National Library of Energy BETA

Sample records for forecasting specific questions

  1. Economics Faculty Advising Do you have economics industry specific questions?

    E-Print Network [OSTI]

    Alpay, S. Pamir

    Economics Faculty Advising Do you have economics industry specific questions? Are you planning to attend graduate school for economics and want more information? Are you looking to build a relationship with an economics faculty member? Below are the Economics Faculty Advisors for Spring 2015 semester. The advisor

  2. The Los Alamos dynamic radiation environment assimilation model (DREAM) for space weather specification and forecasting

    SciTech Connect (OSTI)

    Reeves, Geoffrey D [Los Alamos National Laboratory; Friedel, Reiner H W [Los Alamos National Laboratory; Chen, Yue [Los Alamos National Laboratory; Koller, Josef [Los Alamos National Laboratory; Henderson, Michael G [Los Alamos National Laboratory

    2008-01-01

    The Dynamic Radiation Environment Assimilation Model (DREAM) was developed at Los Alamos National Laboratory to assess, quantify, and predict the hazards from the natural space environment and the anthropogenic environment produced by high altitude nuclear explosions (HANE). DREAM was initially developed as a basic research activity to understand and predict the dynamics of the Earth's Van Allen radiation belts. It uses Kalman filter techniques to assimilate data from space environment instruments with a physics-based model of the radiation belts. DREAM can assimilate data from a variety of types of instruments and data with various levels of resolution and fidelity by assigning appropriate uncertainties to the observations. Data from any spacecraft orbit can be assimilated but DREAM was designed to function with as few as two spacecraft inputs: one from geosynchronous orbit and one from GPS orbit. With those inputs, DREAM can be used to predict the environment at any satellite in any orbit whether space environment data are available in those orbits or not. Even with very limited data input and relatively simple physics models, DREAM specifies the space environment in the radiation belts to a high level of accuracy. DREAM has been extensively tested and evaluated as we transition from research to operations. We report here on one set of test results in which we predict the environment in a highly-elliptical polar orbit. We also discuss long-duration reanalysis for spacecraft design, using DREAM for real-time operations, and prospects for 1-week forecasts of the radiation belt environment.

  3. 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....

  4. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

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

  5. Composing questions

    E-Print Network [OSTI]

    Kotek, Hadas

    2014-01-01

    This dissertation motivates a new syntax and semantics for simplex and multiple wh-questions, concentrating on English and German data. The proposed theory combines Cable's (2007; 2010) Q-based syntax for wh-movement and ...

  6. Waste Specification Records - Hanford Site

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

    Specification Records About Us Hanford Site Solid Waste Acceptance Program What's New Acceptance Criteria Acceptance Process Becoming a new Hanford Customer Annual Waste Forecast...

  7. Wind Power Forecasting Data

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

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

  8. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

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

  9. Forecasting Water Quality & Biodiversity

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

    Forecasting Water Quality & Biodiversity March 25, 2015 Cross-cutting Sustainability Platform Review Principle Investigator: Dr. Henriette I. Jager Organization: Oak Ridge National...

  10. *The questions presented in this Q and A are hypotheticals therefore, the answers should not be relied upon as legal advice. For a specific analysis of the effect of export control laws on your specific

    E-Print Network [OSTI]

    Marsh, David

    should not be relied upon as legal advice. For a specific analysis of the effect of export control laws on your specific situation, contact the Office of General Counsel. Export Controls Q and A* 1. I'm taking their international cell phones and iPods. What impact will export controls have on this trip? A: Your trip

  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 turbines. This second effect is the primary use of the fuel price forecast for the Council's Fifth Power

  12. Weather Forecasting Spring 2014

    E-Print Network [OSTI]

    Hennon, Christopher C.

    ATMS 350 Weather Forecasting Spring 2014 Professor : Dr. Chris Hennon Office : RRO 236C Phone : 232 of atmospheric physics and the ability to include this understanding into modern numerical weather prediction agencies, forecast tools, numerical weather prediction models, model output statistics, ensemble

  13. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    ....................................................................................................1-16 Energy Consumption Data...............................................1-15 Data Sources for Energy Demand Forecasting ModelsCALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report

  14. 100 Questions About Sturgis

    E-Print Network [OSTI]

    Sebelius, John

    2012-05-31

    investigates my connection and exploration of this masculine culture and the individuals I lived amongst. I am fascinated with the duality between conceptual and perceptual information. The settings for a majority of my paintings are not specifically defined.... A common theme throughout my work is the duality between attraction and repulsion. Topically, the surface of a painting can be treated to be visually appealing while the content behind the work may be off-putting. Although “100 Questions About...

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Impact of PV forecasts uncertainty in batteries management in microgrids Andrea Michiorri Arthur-based battery schedule optimisation in microgrids in presence of network constraints. We examine a specific case production forecast algorithm is used in combination with a battery schedule optimisation algorithm. The size

  16. Airplanes Aloft as a Sensor Network for Wind Forecasting

    E-Print Network [OSTI]

    Horvitz, Eric

    Airplanes Aloft as a Sensor Network for Wind Forecasting Ashish Kapoor, Zachary Horvitz, Spencer for observing weather phenomena at a continental scale. We focus specifically on the problem of wind forecasting with the sensed winds. The experiments show the promise of using airplane in flight as a large-scale sensor

  17. Solar Forecast Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE)

    For the Solar Forecast Improvement Project (SFIP), the Earth System Research Laboratory (ESRL) is partnering with the National Center for Atmospheric Research (NCAR) and IBM to develop more...

  18. Pressure Normalization of Production Rates Improves Forecasting Results 

    E-Print Network [OSTI]

    Lacayo Ortiz, Juan Manuel

    2013-08-07

    reliable production forecasting technique suited to interpret unconventional wells in specific situations such as unstable operating conditions, limited availability of production data (short production history) and high-pressure, rate-restricted wells...

  19. Improving automotive battery sales forecast

    E-Print Network [OSTI]

    Bulusu, Vinod

    2015-01-01

    Improvement in sales forecasting allows firms not only to respond quickly to customers' needs but also to reduce inventory costs, ultimately increasing their profits. Sales forecasts have been studied extensively to improve ...

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

    E-Print Network [OSTI]

    Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts ............................................................................................................................ 5 U.S. Natural Gas Commodity Prices

  1. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required in electricity demand is, of course, crucial to determining the need for new electricity resources and helping of any forecast of electricity demand and developing ways to reduce the risk of planning errors

  2. Consensus Coal Production Forecast for

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    Consensus 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 References 27 #12;W.Va. Consensus Coal Forecast Update 2009 iii List of Tables 1. W.Va. Coal Production

  3. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Rutledge, Steven

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary microbursts than in many previously documented microbursts. Alignment of Doppler radar data to reports of wind-related damage to electrical power infrastructure in Phoenix allowed a comparison of microburst wind damage

  4. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary and interpretation of information from National Weather Service watches and warnings by10 decision makers such an outlier to the regional severe weather climatology. An analysis of the synoptic and13 mesoscale

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  6. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

    Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

  7. Critical Question #2: What are the Best Practices for Ventilation...

    Energy Savers [EERE]

    2: What are the Best Practices for Ventilation Specific to Multifamily Buildings? Critical Question 2: What are the Best Practices for Ventilation Specific to Multifamily...

  8. (Infrequently Questions) Lydia

    E-Print Network [OSTI]

    Ehrhardt, Matthias

    Scilab Bag Of Tricks The Scilab­2.5 IAQ (Infrequently Asked Questions) Lydia E. van Dijk (Infrequently Asked Questions) by Lydia E. van Dijk and Christoph L. Spiel Copyright© 2000 by L. E. van Dijk, Ch

  9. Last Call for Questions

    Broader source: Energy.gov [DOE]

    Just a quick reminder that the deadline for submitting your home energy efficiency questions directly to Secretary Chu is midnight tonight (10/07). The Secretary will personally respond to some of the questions next week.

  10. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01

    This presentation describes the importance of good forecasting for variable generation, the different approaches used by industry, and the importance of validated high-quality data.

  11. Wind Power 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentricNCubicthe FOIA?ResourceMeasurement BuoyForecasting Sign

  12. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    s economy. Demand Forecasts The three energy futures wereto meet the forecast demand in each energy futurE2. e e1£~energy saved through improved appliance efficiencies. Also icit in our demand forecasts

  13. Cool Roofs: Your Questions Answered

    Broader source: Energy.gov [DOE]

    When Secretary Chu announced that the Department of Energy had installed a “cool roof” atop the west building of our Washington, DC headquarters, it elicited a fair number of questions from his Facebook fans. We decided to reach out to the people behind the project for their insight on the specific benefits of switching to a cool roof, and the process that went into making that choice.

  14. Price forecasting for notebook computers 

    E-Print Network [OSTI]

    Rutherford, Derek Paul

    1997-01-01

    of individual features are estimated. A time series analysis is used to forecast and can be used, for example, to forecast (1) notebook computer price at introduction, and (2) rate of price erosion for a notebook's life cycle. Results indicate that this approach...

  15. Multivariate Forecast Evaluation And Rationality Testing

    E-Print Network [OSTI]

    Komunjer, Ivana; OWYANG, MICHAEL

    2007-01-01

    Economy, 95(5), 1062—1088. MULTIVARIATE FORECASTS Chaudhuri,Notion of Quantiles for Multivariate Data,” Journal of thePress, United Kingdom. MULTIVARIATE FORECASTS Kirchgässner,

  16. Frequently Asked Questions

    Broader source: Energy.gov [DOE]

    Frequently asked questions (FAQs) and their corresponding answers regarding industrial distributed energy (DE) and combined heat and power (CHP) are provided below.

  17. Short-Term Load Forecasting by Feed-Forward Neural Networks Saied S. Sharif1

    E-Print Network [OSTI]

    Taylor, James H.

    , Department of Electrical and Computer Engineering, University of New Brunswick, Fredericton, NB, CANADA, E3B) is presented for the hourly load forecasting of the coming days. In this approach, 24 independent networks are used for the next day load forecast. Each network is utilized for the prediction of load at a specific

  18. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

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

    2014-11-13

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

  19. Global disease monitoring and forecasting with Wikipedia

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

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

    2014-11-13

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

  20. Student Questioning Educational Outreach

    E-Print Network [OSTI]

    Petta, Jason

    their own water filters First filter- in classroom- filter paper Second filter- in classroom- gravel, sand Trenton High students Two weeks of materials science- water filtration Worked on Potters for Peace filters with clay and sawdust #12;What is a good question? A good question can be answered

  1. Problem of Questioning

    ScienceCinema (OSTI)

    None

    2011-04-25

    Le Prof.Leprince-Ringuet, chercheur sur le plan scientifique, artistique et humain, parle de la remise en question des hommes et la remise en question scientifique fondamentale ou exemplaire- plusieurs personnes prennent la parole p.ex Jeanmairet, Adam, Gregory. Le Prof.Gregory clot la soirée en remerciant le Prof.Leprince-Ringuet

  2. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01

    This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

  3. Downscaling Extended Weather Forecasts for Hydrologic Prediction

    SciTech Connect (OSTI)

    Leung, Lai-Yung R.; Qian, Yun

    2005-03-01

    Weather and climate forecasts are critical inputs to hydrologic forecasting systems. The National Center for Environmental Prediction (NCEP) issues 8-15 days outlook daily for the U.S. based on the Medium Range Forecast (MRF) model, which is a global model applied at about 2? spatial resolution. Because of the relatively coarse spatial resolution, weather forecasts produced by the MRF model cannot be applied directly to hydrologic forecasting models that require high spatial resolution to represent land surface hydrology. A mesoscale atmospheric model was used to dynamically downscale the 1-8 day extended global weather forecasts to test the feasibility of hydrologic forecasting through this model nesting approach. Atmospheric conditions of each 8-day forecast during the period 1990-2000 were used to provide initial and boundary conditions for the mesoscale model to produce an 8-day atmospheric forecast for the western U.S. at 30 km spatial resolution. To examine the impact of initialization of the land surface state on forecast skill, two sets of simulations were performed with the land surface state initialized based on the global forecasts versus land surface conditions from a continuous mesoscale simulation driven by the NCEP reanalysis. Comparison of the skill of the global and downscaled precipitation forecasts in the western U.S. showed higher skill for the downscaled forecasts at all precipitation thresholds and increasingly larger differences at the larger thresholds. Analyses of the surface temperature forecasts show that the mesoscale forecasts generally reduced the root-mean-square error by about 1.5 C compared to the global forecasts, because of the much better resolved topography at 30 km spatial resolution. In addition, initialization of the land surface states has large impacts on the temperature forecasts, but not the precipitation forecasts. The improvements in forecast skill using downscaling could be potentially significant for improving hydrologic forecasts for managing river basins.

