for any degradation. DOE examined

  11. DATE

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    6-001 SECTION A. Project Title: INTEC - Macroencapsulation/Overpack Operations in CPP-659 and CPP-1617 SECTION B. Project Description The proposed action will treat mixed low-level waste (MLLW) at the Idaho Nuclear Technology and Engineering Center (INTEC). The treatment process, macroencapsulation, will result in the waste stream meeting the treatment standards for debris and radioactive lead solids (RLS) for disposition at the Nevada National Security Site (NNSS). The macroencapsulation

  12. DATE

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    EC Document No.: DOE-ID-INL-09-002 SECTION A. Project Title: Smoking Shelters SECTION B. Project Description. Install up to three prefabricated outdoor shelters for smokers. Design and install a shelter base so that shelters can be movable. The base shall be designed to prevent shelters from moving or tipping over due to high winds. Specific location for shelters is to be determined, but the shelter bases will be placed atop existing concrete or asphalt such that no subsurface soil disturbance

  13. DATE

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    09-003 SECTION A. Project Title: Removal of Central Facilities Area (CFA)-661 Interior Walls and Mezzanine. SECTION B. Project Description The initial action to be covered under this Environmental Checklist will be removal of the mezzanines from CFA-661 to provide for material storage and work space for the National and Homeland Security (N&HS) Wireless Test Bed project. More specifically, this involves storage of electronic equipment, antennas and antenna masts, personnel supplies, and a

  14. DATE

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    1 SECTION A. Project Title: CFA-696 Power and Plumbing Upgrades SECTION B. Project Description: There is insufficient electrical power in the East Bay and the West Bay of the Central Facility Area (CFA) Transportation Complex to allow the craftsmen to fully utilize the available floor space without the use of extension cords. Additionally, a new hydraulic hose clamper is to be installed in the Parts Room and it needs a dedicated 30A power supply. The craftsmen also need another wash sink in the

  15. DATE

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    5 SECTION A. Project Title: Replace 200,000 Gallon Water Storage Tank at MFC SECTION B. Project Description: The project is to replace the current 200,000 gallon potable water tank at the Idaho National Laboratory (INL) Materials and Fuels Complex (MFC) with a new 300,000 gallon water tank. The existing tank and foundation will be removed and the waste materials managed and disposed under the direction of Waste Generator Services (WGS). The installation area for the new tank will be excavated

  16. DATE

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    6 SECTION A. Project Title: TRA-653 HVAC Modifications SECTION B. Project Description: The proposed project plans to replace the existing blowers, swamp coolers and electric heaters in the Idaho National Laboratory (INL) Test Reactor Area-653 (TRA-653) office area with three roof mounted heating, ventilating and air conditioning (HVAC) units; and install six roof mounted HVAC units at the TRA-653 machine shop area. These modifications are needed to enhance workplace habitability, maintain a more

  17. DATE

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    7 SECTION A. Project Title: TRA-609 Compressed Air System Drain Line Modification and Valve Replacement SECTION B. Project Description: Due to periods of insufficient water flow to the sewer ponds, the clay liners in the ponds can dry out and crack. This proposed action is to add an additional drain line, which will allow clean well water that has been used to cool compressors to then be drained into the sewer system ponds during low flow periods in order to maintain a higher, more consistent

  18. DATE

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    10-009 SECTION A. Project Title Idaho Falls (IF)-608 Uninterrupted Power Supply Upgrade Project SECTION B. Project Description: This project increases the Uninterrupted Power Supply (UPS) capacity in the IF-608 Information Operations and Research Center (IORC) by removing two existing UPS systems (50 KVA and 36 KVA) and installing a 225 KVA system. A ~15 ton cooling unit will be installed on the roof for heat removal. Associated work will include additional electrical panel(s) and electrical

  19. DATE

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    0 SECTION A. Project Title: Test Reactor Cask Implementation. SECTION B. Project Description: This proposed action is a process and facility modification. Background / Purpose & Need The Advanced Test Reactor (ATR) uses the Naval Reactors (NR) Casks to transport test trains between the Naval Reactors Facility (NRF) Expended Core Facility and the ATR. The Naval Reactor (NR) Casks, however, are approaching the end of their design life. In 1997, Bettis initiated a contract for construction of

  20. DATE

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    EC Document No.: DOE-ID-INL-10-011 DIRECTIONS: Responsible Managers, Project Environmental Lead, and Environmental Support personnel complete this form by following the instructions found at the beginning of each section and submit to Environmental Support & Services (environmental.checklist@inl.gov). SECTION A. Project Title: CFA and ATR-Complex Analytical and R&D Laboratory Operation (Overarching) SECTION B. Project Description: This EC replaces overarching EC INL-05-017 due to changes

  1. DATE

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    2 __________________________ 1 DOE's strategic plans included the Nuclear Energy Research and Development Roadmap" (2010 Predecisional draft) and reports such as "Facilities for the Future of Nuclear Energy Research: A Twenty-year Outlook". SECTION A. Project Title: Materials and Fuel Complex (MFC) Infrastructure Upgrades: Sewage Lagoons Upgrades SECTION B. Project Description: MFC Infrastructure Upgrades - MFC Sewage Lagoon Upgrades This EC focuses on upgrades to the existing 2.4

  2. DATE

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    3 SECTION A. Project Title: Relocation of National and Homeland Security New Generation Wireless Test Bed Equipment and Personnel SECTION B. Project Description: This activity is to relocate and consolidate Battelle Energy Alliance, LLC (BEA) National and Homeland Security (NHS) New Generation Wireless Test Bed (NGWTB) program personnel and equipment from Critical Infrastructure Test Range Complex (CITRC) to Central Facilitis Area (CFA). This activity also includes relocating the antenna field

  3. DATE

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    4 SECTION A. Project Title: Materials and Fuels Complex (MFC) Infrastructure Upgrades - Technical Support Building SECTION B. Project Description: Materials and Fuels Complex (MFC) Infrastructure Upgrades - General The number of researchers and operators at the Materials and Fuels Complex has significantly increased, and is projected to increase further in the future to support the expanding research activities at the facility. These activities will require infrastructure upgrades (office space,

  4. DATE

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    5 SECTION A. Project Title: Materials and Fuel Complex (MFC) Infrastructure Upgrades: Modular Office Units SECTION B. Project Description: MFC Infrastructure Upgrades - General The number of researchers and operators at MFC has significantly increased, and is projected to increase further in the future to support the expanding research activities at the facility. These activities will require Infrastructure upgrades (office space, potable water, wastewater treatment, communications, etc.) to

  5. DATE

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    16 SECTION A. Project Title: GaRDS Vehicle X-Ray System Procurement, Installation and Operations SECTION B. Project Description: . This effort will be to procure, install, and operate a Gamma Radiation Detection System (GaRDS) capable of providing X-Ray images of incoming vehicles and delivery trucks. The scanner will be equipped with a 1 Ci Cobalt-60 gamma source and will be installed in building MFC-736. This security building is located on Taylor Blvd approximately one mile south of the

  6. DATE

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    4-017 SECTION A. Project Title: Test Reactor Area (TRA)-653 Conference Room Modifications SECTION B. Project Description: The Advanced Test Reactor (ATR) Maintenance Shop, building Test Reactor Area (TRA)-653, located at the ATR Complex, has an upstairs conference room capable of being used as one large conference room or can be split into two conference rooms by a sliding curtain divider. The current configuration causes meeting interruptions due to the one available door limiting personnel

  7. DATE

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    1 of 2 CX Posting No.: DOE-ID-INL-14-018 SECTION A. Project Title: Materials and Fuel Complex (MFC)-782 Fire Sprinkler Installation SECTION B. Project Description: MFC-782 (Machine Shop) does not currently have a fire sprinkler system. In order to be in compliance with National Fire Protection Association (NFPA) requirements, an automated sprinkler system needs to be installed. The proposed project would consist of removing existing fire water line, drain line, potable water line, fire alarm

  8. DATE

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    Idaho National Laboratory Page 1 of 2 CX Posting No.: DOE-ID-INL-14-019 SECTION A. Project Title: Advanced Test Reactor (ATR) Electronic Message Board Installation SECTION B. Project Description: The scope of work for this project involves the installation of a new electronic information sign at the south end of the sidewalk by the guardhouse (Test Reactor Area [TRA]-658). The sign would be mounted on metal posts just south of the first sidewalk light pole. The new sign would be powered from the

  9. DATE

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    Environmental Checklist Page 1 of 1 CX Posting No.: DOE-ID-INL-14-021 SECTION A. Project Description: Remote Closure Switch for Test Reactor Area (TRA)-786 Output Breaker SECTION B. Project Description: . The TRA-786 diesel generator output breaker has a high arc flash calculation that requires the operator to use heavy, cumbersome personal protective equipment (PPE) when closing the breaker. This breaker is located in the doorway of a trailer that is approximately 5 feet off the ground. There

  10. DATE

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    DOE-ID-ICP-16-001 R1 SECTION A. Project Title: INTEC - Macroencapsulation/Overpack Operations in CPP-659 and CPP-1617, Rev. 1 SECTION B. Project Description The proposed action will treat mixed low-level waste (MLLW) at the Idaho Nuclear Technology and Engineering Center (INTEC). The treatment process, macroencapsulation, will result in the waste stream meeting the treatment standards for debris and radioactive lead solids (RLS) for disposition at the Nevada National Security Site (NNSS). The

  11. DATE

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    to give the facility the ability to perform tritium analysis. Additionally, under NRC License R-83, Texas A&M will up rate the reactor power from 1MW to 1.5 MW and purchase...

  12. DATE

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    Potential Sources of Impact Chemical UseStorage - Work will be conducted in a chemistry laboratory using chemical reagents, acids, alkalis, and solvents. Chemical Waste...

  13. DATE

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    Electrically-Assisted Tubing Processes for Enhancing Manufacturability of Oxide Dispersion Strengthened Structural Materials for Nuclear Reactor Applications - Northwestern...

  14. DATE

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

    ... rods from light water reactors would be processed as ... gasoline pumps, non road power take offs, laboratory ... into standby (inactive) status 4.25 Reactivating buildings ...

  15. DATE

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

    may be used. However, typical abandonments would use a backhoe or jack hammer to breakup existing concrete pads and have minimal excavation around the casing. The scope of...

  16. DATE:

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

    and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management SUBJECT: Implementation of Division F, Title I, Title II, and Title III ...

  17. DATE:

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

    and Financial Assistance Policy Division Office of Policy Office of Acquisition and Project Management SUBJECT: Implementation of Division D, Titles III and V, and Division E, ...

  18. DATE:

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

    indicated by the moderate (0.454) R 2 value. Observation of the plot shows considerable matching of 'peaks and valleys' indicating there is probably some retained gas in the...

  19. DATE

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

    replacement of conductors of the same nominal voltage, poles, circuit breakers, transformers, capacitors, crossarms, insulators, and downed transmission lines N. Routine...

  20. Date

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

    that Sandia contracts are settled for a reasonable amount and that no instances of fraud related to these contracts is apparent. We will not report on the adequacy of your...

  1. DATE:

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

    has been revised. The subject form has been posted on the DOE Financial Assistance web page on the Recipients Page under the Financial Assistance Forms and Information for...

  2. DATE

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

    and Reinvestment Act (ARRA) Reactive Tracers project will be conducted at both the Raft River hydrothermal site in South Central Idaho and at the INL Research Center in Idaho...

  3. DATE

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

    or CERCLA-excluded petroleum and natural gas products that pre-exist in the environment such that there would be uncontrolled or unpermitted releases; 4) adversely affect...

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

    SciTech Connect (OSTI)

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

    2010-04-20

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

  5. FY 2013 Real Property Deferred, Actual, and Required Maintenance Reporting

    Office of Environmental Management (EM)

    Requirement | Department of Energy Real Property Deferred, Actual, and Required Maintenance Reporting Requirement FY 2013 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement PDF icon FY 2013 DARM Transmittal Letter and Attachment Final.pdf More Documents & Publications FY 2012 Real Property Deferred, Actual, and Required Maintenance Reporting Requirement FY_09_DM_RM_AM_Reporting_Memo_and_attachment_072009.pdf Real Property Maintenance Reporting Requirement

  6. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...

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

    b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2007 and Projected 2008 through 2012 " ,"(Megawatts and 2007 ...

  7. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...

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

    b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2006 and Projected 2007 through 2011 " ,"(Megawatts and 2006 ...

  8. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    2011" ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2009 and Projected 2010 through 2014 "...

  9. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2007 and Projected 2008 through 2012 " ,"(Megawatts and 2007...

  10. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    2010" ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2008 and Projected 2009 through 2013 "...

  11. ,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...

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

    a. Noncoincident Summer Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2006 and Projected 2007 through 2011 " ,"(Megawatts and 2006...

  12. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...

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

    2007" ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, " ,"2005 and Projected 2006 through 2010 "...

  13. ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...

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

    2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2009 and Projected 2010 through 2014 " ,"(Megawatts and 2009...

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

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

    rely on an array of VG forecasts suited to different purposes. Some of the most common types of VG forecasts are defined below: 2 This report is available at no cost from the...

  16. 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...

  17. 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.

  18. NREL: Resource Assessment and Forecasting - Capabilities

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

    Capabilities Best Practices Handbook Helps Industry Collect and Interpret Solar Resource Data Read about this new comprehensive resource for the solar industry. NREL's resource assessment and forecasting research staff provides expertise in renewable energy measurement and instrumentation. Major capabilities include solar resource measurement, instrument calibration, instrument characterization, solar monitoring training, and standards development and information dissemination. Solar Resource

  19. 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.

  20. 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.

  1. 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.

  2. 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)

  3. 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...

