Sample records for forecast updates reference

  1. 1993 Solid Waste Reference Forecast Summary

    SciTech Connect (OSTI)

    Valero, O.J.; Blackburn, C.L. [Westinghouse Hanford Co., Richland, WA (United States); Kaae, P.S.; Armacost, L.L.; Garrett, S.M.K. [Pacific Northwest Lab., Richland, WA (United States)

    1993-08-01T23:59:59.000Z

    This report, which updates WHC-EP-0567, 1992 Solid Waste Reference Forecast Summary, (WHC 1992) forecasts the volumes of solid wastes to be generated or received at the US Department of Energy Hanford Site during the 30-year period from FY 1993 through FY 2022. The data used in this document were collected from Westinghouse Hanford Company forecasts as well as from surveys of waste generators at other US Department of Energy sites who are now shipping or plan to ship solid wastes to the Hanford Site for disposal. These wastes include low-level and low-level mixed waste, transuranic and transuranic mixed waste, and nonradioactive hazardous waste.

  2. Facebook IPO updated valuation and user forecasting

    E-Print Network [OSTI]

    Facebook IPO ≠ updated valuation and user forecasting Based on: Amendment No. 6 to Form S-1 (May 9. Peter Cauwels and Didier Sornette, Quis pendit ipsa pretia: facebook valuation and diagnostic Extreme Growth JPMPaper Cauwels and Sornette 840 1110 1820 S1- filing- May 9 2012 1006 1105 1371 Facebook

  3. Accuracy of near real time updates in wind power forecasting

    E-Print Network [OSTI]

    Heinemann, Detlev

    · advantage: no NWP data necessary ­ very actual shortest term forecasts possible · wind power inputAccuracy of near real time updates in wind power forecasting with regard to different weather October 2007 #12;EMS/ECAM 2007 ­ Nadja Saleck Outline · Study site · Wind power forecasting - method

  4. CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE -APRIL 2014

    E-Print Network [OSTI]

    de Lijser, Peter

    CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE - APRIL 2014 Anil Puri, Ph.D. -- Director, Center for Economic Analysis and Forecasting -- Dean, Mihaylo College of Business and Economics Mira Farka, Ph.D. -- Co-Director, Center for Economic Analysis and Forecasting -- Associate Professor

  5. CALIFORNIA ENERGY COMMISSION0 Annual Update to the Forecasted

    E-Print Network [OSTI]

    Values in TWh forthe Year2022 Formula Mid Demand Forecast Renewable Net High Demand Forecast Renewable Net Low Demand Forecast Renewable Net #12;CALIFORNIA ENERGY COMMISSION5 Demand Forecast · Retail Sales Forecast from California Energy Demand 2012 2022(CED 2011), Adopted Forecast* ­ Form 1.1c · Demand Forecast

  6. CSUF Economic Outlook and Forecasts MidYear Update -April 2013

    E-Print Network [OSTI]

    de Lijser, Peter

    CSUF Economic Outlook and Forecasts MidYear Update - April 2013 Anil Puri & Mira Farka Mihaylo College of Business and Economics California State University, Fullerton U.S. Economic Outlook to the forecast and a are-up in the region can easily derail the global economic recovery. Nonetheless

  7. Continuous Model Updating and Forecasting for a Naturally Fractured Reservoir

    E-Print Network [OSTI]

    Almohammadi, Hisham

    2013-07-26T23:59:59.000Z

    result in suboptimal decisions and huge disappointments (see Sec. 1.2.2) Reservoir simulation literature indicates that an acceptable level of matching historical reservoir performance is required to establish reliable forecasts. However, this does... and field production. Such capabilities enable continuous and automatic fine-tuning of production controls to optimize project economics and/or some well or reservoir performance stated objective. Remotely activated sub-surface valves on ?smart wells...

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

    SciTech Connect (OSTI)

    Pennock, K.

    2012-10-01T23:59:59.000Z

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

  9. EIA-An Updated Annual Energy Outlook 2009 Reference Case Reflecting...

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

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

  10. Hydraulic Fracturing and Horizontal Gas Well Drilling Reference List Updated December 7, 2011

    E-Print Network [OSTI]

    Manning, Sturt

    Hydraulic Fracturing and Horizontal Gas Well Drilling Reference List Updated December 7, 2011. References to popular press and advocacy groups, both of which are numerous and described in detail elsewhere of Hydraulic Fracturing in the Shale Plays (2010). Tudor Pickering Holt & Co with Reservoir Research Partners

  11. Continuous reservoir simulation model updating and forecasting using a markov chain monte carlo method

    E-Print Network [OSTI]

    Liu, Chang

    2009-05-15T23:59:59.000Z

    forecasts of well and reservoir performance, accessible at any time. It can be used to optimize long-term reservoir performance at field scale....

  12. Cost update technology, safety, and costs of decommissioning a reference uranium hexafluoride conversion plant

    SciTech Connect (OSTI)

    Miles, T.L.; Liu, Y.

    1995-08-01T23:59:59.000Z

    The purpose of this study is to update the cost estimates developed in a previous report, NUREG/CR-1757 (Elder 1980) for decommissioning a reference uranium hexafluoride conversion plant from the original mid-1981 dollars to values representative of January 1993. The cost updates were performed by using escalation factors derived from cost index trends over the past 11.5 years. Contemporary price quotes wee used for costs that have increased drastically or for which is is difficult to find a cost trend. No changes were made in the decommissioning procedures or cost element requirements assumed in NUREG/CR-1757. This report includes only information that was changed from NUREG/CR-1757. Thus, for those interested in detailed descriptions and associated information for the reference uranium hexafluoride conversion plant, a copy of NUREG/CR-1757 will be needed.

  13. STAFF FORECAST OF 2007 PEAK STAFFREPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION STAFF FORECAST OF 2007 PEAK DEMAND STAFFREPORT June 2006 CEC-400....................................................................... .................11 Tables Table 1: Revised versus September 2005 Peak Demand Forecast ......................... 2.............................................................................................. 10 #12;Introduction and Background This document describes staff's updated 2007 peak demand forecasts

  14. 2009 CAPS Spring Forecast Program Plan

    E-Print Network [OSTI]

    Droegemeier, Kelvin K.

    package. · Two 18 UTC update forecasts on demand basis, with the same domain and configuration, running2009 CAPS Spring Forecast Experiment Program Plan April 20, 2009 #12;2 Table of Content 1. Overview .......................................................................................................4 3. Forecast System Configuration

  15. EIA-An Updated Annual Energy Outlook 2009 Reference Case - Preface...

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

    tax credit Updated tax credits for renewables Loan guarantees for renewables and biofuels Support for carbon capture and storage (CCS) Smart grid expenditures. Other major...

  16. Consensus Coal Production And Price Forecast For

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    Consensus Coal Production And Price Forecast For West Virginia: 2011 Update Prepared for the West December 2011 © Copyright 2011 WVU Research Corporation #12;#12;W.Va. Consensus Coal Forecast Update 2011 i Table of Contents Executive Summary 1 Recent Developments 3 Consensus Coal Production And Price Forecast

  17. last updated 12/05/2013 Deliverable Quarter Due (Draft!)

    E-Print Network [OSTI]

    Forecast Q3 2014 Draft Results of Flexibility and Balancing Analysis Q4 2014 Demand Forecast Updated Q4, forecasts and other inputs Ongoing Narratives on Power Planning Topics and Issues (RSAC) Identify Topics 2014 Load Forecast Updated Q4 2014 Conservation Supply Curves Updated Q4 2014 Conceptual Definition

  18. Forecast Correlation Coefficient Matrix of Stock Returns in Portfolio Analysis

    E-Print Network [OSTI]

    Zhao, Feng

    2013-01-01T23:59:59.000Z

    Unadjusted Forecasts . . . . . . . . . . . . . . . .Forecasts . . . . . . . . . . . . . . . . . . . . . . . . . .Unadjusted Forecasts . . . . . . . . . . . . . . . . . . .

  19. Update

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched Ferromagnetism inS-4500II Field Emission SEM with EDAX (For3WebinarUpdate on

  20. Forecast Technical Document Forecast Types

    E-Print Network [OSTI]

    Forecast Technical Document Forecast Types A document describing how different forecast types are implemented in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Forecast Types Background Different `types' of forecast are possible for a specified area

  1. Revised 1/6/14 AM *refer updates to ITG. E-MAIL YOUR ROOM REQUEST TO CAROLYN MEISNER: cmeisner@education.ucsb.edu

    E-Print Network [OSTI]

    California at Santa Barbara, University of

    Revised 1/6/14 AM *refer updates to ITG. E-MAIL YOUR ROOM REQUEST TO CAROLYN MEISNER: cmeisner@education.ucsb.edu * No attachments please, copy and paste for software, group access, group folders, etc. please email: help@education

  2. Demand Forecasting of New Products

    E-Print Network [OSTI]

    Sun, Yu

    Demand Forecasting of New Products Using Attribute Analysis Marina Kang A thesis submitted Abstract This thesis is a study into the demand forecasting of new products (also referred to as Stock upon currently employed new-SKU demand forecasting methods which involve the processing of large

  3. Regional-seasonal weather forecasting

    SciTech Connect (OSTI)

    Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

    1980-08-01T23:59:59.000Z

    In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    to estimate the base-case natural gas price forecast, but toComparison of AEO 2010 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts from

  5. Solar Forecasting

    Broader source: Energy.gov [DOE]

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

  6. Forecast Technical Document Restocking in the Forecast

    E-Print Network [OSTI]

    Forecast Technical Document Restocking in the Forecast A document describing how restocking of felled areas is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the forecast Background During the period of a production forecast it is assumed that, as forest sub

  7. > BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS FORECAST IMPROVEMENTS

    E-Print Network [OSTI]

    Greenslade, Diana

    > BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS BRISBANE FORECAST IMPROVEMENTS The Bureau of Meteorology is progressively upgrading its forecast system to provide more detailed forecasts across Australia and Sunshine Coast. FURTHER INFORMATION : www.bom.gov.au/NexGenFWS © Commonwealth of Australia, 2013 Links

  8. Forecasted Opportunities

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsing ZirconiaPolicyFeasibilityFieldMinds" |beamtheFor yourForForecasted

  9. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    and forecasting of solar radiation data: a review,Ēforecasting of solar- radiation data,Ē Solar Energy, vol.sequences of global solar radiation data for isolated sites:

  10. > BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS DISTRICT FORECASTS

    E-Print Network [OSTI]

    Greenslade, Diana

    > BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS DISTRICT FORECASTS IMPROVEMENTS FOR QUEENSLAND across Australia From October 2013, new and improved district forecasts will be introduced in Queensland Protection times FURTHER INFORMATION : www.bom.gov.au/NexGenFWS © Commonwealth of Australia, 2013 PTO> Wind

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2003-12-01T23:59:59.000Z

    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.

  12. Texas Electricity Update

    E-Print Network [OSTI]

    Lloyd, B.

    2012-01-01T23:59:59.000Z

    Texas Electricity Update CATEE 2012 Galveston, Texas Brian Lloyd Executive Director Public Utility Commission of Texas October 10, 2012 1 2 Drought Summary May Reserve Margin Report 3 Demand Growth by Region 4 105? Normal... 917 Firm Load Forecast, MW 65,649 68,403 71,692 73,957 75,360 76,483 CATEE 2012 Questions? Brian H. Lloyd Executive Director Public Utility Commission of Texas 512-936-7040 14 ...

  13. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01T23:59:59.000Z

    Comparison of AEO 2007 Natural Gas Price Forecast to NYMEXs reference case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

  14. Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01T23:59:59.000Z

    Comparison of AEO 2006 Natural Gas Price Forecast to NYMEXs reference case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01T23:59:59.000Z

    Comparison of AEO 2009 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    late January 2008, extend its natural gas futures strip anComparison of AEO 2008 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts from

  17. 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...

  18. Forecast Technical Document Volume Increment

    E-Print Network [OSTI]

    Forecast Technical Document Volume Increment Forecasts A document describing how volume increment is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Volume increment forecasts Background A volume increment forecast is a fundamental output of the forecast

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06T23:59:59.000Z

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

  3. ENSEMBLE RE-FORECASTING : IMPROVING MEDIUM-RANGE FORECAST SKILL

    E-Print Network [OSTI]

    Hamill, Tom

    5.5 ENSEMBLE RE-FORECASTING : IMPROVING MEDIUM-RANGE FORECAST SKILL USING RETROSPECTIVE FORECASTS, Colorado 1. INTRODUCTION Improving weather forecasts is a primary goal of the U.S. National Oceanic predictions has been to improve the accuracy of the numerical forecast models. Much effort has been expended

  4. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    2.1.2 European Solar Radiation Atlas (ESRA)2.4 Evaluation of Solar Forecasting . . . . . . . . .2.4.1 Solar Variability . . . . . . . . . . . . .

  5. CONSULTANT REPORT DEMAND FORECAST EXPERT

    E-Print Network [OSTI]

    CONSULTANT REPORT DEMAND FORECAST EXPERT PANEL INITIAL forecast, end-use demand modeling, econometric modeling, hybrid demand modeling, energyMahon, Carl Linvill 2012. Demand Forecast Expert Panel Initial Assessment. California Energy

  6. Technology Forecasting Scenario Development

    E-Print Network [OSTI]

    Technology Forecasting and Scenario Development Newsletter No. 2 October 1998 Systems Analysis was initiated on the establishment of a new research programme entitled Technology Forecasting and Scenario and commercial applica- tion of new technology. An international Scientific Advisory Panel has been set up

  7. Rainfall-River Forecasting

    E-Print Network [OSTI]

    US Army Corps of Engineers

    ;2Rainfall-River Forecasting Joint Summit II NOAA Integrated Water Forecasting Program · Minimize losses due management and enhance America's coastal assets · Expand information for managing America's Water Resources, Precipitation and Water Quality Observations · USACE Reservoir Operation Information, Streamflow, Snowpack

  8. APPLICATION OF PROBABILISTIC FORECASTS: DECISION MAKING WITH FORECAST UNCERTAINTY

    E-Print Network [OSTI]

    Katz, Richard

    1 APPLICATION OF PROBABILISTIC FORECASTS: DECISION MAKING WITH FORECAST UNCERTAINTY Rick Katz.isse.ucar.edu/HP_rick/dmuu.pdf #12;2 QUOTES ON USE OF PROBABILITY FORECASTS · Lao Tzu (Chinese Philosopher) "He who knows does and Value of Probability Forecasts (4) Cost-Loss Decision-Making Model (5) Simulation Example (6) Economic

  9. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required of any forecast of electricity demand and developing ways to reduce the risk of planning errors that could arise from this and other uncertainties in the planning process. Electricity demand is forecast

  10. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    NONE

    1998-07-01T23:59:59.000Z

    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.

  11. Published in: The Tornado: Its Structure, Dynamics, Prediction, and Hazards (C. Church et al., Eds.), Geophysical Monograph 79, Amer. Geophys. Union, 557-571. Note: The references have been updated from the original to include

    E-Print Network [OSTI]

    Doswell III, Charles A.

    officers who had some early tor- nado forecasting successes at Tinker Air Force Base in Oklahoma. Doswell III National Severe Storms Laboratory, Norman, Oklahoma73069 Steven J. Weiss and Robert H. Johns

  12. Probabilistic manpower forecasting

    E-Print Network [OSTI]

    Koonce, James Fitzhugh

    1966-01-01T23:59:59.000Z

    PROBABILISTIC MANPOWER FORECASTING A Thesis JAMES FITZHUGH KOONCE Submitted to the Graduate College of the Texas ASSAM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May, 1966 Major Subject...: Computer Science and Statistics PROBABILISTIC MANPOWER FORECASTING A Thesis By JAMES FITZHUGH KOONCE Submitted to the Graduate College of the Texas A@M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May...

  13. Multivariate Forecast Evaluation And Rationality Testing

    E-Print Network [OSTI]

    Komunjer, Ivana; OWYANG, MICHAEL

    2007-01-01T23:59:59.000Z

    1062ó1088. MULTIVARIATE FORECASTS Chaudhuri, P. (1996): ďOnKingdom. MULTIVARIATE FORECASTS Kirchgšssner, G. , and U. K.2005): ďEstimation and Testing of Forecast Rationality under

  14. URESC Update

    Broader source: Energy.gov [DOE]

    Presentation covers the URESC Update for the Federal Utility Partnership Working Group (FUPWG) meeting, held on November 18-19, 2009.

  15. Updated March 2010 Reference Guide: IEEE Style

    E-Print Network [OSTI]

    Pallis, George

    ." for more than two. (Note that "et al." is not italicized.) Examples: One author: "Smith [1] reports ..." Two authors: "Smith and Jones [12] report ..." Three or more authors: "Smith et al. [23] report

  16. T-672: Oracle Critical Patch Update Advisory - July 2011 | Department...

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

    Critical Patch Updates and Security Alerts Security Alerts reference LINKS: Oracle Fusion Middleware Risk Matrix Oracle Database Server Risk Matrix Oracle Enterprise Manager...

  17. Sixth Northwest Conservation & Electric Power Plan Draft Wholesale Power Price Forecasts

    E-Print Network [OSTI]

    Price Forecasts 4. Updated load-resource balance by zones\\ regions ∑ Energy ∑ Capacity 5. Impact Higher Coal Prices Medium Long-term Trend Forecasts for PNW Zones 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1 Northwest Power and Conservation Council Comparison of Annual Average Energy Draft 6th Plan vs. Interim

  18. Online short-term solar power forecasting

    SciTech Connect (OSTI)

    Bacher, Peder; Madsen, Henrik [Informatics and Mathematical Modelling, Richard Pedersens Plads, Technical University of Denmark, Building 321, DK-2800 Lyngby (Denmark); Nielsen, Henrik Aalborg [ENFOR A/S, Lyngsoe Alle 3, DK-2970 Hoersholm (Denmark)

    2009-10-15T23:59:59.000Z

    This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model. (author)

  19. Updated U.S. Geothermal Supply Characterization

    SciTech Connect (OSTI)

    Petty, S.; Porro, G.

    2007-03-01T23:59:59.000Z

    This paper documents the approach taken to characterize and represent an updated assessment of U.S. geothermal supply for use in forecasting the penetration of geothermal electrical generation in the National Energy Modeling System (NEMS). This work is motivated by several factors: The supply characterization used as the basis of several recent U.S. Department of Energy (DOE) forecasts of geothermal capacity is outdated; additional geothermal resource assessments have been published; and a new costing tool that incorporates current technology, engineering practices, and associated costs has been released.

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

    SciTech Connect (OSTI)

    Not Available

    1993-12-01T23:59:59.000Z

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

  1. 3, 21452173, 2006 Probabilistic forecast

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    HESSD 3, 2145­2173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page for probabilistic forecasts of continuous hydrological variables F. Laio and S. Tamea DITIC ­ Department­2173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page Abstract Introduction

  2. 4, 189212, 2007 Forecast and

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    OSD 4, 189­212, 2007 Forecast and analysis assessment through skill scores M. Tonani et al. Title Science Forecast and analysis assessment through skill scores M. Tonani 1 , N. Pinardi 2 , C. Fratianni 1 Forecast and analysis assessment through skill scores M. Tonani et al. Title Page Abstract Introduction

  3. Forecast Technical Document Technical Glossary

    E-Print Network [OSTI]

    Forecast Technical Document Technical Glossary A document defining some of the terms used in the 2011 Production Forecast technical documentation. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the Forecast documentation. In some cases, the terms and the descriptions are "industry standard", in others

  4. Forecast Technical Document Tree Species

    E-Print Network [OSTI]

    Forecast Technical Document Tree Species A document listing the tree species included in the 2011 Production Forecast Tom Jenkins Justin Gilbert Ewan Mackie Robert Matthews #12;PF2011 ­ List of tree species The following is the list of species used within the Forecast System. Species are ordered alphabetically

  5. TRAVEL DEMAND AND RELIABLE FORECASTS

    E-Print Network [OSTI]

    Minnesota, University of

    TRAVEL DEMAND AND RELIABLE FORECASTS FOR TRANSIT MARK FILIPI, AICP PTP 23rd Annual Transportation transportation projects § Develop and maintain Regional Travel Demand Model § Develop forecast socio in cooperative review during all phases of travel demand forecasting 4 #12;Cooperative Review Should Include

  6. Consensus Coal Production Forecast for

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    in the consensus forecast produced in 2006, primarily from the decreased demand as a result of the current nationalConsensus Coal Production Forecast for West Virginia 2009-2030 Prepared for the West Virginia Summary 1 Recent Developments 2 Consensus Coal Production Forecast for West Virginia 10 Risks

  7. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400 .......................................................................................................................................1-1 ENERGY DEMAND FORECASTING AT THE CALIFORNIA ENERGY COMMISSION: AN OVERVIEW

  8. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16T23:59:59.000Z

    EMGT 835 FIELD PROJECT: Improving Inventory Control Using Forecasting By Juan Mario Balandran jmbg@hotmail.com Master of Science The University of Kansas Fall Semester, 2005 An EMGT Field Project report submitted...............................................................................................................................................10 Current Inventory Forecast Process ...........................................................................................10 Development of Alternative Forecast Process...