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

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01

    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 ...

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

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

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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    weather prediction solar irradiance forecasts in the US.2013: Review of solar irradiance forecasting methods and asatellite-derived irradiances: Description and validation.

  7. Massachusetts state airport system plan forecasts.

    E-Print Network [OSTI]

    Mathaisel, Dennis F. X.

    This report is a first step toward updating the forecasts contained in the 1973 Massachusetts State System Plan. It begins with a presentation of the forecasting techniques currently available; it surveys and appraises the ...

  8. 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 ...

  9. Forecasting consumer products using prediction markets

    E-Print Network [OSTI]

    Trepte, Kai

    2009-01-01

    Prediction Markets hold the promise of improving the forecasting process. Research has shown that Prediction Markets can develop more accurate forecasts than polls or experts. Our research concentrated on analyzing Prediction ...

  10. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

    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

  11. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    income 7 Figure 1.14: United States inflation Rate 8 Figure 1.15: Select United States interest Rates 8 2014 TABLE OF CONTENTS EXECUTiVE SUMMARY 1 CHAPTER 1: THE UNiTED STATES ECONOMY 3 Recent Trends Forecast Summary 2 CHAPTER 1: THE UNiTED STATES ECONOMY Figure 1.1: United States Real GDP Growth 3 Figure

  12. Modeling and Forecasting Electric Daily Peak Loads

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    for the same data. Two methods are described for forecasting daily peak loads up to one week ahead through, including generator unit commitment, hydro-thermal coordination, short-term maintenance, fuel allocation forecasting accuracies. STLF forecasting covers the daily peak load, total daily energy, and daily load curve

  13. 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

  14. Forecasting phenology under global warming

    E-Print Network [OSTI]

    Silander Jr., John A.

    Forecasting phenology under global warming Ine´s Iba´n~ez1,*, Richard B. Primack2, Abraham J in phenology. Keywords: climate change; East Asia, global warming; growing season, hierarchical Bayes; plant is shifting, and these shifts have been linked to recent global warming (Parmesan & Yohe 2003; Root et al

  15. LOAD FORECASTING Eugene A. Feinberg

    E-Print Network [OSTI]

    Feinberg, Eugene A.

    , regression, artificial intelligence. 1. Introduction Accurate models for electric power load forecasting to make important decisions including decisions on pur- chasing and generating electric power, load for different operations within a utility company. The natures 269 #12;270 APPLIED MATHEMATICS FOR POWER SYSTEMS

  16. Doing Business Frequently Asked Questions

    Broader source: Energy.gov [DOE]

    The following are frequently asked questions about working with in partnership with DOE laboratories.

  17. ARM - Science Questions

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Comments?govInstrumentsnoaacrnBarrow, Alaska OutreachCalendarPressExtended Facility SGPScience Questions Related

  18. ARM - Science Questions

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Comments?govInstrumentsnoaacrnBarrow, Alaska OutreachCalendarPressExtended Facility SGPScience Questions

  19. ARM - Science Questions

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Comments?govInstrumentsnoaacrnBarrow, Alaska OutreachCalendarPressExtended Facility SGPScience QuestionsScience

  20. ARM - Science Questions

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Comments?govInstrumentsnoaacrnBarrow, Alaska OutreachCalendarPressExtended Facility SGPScienceScience Questions

  1. ARM - AMF Science Questions

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTechtail.TheoryTuesday, August 10, 20102016 NewsUsers' Executive09AzoresAMF Science Questions

  2. Forecasting wind speed financial return

    E-Print Network [OSTI]

    D'Amico, Guglielmo; Prattico, Flavio

    2013-01-01

    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.

  3. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16

    and encouragement. I am very grateful to Lucille and Michael Hobbs for their friendship, understanding and financial support. Finally, thank you to Tom Decker, Pat Jackson and Brian Zellar for all their contributions and hard work on this project... below: 1. Na?ve 2. Linear Regression 3. Moving Average 4. Exponential 5. Double exponential The na?ve forecasting method assumes that more recent data values are the best predictors of future values. The model is ? t+1 = Y t . Where ? t...

  4. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

    Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens to the Klim wind farm using three WPPT forecasts based on different weather forecasting systems. It is shown of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

  5. Weather Forecasts are for Wimps: Why Water Resource Managers Do Not Use Climate Forecasts

    E-Print Network [OSTI]

    Rayner, Steve; Lach, Denise; Ingram, Helen

    2005-01-01

    and Winter, S. G. : 1960, Weather Information and EconomicThe ENSO Signal 7, 4–6. WEATHER FORECASTS ARE FOR WIMPSWEATHER FORECASTS ARE FOR WIMPS ? : WHY WATER RESOURCE

  6. The Preservation of Physical Fashion Forecasts

    E-Print Network [OSTI]

    Kosztowny, Alexander John

    2015-01-01

    schools and their libraries, which use trend forecastingin archives and libraries would be that the trend forecastsin a library or archive, not exclusively to trend forecasts.

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

    Energy Savers [EERE]

    R&D translates into improved performance and reduced costs for energy technologies. Motivation Technological forecasts, which plot the anticipated performance and costs of...

  8. Promotional forecasting in the grocery retail business

    E-Print Network [OSTI]

    Koottatep, Pakawkul

    2006-01-01

    Predicting customer demand in the highly competitive grocery retail business has become extremely difficult, especially for promotional items. The difficulty in promotional forecasting has resulted from numerous internal ...

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

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

    that take place in complex terrain, this funding opportunity will improve foundational weather models by developing short-term wind forecasts for use by industry professionals,...

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

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

    processes that take place in complex terrain, this funding would improve foundational weather models by developing short-term wind forecasts for use by industry professionals,...

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

    E-Print Network [OSTI]

    to the electricity price forecast. This resource mix is used to forecast the fuel consumption and carbon dioxide (CO2Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price forecast of the Fifth Northwest Power Plan. This forecast is an estimate of the future price of electricity

  12. 1Bureau of Meteorology | Water Information > INFORMATION SHEET 6 > Flood Forecasting and Warning Services Flood Forecasting

    E-Print Network [OSTI]

    Greenslade, Diana

    SHEET 6 1Bureau of Meteorology | Water Information > INFORMATION SHEET 6 > Flood Forecasting and Warning Services Flood Forecasting and Warning Services The Bureau of Meteorology (the Bureau) is responsible for providing an effective flood forecasting and warning service in each Australian state

  13. From Question Answering to Visual Exploration

    SciTech Connect (OSTI)

    McColgin, Dave W.; Gregory, Michelle L.; Hetzler, Elizabeth G.; Turner, Alan E.

    2006-08-11

    Research in Question Answering has focused on the quality of information retrieval or extraction using the metrics of precision and recall to judge success; these metrics drive toward finding the specific best answer(s) and are best supportive of a lookup type of search. These do not address the opportunity that users? natural language questions present for exploratory interactions. In this paper, we present an integrated Question Answering environment that combines a visual analytics tool for unstructured text and a state-of-the-art query expansion tool designed to compliment the cognitive processes associated with an information analysts work flow. Analysts are seldom looking for factoid answers to simple questions; their information needs are much more complex in that they may be interested in patterns of answers over time, conflicting information, and even related non-answer data may be critical to learning about a problem or reaching prudent conclusions. In our visual analytics tool, questions result in a comprehensive answer space that allows users to explore the variety within the answers and spot related information in the rest of the data. The exploratory nature of the dialog between the user and this system requires tailored evaluation methods that better address the evolving user goals and counter cognitive biases inherent to exploratory search tasks.

  14. 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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines lightGeospatial ToolkitSMARTS -BeingFuture forForecasting NREL researchers

  15. 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 QA:QA J-E-1 SECTION J APPENDIX E LISTStar2-0057-EA Jump to:ofEnia SpAFlex Fuels Energy JumpVyncke Jump to:Forecast

  16. 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

  17. Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting

    E-Print Network [OSTI]

    Plale, Beth

    Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting Nithya N. Vijayakumar {rramachandran, xli}@itsc.uah.edu Abstract-- Mesoscale meteorology forecasting as a data driven application Triggers, Data Mining, Stream Processing, Meteorology Forecasting I. INTRODUCTION Mesoscale meteorologists

  18. Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts

    E-Print Network [OSTI]

    Raftery, Adrian

    Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts VERONICA ensembles that generates calibrated probabilistic forecast products for weather quantities at indi- vidual perturbation (GOP) method, and extends BMA to generate calibrated probabilistic forecasts of whole weather

  19. 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

  20. INTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev

    E-Print Network [OSTI]

    , discourse and semantic. They are based on a conceptual model underlying weather forecasts as well situations represented in the form of texts in NL, weather maps, data tables or combined information objectsINTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev I n s t i t u t e of Mathematics Acad

  1. Smooth Calibration, Leaky Forecasts, and Finite Recall

    E-Print Network [OSTI]

    Hart, Sergiu

    Smooth Calibration, Leaky Forecasts, and Finite Recall Sergiu Hart October 2015 SERGIU HART c 2015 ­ p. #12;Smooth Calibration, Leaky Forecasts, and Finite Recall Sergiu Hart Center for the Study of Rationality Dept of Mathematics Dept of Economics The Hebrew University of Jerusalem hart@huji.ac.il http://www.ma.huji.ac.il/hart

  2. Multivariate Time Series Forecasting in Incomplete Environments

    E-Print Network [OSTI]

    Roberts, Stephen

    Multivariate Time Series Forecasting in Incomplete Environments Technical Report PARG 08-03 Seung of Oxford December 2008 #12;Seung Min Lee and Stephen J. Roberts Technical Report PARG 08-03 Multivariate missing observations and forecasting future values in incomplete multivariate time series data. We study

  3. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary PDF of the author, Guangzhou 510301, China9 2. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological10, China20 21 22 23 24 Submitted to Weather and Forecasting25 2014. 12. 2826 27 Corresponding author: Dr

  4. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Johnson, Richard H.

    Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary PDF of the author Fort Collins, Colorado7 October 20128 (submitted to Weather and Forecasting)9 1 Corresponding author address: Rebecca D. Adams-Selin, HQ Air Force Weather Agency 16th Weather Squadron, 101 Nelson Dr., Offutt

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

    Office of Environmental Management (EM)

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

  6. LED Frequently Asked Questions | Department of Energy

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

    Frequently Asked Questions LED Frequently Asked Questions EERE Solid-State Lighting LED Factsheet ledbasics.pdf More Documents & Publications LED Frequently Asked Questions SSL...