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

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

    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

  5. Uncertainty Reduction in Power Generation Forecast Using Coupled

    Office of Scientific and Technical Information (OSTI)

    Wavelet-ARIMA (Conference) | SciTech Connect Conference: 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

  6. ANL Software Improves Wind Power Forecasting | Department of Energy

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

    ANL Software Improves Wind Power Forecasting ANL Software Improves Wind Power Forecasting May 1, 2012 - 3:19pm Addthis This is an excerpt from the Second Quarter 2012 edition of the Wind Program R&D Newsletter. Since 2008, Argonne National Laboratory and INESC TEC (formerly INESC Porto) have conducted a research project to improve wind power forecasting and better use of forecasting in electricity markets. One of the main results from the project is ARGUS PRIMA (PRediction Intelligent

  7. Today's Forecast: Improved Wind Predictions | Department of Energy

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

    Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical

  8. Property:StartDate | Open Energy Information

    Open Energy Info (EERE)

    StartDate Jump to: navigation, search This is a property of type Date. Pages using the property "StartDate" Showing 25 pages using this property. (previous 25) (next 25) 4 4-County...

  9. Property:EndDate | Open Energy Information

    Open Energy Info (EERE)

    EndDate Jump to: navigation, search This is a property of type Date. Pages using the property "EndDate" Showing 25 pages using this property. (previous 25) (next 25) 4 4-County...

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

    SciTech Connect (OSTI)

    Wilczak, J. 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.

    2015-10-11

    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.

  11. 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.

  12. 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.

  13. Table 5. Domestic Crude Oil Production, Projected vs. Actual

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

    Domestic Crude Oil Production, Projected vs. Actual" "Projected" " (million barrels)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,201...

  14. Table 5. Domestic Crude Oil Production, Projected vs. Actual

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

    Domestic Crude Oil Production, Projected vs. Actual Projected (million barrels) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012...

  15. Table 14b. Average Electricity Prices, Projected vs. Actual

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

    b. Average Electricity Prices, Projected vs. Actual" "Projected Price in Nominal Dollars" " (nominal dollars, cents per kilowatt-hour)" ,1993,1994,1995,1996,1997,1998,1999,2000,200...

  16. Table 14b. Average Electricity Prices, Projected vs. Actual

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

    b. Average Electricity Prices, Projected vs. Actual Projected Price in Nominal Dollars (nominal dollars, cents per kilowatt-hour) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002...

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. Save the Date - NTSF 2013

    Office of Environmental Management (EM)

    Save the Date U.S. Department of Energy National Transportation Stakeholders Forum May 14-16 th , 2013 Buffalo, New York Please mark your calendar to attend the next meeting of the U.S. Department of Energy (DOE) National Transportation Stakeholders Forum (NTSF) scheduled for May 14-16, 2013. This annual event will be held at the Hyatt Regency Hotel, located near the downtown business and entertainment districts in Buffalo, New York. The 2013 meeting is co-sponsored by DOE's Offices of

  2. Estimated Cost Description Determination Date:

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

    Title, Location Estimated Cost Description Determination Date: 2010 LCLS Undulator 2 is envisioned to be a 0.2 - 2keV FEL x-ray source, capable of delivering x-rays to End Station A (ESA), located in the existing Research Yard at SLAC. It will also be configurable as a non- FEL hard x-ray source capable of delivering a chirped x-ray pulse for single-shot broad-spectrum measurements. The project would entail reconstruction of the electron beam transport to End Station A, construction and

  3. 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.

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

    SciTech Connect (OSTI)

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

    2010-01-01

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

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2000-08-31

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  7. "Title","Creator/Author","Publication Date","OSTI Identifier...

    Office of Scientific and Technical Information (OSTI)

    ACIDS; CALIFORNIA; CHAINS; CHEMISTRY; DISEASES; FIBROSIS; FORECASTING; GENETICS; OPTIMIZATION; PROTEIN STRUCTURE; PROTEINS; QUEUES; SHAPE; SIMULATION PROTEIN STRUCTURE...

  8. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

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

  9. Module 6 - Metrics, Performance Measurements and Forecasting | Department

    Energy Savers [EERE]

    of Energy 6 - Metrics, Performance Measurements and Forecasting Module 6 - Metrics, Performance Measurements and Forecasting This module focuses on the metrics and performance measurement tools used in Earned Value. This module reviews metrics such as cost and schedule variance along with cost and schedule performance indices. In addition, this module will outline forecasting tools such as estimate to complete (ETC) and estimate at completion (EAC)

  10. Funding Opportunity Announcement for Wind Forecasting Improvement Project

    Office of Environmental Management (EM)

    in Complex Terrain | Department of Energy Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain April 4, 2014 - 9:47am Addthis 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 that take place in complex

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

    Office of Environmental Management (EM)

    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

  12. NREL: Resource Assessment and Forecasting - Webmaster

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

    Webmaster Use this form to send us your comments and questions, report problems with the site, or ask for help finding information on the site. Please enter your name and email address in the boxes provided, then type your message below. When you are finished, click "Send Message." NOTE: If you enter your e-mail address incorrectly, we will be unable to reply. Your name: Your email address: Your message: Send Message Printable Version Resource Assessment & Forecasting Home

  13. 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.

  14. 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.

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

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

    research project whose overarching goals are to improve the accuracy of short-term wind energy forecasts, and to demonstrate the economic value of these improvements. WFIP Round...

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

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

    Opportunity, DOE is funding solar projects that are helping utilities, grid operators, solar power plant owners, and other stakeholders better forecast when, where, and how much...

  17. 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...

  18. 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...

  19. 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 " " % % &...

  20. 2014 NEJC Save the Date (English)

    Broader source: Energy.gov [DOE]

    2014 National Environmental Justice Conference and Training Program  Save the Date, March 26 to 28, 2014

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

    SciTech Connect (OSTI)

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

    1997-01-07

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

  2. 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.

  3. Property:NEPA ApplicationDate | Open Energy Information

    Open Energy Info (EERE)

    ApplicationDate Jump to: navigation, search Property Name NEPA ApplicationDate Property Type Date This is a property of type Date. Pages using the property "NEPA ApplicationDate"...

  4. 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.

  5. Table 4. Total Petroleum Consumption, Projected vs. Actual

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

    Total Petroleum Consumption, Projected vs. Actual" "Projected" " (million barrels)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",6449.55,6566.35,6643,6723.3,6810.9,6880.25,6956.9,7059.1,7124.8,7205.1,7296.35,7376.65,7446,7522.65,7595.65,7665,7712.45,7774.5 "AEO

  6. Table 6. Petroleum Net Imports, Projected vs. Actual

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

    Petroleum Net Imports, Projected vs. Actual" "Projected" " (million barrels)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",2934.6,3201.05,3361.65,3504,3657.3,3737.6,3879.95,3993.1,4098.95,4212.1,4303.35,4398.25,4474.9,4540.6,4584.4,4639.15,4668.35,4672 "AEO

  7. FRACTIONAL CRYSTALLIZATION FLOWSHEET TESTS WITH ACTUAL TANK WASTE

    SciTech Connect (OSTI)

    HERTING, D.L.

    2007-04-13

    Laboratory-scale flowsheet tests of the fractional crystallization process were conducted with actual tank waste samples in a hot cell at the 2224 Laboratory. The process is designed to separate medium-curie liquid waste into a low-curie stream for feeding to supplemental treatment and a high-curie stream for double-shell tank storage. Separations criteria (for Cesium-137 sulfate and sodium) were exceeded in all three of the flowsheet tests that were performed.

  8. FRACTIONAL CRYSTALLIZATION FLOWSHEET TESTS WITH ACTUAL TANK WASTE

    SciTech Connect (OSTI)

    HERTING, D.L.

    2006-10-18

    Laboratory-scale flowsheet tests of the fractional crystallization process were conducted with actual tank waste samples in a hot cell at the 222-S Laboratory. The process is designed to separate medium-curie liquid waste into a low-curie stream for feeding to supplemental treatment and a high-curie stream for double-shell tank storage. Separations criteria (for Cs-137 sulfate, and sodium) were exceeded in all three of the flowsheet tests that were performed.

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

    Energy Savers [EERE]

    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

  10. 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.

  11. 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...

  12. Energy Savings Forecast of Solid-State Lighting in General Illuminatio...

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

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

  13. Property:GEAReportDate | Open Energy Information

    Open Energy Info (EERE)

    the project. Pages using the property "GEAReportDate" Showing 1 page using this property. L Los Humeros III Geothermal Power Plant + 19 December 2013 + Retrieved from "http:...

  14. Categorical Exclusion (CX) Determinations By Date | Department...

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

    CX(s) Applied: DOEEA-1914 National Renewable Energy Laboratory (NREL) Date: 072815 Location(s): CO Office(s): Golden Field Office July 21, 2015 CX-100313...

  15. Nuclear Speed-Dating | Department of Energy

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

    Speed-Dating Nuclear Speed-Dating March 10, 2015 - 10:48am Addthis Photo courtesy of Idaho National Laboratory. Photo courtesy of Idaho National Laboratory. Pat Adams Pat Adams Digital Content Specialist, Office of Public Affairs Nuclear Speed-Dating The future of nuclear energy needs smart, creative thinkers. That's why more than 120 experts met up last week to "speed-date" each other's ideas. Storified by Energy Department * Tue, Mar 10 2015 15:28:50 Nuclear Wetlands * James Marvin

  16. ,"Table 1. Net Energy For Load, Actual and Projected by North...

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

    1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Assessment Area," ,"1990-2010 Actual, 2011-2015 Projected" ,"(Thousands of...

  17. 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.

  18. 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.

  19. Table 12. Total Coal Consumption, Projected vs. Actual Projected

    Gasoline and Diesel Fuel Update (EIA)

    Total Coal Consumption, Projected vs. Actual Projected (million short tons) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 920 928 933 938 943 948 953 958 962 967 978 990 987 992 1006 1035 1061 1079 AEO 1995 935 940 941 947 948 951 954 958 963 971 984 992 996 1002 1013 1025 1039 AEO 1996 937 942 954 962 983 990 1004 1017 1027 1033 1046 1067 1070 1071 1074 1082 1087 1094 1103 AEO 1997 948 970 987 1003 1017 1020 1025 1034 1041 1054

  20. Table 13. Coal Production, Projected vs. Actual Projected

    Gasoline and Diesel Fuel Update (EIA)

    Coal Production, Projected vs. Actual Projected (million short tons) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 999 1021 1041 1051 1056 1066 1073 1081 1087 1098 1107 1122 1121 1128 1143 1173 1201 1223 AEO 1995 1006 1010 1011 1016 1017 1021 1027 1033 1040 1051 1066 1076 1083 1090 1108 1122 1137 AEO 1996 1037 1044 1041 1045 1061 1070 1086 1100 1112 1121 1135 1156 1161 1167 1173 1184 1190 1203 1215 AEO 1997 1028 1052 1072 1088

  1. Table 15. Total Electricity Sales, Projected vs. Actual Projected

    Gasoline and Diesel Fuel Update (EIA)

    Total Electricity Sales, Projected vs. Actual Projected (billion kilowatt-hours) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 2843 2891 2928 2962 3004 3039 3071 3112 3148 3185 3228 3263 3298 3332 3371 3406 3433 3469 AEO 1995 2951 2967 2983 3026 3058 3085 3108 3134 3166 3204 3248 3285 3321 3357 3396 3433 3475 AEO 1996 2973 2998 3039 3074 3106 3137 3173 3215 3262 3317 3363 3409 3454 3505 3553 3604 3660 3722 3775 AEO 1997 3075

  2. Table 4. Total Petroleum Consumption, Projected vs. Actual

    Gasoline and Diesel Fuel Update (EIA)

    Petroleum Consumption, Projected vs. Actual Projected (million barrels) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 6450 6566 6643 6723 6811 6880 6957 7059 7125 7205 7296 7377 7446 7523 7596 7665 7712 7775 AEO 1995 6398 6544 6555 6676 6745 6822 6888 6964 7048 7147 7245 7337 7406 7472 7537 7581 7621 AEO 1996 6490 6526 6607 6709 6782 6855 6942 7008 7085 7176 7260 7329 7384 7450 7501 7545 7581 7632 7676 AEO 1997 6636 6694 6826

  3. Table 6. Petroleum Net Imports, Projected vs. Actual Projected

    Gasoline and Diesel Fuel Update (EIA)

    Petroleum Net Imports, Projected vs. Actual Projected (million barrels) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 2935 3201 3362 3504 3657 3738 3880 3993 4099 4212 4303 4398 4475 4541 4584 4639 4668 4672 AEO 1995 2953 3157 3281 3489 3610 3741 3818 3920 4000 4103 4208 4303 4362 4420 4442 4460 4460 AEO 1996 3011 3106 3219 3398 3519 3679 3807 3891 3979 4070 4165 4212 4260 4289 4303 4322 4325 4347 4344 AEO 1997 3099 3245 3497

  4. Table 12. Total Coal Consumption, Projected vs. Actual

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

    Total Coal Consumption, Projected vs. Actual" "Projected" " (million short tons)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",920,928,933,938,943,948,953,958,962,967,978,990,987,992,1006,1035,1061,1079 "AEO 1995",,935,940,941,947,948,951,954,958,963,971,984,992,996,1002,1013,1025,1039 "AEO

  5. Table 14a. Average Electricity Prices, Projected vs. Actual

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

    a. Average Electricity Prices, Projected vs. Actual" "Projected Price in Constant Dollars" " (constant dollars, cents per kilowatt-hour in ""dollar year"" specific to each AEO)" ,"AEO $ Year",1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",1992,6.799,6.7999,6.9,6.9,6.9,6.9,7,7,7.1,7.1,7.2,7.2,7.2,7.3,7.3,7.4,7.5,7.6 "AEO

  6. Table 15. Total Electricity Sales, Projected vs. Actual

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

    Total Electricity Sales, Projected vs. Actual" "Projected" " (billion kilowatt-hours)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",2843,2891,2928,2962,3004,3039,3071,3112,3148,3185,3228,3263,3298,3332,3371,3406,3433,3469 "AEO 1995",,2951,2967,2983,3026,3058,3085,3108,3134,3166,3204,3248,3285,3321,3357,3396,3433,3475 "AEO

  7. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

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

  8. Approved for Public Release; Further Dissemination Unlimited

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

    ... Number Title Due Date Actual Date Forecast Date Status Comment M-016-175 Begin sludge ... L. T. Blackford Vice President and Project Manager for Decommissioning, Waste, Fuels, and ...