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

    SciTech Connect (OSTI)

    Widiss, R.; Porter, K.

    2014-03-01T23:59:59.000Z

    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.

  10. Short-Termed Integrated Forecasting System: 1993 Model documentation report

    SciTech Connect (OSTI)

    Not Available

    1993-05-01T23:59:59.000Z

    The purpose of this report is to define the Short-Term Integrated Forecasting System (STIFS) and describe its basic properties. The Energy Information Administration (EIA) of the US Energy Department (DOE) developed the STIFS model to generate short-term (up to 8 quarters), monthly forecasts of US supplies, demands, imports exports, stocks, and prices of various forms of energy. The models that constitute STIFS generate forecasts for a wide range of possible scenarios, including the following ones done routinely on a quarterly basis: A base (mid) world oil price and medium economic growth. A low world oil price and high economic growth. A high world oil price and low economic growth. This report is written for persons who want to know how short-term energy markets forecasts are produced by EIA. The report is intended as a reference document for model analysts, users, and the public.

  11. Fuel Price Forecasts INTRODUCTION

    E-Print Network [OSTI]

    Fuel Price Forecasts INTRODUCTION Fuel prices affect electricity planning in two primary ways and water heating, and other end-uses as well. Fuel prices also influence electricity supply and price because oil, coal, and natural gas are potential fuels for electricity generation. Natural gas

  12. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    Quantifying PV power output variability,Ē Solar Energy, vol.each solar sen at node i, P(t) the total power output of theSolar Forecasting Historically, traditional power generation technologies such as fossil and nu- clear power which were designed to run in stable output

  13. Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

    Forecasting and Resource Assessment, 1 st Edition, Editors:Forecasting and Resource Assessment, 1 st Edition, Editors:Forecasting and Resource Assessment, 1 st Ed.. Editor: Jan

  14. Forecasting oilfield economic performance

    SciTech Connect (OSTI)

    Bradley, M.E. (Univ. of Chicago, IL (United States)); Wood, A.R.O. (BP Exploration, Anchorage, AK (United States))

    1994-11-01T23:59:59.000Z

    This paper presents a general method for forecasting oilfield economic performance that integrates cost data with operational, reservoir, and financial information. Practices are developed for determining economic limits for an oil field and its components. The economic limits of marginal wells and the role of underground competition receive special attention. Also examined is the influence of oil prices on operating costs. Examples illustrate application of these concepts. Categorization of costs for historical tracking and projections is recommended.

  15. 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.

    2012-09-01T23:59:59.000Z

    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.

  16. March 6, 2013, Human Resource Services UF Tobacco-free Policy Update

    E-Print Network [OSTI]

    Mazzotti, Frank

    .hr.ufl.edu/academic/letters · Template letters have been updated to reflect statement in reference to verification of education#12;March 6, 2013, Human Resource Services #12;Agenda · UF Tobacco-free Policy Update · Vacant Appointments · OPT · Retirement Updates · Benefits Reminders & GatorCare Updates · Changes to FMLA Law · Summer

  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. (Decision and Information Sciences); (INESC Porto)

    2011-12-06T23:59:59.000Z

    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. Forecast Technical Document Growing Stock Volume

    E-Print Network [OSTI]

    Forecast Technical Document Growing Stock Volume Forecasts A document describing how growing stock (`standing') volume is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Growing stock volume forecasts Background A forecast of standing volume (or

  19. NOAA Harmful Algal Bloom Operational Forecast System Southwest Florida Forecast Region Maps

    E-Print Network [OSTI]

    Forecast System Southwest Florida Forecast Region Maps 0 20 4010 Miles #12;Bay-S Pinellas Bay-UPR Bay Bloom Operational Forecast System Southwest Florida Forecast Region Maps 0 5 102.5 Miles #12;Bay Harmful Algal Bloom Operational Forecast System Southwest Florida Forecast Region Maps 0 5 102.5 Miles #12

  20. Price forecasting for notebook computers.

    E-Print Network [OSTI]

    Rutherford, Derek Paul

    2012-01-01T23:59:59.000Z

    ??This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over aÖ (more)

  1. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01T23:59:59.000Z

    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.

  2. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN Manager Joseph O' Hagan Project Manager Kelly Birkinshaw Program Area Manager ENERGY-RELATED ENVIRONMENTAL

  3. Heating Season Has Ended An Update On The Numbers

    E-Print Network [OSTI]

    Heating Season Has Ended An Update On The Numbers Heating Season Has Ended The snow in the mid to last at least 10 days!! So, we are declaring an end to the heating season and entering late into what temperature dip. As you likely do at home, please be mindful of the weather forecast and adjust accordingly

  4. Application of a medium-range global hydrologic probabilistic forecast scheme to the Ohio River Basin

    SciTech Connect (OSTI)

    Voisin, Nathalie; Pappenberger, Florian; Lettenmaier, D. P.; Buizza, Roberto; Schaake, John

    2011-08-15T23:59:59.000Z

    A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003-2007. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium Range Weather Forecasts (ECMWF) analysis temperatures and wind, and Tropical Rainfall Monitoring Mission Multi Satellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF ensemble prediction system (EPS) 10-day ensemble forecast. A parallel set up was used where ECMWF EPS forecasts were interpolated to the spatial scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The flood prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. Initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.

  5. Conservation The Northwest ForecastThe Northwest Forecast

    E-Print Network [OSTI]

    & Resources Creating Mr. Toad's Wild Ride for the PNW's Energy Efficiency InCreating Mr. Toad's Wild RideNorthwest Power and Conservation Council The Northwest ForecastThe Northwest Forecast ≠≠ Energy EfficiencyEnergy Efficiency Dominates ResourceDominates Resource DevelopmentDevelopment Tom EckmanTom Eckman

  6. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    · NATIONAL AND GLOBAL FORECASTS · WEST VIRGINIA PROFILES AND FORECASTS · ENERGY · HEALTHCARE Research West Virginia University College of Business and Economics P.O. Box 6527, Morgantown, WV 26506 EXPERT OPINION PROVIDED BY Keith Burdette Cabinet Secretary West Virginia Department of Commerce

  7. CORPORATE GOVERNANCE AND MANAGEMENT EARNINGS FORECAST

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 CORPORATE GOVERNANCE AND MANAGEMENT EARNINGS FORECAST QUALITY: EVIDENCE FROM FRENCH IPOS Anis attributes, ownership retained, auditor quality, and underwriter reputation and management earnings forecast quality measured by management earnings forecast accuracy and bias. Using 117 French IPOs, we find

  8. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand.Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product estimates. Margaret Sheridan provided the residential forecast. Mitch Tian prepared the peak demand

  9. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Robert P. Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined provided estimates for demand response program impacts and contributed to the residential forecast. Mitch

  10. Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price Forecast

    E-Print Network [OSTI]

    Forecast Introduction.................................................................................................................................... 6 Demand................................................................... 16 The Base Case Forecast

  11. Electricity price forecasting in a grid environment.

    E-Print Network [OSTI]

    Li, Guang, 1974-

    2007-01-01T23:59:59.000Z

    ??Accurate electricity price forecasting is critical to market participants in wholesale electricity markets. Market participants rely on price forecasts to decide their bidding strategies, allocateÖ (more)

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

    SciTech Connect (OSTI)

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

    2013-11-01T23:59:59.000Z

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

  13. Atmospheric Lagrangian coherent structures considering unresolved turbulence and forecast uncertainty

    E-Print Network [OSTI]

    Ross, Shane

    Atmospheric Lagrangian coherent structures considering unresolved turbulence and forecast structures Stochastic trajectory Stochastic FTLE field Ensemble forecasting Uncertainty analysis a b s t r of the forecast FTLE fields is analyzed using ensemble forecasting. Unavoidable errors of the forecast velocity

  14. Update On The Wholesale Electricity Price Forecast & Modeling Results

    E-Print Network [OSTI]

    Control Board adopted a statewide water quality control policy on the use of Once Through Cooling (OTC Continue to Operate San Onofre 2,3 2,150 Continue to Operate Total 10,797 Continue to Operate Haynes CC 1,334 Retirement Scattergood 1-3 817 Retirement South Bay 1-4 693 Retirement Total 11,127 Retirement Alamitos 1-6 R

  15. Benefits of postponement for fashion products with forecast updates

    E-Print Network [OSTI]

    Gong, Huiling

    2005-01-01T23:59:59.000Z

    This thesis examines the benefit of postponement of fashion products by considering the overage cost of the intermediate product and the correlation between the demand for each end products produced from it. The benefit ...

  16. CSUF Economic Outlook and Forecasts Midyear Update, April 2011

    E-Print Network [OSTI]

    de Lijser, Peter

    , (4) sustained elevated oil prices, and (5) financial shocks from the European sovereign debt crisis in this recovery cycle with the expansion progressing at a faster clip in 2011 and 2012. Production indicators-based, almost self-sustained recovery where the transition from non-fundamentals (the inventory cycle

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

    SciTech Connect (OSTI)

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04T23:59:59.000Z

    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.

  18. PROBLEMS OF FORECAST1 Dmitry KUCHARAVY

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 PROBLEMS OF FORECAST1 Dmitry KUCHARAVY dmitry.kucharavy@insa-strasbourg.fr Roland DE GUIO roland for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods of the forecast errors. Second, using a contradiction analysis, a set of problems related to technology forecast

  19. Using reforecasts for probabilistic forecast calibration

    E-Print Network [OSTI]

    Hamill, Tom

    1 Using reforecasts for probabilistic forecast calibration Tom Hamill NOAA Earth System Research that is currently operational. #12;3 Why compute reforecasts? · For many forecast problems, such as long-lead forecasts or high-precipitation events, a few past forecasts may be insufficient for calibrating

  20. Forecast Combination With Outlier Protection Gang Chenga,

    E-Print Network [OSTI]

    Yuhong, Yang

    Forecast Combination With Outlier Protection Gang Chenga, , Yuhong Yanga,1 a313 Ford Hall, 224 Church St SE, Minneapolis, MN 55455 Abstract Numerous forecast combination schemes with distinct on combining forecasts with minimizing the occurrence of forecast outliers in mind. An unnoticed phenomenon

  1. Forecast Technical Document Felling and Removals

    E-Print Network [OSTI]

    Forecast Technical Document Felling and Removals Forecasts A document describing how volume fellings and removals are handled in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Felling and removals forecasts Background A fellings and removals

  2. Assessing Forecast Accuracy Measures Department of Economics

    E-Print Network [OSTI]

    Assessing Forecast Accuracy Measures Zhuo Chen Department of Economics Heady Hall 260 Iowa State forecast accuracy measures. In the theoretical direction, for comparing two forecasters, only when the errors are stochastically ordered, the ranking of the forecasts is basically independent of the form

  3. Load Forecast For use in Resource Adequacy

    E-Print Network [OSTI]

    -term Electricity Demand Forecasting System 1) Obtain Daily Regional Temperatures 6) Estimate Daily WeatherLoad Forecast 2019 For use in Resource Adequacy Massoud Jourabchi #12;In today's presentation d l­ Load forecast methodology ­ Drivers of the forecast f i­ Treatment of conservation

  4. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work to the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid provided the projections

  5. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work and expertise of numerous the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid provided the projections

  6. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work Sheridan provided the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid

  7. Nuclear Science References Database

    E-Print Network [OSTI]

    B. Pritychenko; E. B?tŠk; B. Singh; J. Totans

    2014-07-08T23:59:59.000Z

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

  8. Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model

    E-Print Network [OSTI]

    1 1 Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model 2007 Federal prices are being inputted into the model 2 Sales forecast Select yearsSales forecast Select years --Draft 0.53% Irrigation 2.76% Annual Growth Rates Preliminary Electricity ForecastAnnual Growth Rates

  9. Can earnings forecasts be improved by taking into account the forecast bias?

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Can earnings forecasts be improved by taking into account the forecast bias? François DOSSOU allow the calculation of earnings adjusted forecasts, for horizons from 1 to 24 months. We explain variables. From the forecast evaluation statistics viewpoints, the adjusted forecasts make it possible quasi

  10. Revised Economic andRevised Economic and Demand ForecastsDemand Forecasts

    E-Print Network [OSTI]

    Revised Economic andRevised Economic and Demand ForecastsDemand Forecasts April 14, 2009 Massoud,000 MW #12;6 Demand Forecasts Price Effect (prior to conservation) - 5,000 10,000 15,000 20,000 25,000 30 Jourabchi #12;2 Changes since the Last Draft ForecastChanges since the Last Draft Forecast Improved

  11. Poroelastic references

    SciTech Connect (OSTI)

    Christina Morency

    2014-12-12T23:59:59.000Z

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

  12. Poroelastic references

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

    Christina Morency

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

  13. Winter Heating Fuels Update

    Gasoline and Diesel Fuel Update (EIA)

    Heating Fuels Update For: Congressional Briefings October 20, 2014 | Washington, DC By U.S. Energy Information Administration Winter Heating Fuels Update October 20, 2014 |...

  14. Price forecasting for notebook computers

    E-Print Network [OSTI]

    Rutherford, Derek Paul

    2012-06-07T23:59:59.000Z

    This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a series of time periods, and the rates of change in the influence...

  15. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN with primary contributions in the area of decision support for reservoir planning and management Commission Energy-Related Environmental Research Joseph O' Hagan Contract Manager Joseph O' Hagan Project

  16. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

    Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN: California Energy Commission Energy-Related Environmental Research Joseph O' Hagan Contract Manager Joseph O' Hagan Project Manager Kelly Birkinshaw Program Area Manager ENERGY-RELATED ENVIRONMENTAL RESEARCH Martha

  17. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01T23:59:59.000Z

    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.

  18. Weather forecasting : the next generation : the potential use and implementation of ensemble forecasting

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01T23:59:59.000Z

    This thesis discusses ensemble forecasting, a promising new weather forecasting technique, from various viewpoints relating not only to its meteorological aspects but also to its user and policy aspects. Ensemble forecasting ...

  19. APPENDIX Q RULE IMPACT STATEMENT Subchapter 2. Incorporation By Reference 252:100-2-3. Incorporation by reference [AMENDED] APPENDIX Q. INCORPORATION BY REFERENCE [REVOKED

    E-Print Network [OSTI]

    unknown authors

    Reference, and Appendix Q, to update the federal regulations incorporated by reference. As required by the Administrative Rules on Rulemaking, the existing Appendix Q will be revoked and a new Appendix Q will be adopted. These proposals are part of the annual review of Title 40, Code of Federal Regulations (40 CFR) incorporations by reference. 2. CLASSES OF PERSONS AFFECTED: The classes of persons affected are the owners and operators of facilities that are subject to the regulations incorporated by reference.

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

    Office of Environmental Management (EM)

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

  1. FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007 INTEGRATED Table of Contents General Instructions for Demand Forecast Submittals.............................................................................. 4 Protocols for Submitted Demand Forecasts

  2. Applying Bayesian Forecasting to Predict New Customers' Heating Oil Demand.

    E-Print Network [OSTI]

    Sakauchi, Tsuginosuke

    2011-01-01T23:59:59.000Z

    ??This thesis presents a new forecasting technique that estimates energy demand by applying a Bayesian approach to forecasting. We introduce our Bayesian Heating Oil ForecasterÖ (more)

  3. Coal data: A reference

    SciTech Connect (OSTI)

    Not Available

    1995-02-01T23:59:59.000Z

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

  4. Reference Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared at 278, 298,NIST 800-53 NationalTreatment.Reference-Documents Sign

  5. Reference Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared at 278, 298,NIST 800-53 NationalTreatment.Reference-Documents

  6. Reference Material

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared at 278, 298,NIST 800-53Reference Materials There are a variety of

  7. STRESS AND FAULTING IN THE COSO GEOTHERMAL FIELD: UPDATE AND...

    Open Energy Info (EERE)

    FLANK AND COSO WASH Jump to: navigation, search OpenEI Reference LibraryAdd to library Conference Proceedings: STRESS AND FAULTING IN THE COSO GEOTHERMAL FIELD: UPDATE AND...

  8. Aggregate vehicle travel forecasting model

    SciTech Connect (OSTI)

    Greene, D.L.; Chin, Shih-Miao; Gibson, R. [Tennessee Univ., Knoxville, TN (United States)

    1995-05-01T23:59:59.000Z

    This report describes a model for forecasting total US highway travel by all vehicle types, and its implementation in the form of a personal computer program. The model comprises a short-run, econometrically-based module for forecasting through the year 2000, as well as a structural, scenario-based longer term module for forecasting through 2030. The short-term module is driven primarily by economic variables. It includes a detailed vehicle stock model and permits the estimation of fuel use as well as vehicle travel. The longer-tenn module depends on demographic factors to a greater extent, but also on trends in key parameters such as vehicle load factors, and the dematerialization of GNP. Both passenger and freight vehicle movements are accounted for in both modules. The model has been implemented as a compiled program in the Fox-Pro database management system operating in the Windows environment.

  9. LHCb Computing Resources: 2011 re-assessment, 2012 request and 2013 forecast

    E-Print Network [OSTI]

    Graciani, R

    2011-01-01T23:59:59.000Z

    This note covers the following aspects: re-assessment of computing resource usage estimates for 2011 data taking period, request of computing resource needs for 2012 data taking period and a first forecast of the 2013 needs, when no data taking is foreseen. Estimates are based on 2010 experienced and last updates from LHC schedule, as well as on a new implementation of the computing model simulation tool. Differences in the model and deviations in the estimates from previous presented results are stressed.

  10. Management forecast credibility and underreaction to news

    E-Print Network [OSTI]

    Ng, Jeffrey

    In this paper, we first document evidence of underreaction to management forecast news. We then hypothesize that the credibility of the forecast influences the magnitude of this underreaction. Relying on evidence that more ...

  11. Management Forecast Quality and Capital Investment Decisions

    E-Print Network [OSTI]

    Goodman, Theodore H.

    Corporate investment decisions require managers to forecast expected future cash flows from potential investments. Although these forecasts are a critical component of successful investing, they are not directly observable ...

  12. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01T23:59:59.000Z

    FORECASTING THE ROLE OF RENEWABLES IN HAWAII Jayant SathayeFORECASTING THE ROLF OF RENEWABLES IN HAWAII J Sa and Henrythe Conservation Role of Renewables November 18, 1980 Page 2

  13. Improving week two forecasts with multi-model re-forecast ensembles

    E-Print Network [OSTI]

    Whitaker, Jeffrey S.