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

    SciTech Connect (OSTI)

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

    2012-08-01

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

  8. Algorithms for bispectra: forecasting, optimal analysis, and simulation

    E-Print Network [OSTI]

    Kendrick M. Smith; Matias Zaldarriaga

    2011-11-08

    We propose a factorizability ansatz for angular bispectra which permits fast algorithms for forecasting, analysis, and simulation, yet is general enough to encompass many interesting CMB bispectra. We describe a suite of general algorithms which apply to any bispectrum which can be represented in factorizable form. First, we present algorithms for Fisher matrix forecasts and the related problem of optimizing the factorizable representation, giving a Fisher forecast for Planck as an example. We show that the CMB can give independent constraints on the amplitude of primordial bispectra of both local and equilateral shape as well as those created by secondary anisotropies. We also show that the ISW-lensing bispectrum should be detected by Planck and could bias estimates of the local type of non-Gaussianity if not properly accounted for. Second, we implement a bispectrum estimator which is fully optimal in the presence of sky cuts and inhomogeneous noise, extends the generality of fast estimators which have been limited to a few specific forms of the bispectrum, and improves the running time of existing implementations by several orders of magnitude. Third, we give an algorithm for simulating random, weakly non-Gaussian maps with prescribed power spectrum and factorizable bispectrum.

  9. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

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

    2015-01-01

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

  10. Earthquake Forecast via Neutrino Tomography

    E-Print Network [OSTI]

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

    2011-03-29

    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 \

  11. Forecasting Random Walks Under Drift Instability

    E-Print Network [OSTI]

    Pesaran, M Hashem; Pick, Andreas

    will yield a biased forecast but will continue to have the least variance. On the other hand a forecast based on the sub-sample {yTi , yTi+1, . . . , yT }, where Ti > 1 is likely to have a lower bias but could be inefficient due to a higher variance... approach considered in Pesaran and Timmermann (2007) is to use different sub-windows to forecast and then average the outcomes, either by means of cross-validated weights or by simply using equal weights. To this end consider the sample {yTi , yTi+1...

  12. 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)

    1993-08-01

    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.

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  14. Wind-Wave Probabilistic Forecasting based on Ensemble

    E-Print Network [OSTI]

    Wind-Wave Probabilistic Forecasting based on Ensemble Predictions Maxime FORTIN Kongens Lyngby 2012.imm.dtu.dk IMM-PhD-2012-86 #12;Summary Wind and wave forecasts are of a crucial importance for a number weather forecasts and do not take any possible correlation into ac- count. Since wind and wave forecasts

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  16. 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 networks, Neural networks, Modeling, Forecasting, Energy demand, Time series forecasting, Power system demand time series based only on data for six years to forecast the demand for the seventh year. Both

  17. AVLIS: a technical and economic forecast

    SciTech Connect (OSTI)

    Davis, J.I.; Spaeth, M.L.

    1986-01-01

    The AVLIS process has intrinsically large isotopic selectivity and hence high separative capacity per module. The critical components essential to achieving the high production rates represent a small fraction (approx.10%) of the total capital cost of a production facility, and the reference production designs are based on frequent replacement of these components. The specifications for replacement frequencies in a plant are conservative with respect to our expectations; it is reasonable to expect that, as the plant is operated, the specifications will be exceeded and production costs will continue to fall. Major improvements in separator production rates and laser system efficiencies (approx.power) are expected to occur as a natural evolution in component improvements. With respect to the reference design, such improvements have only marginal economic value, but given the exigencies of moving from engineering demonstration to production operations, we continue to pursue these improvements in order to offset any unforeseen cost increases. Thus, our technical and economic forecasts for the AVLIS process remain very positive. The near-term challenge is to obtain stable funding and a commitment to bring the process to full production conditions within the next five years. If the funding and commitment are not maintained, the team will disperse and the know-how will be lost before it can be translated into production operations. The motivation to preserve the option for low-cost AVLIS SWU production is integrally tied to the motivation to maintain a competitive nuclear option. The US industry can certainly survive without AVLIS, but our tradition as technology leader in the industry will certainly be lost.

  18. Final RFP - Questions and Answers

    National Nuclear Security Administration (NNSA)

    amended to incorporate this information. 5. Question: In reference to Section L NNS-L-2000 Instructions for Proposal Preparation - General (b)(9) (p. L-11) and Section L...

  19. Mathematics: A Tool for Questioning

    E-Print Network [OSTI]

    Ghoussoub, Nassif

    . Mathematics (Greek for "learning") should be cultivated as a tool for sys- tematic questioning, our primary of army would comprise one percent of the male population. If their life expectancy was 50 years, how long

  20. Draft RFP - Questions and Answers

    National Nuclear Security Administration (NNSA)

    DE-SOL-0005982 175. Question: Attachment 1, Performance Work Statement: For UGTA drilling activities, there is no mention of whether the contractor of or the M&O...

  1. 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

  2. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand Bill Junker Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS

  3. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P

  4. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    /demographic growth, relatively low electricity and natural gas rates, and relatively low efficiency program CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity Manager Bill Junker Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY

  5. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    incorporates relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P. Oglesby Executive

  6. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    high economic/demographic growth, relatively low electricity and natural gas rates, and relatively low CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION

  7. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    incorporates relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P

  8. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand Gough Office Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS

  9. Text-Alternative Version LED Lighting Forecast

    Broader source: Energy.gov [DOE]

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

  10. Load Forecast For use in Resource Adequacy

    E-Print Network [OSTI]

    forecast of 4) Calculate Hourly Load Allocation Factor s for each day for 2019 For use in RA analysis as a function ofthe load for electricity in the region as a function of cyclical, weather and economic variables

  11. Wind Speed Forecasting for Power System Operation 

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22

    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...

  12. Testing Competing High-Resolution Precipitation Forecasts

    E-Print Network [OSTI]

    Gilleland, Eric

    Testing Competing High-Resolution Precipitation Forecasts Eric Gilleland Research Prediction Comparison Test D1 D2 D = D1 ­ D2 copyright NCAR 2013 Loss Differential Field #12;Spatial Prediction Comparison Test Introduced by Hering and Genton

  13. New product forecasting in volatile markets

    E-Print Network [OSTI]

    Baldwin, Alexander (Alexander Lee)

    2014-01-01

    Forecasting demand for limited-life cycle products is essentially projecting an arc trend of demand growth and decline over a relatively short time horizon. When planning for a new limited-life product, many marketing and ...

  14. Potential Economic Value of Seasonal Hurricane Forecasts

    E-Print Network [OSTI]

    Emanuel, Kerry Andrew

    This paper explores the potential utility of seasonal Atlantic hurricane forecasts to a hypothetical property insurance firm whose insured properties are broadly distributed along the U.S. Gulf and East Coasts. Using a ...

  15. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  16. Some open questions in hydrodynamics

    E-Print Network [OSTI]

    Mateusz Dyndal; Laurent Schoeffel

    2014-12-16

    When speaking of unsolved problems in physics, this is surprising at first glance to discuss the case of fluid mechanics. However, there are many deep open questions that come with the theory of fluid mechanics. In this paper, we discuss some of them that we classify in two categories, the long term behavior of solutions of equations of hydrodynamics and the definition of initial (boundary) conditions. The first set of questions come with the non-relativistic theory based on the Navier-Stokes equations. Starting from smooth initial conditions, the purpose is to understand if solutions of Navier-Stokes equations remain smooth with the time evolution. Existence for just a finite time would imply the evolution of finite time singularities, which would have a major influence on the development of turbulent phenomena. The second set of questions come with the relativistic theory of hydrodynamics. There is an accumulating evidence that this theory may be relevant for the description of the medium created in high energy heavy-ion collisions. However, this is not clear that the fundamental hypotheses of hydrodynamics are valid in this context. Also, the determination of initial conditions remains questionable. The purpose of this paper is to explore some ideas related to these questions, both in the non-relativistic and relativistic limits of fluid mechanics. We believe that these ideas do not concern only the theory side but can also be useful for interpreting results from experimental measurements.

  17. Intra-hour Direct Normal Irradiance solar forecasting using genetic programming

    E-Print Network [OSTI]

    Queener, Benjamin Daniel

    2012-01-01

    guideline for Solar Power Forecasting Performance . . 46 viof forecasting techniques for solar power production with noand A. Pavlovski, “Solar power forecasting performance

  18. A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of the WRF model solar irradiance forecasts in Andalusia (Beyer, H. , 2009.    Irradiance forecasting for the power dependent probabilistic irradiance  forecasts for coastal 

  19. Mathematics Of Ice To Aid Global Warming Forecasts Mathematics Of Ice To Aid Global Warming Forecasts

    E-Print Network [OSTI]

    Golden, Kenneth M.

    Mathematics Of Ice To Aid Global Warming Forecasts Mathematics Of Ice To Aid Global Warming forecasts of how global warming will affect polar icepacks. See also: Earth & Climate q Global Warming q the effects of climate warming, and its presence greatly reduces solar heating of the polar oceans." "Sea ice

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

    SciTech Connect (OSTI)

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

    2014-05-01

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

  1. Forecasting Prices andForecasting Prices and Congestion forCongestion for

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    Goal: Design nodal price and grid congestion forecasting tools for market operators and market Traders To facilitate scenario-conditioned planning Price forecasting for Market Participants (MPs) To manage short for portfolio management by power market participants Conclusion #12;Project OverviewProject Overview Project

  2. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

    Templeton, K.J.; Clary, J.L.

    1994-09-01

    This report describes a 30-year forecast of the solid waste volumes by container type. The volumes described are low-level mixed waste (LLMW) and transuranic/transuranic mixed (TRU/TRUM) waste. These volumes and their associated container types will be generated or received at the US Department of Energy Hanford Site for storage, treatment, and disposal at Westinghouse Hanford Company`s Solid Waste Operations Complex (SWOC) during a 30-year period from FY 1994 through FY 2023. The forecast data for the 30-year period indicates that approximately 307,150 m{sup 3} of LLMW and TRU/TRUM waste will be managed by the SWOC. The main container type for this waste is 55-gallon drums, which will be used to ship 36% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of 55-gallon drums is Past Practice Remediation. This waste will be generated by the Environmental Restoration Program during remediation of Hanford`s past practice sites. Although Past Practice Remediation is the primary generator of 55-gallon drums, most waste generators are planning to ship some percentage of their waste in 55-gallon drums. Long-length equipment containers (LECs) are forecasted to contain 32% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of LECs is the Long-Length Equipment waste generator, which is responsible for retrieving contaminated long-length equipment from the tank farms. Boxes are forecasted to contain 21% of the waste. These containers are primarily forecasted for use by the Environmental Restoration Operations--D&D of Surplus Facilities waste generator. This waste generator is responsible for the solid waste generated during decontamination and decommissioning (D&D) of the facilities currently on the Surplus Facilities Program Plan. The remaining LLMW and TRU/TRUM waste volume is planned to be shipped in casks and other miscellaneous containers.

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

    SciTech Connect (OSTI)

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

    2015-01-01

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

  4. QUESTIONS & ANSWERS ABOUT LUNG CANCER

    E-Print Network [OSTI]

    QUESTIONS & ANSWERS ABOUT LUNG CANCER Q: What are the early signs of lung cancer? How would I know I have it? A: Some of the early warning signs of lung cancer are: · A cough that doesn't go away what may be causing these symptoms. Q: How is lung cancer diagnosed? A: Your doctor may do one or more

  5. 10 CFR 707 Frequently Asked Questions

    Broader source: Energy.gov [DOE]

    NOTE: The Questions on this site were compiled from questions asked during the four DOE complex wide tele-videos, as well as, questions submitted by e-mail and telephone. The answers provided are...

  6. Appendix C: Examples of review questions

    SciTech Connect (OSTI)

    None, None

    2009-01-18

    This set of review questions was pulled from a number of EERE evaluations by the PEER Review Task Force and organized to show how questions for assessing a program differ from questions for assessing projects that make up that program.

  7. Traffic congestion forecasting model for the INFORM System. Final report

    SciTech Connect (OSTI)

    Azarm, A.; Mughabghab, S.; Stock, D.