  9. Property:OpenEI/PublicationDate | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search Property Name OpenEIPublicationDate Property Type Date Description The date the resource was first published. Retrieved from "http:...

  10. Property:Geothermal/ProjectEndDate | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search Property Name GeothermalProjectEndDate Property Type Date Description Project End Date Retrieved from "http:en.openei.orgw...

  11. Property:Geothermal/ProjectStartDate | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search Property Name GeothermalProjectStartDate Property Type Date Description Project Start Date Retrieved from "http:en.openei.orgw...

  12. Property:Estimated End Date | Open Energy Information

    Open Energy Info (EERE)

    Estimated End Date Jump to: navigation, search Property Name Estimated End Date Property Type String Pages using the property "Estimated End Date" Showing 4 pages using this...

  13. Pretreated Slurries; Issue Date: August 2010; Revision Date: July 2011 (Version 07-08-2011)

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

    Summative Mass Closure Laboratory Analytical Procedure (LAP) Review and Integration: Pretreated Slurries Issue Date: August 2010 Revision Date: July 2011 (Version 07-08-2011) J. Sluiter and A. Sluiter Technical Report NREL/TP-510-48825 Revised July 2011 Technical Report Summative Mass Closure NREL/TP-510-48825 Revised July 2011 Laboratory Analytical Procedure (LAP) Review and Integration: Pretreated Slurries Issue Date: August 2010 Revision Date: July 2011 (Version 07-08-2011) J. Sluiter and A.

  14. 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....

  15. 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.

  16. 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,...

  17. 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.

  18. 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.

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

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

    The Energy Department will present a live webinar titled "Solar Forecasting Metrics" on Thursday, February 13, from 3:00 p.m. to 5:00 p.m. Eastern Standard Time. During this ...

  20. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

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

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

    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 ...

  2. 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

  3. 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

  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. Energy Department Forecasts Geothermal Achievements in 2015 | Department of

    Office of Environmental Management (EM)

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

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

    Office of Environmental Management (EM)

    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

  7. Property:File/CreationDate | Open Energy Information

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    CreationDate Jump to: navigation, search Property Name FileCreationDate Property Type Date Description Original creation date for the file. Note that this is usually not the same...

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    DecisionDocumentDate Jump to: navigation, search Property Name NEPA DecisionDocumentDate Property Type Date This is a property of type Date. Subproperties This property has the...

  11. Table 10. Natural Gas Net Imports, Projected vs. Actual

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

    Natural Gas Net Imports, Projected vs. Actual" "Projected" " (trillion cubic feet)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",2.02,2.4,2.66,2.74,2.81,2.85,2.89,2.93,2.95,2.97,3,3.16,3.31,3.5,3.57,3.63,3.74,3.85 "AEO 1995",,2.46,2.54,2.8,2.87,2.87,2.89,2.9,2.9,2.92,2.95,2.97,3,3.03,3.19,3.35,3.51,3.6 "AEO

  12. Table 16. Total Energy Consumption, Projected vs. Actual

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

    Total Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",88.02,89.53,90.72,91.73,92.71,93.61,94.56,95.73,96.69,97.69,98.89,100,100.79,101.7,102.7,103.6,104.3,105.23 "AEO 1995",,89.21,89.98,90.57,91.91,92.98,93.84,94.61,95.3,96.19,97.18,98.38,99.37,100.3,101.2,102.1,102.9,103.88 "AEO

  13. Table 9. Natural Gas Production, Projected vs. Actual

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

    Natural Gas Production, Projected vs. Actual" "Projected" " (trillion cubic feet)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",17.71,17.68,17.84,18.12,18.25,18.43,18.58,18.93,19.28,19.51,19.8,19.92,20.13,20.18,20.38,20.35,20.16,20.19 "AEO 1995",,18.28,17.98,17.92,18.21,18.63,18.92,19.08,19.2,19.36,19.52,19.75,19.94,20.17,20.28,20.6,20.59,20.88 "AEO

  14. 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

  15. Date centerdTimes New Roman

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

    April 2010 DOE F 1325.8 (493) United States Government Department of Energy Memorandum DATE: April 6, 2010 Audit Report Number: OAS-RA-L-10-01 REPLY TO ATTN TO: IG-32 (A10RA006)...

  16. Categorical Exclusion (CX) Determinations By Date | Department...

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

    Air Conditioners RIN: 1904-AC82 CX(s) Applied: B5.1 EERE- Buildings Technology Program Date: 06172015 Location(s): Nationwide Office(s): Golden Field Office June 16, 2015...

  17. Date centerdTimes New Roman

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

    April 2010 DOE F 1325.8 (493) United States Government Department of Energy memorandum DATE: April 27, 2010 Audit Report Number: OAS-RA-L-10-04 REPLY TO ATTN TO: IG-32 (A10RA025)...

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

    2010 DOE F 1325.8 (08-93) United States Government Department of Energy Memorandum DATE: April 23, 2010 Audit Report Number: OAS-RA-L-10-03 REPLY TO ATTN OF: IG-34 (A09ID019)...

  19. Categorical Exclusion (CX) Determinations By Date | Department...

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

    Number: DE-EE0007137 CX(s) Applied: A9, B3.6, B3.11 Solar Energy Technologies Office Date: 09102015 Location(s): AL Office(s): Golden Field Office September 8, 2015 CX-100362...

  20. Categorical Exclusion (CX) Determinations By Date | Department...

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

    Products Award Number: DE-EE0006875 CX(s) Applied: B3.6 Bioenergy Technologies Office Date: 05152015 Location(s): CA Office(s): Golden Field Office May 15, 2015 CX-100243...

  1. Willard Libby, Radiocarbon, and Carbon Dating

    Office of Scientific and Technical Information (OSTI)

    Willard Libby, Radiocarbon, and Carbon Dating Resources with Additional Information * Radiocarbon Dating Willard Libby Courtesy UCLA Photography 'Scientific discoveries of various magnitudes are constantly occurring in myriad fields of study. It is a rarity, however, to make a breakthrough that not only has an impact on an individual field but also revolutionizes scientific thought across multiple disciplines. Willard Frank Libby accomplished this feat. Libby first proposed his idea of carbon

  2. MEMORANDUM TO: FILE I' DATE---- SITE

    Office of Legacy Management (LM)

    I' DATE---- SITE -7Jwl-h-G' ALTERNATE NAME: ~------~~~~~~~~----~___________________N~~~: --------------------- CITY: ti -------------------------- STATE: YM/% ------ OWNER (S.) -----___ p==t: -zLL%ddk ----------- Curr="t: _-ti--A-i- ________ Owner contacted 0 yes &no; if yee, date contacted ----------_-- TYPE OF OPERATION ~~~------~~~~---- q Research & Development 0 Production scale testing Cl Pilot Scale 0 Bench Scale Process 0 Thearetical Studies 0 Sample 84 Analysis 0 Facility

  3. MEMORANDUM TO: FILE, OH. 0 DATE

    Office of Legacy Management (LM)

    FILE, OH. 0 DATE d4, ------------------- FROM: b. x&,.& ---------S-----W SUBJECT: 1-3/;4*~ i&-h /LCL)&l&OAiOH h fi Q-cc& )2~see~ SITE NAME: ----fl eAd4 RQJ-cL ALTERNATE __-_-_---------------------------- NAME: ---------------------- CITY: -------------------------- STATE: B---m- OWNER(S) -------- Past: JAwd* ------------------------ Current: _------------------------- Owwr contacted 0 yes rno; if yes, date contacted B-m -----w-v TYPE OF OPERATION ----------------- pg

  4. 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.

  5. Table 10. Natural Gas Net Imports, Projected vs. Actual Projected

    Gasoline and Diesel Fuel Update (EIA)

    Natural Gas Net Imports, Projected vs. Actual Projected (trillion cubic feet) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 2.02 2.40 2.66 2.74 2.81 2.85 2.89 2.93 2.95 2.97 3.00 3.16 3.31 3.50 3.57 3.63 3.74 3.85 AEO 1995 2.46 2.54 2.80 2.87 2.87 2.89 2.90 2.90 2.92 2.95 2.97 3.00 3.03 3.19 3.35 3.51 3.60 AEO 1996 2.56 2.75 2.85 2.88 2.93 2.98 3.02 3.06 3.07 3.09 3.12 3.17 3.23 3.29 3.37 3.46 3.56 3.68 3.79 AEO 1997 2.82 2.96

  6. Table 14a. Average Electricity Prices, Projected vs. Actual

    Gasoline and Diesel Fuel Update (EIA)

    a. Average Electricity Prices, Projected vs. Actual Projected Price in Constant Dollars (constant dollars, cents per kilowatt-hour in "dollar year" specific to each AEO) AEO $ Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 1992 6.80 6.80 6.90 6.90 6.90 6.90 7.00 7.00 7.10 7.10 7.20 7.20 7.20 7.30 7.30 7.40 7.50 7.60 AEO 1995 1993 6.80 6.80 6.70 6.70 6.70 6.70 6.70 6.80 6.80 6.90 6.90 6.90 7.00 7.00 7.10 7.10 7.20

  7. Table 16. Total Energy Consumption, Projected vs. Actual Projected

    Gasoline and Diesel Fuel Update (EIA)

    Total Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 88.0 89.5 90.7 91.7 92.7 93.6 94.6 95.7 96.7 97.7 98.9 100.0 100.8 101.7 102.7 103.6 104.3 105.2 AEO 1995 89.2 90.0 90.6 91.9 93.0 93.8 94.6 95.3 96.2 97.2 98.4 99.4 100.3 101.2 102.1 102.9 103.9 AEO 1996 90.6 91.3 92.5 93.5 94.3 95.1 95.9 96.9 98.0 99.2 100.4 101.4 102.1 103.1 103.8 104.7 105.5 106.5 107.2

  8. Table 17. Total Delivered Residential Energy Consumption, Projected vs. Actual

    Gasoline and Diesel Fuel Update (EIA)

    Total Delivered Residential Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 10.3 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.5 10.5 10.5 10.5 10.5 10.6 10.6 AEO 1995 11.0 10.8 10.8 10.8 10.8 10.8 10.8 10.7 10.7 10.7 10.7 10.7 10.7 10.7 10.8 10.8 10.9 AEO 1996 10.4 10.7 10.7 10.7 10.8 10.8 10.9 10.9 11.0 11.2 11.2 11.3 11.4 11.5 11.6 11.7 11.8 12.0 12.1

  9. Table 18. Total Delivered Commercial Energy Consumption, Projected vs. Actual

    Gasoline and Diesel Fuel Update (EIA)

    Total Delivered Commercial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 6.8 6.9 6.9 7.0 7.1 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.4 7.5 7.5 7.5 7.5 7.6 AEO 1995 6.9 6.9 7.0 7.0 7.0 7.1 7.1 7.1 7.1 7.1 7.2 7.2 7.2 7.2 7.3 7.3 7.3 AEO 1996 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.5 7.6 7.6 7.7 7.7 7.8 7.9 8.0 8.0 8.1 8.2 8.2 AEO 1997 7.4 7.4 7.4 7.5 7.5 7.6 7.7 7.7 7.8 7.8 7.9 7.9

  10. Table 19. Total Delivered Industrial Energy Consumption, Projected vs. Actual

    Gasoline and Diesel Fuel Update (EIA)

    Total Delivered Industrial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 25.4 25.9 26.3 26.7 27.0 27.1 26.8 26.6 26.9 27.2 27.7 28.1 28.3 28.7 29.1 29.4 29.7 30.0 AEO 1995 26.2 26.3 26.5 27.0 27.3 26.9 26.6 26.8 27.1 27.5 27.9 28.2 28.4 28.7 29.0 29.3 29.6 AEO 1996 26.5 26.6 27.3 27.5 26.9 26.5 26.7 26.9 27.2 27.6 27.9 28.2 28.3 28.5 28.7 28.9 29.2 29.4 29.6

  11. Table 20. Total Delivered Transportation Energy Consumption, Projected vs. Actual

    Gasoline and Diesel Fuel Update (EIA)

    Total Delivered Transportation Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 23.6 24.1 24.5 24.7 25.1 25.4 25.7 26.2 26.5 26.9 27.2 27.6 27.9 28.3 28.6 28.9 29.2 29.5 AEO 1995 23.3 24.0 24.2 24.7 25.1 25.5 25.9 26.2 26.5 26.9 27.3 27.7 28.0 28.3 28.5 28.7 28.9 AEO 1996 23.9 24.1 24.5 24.8 25.3 25.7 26.0 26.4 26.7 27.1 27.5 27.8 28.1 28.4 28.6 28.9 29.1 29.3

  12. Table 22. Energy Intensity, Projected vs. Actual Projected

    Gasoline and Diesel Fuel Update (EIA)

    Energy Intensity, Projected vs. Actual Projected (quadrillion Btu / $Billion 2005 Chained GDP) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 10.9 10.7 10.6 10.5 10.3 10.2 10.1 9.9 9.8 9.7 9.6 9.5 9.4 9.3 9.2 9.1 9.0 8.9 AEO 1995 10.5 10.4 10.3 10.1 10.0 9.8 9.7 9.6 9.4 9.3 9.2 9.1 9.0 8.9 8.9 8.8 8.7 AEO 1996 10.4 10.3 10.1 10.0 9.8 9.7 9.5 9.4 9.3 9.2 9.1 9.0 8.9 8.9 8.8 8.7 8.7 8.6 8.5 AEO 1997 10.0 9.9 9.8 9.7 9.6 9.5 9.4 9.3

  13. Posting Date: 12/18/15 Posting Close Date: 1/4/16

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

    815 Posting Close Date: 1416 North American Industry Classification System (NAICS) code for the request: 336211 Estimated SubcontractPO Value: TBD Estimated Period of...