    Improving week two forecasts with multi-model re-forecast ensembles Jeffrey S. Whitaker and Xue Wei NOAA-CIRES Climate Diagnostics Center, Boulder, CO Fr¬īed¬īeric Vitart Seasonal Forecasting Group, ECMWF dataset of ensemble 're-forecasts' from a single model can significantly improve the skill

  14. Updated January 2013 List of Faculty Advisors

    E-Print Network [OSTI]

    Eirinaki, Magdalini

    Updated January 2013 List of Faculty Advisors Note: While this list will change over time, you may keep the advisor originally assigned to you unless that advisor is not here (on leave or retired or has of the faculty advisors listed here or Rocio Avila, please refer to the CS Department Advising Flowchart at www

  15. Updated June 2014 List of Faculty Advisors

    E-Print Network [OSTI]

    Su, Xiao

    Updated June 2014 List of Faculty Advisors Note: While this list will change over time, you may keep the advisor originally assigned to you unless that advisor is not here (on leave or retired or has of the faculty advisors listed here or COSAC, please refer to the CS Department Advising Flowchart at www.cs.sjsu

  16. Updated August 2013 List of Faculty Advisors

    E-Print Network [OSTI]

    Su, Xiao

    Updated August 2013 List of Faculty Advisors Note: While this list will change over time, you may keep the advisor originally assigned to you unless that advisor is not here (on leave be seeing one of the faculty advisors listed here or Rocio Avila, please refer to the CS Department

  17. 5, 183218, 2008 A rainfall forecast

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    HESSD 5, 183­218, 2008 A rainfall forecast model using Artificial Neural Network N. Q. Hung et al An artificial neural network model for rainfall forecasting in Bangkok, Thailand N. Q. Hung, M. S. Babel, S Geosciences Union. 183 #12;HESSD 5, 183­218, 2008 A rainfall forecast model using Artificial Neural Network N

  18. Ensemble Forecast of Analyses With Uncertainty Estimation

    E-Print Network [OSTI]

    Boyer, Edmond

    Ensemble Forecast of Analyses With Uncertainty Estimation Vivien Mallet1,2, Gilles Stoltz3 2012 Mallet, Stoltz, Zhuk, Nakonechniy Ensemble Forecast of Analyses November 2012 1 / 14 hal-00947755,version1-21Feb2014 #12;Objective To produce the best forecast of a model state using a data assimilation

  19. (1) Ensemble forecast calibration & (2) using reforecasts

    E-Print Network [OSTI]

    Hamill, Tom

    1 (1) Ensemble forecast calibration & (2) using reforecasts Tom Hamill NOAA Earth System Research · Calibration: ; the statistical adjustment of the (ensemble) forecast ­ Rationale 1: Infer large-sample probabilities from small ensemble. ­ Rationale 2: Remove bias, increase forecast reliability while preserving

  20. Load forecast and treatment of conservation

    E-Print Network [OSTI]

    conservation is implicitly incorporated in the short-term demand forecast? #12;3 Incorporating conservationLoad forecast and treatment of conservation July 28th 2010 Resource Adequacy Technical Committee in the short-term model Our short-term model is an econometric model which can not explicitly forecast

  1. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand prepared the peak demand forecast. Ravinderpal Vaid provided the projections of commercial floor space

  2. FINAL STAFF FORECAST OF 2008 PEAK DEMAND

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION FINAL STAFF FORECAST OF 2008 PEAK DEMAND STAFFREPORT June 2007 CEC-200 of the information in this paper. #12;Abstract This document describes staff's final forecast of 2008 peak demand demand forecasts for the respective territories of the state's three investor-owned utilities (IOUs

  3. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand The demand forecast is the combined product of the hard work and expertise of numerous California Energy for demand response program impacts and contributed to the residential forecast. Mitch Tian prepared

  4. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work provided estimates for demand response program impacts and contributed to the residential forecast. Mitch

  5. TEPP Briefing Update

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

    * Comments have been incorporated and final review is in progress. Release date is forecast for early May 04 * Development of two additional MERRTT Modules - Rail Shipments -...

  6. ELECTRICITY DEMAND FORECAST COMPARISON REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005 Gorin Principal Authors Lynn Marshall Project Manager Kae C. Lewis Acting Manager Demand Analysis Office Valerie T. Hall Deputy Director Energy Efficiency and Demand Analysis Division Scott W. Matthews Acting

  7. Load Forecasting of Supermarket Refrigeration

    E-Print Network [OSTI]

    energy system. Observed refrigeration load and local ambient temperature from a Danish su- permarket renewable energy, is increasing, therefore a flexible energy system is needed. In the present ThesisLoad Forecasting of Supermarket Refrigeration Lisa Buth Rasmussen Kongens Lyngby 2013 M.Sc.-2013

  8. Reference wind farm selection for regional wind power prediction models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Reference wind farm selection for regional wind power prediction models Nils Siebert George.siebert@ensmp.fr, georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting is recognized today as a major requirement for a secure and economic integration of wind generation in power systems. This paper deals

  9. Forecasting Distributions with Experts Advice

    E-Print Network [OSTI]

    Sancetta, Alessio

    2006-03-14T23:59:59.000Z

    ) is the probability forecast based on an arbitrary vector wE in the unit simplex, experts forecasts ?ąE , and model {p?} . Remark 2 In most cases, we can choose c = 1/?, implying in the result below that c? = 1. Example 3 The prediction function is a mixture... 0 = 1, and #IT (k) = tk+1 ? tk. Define ek ? E. Theorem 12 Under Conditions 1 and 7, R1,...,t (pW ) ? c? K? k=0 Rt(k),...,t(k+1)?1 ( p?(e(k)) ) + c ln (#E) ?c K? k=1 ln ut(k) (ek, ek?1)? c K? k=0 t(k+1)?2? s=t(k) ln (us+1 (ek, ek)) . 9 Remark 13...

  10. Forecasting wind speed financial return

    E-Print Network [OSTI]

    D'Amico, Guglielmo; Prattico, Flavio

    2013-01-01T23:59:59.000Z

    The prediction of wind speed is very important when dealing with the production of energy through wind turbines. In this paper, we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model that has been shown to be able to reproduce accurately the statistical behavior of wind speed. The model is used to forecast, one step ahead, wind speed. In order to check the validity of the model we show, as indicator of goodness, the root mean square error and mean absolute error between real data and predicted ones. We also compare our forecasting results with those of a persistence model. At last, we show an application of the model to predict financial indicators like the Internal Rate of Return, Duration and Convexity.

  11. Multiagent Bayesian Forecasting of Structural Time-Invariant Dynamic Systems with

    E-Print Network [OSTI]

    Xiang, Yang

    . Alternatively, time series are represented by state-space models, also referred to as multivariate dynamic and science. We study forecasting of stochastic, dynamic systems based on observations from multivariate time to a discrete time, multivariate time series [1, 2]. The primary inference that we address is one- step

  12. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating Solar Power Basics (TheEtelligence (SmartHome Kyoung's pictureFlintFlowerForecast

  13. Geothermal wells: a forecast of drilling activity

    SciTech Connect (OSTI)

    Brown, G.L.; Mansure, A.J.; Miewald, J.N.

    1981-07-01T23:59:59.000Z

    Numbers and problems for geothermal wells expected to be drilled in the United States between 1981 and 2000 AD are forecasted. The 3800 wells forecasted for major electric power projects (totaling 6 GWe of capacity) are categorized by type (production, etc.), and by location (The Geysers, etc.). 6000 wells are forecasted for direct heat projects (totaling 0.02 Quads per year). Equations are developed for forecasting the number of wells, and data is presented. Drilling and completion problems in The Geysers, The Imperial Valley, Roosevelt Hot Springs, the Valles Caldera, northern Nevada, Klamath Falls, Reno, Alaska, and Pagosa Springs are discussed. Likely areas for near term direct heat projects are identified.

  14. Online Forecast Combination for Dependent Heterogeneous Data

    E-Print Network [OSTI]

    Sancetta, Alessio

    the single individual forecasts. Several studies have shown that combining forecasts can be a useful hedge against structural breaks, and forecast combinations are often more stable than single forecasts (e.g. Hendry and Clements, 2004, Stock and Watson, 2004... in expectations. Hence, we have the following. Corollary 4 Suppose maxt?T kl (Yt, hwt,Xti)kr ? A taking expectation on the left hand side, adding 2A ? T and setting ? = 0 in mT (?), i.e. TX t=1 E [lt (wt)? lt (ut...

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

    Office of Environmental Management (EM)

    to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

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

    Office of Environmental Management (EM)

    to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

  17. Solid low-level waste forecasting guide

    SciTech Connect (OSTI)

    Templeton, K.J.; Dirks, L.L.

    1995-03-01T23:59:59.000Z

    Guidance for forecasting solid low-level waste (LLW) on a site-wide basis is described in this document. Forecasting is defined as an approach for collecting information about future waste receipts. The forecasting approach discussed in this document is based solely on hanford`s experience within the last six years. Hanford`s forecasting technique is not a statistical forecast based upon past receipts. Due to waste generator mission changes, startup of new facilities, and waste generator uncertainties, statistical methods have proven to be inadequate for the site. It is recommended that an approach similar to Hanford`s annual forecasting strategy be implemented at each US Department of Energy (DOE) installation to ensure that forecast data are collected in a consistent manner across the DOE complex. Hanford`s forecasting strategy consists of a forecast cycle that can take 12 to 30 months to complete. The duration of the cycle depends on the number of LLW generators and staff experience; however, the duration has been reduced with each new cycle. Several uncertainties are associated with collecting data about future waste receipts. Volume, shipping schedule, and characterization data are often reported as estimates with some level of uncertainty. At Hanford, several methods have been implemented to capture the level of uncertainty. Collection of a maximum and minimum volume range has been implemented as well as questionnaires to assess the relative certainty in the requested data.

  18. The Value of Wind Power Forecasting

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

    Wind Power Forecasting Preprint Debra Lew and Michael Milligan National Renewable Energy Laboratory Gary Jordan and Richard Piwko GE Energy Presented at the 91 st American...

  19. Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations

    E-Print Network [OSTI]

    Kemner, Ken

    Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations Audun Botterud://www.dis.anl.gov/projects/windpowerforecasting.html IAWind 2010 Ames, IA, April 6, 2010 #12;Outline Background Using wind power forecasts in market operations ­ Current status in U.S. markets ­ Handling uncertainties in system operations ­ Wind power

  20. U-M Construction Forecast December 15, 2011 U-M Construction Forecast

    E-Print Network [OSTI]

    Kamat, Vineet R.

    U-M Construction Forecast December 15, 2011 U-M Construction Forecast Spring ≠ Fall 2012 As of December 15, 2011 Prepared by AEC Preliminary & Advisory #12;U-M Construction Forecast December 15, 2011 Overview ∑ Campus by campus ∑ Snapshot in time ≠ Not all projects ∑ Construction coordination efforts

  1. NOAA GREAT LAKES COASTAL FORECASTING SYSTEM Forecasts (up to 5 days in the future)

    E-Print Network [OSTI]

    conditions for up to 5 days in the future. These forecasts are run twice daily, and you can step through are generated every 6 hours and you can step backward in hourly increments to view conditions over the previousNOAA GREAT LAKES COASTAL FORECASTING SYSTEM Forecasts (up to 5 days in the future) and Nowcasts

  2. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

    Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

  3. Ensemble forecast of analyses: Coupling data assimilation and sequential aggregation

    E-Print Network [OSTI]

    Mallet, Vivien

    Ensemble forecast of analyses: Coupling data assimilation and sequential aggregation Vivien Mallet1. [1] Sequential aggregation is an ensemble forecasting approach that weights each ensemble member based on past observations and past forecasts. This approach has several limitations: The weights

  4. Probabilistic Wind Speed Forecasting using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Washington at Seattle, University of

    is to issue deterministic forecasts based on numerical weather prediction models. Uncertainty canProbabilistic Wind Speed Forecasting using Ensembles and Bayesian Model Averaging J. Mc discretization than is seen in other weather quantities. The prevailing paradigm in weather forecasting

  5. Coordinating production quantities and demand forecasts through penalty schemes

    E-Print Network [OSTI]

    Swaminathan, Jayashankar M.

    Coordinating production quantities and demand forecasts through penalty schemes MURUVVET CELIKBAS1 departments which enable organizations to match demand forecasts with production quantities. This research problem where demand is uncertain and the marketing de- partment provides a forecast to manufacturing

  6. CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Demand Forecast report is the product of the efforts of many current and former California Energy-2 Demand Forecast Disaggregation......................................................1-4 Statewide

  7. HIERARCHY OF PRODUCTION DECISIONS Forecasts of future demand

    E-Print Network [OSTI]

    Brock, David

    HIERARCHY OF PRODUCTION DECISIONS Forecasts of future demand Aggregate plan Master production Planning and Forecast Bias · Forecast error seldom is normally distributed · There are few finite planning

  8. Forecasting Market Demand for New Telecommunications Services: An Introduction

    E-Print Network [OSTI]

    Parsons, Simon

    Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc in demand forecasting for new communication services. Acknowledgments: The writing of this paper commenced employers or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica- tions

  9. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    has developed longterm forecasts of transportation energy demand as well as projected ranges of transportation fuel and crude oil import requirements. The transportation energy demand forecasts makeCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY

  10. NREL: Transmission Grid Integration - Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the Contributions andData and ResourcesOtherForecasting NREL researchers use solar and

  11. Electricity Monthly Update

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

    Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S....

  12. Directives Quarterly Updates

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

    Listings of new Justification Memoranda and new or revised Directives that have been posted to the DOE Directives, Delegations, and Requirements Portal. Updated quarterly.

  13. Plans, Updates, Regulatory Documents

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

    2010 Target Action Level (TAL) Exceedance Report 2011 Updates on Permit Compliance March 7, 2013, NPDES Permit No. NM0030759 - Request for Extenstion to Submit Renewal Application...

  14. Electricity Monthly Update

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

    See all Electricity Reports Electricity Monthly Update With Data for September 2014 | Release Date: Nov. 25, 2014 | Next Release Date: Dec. 23, 2014 Previous Issues Issue:...

  15. Electricity Monthly Update

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

    See all Electricity Reports Electricity Monthly Update With Data for October 2014 | Release Date: Dec. 23, 2014 | Next Release Date: Jan. 26, 2015 Previous Issues Issue:...

  16. Skye, Schell, Washington Update

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

    Updates in the Program 13 qualified ESCOs under GSA Schedule 84 * Four Small Business vendors Expanded ECMs to solar (PV) and related HVAC equipment ...

  17. Navy Technology Evaluation Update

    Broader source: Energy.gov [DOE]

    Presentation covers the Navy Technology Evaluation update at the Federal Utility Partnership Working Group (FUPWG) meeting, held on November 18-19, 2009.

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

    Energy Savers [EERE]

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

  19. Forecasting of Solar Radiation Detlev Heinemann, Elke Lorenz, Marco Girodo

    E-Print Network [OSTI]

    Heinemann, Detlev

    Forecasting of Solar Radiation Detlev Heinemann, Elke Lorenz, Marco Girodo Oldenburg University have been presented more than twenty years ago (Jensenius, 1981), when daily solar radiation forecasts

  20. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    differ slightly from official EIA data reports." " Sources: 2006 and 2007 data based on: Energy Information Administration (EIA), Annual Coal Report 2007, DOEEIA-0584(2007)...

  1. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    .084213257,4.084763527,4.085253239,4.086043358,4.086883545,4.08779335 " Wood and Other Biomass 4, 5",2.012529135,2.178429127,2.202429295,2.202429295,2.202429295,2.202429295,2.202...

  2. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    9271171,0.4940533936,0.4959642291,0.5000987649,0.5019134879,0.5048595071 " Commercial (biomass)",0.1225208715,0.123636879,0.123636879,0.123636879,0.123636879,0.123636879,0.12363687...

  3. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    339333534,4.339333534,4.339333534,4.339333534,4.339333534,4.339333534 " Wood and Other Biomass 4, 5",2.012529135,2.178429127,2.202429295,2.202429295,2.202429295,2.202429295,3.202...

  4. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    93561602,0.4912903309,0.493681103,0.4979000986,0.4991129935,0.5017791986 " Commercial (biomass)",0.1225208715,0.123636879,0.123636879,0.123636879,0.123636879,0.123636879,0.12363687...

  5. Report: An Updated Annual Enrgy Outlook 2009 Reference Case...

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

    80786,1464.767212,1483.14917,1502.96521,1520.739136,1541.415894,1567.712524,1574.372437,1603.990845,1621.778076,1658.238892,1685.856445,1717.056152 "Prices in Nominal Dollars" "...

  6. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    generated for sale to the grid and for own use from renewable sources, and non-electric energy from renewable sources. Excludes ethanol and nonmarketed" "renewable energy...

  7. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    and Development - Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary," "Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway,...

  8. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    580341,0.234126538,0.2484457195,0.2636235356,0.2796605229,0.2965483367,0.3142693639 " Biofuels Heat and Coproducts",0.3014252484,0.4017974138,0.8812832832,0.6545989513,0.7614424229...

  9. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    718282,0.4047937393,0.426415354,0.4484965503,0.4709428847,0.4936529398,0.5165205002 " Biofuels Heat and Coproducts",0.3014252484,0.4017974138,0.8727406263,0.6553280354,0.7593224645...

  10. Report: An Updated Annual Enrgy Outlook 2009 Reference Case...

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

    Federal Highway Administration, Highway Statistics 2005 (Washington, DC, October 2006); Oak Ridge National Laboratory," "Transportation Energy Data Book: Edition 27 and Annual...

  11. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    Federal Highway Administration, Highway Statistics 2005 (Washington, DC, October 2006); Oak Ridge National Laboratory," "Transportation Energy Data Book: Edition 27 and Annual...

  12. Report: An Updated Annual Enrgy Outlook 2009 Reference Case...

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

    3. Energy Prices by Sector and Source" " (2007 dollars per million Btu, unless otherwise noted)" ,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,20...

  13. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    69885,198.2767029,201.6399841,203.1015015,205.0171509,206.375,214.1217346 " Combustion TurbineDiesel",128.0535889,130.4069824,131.0970154,134.3223114,135.7783051,139.0514526,140.2...

  14. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    954,187.4152832,195.0196533,198.018158,199.3361816,199.999054,202.2591553 " Combustion TurbineDiesel",128.0535889,130.4069824,131.0970154,134.1412354,135.597229,137.0042267,138.13...

  15. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    02222,285.047821,287.803772,286.3456116,289.9999695,296.2648315,293.4924622 " Ethanol Wholesale Price",256.951416,212.434845,239.2897644,239.2897644,187.5945435,218.6475677,218.224...

  16. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    851,285.4412842,288.5114746,286.9178162,290.6092529,293.4446106,296.4165649 " Ethanol Wholesale Price",256.951416,212.434845,239.2897644,239.2897644,186.9664001,216.5590668,216.755...

  17. Report: An Updated Annual Enrgy Outlook 2009 Reference Case...

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

    "Prices (nominal dollars per unit)" " dollars per barrel" " Low Sulfur Light Price 13",66.04425049,72.33104706,101.2538528,41.82230377,54.13137817,68.26350403,7...

  18. Report: An Updated Annual Enrgy Outlook 2009 Reference Case...

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

    "Prices (nominal dollars per unit)" " dollars per barrel" " Low Sulfur Light Price 13",66.04425049,72.33104706,101.2538528,41.80298615,54.00071335,68.15581512,7...

  19. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    format, definition, and respondent type. In addition, 2006 and 2007 values include net storage injections." " 11 Represents lower 48 onshore and offshore supplies." " 12...

  20. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    76746,168.7196808,167.7555847,167.2697449,166.1452637,165.26474,163.7099457,162.1619873 " Refrigeration",73.73152161,73.53018188,70.35580444,69.01031494,68.77349854,68.24703217,68....

  1. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    047,166.5447693,166.1189423,166.1058655,165.6287994,165.2559509,163.7746735,162.5454559 " Refrigeration",73.73152161,73.53016663,70.39669037,69.04760742,68.3507309,67.49963379,67.0...

  2. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    ,0.3095597923,0.3089521229,0.3097482622,0.3104477823,0.3113028109,0.3122006357 "Delivered Energy Consumption by End Use" " Space Heating 1",1.659170747,1.786749244,1.892402887,1.9...

  3. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    ,0.3093057573,0.3091662526,0.3099833727,0.3105697036,0.3115277886,0.3126308322 "Delivered Energy Consumption by End Use" " Space Heating 1",1.65917182,1.786752224,1.892034054,1.96...