    1995-05-01

    This report describes a computerized traffic forecasting model, developed by Brookhaven National Laboratory (BNL) for a portion of the Long Island INFORM Traffic Corridor. The model has gone through a testing phase, and currently is able to make accurate traffic predictions up to one hour forward in time. The model will eventually take on-line traffic data from the INFORM system roadway sensors and make projections as to future traffic patterns, thus allowing operators at the New York State Department of Transportation (D.O.T.) INFORM Traffic Management Center to more optimally manage traffic. It can also form the basis of a travel information system. The BNL computer model developed for this project is called ATOP for Advanced Traffic Occupancy Prediction. The various modules of the ATOP computer code are currently written in Fortran and run on PC computers (pentium machine) faster than real time for the section of the INFORM corridor under study. The following summarizes the various routines currently contained in the ATOP code: Statistical forecasting of traffic flow and occupancy using historical data for similar days and time (long term knowledge), and the recent information from the past hour (short term knowledge). Estimation of the empirical relationships between traffic flow and occupancy using long and short term information. Mechanistic interpolation using macroscopic traffic models and based on the traffic flow and occupancy forecasted (item-1), and the empirical relationships (item-2) for the specific highway configuration at the time of simulation (construction, lane closure, etc.). Statistical routine for detection and classification of anomalies and their impact on the highway capacity which are fed back to previous items.

  8. Frequently Asked Questions - HPMC Occupational Health Services

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

    Font Size Quick Links: General Questions and Scheduling Two-Encounter Exam Process Health and Wellness Services Behavioral Health Services General Questions and Scheduling Is...

  9. Frequently Asked Questions | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    Operations Management and Budget Human Resources Pay-banding Frequently Asked Questions Frequently Asked Questions General What is a demonstration project? What employees...

  10. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output Perturbation

    E-Print Network [OSTI]

    Raftery, Adrian

    Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output. This is typically not feasible for mesoscale weather prediction carried out locally by organizations without by simulating realizations of the geostatistical model. The method is applied to 48-hour mesoscale forecasts

  11. New directions for forecasting air travel passenger demand

    E-Print Network [OSTI]

    Garvett, Donald Stephen

    1974-01-01

    While few will disagree that sound forecasts are an essential prerequisite to rational transportation planning and analysis, the making of these forecasts has become a complex problem with the broadening of the scope and ...

  12. Generalized Cost Function Based Forecasting for Periodically Measured Nonstationary Traffic

    E-Print Network [OSTI]

    Zeng, Yong - Department of Mathematics and Statistics, University of Missouri

    1 Generalized Cost Function Based Forecasting for Periodically Measured Nonstationary Traffic true value. However, such a forecast- ing function is not directly applicable for applications potentially result in insufficient allocation of bandwidth leading to short term data loss. To facilitate

  13. The effect of multinationality on management earnings forecasts 

    E-Print Network [OSTI]

    Runyan, Bruce Wayne

    2005-08-29

    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...

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

    E-Print Network [OSTI]

    Chevis, Gia Marie

    2004-11-15

    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. DOE Releases Latest Report on Energy Savings Forecast of Solid...

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

    Latest Report on Energy Savings Forecast of Solid-State Lighting DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting September 12, 2014 - 2:06pm Addthis...

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

    E-Print Network [OSTI]

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

    2005-01-01

    Forecasts Using NEMS and GIS National Climatic Data Center.with Changing Boundaries." Use of GIS to Understand Socio-Forecasts Using NEMS and GIS Appendix A. Map Results Gallery

  17. OPERATIONAL EARTHQUAKE FORECASTING State of Knowledge and Guidelines for Utilization

    E-Print Network [OSTI]

    .................................................................................................................................... 323 II. SCIENCE OF EARTHQUAKE FORECASTING AND PREDICTION 325 A. Definitions and Concepts....................................................................................................................................... 325 B. Research on Earthquake PredictabilityOPERATIONAL EARTHQUAKE FORECASTING State of Knowledge and Guidelines for Utilization Report

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

    SciTech Connect (OSTI)

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

    2010-04-01

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

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

    SciTech Connect (OSTI)

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

    2010-04-15

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

  20. Managerial Career Concerns and Earnings Forecasts SARAH SHAIKH

    E-Print Network [OSTI]

    Tipple, Brett

    's aversion to risk, I find that a CEO is less likely to issue an earnings forecast in periods of stricter non is more pronounced for a CEO who has greater concern for his reputation, faces more risk in forecasting the provision of earnings forecasts. Literature has long recognized that the labor market provides distinct

  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. Neural Network forecasts of the tropical Pacific sea surface temperatures

    E-Print Network [OSTI]

    Hsieh, William

    Neural Network forecasts of the tropical Pacific sea surface temperatures Aiming Wu, William W Tang Jet Propulsion Laboratory, Pasadena, CA, USA Neural Networks (in press) December 11, 2005 title: Forecast of sea surface temperature 1 #12;Neural Network forecasts of the tropical Pacific sea

  3. Managing Wind Power Forecast Uncertainty in Electric Brandon Keith Mauch

    E-Print Network [OSTI]

    i Managing Wind Power Forecast Uncertainty in Electric Grids Brandon Keith Mauch Co Paulina Jaramillo Doctor Paul Fischbeck 2012 #12;ii #12;iii Managing Wind Power Forecast Uncertainty generated from wind power is both variable and uncertain. Wind forecasts provide valuable information

  4. Forecasting Uncertainty Related to Ramps of Wind Power Production

    E-Print Network [OSTI]

    Boyer, Edmond

    Forecasting 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. This paper presents two methods focusing on forecasting large and sharp variations in power output of a wind

  5. SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS

    E-Print Network [OSTI]

    Heinemann, Detlev

    SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS Detlev Heinemann Oldenburg in irradiance forecasting have been presented more than twenty years ago (Jensenius and Cotton, 1981), when or progress with respect to the development of solar irradiance forecasting methods. Heck and Takle (1987

  6. Choosing Words in Computer-Generated Weather Forecasts

    E-Print Network [OSTI]

    Reiter, Ehud

    to communicate numeric weather data. A corpus-based analysis of how humans write forecasts showed that there wereTime- Mousam weather-forecast generator to use consistent data-to-word rules, which avoided words which were weather forecast texts from numerical weather pre- diction data (SumTime-Mousam in fact is used

  7. Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging J. MCLEAN 2011, in final form 26 May 2012) ABSTRACT Probabilistic forecasts of wind vectors are becoming critical with univariate quantities, statistical approaches to wind vector forecasting must be based on bivariate

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

    E-Print Network [OSTI]

    Heinemann, Detlev

    Accuracy 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 #12;EMS/ECAM 2007 ­ Nadja Saleck Wind power forecast data observed wind power input (2004 ­ 2006

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

    E-Print Network [OSTI]

    Raftery, Adrian

    Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging J. Mc in the context of wind power, where under- forecasting and overforecasting carry different financial penal- ties, calibrated and sharp probabilistic forecasts can help to make wind power a more financially competitive alter

  10. Forecasting Building Occupancy Using Sensor Network James Howard

    E-Print Network [OSTI]

    Hoff, William A.

    Forecasting Building Occupancy Using Sensor Network Data James Howard Colorado School of Mines@mines.edu ABSTRACT Forecasting the occupancy of buildings can lead to signif- icant improvement of smart heating throughout a building, we perform data mining to forecast occupancy a short time (i.e., up to 60 minutes

  11. Weather Forecasting -Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting - Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, "weather forecasts" are created such that selected wireless LAN performance indicators might be used to evaluate the effec- tiveness of individual weather forecasts. The paper evaluates six distinct weather

  12. Weather Forecasting Predicting Performance for Streaming Video over Wireless LANs

    E-Print Network [OSTI]

    Claypool, Mark

    Weather Forecasting ­ Predicting Performance for Streaming Video over Wireless LANs Mingzhe Li, ``weather forecasts'' are created such that selected wireless LAN performance indicators might be used to evaluate the e#ec­ tiveness of individual weather forecasts. The paper evaluates six distinct weather

  13. 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

  14. Preprints, 15th AMS Conference on Weather Analysis and Forecasting

    E-Print Network [OSTI]

    Doswell III, Charles A.

    ) models have substantially improved forecast skill. Recent and planned changes along these lines (e to delivering two kinds of weather products. The first is a day-to-day forecast of weather elements, e by the private sector. Improvements in automated techniques for the forecasting of basic weather elements

  15. Influences of soil moisture and vegetation on convective precipitation forecasts

    E-Print Network [OSTI]

    Robock, Alan

    Influences of soil moisture and vegetation on convective precipitation forecasts over the United and vegetation on 30 h convective precipitation forecasts using the Weather Research and Forecasting model over, the complete removal of vegetation produced substantially less precipitation, while conversion to forest led

  16. Potpourri of deposition and resuspension questions

    SciTech Connect (OSTI)

    Slinn, W.G.N.

    1983-01-01

    Twenty questions and answers are listed dealing with particulate deposition, resuspension, and precipitation scavenging.

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

    of Solar 2011, American Solar Energy Society, Raleigh, NC.Description and validation. Solar Energy, 73 (5), 307-317.forecast database. Solar Energy, Perez, R. , S. Kivalov, J.

  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)

    2009-10-15

    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. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    1996-08-01

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

  20. Forecasting Hot Water Consumption in Residential Houses

    E-Print Network [OSTI]

    MacDonald, Mark

    and technological advancement in energy-intensive applications are causing fast electric energy consumption growth and consumption of electricity [8], as long as there is no significant correlation between intermittent energyArticle Forecasting Hot Water Consumption in Residential Houses Linas Gelazanskas * and Kelum A

  1. GENETIC ALGORITHM FORECASTING FOR TELECOMMUNICATIONS PRODUCTS

    E-Print Network [OSTI]

    Havlicek, Joebob

    available economic indicators such as Disposable Personal Income and New Housing Starts as independent exhibiting maximal fitness achieved RMS forecast errors below the the average two-week sales figure. 1 (Holland, 1975), (Packard, 1990), (Koza, 1992), (Bäck, et al., 1997), (Mitchell, 1998). For example, Meyer

  2. GOES Aviation Products Aviation Weather Forecasting

    E-Print Network [OSTI]

    Kuligowski, Bob

    GOES Aviation Products · The GOES aviation forecast products are based on energy measured in different characteristics #12;GOES Aviation Products Quiz · What is a geostationary satellite? · What generates energy received by the satellite in the visible band? · What generates energy received by the satellite

  3. Solar Forecasting System and Irradiance Variability Characterization

    E-Print Network [OSTI]

    solar forecasting system based on numerical weather prediction plus satellite and ground-based data.1 Photovoltaic Systems: Report 3 Development of data base allowing managed access to statewide PV and insolation Based Data 13 Summary 14 References 14 #12;List of Figures Figure Number and Title Page # 1. Topography

  4. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Reiter, Ehud

    summarisation. We found three alternative ways in which we could model data summarisation. One approach is based turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP) models is summarised as weather forecast texts. In the domain of gas turbines, sensor data from

  5. "FLIGHT PLAN" FORECASTS SEATTLE/TACOMA AND

    E-Print Network [OSTI]

    ASSESSMENT OF THE "FLIGHT PLAN" FORECASTS FOR SEATTLE/TACOMA AND REGIONAL AIRPORTS TOGETHER 1. Introduction 5 2. Airport Planning Process 7 Traditional Master Planning Application to Seattle/Tacoma. Uncertainty about Capacity 27 A Fuzzy Concept Assessment Factors Application to Seattle/Tacoma 7. Assessment

  6. Forecast Technical Document Felling and Removals

    E-Print Network [OSTI]

    of local investment and business planning. Timber volume production will be estimated at sub. Planning of operations. Control of the growing stock. Wider reporting (under UKWAS). The calculation fellings and removals are handled in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan

  7. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27

    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. Stochastic Weather Generator Based Ensemble Streamflow Forecasting

    E-Print Network [OSTI]