  14. TT Coordinator Ltr dated May 13 2010 | Department of Energy

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

    TT Coordinator Ltr dated May 13 2010 » TT Coordinator Ltr dated May 13 2010 TT Coordinator Ltr dated May 13 2010 TT Coordinator Ltr dated May 13 2010 PDF icon TT_Coordinator_Ltr_dated_May_13_2010.pdf More Documents & Publications Technology Partnership Ombudsman - Roles, Responsibilities, Authorities and Accountabilities Technology Partnership Ombudsman - Roles, Responsibilities, Authorities and Accountabilities ADR Revised Policy

  15. 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).

  16. 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).

  17. Property:ASHRAE 169 Start Date | Open Energy Information

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    Start Date Jump to: navigation, search This is a property of type Date. Pages using the property "ASHRAE 169 Start Date" Showing 25 pages using this property. (previous 25) (next...

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  19. Adv. Fossil Solicitation Part I Due Date | Department of Energy

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

    Fossil Solicitation Part I Due Date Adv. Fossil Solicitation Part I Due Date March 16, 2016 12:01PM to 11:59PM EDT ADVANCED FOSSIL ENERGY PROJECTS SOLICITATION PART I DUE DATE...

  20. 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.

  1. 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...

  2. 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.

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

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

    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 ...

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  5. Franklin retirement date is set: 04/30/2012

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    Announcements Franklin retirement date is set: 04302012 Franklin retirement date is set: 04302012 March 6, 2012 by Helen He The Franklin (and its external login node...

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  7. FAQ's for: ENERGY STAR Verification Testing Pilot Program dated...

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    FAQ's for: ENERGY STAR Verification Testing Pilot Program dated December 2010 FAQ's for: ENERGY STAR Verification Testing Pilot Program dated December 2010 This document is the...

  8. NEMA Lighting, CCE Overview and Update presentation, dated 05...

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    Lighting, CCE Overview and Update presentation, dated 05252011. NEMA Lighting, CCE Overview and Update presentation, dated 05252011. This document is the U.S. Department of ...

  9. POLICY GUIDANCE MEMORANDUM #04 Setting Effective Date for New...

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    04 Setting Effective Date for New Hires POLICY GUIDANCE MEMORANDUM 04 Setting Effective Date for New Hires The purpose of this memorandum is to establish the Department of...

  10. Jupiter Laser Facility Target Fab Request Requester: Date Requested:

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    / Sketches: « Jupiter Laser Facility Target Fab Request Requester: Date Requested: Phone or E-Mail: Date Required: Target Name: Reference #: Laser System: Project: Task:

  11. Key Dates | U.S. DOE Office of Science (SC)

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    Key Dates Albert Einstein Distinguished Educator Fellowship (AEF) Program Einstein Fellowship Home Eligibility Benefits Obligations How to Apply Key Dates Frequently Asked...

  12. Memorandum from Daniel B. Poneman dated August 27, 2010, Strategic...

    Office of Environmental Management (EM)

    Daniel B. Poneman dated August 27, 2010, Strategic Business Initiatives Memorandum from Daniel B. Poneman dated August 27, 2010, Strategic Business Initiatives PDF icon Dep Sec...

  13. 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.

  14. 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.

  15. 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.

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

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

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

  17. 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.

  18. 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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

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

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

    SciTech Connect (OSTI)

    Valero, O.J.

    1996-10-03

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

  1. 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.

  2. Posting Date: 1/27/2016 Posting Close Date: 2/3/2016

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

    /27/2016 Posting Close Date: 2/3/2016 North American Industry Classification System (NAICS) code for the request: 236220 Estimated Subcontract/PO Value: TBD Estimated Period of Performance 2 Months Estimated RFP/RFQ Release Date: 2/4/2016 Estimated Award Date: 3/4/2016 Competition Type: SB Set-Aside Buyer Contact Email: amyp@lanl.gov Title: SII Locker Room Expansion Description of Product or Service Required Perform all required demolition and dispose of all removed materials. Furnish and

  3. Posting Date: 12/17/15 Posting Close Date: 12/24/15

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

    2/17/15 Posting Close Date: 12/24/15 North American Industry Classification System (NAICS) code for the request: 236220 Estimated Subcontract/PO Value: TBD Estimated Period of Performance N/A Estimated RFP/RFQ Release Date: 12/15/16 Estimated Award Date: 5/15/16 Competition Type: Not Set-Aside Buyer Contact Email: ajsaunders@lanl.gov Title: Off-Site Built Laboratory Description of Product or Service Required This project will provide a new permanent laboratory building to support the on-going

  4. Supplier Information Form Date: New Revision

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

    Supplier Information Form Date: New Revision Interested suppliers may complete and submit a Supplier Information Form to be included into LANS' vendor database. Suppliers are advised that there is no guarantee any solicitations or awards will be sent to Supplier by submitting a Supplier Information Form; however, in the event a solicitation is sent to the Supplier from an LANS Procurement Official, then a more formal quotation/offer may be required. Legal Business Name: D/B/A: (if applicable)

  5. WEATHERIZATION PROGRAM NOTICE 16-XX EFFECTIVE DATE:

    Energy Savers [EERE]

    WEATHERIZATION PROGRAM NOTICE 16-XX EFFECTIVE DATE: SUBJECT: WEATHERIZATION OF RENTAL UNITS - Applicable to single family and multifamily dwellings PURPOSE: To provide Grantees with updated guidance on weatherizing rental units in the Weatherization Assistance Program (WAP). DOE has answered specific questions from Grantees related to the weatherization of rental units, whether single family building or multifamily dwellings, over a number of years. However, the responses to these questions have

  6. Date centerdTimes New Roman

    Office of Environmental Management (EM)

    Summary of Audit Report National Nuclear Security Administration's Use of Innovative Technologies to Meet Security Requirements This document provides a summary of an Audit Report that is not publicly releasable. Public release is controlled pursuant to the Freedom of Information Act OAS-L-09-02 October 2008 The following is a summary o f a Special Access Unclassified Controlled Nuclear Information Audit Report, OAS-L-09-02, dated October 31, 2008, entitled "National Nuclear Security

  7. 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.

  8. Low energy cyclotron for radiocarbon dating

    SciTech Connect (OSTI)

    Welch, J.J.

    1984-12-01

    The measurement of naturally occurring radioisotopes whose half lives are less than a few hundred million years but more than a few years provides information about the temporal behavior of geologic and climatic processes, the temporal history of meteoritic bodies as well as the production mechanisms of these radioisotopes. A new extremely sensitive technique for measuring these radioisotopes at tandem Van de Graaff and cyclotron facilities has been very successful though the high cost and limited availability have been discouraging. We have built and tested a low energy cyclotron for radiocarbon dating similar in size to a conventional mass spectrometer. These tests clearly show that with the addition of a conventional ion source, the low energy cyclotron can perform the extremely high sensitivity /sup 14/C measurements that are now done at accelerator facilities. We found that no significant background is present when the cyclotron is tuned to accelerate /sup 14/C negative ions and the transmission efficiency is adequate to perform radiocarbon dating on milligram samples of carbon. The internal ion source used did not produce sufficient current to detect /sup 14/C directly at modern concentrations. We show how a conventional carbon negative ion source, located outside the cyclotron magnet, would produce sufficient beam and provide for quick sampling to make radiocarbon dating milligram samples with a modest laboratory instrument feasible.

  9. 2014 NEJC Save the Date (Spanish) | Department of Energy

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

    Spanish) 2014 NEJC Save the Date (Spanish) 2014 National Environmental Justice Conference and Training Program Save the Date, March 26 to 28, 2014 PDF icon Save the Date (Spanish) More Documents & Publications 2013 National Environmental Justice Conference and Training Program 2014 NEJC Save the Date (English) 2015 National Environmental Justice Conference and Training Program Call for PowerPoint/Video Presentations

  10. TT Coordinator Ltr dated May 13 2010 | Department of Energy

    Energy Savers [EERE]

    TT Coordinator Ltr dated May 13 2010 TT Coordinator Ltr dated May 13 2010 TT Coordinator Ltr dated May 13 2010 PDF icon TT_Coordinator_Ltr_dated_May_13_2010.pdf More Documents & Publications Technology Partnership Ombudsman - Roles, Responsibilities, Authorities and Accountabilities Technology Partnership Ombudsman - Roles, Responsibilities, Authorities and Accountabilities Microsoft Word - ADR Revised Policy82508Reformatted.doc

  11. Date Time Event Description/Participants Location

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

    Updated: 06/11/2015 Date Time Event Description/Participants Location Point of Contact 11 thru 12 All Day Meeting Todd Allen, deputy director of Science and Technology at INL, has been invited to speak at the Idaho Society of Professional Engineers (ISPE) annual meeting. Coeur d'Alene, ID Sara Prentice, 526-9591 18 9:00 AM Education Outreach Approximately 50 iSTEM students and instructors will tour various INL Idaho Falls facilities Idaho Falls, ID INL Tours Office, 526-0050 23 All Day Meeting

  12. Date centerdTimes New Roman

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

    Department's Management of Cloud Computing Services OAS-RA-L-11-06 April 2011 DOE F 1325.8 (08-93) United States Government Department of Energy Memorandum DATE: April 1, 2011 Audit Report Number: OAS-RA-L-11-06 REPLY TO ATTN OF: IG-34 (A11TG021) SUBJECT: Report on "Department's Management of Cloud Computing Services" TO: Administrator, National Nuclear Security Administration Acting Under Secretary of Energy Under Secretary for Science Chief Information Officer INTRODUCTION AND

  13. : H. Jack Elackwell, Area Manager, LAAO DATE:

    Office of Legacy Management (LM)

    O.&E b.&AORANDti~ l > : H. Jack Elackwell, Area Manager, LAAO DATE: June 5, 1973 70~ : ~$?$Z~H-Division Leader ,WE~,T : ENVIRONMENTAL RADIOACTIVITY SURVEY OF LOS ALAMOS COMIMUNITY LAND AREAS ' MBOL : H8M-73-102 At your request an environmental radioactivity survey of four' .tracts of AEC-owned land in Los Alamos County was conducted. The monitoring and analysis of samples paralleled that described in Los Alamos Scientific Laboratory Report LA5097-MS, "Los Alamos Land Areas

  14. United States Government Department of Energy DATE:

    Office of Legacy Management (LM)

    kE FJ325.8 d& * 9 -1 . (8-89) ZFG fO7440 1 United States Government Department of Energy DATE: DEC 2 3 :gg3 REPLY TO ATTN OF: EM-421 (W. A. Williams, 903-8149) SUBJECT: Elimination of the Sites from the Formerly Utilized Sites Remedial Action Program TO: The File I have reviewed the attached site summaries and elimination recommendations for the following sites: e l Mitts & Merrel Co., Saginaw, Michigan l North Carolina State University, Raleigh, North Carolina l National Smelt &

  15. Date centerdTimes New Roman

    Office of Environmental Management (EM)

    Office of Science's Energy Frontier Research Centers OAS-RA-L-10-09 August 2010 DOE F 1325.8 (08-93) United States Government Department of Energy Memorandum DATE: August 27, 2010 Audit Report Number: OAS-RA-L-10-09 REPLY TO ATTN OF: IG-32 (A10RA003) SUBJECT: Audit Report on "Office of Science's Energy Frontier Research Centers" TO: Associate Director, Office of Basic Energy Sciences, SC-22 INTRODUCTION AND OBJECTIVE In 2008, the Department of Energy's (Department) Office of Science

  16. Date centerdTimes New Roman

    Office of Environmental Management (EM)

    Management of the Tank Farm Recovery Act Infrastructure Upgrades Project OAS-RA-L-11-03 February 2011 DOE F 1325.8 (08-93) United States Government Department of Energy Memorandum DATE: February 9, 2011 Audit Report Number: OAS-RA-L-11-03 REPLY TO ATTN OF: IG-34 (A10RA043) SUBJECT: Report on "Management of the Tank Farm Recovery Act Infrastructure Upgrades Project" TO: Manager, Office of River Protection INTRODUCTION AND OBJECTIVE As part of the American Recovery and Reinvestment Act

  17. Date centerdTimes New Roman

    Office of Environmental Management (EM)

    Department's Infrastructure Modernization Projects under the Recovery and Reinvestment Act of 2009 OAS-RA-L-11-04 March 2011 DOE F 1325.8 (08-93) United States Government Department of Energy Memorandum DATE: March 2, 2011 Audit Report Number: OAS-RA-L-11-04 REPLY TO ATTN OF: IG-34 (A10RA032) SUBJECT: Report on "The Department's Infrastructure Modernization Projects under the American Recovery and Reinvestment Act of 2009" TO: Manager, Oak Ridge Office Manager, Berkeley Site Office

  18. ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected...

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

    EIA-411 for 2005" ,"Released: September 26, 2007" ,"Next Update: October 2007" ,"Table 3d. April Monthly Peak Hour Demand, Actual and Projected by North American Electric...

  19. ,"Table 1. Net Energy For Load, Actual and Projected by North...