  4. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    4288.022461,4495.833008,4718.956055 "Energy Intensity" " (thousand Btu per 2000 dollar of GDP)" " Delivered Energy",6.45164299,6.422497749,6.280744553,6.26495409,6.143614769,6.0102...

  5. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    4369.788574,4597.428223,4843.846191 "Energy Intensity" " (thousand Btu per 2000 dollar of GDP)" " Delivered Energy",6.45164299,6.422497749,6.283946991,6.304526806,6.22622776,6.0826...

  6. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    666,1876.378052,1886.589233,1896.617065,1906.307617,1915.627686,1924.664062,1933.551636 " Energy Intensity" " (million Btu per household)" " Delivered Energy Consumption",95.737358...

  7. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    086,1876.765991,1887.016235,1897.062622,1906.736938,1916.007446,1924.966064,1933.756714 " Energy Intensity" " (million Btu per household)" " Delivered Energy Consumption",95.737365...

  8. An Updated Anual Energy Outlook 2009 Reference Case

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    1011001, July 2004. 7 Electric Power Research Institute, Palo Alto, California, The Green Grid, Energy Savings and Carbon Emissions Reductions Enabled by a Smart Grid,...

  9. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    82,0.03032295778,0.0484597832,0.0715117529,0.08738397807,0.09538029134,0.1489757597 " Biodiesel",0.01634000055,0.03195999935,0.05162922293,0.0603415668,0.04972303659,0.05156201124,...

  10. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    485,0.04698261991,0.0499894917,0.07529722899,0.09143737704,0.134942472,0.1123351306 " Biodiesel",0.01634000055,0.03195999935,0.05162922293,0.0603415668,0.05086546764,0.05111300573,...

  11. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    ,52.30285645,44.93989182,37.57692337,37.57692337,37.57692337,37.57692337,37.57692337 " Economy",151.0680084,119.2772064,181.7343292,192.2477264,200.8796387,230.3806,237.3785706,233...

  12. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    ,52.30285645,44.93989182,37.57692337,37.57692337,37.57692337,37.57692337,37.57692337 " Economy",151.0680695,119.2772064,184.7323303,193.9302216,191.5695343,228.6072388,241.4474335,...

  13. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    plants that only produce electricity." " 3 Includes electricity generation from fuel cells." " 4 Includes non-biogenic municipal waste. The Energy Information Administration...

  14. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    4. Oil and Gas Supply" ,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023,2024,2025,2026,2027,2028,2029,2030 "Crude Oil" "Lower 48 Average...

  15. Report: An Updated Annual Energy Outlook 2009 Reference Case...

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

    8. Carbon Dioxide Emissions by Sector and Source" " (million metric tons carbon dioxide equivalent, unless otherwise noted)" ,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016...

  16. Agricultural and Resource Economics Update

    E-Print Network [OSTI]

    2011-01-01T23:59:59.000Z

    forecasting drought effects on agriculture based on waterEffects of 2009 Drought on San Joaquin Valley Agriculture

  17. New Concepts in Wind Power Forecasting Models

    E-Print Network [OSTI]

    Kemner, Ken

    New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, Jo√£o Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind for more accurate short term wind power forecasting models has led to solid and impressive development

  18. Inverse Modelling to Forecast Enclosure Fire Dynamics†

    E-Print Network [OSTI]

    Jahn, Wolfram

    . This thesis proposes and studies a method to use measurements of the real event in order to steer and accelerate fire simulations. This technology aims at providing forecasts of the fire development with a positive lead time, i.e. the forecast of future events...

  19. QUIKSCAT MEASUREMENTS AND ECMWF WIND FORECASTS

    E-Print Network [OSTI]

    Malmberg, Anders

    . (2004) this forecast error was encountered when assimilating satellite measurements of zonal wind speeds between satellite measurements and meteorological forecasts of near-surface ocean winds. This type of covariance enters in assimilation techniques such as Kalman filtering. In all, six residual fields

  20. QUIKSCAT MEASUREMENTS AND ECMWF WIND FORECASTS

    E-Print Network [OSTI]

    Malmberg, Anders

    . (2004) this forecast error was encountered when assimilating satellite measurements of zonal wind speeds between satellite measurements and meteorological forecasts of near­surface ocean winds. This type of covariance enters in assimilation techniques such as Kalman filtering. In all, six residual fields

  1. Nonparametric models for electricity load forecasting

    E-Print Network [OSTI]

    Genève, Université de

    Electricity consumption is constantly evolving due to changes in people habits, technological innovations1 Nonparametric models for electricity load forecasting JANUARY 23, 2015 Yannig Goude, Vincent at University Paris-Sud 11 Orsay. His research interests are electricity load forecasting, more generally time

  2. UHERO FORECAST PROJECT DECEMBER 5, 2014

    E-Print Network [OSTI]

    deficits. After solid 3% growth this year, real GDP growth will recede a bit for the next two years. New household spending. Real GDP will firm above 3% in 2015. · The pace of growth in China has continuedUHERO FORECAST PROJECT DECEMBER 5, 2014 Asia-Pacific Forecast: Press Version: Embargoed Until 2

  3. -Assessment of current water conditions -Precipitation Forecast

    E-Print Network [OSTI]

    #12;-Assessment of current water conditions - Precipitation Forecast - Recommendations for Drought of the mountains, so early demand for irrigation water should be minimal as we officially move into spring. Western, it is forecast to bring wet snow to the eastern slope of the Rockies, with less accumulations west of the divide

  4. A NEW APPROACH FOR EVALUATING ECONOMIC FORECASTS

    E-Print Network [OSTI]

    Vertes, Akos

    APPROACH FOR EVALUATING ECONOMIC FORECASTS Tara M. Sinclair , H.O. Stekler, and Warren Carnow Department of Economics The George Washington University Monroe Hall #340 2115 G Street NW Washington, DC 20052 JEL Codes, Mahalanobis Distance Abstract This paper presents a new approach to evaluating multiple economic forecasts

  5. 2013 Midyear Economic Forecast Sponsorship Opportunity

    E-Print Network [OSTI]

    de Lijser, Peter

    2013 Midyear Economic Forecast Sponsorship Opportunity Thursday, April 18, 2013, ­ Hyatt Regency Irvine 11:30 a.m. ­ 1:30 p.m. Dr. Anil Puri presents his annual Midyear Economic Forecast addressing and Economics at California State University, Fullerton, the largest accredited business school in California

  6. Electric Turbo Compounding Technology Update

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

    Turbo Compounding Technology Update Electric Turbo Compounding Technology Update 15 August, 2007 Carl Vuk 15 August, 2007 Carl Vuk Electric Turbo Compounding Highlights Electric...

  7. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1994-02-01T23:59:59.000Z

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

  8. Earthquake Forecast via Neutrino Tomography

    E-Print Network [OSTI]

    Bin Wang; Ya-Zheng Chen; Xue-Qian Li

    2011-03-29T23:59:59.000Z

    We discuss the possibility of forecasting earthquakes by means of (anti)neutrino tomography. Antineutrinos emitted from reactors are used as a probe. As the antineutrinos traverse through a region prone to earthquakes, observable variations in the matter effect on the antineutrino oscillation would provide a tomography of the vicinity of the region. In this preliminary work, we adopt a simplified model for the geometrical profile and matter density in a fault zone. We calculate the survival probability of electron antineutrinos for cases without and with an anomalous accumulation of electrons which can be considered as a clear signal of the coming earthquake, at the geological region with a fault zone, and find that the variation may reach as much as 3% for $\\bar \

  9. MSSM Forecast for the LHC

    E-Print Network [OSTI]

    Maria Eugenia Cabrera; Alberto Casas; Roberto Ruiz de Austri

    2010-12-10T23:59:59.000Z

    We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of $M_Z$ is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental information is equally robust, we perform separate analyses depending on the group of observables used. When only the most robust ones are used, the favoured region of the parameter space contains a significant portion outside the LHC reach. This effect gets reinforced if the Higgs mass is not close to its present experimental limit and persits when dark matter constraints are included. Only when the g-2 constraint (based on $e^+e^-$ data) is considered, the preferred region (for $\\mu>0$) is well inside the LHC scope. We also perform a Bayesian comparison of the positive- and negative-$\\mu$ possibilities.

  10. Changing quantum reference frames

    E-Print Network [OSTI]

    Matthew C. Palmer; Florian Girelli; Stephen D. Bartlett

    2014-05-21T23:59:59.000Z

    We consider the process of changing reference frames in the case where the reference frames are quantum systems. We find that, as part of this process, decoherence is necessarily induced on any quantum system described relative to these frames. We explore this process with examples involving reference frames for phase and orientation. Quantifying the effect of changing quantum reference frames serves as a first step in developing a relativity principle for theories in which all objects including reference frames are necessarily quantum.

  11. Using Wikipedia to forecast diseases

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered energy consumption by sectorlongUpdates byUser GuideHadoopUsing Wikipedia to

  12. T-585: Mac OS X v10.6.7 Security Update 2011-001 | Department...

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

    installation is to start up from the volume that you wish to update. reference LINKS: APPLE-SA-2011-03-21-1 Mac OS X v10.6.7 About the Mac OS X Server v10.6.7 Update Apple...

  13. PSO (FU 2101) Ensemble-forecasts for wind power

    E-Print Network [OSTI]

    PSO (FU 2101) Ensemble-forecasts for wind power Analysis of the Results of an On-line Wind Power Ensemble- forecasts for wind power (FU2101) a demo-application producing quantile forecasts of wind power correct) quantile forecasts of the wind power production are generated by the application. However

  14. A New Measure of Earnings Forecast Uncertainty Xuguang Sheng

    E-Print Network [OSTI]

    Kim, Kiho

    A New Measure of Earnings Forecast Uncertainty Xuguang Sheng American University Washington, D of earnings forecast uncertainty as the sum of dispersion among analysts and the variance of mean forecast available to analysts at the time they make their forecasts. Hence, it alleviates some of the limitations

  15. AN ANALYSIS OF FORECAST BASED REORDER POINT POLICIES : THE BENEFIT

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    AN ANALYSIS OF FORECAST BASED REORDER POINT POLICIES : THE BENEFIT OF USING FORECASTS Mohamed Zied Ch^atenay-Malabry Cedex, France Abstract: In this paper, we analyze forecast based inventory control policies for a non-stationary demand. We assume that forecasts and the associated uncertainties are given

  16. The Complexity of Forecast Testing Lance Fortnow # Rakesh V. Vohra +

    E-Print Network [OSTI]

    Fortnow, Lance

    The Complexity of Forecast Testing Lance Fortnow # Rakesh V. Vohra + Abstract Consider a weather forecaster predicting a probability of rain for the next day. We consider tests that given a finite sequence of forecast predictions and outcomes will either pass or fail the forecaster. Sandroni shows that any test

  17. Does increasing model stratospheric resolution improve extended range forecast skill?

    E-Print Network [OSTI]

    Does increasing model stratospheric resolution improve extended range forecast skill? Greg Roff,1 forecast skill at high Southern latitudes is explored. Ensemble forecasts are made for two model configurations that differ only in vertical resolution above 100 hPa. An ensemble of twelve 30day forecasts

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

    SciTech Connect (OSTI)

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

    2011-10-01T23:59:59.000Z

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

  19. Univariate Modeling and Forecasting of Monthly Energy Demand Time Series

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural demand time series based only on data for six years to forecast the demand for the seventh year. Both networks, Neural networks, Modeling, Forecasting, Energy demand, Time series forecasting, Power system

  20. PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022

    E-Print Network [OSTI]

    PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA or adequacy of the information in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid provided the projections

  1. Strategic safety stocks in supply chains with evolving forecasts

    E-Print Network [OSTI]

    Graves, Stephen C.

    we have an evolving demand forecast. Under assumptions about the forecasts, the demand process their supply chain operations based on a forecast of future demand over some planning horizon. Furthermore stock inventory in a supply chain that is subject to a dynamic, evolving demand forecast. In particular

  2. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST Energy Demand 2008-2018 forecast supports the analysis and recommendations of the 2007 Integrated Energy Commission demand forecast models. Both the staff draft energy consumption and peak forecasts are slightly

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

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

  4. A leading index of drilling activity: Update and improvements

    SciTech Connect (OSTI)

    Buell, R.S.; Maurer, R.A.

    1986-01-01T23:59:59.000Z

    A five-component composite leading index of United States rotary rig drilling activity is updated. The index is presented for 1949 through April 1986 and is shown to consistently lead turning points in drilling activity. Seven new leading indices based on some new components are also presented. A forecast of drilling activity is made for the remainder of 1986 based on the leading index and the current economic condition of the petroleum industry. The methods used to prepare time series and construct indices are reviewed.

  5. Environmental Guidance Program Reference Book: American Indian Religious Freedom Act

    SciTech Connect (OSTI)

    Not Available

    1987-11-01T23:59:59.000Z

    This Reference Book contains a copy of the American Indian Religious Freedom Act and guidance for DOE compliance with the statute. The document is provided to DOE and contractor staff for informational purposes only and should not be interpreted as legal guidance. Updates that include important new requirements will be provided periodically.

  6. SolarAnywhere forecast (Perez & Hoff) This chapter describes, and presents an evaluation of, the forecast models imbedded in the

    E-Print Network [OSTI]

    Perez, Richard R.

    SolarAnywhere forecast (Perez & Hoff) ABSTRACT This chapter describes, and presents an evaluation of, the forecast models imbedded in the SolarAnywhere platform. The models include satellite derived cloud motion based forecasts for the short to medium horizon (1 5 hours) and forecasts derived from NOAA

  7. Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

    J.B. , 2004: Probabilistic wind power forecasts using localforecast intervals for wind power output using NWP-predictedsources such as wind and solar power. Integration of this

  8. Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

    United States California Solar Initiative Coastally Trappedparticipants in the California Solar Initiative (CSI)on location. In California, solar irradiance forecasts near

  9. Wind Speed Forecasting for Power System Operation

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

    In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

  10. Appendix A: Fuel Price Forecast Introduction..................................................................................................................................... 1

    E-Print Network [OSTI]

    Appendix A: Fuel Price Forecast Introduction ................................................................................................................... 17 INTRODUCTION Since the millennium, the trend for fuel prices has been one of uncertainty prices, which have traditionally been relatively stable, increased by about 50 percent in 2008. Fuel

  11. STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES 2005 TO 2018 Mignon Marks Principal Author Mignon Marks Project Manager David Ashuckian Manager ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY DIVISION B.B. Blevins Executive Director

  12. Essays in International Macroeconomics and Forecasting

    E-Print Network [OSTI]

    Bejarano Rojas, Jesus Antonio

    2012-10-19T23:59:59.000Z

    This dissertation contains three essays in international macroeconomics and financial time series forecasting. In the first essay, I show, numerically, that a two-country New-Keynesian Sticky Prices model, driven by monetary and productivity shocks...

  13. Dynamic Algorithm for Space Weather Forecasting System

    E-Print Network [OSTI]

    Fischer, Luke D.

    2011-08-08T23:59:59.000Z

    for the designation as UNDERGRADUATE RESEARCH SCHOLAR April 2010 Major: Nuclear Engineering DYNAMIC ALGORITHM FOR SPACE WEATHER FORECASTING SYSTEM A Junior Scholars Thesis by LUKE DUNCAN FISCHER Submitted to the Office of Undergraduate... 2010 Major: Nuclear Engineering iii ABSTRACT Dynamic Algorithm for Space Weather Forecasting System. (April 2010) Luke Duncan Fischer Department of Nuclear Engineering Texas A&M University Research Advisor: Dr. Stephen Guetersloh...

  14. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01T23:59:59.000Z

    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.

  15. Sixth Northwest Conservation and Electric Power Plan Chapter 3: Electricity Demand Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Chapter 3: Electricity Demand Forecast Summary............................................................................................................ 2 Sixth Power Plan Demand Forecast................................................................................................ 4 Demand Forecast Range

  16. Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast Energy Demand................................................................................................................................. 1 Demand Forecast Methodology.................................................................................................. 3 New Demand Forecasting Model for the Sixth Plan

  17. LEAVE OF ABSENCE OR Updated 11/2010

    E-Print Network [OSTI]

    Heller, Barbara

    refer to the "Transfer Out" handout on the International Center website. Procedures: 1) Initiate a LOALEAVE OF ABSENCE OR WITHDRAWAL Updated 11/2010 International Center · Illinois Institute of Technology 3201 South State Street, MTCC - Room 203 · Chicago, IL 60616 Phone: 312.567.3680 · Fax: 312

  18. Program reference book for the Energy Economic Data Base Program (EEDB)

    SciTech Connect (OSTI)

    Allen, R.E.; Brown, P.E.; Hodson, J.S.; Kaminski, R.S.; Ziegler, E.J.

    1983-07-01T23:59:59.000Z

    The objective of the Energy Economic Data Base (EEDB) Program is to provide periodic updates of technical and cost (capital, fuel and operating and maintenance) information for nuclear and comparison electric power generating stations that is of significance to the US Department of Energy (USDOE). The purpose of this Reference Book is to provide the historical content of the EEDB through the Fourth Update (1981). It contains important descriptive and tutorial information concerning the structure and use of the EEDB. It also contains reports of work done to support various aspects of the first four updates, together with significant reference data developed during those updates. As a convenience to the user, it is intended that the Reference Book be sufficiently stable that revisions are required no more frequently than once every five years.

  19. State Energy Price System: 1982 update

    SciTech Connect (OSTI)

    Imhoff, K.L.; Fang, J.M.

    1984-10-01T23:59:59.000Z

    The State Energy Price System (STEPS) contains estimates of energy prices for ten major fuels (electricity, natural gas, metallurgical coal, steam coal, distillate, motor gasoline, diesel, kerosene/jet fuel, residual fuel, and liquefied petroleum gas), by major end-use sectors (residential, commercial, industrial, transportation, and electric utility), and by state through 1982. Both physical unit prices and prices per million Btu are included in STEPS. Major changes in STEPS data base for 1981 and 1982 are described. The most significant changes in procedures for the updates occur in the residential sector distillate series and the residential sector kerosene series. All physical unit and Btu prices are shown with three significant digits instead of with four significant digits as shown in the original documentation. Details of these and other changes are contained in this report, along with the updated data files. 31 references, 65 tables.

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

    SciTech Connect (OSTI)

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

    2014-05-01T23:59:59.000Z

    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.

  1. Forecasting the Price of Oil

    E-Print Network [OSTI]

    Ron Alquist; Lutz Kilian; Robert J. Vigfusson; Ron Alquist; Lutz Kilian; Robert J. Vigfusson

    2011-01-01T23:59:59.000Z

    NOTE: International Finance Discussion Papers are preliminary materials circulated to stimulate discussion and critical comment. References in publications to International Finance Discussion Papers (other than an acknowledgment that the writer has had access to unpublished material) should be cleared with the author or authors. Recent IFDPs are available on the Web at www.federalreserve.gov/pubs/ifdp/. This paper can be downloaded without charge from Social

  2. Updates - DOE Directives, Delegations, and Requirements

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

    Updates by Diane Johnson Email Alerts Subscribe to automatic e-mail notification about updates to the portal. Email Alerts...

  3. Academy Member Annual Update Report 1Academy Member Update Report

    E-Print Network [OSTI]

    Academy Member Annual Update Report 1Academy Member Update Report The annual update report is an important activity associated with active membership in the Academy. These reports are due annually questions. A separate document includes the required report format and directions. Please email omerad

  4. Program Review Updates and Briefings

    Broader source: Energy.gov [DOE]

    You can learn more about the U.S. Department of Energy (DOE) Geothermal Technologies Program by reading its program review updates and program briefings. These updates and briefings feature...

  5. High frequency reference electrode

    DOE Patents [OSTI]

    Kronberg, J.W.

    1994-05-31T23:59:59.000Z

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

  6. Optical voltage reference

    DOE Patents [OSTI]

    Rankin, R.; Kotter, D.

    1994-04-26T23:59:59.000Z

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

  7. CAC Update: HFBR and BGRR

    E-Print Network [OSTI]

    Homes, Christopher C.

    rod blades and casks has been installed and tested #12;HFBR Update #12;HFBR Update Personnel have been on procedures for completing the work · Drills and dry-runs have been conducted to develop worker proficiency under normal and off-normal conditions #12;HFBR Update Transportation cask Certificates of Compliance

  8. Richmond Bay Campus: Project Update

    E-Print Network [OSTI]

    Lee, Jason R.