    Stochastic Weather Generator Based Ensemble Streamflow Forecasting by Nina Marie Caraway B of Civil Engineering 2012 #12;This thesis entitled: Stochastic Weather Generator Based Ensemble Streamflow mentioned discipline. #12;iii Caraway, Nina Marie (M.S., Civil Engineering) Stochastic Weather Generator

  9. Inquiring Minds - Questions About Physics

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACT EVALUATION PLANIs gravity a particle or aHow doQuestion: Do you think

  10. Inquiring Minds - Questions About Physics

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACT EVALUATION PLANIs gravity a particle or aHow doQuestion: Do you

  11. Inquiring Minds - Questions About Physics

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACT EVALUATION PLANIs gravity a particle or aHow doQuestion: Do youVirtual

  12. Inquiring Minds - Questions About Physics

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACT EVALUATION PLANIs gravity a particle or aHow doQuestion: Do

  13. Inquiring Minds - Questions About Physics

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACT EVALUATION PLANIs gravity a particle or aHow doQuestion: DoWave

  14. Inquiring Minds - Questions About Physics

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACT EVALUATION PLANIs gravity a particle or aHow doQuestion: DoWaveCan an

  15. Inquiring Minds - Questions About Physics

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACT EVALUATION PLANIs gravity a particle or aHow doQuestion: DoWaveCan

  16. Inquiring Minds - Questions About Physics

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACT EVALUATION PLANIs gravity a particle or aHow doQuestion: DoWaveCanYou

  17. Inquiring Minds - Questions About Physics

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACT EVALUATION PLANIs gravity a particle or aHow doQuestion:

  18. State DOT Representative Report Questions National Concrete Consortium

    E-Print Network [OSTI]

    , Texas April 2, 2009 Theme: Ride Quality for Bridges Please provide your state DOT's perspective regarding the following theme questions. Each NCC state DOT representative will be asked to present requirements set forth in the Caltrans Standard Specification 51-1.17 and which are tested for conformance

  19. A 110-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe Floods of 200307*

    E-Print Network [OSTI]

    Webster, Peter J.

    A 1­10-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe of the Brahmaputra and Ganges Rivers as they flow into Bangladesh; it has been operational since 2003. The Bangladesh points of the Ganges and Brahmaputra into Bangladesh. Forecasts with 1­10-day horizons are presented

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

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

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01

    This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

  2. Combinatorial Evolution and Forecasting of Communication Protocol ZigBee

    E-Print Network [OSTI]

    Levin, Mark Sh; Kistler, Rolf; Klapproth, Alexander

    2012-01-01

    The article addresses combinatorial evolution and forecasting of communication protocol for wireless sensor networks (ZigBee). Morphological tree structure (a version of and-or tree) is used as a hierarchical model for the protocol. Three generations of ZigBee protocol are examined. A set of protocol change operations is generated and described. The change operations are used as items for forecasting based on combinatorial problems (e.g., clustering, knapsack problem, multiple choice knapsack problem). Two kinds of preliminary forecasts for the examined communication protocol are considered: (i) direct expert (expert judgment) based forecast, (ii) computation of the forecast(s) (usage of multicriteria decision making and combinatorial optimization problems). Finally, aggregation of the obtained preliminary forecasts is considered (two aggregation strategies are used).

  3. Contributions from a Local Ensemble Prediction System (LEPS) for Improving Fog and Low Cloud Forecasts at Airports

    E-Print Network [OSTI]

    Contributions from a Local Ensemble Prediction System (LEPS) for Improving Fog and Low Cloud authorities with accurate forecasts of fog and cloud ceiling. A specific event, which is called a low with the prediction of infrequent events like fog and the life cycles of low clouds. At Paris' Charles de Gaulle (Cd

  4. LANL JOWOG 31 2012 Forecast

    SciTech Connect (OSTI)

    Vidlak, Anton J. II [Los Alamos National Laboratory

    2012-08-08

    Joint Working Group (JOWOG) 31, Nuclear Weapons Engineering, has a particularly broad scope of activities within its charter which emphasizes systems engineering. JOWOG 31 brings together experts from AWE and the national laboratories to address engineering issues associated with warhead design and certification. Some of the key areas of interaction, as addressed by the HOCWOGs are: (1) Engineering Analysis, (2) Hydrodynamic Testing, (3) Environmental Testing, and (4) Model Based Integrated Toolkit (MBIT). Gas Transfer Systems and Condition Monitoring interaction has been moved back to JOWOG 31. The regularly scheduled JOWOG 31 activities are the General Sessions, Executive Sessions, Focused Exchanges and HOCWOGs. General Sessions are scheduled every 12-18 months and are supported by the four design laboratories (AWE, LANL, LLNL, and SNL). Beneficial in educating the next generation of weapons engineers and establishing contacts between AWE and the US laboratory personnel. General Sessions are based on a blend of presentations and workshops centered on various themed subjects directly related to Stockpile Stewardship. HOCWOG meetings are more narrowly focused than the General Sessions. They feature presentations by experts in the field with a greater emphasis on round table discussions. Typically about 20 people attend. Focused exchanges are generally the result of interactions within JOWOG general sessions or HOCWOG meetings. They generally span a very specific topic of current interest within the US and UK.

  5. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

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

    2014-12-30

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

  6. Two techniques for forecasting clear air turbulence 

    E-Print Network [OSTI]

    Arbeiter, Randolph George

    1977-01-01

    result in only mild annoyance or discomfort (air sickness) to crew and passengers. As it becomes moderate, difficulty may be experienced in moving about inside the airplane and the crew may momentarily lose control. Severe CAT can result in injury... successfully used by the Air Force Clobal Heather Central (Barnett, 1970) for oper" tional forecasting on a day-to-day basis. Furthermore, its usefulness 1' or supersonic aircraft in the stratosphere v;as successfully demonstrated by Scoggins et H. (1975...

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

    SciTech Connect (OSTI)

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

    2015-08-05

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

  8. Solar Wind Forecasting with Coronal Holes

    E-Print Network [OSTI]

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

    2007-01-09

    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.

  9. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

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

    2011-02-23

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  11. The Commission Forecast 1992 Report: Important Resource Planning Issues 

    E-Print Network [OSTI]

    Adib, P.

    1992-01-01

    FORECAST 1992 REPORT: IMPORTANT RESOURCE PLANNING ISSUES PARVIZ ADIB MANAGER, ECONOMIC ANALYSIS SECTION ELECTRIC DIVISION PUBLIC UTILITY COMMISSION OF TEXAS ABSTRACT There is a general agreement among experts in the electric utility industry... there are many important issues in the preparation of a utility's electric resource plan, the Commission staff will address a few important ones in the next Commission Forecast Report (Forecast '92). In particular, the Commission staff will insure...

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

  13. The Rationality of EIA Forecasts under Symmetric and Asymmetric Loss

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01

    function. The forecasts of oil, coal and gas prices as wellforecasts for natural gas consumption, electricity sales, coal and electricity prices,

  14. Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures

    E-Print Network [OSTI]

    Richard A. Berk; Brian Kriegler; Jong-Ho Baek

    2011-01-01

    Forecasting Dangerous Inmate Misconduct: An Applications ofof Term Length more dangerous than other inmates servingIV beds or moving less dangerous Level IV inmates to Level

  15. Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures

    E-Print Network [OSTI]

    Berk, Richard; Kriegler, Brian; Baek, Jong-Ho

    2005-01-01

    Forecasting Dangerous Inmate Misconduct: An Applications ofof Term Length more dangerous than other inmates servingIV beds or moving less dangerous Level IV inmates to Level

  16. Electric Grid - Forecasting system licensed | ornl.gov

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

    Electric Grid - Forecasting system licensed Location Based Technologies has signed an agreement to integrate and market an Oak Ridge National Laboratory technology that provides...

  17. Ramping Effect on Forecast Use: Integrated Ramping (Presentation...

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

    the shift from ramping. * the benefits - better use of forecast values (load or net load) - reduce the amount of variability that the regulation reserve must accommodate...

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

    SciTech Connect (OSTI)

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

    2015-12-08

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

  19. Weather-based yield forecasts developed for 12 California crops

    E-Print Network [OSTI]

    Lobell, David; Cahill, Kimberly Nicholas; Field, Christopher

    2006-01-01

    RESEARCH ARTICLE Weather-based yield forecasts developed fordepend largely on the weather, measurements from existingpredictions. We developed weather-based models of statewide

  20. Nuclear Theory Helps Forecast Neutron Star Temperatures | U.S...

    Office of Science (SC) Website

    Nuclear Theory Helps Forecast Neutron Star Temperatures Nuclear Physics (NP) NP Home About Research Facilities Science Highlights Benefits of NP Funding Opportunities Nuclear...

  1. Frequently Asked Questions about Patient Care Costs And a Quick Guide to Patient Care Costs

    E-Print Network [OSTI]

    Janssen, Michel

    Frequently Asked Questions about Patient Care Costs And a Quick Guide to Patient Care Costs questions regarding human research patient care costs. Human research patient care costs are the costs. The costs of these services normally are assigned to specific research projects through the development

  2. EIA lowers forecast for summer gasoline prices

    Gasoline and Diesel Fuel Update (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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural GasNatural GasEIA lowers forecast for summer gasoline prices

  3. Motivation Methods Model configuration Results Forecasting Summary & Outlook Retrieving direct and diffuse radiation with the

    E-Print Network [OSTI]

    Heinemann, Detlev

    Motivation Methods Model configuration Results Forecasting Summary & Outlook 1/ 14 Retrieving. 17, 2015 #12;Motivation Methods Model configuration Results Forecasting Summary & Outlook 2/ 14 Motivation Sky Imager based shortest-term solar irradiance forecasts for local solar energy applications

  4. ECMWF analyses and forecasts of 500 mb synoptic-scale activity during wintertime blocking 

    E-Print Network [OSTI]

    Matson, David Michael

    1993-01-01

    An observational study of 500 mb atmospheric blocking is conducted based on an European Centre for Medium-Range Weather Forecasts (ECMWF) wintertime analysis and forecast dataset during dynamic extended range forecasting ...

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

    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

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

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01

    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 ...

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

    revisions to the EIA’s natural gas price forecasts in AEOon the AEO 2005 natural gas price forecasts will likely onceComparison of AEO 2005 Natural Gas Price Forecast to NYMEX

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

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

  10. HOW ACCURATE ARE WEATHER MODELS IN ASSISTING AVALANCHE FORECASTERS? M. Schirmer, B. Jamieson

    E-Print Network [OSTI]

    Jamieson, Bruce

    HOW ACCURATE ARE WEATHER MODELS IN ASSISTING AVALANCHE FORECASTERS? M. Schirmer, B. Jamieson and decision makers strongly rely on Numerical Weather Prediction (NWP) models, for example on the forecasted on forecasted precipitation. KEYWORDS: Numerical weather prediction models, validation, precipitation 1

  11. Program Evaluation Topics and Questions Library

    Broader source: Energy.gov [DOE]

    Menu of initial questions for a program administrator to use in developing a real-time evaluation survey to collect qualitative data from program contractors.

  12. Frequently Asked Questions | Environmental Management Science...

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

    Frequently Asked Questions About the Oak Ridge Environmental Management Science Education and Internship Program 1. What kind of program is the OREM Science Education and...

  13. UPF Forecast | Y-12 National Security Complex

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

    Keep in mind that these requirements may be revised or cancelled, depending on program budget funding or departmental needs. If you have questions or would like to express an...