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

    . Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2009 and Projected 2010 through 2014" ,"(Thousands of Megawatthours and...

  20. ,"Table 1. Net Energy For Load, Actual and Projected by North...

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

    Update: October 2010" ,"Table 1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2008 and Projected 2009 through 2013 "...

  1. ,"Table 1. Net Energy For Load, Actual and Projected by North...

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

    1. Net Energy For Load, Actual and Projected by North American Electric Reliability Corporation Region, " ,"2006 and Projected 2008 through 2012 " ,"(Thousands of Megawatthours and...

  2. 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.

  3. 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 Victor Diakov Nicholas DiOrio Aron Dobos Kelly Eurek Janine Freeman Bethany Frew Pieter Gagnon

  4. 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

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2005-08-17

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

  6. 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.

  7. 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.

  8. COST BREAKDOWN AWARD NO: START DATE: EXPIRATION DATE: FISCAL YEAR BREAKDOWN OF FUNDS

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

    COST BREAKDOWN AWARD NO: START DATE: EXPIRATION DATE: FISCAL YEAR BREAKDOWN OF FUNDS ELEMENTS FY FY FY FY FY TOTAL Direct Labor Overhead Materials Supplies Travel Other Direct Costs Subcontractors Total Direct Costs G&A Expense Total All Costs DOE Share* Awardee Share* Overhead Rate G&A Rate 1. The cost elements indicated are provided as an example only. Your firm should indicate the costs elements you have used on your invoices. 2. You should indicate the cost incurred for each of your

  9. Document: NA Actionee: Dorothy Riehie Document Date: 03/09/2011 Due Date: NO ACTION

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

    SN~T op Document: NA Actionee: Dorothy Riehie Document Date: 03/09/2011 Due Date: NO ACTION I Author: ALDRIDGE M Addressee: RIEHLE DC 7PES 01 Title: Re: Prime Contract # DE-AC06-08RL14788 Drilling Project Contract #41293-l:ARRA 300-FF-5 RJ/FS Installation of 11I Extract/Inj. Wells DIR DIV NAME DIR DIV NAME MGR AMRC ______ __ DEP AMSE _______ ___ AMA ___EMD____ FMD QOD HRM SED PRO 0CC ______________ AMCP _________OE Riehie, Dorothy (Actionee) AMMS ORP ______________ 15 _____________ PNSO PIC RLCI

  10. Save Energy, Save Date Night | Department of Energy

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

    Energy, Save Date Night Save Energy, Save Date Night February 11, 2013 - 1:42pm Addthis Saving energy allows you to spend that money elsewhere. Saving energy allows you to spend ...

  11. Adv. Nuclear Solicitation Part I Due Date | Department of Energy

    Energy Savers [EERE]

    I Due Date Adv. Nuclear Solicitation Part I Due Date July 20, 2016 12:01AM to 11:59PM EDT ADVANCED NUCLEAR ENERGY PROJECTS SOLICITATION PART I

  12. Adv. Nuclear Solicitation Part II Due Date | Department of Energy

    Energy Savers [EERE]

    II Due Date Adv. Nuclear Solicitation Part II Due Date November 23, 2016 12:01AM to 11:59PM EST ADVANCED NUCLEAR ENERGY PROJECTS SOLICITATION PART II

  13. Appliance Standards Program Schedule - CCE Overview and Update, dated

    Office of Environmental Management (EM)

    October 26, 2011 | Department of Energy dated October 26, 2011 Appliance Standards Program Schedule - CCE Overview and Update, dated October 26, 2011 This document is Appliance Standards Program Schedule & CCE Overview and Update presentation, dated 10/26/2011, presented to Energy-Efficiency Advocacy Groups PDF icon doe_eeag_present2011.pdf More Documents & Publications Appliance Standards Program Schedule - CCE Overview and Update, presented at AHRI 2011 Annual Meeting, dated

  14. Adv. Fossil Solicitation Part I Due Date | Department of Energy

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

    ADVANCED FOSSIL ENERGY PROJECTS SOLICITATION PART I DUE DATE Learn more about the Advanced Fossil Energy Projects Solicitation

  15. POLICY GUIDANCE MEMORANDUM #04 Setting Effective Date for New Hires |

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

    Department of Energy 4 Setting Effective Date for New Hires POLICY GUIDANCE MEMORANDUM #04 Setting Effective Date for New Hires The purpose of this memorandum is to establish the Department of Energy's (DOE) policy for setting effective dates for newly hired employees and to ensure uniform application among DOE Headquarters, Elements and Field Human Resources Offices. PDF icon POLICY GUIDANCE MEMORANDUM #4 Setting Effective Date for New Hires Responsible Contacts Tiffany Wheeler Human

  16. Key Dates | U.S. DOE Office of Science (SC)

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

    Key Dates DOE Office of Science Graduate Student Research (SCGSR) Program SCGSR Home Eligibility Benefits Participant Obligations How to Apply Information for Laboratory Scientists and Thesis Advisors Key Dates Frequently Asked Questions Contact WDTS Home Key Dates Print Text Size: A A A FeedbackShare Page The SCGSR Program Key Dates are noted below. At the submission deadline (shown in red), the online application system will close after which no additional materials will be accepted. The

  17. 2016 EJ Save the Date | Department of Energy

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

    EJ Save the Date 2016 EJ Save the Date Save the Date! March 9 to 12, 2016. 2016 National Environmental Justice Conference and Training Program and The Ninth Annual National Conference on Health Disparities PDF icon 2016 EJ Save the Date More Documents & Publications Call For Abstracts (Student Research Forum) 2016 Call for Abstracts 2015 National Environmental Justice Conference and Training Program Concludes in Washington, DC

  18. DOE Guidance-Setting Effective Date for New Hires

    Office of Environmental Management (EM)

    HUMAN RESOURCES DIRECTORS FROM: SARA I. BONIL HUMAN CAPITAL OFFICER GUIDANCE MEMORANDUM#4: SETTING EFFECTIVE DATE FOR NEW HIRES The purpose of this memorandum is to establish the Department of Energy's (DOE) policy for setting effective dates for newly hired employees and to ensure uniform appli-cation among DOE Headquarters, ~lements and ~ i e l d Human Resources Offices. As of the date of this memorandum, the effective date of employment for all new employees or reinstated employees (first

  19. Adv. Fossil Solicitation Part I Due Date | Department of Energy

    Energy Savers [EERE]

    Fossil Solicitation Part I Due Date Adv. Fossil Solicitation Part I Due Date May 18, 2016 12:01AM to 11:59PM EDT ADVANCED FOSSIL ENERGY PROJECTS SOLICITATION PART I DUE DATE Learn more about the Advanced Fossil

  20. Adv. Nuclear Solicitation Part I Due Date | Department of Energy

    Energy Savers [EERE]

    Nuclear Solicitation Part I Due Date Adv. Nuclear Solicitation Part I Due Date May 18, 2016 12:01AM to 11:59PM EDT ADVANCED NUCLEAR ENERGY PROJECTS SOLICITATION PART I DUE DATE Learn more about the Advanced Nuclear

  1. Adv. Nuclear Solicitation Part II Due Date | Department of Energy

    Energy Savers [EERE]

    Nuclear Solicitation Part II Due Date Adv. Nuclear Solicitation Part II Due Date April 13, 2016 12:01AM to 11:59PM EDT ADVANCED NUCLEAR ENERGY PROJECTS SOLICITATION PART II DUE DATE Learn more about the Advanced Nuclear

  2. Adv. Fossil Solicitation Part I Due Date | Department of Energy

    Energy Savers [EERE]

    Fossil Solicitation Part I Due Date Adv. Fossil Solicitation Part I Due Date July 13, 2016 12:01AM to 11:59PM EDT ADVANCED FOSSIL ENERGY PROJECTS SOLICITATION PART I DUE DATE Learn more about the Advanced Fossil

  3. Adv. Nuclear Solicitation Part II Due Date | Department of Energy

    Energy Savers [EERE]

    Nuclear Solicitation Part II Due Date Adv. Nuclear Solicitation Part II Due Date October 19, 2016 12:01AM to 11:59PM EDT ADVANCED NUCLEAR ENERGY PROJECTS SOLICITATION PART II DUE DATE Learn more about the Advanced Nuclear

  4. REEE Solicitation Part I Due Date | Department of Energy

    Energy Savers [EERE]

    REEE Solicitation Part I Due Date REEE Solicitation Part I Due Date May 18, 2016 12:01AM to 11:59PM EDT RENEWABLE ENERGY AND EFFICENT ENERGY PROJECTS SOLICITATION PART I DUE DATE Learn more about the Renewable Energy and Efficent Energy Projects Solicitation

  5. Adv. Fossil Solicitation Part I Due Date | Department of Energy

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

    Fossil Solicitation Part I Due Date Adv. Fossil Solicitation Part I Due Date January 13, 2016 12:01AM to 11:59PM EST ADVANCED FOSSIL ENERGY PROJECTS SOLICITATION PART I DUE DATE Learn more about the Advanced Fossil

  6. Adv. Nuclear Solicitation Part I Due Date | Department of Energy

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

    Nuclear Solicitation Part I Due Date Adv. Nuclear Solicitation Part I Due Date March 16, 2016 12:01AM to 11:59PM EDT ADVANCED NUCLEAR ENERGY PROJECTS SOLICITATION PART I DUE DATE Learn more about the Advanced Nuclear

  7. Hazard Communication Training - Upcoming Implementation Date for New Hazard

    Office of Environmental Management (EM)

    Communication Standard | Department of Energy Hazard Communication Training - Upcoming Implementation Date for New Hazard Communication Standard Hazard Communication Training - Upcoming Implementation Date for New Hazard Communication Standard Hazard Communication Training - 10 CFR 851, Worker Safety and Health Program, requires all DOE Federal and contractor employees with hazardous chemicals in their workplaces to complete new Hazard Communication Training. Upcoming Implementation Date for

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

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

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

  9. 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.

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

    Office of Environmental Management (EM)

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

  11. 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)

  12. 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.

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

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

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

  14. 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.

  15. NTSF Spring 2012 Save The Date! | Department of Energy

    Energy Savers [EERE]

    NTSF Spring 2012 Save The Date! NTSF Spring 2012 Save The Date! Please mark your calendar for May 15 thru 17 to attend the 2012 U.S. Department of Energy (DOE) National Transportation Stakeholders Forum (NTSF). This year's Forum will be held at the Hilton Knoxville, which is located in the heart of the downtown business district in Knoxville, Tennessee. PDF icon NTSF Spring 2012 Save The Date! More Documents & Publications NTSF Spring 2015 Save the Date NTSF Spring 2016 Save the Date NTSF

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

    SciTech Connect (OSTI)

    Finley, Cathy

    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.

  17. 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

  18. 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.

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

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

    Applications | Department of Energy Forecast of Solid-State Lighting in General Illumination Applications Energy Savings Forecast of Solid-State Lighting in General Illumination Applications PDF icon energysavingsforecast14.pdf More Documents & Publications Energy Savings Potential of Solid-State Lighting in General Illumination Applications - Report LED ADOPTION REPORT Solid-State Lighting R&D

  20. 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.

  1. Save the Date! Pennsylvania Strategic Energy Management Showcase 2015 |

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

    Department of Energy Save the Date! Pennsylvania Strategic Energy Management Showcase 2015 Save the Date! Pennsylvania Strategic Energy Management Showcase 2015 December 19, 2014 - 12:31pm Addthis Save the Date! Pennsylvania Strategic Energy Management Showcase 2015 Attend the Pennsylvania Strategic Energy Management Showcase on April 7, 2015, at the Penn Stater Conference Center Hotel in State College, Pennsylvania, and learn about the Better Plants Program and Superior Energy Performance®

  2. Upcoming Implementation Date for New Hazard Communication Standard |

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

    Department of Energy Upcoming Implementation Date for New Hazard Communication Standard Upcoming Implementation Date for New Hazard Communication Standard May 1, 2015 - 10:30am Addthis The upcoming implementation date for the new Hazard Communication Standard requires all Federal and Contractor employees with hazardous chemicals in their workplace must be in compliance with all modified revisions of this final rule, except: The distributors shall not ship containers labeled by the chemical

  3. Key Dates | U.S. DOE Office of Science (SC)

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

    Key Dates Community College Internships (CCI) CCI Home Eligibility Benefits Participant Obligations How to Apply Key Dates Frequently Asked Questions Contact WDTS Home Key Dates Print Text Size: A A A FeedbackShare Page At the submission deadline (shown in red) the application system will close, and no materials will be accepted after the submission deadline has passed. The Application System closes at 5:00 PM Eastern Time. CCI Internship Term: Spring 2016 Summer 2016 On-line Application Opens

  4. FAQ's for: ENERGY STAR Verification Testing Pilot Program dated December

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

    2010 | Department of Energy FAQ's for: ENERGY STAR Verification Testing Pilot Program dated December 2010 FAQ's for: ENERGY STAR Verification Testing Pilot Program dated December 2010 This document is the FAQ's for the ENERGY STAR Verification Testing Pilot Program dated December 2010 PDF icon faq_final_december-2010.pdf More Documents & Publications Comment submitted by the Alliance for Water Efficiency (AWE) regarding the Energy Star Verification Testing Program DOE Verification

  5. NEMA Distribution Transformers, CCE Overview and Update presentation, dated

    Office of Environmental Management (EM)

    05/24/2011 | Department of Energy Distribution Transformers, CCE Overview and Update presentation, dated 05/24/2011 NEMA Distribution Transformers, CCE Overview and Update presentation, dated 05/24/2011 This document is the U.S. Department of Energys presentation titled NEMA Distribution Transformers, CCE Overview and UpdateŽ, date - May 24, 2011 PDF icon nema_distributiontransformers_presentation.pdf More Documents & Publications Energy Conservation Program for Consumer Products

  6. REEE Solicitation Part I Due Date | Department of Energy

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

    RENEWABLE ENERGY AND EFFICENT ENERGY PROJECTS SOLICITATION PART I DUE DATE Learn more about the Renewable Energy and Efficent Energy Projects Solicitation

  7. Property:Incentive/StartDateString | Open Energy Information

    Open Energy Info (EERE)

    Pages using the property "IncentiveStartDateString" Showing 25 pages using this property. (previous 25) (next 25) 3 30% Business Tax Credit for Solar (Vermont) +...