    Coordinate with City of Richmond South Shoreline Area planning #12;Richmond Bay Campus Vision A stateRichmond Bay Campus: Project Update Prepared for the Richmond City Council October 1, 2013 #12 and UCB ∑ City of Richmond Updates ∑ Summary ∑ Questions & Answers #12;LBNL Project Update #12;University

  9. Information Updates: Position/Title

    E-Print Network [OSTI]

    Sheridan, Jennifer

    Information Updates: Name: Position/Title: Business Mailing Address: Home Mailing Address: Phone of nurse involvement and patient education. She is an active nurse leader that brings thoughtful discussion be a chapter update for upcoming future events and plans for the future. Don't miss this exciting update! Beta

  10. Autoregressive Time Series Forecasting of Computational Demand

    E-Print Network [OSTI]

    Sandholm, Thomas

    2007-01-01T23:59:59.000Z

    We study the predictive power of autoregressive moving average models when forecasting demand in two shared computational networks, PlanetLab and Tycoon. Demand in these networks is very volatile, and predictive techniques to plan usage in advance can improve the performance obtained drastically. Our key finding is that a random walk predictor performs best for one-step-ahead forecasts, whereas ARIMA(1,1,0) and adaptive exponential smoothing models perform better for two and three-step-ahead forecasts. A Monte Carlo bootstrap test is proposed to evaluate the continuous prediction performance of different models with arbitrary confidence and statistical significance levels. Although the prediction results differ between the Tycoon and PlanetLab networks, we observe very similar overall statistical properties, such as volatility dynamics.

  11. Fallout forecasting: 1945-1962

    SciTech Connect (OSTI)

    Kennedy, W.R. Jr.

    1986-03-01T23:59:59.000Z

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

  12. Do Investors Forecast Fat Firms? Evidence from the Gold Mining Industry

    E-Print Network [OSTI]

    Borenstein, Severin; Farrell, Joseph

    2006-01-01T23:59:59.000Z

    Economistsí Gold Price Forecasts,Ē Australian Journal ofDo Investors Forecast Fat Firms? Evidence from the Gold

  13. Potential to Improve Forecasting Accuracy: Advances in Supply Chain Management

    E-Print Network [OSTI]

    Datta, Shoumen

    2008-07-31T23:59:59.000Z

    Forecasting is a necessity almost in any operation. However, the tools of forecasting are still primitive in view of the great strides made by research and the increasing abundance of data made possible by automatic ...

  14. Market perceptions of efficiency and news in analyst forecast errors

    E-Print Network [OSTI]

    Chevis, Gia Marie

    2004-11-15T23:59:59.000Z

    Financial analysts are considered inefficient when they do not fully incorporate relevant information into their forecasts. In this dissertation, I investigate differences in the observable efficiency of analysts' earnings forecasts between firms...

  15. The effect of multinationality on management earnings forecasts

    E-Print Network [OSTI]

    Runyan, Bruce Wayne

    2005-08-29T23:59:59.000Z

    This study examines the relationship between a firm??s degree of multinationality and its managers?? earnings forecasts. Firms with a high degree of multinationality are subject to greater uncertainty regarding earnings forecasts due...

  16. Application Protocol Reference Architecture Application Protocol Reference Architecture

    E-Print Network [OSTI]

    van Sinderen, Marten

    Application Protocol Reference Architecture 165 Chapter 7 Application Protocol Reference Architecture This chapter proposes an alternative reference architecture for application protocols. The proposed reference architecture consists of the set of possible architectures for application protocols

  17. Sample References Business Student

    E-Print Network [OSTI]

    and provide them with the job description/your resume Brand Yourself- the heading should be the same as your resume and cover letter Be Consistent- use the same fonts/sizes as your resume and cover letter Pay/advice-tools/resume-cover-letter/how-to-make-the-best-use-of-references Obtaining References http

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

    SciTech Connect (OSTI)

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

    2010-04-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2010-04-15T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01T23:59:59.000Z

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

  1. WECC and Peak Update

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

    WECC and Peak Update Transmission B O N N E V I L L E P O W E R A D M I N I S T R A T I O N Pre-decisional. For Discussion Purposes Only. WECC and Peak Background In the...

  2. RESEARCH UPDATE Ecology Division

    E-Print Network [OSTI]

    1 RESEARCH UPDATE Ecology Division Biotype has changed its name to Ecotype! Following the re-organisation of Forest Research into five science Divisions and three Support Divisions, the former Woodland Ecology Branches to form the new Ecology Division. We decided to give the divisional newsletter a new name (and

  3. 0 20 4010 Miles NOAA Harmful Algal Bloom Operational Forecast System

    E-Print Network [OSTI]

    0 20 4010 Miles NOAA Harmful Algal Bloom Operational Forecast System Texas Forecast Region Maps to Sargent BCH NOAA Harmful Algal Bloom Operational Forecast System Texas Forecast Region Maps 0 5 102 Bloom Operational Forecast System Texas Forecast Region Maps 0 5 102.5 Miles West Bay #12;Aransas Bay

  4. PSO (FU 2101) Ensemble-forecasts for wind power

    E-Print Network [OSTI]

    PSO (FU 2101) Ensemble-forecasts for wind power Wind Power Ensemble Forecasting Using Wind Speed the problems of (i) transforming the meteorological ensembles to wind power ensembles and, (ii) correcting) data. However, quite often the actual wind power production is outside the range of ensemble forecast

  5. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    requirements. The transportation energy demand forecasts make assumptions about fuel price forecastsCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY ENERGY COMMISSION Gordon Schremp, Jim Page, and Malachi Weng-Gutierrez Principal Authors Jim Page Project

  6. Using Bayesian Model Averaging to Calibrate Forecast Ensembles 1

    E-Print Network [OSTI]

    Washington at Seattle, University of

    Using Bayesian Model Averaging to Calibrate Forecast Ensembles 1 Adrian E. Raftery, Fadoua forecasting often exhibit a spread-skill relationship, but they tend to be underdispersive. This paper of PDFs centered around the individual (possibly bias-corrected) forecasts, where the weights are equal

  7. Forecast Combinations of Computational Intelligence and Linear Models for the

    E-Print Network [OSTI]

    Atiya, Amir

    Forecast Combinations of Computational Intelligence and Linear Models for the NN5 Time Series Forecasting competition Robert R. Andrawis Dept Computer Engineering Cairo University, Giza, Egypt robertrezk@eg.ibm.com November 6, 2010 Abstract In this work we introduce a forecasting model with which we participated

  8. GET your forecast at the click of a button.

    E-Print Network [OSTI]

    Greenslade, Diana

    GET your forecast at the click of a button. EXPLORE your local weather in detail. PLAN your days favourite locations; · Pan and zoom to any area in Australia; · Combine the latest weather and forecast current temperatures across Australia. MetEyeTM computer screen image displaying the weather forecast

  9. Compatibility of Stand Basal Area Predictions Based on Forecast Combination

    E-Print Network [OSTI]

    Cao, Quang V.

    Compatibility of Stand Basal Area Predictions Based on Forecast Combination Xiongqing Zhang Carr.) in Beijing, forecast combination was used to adjust predicted stand basal areas from these three types of models. The forecast combination method combines information and disperses errors from

  10. MOUNTAIN WEATHER PREDICTION: PHENOMENOLOGICAL CHALLENGES AND FORECAST METHODOLOGY

    E-Print Network [OSTI]

    Steenburgh, Jim

    MOUNTAIN WEATHER PREDICTION: PHENOMENOLOGICAL CHALLENGES AND FORECAST METHODOLOGY Michael P. Meyers of the American Meteorological Society Mountain Weather and Forecasting Monograph Draft from Friday, May 21, 2010 of weather analysis and forecasting in complex terrain with special emphasis placed on the role of humans

  11. WP1: Targeted and informative forecast system design

    E-Print Network [OSTI]

    Stevenson, Paul

    WP1: Targeted and informative forecast system design Emma Suckling, Leonard A. Smith and David Stainforth EQUIP Meeting ­ August 2011 Edinburgh #12;Targeted and informative forecast system design Develop models to support decision making (1.4) #12;Targeted and informative forecast system design KEY QUESTIONS

  12. Earnings forecast bias -a statistical analysis Franois Dossou

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Earnings forecast bias - a statistical analysis François Dossou Sandrine Lardic** Karine Michalon' earnings forecasts is an important aspect of research for different reasons: Many empirical studies employ analysts' consensus forecasts as a proxy for the market's expectations of future earnings in order

  13. Using Large Datasets to Forecast Sectoral Employment Rangan Gupta*

    E-Print Network [OSTI]

    Ahmad, Sajjad

    Using Large Datasets to Forecast Sectoral Employment Rangan Gupta* Department of Economics Bayesian and classical methods to forecast employment for eight sectors of the US economy. In addition-sample period and January 1990 to March 2009 as the out-of- sample horizon, we compare the forecast performance

  14. Power load forecasting Organization: Huizhou Electric Power, P. R. China

    E-Print Network [OSTI]

    Power load forecasting Organization: Huizhou Electric Power, P. R. China Presenter: Zhifeng Hao can be divided into load forecasting and electrical consumption predicting according to forecasting in generators macroeconomic control, power exchange plan and so on. And the prediction is from one day to seven

  15. Weighted Parametric Operational Hydrology Forecasting Thomas E. Croley II1

    E-Print Network [OSTI]

    1 Weighted Parametric Operational Hydrology Forecasting Thomas E. Croley II1 1 Great Lakes forecasts in operational hydrology builds a sample of possibilities for the future, of climate series from-parametric method can be extended into a new weighted parametric hydrological forecasting technique to allow

  16. Forecasting wave height probabilities with numerical weather prediction models

    E-Print Network [OSTI]

    Stevenson, Paul

    Forecasting wave height probabilities with numerical weather prediction models Mark S. Roulstona; Numerical weather prediction 1. Introduction Wave forecasting is now an integral part of operational weather methods for generating such forecasts from numerical model output from the European Centre for Medium

  17. AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.

    E-Print Network [OSTI]

    Povinelli, Richard J.

    AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

  18. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff members in the Demand, and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption

  19. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff in the Demand Analysis. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data

  20. Draft for Public Comment Appendix A. Demand Forecast

    E-Print Network [OSTI]

    Draft for Public Comment A-1 Appendix A. Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required component of the Council's Northwest Regional Conservation had a tradition of acknowledging the uncertainty of any forecast of electricity demand and developing

  1. Forecasting Market Demand for New Telecommunications Services: An Introduction

    E-Print Network [OSTI]

    McBurney, Peter

    Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc to redress this situation by presenting a discussion of the issues involved in demand forecasting for new or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica­ tions Services. 1 #12

  2. Using Belief Functions to Forecast Demand for Mobile Satellite Services

    E-Print Network [OSTI]

    McBurney, Peter

    Using Belief Functions to Forecast Demand for Mobile Satellite Services Peter McBurney and Simon.j.mcburney,s.d.parsonsg@elec.qmw.ac.uk Abstract. This paper outlines an application of belief functions to forecasting the demand for a new service in a new category, based on new technology. Forecasting demand for a new product or service

  3. A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION

    E-Print Network [OSTI]

    Boyer, Edmond

    1 A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION in the realm of solar radiation forecasting. In this work, two forecasting models: Autoregressive Moving. The very first results show an improvement brought by this approach. 1. INTRODUCTION Solar radiation

  4. FORECASTING SOLAR RADIATION PRELIMINARY EVALUATION OF AN APPROACH

    E-Print Network [OSTI]

    Perez, Richard R.

    FORECASTING SOLAR RADIATION -- PRELIMINARY EVALUATION OF AN APPROACH BASED UPON THE NATIONAL, and undertake a preliminary evaluation of, a simple solar radiation forecast model using sky cover predictions forecasts is 0.05o in latitude and longitude. Solar Radiation model: The model presented in this paper

  5. Forecasting the Market Penetration of Energy Conservation Technologies: The Decision Criteria for Choosing a Forecasting Model

    E-Print Network [OSTI]

    Lang, K.

    1982-01-01T23:59:59.000Z

    capital requirements and research and development programs in the alum inum industry. : CONCLUSIONS Forecasting the use of conservation techndlo gies with a market penetration model provides la more accountable method of projecting aggrega...

  6. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    NONE

    1996-08-01T23:59:59.000Z

    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.

  7. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27T23:59:59.000Z

    This paper presents a nonparametric diffusion modeling approach for forecasting partially observed noisy turbulent modes. The proposed forecast model uses a basis of smooth functions (constructed with the diffusion maps algorithm) to represent probability densities, so that the forecast model becomes a linear map in this basis. We estimate this linear map by exploiting a previously established rigorous connection between the discrete time shift map and the semi-group solution associated to the backward Kolmogorov equation. In order to smooth the noisy data, we apply diffusion maps to a delay embedding of the noisy data, which also helps to account for the interactions between the observed and unobserved modes. We show that this delay embedding biases the geometry of the data in a way which extracts the most predictable component of the dynamics. The resulting model approximates the semigroup solutions of the generator of the underlying dynamics in the limit of large data and in the observation noise limit. We will show numerical examples on a wide-range of well-studied turbulent modes, including the Fourier modes of the energy conserving Truncated Burgers-Hopf (TBH) model, the Lorenz-96 model in weakly chaotic to fully turbulent regimes, and the barotropic modes of a quasi-geostrophic model with baroclinic instabilities. In these examples, forecasting skills of the nonparametric diffusion model are compared to a wide-range of stochastic parametric modeling approaches, which account for the nonlinear interactions between the observed and unobserved modes with white and colored noises.

  8. Do quantitative decadal forecasts from GCMs provide

    E-Print Network [OSTI]

    Stevenson, Paul

    ' · Empirical models quantify our ability to predict without knowing the laws of physics · Climatology skill' model? 2. Dynamic climatology (DC) is a more appropriate benchmark for near- term (initialised) climate forecasts · A conditional climatology, initialised at launch and built from the historical archive

  9. > BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS MARINE SERVICE

    E-Print Network [OSTI]

    Greenslade, Diana

    > BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS MARINE SERVICE IMPROVEMENTS FOR QUEENSLAND across Australia. FURTHER INFORMATION: www.bom.gov.au/NexGenFWS © Commonwealth of Australia, 2013 From © Copyright Commonwealth of Australia 2013, Bureau of Meteorology Queensland Australia Coastal Waters Zones

  10. Modeling of Uncertainty in Wind Energy Forecast

    E-Print Network [OSTI]

    regression and splines are combined to model the prediction error from Tun√ł Knob wind power plant. This data of the thesis is quantile regression and splines in the context of wind power modeling. Lyngby, February 2006Modeling of Uncertainty in Wind Energy Forecast Jan Kloppenborg M√łller Kongens Lyngby 2006 IMM-2006

  11. Forecasting sudden changes in environmental pollution patterns

    E-Print Network [OSTI]

    Olascoaga, Maria Josefina

    Forecasting sudden changes in environmental pollution patterns María J. Olascoagaa,1 and George of Mexico in 2010. We present a methodology to predict major short-term changes in en- vironmental River's mouth in the Gulf of Mexico. The resulting fire could not be extinguished and the drilling rig

  12. Amending Numerical Weather Prediction forecasts using GPS

    E-Print Network [OSTI]

    Stoffelen, Ad

    to validate the amounts of humidity in Numerical Weather Prediction (NWP) model forecasts. This paper presents. Satellite images and Numerical Weather Prediction (NWP) models are used together with the synoptic surface. In this paper, a case is presented for which the operational Numerical Weather Prediction Model (NWP) HIRLAM

  13. Prediction versus Projection: How weather forecasting and

    E-Print Network [OSTI]

    Howat, Ian M.

    Prediction versus Projection: How weather forecasting and climate models differ. Aaron B. Wilson Context: Global http://data.giss.nasa.gov/ #12;Numerical Weather Prediction Collect Observations alters associated weather patterns. Models used to predict weather depend on the current observed state

  14. FORECAST OF VACANCIES Until end of 2016

    E-Print Network [OSTI]

    #12;FORECAST OF VACANCIES Until end of 2016 (Issue No. 22) #12;Page 2 OVERVIEW OF BASIC REQUIREMENTS FOR PROFESSIONAL VACANCIES IN THE IAEA Education, Experience and Skills: Professional staff the team of professionals. Second half 2015 VACANCY GRADE REQUIREMENTS / ROLE EXPECTED DATE OF VACANCY

  15. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Sripada, Yaji

    ) models is summarised as weather forecast texts. In the domain of gas turbines, sensor data from an operational gas turbine is summarised for the maintenance engineers. More details on SUMTIME have been to develop a generic model for summarisation of time series data. Initially, we have applied standard

  16. Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price forecast of the Fifth Northwest Power

    E-Print Network [OSTI]

    Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price as traded on the wholesale, short-term (spot) market at the Mid-Columbia trading hub. This price represents noted. BASE CASE FORECAST The base case wholesale electricity price forecast uses the Council's medium

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18T23:59:59.000Z

    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.

  18. Value of Information References

    SciTech Connect (OSTI)

    Morency, Christina

    2014-12-12T23:59:59.000Z

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

  19. Value of Information References

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

    Morency, Christina

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

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

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01T23:59:59.000Z

    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.

  1. Technical reference book for the Energy Economic Data Base (EEDB) Program

    SciTech Connect (OSTI)

    Allen, R.E.; Benedict, R.G.; Hodson, J.S.

    1984-09-01T23:59:59.000Z

    The Energy Economic Data Base (EEDB) Program is sponsored by the US Department of Energy (DOE) for the purpose of developing current technical and cost information for nuclear and comparison electric power generating stations. The EEDB contains a variety of nuclear and coal-fired power plant technical data models. Each of these data models is a complete and detailed conceptual design for a single unit, commercial, steam electric, power generating station located on a standard hypothetical Middletown site. A major effort for the Sixth Update (1983) has been the updating of the system design descriptions and selected engineering drawings for the technical data models. This update took the form of revising and expanding the system design descriptions and engineering drawings contained in the Base Data Studies, to include the technical information developed and recorded in the first five EEDB updates. The results of the update effort are contained in this EEDB Program Technical Reference Book.

  2. Membrane reference electrode

    DOE Patents [OSTI]

    Redey, L.; Bloom, I.D.

    1988-01-21T23:59:59.000Z

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

  3. Precision displacement reference system

    DOE Patents [OSTI]

    Bieg, Lothar F. (Albuquerque, NM); Dubois, Robert R. (Albuquerque, NM); Strother, Jerry D. (Edgewood, NM)

    2000-02-22T23:59:59.000Z

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

  4. DOE interpretations Guide to OSH standards. Update to the Guide

    SciTech Connect (OSTI)

    Not Available

    1994-03-31T23:59:59.000Z

    Reflecting Secretary O`Leary`s focus on occupational safety and health, the Office of Occupational Safety is pleased to provide you with the latest update to the DOE Interpretations Guide to OSH Standards. This Guide was developed in cooperation with the Occupational Safety and Health Administration, which continued its support during this last revision by facilitating access to the interpretations found on the OSHA Computerized Information System (OCIS). This March 31, 1994 update contains 123 formal interpretation letters written by OSHA. As a result of the unique requests received by the 1-800 Response Line, this update also contains 38 interpretations developed by DOE. This new occupational safety and health information adds still more important guidance to the four volume reference set that you presently have in your possession.

  5. DOE interpretations Guide to OSH standards. Update to the Guide

    SciTech Connect (OSTI)

    Not Available

    1994-03-31T23:59:59.000Z

    Reflecting Secretary O`Leary`s focus on occupational safety and health, the Office of Occupational Safety is pleased to provide you with the latest update to the DOE Interpretations Guide to OSH Standards. This Guide was developed in cooperation with the Occupational Safety and Health Administration, which continued it`s support during this last revision by facilitating access to the interpretations found on the OSHA Computerized Information System (OCIS). This March 31, 1994 update contains 123 formal in letter written by OSHA. As a result of the unique requests received by the 1-800 Response Line, this update also contains 38 interpretations developed by DOE. This new occupational safety and health information adds still more important guidance to the four volume reference set that you presently have in your possession.