  14. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01

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

  15. 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

  16. Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence

    E-Print Network [OSTI]

    Lawrence, Ramon

    Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence Department of Computer Science on the application of neural networks in forecasting stock market prices. With their ability to discover patterns in nonlinear and chaotic systems, neural networks offer the ability to predict market directions more

  17. Forecasting Hot Water Consumption in Dwellings Using Artifitial Neural Networks

    E-Print Network [OSTI]

    MacDonald, Mark

    electricity consumption in time. This paper investigates the ability on Artificial Neural Networks to predict shift electric energy. Keywords--Hot Water Consumption; Forecasting; Artifitial Neural Networks; SmartForecasting Hot Water Consumption in Dwellings Using Artifitial Neural Networks Linas Gelazanskas

  18. Draft for Public Comment Appendix A. Demand Forecast

    E-Print Network [OSTI]

    in the forecast of electricity consumption for those years has been less than one half of a percent. Figure A-1 forecast of electricity demand is a required component of the Council's Northwest Regional Conservation and Electric Power Plan.1 Understanding growth in electricity demand is, of course, crucial to determining

  19. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    of transportation fuel and crude oil import requirements. The transportation energy demand forecasts make. The transportation fuel and crude oil import requirement assessments build on assumptions about California crude oil forecasts, transportation energy, gasoline, diesel, jet fuel, crude oil production, fuel imports, crude oil

  20. A Deep Hybrid Model for Weather Forecasting Aditya Grover

    E-Print Network [OSTI]

    Horvitz, Eric

    @microsoft.com ABSTRACT Weather forecasting is a canonical predictive challenge that has depended primarily on model-based methods. We ex- plore new directions with forecasting weather as a data- intensive challenge that involves the joint statistics of a set of weather-related vari- ables. We show how the base model can be enhanced

  1. Hydrological Forecasting Improvements Primary Investigator: Thomas Croley -NOAA GLERL (Emeritus)

    E-Print Network [OSTI]

    multiple data streams in a near-real-time manner and incorporate them into the AHPS data base, run for matching weather forecasts with historical data, and prepare extensive forecasts of hydrology probabilities maximum use of all available information and be based on efficient and true hydrological process models

  2. DEEP COMPREHENSION, GENERATION AND TRANSLATION OF WEATHER FORECASTS (WEATHRA)

    E-Print Network [OSTI]

    in a data base and graphic representation with tile standard meteorological icons on a map, e.g. iconsDEEP COMPREHENSION, GENERATION AND TRANSLATION OF WEATHER FORECASTS (WEATHRA) by BENGT SIGURD, Sweden E-mail: linglund@gemini.ldc.lu.se FAX:46-(0)46 104210 Introduction and abstract Weather forecasts

  3. Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    markets could aid in the design of appropriate price forecasting tools for such markets. Scenario1 Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets Qun Zhou, restructured wholesale power markets, scenario generation, ARMA model, moment-matching method I. INTRODUCTION

  4. Probabilistic forecasting of solar flares from vector magnetogram data

    E-Print Network [OSTI]

    Barnes, Graham

    Probabilistic forecasting of solar flares from vector magnetogram data G. Barnes,1 K. D. Leka,1 E to solar flare forecasting, adapted to provide the probability that a measurement belongs to either group, the groups in this case being solar active regions which produced a flare within 24 hours and those

  5. Viability, Development, and Reliability Assessment of Coupled Coastal Forecasting Systems 

    E-Print Network [OSTI]

    Singhal, Gaurav

    2012-10-19

    Real-time wave forecasts are critical to a variety of coastal and offshore opera- tions. NOAA’s global wave forecasts, at present, do not extend into many coastal regions of interest. Even after more than two decades of the historical Exxon Valdez...

  6. Human Trajectory Forecasting In Indoor Environments Using Geometric Context

    E-Print Network [OSTI]

    . In addressing this problem, we have built a model to estimate the occupancy behavior of humans based enhancement in the accuracy of trajectory forecasting by incorporating the occupancy behavior model. Keywords Trajectory forecasting, human occupancy behavior, 3D ge- ometric context 1. INTRODUCTION Given a human

  7. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    . Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data Office. Andrea Gough ran the summary energy model and supervised data preparation. Glen Sharp prepared models. Both the staff revised energy consumption and peak forecasts are slightly higher than

  8. 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

  9. MAINTENANCE, UPGRADE AND VERIFICATION OF OPERATIONAL FORECASTS OF

    E-Print Network [OSTI]

    MAINTENANCE, UPGRADE AND VERIFICATION OF OPERATIONAL FORECASTS OF CLOUD COVER AND WATER VAPOUR Purchase Order 58311/ODG/99/8362/GWI/LET #12;i PREFACE Starting in August 1998, operational forecasts satellite imagery from the Co-operative Institute for Research in the Atmosphere (CIRA) and upper

  10. Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids

    E-Print Network [OSTI]

    Hwang, Kai

    1 Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids Yogesh Simmhan. One of the characteristic applications of Smart Grids is demand response optimization (DR). The goal of DR is to use the power consumption time series data to reliable forecast the future consumption

  11. THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD

    E-Print Network [OSTI]

    THE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD ENERGY SERVICES by Steven Groves BASc of Research Project: The Desire to Acquire: Forecasting the Evolution of Household Energy Services Report No, and gasoline. A fixed effects panel model was used to examine the relationship of demand for energy

  12. Classification of Commodity Price Forecast With Random Forests and Bayesian

    E-Print Network [OSTI]

    Freitas, Nando de

    on the sentiment of price39 forecasts and reports for commodities such as gold, natural gas or most commonly oil or natural gas can impact everything from the21 critical business decisions made within nationsClassification of Commodity Price Forecast Sentiment With Random Forests and Bayesian Optimization

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

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

  14. A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

    of numerical weather prediction solar irradiance forecasts numerical weather prediction model for solar irradiance weather prediction for intra?day solar  forecasting in the 

  15. Building Electricity Load Forecasting via Stacking Ensemble Learning Method with Moving Horizon Optimization

    E-Print Network [OSTI]

    Burger, Eric M.; Moura, Scott J.

    2015-01-01

    K. W. Yau, “Predicting electricity energy con- sumption: Afor building-level electricity load forecasts,” Energy andannealing algorithms in electricity load forecasting,”

  16. Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts ............................................................................................................................ 5 U.S. Natural Gas Commodity Prices

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

    SciTech Connect (OSTI)

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

    2014-10-27

    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 “quasi-deterministic” components of forecast errors. This helps improve forecasts produced by other means, e.g., using weather-based models, and reduce forecast errors prediction intervals.

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01

    Comparison of AEO 2009 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01

    Comparison of AEO 2008 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01

    Comparison of AEO 2006 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

    Comparison of AEO 2007 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

  2. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    to  predict daily solar radiation.   Agriculture and Forest and Chuo, S.   2008.  Solar radiation forecasting using Short?term forecasting of solar radiation:   A statistical 

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

    SciTech Connect (OSTI)

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

    2012-07-01

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

  4. Your Unanswered Questions…. Answered- Batch 2

    Broader source: Energy.gov [DOE]

    Secretary Chu hosted an online town hall to discuss President Obama's clean energy innovation agenda -- and while he was able to answer about 10 questions submitted online during the event, we received more than 200! Here is our second batch of questions and answers.

  5. Questions and Answers about National Environmental Policy Act...

    Office of Environmental Management (EM)

    Questions and Answers about National Environmental Policy Act (NEPA) Compliance Questions and Answers about National Environmental Policy Act (NEPA) Compliance Questions and...

  6. Natural Gas from Shale: Questions and Answers | Department of...

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

    Natural Gas from Shale: Questions and Answers Natural Gas from Shale: Questions and Answers Natural Gas from Shale: Questions and Answers More Documents & Publications Shale Gas...

  7. Questions and Answers for the Smart Grid Investment Grant Program...

    Energy Savers [EERE]

    Questions and Answers for the Smart Grid Investment Grant Program: Frequently Asked Questions Questions and Answers for the Smart Grid Investment Grant Program: Frequently Asked...

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

    Reports and Publications (EIA)

    2010-01-01

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

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  10. DOT specification packages evaluation

    SciTech Connect (OSTI)

    Ratledge, J.E.; Rawl, R.R. )

    1991-01-01

    During the late 1960s and early 1970s, the Department of Transportation (DOT) specification package system was implemented to serve as a useful and equivalent alternative to the Nuclear Regulatory Commission (NRC) and the Bureau of Explosives approval systems for Type B and fissile radioactive material package designs. When a package design was used by a large number of organizations, the package design was added to the DOT regulations as a specification package authorized for use by any shipper. In the mid-1970s, the NRC revised its package design certification system to the one in use today. This paper reports that, while the NRC and DOT transportation regulations have evolved over the years, the DOT specification package designs have remained largely unchanged. Questions have been raised as to whether these designs meet the current and proposed regulations. In order to enable the NRC and DOT to develop a regulatory analysis that will support appropriate action regarding the specification packages, a study is being performed to compile all available design, testing, and analysis information on these packages.

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

    SciTech Connect (OSTI)

    McNamara, Laura A.

    2010-08-01

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

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

    SciTech Connect (OSTI)

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J. (Decision and Information Sciences); (INESC Porto)

    2011-12-06

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

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

    SciTech Connect (OSTI)

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

    2005-07-01

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

  14. Science and Engineering of an Operational Tsunami Forecasting System

    SciTech Connect (OSTI)

    Gonzalez, Frank

    2009-04-06

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

  15. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

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

  16. Frequently Asked Questions About the Higgs Boson

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

    Questions About the Higgs Boson What is a Higgs field? What is a Higgs boson? The Higgs field is like a giant vat of molasses spread throughout the universe. Most of the known...

  17. Solar Instructor Training Network Frequently Asked Questions

    Broader source: Energy.gov [DOE]

    These frequently asked questions (FAQs) relate to the solar instructor training network. This project was launched by the U.S. Department of Energy (DOE) Solar Energy Technologies Program (SETP or...

  18. Questions about Groundwater Conservation Districts in Texas 

    E-Print Network [OSTI]

    Lesikar, Bruce J.; Silvy, Valeen

    2008-09-22

    Groundwater conservation districts (GCDs) are being created in many parts of Texas to allow local citizens to manage and protect their groundwater. This publication answers frequently asked questions about groundwater and GCDs....

  19. Response to Questions on Presentation to NAS

    SciTech Connect (OSTI)

    Meier, W R

    2011-03-17

    Response to questions on the presentation 'Overview to Chamber and Power Plant Designs for IFE' made at the 1/29-31 meeting of the National Academies Committee on the Prospects for Inertial Confinement Fusion Energy Systems.

  20. Ten questions and answers about superconductivity

    E-Print Network [OSTI]

    Tian De Cao

    2012-11-13

    This work answers the basic questions of superconductivity in a question-and-answer format. We extend a basic hypothesis to various superconductors. This hypothesis is that superconductivity requires that the pairing gap locates around the Fermi level. On the basis of this hypothesis our calculations give the so-called three factor theory with which some key problems of the high temperature superconductivity are explained.

  1. CloudCast: Cloud Computing for Short-term Mobile Weather Forecasts

    E-Print Network [OSTI]

    Shenoy, Prashant

    of Massachusetts Amherst Abstract--Since today's weather forecasts only cover large regions every few hours algorithm for generating accurate short-term weather forecasts. We study CloudCast's design space, which One useful application is mobile weather forecasting, which provides hour-to-hour forecasts

  2. Smard Grid Software Applications for Distribution Network Load Forecasting Eugene A. Feinberg, Jun Fei

    E-Print Network [OSTI]

    Feinberg, Eugene A.

    of the distribution network. Keywords: load forecasting, feeder, transformer, load pocket, SmartGrid I. INTRODUCTION

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

    Solar irradiance data . . . . . . . . . . . . .Irradiance . . . . . . . . . . . . . . . . . . . . . . . . . . .4 Forecasting Solar Irradiance With GOES-West Satellite

  4. Ensemble Kalman Filter Data Assimilation in a 1D Numerical Model Used for Fog Forecasting

    E-Print Network [OSTI]

    Ensemble Kalman Filter Data Assimilation in a 1D Numerical Model Used for Fog Forecasting SAMUEL RE, a need exists for accurate and updated fog and low-cloud forecasts. Couche Brouillard Eau Liquide (COBEL for the very short-term forecast of fog and low clouds. This forecast system assimilates local observations

  5. Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction

    E-Print Network [OSTI]

    Raftery, Adrian

    Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction LE proposes an effective bias correction technique for wind direction forecasts from numerical weather forecasts. These techniques are applied to 48-h forecasts of surface wind direction over the Pacific

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

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

  8. 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

  9. Improved forecasts of extreme weather events by future space borne Doppler wind lidar

    E-Print Network [OSTI]

    Marseille, Gert-Jan

    of forecast failures, in particular those with large socio economic impact. Forecast failures of high- impact on their ability to improve meteorological analyses and subsequently reduce the probability of forecast failures true atmospheric state. This was generated by the European Centre for Medium-Range Weather Forecasts

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

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

  11. Solar Trackers Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  12. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    G. Bel; C. P. Connaughton; M. Toots; M. M. Bandi

    2015-03-29

    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 ($e_{\\zeta}$).