  8. "Title","Creator/Author","Publication Date","OSTI Identifier...

    Office of Scientific and Technical Information (OSTI)

    Date: 31-DEC-64","Maryland. Univ., College Park, MD (United States)","US Atomic Energy Commission (AEC)","PHYSICS; ANGULAR DISTRIBUTION; DEUTERON BEAMS; ELASTIC SCATTERING;...

  9. Memorandum from Paul Bosco dated May, 20, 2012, Utlization of...

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

    Paul Bosco dated May, 20, 2012, Utlization of the General Services Administration's Federal Strategic Sourcing Initiative Blanket Purchase Agreements Memorandum from Paul Bosco...

  10. Microsoft Word - EIA-914 Instructions_Expiration Date 09202012...

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

    ENERGY INFORMATION ADMINISTRATION OMB No. 1905-0205 Washington, DC 20585 Expiration Date: 09202012 INSTRUCTIONS for FORM EIA-914 MONTHLY NATURAL GAS PRODUCTION REPORT PURPOSE...

  11. "Title","Speaker","Publication Date","OSTI Identifier","Report...

    Office of Scientific and Technical Information (OSTI)

    Speaker","Publication Date","OSTI Identifier","Report Number(s)","DOE Contract Number","Other Number(s)","Resource Type","Specific Type","Coverage

  12. PLEASE NOTE THURSDAY DATE - COLLOQUIUM: Professor Ralph Roskies...

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

    MBG Auditorium PLEASE NOTE THURSDAY DATE - COLLOQUIUM: Professor Ralph Roskies - "Big Data at the Pittsburgh Supercomputing Center" Professor Ralph Roskies Pittsburgh...

  13. Dating of major normal fault systems using thermochronology-...

    Open Energy Info (EERE)

    Dating of major normal fault systems using thermochronology- An example from the Raft River detachment, Basin and Range, western United States Jump to: navigation, search OpenEI...

  14. Date Set for Closure of Russian Nuclear Weapons Plant - NNSA...

    National Nuclear Security Administration (NNSA)

    Date Set for Closure of Russian Nuclear Weapons Plant - NNSA Is Helping Make It Happen | National Nuclear Security Administration Facebook Twitter Youtube Flickr RSS People Mission ...

  15. 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.

  16. Weather Research and Forecasting Model with Vertical Nesting Capability

    Energy Science and Technology Software Center (OSTI)

    2014-08-01

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

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

    Broader source: Energy.gov [DOE]

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

  18. 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.

  19. Table 11b. Coal Prices to Electric Generating Plants, Projected vs. Actual

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

    b. Coal Prices to Electric Generating Plants, Projected vs. Actual" "Projected Price in Nominal Dollars" " (nominal dollars per million Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO

  20. Table 3b. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual

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

    b. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual" "Projected Price in Nominal Dollars" " (nominal dollars per barrel)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO

  1. "Table 2. Real Gross Domestic Product Growth Trends, Projected vs. Actual"

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

    Real Gross Domestic Product Growth Trends, Projected vs. Actual" "Projected Real GDP Growth Trend" " (cumulative average percent growth in projected real GDP from first year shown for each AEO)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO

  2. "Table 7b. Natural Gas Price, Electric Power Sector, Actual vs. Projected"

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

    b. Natural Gas Price, Electric Power Sector, Actual vs. Projected" "Projected Price in Nominal Dollars" " (nominal dollars per million Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO

  3. 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.

  4. Energy Department Announces $2.5 Million to Improve Wind Forecasting |

    Office of Environmental Management (EM)

    Department of Energy .5 Million to Improve Wind Forecasting Energy Department Announces $2.5 Million to Improve Wind Forecasting January 8, 2015 - 12:00pm Addthis The Energy Department today announced $2.5 million for a new project to research the atmospheric processes that generate wind in mountain-valley regions. This in-depth research, conducted by Vaisala of Louisville, Colorado, will be used to improve the wind industry's weather models for short-term wind forecasts, especially for

  5. Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% |

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

    Department of Energy 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 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 forecasting accuracy by as much

  6. Franklin retirement date is set: 04/30/2012

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

    Announcements » Franklin retirement date is set: 04/30/2012 Franklin retirement date is set: 04/30/2012 March 6, 2012 by Helen He The Franklin (and its external login node Freedom) retirement date has been set to April 30, 2012. Below are the related schedules: Effective immediately: Software frozen except for critical updates Mon Apr 2: No new accounts will be created Thurs Apr 26, 23:59: Batch system is drained, batch queues are stopped (no jobs will be running at this point) Mon Apr 30: Last

  7. Categorical Exclusion (CX) Determinations By Date | Department of Energy

    Energy Savers [EERE]

    Date Categorical Exclusion (CX) Determinations By Date March 11, 2016 CX-100569 Categorical Exclusion Determination Enabling Sustainable Landscape Design for Continual Improvement of Operating Bioenergy Supply Systems Award Number: DE-EE0007088 CX(s) Applied: A9, B3.1, B3.16, B5.15 Bioenergy Technologies Office Date: 03/08/2016 Location(s): MD Office(s): Golden Field Office March 11, 2016 CX-100568 Categorical Exclusion Determination Survivability Enhancement of a Multi-Mode Point Absorber Award

  8. 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.

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

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

    Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Clean Power Research logo.jpg This project will address the need for a more accurate approach ...

  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. 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.

  12. 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.

  13. 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.

  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. 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 ...

  16. NOAA Teams Up with Department of Energy & Industry to Improve Wind Forecasts

    Broader source: Energy.gov [DOE]

    The growth of wind-generated power in the United States  is creating greater demand for improved wind forecasts. To address this need, the Department of Energy is working with NOAA and industry on...

  17. Property:Project Start Date | Open Energy Information

    Open Energy Info (EERE)

    Date" Showing 25 pages using this property. (previous 25) (next 25) M MHK Projects40MW Lewis project + 112012 + MHK ProjectsADM 3 + 112010 + MHK ProjectsADM 4 + 112010 +...

  18. Building Number/Name: Date prepared: Responsible Contractor...

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

    22-S February 2, 2012 WRPS C M Smith; E A Hill PAST OPERATIONS Beryllium brought in facility: YES Form of beryllium: LIQUID matrix Period of beryllium operations (dates): (1) ...

  19. Building Number/Name: Date prepared: Responsible Contractor...

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

    WA February 7, 2012 WRPS C M Smith; E A Hill PAST OPERATIONS Beryllium brought in facility: YES Form of beryllium: SOLID Period of beryllium operations (dates): Start: Early 1980s ...

  20. Building Number/Name: Date prepared: Responsible Contractor...

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

    07-SX Jan 29, 2012 WRPS C M Smith; E A Hill PAST OPERATIONS Beryllium brought in facility: YES Form of beryllium: SOLID Period of beryllium operations (dates): Start: Early 1980s ...

  1. Building Number/Name: Date prepared: Responsible Contractor...

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

    2-AW Feb 10,2012 WRPS C M Smith; E A Hill PAST OPERATIONS Beryllium brought in facility: YES Form of beryllium: SOLID Period of beryllium operations (dates): Start: Early 1980s ...

  2. Building Number/Name: Date prepared: Responsible Contractor...

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

    S Feb 10, 2012 WRPS C M Smith; E A Hill PAST OPERATIONS Beryllium brought in facility: YES Form of beryllium: SOLID Period of beryllium operations (dates): Start: Early 1980s End: ...

  3. Building Number/Name: Date prepared: Responsible Contractor...

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

    101-HV Feb 8 201 WRPS C M Smith; E A Hill PAST OPERATIONS Beryllium brought in facility: YES Form of beryllium: SOLID Period of beryllium operations (dates): Start: Early 1980s ...

  4. Building Number/Name: Date prepared: Responsible Contractor...

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

    3-E Jan 28, 2012 WRPS C M Smith; E A Hill PAST OPERATIONS Beryllium brought in facility: YES Form of beryllium: SOLID Period of beryllium operations (dates): Start: Early 1980s ...

  5. United States Government Department of Energy Memorandum DATE...

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

    Memorandum DATE: AliNOF: SUBJECT: DEC 2 o 2010 NE-32 Delegation of Acquisition Executive (AE) Authority for the Material Security and Consolidation Project (08-D-702) ro: Richard...

  6. NTSF Spring 2013 Save The Date | Department of Energy

    Office of Environmental Management (EM)

    Services » Waste Management » Packaging and Transportation » National Transportation Stakeholders Forum » National Transportation Stakeholders Forum (NTSF) Charter » NTSF Spring 2013 Save The Date NTSF Spring 2013 Save The Date Please mark your calendar to attend the next meeting of the U.S. Department of Energy (DOE) National Transportation Stakeholders Forum (NTSF) scheduled for May 14-16, 2013. This annual event will be held at the Hyatt Regency Hotel, located near the downtown business

  7. Oak Ridge Finishes Site's Largest Demolition Project to Date | Department

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

    of Energy Finishes Site's Largest Demolition Project to Date Oak Ridge Finishes Site's Largest Demolition Project to Date July 1, 2012 - 12:00pm Addthis BEFORE: An aerial photo shows Building K-33 before demolition. BEFORE: An aerial photo shows Building K-33 before demolition. AFTER: This photo shows the site of Building K-33 following completion of the demolition project. AFTER: This photo shows the site of Building K-33 following completion of the demolition project. BEFORE: An aerial

  8. Actual and Estimated Energy Savings Comparison for Deep Energy Retrofits in the Pacific Northwest

    SciTech Connect (OSTI)

    Blanchard, Jeremy; Widder, Sarah H.; Giever, Elisabeth L.; Baechler, Michael C.

    2012-10-01

    Seven homes from the Pacific Northwest were selected to evaluate the differences between estimated and actual energy savings achieved from deep energy retrofits. The energy savings resulting from these retrofits were estimated, using energy modeling software, to save at least 30% on a whole-house basis. The modeled pre-retrofit energy use was trued against monthly utility bills. After the retrofits were completed, each of the homes was extensively monitored, with the exception of one home which was monitored pre-retrofit. This work is being conducted by Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy Building Technologies Program as part of the Building America Program. This work found many discrepancies between actual and estimated energy savings and identified the potential causes for the discrepancies. The differences between actual energy use and modeled energy use also suggest improvements to improve model accuracy. The difference between monthly whole-house actual and estimated energy savings ranged from 75% more energy saved than predicted by the model to 16% less energy saved for all the monitored homes. Similarly, the annual energy savings difference was between 36% and -14%, which was estimated based on existing monitored savings because an entire year of data is not available. Thus, on average, for all six monitored homes the actual energy use is consistently less than estimates, indicating home owners are saving more energy than estimated. The average estimated savings for the eight month monitoring period is 43%, compared to an estimated savings average of 31%. Though this average difference is only 12%, the range of inaccuracies found for specific end-uses is far greater and are the values used to directly estimate energy savings from specific retrofits. Specifically, the monthly post-retrofit energy use differences for specific end-uses (i.e., heating, cooling, hot water, appliances, etc.) ranged from 131% under-predicted to 77% over-predicted by the model with respect to monitored energy use. Many of the discrepancies were associated with occupant behavior which influences energy use, dramatically in some cases, actual versus modeled weather differences, modeling input limitations, and complex homes that are difficult to model. The discrepancy between actual and estimated energy use indicates a need for better modeling tools and assumptions. Despite the best efforts of researchers, the estimated energy savings are too inaccurate to determine reliable paybacks for retrofit projects. While the monitored data allows researchers to understand why these differences exist, it is not cost effective to monitor each home with the level of detail presented here. Therefore an appropriate balance between modeling and monitoring must be determined for more widespread application in retrofit programs and the home performance industry. Recommendations to address these deficiencies include: (1) improved tuning process for pre-retrofit energy use, which currently utilized broad-based monthly utility bills; (2) developing simple occupant-based energy models that better address the many different occupant types and their impact on energy use; (3) incorporating actual weather inputs to increase accuracy of the tuning process, which uses utility bills from specific time period; and (4) developing simple, cost-effective monitoring solutions for improved model tuning.

  9. 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%.

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

    SciTech Connect (OSTI)

    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.

  11. 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.

  12. Nuclear Theory Helps Forecast Neutron Star Temperatures | U.S. DOE Office

    Office of Science (SC) Website

    of Science (SC) Nuclear Theory Helps Forecast Neutron Star Temperatures Nuclear Physics (NP) NP Home About Research Facilities Science Highlights Benefits of NP Funding Opportunities Nuclear Science Advisory Committee (NSAC) Community Resources Contact Information Nuclear Physics U.S. Department of Energy SC-26/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3613 F: (301) 903-3833 E: Email Us More Information » 05.01.14 Nuclear Theory Helps Forecast Neutron

  13. 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.

  14. 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.)

  15. 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.)

  16. 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.