  6. DOE interpretations Guide to OSH standards. Update to the Guide

    SciTech Connect (OSTI)

    Not Available

    1994-03-31T23:59:59.000Z

    Reflecting Secretary O`Leary`s focus on occupational safety and health, the Office of Occupational Safety is pleased to provide you with the latest update to the DOE Interpretations Guide to OSH Standards. This Guide was developed in cooperation with the Occupational Safety and Health Administration, which continued its support during this last revision by facilitating access to the interpretations found on the OSHA Computerized Information System (OCIS). This March 31, 1994 update contains 123 formal interpretation letters written OSHA. As a result of the unique requests received by the 1-800 Response Line, this update also contains 38 interpretations developed by DOE. This new occupational safety and health information adds still more important guidance to the four volume reference set that you presently have in your possession.

  7. Next Update: November 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in Nonproducing ReservoirsYear-Month WeekReserves (Billion Cubic Next Update:

  8. Test application of a semi-objective approach to wind forecasting for wind energy applications

    SciTech Connect (OSTI)

    Wegley, H.L.; Formica, W.J.

    1983-07-01T23:59:59.000Z

    The test application of the semi-objective (S-O) wind forecasting technique at three locations is described. The forecasting sites are described as well as site-specific forecasting procedures. Verification of the S-O wind forecasts is presented, and the observed verification results are interpreted. Comparisons are made between S-O wind forecasting accuracy and that of two previous forecasting efforts that used subjective wind forecasts and model output statistics. (LEW)

  9. Health & Safety Plan Last Updated

    E-Print Network [OSTI]

    Anderson, Richard

    Health & Safety Plan Last Updated March 2008 1 #12;A. SCOPE AND RESPONSIBILITY....................................................................................................................................... 3 2. Safety and Health Policy...................................................................................................................... 3 4. Safety Coordinator

  10. Agricultural and Resource Economics Update

    E-Print Network [OSTI]

    2012-01-01T23:59:59.000Z

    Analysis for Evaluating Biofuels. Ē ARE Update 11(3) (2008):the RFS conventional biofuels mandate is severely harmingThe first is growth in biofuels demand. Notably, corn

  11. Agricultural and Resource Economics Update

    E-Print Network [OSTI]

    Lee, Hyunok; Sumner, Daniel A.; Martin, Philip; Hochman, Gal; Rajagopal, Deepak; Zilberman, David

    2011-01-01T23:59:59.000Z

    Environmental Impact of Biofuels. Ē ARE Update 15(2):9-11.and the Environmental Impact of Biofuels Gal Hochman, Deepakand the Environmental Impact of Biofuels Gal Hochman, Deepak

  12. Progress Update: TRU Waste Shipping

    SciTech Connect (OSTI)

    Cody, Tom

    2010-01-01T23:59:59.000Z

    A progress update at the Savannah River Site. A continued effort on shipping TRU waste to WIPP in Carlsbad, New Mexico.

  13. Progress Update: TRU Waste Shipping

    ScienceCinema (OSTI)

    Cody, Tom

    2012-06-14T23:59:59.000Z

    A progress update at the Savannah River Site. A continued effort on shipping TRU waste to WIPP in Carlsbad, New Mexico.

  14. Forecasting hotspots using predictive visual analytics approach

    SciTech Connect (OSTI)

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

    2014-12-30T23:59:59.000Z

    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.

  15. Solar Wind Forecasting with Coronal Holes

    E-Print Network [OSTI]

    S. Robbins; C. J. Henney; J. W. Harvey

    2007-01-09T23:59:59.000Z

    An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

  16. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J. (Decision and Information Sciences); (INESC Porto)

    2011-02-23T23:59:59.000Z

    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.

  17. Eagle Project Update Eagle P3 Project Update

    E-Print Network [OSTI]

    Bustamante, Fabi√°n E.

    ) offers 11-minute travel time to Westminster #12;5 Eagle P3 Project Scope · Overall capital cost $2 for cost effective index · Allows RTD to spread the cost of the project over a longer time periodEagle Project Update Eagle P3 Project Update Rick Clarke Assistant General Manager, Capital

  18. 1 POSTGRADUATE SCHOLARSHIPS UPDATE -July -August 2014 Postgraduate Scholarships Update

    E-Print Network [OSTI]

    Frean, Marcus

    - August 2014 ADDRESSENQUIRIESAND YOURCOMPLETEDFORMTO: SCHOLARSHIPSMANAGER ScholarshipsOffice Victoria1 POSTGRADUATE SCHOLARSHIPS UPDATE - July - August 2014 Postgraduate Scholarships Update JulyUniversityofWellington POBox600 Wellington6140 NewZealand PHONE +64-4-4635113 EMAIL scholarships-office@vuw.ac.nz WEBSITE www.victoria

  19. WECC Variable Generation Planning Reference Book

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Du, Pengwei; Etingov, Pavel V.; Ma, Jian; Vyakaranam, Bharat

    2013-05-14T23:59:59.000Z

    This planning reference book is a document reflecting a Western Electricity Coordination Council (WECC) effort to put together multiple sources of information and provide a clear, systemic, comprehensive outline of the problems, both existing and anticipated; their impacts on the system; currently used and proposed solutions by the industry and research community; planning practices; new technologies, equipment, and standards; and expected future trends. This living (periodically updated) document could help WECC and other practicing engineers, especially the younger generation of engineers joining the workforce, to get familiar with a large variety of information related to the integration of variable resources into the WECC system, bypassing in part the need for time-consuming information gathering and learning processes from more experienced engineers or from the literature.

  20. Nonresident Alien Reference Guide

    E-Print Network [OSTI]

    Adali, Tulay

    - 1 - Nonresident Alien Reference Guide #12;- 2 - Definition Nonresident Alien (NRA) is defined as any employee who is NOT a United States Citizen or a Permanent Resident (Resident Alien or Green Card status. These are NOT Immigration categories. United States Citizen Permanent Resident Alien Resident

  1. (Nonresident Alien) Reference Guide

    E-Print Network [OSTI]

    Adali, Tulay

    - 1 - NRA (Nonresident Alien) Reference Guide #12;- 2 - UMBC'S OFFICES ASSISTING THE NONRESIDENT ALIEN (NRA) Office of International Education Administration Building 2nd floor Arlene Wergin Ext: 5 - Definition Nonresident Alien (NRA) is defined as any employee who is NOT a United States Citizen

  2. MSL ENTERANCE REFERENCE AREA

    E-Print Network [OSTI]

    Aalberts, Daniel P.

    MSL ENTERANCE LOBBY ELEV STAIRS SSL-019 REFERENCE AREA SSL-021 GROUP STUDY SSL-018 STUDY ROOM SSL-029 SSL-020 COPY ROOM SSL-022 GROUP STUDY SSL-026 STACKS SSL-023 GROUP STUDY SSL-024 GROUP STUDY SSL TBL-014 TBL-014A STAIRS SSL-007 GIS/ WORKROOM SSL-011 SSL-008 SSL-009 SSL-010 SSL-014 SSL-017 STAIRS

  3. Building America Residential Energy Efficiency Technical Update...

    Energy Savers [EERE]

    Residential Energy Efficiency Technical Update Meeting: August 2011 Building America Residential Energy Efficiency Technical Update Meeting: August 2011 On this page, you may link...

  4. Energy Storage Systems 2010 Update Conference Presentations ...

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

    by SNL's Ross Guttromson, are below. ESS 2010 Update Conference - NYSERDA-DOE Joint Energy Storage Initiative - Georgianne Huff, SNL.pdf ESS 2010 Update Conference - Testing...

  5. Energy Storage Systems 2010 Update Conference Presentations ...

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

    and Peak Shifting - Steve Willard, PNM.pdf ESS 2010 Update Conference - Tehachapi Wind Energy Storage - Loic Gaillac, SCE.pdf ESS 2010 Update Conference - Flow Battery Solution...

  6. Residential Energy Efficiency Technical Update Meeting: August...

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

    Technical Update Meeting: August 2011 Residential Energy Efficiency Technical Update Meeting: August 2011 On this page, you may link to the summary report and presentations for the...

  7. Hopper Updates and Status

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-SeriesFlickr FlickrGuidedCH2MLLC HistoryVeterans | Updates and Status Current

  8. Carver Updates and Status

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone6Energy,MUSEUM DISPLAYCareers TheEmail Announcements Updates and

  9. Next Update: November 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in Nonproducing ReservoirsYear-Month WeekReserves (Billion Cubic Next Update:Next

  10. Next Update: November 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia,(Million Barrels) Crude Oil Reserves in Nonproducing ReservoirsYear-Month WeekReserves (Billion Cubic Next Update:Next

  11. Updates and Status

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered energy consumption by sectorlongUpdates by Diane Johnson Email Alerts Subscribe to

  12. Euclid Updates and Status

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series toESnet4:Epitaxial Thin Film XRD EpitaxialProgrammingStatus Updates and

  13. Genepool Updates and Status

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-SeriesFlickr Flickr Editor'sshort version) ThelongEmailStatus Updates and Status

  14. Draft Fourth Northwest Conservation and Electric Power Plan, Appendix D ECONOMIC AND DEMAND FORECASTS

    E-Print Network [OSTI]

    AND DEMAND FORECASTS INTRODUCTION AND SUMMARY Role of the Demand Forecast A demand forecast of at least 20 years is one of the explicit requirements of the Northwest Power Act. A demand forecast is, of course analysis. Because the future is inherently uncertain, the Council forecasts a range of future demand levels

  15. 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.

    2013-10-01T23:59:59.000Z

    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.

  16. PBL FY 2002 Third Quarter Review Forecast of Generation Accumulated Net Revenues, Updated August 30, 2002

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 - September 2006 The 2002OpticsPeriodical: Volume 5, Issue 32012)J

  17. PBL FY 2003 Third Quarter Review Forecast of Generation Accumulated Net Revenues, Updated August 18, 2003

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 - September 2006 The 2002OpticsPeriodical: Volume 5, Issue 32012)JBPA-PBL May

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2005-08-17T23:59:59.000Z

    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.

  19. Managing Wind Power Forecast Uncertainty in Electric Grids.

    E-Print Network [OSTI]

    Mauch, Brandon Keith

    2012-01-01T23:59:59.000Z

    ??Electricity generated from wind power is both variable and uncertain. Wind forecasts provide valuable information for wind farm management, but they are not perfect. ChapterÖ (more)

  20. Western Area Power Administration Starting Forecast Month: Sierra...

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

    CVP Generation Project Use First Preference Purchases and Exchanges Base Resource February 2014 Twelve-Month Forecast of CVP Generation and Base Resource February 2014 January...

  1. Western Area Power Administration Starting Forecast Month: Sierra...

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

    Use First Preference Purchases and Exchanges Base Resource April 2014 Twelve-Month Forecast of CVP Generation and Base Resource April 2014 March 2015 Exceedence Level: 90% (Dry)...

  2. Western Area Power Administration Starting Forecast Month: Sierra...

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

    Preference Month CVP Generation Project Use First Preference Purchases and Exchanges Base Resource May 2014 Twelve-Month Forecast of CVP Generation and Base Resource May 2014 April...

  3. Western Area Power Administration Starting Forecast Month: Sierra...

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

    based on Green Book ("Above Normal") values. Base Resource March 2014 Twelve-Month Forecast of CVP Generation and Base Resource March 2014 February 2015 Exceedence Level: 90%...

  4. analytical energy forecasting: Topics by E-print Network

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

    COMMISSION Tom Gorin Lynn Marshall Principal Author Tom Gorin Project 11 Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Computer Technologies and...

  5. 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.

    2012-09-01T23:59:59.000Z

    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.

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

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

    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...

  7. Forecasting the underlying potential governing climatic time series

    E-Print Network [OSTI]

    Livina, V N; Mudelsee, M; Lenton, T M

    2012-01-01T23:59:59.000Z

    We introduce a technique of time series analysis, potential forecasting, which is based on dynamical propagation of the probability density of time series. We employ polynomial coefficients of the orthogonal approximation of the empirical probability distribution and extrapolate them in order to forecast the future probability distribution of data. The method is tested on artificial data, used for hindcasting observed climate data, and then applied to forecast Arctic sea-ice time series. The proposed methodology completes a framework for `potential analysis' of climatic tipping points which altogether serves anticipating, detecting and forecasting climate transitions and bifurcations using several independent techniques of time series analysis.

  8. Econometric model and futures markets commodity price forecasting

    E-Print Network [OSTI]

    Just, Richard E.; Rausser, Gordon C.

    1979-01-01T23:59:59.000Z

    Versus CCll1rnercial Econometric M:ldels." Uni- versity ofWorking Paper No. 72 ECONOMETRIC ! 'econometric forecasts with the futures

  9. Using Customers' Reported Forecasts to Predict Future Sales

    E-Print Network [OSTI]

    Gordon, Geoffrey J.

    Using Customers' Reported Forecasts to Predict Future Sales Nihat Altintas , Alan Montgomery , Michael Trick Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA 15213. nihat

  10. OSH technical reference manual

    SciTech Connect (OSTI)

    Not Available

    1993-11-01T23:59:59.000Z

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

  11. STEP Intern Reference Check Sheet

    Broader source: Energy.gov [DOE]

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

  12. State-of-the art of freight forecast modeling: lessons learned and the road ahead

    E-Print Network [OSTI]

    Chow, Joseph Y.; Yang, Choon Heon; Regan, Amelia C.

    2010-01-01T23:59:59.000Z

    of-the art of freight forecast modeling: lessons learned andof goods as well as to forecast the expected future truckused for the short-term forecasts of freight volumes on

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01T23:59:59.000Z

    revisions to the EIAís natural gas price forecasts in AEOsolely on the AEO 2005 natural gas price forecasts willComparison of AEO 2005 Natural Gas Price Forecast to NYMEX

  14. Electricity Demand Forecasting using Gaussian Processes Manuel Blum and Martin Riedmiller

    E-Print Network [OSTI]

    Teschner, Matthias

    Electricity Demand Forecasting using Gaussian Processes Manuel Blum and Martin Riedmiller Abstract We present an electricity demand forecasting algorithm based on Gaussian processes. By introducing. Introduction Electricity demand forecasting is an important aspect of the control and scheduling of power

  15. Reducing the demand forecast error due to the bullwhip effect in the computer processor industry

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01T23:59:59.000Z

    Intel's current demand-forecasting processes rely on customers' demand forecasts. Customers do not revise demand forecasts as demand decreases until the last minute. Intel's current demand models provide little guidance ...

  16. Evaluation of forecasting techniques for short-term demand of air transportation

    E-Print Network [OSTI]

    Wickham, Richard Robert

    1995-01-01T23:59:59.000Z

    Forecasting is arguably the most critical component of airline management. Essentially, airlines forecast demand to plan the supply of services to respond to that demand. Forecasts of short-term demand facilitate tactical ...

  17. Wind Forecasting Improvement Project | Department of Energy

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomen Owned SmallOf TheViolations | Department of EnergyisWilliamForecasting

  18. Renewable Forecast Min-Max2020.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared at 278, 298,NIST31 ORV 15051SoilWind Energy Wind RenewableForecast

  19. Forecast calls for better models | EMSL

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-SeriesFlickr Flickr Editor's note: Since theNational SupplementalFor theForecast

  20. NREL: Resource Assessment and Forecasting - Facilities

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the Contributions andData and Resources NREL resource assessment and forecasting

  1. NREL: Resource Assessment and Forecasting - Research Staff

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the Contributions andData and Resources NREL resource assessment and forecastingResearch

  2. APPROVED MINORS Updated on April 4, 2013

    E-Print Network [OSTI]

    New Hampshire, University of

    APPROVED MINORS Updated on April 4, 2013 Note: Please go to Department webpages for updates. Page 1;APPROVED MINORS Updated on April 4, 2013 Note: Please go to Department webpages for updates. Page 2 COLLEGE Studies Cinema Studies Classics Communication Dance Education English European Cultural Studies Forensics

  3. IEAB Invasive Mussels Update September 2013 Invasive Mussels Update

    E-Print Network [OSTI]

    ....................................................... 16 8. Update on Mussel Control Agents Area MFWP Montana Fish Wildlife and Parks NASQAN National Stream Quality Accounting Network NGO Non, respectively, during 2012. A total of 109 mussel-infested boats were found during

  4. Appendix A: Reference case

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) " ,"ClickPipelinesProved Reserves (Billion CubicCubic Feet)Year Jan FebForeign Distribution6 Reference

  5. Appendix A: Reference case

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) " ,"ClickPipelinesProved Reserves (Billion CubicCubic Feet)Year Jan FebForeign Distribution6 Reference4

  6. Appendix A: Reference case

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) " ,"ClickPipelinesProved Reserves (Billion CubicCubic Feet)Year Jan FebForeign Distribution6 Reference44

  7. Appendix A: Reference case

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) " ,"ClickPipelinesProved Reserves (Billion CubicCubic Feet)Year Jan FebForeign Distribution66 Reference

  8. Appendix A: Reference case

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) " ,"ClickPipelinesProved Reserves (Billion CubicCubic Feet)Year Jan FebForeign Distribution66 Reference8

  9. Clean Water Act (excluding Section 404). Environmental guidance program reference book: Revision 6

    SciTech Connect (OSTI)

    Not Available

    1993-01-15T23:59:59.000Z

    This Reference Book contains a current copy of the Clean Water Act (excluding Section 404) and those regulations that implement the statutes and appear to be most relevant to US Department of Energy (DOE) activities. The document is provided to DOE and contractor staff for informational purposes only and should not be interpreted as legal guidance. Updates that include important new requirements will be provided periodically. Questions concerning this Reference Book may be directed to Mark Petts, EH-231 (202/586-2609).

  10. Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01T23:59:59.000Z

    114 Solar Irradiance And Power Output Variabilityand L. Bangyin. Online 24-h solar power forecasting based onNielsen. Online short-term solar power forecasting. Solar

  11. Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast Role of the Economic Forecast ................................................................................................. 2 Economic Drivers of Residential Demand

  12. Improving baseline forecasts in a 500-industry dynamic CGE model of the USA.

    E-Print Network [OSTI]

    Mavromatis, Peter George

    2013-01-01T23:59:59.000Z

    ??MONASH-style CGE models have been used to generate baseline forecasts illustrating how an economy is likely to evolve through time. One application of such forecastsÖ (more)

  13. Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA

    SciTech Connect (OSTI)

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

    2014-10-27T23:59:59.000Z

    In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of forecasts. We use automatically coupled wavelet transform and autoregressive integrated moving-average (ARIMA) forecasting to reflect multi-scale variability of forecast errors. The proposed analysis reveals slow-changing ďquasi-deterministicĒ components of forecast errors. This helps improve forecasts produced by other means, e.g., using weather-based models, and reduce forecast errors prediction intervals.