  13. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

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

  14. Forecasting and Risk Analysis in Supply Chain Management

    E-Print Network [OSTI]

    Hilmola, Olli-Pekka

    Forecasting is an underestimated field of research in supply chain management. Recently advanced methods are coming into use. Initial results are encouraging, but often require changes in policies for collaboration and ...

  15. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

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

  16. PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022

    E-Print Network [OSTI]

    low electricity and natural gas rates, and relatively low efficiency program and self Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert Oglesby Executive Director DISCLAIMER Staff for electric vehicles. #12;ii #12;iii ABSTRACT The Preliminary California Energy Demand Forecast 2012

  17. 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 ...

  18. Multidimensional approaches to performance evaluation of competing forecasting models 

    E-Print Network [OSTI]

    Xu, Bing

    2009-01-01

    The purpose of my research is to contribute to the field of forecasting from a methodological perspective as well as to the field of crude oil as an application area to test the performance of my methodological contributions ...

  19. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    Bel, G; Toots, M; Bandi, M M

    2015-01-01

    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. Optimally controlling hybrid electric vehicles using path forecasting

    E-Print Network [OSTI]

    Katsargyri, Georgia-Evangelina

    2008-01-01

    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. ...

  1. Mesoscale predictability and background error convariance estimation through ensemble forecasting 

    E-Print Network [OSTI]

    Ham, Joy L

    2002-01-01

    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 ...

  2. Forecasting and strategic inventory placement for gas turbine aftermarket spares

    E-Print Network [OSTI]

    Simmons, Joshua T. (Joshua Thomas)

    2007-01-01

    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. ...

  3. Dispersion in analysts' forecasts: does it make a difference? 

    E-Print Network [OSTI]

    Adut, Davit

    2004-09-30

    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...

  4. Radiation fog forecasting using a 1-dimensional model 

    E-Print Network [OSTI]

    Peyraud, Lionel

    2001-01-01

    weather patterns known to be favorable for producing fog and once it has formed, to state that it will persist unless the pattern changes. Unfortunately, while such methods have shown some success, many times they have led weather forecasters astray...

  5. Forecasting Stock Market Volatility: Evidence from Fourteen Countries. 

    E-Print Network [OSTI]

    Balaban, Ercan; Bayar, Asli; Faff, Robert

    2002-01-01

    This paper evaluates the out-of-sample forecasting accuracy of eleven models for weekly and monthly volatility in fourteen stock markets. Volatility is defined as within-week (within-month) standard deviation of continuously ...

  6. Adaptive sampling and forecasting with mobile sensor networks

    E-Print Network [OSTI]

    Choi, Han-Lim

    2009-01-01

    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 ...

  7. FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007

    E-Print Network [OSTI]

    ......................................................................... 11 3. Demand Side Management (DSM) Program Impacts................................... 13 4. Demand Sylvia Bender Manager DEMAND ANALYSIS OFFICE Scott W. Matthews Chief Deputy Director B.B. Blevins Forecast Methods and Models ....................................................... 14 5. Demand-Side

  8. Forecasting the probability of forest fires in Northeast Texas 

    E-Print Network [OSTI]

    Wadleigh, Stuart Allen

    1972-01-01

    FORECASTING THE PROBABILITY OF FOREST FIRES IN NORTHEAST TEXAS A Thesis by STUART ALLEN WADLEIGH Submit ted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE... December 1972 Major Subject: Meteorology FORECASTING THE PROBABILITY OF FOREST FIRES IN NORTHEAST TEXAS A Thesis by STUART ALLEN WADLEIGH Approved as to style and content by: ( irman of ee) (Head of Depar nt) (Member) (Member) December 1972 c...

  9. Forecasting potential project risks through leading indicators to project outcome 

    E-Print Network [OSTI]

    Choi, Ji Won

    2007-09-17

    for the degree of MASTER OF SCIENCE May 2007 Major Subject: Civil Engineering FORECASTING POTENTIAL PROJECT RISKS THROUGH LEADING INDICATORS TO PROJECT OUTCOME A Thesis by JI WON CHOI... Guikema Head of Department, David Rosowsky May 2007 Major Subject: Civil Engineering iii ABSTRACT Forecasting Potential Project Risks through Leading Indicators to Project Outcome. (May 2007) Ji Won Choi, B.S., Han-Yang University...

  10. Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use with the National Digital Forecast Database

    E-Print Network [OSTI]

    Douches, David S.

    Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use with the National Digital Forecast Database Kathleen Baker a, , Paul Roehsner a , Thomas Lake b , Douglas Rivet

  11. Weather-based forecasts of California crop yields

    SciTech Connect (OSTI)

    Lobell, D B; Cahill, K N; Field, C B

    2005-09-26

    Crop yield forecasts provide useful information to a range of users. Yields for several crops in California are currently forecast based on field surveys and farmer interviews, while for many crops official forecasts do not exist. As broad-scale crop yields are largely dependent on weather, measurements from existing meteorological stations have the potential to provide a reliable, timely, and cost-effective means to anticipate crop yields. We developed weather-based models of state-wide yields for 12 major California crops (wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios), and tested their accuracy using cross-validation over the 1980-2003 period. Many crops were forecast with high accuracy, as judged by the percent of yield variation explained by the forecast, the number of yields with correctly predicted direction of yield change, or the number of yields with correctly predicted extreme yields. The most successfully modeled crop was almonds, with 81% of yield variance captured by the forecast. Predictions for most crops relied on weather measurements well before harvest time, allowing for lead times that were longer than existing procedures in many cases.

  12. Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS 

    E-Print Network [OSTI]

    Roop, J. M.; Dahowski, R. T

    2000-01-01

    Comparisons are made of energy forecasts using results from the Industrial module of the National Energy Modeling System (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy Modeling System (ITEMS), a model...

  13. Ian Hinchliffe Answers Your Higgs Boson Questions

    SciTech Connect (OSTI)

    Hinchliffe, Ian

    2012-01-01

    contingent with the ATLAS experiment at CERN, answers many of your questions about the Higgs boson. Ian invited viewers to send in questions about the Higgs via email, Twitter, Facebook, or YouTube in an "Ask a Scientist" video posted July 3: http://youtu.be/xhuA3wCg06s CERN's July 4 announcement that the ATLAS and CMS experiments at the Large Hadron Collider have discovered a particle "consistent with the Higgs boson" has raised questions about what scientists have found and what still remains to be found -- and what it all means. If you have suggestions for future "Ask a Scientist" videos, post them below or send ideas to askascientist@lbl.gov

  14. Ian Hinchliffe Answers Your Higgs Boson Questions

    ScienceCinema (OSTI)

    Hinchliffe, Ian

    2013-05-29

    contingent with the ATLAS experiment at CERN, answers many of your questions about the Higgs boson. Ian invited viewers to send in questions about the Higgs via email, Twitter, Facebook, or YouTube in an "Ask a Scientist" video posted July 3: http://youtu.be/xhuA3wCg06s CERN's July 4 announcement that the ATLAS and CMS experiments at the Large Hadron Collider have discovered a particle "consistent with the Higgs boson" has raised questions about what scientists have found and what still remains to be found -- and what it all means. If you have suggestions for future "Ask a Scientist" videos, post them below or send ideas to askascientist@lbl.gov

  15. Value of Probabilistic Weather Forecasts: Assessment by Real-Time Optimization of Irrigation Scheduling

    SciTech Connect (OSTI)

    Cai, Ximing; Hejazi, Mohamad I.; Wang, Dingbao

    2011-09-29

    This paper presents a modeling framework for real-time decision support for irrigation scheduling using the National Oceanic and Atmospheric Administration's (NOAA's) probabilistic rainfall forecasts. The forecasts and their probability distributions are incorporated into a simulation-optimization modeling framework. In this study, modeling irrigation is determined by a stochastic optimization program based on the simulated soil moisture and crop water-stress status and the forecasted rainfall for the next 1-7 days. The modeling framework is applied to irrigated corn in Mason County, Illinois. It is found that there is ample potential to improve current farmers practices by simply using the proposed simulation-optimization framework, which uses the present soil moisture and crop evapotranspiration information even without any forecasts. It is found that the values of the forecasts vary across dry, normal, and wet years. More significant economic gains are found in normal and wet years than in dry years under the various forecast horizons. To mitigate drought effect on crop yield through irrigation, medium- or long-term climate predictions likely play a more important role than short-term forecasts. NOAA's imperfect 1-week forecast is still valuable in terms of both profit gain and water saving. Compared with the no-rain forecast case, the short-term imperfect forecasts could lead to additional 2.4-8.5% gain in profit and 11.0-26.9% water saving. However, the performance of the imperfect forecast is only slightly better than the ensemble weather forecast based on historical data and slightly inferior to the perfect forecast. It seems that the 1-week forecast horizon is too limited to evaluate the role of the various forecast scenarios for irrigation scheduling, which is actually a seasonal decision issue. For irrigation scheduling, both the forecast quality and the length of forecast time horizon matter. Thus, longer forecasts might be necessary to evaluate the role of forecasts for irrigation scheduling in a more effective way.

  16. Results from the Second Forum on the Future Role of the Human in the Forecast Process. Part II: Cognitive Psychological Aspects of Expert Weather Forecasters

    E-Print Network [OSTI]

    Schultz, David

    : Cognitive Psychological Aspects of Expert Weather Forecasters NEIL A. STUART* NOAA/National Weather Service of Applied Research Associates, Fairborn, Ohio In Preparation for Submission to Forecasters Forum, Weather and Forecasting 30 June 2006 Corresponding author address: Neil A. Stuart, National Weather Service, 10009 General

  17. Forecasting the 2013–2014 influenza season using Wikipedia

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

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are appliedmore »to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.« less

  18. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect (OSTI)

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are applied to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.

  19. Fish and Wildlife Management Questions and RM&E Strategies Key Management Questions

    E-Print Network [OSTI]

    -hydro agency responsibilities. #12;2 Strategic Category: Hydro RM&E The following are the primary management1 Fish and Wildlife Management Questions and RM&E Strategies Key Management Questions 1. Are we implemented and accomplished as proposed? Strategic Category: Fish Population Status Monitoring The following

  20. On a question of Cooper and Kennedy

    E-Print Network [OSTI]

    Prodinger, Helmut

    On a question of Cooper and Kennedy@rsmb.tuwien.ac.at In [2], Cooper and Kennedy note the following: If xn = axn-1 + bxn-2 + cxn. Kennedy. Proof of a result by Jarden by generalizing* * a proof of Carlitz. Fibonacci Quarterly, 33

  1. Questioning Yourself Ready Reference B-2

    E-Print Network [OSTI]

    Questioning Yourself Ready Reference B-2 College of Engineering, Architecture & Technology Career Services Oklahoma State University College of Engineering, Architecture & Technology Career Services Office set my own hours? Do I thrive in a high-stress atmosphere, or would I prefer something a bit more

  2. Common Questions Why should I soil test?

    E-Print Network [OSTI]

    Isaacs, Rufus

    Common Questions Why should I soil test? Soil testing is an important diagnostic tool to evaluate nutrient imbalances and understand plant growth. The most important reason to soil test is to have a basis for intelligent application of fertilizer and lime. Testing also allows for growers and homeowners to maintain

  3. Basics of Photometry Photometry: Basic Questions

    E-Print Network [OSTI]

    Masci, Frank

    Basics of Photometry #12;Photometry: Basic Questions · How do you identify objects in your image type of object you're studying? #12;#12;#12;Topics 1. General Considerations 2. Stellar Photometry 3. Galaxy Photometry #12;I: General Considerations 1. Garbage in, garbage out... 2. Object Detection 3

  4. CRAD, Facility Safety- Unreviewed Safety Question Requirements

    Broader source: Energy.gov [DOE]

    A section of Appendix C to DOE G 226.1-2 "Federal Line Management Oversight of Department of Energy Nuclear Facilities." Consists of Criteria Review and Approach Documents (CRADs) that can be used for assessment of a contractor's Unreviewed Safety Question (USQ) process.