  17. DOE Announces Webinars on Solar Forecasting Metrics, the DOE Wind Vision,

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

    and More | Department of Energy Solar Forecasting Metrics, the DOE Wind Vision, and More DOE Announces Webinars on Solar Forecasting Metrics, the DOE Wind Vision, and More February 12, 2014 - 7:38pm Addthis EERE offers webinars to the public on a range of subjects, from adopting the latest energy efficiency and renewable energy technologies to training for the clean energy workforce. Webinars are free; however, advanced registration is typically required. You can also watch archived webinars

  18. "Table 21. Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual"

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

    Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual" "Projected" " (million metric tons)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",5060,5129.666667,5184.666667,5239.666667,5287.333333,5335,5379,5437.666667,5481.666667,5529.333333,5599,5657.666667,5694.333333,5738.333333,5797,5874,5925.333333,5984 "AEO

  19. Reaction chemistry of nitrogen species in hydrothermal systems: Simple reactions, waste simulants, and actual wastes

    SciTech Connect (OSTI)

    Dell`Orco, P.; Luan, L.; Proesmans, P.; Wilmanns, E.

    1995-02-01

    Results are presented from hydrothermal reaction systems containing organic components, nitrogen components, and an oxidant. Reaction chemistry observed in simple systems and in simple waste simulants is used to develop a model which presents global nitrogen chemistry in these reactive systems. The global reaction path suggested is then compared with results obtained for the treatment of an actual waste stream containing only C-N-0-H species.

  20. Dose Rate Analysis Capability for Actual Spent Fuel Transportation Cask Contents

    SciTech Connect (OSTI)

    Radulescu, Georgeta; Lefebvre, Robert A; Peplow, Douglas E.; Williams, Mark L; Scaglione, John M

    2014-01-01

    The approved contents for a U.S. Nuclear Regulatory Commission (NRC) licensed spent nuclear fuel casks are typically based on bounding used nuclear fuel (UNF) characteristics. However, the contents of the UNF canisters currently in storage at independent spent fuel storage installations are considerably heterogeneous in terms of fuel assembly burnup, initial enrichment, decay time, cladding integrity, etc. Used Nuclear Fuel Storage, Transportation & Disposal Analysis Resource and Data System (UNF ST&DARDS) is an integrated data and analysis system that facilitates automated cask-specific safety analyses based on actual characteristics of the as-loaded UNF. The UNF-ST&DARDS analysis capabilities have been recently expanded to include dose rate analysis of as-loaded transportation packages. Realistic dose rate values based on actual canister contents may be used in place of bounding dose rate values to support development of repackaging operations procedures, evaluation of radiation-related transportation risks, and communication with stakeholders. This paper describes the UNF-ST&DARDS dose rate analysis methodology based on actual UNF canister contents and presents sample dose rate calculation results.

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

    SciTech Connect (OSTI)

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

    2009-11-20

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

  2. Forecast of contracting and subcontracting opportunities: Fiscal year 1998

    SciTech Connect (OSTI)

    1998-01-01

    This report describes procurement procedures and opportunities for small businesses with the Department of Energy (DOE). It describes both prime and subcontracting opportunities of $100,000 and above which are being set aside for 8(a) and other small business concerns. The report contains sections on: SIC codes; procurement opportunities with headquarters offices; procurement opportunities with field offices; subcontracting opportunities with major contractors; 8(a) contracts expiring in FY 1998; other opportunities to do business with DOE; management and operating contractors--expiration dates; Office of Small and Disadvantaged Business Utilization (OSDBU) staff directory; and small business survey. This document will be updated quarterly on the home page.

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

  4. TESTING OF THE SPINTEK ROTARY MICROFILTER USING ACTUAL HANFORD WASTE SAMPLES

    SciTech Connect (OSTI)

    HUBER HJ

    2010-04-13

    The SpinTek rotary microfilter was tested on actual Hanford tank waste. The samples were a composite of archived Tank 241-AN-105 material and a sample representing single-shell tanks (SST). Simulants of the two samples have been used in non-rad test runs at the 222-S laboratory and at Savannah River National Laboratory (SRNL). The results of these studies are compared in this report. Two different nominal pore sizes for the sintered steel rotating disk filter were chosen: 0.5 and 0.1 {micro}m. The results suggest that the 0.5-{micro}m disk is preferable for Hanford tank waste for the following reasons: (1) The filtrate clarity is within the same range (<<4 ntu for both disks); (2) The filtrate flux is in general higher for the 0.5-{micro}m disk; and (3) The 0.1-{micro}m disk showed a higher likelihood of fouling. The filtrate flux of the actual tank samples is generally in the range of 20-30% compared to the equivalent non-rad tests. The AN-105 slurries performed at about twice the filtrate flux of the SST slurries. The reason for this difference has not been identified. Particle size distributions in both cases are very similar; comparison of the chemical composition is not conclusive. The sole hint towards what material was stuck in the filter pore holes came from the analysis of the dried flakes from the surface of the fouled 0.1-{micro}m disk. A cleaning approach developed by SRNL personnel to deal with fouled disks has been found adaptable when using actual Hanford samples. The use of 1 M nitric acid improved the filtrate flux by approximately two times; using the same simulants as in the non-rad test runs showed that the filtrate flux was restored to 1/2 of its original amount.

  5. Actual versus predicted impacts of three ethanol plants on aquatic and terrestrial resources

    SciTech Connect (OSTI)

    Eddlemon, G.K.; Webb, J.W.; Hunsaker, D.B. Jr.; Miller, R.L.

    1993-03-15

    To help reduce US dependence on imported petroleum, Congress passed the Energy Security Act of 1980 (public Law 96-294). This legislation authorized the US Department of Energy (DOE) to promote expansion of the fuel alcohol industry through, among other measures, its Alcohol Fuels Loan Guarantee Program. Under this program, selected proposals for the conversion of plant biomass into fuel-grade ethanol would be granted loan guarantees. of 57 applications submitted for loan guarantees to build and operate ethanol fuel projects under this program, 11 were considered by DOE to have the greatest potential for satisfying DOE`s requirements and goals. In accordance with the National Environmental Policy Act (NEPA), DOE evaluated the potential impacts of proceeding with the Loan Guarantee Program in a programmatic environmental assessment (DOE 1981) that resulted in a finding of no significant impact (FANCY) (47 Federal Register 34, p. 7483). The following year, DOE conducted site-specific environmental assessments (EAs) for 10 of the proposed projects. These F-As predicted no significant environmental impacts from these projects. Eventually, three ethanol fuel projects received loan guarantees and were actually built: the Tennol Energy Company (Tennol; DOE 1982a) facility near Jasper in southeastern Tennessee; the Agrifuels Refining Corporation (Agrifuels; DOE 1985) facility near New Liberia in southern Louisiana; and the New Energy Company of Indiana (NECI; DOE 1982b) facility in South Bend, Indiana. As part of a larger retrospective examination of a wide range of environmental effects of ethanol fuel plants, we compared the actual effects of the three completed plants on aquatic and terrestrial resources with the effects predicted in the NEPA EAs several years earlier. A secondary purpose was to determine: Why were there differences, if any, between actual effects and predictions? How can assessments be improved and impacts reduced?

  6. Table 21. Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual

    Gasoline and Diesel Fuel Update (EIA)

    Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual Projected (million metric tons) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 5060 5130 5185 5240 5287 5335 5379 5438 5482 5529 5599 5658 5694 5738 5797 5874 5925 5984 AEO 1995 5137 5174 5188 5262 5309 5361 5394 5441 5489 5551 5621 5680 5727 5775 5841 5889 5944 AEO 1996 5182 5224 5295 5355 5417 5464 5525 5589 5660 5735 5812 5879 5925 5981 6030 6087 6142 6203

  7. Table 3a. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual

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

    a. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual" "Projected Price in Constant Dollars" " (constant dollars per barrel in ""dollar year"" specific to each AEO)" ,"AEO $ Year",1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",1992,16.69,16.42999,16.9899,17.66,18.28,19.0599,19.89,20.72,21.65,22.61,23.51,24.29,24.9,25.6,26.3,27,27.64,28.16

  8. Method and apparatus for distinguishing actual sparse events from sparse event false alarms

    DOE Patents [OSTI]

    Spalding, Richard E. (Albuquerque, NM); Grotbeck, Carter L. (Albuquerque, NM)

    2000-01-01

    Remote sensing method and apparatus wherein sparse optical events are distinguished from false events. "Ghost" images of actual optical phenomena are generated using an optical beam splitter and optics configured to direct split beams to a single sensor or segmented sensor. True optical signals are distinguished from false signals or noise based on whether the ghost image is presence or absent. The invention obviates the need for dual sensor systems to effect a false target detection capability, thus significantly reducing system complexity and cost.

  9. ACTUAL WASTE TESTING OF GYCOLATE IMPACTS ON THE SRS TANK FARM

    SciTech Connect (OSTI)

    Martino, C.

    2014-05-28

    Glycolic acid is being studied as a replacement for formic acid in the Defense Waste Processing Facility (DWPF) feed preparation process. After implementation, the recycle stream from DWPF back to the high-level waste Tank Farm will contain soluble sodium glycolate. Most of the potential impacts of glycolate in the Tank Farm were addressed via a literature review and simulant testing, but several outstanding issues remained. This report documents the actual-waste tests to determine the impacts of glycolate on storage and evaporation of Savannah River Site high-level waste. The objectives of this study are to address the following: ? Determine the extent to which sludge constituents (Pu, U, Fe, etc.) dissolve (the solubility of sludge constituents) in the glycolate-containing 2H-evaporator feed. ? Determine the impact of glycolate on the sorption of fissile (Pu, U, etc.) components onto sodium aluminosilicate solids. The first objective was accomplished through actual-waste testing using Tank 43H and 38H supernatant and Tank 51H sludge at Tank Farm storage conditions. The second objective was accomplished by contacting actual 2H-evaporator scale with the products from the testing for the first objective. There is no anticipated impact of up to 10 g/L of glycolate in DWPF recycle to the Tank Farm on tank waste component solubilities as investigated in this test. Most components were not influenced by glycolate during solubility tests, including major components such as aluminum, sodium, and most salt anions. There was potentially a slight increase in soluble iron with added glycolate, but the soluble iron concentration remained so low (on the order of 10 mg/L) as to not impact the iron to fissile ratio in sludge. Uranium and plutonium appear to have been supersaturated in 2H-evaporator feed solution mixture used for this testing. As a result, there was a reduction of soluble uranium and plutonium as a function of time. The change in soluble uranium concentration was independent of added glycolate concentration. The change in soluble plutonium content was dependent on the added glycolate concentration, with higher levels of glycolate (5 g/L and 10 g/L) appearing to suppress the plutonium solubility. The inclusion of glycolate did not change the dissolution of or sorption onto actual-waste 2H-evaporator pot scale to an extent that will impact Tank Farm storage and concentration. The effects that were noted involved dissolution of components from evaporator scale and precipitation of components onto evaporator scale that were independent of the level of added glycolate.

  10. "Table 19. Total Delivered Industrial Energy Consumption, Projected vs. Actual"

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

    Total Delivered Industrial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",25.43,25.904,26.303,26.659,26.974,27.062,26.755,26.598,26.908,27.228,27.668,28.068,28.348,28.668,29.068,29.398,29.688,30.008 "AEO

  11. TPA Change Package Dates in order with explanation.xlsx

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

    015-00 Milestone Series: Investigation Work on the Central Plateau Milestone TPA Milestone Language Explanation TPA Old Date TPA New Date Delay M-015-92A Submit a RCRA Facility Investigation/Corrective Measures Study and Remedial Investigation/Feasibility Study work plan for the 200-EA-1 operable unit (200 East Inner Area) to Ecology. 6/30/2015 9/30/2017 2 Years M-015-21A Submit a 200-BP-5 and 200-PO-1 OU Feasibility Study Report and Proposed Plan(s) to Ecology. 6/30/2015 6/30/2018 2 Years

  12. PERFORMANCE TESTING OF THE NEXT-GENERATION CSSX SOLVENT WITH ACTUAL SRS TANK WASTE

    SciTech Connect (OSTI)

    Pierce, R.; Peters, T.; Crowder, M.; Fink, S.

    2011-11-01

    Efforts are underway to qualify the Next-Generation Solvent for the Caustic Side Solvent Extraction (CSSX) process. Researchers at multiple national laboratories have been involved in this effort. As part of the effort to qualify the solvent extraction system at the Savannah River Site (SRS), SRNL performed a number of tests at various scales. First, SRNL completed a series of batch equilibrium, or Extraction-Scrub-Strip (ESS), tests. These tests used {approx}30 mL of Next-Generation Solvent and either actual SRS tank waste, or waste simulant solutions. The results from these cesium mass transfer tests were used to predict solvent behavior under a number of conditions. At a larger scale, SRNL assembled 12 stages of 2-cm (diameter) centrifugal contactors. This rack of contactors is structurally similar to one tested in 2001 during the demonstration of the baseline CSSX process. Assembly and mechanical testing found no issues. SRNL performed a nonradiological test using 35 L of cesium-spiked caustic waste simulant and 39 L of actual tank waste. Test results are discussed; particularly those related to the effectiveness of extraction.

  13. 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.

  14. ES&H Manual Welding and Brazing Supplement ISSUING AUTHORITY SUPPLEMENT AUTHOR APPROVAL DATE REVIEW DATE REV.

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

    ES&H Manual Welding and Brazing Supplement ISSUING AUTHORITY SUPPLEMENT AUTHOR APPROVAL DATE REVIEW DATE REV. Page 1 of 33 QA/CI Dept. Welding Technical Committee 01/21/15 01/21/20 2.1 This document is controlled as an on line file. It may be printed but the print copy is not a controlled document. It is the user's responsibility to ensure that the document is the same revision as the current on line file. This copy was printed on 1/26/2016. 1 Purpose and Scope This supplement provides the

  15. Property:OpenEI/UtilityRate/EndDate | Open Energy Information

    Open Energy Info (EERE)

    EndDate Jump to: navigation, search This is a property of type Date. Name: End Date Retrieved from "http:en.openei.orgwindex.php?titleProperty:OpenEIUtilityRate...