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

    SciTech Connect (OSTI)

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

    2010-02-21T23:59:59.000Z

    The operators of electrical grids, sometimes referred to as Balancing Authorities (BA), typically make critical decisions on how to most reliably and economically balance electrical load and generation in time frames ranging from a few minutes to six hours ahead. At higher levels of wind power generation, there is an increasing need to improve the accuracy of 0- to 6-hour ahead wind power forecasts. Forecasts on this time scale have typically been strongly dependent on short-term trends indicated by the time series of power production and meteorological data from a wind farm. Additional input information is often available from the output of Numerical Weather Prediction (NWP) models and occasionally from off-site meteorological towers in the region surrounding the wind generation facility. A widely proposed approach to improve short-term forecasts is the deployment of off-site meteorological towers at locations upstream from the wind generation facility in order to sense approaching wind perturbations. While conceptually appealing, it turns out that, in practice, it is often very difficult to derive significant benefit in forecast performance from this approach. The difficulty is rooted in the fact that the type, scale, and amplitude of the processes controlling wind variability at a site change from day to day if not from hour to hour. Thus, a location that provides some useful forecast information for one time may not be a useful predictor a few hours later. Indeed, some processes that cause significant changes in wind power production operate predominantly in the vertical direction and thus cannot be monitored by employing a network of sensors at off-site locations. Hence, it is very challenging to determine the type of sensors and deployment locations to get the most benefit for a specific short-term forecast application. Two tools recently developed in the meteorological research community have the potential to help determine the locations and parameters to measure in order to get the maximum positive impact on forecast performance for a particular site and short-term look-ahead period. Both tools rely on the use of NWP models to assess the sensitivity of a forecast for a particular location to measurements made at a prior time (i.e. the look-ahead period) at points surrounding the target location. The fundamental hypothesis is that points and variables with high sensitivity are good candidates for measurements since information at those points are likely to have the most impact on the forecast for the desired parameter, location and look-ahead period. One approach is called the adjoint method (Errico and Vukicevic, 1992; Errico, 1997) and the other newer approach is known as Ensemble Sensitivity Analysis (ESA; Ancell and Hakim 2007; Torn and Hakim 2008). Both approaches have been tested on large-scale atmospheric prediction problems (e.g. forecasting pressure or precipitation over a relatively large region 24 hours ahead) but neither has been applied to mesoscale space-time scales of winds or any other variables near the surface of the earth. A number of factors suggest that ESA is better suited for short-term wind forecasting applications. One of the most significant advantages of this approach is that it is not necessary to linearize the mathematical representation of the processes in the underlying atmospheric model as required by the adjoint approach. Such a linearization may be especially problematic for the application of short-term forecasting of boundary layer winds in complex terrain since non-linear shifts in the structure of boundary layer due to atmospheric stability changes are a critical part of the wind power production forecast problem. The specific objective of work described in this paper is to test the ESA as a tool to identify measurement locations and variables that have the greatest positive impact on the accuracy of wind forecasts in the 0- to 6-hour look-ahead periods for the wind generation area of California's Tehachapi Pass during the warm (high generation) season. The paper is organized

  15. Distribution Based Data Filtering for Financial Time Series Forecasting

    E-Print Network [OSTI]

    Bailey, James

    recent past. In this paper, we address the challenge of forecasting the behavior of time series using@unimelb.edu.au Abstract. Changes in the distribution of financial time series, particularly stock market prices, can of stock prices, which aims to forecast the future values of the price of a stock, in order to obtain

  16. On the reliability of seasonal forecasts Antje Weisheimer

    E-Print Network [OSTI]

    Stevenson, Paul

    On the reliability of seasonal forecasts Antje Weisheimer Weisheimer to achieving a "5"? à Use reliability of non-climatological forecastsDon: · if (X) C(X) à climatological (reliable) informaDon · if (X) C(X) à

  17. SATELLITE BASED SHORT-TERM FORECASTING OF SOLAR IRRADANCE

    E-Print Network [OSTI]

    Heinemann, Detlev

    SATELLITE BASED SHORT-TERM FORECASTING OF SOLAR IRRADANCE - COMPARISON OF METHODS AND ERROR Forecasting of solar irradiance will become a major issue in the future integration of solar energy resources method was used to derive motion vector fields from two consecutive images. The future image

  18. Predicting Solar Generation from Weather Forecasts Using Machine Learning

    E-Print Network [OSTI]

    Shenoy, Prashant

    of smart grid initiatives is significantly increasing the fraction of grid energy contributed by renewables existing forecast-based models. I. INTRODUCTION A key goal of smart grid efforts is to substantially-based prediction models built using seven distinct weather forecast metrics are 27% more accurate for our site than

  19. Forecasting Uncertainty Related to Ramps of Wind Power Production

    E-Print Network [OSTI]

    Boyer, Edmond

    - namic reserve quantification [8], for the optimal oper- ation of combined wind-hydro power plants [5, 1Forecasting Uncertainty Related to Ramps of Wind Power Production Arthur Bossavy, Robin Girard - The continuous improvement of the accuracy of wind power forecasts is motivated by the increasing wind power

  20. FORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS

    E-Print Network [OSTI]

    Keller, Arturo A.

    FORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS by Bruce Bishop Professor of Civil resources resulting in water stress. Effective water management ­ a solution Supply side management Demand side management #12;Developing a regression equation based on cluster analysis for forecasting water

  1. Revised 1997 Retail Electricity Price Forecast Principal Author: Ben Arikawa

    E-Print Network [OSTI]

    Revised 1997 Retail Electricity Price Forecast March 1998 Principal Author: Ben Arikawa Electricity 1997 FORE08.DOC Page 1 CALIFORNIA ENERGY COMMISSION ELECTRICITY ANALYSIS OFFICE REVISED 1997 RETAIL ELECTRICITY PRICE FORECAST Introduction The Electricity Analysis Office of the California Energy Commission

  2. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center

    E-Print Network [OSTI]

    Washington at Seattle, University of

    Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological forecast regimes at the wind energy site and fits a conditional predictive model for each regime

  3. Impact of PV forecasts uncertainty in batteries management in microgrids

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    -- Photovoltaic systems, Batteries, Forecasting I. INTRODUCTION This paper presents first results of a study Energies and Energy Systems Sophia Antipolis, France andrea.michiorri@mines-paristech.fr Abstract production forecast algorithm is used in combination with a battery schedule optimisation algorithm. The size

  4. Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    distribution; Numerical weather prediction; Skewed distribution; Truncated data; Wind energy. 1. INTRODUCTION- native. Purely statistical methods have been applied to short-range forecasts for wind speed only a fewProbabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging J. Mc

  5. Introducing the Canadian Crop Yield Forecaster Aston Chipanshi1

    E-Print Network [OSTI]

    Miami, University of

    for crop yield forecasting and risk analysis. Using the Census Agriculture Region (CAR) as the unit Climate Decision Support and Adaptation, Agriculture and Agri-Food Canada, 1011, Innovation Blvd, Saskatoon, SK S7V 1B7, Canada The Canadian Crop Yield Forecaster (CCYF) is a statistical modelling tool

  6. A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size

    E-Print Network [OSTI]

    Hansens, Jim

    A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size Andrew. R.Lawrence@ecmwf.int #12;Abstract An ensemble-based data assimilation approach is used to transform old en- semble. The impact of the transformations are propagated for- ward in time over the ensemble's forecast period

  7. Forecasting Building Occupancy Using Sensor Network James Howard

    E-Print Network [OSTI]

    Hoff, William A.

    of the forecasting algorithm for the different conditions. 1. INTRODUCTION According to the U.S. Department of Energy could take advantage of times when electricity cost is lower, to chill a cold water storage tankForecasting Building Occupancy Using Sensor Network Data James Howard Colorado School of Mines

  8. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2012-07-01T23:59:59.000Z

    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.

  10. www.northernsportcentre.ca12 *Information is subject to change, please refer to the website

    E-Print Network [OSTI]

    Northern British Columbia, University of

    www.northernsportcentre.ca12 *Information is subject to change, please refer to the website for updated and current information www.northernsportcentre.ca JOIN THE NORTHERN SPORT CENTRE FOR OUR ANNUAL MULTISPORT ENDURANCE EVENT! THE STORM IS COMING! www.northernsportcentre.ca Register in person

  11. Progress Update: M Area Closure

    ScienceCinema (OSTI)

    Cody, Tom

    2012-06-14T23:59:59.000Z

    A progress update of the Recovery Act at work at the Savannah River Site. The celebration of the first area cleanup completion with the help of the Recovery Act.

  12. Gearbox Reliability Collaborative Update (Presentation)

    SciTech Connect (OSTI)

    Sheng, S.

    2013-10-01T23:59:59.000Z

    This presentation was given at the Sandia Reliability Workshop in August 2013 and provides information on current statistics, a status update, next steps, and other reliability research and development activities related to the Gearbox Reliability Collaborative.

  13. Agricultural and Resource Economics Update

    E-Print Network [OSTI]

    2012-01-01T23:59:59.000Z

    corn prices, but crude oil prices are also relatively highSmith. ďWhat is the Price of Oil? Ē ARE Update 11(5) (2008):ates with the prices of corn and crude oil. Until 2011 there

  14. Sign Up For Email Updates

    Broader source: Energy.gov [DOE]

    Be the first to know of the latest developments from the Energy.gov team -- from videos to infographics to live Q&Aís -- by signing up for email updates.

  15. Updated 030613 University of California

    E-Print Network [OSTI]

    Walker, Matthew P.

    Updated 030613 University of California Berkeley UC Berkeley Summer Sessions- ASTRON W12/EPS W12: The Solar System with MasteringAstronomy, 6/E. Jeffrey O. Bennett, et al. ISBN-10: 0321642678 ISBN-13

  16. Ksplice: Automatic Rebootless Kernel Updates

    E-Print Network [OSTI]

    Kaashoek, M. Frans

    2009-01-01T23:59:59.000Z

    Ksplice allows system administrators to apply patches to their operating system kernels without rebooting. Unlike previous hot update systems, Ksplice operates at the object code layer, which allows Ksplice to transform ...

  17. CH 6 REFERENCES.DOC 6-1 6 References

    E-Print Network [OSTI]

    REFERENCES.DOC Allan, S., A. R. Buckley, and J. E. Meacham. 2001. Atlas of Oregon. Second Edition. William J

  18. Microsoft Word - updated Recipient Webinar Transcript GL | Department...

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

    updated Recipient Webinar Transcript GL Microsoft Word - updated Recipient Webinar Transcript GL Microsoft Word - updated Recipient Webinar Transcript GL More Documents &...

  19. Verification of hourly forecasts of wind turbine power output

    SciTech Connect (OSTI)

    Wegley, H.L.

    1984-08-01T23:59:59.000Z

    A verification of hourly average wind speed forecasts in terms of hourly average power output of a MOD-2 was performed for four sites. Site-specific probabilistic transformation models were developed to transform the forecast and observed hourly average speeds to the percent probability of exceedance of an hourly average power output. (This transformation model also appears to have value in predicting annual energy production for use in wind energy feasibility studies.) The transformed forecasts were verified in a deterministic sense (i.e., as continuous values) and in a probabilistic sense (based upon the probability of power output falling in a specified category). Since the smoothing effects of time averaging are very pronounced, the 90% probability of exceedance was built into the transformation models. Semiobjective and objective (model output statistics) forecasts were made compared for the four sites. The verification results indicate that the correct category can be forecast an average of 75% of the time over a 24-hour period. Accuracy generally decreases with projection time out to approx. 18 hours and then may increase due to the fairly regular diurnal wind patterns that occur at many sites. The ability to forecast the correct power output category increases with increasing power output because occurrences of high hourly average power output (near rated) are relatively rare and are generally not forecast. The semiobjective forecasts proved superior to model output statistics in forecasting high values of power output and in the shorter time frames (1 to 6 hours). However, model output statistics were slightly more accurate at other power output levels and times. Noticeable differences were observed between deterministic and probabilistic (categorical) forecast verification results.

  20. NatioNal aNd Global Forecasts West VirGiNia ProFiles aNd Forecasts

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    · NatioNal aNd Global Forecasts · West VirGiNia ProFiles aNd Forecasts · eNerGy · Healt Global Insight, paid for by the West Virginia Department of Revenue. 2013 WEST VIRGINIA ECONOMIC OUTLOOKWest Virginia Economic Outlook 2013 is published by: Bureau of Business & Economic Research West

  1. Tank characterization reference guide

    SciTech Connect (OSTI)

    De Lorenzo, D.S.; DiCenso, A.T.; Hiller, D.B.; Johnson, K.W.; Rutherford, J.H.; Smith, D.J. [Los Alamos Technical Associates, Kennewick, WA (United States); Simpson, B.C. [Westinghouse Hanford Co., Richland, WA (United States)

    1994-09-01T23:59:59.000Z

    Characterization of the Hanford Site high-level waste storage tanks supports safety issue resolution; operations and maintenance requirements; and retrieval, pretreatment, vitrification, and disposal technology development. Technical, historical, and programmatic information about the waste tanks is often scattered among many sources, if it is documented at all. This Tank Characterization Reference Guide, therefore, serves as a common location for much of the generic tank information that is otherwise contained in many documents. The report is intended to be an introduction to the issues and history surrounding the generation, storage, and management of the liquid process wastes, and a presentation of the sampling, analysis, and modeling activities that support the current waste characterization. This report should provide a basis upon which those unfamiliar with the Hanford Site tank farms can start their research.

  2. Xradia Performance Summary - Update

    SciTech Connect (OSTI)

    Waters, A M; Martz, H E; Chinn, D J; Logan, C M; Gross, J C; Scott, D

    2004-05-24T23:59:59.000Z

    High Energy Density Physics (HEDP) Experiments play an important role in corroborating the improved physics codes that underlie LLNL's Stockpile Stewardship mission. Conducting these experiments, whether on the National Ignition Facility (NIF) or another national facility such as Omega, will require not only improvement in the diagnostics for measuring the experiment, but also detailed knowledge of the as-built target components and assemblies themselves. To assist in this effort, a defined set of well-known reference standards designed to represent a range of HEDP targets have been built and are being used to quantify the performance of different characterization techniques. Without the critical step of using reference standards for qualifying characterization tools there can be no verification of either commercial or internallydeveloped characterization techniques and thus an uncertainty in the as-built-model for the initial condition to the physics codes.

  3. Landscapes as references for design

    E-Print Network [OSTI]

    Batchelor, James P

    1981-01-01T23:59:59.000Z

    This is a study of the ways in which the forms in landscapes - natural terrain adapted and inhabited - can serve as references in architectural design. As references for design, landscapes provide a richness of responses ...

  4. ENRAF gauge reference level calculations

    SciTech Connect (OSTI)

    Huber, J.H., Fluor Daniel Hanford

    1997-02-06T23:59:59.000Z

    This document describes the method for calculating reference levels for Enraf Series 854 Level Detectors as installed in the tank farms. The reference level calculation for each installed level gauge is contained herein.

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

    SciTech Connect (OSTI)

    Templeton, K.J.

    1996-05-23T23:59:59.000Z

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

  6. Budget Reconciliation Procedures Reference Guide

    E-Print Network [OSTI]

    Shull, Kenneth R.

    Budget Reconciliation Procedures Reference Guide eDev Course Number FMS723 Subject Area Budget Northwestern University #12;Reference Guide Budget Reconciliation Table of Contents Helpful Contacts....................................................................................... 14 723QuickRefGuidev1.4 2 of 14 #12;Reference Guide Budget Reconciliation Helpful Contacts Below

  7. Database Updating Through User Feedback in Fingerprint-Based Wi-Fi Location Systems

    E-Print Network [OSTI]

    Sekercioglu, Y. Ahmet

    Database Updating Through User Feedback in Fingerprint-Based Wi-Fi Location Systems Thomas- Fi signals. It first requires the construction of a database of "fingerprints", i.e. signal strengths it with the different reference fingerprints in the database. The main disadvantage of this technique is the labour

  8. Federal Fuels Taxes and Tax Credits (Update) (released in AEO2008)

    Reports and Publications (EIA)

    2008-01-01T23:59:59.000Z

    The Annual Energy Outlook 2008 (AEO) reference case incorporates current regulations that pertain to the energy industry. This section describes the handling of federal taxes and tax credits in AEO2008, focusing primarily on areas where regulations have changed or the handling of taxes or tax credits has been updated.

  9. A Cosmology Forecast Toolkit -- CosmoLib

    E-Print Network [OSTI]

    Zhiqi Huang

    2012-06-11T23:59:59.000Z

    The package CosmoLib is a combination of a cosmological Boltzmann code and a simulation toolkit to forecast the constraints on cosmological parameters from future observations. In this paper we describe the released linear-order part of the package. We discuss the stability and performance of the Boltzmann code. This is written in Newtonian gauge and including dark energy perturbations. In CosmoLib the integrator that computes the CMB angular power spectrum is optimized for a $\\ell$-by-$\\ell$ brute-force integration, which is useful for studying inflationary models predicting sharp features in the primordial power spectrum of metric fluctuations. The numerical code and its documentation are available at http://www.cita.utoronto.ca/~zqhuang/CosmoLib.

  10. Incorporating Forecast Uncertainty in Utility Control Center

    SciTech Connect (OSTI)

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

    2014-07-09T23:59:59.000Z

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

  11. UPF Forecast | Y-12 National Security Complex

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched Ferromagnetism in Layeredof EnergyLeaseEnergyUNCLASSIFIED 2UPDATED: Apps

  12. Humboldt Bay Initiative: 2001 update and accomplishments

    E-Print Network [OSTI]

    Schlosser, Susan; Price-Hall, Rebecca

    2011-01-01T23:59:59.000Z

    from the Humboldt Bay Sea Level Rise Synthesis and Communityis essential to all sea level rise forecasting, estuarineDiego ? ? Visualizing sea-level rise and potential impacts

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

    SciTech Connect (OSTI)

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

    2005-07-01T23:59:59.000Z

    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.

  14. Capillary reference half-cell

    DOE Patents [OSTI]

    Hall, S.H.

    1996-02-13T23:59:59.000Z

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

  15. BETO Announces Updated Multi-Year Program Plan: November 2014...

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

    update of the MYPP. Addthis Related Articles Update Released to BETO's Multi-Year Program Plan BETO Announces Updated Multi-Year Program Plan DOE Publishes Updated SSL R&D Plan...

  16. COSY INFINITY reference manual

    SciTech Connect (OSTI)

    Berz, M.

    1990-07-01T23:59:59.000Z

    This is a reference manual for the arbitrary order particle optics and beam dynamics code COSY INFINITY. It is current as of June 28, 1990. COSY INFINITY is a code to study and design particle optical systems, including beamlines, spectrometers, and particle accelerators. At its core it is using differential algebraic (DA) methods, which allow a very systematic and simple calculation of high order effects. At the same time, it allows the computation of dependences on system parameters, which is often interesting in its own right and can also be used for fitting. COSY INFINITY has a full structured object oriented language environment. This provides a simple interface for the casual user. At the same time, it offers the demanding user a very flexible and powerful tool for the study and design of systems, and more generally, the utilization of DA methods. The power and generality of the environment is perhaps best demonstrated by the fact that the physics routines of COSY INFINITY are written in its own input language and are very compact. The approach also considerably facilitates the implementation of new features because they are incorporated with the same commands that are used for design and study. 26 refs.

  17. Sensor Characteristics Reference Guide

    SciTech Connect (OSTI)

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

    2013-04-01T23:59:59.000Z

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

  18. Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01T23:59:59.000Z

    Solar irradiance data . . . . . . . . . . . . .Accuracy . . . . . . . . . . . . . . . . . Solar Resourcev Uncertainty In Solar Resource: Forecasting

  19. Documentation of the Hourly Time Series NCEP Climate Forecast System Reanalysis

    E-Print Network [OSTI]

    - 1 - Documentation of the Hourly Time Series from the NCEP Climate Forecast System Reanalysis: ------------------------------------------------------------------------------------------------------------ Initial condition 1 Jan 1979, 0Z Record 1: f00: forecast at first time step of 3 mins Record 2: f01: forecast (either averaged over 0 to 1 hour, or instantaneous at 1 hour) Record 3: f02: forecast (either

  20. Solving the problem of inadequate scoring rules for assessing probabilistic football forecast models

    E-Print Network [OSTI]

    Fenton, Norman

    Solving the problem of inadequate scoring rules for assessing probabilistic football forecast forecasting models, and the relative simplicity of the outcome of such forecasts (they require only three their forecast accuracy. Moreover, the various scoring rules used for validation in previous studies

  1. Development, implementation, and skill assessment of the NOAA/NOS Great Lakes Operational Forecast System

    E-Print Network [OSTI]

    Development, implementation, and skill assessment of the NOAA/NOS Great Lakes Operational Forecast Lakes Operational Forecast System (GLOFS) uses near-real-time atmospheric observa- tions and numerical weather prediction forecast guidance to produce three-dimensional forecasts of water temperature

  2. Distributed Forcing of Forecast and Assimilation Error Systems BRIAN F. FARRELL

    E-Print Network [OSTI]

    Farrell, Brian F.