  16. Property:OpenEI/UtilityRate/StartDate | Open Energy Information

    Open Energy Info (EERE)

    StartDate Jump to: navigation, search This is a property of type Date. Name: Start Date Retrieved from "http:en.openei.orgwindex.php?titleProperty:OpenEIUtilityRate...

  17. Table 11a. Coal Prices to Electric Generating Plants, Projected vs. Actual

    Gasoline and Diesel Fuel Update (EIA)

    a. Coal Prices to Electric Generating Plants, Projected vs. Actual Projected Price in Constant Dollars (constant dollars per million Btu in "dollar year" specific to each AEO) AEO $ Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 1992 1.47 1.48 1.53 1.57 1.58 1.57 1.61 1.63 1.68 1.69 1.70 1.72 1.70 1.76 1.79 1.81 1.88 1.92 AEO 1995 1993 1.39 1.39 1.38 1.40 1.40 1.39 1.39 1.42 1.41 1.43 1.44 1.45 1.46 1.46 1.46 1.47

  18. Table 3a. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual

    Gasoline and Diesel Fuel Update (EIA)

    Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual Projected Price in Constant Dollars (constant dollars per barrel in "dollar year" specific to each AEO) AEO $ Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 1992 16.69 16.43 16.99 17.66 18.28 19.06 19.89 20.72 21.65 22.61 23.51 24.29 24.90 25.60 26.30 27.00 27.64 28.16 AEO 1995 1993 14.90 16.41 16.90 17.45 18.00 18.53 19.13 19.65 20.16 20.63 21.08

  19. Table 3b. Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual

    Gasoline and Diesel Fuel Update (EIA)

    Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual Projected Price in Nominal Dollars (nominal dollars per barrel) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 17.06 17.21 18.24 19.43 20.64 22.12 23.76 25.52 27.51 29.67 31.86 34.00 36.05 38.36 40.78 43.29 45.88 48.37 AEO 1995 15.24 17.27 18.23 19.26 20.39 21.59 22.97 24.33 25.79 27.27 28.82 30.38 32.14 33.89 35.85 37.97 40.28 AEO 1996 17.16 17.74 18.59 19.72

  20. Table 7a. Natural Gas Price, Electric Power Sector, Actual vs. Projected

    Gasoline and Diesel Fuel Update (EIA)

    a. Natural Gas Price, Electric Power Sector, Actual vs. Projected Projected Price in Constant Dollars (constant dollars per million Btu in "dollar year" specific to each AEO) AEO $ Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 1992 2.44 2.48 2.57 2.66 2.70 2.79 2.84 2.92 3.04 3.16 3.25 3.36 3.51 3.60 3.77 3.91 3.97 4.08 AEO 1995 1993 2.39 2.48 2.42 2.45 2.45 2.53 2.59 2.78 2.91 3.10 3.24 3.38 3.47 3.53 3.61 3.68

  1. Table 11a. Coal Prices to Electric Generating Plants, Projected vs. Actual

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

    a. Coal Prices to Electric Generating Plants, Projected vs. Actual" "Projected Price in Constant Dollars" " (constant dollars per million Btu in ""dollar year"" specific to each AEO)" ,"AEO $ Year",1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",1992,1.4699,1.4799,1.53,1.57,1.58,1.57,1.61,1.63,1.68,1.69,1.7,1.72,1.7,1.76,1.79,1.81,1.88,1.92 "AEO

  2. "Table 17. Total Delivered Residential Energy Consumption, Projected vs. Actual"

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

    Total Delivered Residential Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",10.31,10.36,10.36,10.37,10.38,10.4,10.4,10.41,10.43,10.43,10.44,10.45,10.46,10.49,10.51,10.53,10.56,10.6 "AEO 1995",,10.96,10.8,10.81,10.81,10.79,10.77,10.75,10.73,10.72,10.7,10.7,10.69,10.7,10.72,10.75,10.8,10.85 "AEO

  3. "Table 18. Total Delivered Commercial Energy Consumption, Projected vs. Actual"

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

    Total Delivered Commercial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",6.82,6.87,6.94,7,7.06,7.13,7.16,7.22,7.27,7.32,7.36,7.38,7.41,7.45,7.47,7.5,7.51,7.55 "AEO 1995",,6.94,6.9,6.95,6.99,7.02,7.05,7.08,7.09,7.11,7.13,7.15,7.17,7.19,7.22,7.26,7.3,7.34 "AEO

  4. "Table 20. Total Delivered Transportation Energy Consumption, Projected vs. Actual"

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

    Total Delivered Transportation Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",23.62,24.08,24.45,24.72,25.06,25.38,25.74,26.16,26.49,26.85,27.23,27.55,27.91,28.26,28.61,28.92,29.18,29.5 "AEO 1995",,23.26,24.01,24.18,24.69,25.11,25.5,25.86,26.15,26.5,26.88,27.28,27.66,27.99,28.25,28.51,28.72,28.94 "AEO

  5. "Table 7a. Natural Gas Price, Electric Power Sector, Actual vs. Projected"

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

    a. Natural Gas Price, Electric Power Sector, Actual vs. Projected" "Projected Price in Constant Dollars" " (constant dollars per million Btu in ""dollar year"" specific to each AEO)" ,"AEO $ Year",1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",1992,2.44,2.48,2.57,2.66,2.7,2.79,2.84,2.92,3.04,3.16,3.25,3.36,3.51,3.6,3.77,3.91,3.97,4.08 "AEO

  6. 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.

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

    Gasoline and Diesel Fuel Update (EIA)

    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

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

    Office of Environmental Management (EM)

    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

  9. Property:NEPA TMP/EISFederalRegisterDate | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search This is a property of type Date. Retrieved from "http:en.openei.orgwindex.php?titleProperty:NEPATMPEISFederalRegisterDate&oldid637471...

  10. Property:NEPA TMP/PreApplicationMeetingDate | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search This is a property of type Date. Retrieved from "http:en.openei.orgwindex.php?titleProperty:NEPATMPPreApplicationMeetingDate&oldid637468...

  11. Age Dating of Mixed SNM--Preliminary Investigations

    SciTech Connect (OSTI)

    Yuan, D., Guss, P. P., Yfantis, E., Klingensmith, A., Emer, D.

    2011-12-01

    Recently we investigated the nuclear forensics problem of age determination for mixed special nuclear material (SNM). Through limited computational mixing experiments and interactive age analysis, it was observed that age dating results are generally affected by the mixing of samples with different assays or even by small radioactive material contamination. The mixing and contamination can be detected through interactive age analysis, a function provided by the Decay Interaction, Visualization and Analysis (DIVA) software developed by NSTec. It is observed that for mixed SNM with two components, the age estimators typically fall into two distinct clusters on the time axis. This suggests that averaging or other simple statistical methods may not always be suitable for age dating SNM mixtures. Instead, an interactive age analysis would be more suitable for age determination of material components of such SNM mixtures. This work was supported by the National Center for Nuclear Security (NCNS).

  12. WEATHERIZATION PROGRAM NOTICE 16-XX EFFECTIVE DATE: SUBJECT: MULTIFAMILY WEATHERIZATION

    Energy Savers [EERE]

    6-XX EFFECTIVE DATE: SUBJECT: MULTIFAMILY WEATHERIZATION PURPOSE: To provide Grantees with consolidated guidance on previously issued Weatherization Program Notices (WPNs) on weatherizing multifamily buildings in the Weatherization Assistance Program (WAP). This supersedes WPN 10-7 and WPN 11-9 SCOPE: The provisions of this guidance apply to Grantees applying for financial assistance under the Department of Energy (DOE) WAP. LEGAL AUTHORITY: Title IV, Energy Conservation and Production Act, as

  13. From: David Newacheck To: Congestion Study Comments Date:

    Office of Environmental Management (EM)

    Newacheck To: Congestion Study Comments Date: Sunday, October 19, 2014 9:15:20 PM Dear Sir or Ma'am; I am opposed to the establishment of National Interest Energy Transmission Corridors (NIETC's) for the following reasons: First, the easements place an undo burden on landowners on and near the transmission lines. The compensation cannot begin to cover the all of the losses, tangible and intangible that landowners would suffer. Second, I believe that condemning private property for transmission

  14. From: MCKEOWN D To: Congestion Study Comments Date:

    Office of Environmental Management (EM)

    MCKEOWN D To: Congestion Study Comments Date: Friday, September 19, 2014 2:18:11 AM I am opposed to the establishment of National Interest Energy Transmission Corridors (NIETC's) for the following reasons. First, the easements place an undo burden on landowners on and near the transmission lines. The compensation cannot begin to cover the all of the losses, tangible and intangible that landowners would suffer. Second, I believe that condemning private property for transmission lines in one state

  15. From: Wayne Beach To: Congestion Study Comments Date:

    Office of Environmental Management (EM)

    Wayne Beach To: Congestion Study Comments Date: Thursday, October 09, 2014 12:32:40 PM I am opposed to the establishment of National Interest Energy Transmission Corridors (NIETC's) for the following reasons. First, the easements place an undo burden on landowners on and near the transmission lines. The compensation cannot begin to cover the all of the losses, tangible and intangible that landowners would suffer. Second, I believe that condemning private property for transmission lines in one

  16. MEMORANDUM TO: FILE DATE FROM: SUBJECT: I ALTERNATE NAME:

    Office of Legacy Management (LM)

    FROM: SUBJECT: I ALTERNATE NAME: -__--__------------~-~ ------------_--__---__ CI+f: h&d --------- STATE:-&~ Owner cork&&d 0 yes .j -. ___ Current: ~-~~-_----_-_-~~--~--~~-~~ if yes, date contacted TYPE OF OPERATIkN --_--~~--~_-----_ 0 Research & Development' 0 Facility Type 0 Production scale tastinq Cl PiL'at Scale a Bench Scale Process a Theoretical Studies 0 Sample 7s Analysis q Production I3 Disposal /Storage 0 Manufacturing 0 University 0 Research Orqariizaticn 0

  17. 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.

  18. BENCH-SCALE STEAM REFORMING OF ACTUAL TANK 48H WASTE

    SciTech Connect (OSTI)

    Burket, P; Gene Daniel, G; Charles Nash, C; Carol Jantzen, C; Michael Williams, M

    2008-09-25

    Fluidized Bed Steam Reforming (FBSR) has been demonstrated to be a viable technology to remove >99% of the organics from Tank 48H simulant, to remove >99% of the nitrate/nitrite from Tank 48H simulant, and to form a solid product that is primarily carbonate based. The technology was demonstrated in October of 2006 in the Engineering Scale Test Demonstration Fluidized Bed Steam Reformer1 (ESTD FBSR) at the Hazen Research Inc. (HRI) facility in Golden, CO. The purpose of the Bench-scale Steam Reformer (BSR) testing was to demonstrate that the same reactions occur and the same product is formed when steam reforming actual radioactive Tank 48H waste. The approach used in the current study was to test the BSR with the same Tank 48H simulant and same Erwin coal as was used at the ESTD FBSR under the same operating conditions. This comparison would allow verification that the same chemical reactions occur in both the BSR and ESTD FBSR. Then, actual radioactive Tank 48H material would be steam reformed in the BSR to verify that the actual tank 48H sample reacts the same way chemically as the simulant Tank 48H material. The conclusions from the BSR study and comparison to the ESTD FBSR are the following: (1) A Bench-scale Steam Reforming (BSR) unit was successfully designed and built that: (a) Emulated the chemistry of the ESTD FBSR Denitration Mineralization Reformer (DMR) and Carbon Reduction Reformer (CRR) known collectively as the dual reformer flowsheet. (b) Measured and controlled the off-gas stream. (c) Processed real (radioactive) Tank 48H waste. (d) Met the standards and specifications for radiological testing in the Savannah River National Laboratory (SRNL) Shielded Cells Facility (SCF). (2) Three runs with radioactive Tank 48H material were performed. (3) The Tetraphenylborate (TPB) was destroyed to > 99% for all radioactive Bench-scale tests. (4) The feed nitrate/nitrite was destroyed to >99% for all radioactive BSR tests the same as the ESTD FBSR. (5) The radioactive Tank 48H DMR product was primarily made up of soluble carbonates. The three most abundant species were thermonatrite, [Na{sub 2}CO{sub 3} {center_dot} H{sub 2}O], sodium carbonate, [Na{sub 2}CO{sub 3}], and trona, [Na{sub 3}H(CO{sub 3}){sub 2} {center_dot} 2H{sub 2}O] the same as the ESTD FBSR. (6) Insoluble solids analyzed by X-Ray Diffraction (XRD) did not detect insoluble carbonate species. However, they still may be present at levels below 2 wt%, the sensitivity of the XRD methodology. Insoluble solids XRD characterization indicated that various Fe/Ni/Cr/Mn phases are present. These crystalline phases are associated with the insoluble sludge components of Tank 48H slurry and impurities in the Erwin coal ash. The percent insoluble solids, which mainly consist of un-burnt coal and coal ash, in the products were 4 to 11 wt% for the radioactive runs. (7) The Fe{sup +2}/Fe{sub total} REDOX measurements ranged from 0.58 to 1 for the three radioactive Bench-scale tests. REDOX measurements > 0.5 showed a reducing atmosphere was maintained in the DMR indicating that pyrolysis was occurring. (8) Greater than 90% of the radioactivity was captured in the product for all three runs. (9) The collective results from the FBSR simulant tests and the BSR simulant tests indicate that the same chemistry occurs in the two reactors. (10) The collective results from the BSR simulant runs and the BSR radioactive waste runs indicates that the same chemistry occurs in the simulant as in the real waste. The FBSR technology has been proven to destroy the organics and nitrates in the Tank 48H waste and form the anticipated solid carbonate phases as expected.

  19. 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.

  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.