    Distributed Forcing of Forecast and Assimilation Error Systems BRIAN F. FARRELL Division forecast system gov- erning forecast error growth and the tangent linear observer system governing deterministic and stochastic forcings of the forecast and observer systems over a chosen time interval

  3. Ozone ensemble forecast with machine learning Vivien Mallet,1,2

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Ozone ensemble forecast with machine learning algorithms Vivien Mallet,1,2 Gilles Stoltz,3 forecasts. The latter rely on a multimodel ensemble built for ozone forecasting with the modeling system Europe in order to forecast ozone daily peaks and ozone hourly concentrations. On the basis of past

  4. MLWFA: A Multilingual Weather Forecast Text Generation Tianfang YAO Dongmo ZHANG Qian WANG

    E-Print Network [OSTI]

    Wu, Dekai

    MLWFA: A Multilingual Weather Forecast Text Generation System1 Tianfang YAO Dongmo ZHANG Qian WANG generation; Weather forecast generation system Abstract In this demonstration, we present a system for multilingual text generation in the weather forecast domain. Multilingual Weather Forecast Assistant (MLWFA

  5. November 14, 2000 A Quarterly Forecast of U.S. Trade

    E-Print Network [OSTI]

    Shyy, Wei

    November 14, 2000 A Quarterly Forecast of U.S. Trade in Services and the Current Account, 2000 of Forecast*** We forecast that the services trade surplus, which declined from 1997 to 1998 and edged upward. That is, from a level of $80.6 billion in 1999, we forecast that the services trade surplus will be $80

  6. USING BOX-JENKINS MODELS TO FORECAST FISHERY DYNAMICS: IDENTIFICATION, ESTIMATION, AND CHECKING

    E-Print Network [OSTI]

    ~ is illustrated by developing a model that makes monthly forecasts of skipjack tuna, Katsuwonus pelamis, catches

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

    SciTech Connect (OSTI)

    Lantz, E.; Hand, M.

    2010-05-01T23:59:59.000Z

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

  8. ASSESSING THE QUALITY AND ECONOMIC VALUE OF WEATHER AND CLIMATE FORECASTS

    E-Print Network [OSTI]

    Katz, Richard

    INFORMATION SYSTEM ∑ Forecast -- Conditional probability distribution for event Z = z indicates forecast tornado #12;(1.2) FRAMEWORK ∑ Joint Distribution of Observations & Forecasts Observed Weather = Forecast probability p (e.g., induced by Z) ∑ Reliability Diagram Observed weather: = 1 (Adverse weather occurs) = 0

  9. A comparison of univariate methods for forecasting electricity demand up to a day ahead

    E-Print Network [OSTI]

    McSharry, Patrick E.

    A comparison of univariate methods for forecasting electricity demand up to a day ahead James W methods for short-term electricity demand forecasting for lead times up to a day ahead. The very short of Forecasters. Published by Elsevier B.V. All rights reserved. Keywords: Electricity demand forecasting

  10. Resource Adequacy Load Forecast A Report to the Resource Adequacy Advisory Committee

    E-Print Network [OSTI]

    one hour peak demand and monthly energy assuming normal weather. The Council forecast includes loadsResource Adequacy Load Forecast A Report to the Resource Adequacy Advisory Committee Tom√°s of the assessment is the load forecast. The Council staff has recently developed a load forecast to be used

  11. A collaborative demand forecasting process with event-based fuzzy judgements Naoufel Cheikhrouhou a,

    E-Print Network [OSTI]

    A collaborative demand forecasting process with event-based fuzzy judgements Naoufel Cheikhrouhou a July 2011 Keywords: Collaborative forecasting Demand planning Judgement Time series Fuzzy logic a b s t r a c t Mathematical forecasting approaches can lead to reliable demand forecast in some

  12. Demand forecast accuracy and performance of inventory policies under multi-level rolling

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Demand forecast accuracy and performance of inventory policies under multi-level rolling schedule is to study the behaviour of lot-sizing rules in a multi- level context when forecast demand is subject Interchange to ameliorate demand forecast. Although the presence or absence of forecast errors matters more

  13. NEMA Distribution Transformers, CCE Overview and Update presentation...

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

    Distribution Transformers, CCE Overview and Update presentation, dated 05242011 NEMA Distribution Transformers, CCE Overview and Update presentation, dated 05242011 This...

  14. 2006 INTEGRATED ENERGY POLICY REPORT UPDATE

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION 2006 INTEGRATED ENERGY POLICY REPORT UPDATE INTEGRATED ENERGY POLICY REPORT UPDATE January 3, 2007 Executive Summary Page E-2, first paragraph under conducted two cycles of renewable energy solicitations and negotiated a number of bilateral agreements

  15. Energy Storage Systems 2010 Update Conference Presentations ...

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

    3 Energy Storage Systems 2010 Update Conference Presentations - Day 2, Session 3 The U.S. DOE Energy Storage Systems Program (ESS) conducted a record-breaking Update Conference at...

  16. Energy Storage Systems 2010 Update Conference Presentations ...

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

    2 Energy Storage Systems 2010 Update Conference Presentations - Day 2, Session 2 The U.S. DOE Energy Storage Systems Program (ESS) conducted a record-breaking Update Conference at...

  17. Energy Storage Systems 2010 Update Conference Presentations ...

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

    of Day 2, chaired by NETL's Kim Nuhfer, are below. ESS 2010 Update Conference - Low Cost Energy Storage - Ted Wiley, Aquion.pdf Ess 2010 Update Conference - Solid State Li Metal...

  18. Energy Storage Systems 2010 Update Conference Presentations ...

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

    4 Energy Storage Systems 2010 Update Conference Presentations - Day 1, Session 4 The U.S. DOE Energy Storage Systems Program (ESS) conducted a record-breaking Update Conference at...

  19. Energy Storage Systems 2010 Update Conference Presentations ...

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

    1 Energy Storage Systems 2010 Update Conference Presentations - Day 1, Session 1 The U.S. DOE Energy Storage Systems Program (ESS) conducted a record-breaking Update Conference at...

  20. Energy Storage Systems 2010 Update Conference Presentations ...

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

    Terry Aselage, are below. ESS 2010 Update Conference - Advanced Stationary Electrical Energy Storage R&D at PNNL - Z Gary Yang, PNNL.pdf ESS 2010 Update Conference - A New...

  1. Energy Storage Systems 2010 Update Conference Presentations ...

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

    3 Energy Storage Systems 2010 Update Conference Presentations - Day 1, Session 3 The U.S. DOE Energy Storage Systems Program (ESS) conducted a record-breaking Update Conference at...

  2. Energy Storage Systems 2010 Update Conference Presentations ...

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

    chaired by ARPA-E's Mark Johnson, are below. ESS 2010 Update Conference - Electrochemical Energy Storage for the Grid - Yet-Ming Chiang, MIT.pdf ESS 2010 Update Conference - DOE...

  3. Nano Communication Networks Update | GE Global Research

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

    Nano Communication Networks Update Nano Communication Networks Update Steve Bush 2011.12.09 Hi everybody, In my last blog I talked about some of the work I have been doing...

  4. Catalog Update 2006 International Education Abroad 1

    E-Print Network [OSTI]

    Gering, Jon C.

    Catalog Update 2006 International Education Abroad 1 INTERNATIONAL EDUCATION ABROAD 2005-2007 CATALOG UPDATE Changes effective 2006-2007 New Courses CHN 310 China Summer Study Abroad Program 6-7 hours

  5. Forecasting Volatility in Stock Market Using GARCH Models

    E-Print Network [OSTI]

    Yang, Xiaorong

    2008-01-01T23:59:59.000Z

    Forecasting volatility has held the attention of academics and practitioners all over the world. The objective for this master's thesis is to predict the volatility in stock market by using generalized autoregressive conditional heteroscedasticity(GARCH...

  6. Forecasting Returns and Volatilities in GARCH Processes Using the Bootstrap

    E-Print Network [OSTI]

    Romo, Juan

    Forecasting Returns and Volatilities in GARCH Processes Using the Bootstrap Lorenzo Pascual, Juan generated by GARCH processes. The main advantage over other bootstrap methods previously proposed for GARCH by having conditional heteroscedasticity. Generalized Autoregressive Conditionally Heteroscedastic (GARCH

  7. Wind Power Forecasting: State-of-the-Art 2009

    E-Print Network [OSTI]

    Kemner, Ken

    Wind Power Forecasting: State-of-the-Art 2009 ANL/DIS-10-1 Decision and Information Sciences about Argonne and its pioneering science and technology programs, see www.anl.gov. #12;Wind Power

  8. 2007 National Hurricane Center Forecast Verification Report James L. Franklin

    E-Print Network [OSTI]

    storms 17 4. Genesis Forecasts 17 5. Summary and Concluding Remarks 18 a. Atlantic Summary 18 statistical models, provided the best intensity guidance at each time period. The 2007 season marked the first

  9. Recently released EIA report presents international forecasting data

    SciTech Connect (OSTI)

    NONE

    1995-05-01T23:59:59.000Z

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

  10. Optimally controlling hybrid electric vehicles using path forecasting

    E-Print Network [OSTI]

    Katsargyri, Georgia-Evangelina

    2008-01-01T23:59:59.000Z

    Hybrid Electric Vehicles (HEVs) with path-forecasting belong to the class of fuel efficient vehicles, which use external sensory information and powertrains with multiple operating modes in order to increase fuel economy. ...

  11. Variable Selection and Inference for Multi-period Forecasting Problems

    E-Print Network [OSTI]

    Pesaran, M Hashem; Pick, Andreas; Timmermann, Allan

    Variable Selection and Inference for Multi-period Forecasting Problems? M. Hashem Pesaran Cambridge University and USC Andreas Pick De Nederlandsche Bank and Cambridge University, CIMF Allan Timmermann UC San Diego and CREATES January 26, 2009...

  12. Optimally Controlling Hybrid Electric Vehicles using Path Forecasting

    E-Print Network [OSTI]

    Kolmanovsky, Ilya V.

    The paper examines path-dependent control of Hybrid Electric Vehicles (HEVs). In this approach we seek to improve HEV fuel economy by optimizing charging and discharging of the vehicle battery depending on the forecasted ...

  13. Post-Construction Evaluation of Forecast Accuracy Pavithra Parthasarathi1

    E-Print Network [OSTI]

    Levinson, David M.

    Post-Construction Evaluation of Forecast Accuracy Pavithra Parthasarathi1 David Levinson 2 February, the assumed networks to the actual in-place networks and other travel behavior assumptions that went

  14. africa conditional forecasts: Topics by E-print Network

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

    forecasts had the potential to improve resource management but instead played only a marginal role in real-world decision making. 1 A widespread perception that the quality of the...

  15. An econometric analysis and forecasting of Seoul office market

    E-Print Network [OSTI]

    Kim, Kyungmin

    2011-01-01T23:59:59.000Z

    This study examines and forecasts the Seoul office market, which is going to face a big supply in the next few years. After reviewing several previous studies on the Dynamic model and the Seoul Office market, this thesis ...

  16. A methodology for forecasting carbon dioxide flooding performance

    E-Print Network [OSTI]

    Marroquin Cabrera, Juan Carlos

    1998-01-01T23:59:59.000Z

    A methodology was developed for forecasting carbon dioxide (CO2) flooding performance quickly and reliably. The feasibility of carbon dioxide flooding in the Dollarhide Clearfork "AB" Unit was evaluated using the methodology. This technique is very...

  17. Weather Research and Forecasting Model 2.2 Documentation

    E-Print Network [OSTI]

    Sadjadi, S. Masoud

    ................................................................................................. 20 3.1.2 Integrate's Flow of ControlWeather Research and Forecasting Model 2.2 Documentation: A Step-by-step guide of a Model Run .......................................................................................................................... 19 3.1 The Integrate Subroutine

  18. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07T23:59:59.000Z

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

  19. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    Bel, G; Toots, M; Bandi, M M

    2015-01-01T23:59:59.000Z

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  20. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    G. Bel; C. P. Connaughton; M. Toots; M. M. Bandi

    2015-03-29T23:59:59.000Z

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  1. Dispersion in analysts' forecasts: does it make a difference?

    E-Print Network [OSTI]

    Adut, Davit

    2004-09-30T23:59:59.000Z

    Financial analysts are an important group of information intermediaries in the capital markets. Their reports, including both earnings forecasts and stock recommendations, are widely transmitted and have a significant impact on stock prices (Womack...

  2. OCTOBER-NOVEMBER FORECAST FOR 2014 CARIBBEAN BASIN HURRICANE ACTIVITY

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    and hurricanes, but instead predicts both hurricane days and Accumulated Cyclone Energy (ACE). Typically, while) tropical cyclone (TC) activity. We have decided to issue this forecast, because Klotzbach (2011) has

  3. Adaptive sampling and forecasting with mobile sensor networks

    E-Print Network [OSTI]

    Choi, Han-Lim

    2009-01-01T23:59:59.000Z

    This thesis addresses planning of mobile sensor networks to extract the best information possible out of the environment to improve the (ensemble) forecast at some verification region in the future. To define the information ...

  4. Pacific Adaptation Strategy Assistance Program Dynamical Seasonal Forecasting

    E-Print Network [OSTI]

    Lim, Eun-pa

    Pacific Adaptation Strategy Assistance Program Dynamical Seasonal Forecasting Seasonal Prediction · POAMA · Issues for future Outline #12;Pacific Adaptation Strategy Assistance Program Major source Adaptation Strategy Assistance Program El Nino Mean State · Easterlies westward surface current upwelling

  5. The Rationality of EIA Forecasts under Symmetric and Asymmetric Loss

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01T23:59:59.000Z

    Agency: 1982-2005a, Annual Energy Outlook, EIA, Washington,Agency: 2004, Annual Energy Outlook Forecast Evaluation,Agency: 2005b, Annual Energy Outlook, EIA, Washington, D.C.

  6. Forecasting and strategic inventory placement for gas turbine aftermarket spares

    E-Print Network [OSTI]

    Simmons, Joshua T. (Joshua Thomas)

    2007-01-01T23:59:59.000Z

    This thesis addresses the problem of forecasting demand for Life Limited Parts (LLPs) in the gas turbine engine aftermarket industry. It is based on work performed at Pratt & Whitney, a major producer of turbine engines. ...

  7. Mesoscale predictability and background error convariance estimation through ensemble forecasting

    E-Print Network [OSTI]

    Ham, Joy L

    2002-01-01T23:59:59.000Z

    Over the past decade, ensemble forecasting has emerged as a powerful tool for numerical weather prediction. Not only does it produce the best estimate of the state of the atmosphere, it also could quantify the uncertainties associated with the best...

  8. A model for short term electric load forecasting

    E-Print Network [OSTI]

    Tigue, John Robert

    1975-01-01T23:59:59.000Z

    A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE, III Submitted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE May 1975 Major... Subject: Electrical Engineering A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE& III Approved as to style and content by: (Chairman of Committee) (Head Depart t) (Member) ;(Me r (Member) (Member) May 1975 ABSTRACT...

  9. Subhourly wind forecasting techniques for wind turbine operations

    SciTech Connect (OSTI)

    Wegley, H.L.; Kosorok, M.R.; Formica, W.J.

    1984-08-01T23:59:59.000Z

    Three models for making automated forecasts of subhourly wind and wind power fluctuations were examined to determine the models' appropriateness, accuracy, and reliability in wind forecasting for wind turbine operation. Such automated forecasts appear to have value not only in wind turbine control and operating strategies, but also in improving individual wind turbine control and operating strategies, but also in improving individual wind turbine operating strategies (such as determining when to attempt startup). A simple persistence model, an autoregressive model, and a generalized equivalent Markhov (GEM) model were developed and tested using spring season data from the WKY television tower located near Oklahoma City, Oklahoma. The three models represent a pure measurement approach, a pure statistical method and a statistical-dynamical model, respectively. Forecasting models of wind speed means and measures of deviations about the mean were developed and tested for all three forecasting techniques for the 45-meter level and for the 10-, 30- and 60-minute time intervals. The results of this exploratory study indicate that a persistence-based approach, using onsite measurements, will probably be superior in the 10-minute time frame. The GEM model appears to have the most potential in 30-minute and longer time frames, particularly when forecasting wind speed fluctuations. However, several improvements to the GEM model are suggested. In comparison to the other models, the autoregressive model performed poorly at all time frames; but, it is recommended that this model be upgraded to an autoregressive moving average (ARMA or ARIMA) model. The primary constraint in adapting the forecasting models to the production of wind turbine cluster power output forecasts is the lack of either actual data, or suitable models, for simulating wind turbine cluster performance.

  10. Weather Forecast Data an Important Input into Building Management Systems

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01T23:59:59.000Z

    it can generate as much or more energy that it needs ? Building activities need N kWhrs per day (solar panels, heating, etc) ? Harvested from solar panels & passive solar. Amount depends on weather ? NWP models forecast DSWRF @ surface (MJ/m2... contract work Saturday Would you plan work for Saturday? Not much detail for Saturday and Sunday With more info could be easier to decide go, no go From deterministic to probabilistic ? Forecast presented as a single scenario ? One scenario presented...

  11. Streamflow forecasting for large-scale hydrologic systems

    E-Print Network [OSTI]

    Awwad, Haitham Munir

    1991-01-01T23:59:59.000Z

    STREAMFLOW FORECASTING FOR LARGE-SCALE HYDROLOGIC SYSTEMS A Thesis by HAITHAM MUNIR AWWAD Submitted to the Office of Graduate Studies of Texas AkM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May... 1991 Major Subject: Civil Engineering STREAMFLOW FORECASTING FOR LARGE-SCALE HYDROLOGIC SYSTEMS A Thesis by HAITHAM MUNIR AWWAD Approved as to style and content by: uan B. Valdes (Chair of Committee) alph A. Wurbs (Member) Marshall J. Mc...

  12. Optical probe with reference fiber

    DOE Patents [OSTI]

    Da Silva, Luiz B. (Danville, CA); Chase, Charles L. (Dublin, CA)

    2006-03-14T23:59:59.000Z

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

  13. ECONOMICS UPDATE Issue 1 Autumn 2014

    E-Print Network [OSTI]

    Levi, Ran

    ECONOMICS UPDATE Issue 1 Economics Update Autumn 2014 UNIVERSITY OF ABERDEEN ­ DEPARTMENT OF ECONOMICS IN THIS ISSUE Welcome to the first Economics update! In this twice-yearly publication, we. In the Research Assessment Exercise results of 2008, 100% of Economics research, was judged to be of international

  14. Software Update Recovery for Wireless Sensor Networks

    E-Print Network [OSTI]

    Sreenan, Cormac J.

    mechanism that uses loss-of- control to provide high-reliability, low energy, software updates, includingSoftware Update Recovery for Wireless Sensor Networks Stephen Brown1 and Cormac J. Sreenan2 1 Laboratory, University College Cork, Ireland Abstract. Updating software over the network is important

  15. Catalog Update 2006 Math & Computer Science 1

    E-Print Network [OSTI]

    Gering, Jon C.

    Catalog Update 2006 Math & Computer Science 1 MATH AND COMPUTER SCIENCE DIVISION 2005-2007 CATALOG UPDATE Changes effective 2006-2007 Degree Update COMPUTER SCIENCE BACHELOR OF SCIENCE Semester Hours CS 100 Computer Science Seminar.........................1 CS 180 Foundations of Computer Science I

  16. Opportunity for feedback Opportunity for updates

    E-Print Network [OSTI]

    Opportunity for feedback Opportunity for updates Opportunity to find out all of the things I don) What do these all mean? Vision (1) Values (5-10) Strategic Priorities (5-7) Education, scholarship update Research Plan Pinnacles or not? Focus on impact Update every 3 yrs Capital Plan Existing

  17. FAQS Reference Guide- Chemical Processing

    Broader source: Energy.gov [DOE]

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

  18. FAQS Reference Guide Ė Emergency Management

    Broader source: Energy.gov [DOE]

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

  19. FAQS Reference Guide Ė Environmental Compliance

    Broader source: Energy.gov [DOE]

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

  20. FAQS Reference Guide Ė Construction Management

    Broader source: Energy.gov [DOE]

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