  5. Ten Questions Concerning Generative Computer Art

    E-Print Network [OSTI]

    McCormack, Jon

    Ten Questions Concerning Generative Computer Art Jon McCormack, Oliver Bown, Alan Dorin, Jonathan), Centre for Electronic Media Art, Faculty of Information Technology, Monash University, Caulfield East, Australia, Email: Jonathan McCabe (generative artist), Faculty of Arts and Design

  6. ANNUAL REPORT 20112012 ASKING BETTER QUESTIONS

    E-Print Network [OSTI]

    Bhunia, Swarup

    panels?" and "How long will a solar panel really last?" And the distinction that divides "What should we, how wind turbine blades can be lighter yet stronger, how flow batteries can store energy longer. They questioned how to bring power to developing countries with no established energy sources, ways to power

  7. Questions to In general, when planning an

    E-Print Network [OSTI]

    Royer, Dana

    Questions to Ponder.... In general, when planning an event there are many things to think about for this event? Program Planning "The one who fails to plan, plans to fail" --Unknown Paperwork Yes No Social in planning a program or event on campus? Are you unsure of where to begin with the planning process

  8. 10 Questions for a Physicist: Antonio Checco

    Broader source: Energy.gov [DOE]

    Today, the Energy Blog is launching a new series, 10 Questions, with a simple goal in mind – to introduce you to our scientists and their incredible work. Dr. Checco explains wetting on the nanoscale, shares some advice for students and tells us about his favorite movie scientist.

  9. Treatment of Anthrax Disease Frequently Asked Questions

    SciTech Connect (OSTI)

    Judd, Kathleen S.; Young, Joan E.; Lesperance, Ann M.; Malone, John D.

    2010-05-14

    This document provides a summary of Frequently Asked Questions (FAQs) on the treatment of anthrax disease caused by a wide-area release of Bacillus anthracis spores as an act bioterrorism. These FAQs are intended to provide the public health and medical community, as well as others, with guidance and communications to support the response and long-term recovery from an anthrax event.

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01

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

  11. Forty Most Asked Questions Concerning CEQ's National Environmental...

    Energy Savers [EERE]

    Forty Most Asked Questions Concerning CEQ's National Environmental Policy Act Regulations Forty Most Asked Questions Concerning CEQ's National Environmental Policy Act Regulations...

  12. DOE response to questions from AHAM on the supplemental proposed...

    Energy Savers [EERE]

    response to questions from AHAM on the supplemental proposed test procedure for residential clothes washers DOE response to questions from AHAM on the supplemental proposed test...

  13. Sample Questions | U.S. DOE Office of Science (SC)

    Office of Science (SC) Website

    Sample Questions Academic Question Resources Attending National Event Volunteers 2015 Competition Results News Media WDTS Home Contact Information National Science Bowl...

  14. Submit Your Home Energy Efficiency Questions Now for Earth Day...

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

    Submit Your Home Energy Efficiency Questions Now for Earth Day Google+ Hangout Submit Your Home Energy Efficiency Questions Now for Earth Day Google+ Hangout April 2, 2013 -...

  15. Questions and Issues on Hydrogen Pipelines: Pipeline Transmission...

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

    Questions and Issues on Hydrogen Pipelines: Pipeline Transmission of Hydrogen Questions and Issues on Hydrogen Pipelines: Pipeline Transmission of Hydrogen Pipping of GH2 Pipeline....

  16. Frequently Asked Questions about the Office of Energy Efficiency...

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

    Frequently Asked Questions about the Office of Energy Efficiency and Renewable Energy Frequently Asked Questions about the Office of Energy Efficiency and Renewable Energy Below...

  17. Berkeley Lab Answers Your Home Energy Efficiency Questions (Other...

    Office of Scientific and Technical Information (OSTI)

    Other: Berkeley Lab Answers Your Home Energy Efficiency Questions Citation Details In-Document Search Title: Berkeley Lab Answers Your Home Energy Efficiency Questions In this...

  18. Electric Vehicle Deployment: Policy Questions and Impacts to...

    Office of Environmental Management (EM)

    Vehicle Deployment: Policy Questions and Impacts to the U.S. Electric Grid - EAC Recommendations (November 2011) Electric Vehicle Deployment: Policy Questions and Impacts to the...

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

    SciTech Connect (OSTI)

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

    2009-11-20

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

  20. The Question of Conation in Action Theory

    E-Print Network [OSTI]

    Good, Robert

    The Question of Conation in Action Theory Robert Good Rider College In some recent and most interesting articles, Myles Brand argues that intending has an exclusively conative feature. 1 This conative feature is said by Brand to be non... of a conative component of intending is best understood in light of the recent history of Causal theories of action. Basciaily, a Causal theory is one which holds that intentional ac­ tion is caused by a preceding mental event of a partic­ ular kind...

  1. Case-based Teaching Discovery Questions

    E-Print Network [OSTI]

    Campbell, A. Malcolm

    Goals Case-based Teaching Discovery Questions Teaching Chips Assessment Web Tools 1 Biology & 2.bio.davidson.edu/people/macampbell/ASCB/2002.html www.aw.com/genomics www.bio.davidson.edu/courses/genomics/studentpages.html www.bio.davidson.edu/courses/genomics/Exams/exams.html www.bio.davidson.edu/projects/GCAT/MAGICTool.html www.bio.davidson.edu/projects/GCAT/teachingchip.html

  2. EPS 236: Flow in porous materials, optional questions 1. Adapted from question 11 on page 56 in Domenico and Schwartz.

    E-Print Network [OSTI]

    Manga, Michael

    to low head. 1 #12;4. This question is adapted from question 1.4 in Ingebritsen and Sanford. A variety

  3. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    2008-01-15

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

  4. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

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

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

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

    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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01

    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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01

    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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01

    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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

    the AEO 2005 reference case oil price forecast and NYMEX oibasis-adjusted NYMEX crude oil futures con tracts fo r 2010more than the reference case oil price forecast for that

  12. Forecasting 65+ travel : an integration of cohort analysis and travel demand modeling

    E-Print Network [OSTI]

    Bush, Sarah, 1973-

    2003-01-01

    Over the next 30 years, the Boomers will double the 65+ population in the United States and comprise a new generation of older Americans. This study forecasts the aging Boomers' travel. Previous efforts to forecast 65+ ...

  13. ESTIMATING POTENTIAL SEVERE WEATHER SOCIETAL IMPACTS USING PROBABILISTIC FORECASTS ISSUED BY THE NWS STORM PREDICTION CENTER

    E-Print Network [OSTI]

    effort to estimate potential severe weather societal impacts based on a combination of probabilistic forecasts and high resolution population data. For equal severe weather threat, events that occur over1 ESTIMATING POTENTIAL SEVERE WEATHER SOCIETAL IMPACTS USING PROBABILISTIC FORECASTS ISSUED

  14. Generating day-of-operation probabilistic capacity scenarios from weather forecasts

    E-Print Network [OSTI]

    Buxi, Gurkaran

    2012-01-01

    0400Z on the 18 th the wind is forecast at 15Knots blowingforecast for the day for the quarter-hour period , representing the windthe forecast is valid. The TAF predicts the wind speed, wind

  15. Earnings Management Pressure on Audit Clients: Auditor Response to Analyst Forecast Signals 

    E-Print Network [OSTI]

    Newton, Nathan J.

    2013-06-26

    This study investigates whether auditors respond to earnings management pressure created by analyst forecasts. Analyst forecasts create an important earnings target for management, and professional standards direct auditors to consider how...

  16. Error growth in poor ECMWF forecasts over the contiguous United States 

    E-Print Network [OSTI]

    Modlin, Norman Ray

    1993-01-01

    Successive improvements to the European Center for Medium-range Weather Forecasting model have resulted in improved forecast performance over the Contiguous United States (CONUS). While the overall performance of the model ...

  17. Improving Groundwater Predictions Utilizing Seasonal Precipitation Forecasts from General Circulation Models

    E-Print Network [OSTI]

    Arumugam, Sankar

    Improving Groundwater Predictions Utilizing Seasonal Precipitation Forecasts from General. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater

  18. A supply forecasting model for Zimbabwe's corn sector: a time series and structural analysis 

    E-Print Network [OSTI]

    Makaudze, Ephias

    1993-01-01

    Board's financial resource needs. Thus, the corn supply forecasts are important information used by the government for contingency planning, decision-making, policy-formulation and implementation. As such, the need for accurate forecasts is obvious...

  19. Application of the Stretched Exponential Production Decline Model to Forecast Production in Shale Gas Reservoirs 

    E-Print Network [OSTI]

    Statton, James Cody

    2012-07-16

    . This study suggests a type curve is most useful when 24 months or less is available to forecast. The SEPD model generally provides more conservative forecasts and EUR estimates than Arps' model with a minimum decline rate of 5%....

  20. Distributed quantitative precipitation forecasts combining information from radar and numerical weather prediction model outputs

    E-Print Network [OSTI]

    Ganguly, Auroop Ratan

    2002-01-01

    Applications of distributed Quantitative Precipitation Forecasts (QPF) range from flood forecasting to transportation. Obtaining QPF is acknowledged to be one of the most challenging areas in hydrology and meteorology. ...

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

    Figure 9: Two Alternative Price Forecasts (denoted by openComparison of AEO 2007 Natural Gas Price Forecast toNYMEX Futures Prices Date: December 6, 2006 Introduction On

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

    and forecasting of solar radiation data: a review. Int. J.beam and global solar radiation data. Solar Energy , 81:768–forecasting of solar radiation data: a review. International

  3. An Intelligent Solar Powered Battery Buffered EV Charging Station with Solar Electricity Forecasting and EV Charging Load Projection Functions

    E-Print Network [OSTI]

    Zhao, Hengbing; Burke, Andrew

    2014-01-01

    power source from inherent intermittent solar PV power.B. Solar PV Electricity Forecasting Fig. 1. Charging stationForecasting Power Output of Solar Photovoltaic System Using

  4. !! Plan to answer a specific question. !! Limit the number of variables in the test.

    E-Print Network [OSTI]

    . !! Establish adjacent control plots. !! Replicate, replicate, replicate. !! Set up a written measurement built in the past and have been excellent areas for demonstrating wildlife effects on various stages be a waste of 20 plots. Example hypothesis may include: ! Hare are more damaging to small cedar seedlings

  5. Critical Question #2: What are the Best Practices for Ventilation Specific

    Office of Energy Efficiency and Renewable Energy (EERE) 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 Center Home Page on Delicious Rank EERE:FinancingPetroleum Based| Department of Energy Whole-Home Gas8 AUDITApril 3, 2012 AMOofto

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01

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

  7. Detiding DART buoy data for real-time extraction of source coefficients for operational tsunami forecasting

    E-Print Network [OSTI]

    Percival, Donald B; Eble, Marie C; Gica, Edison; Huang, Paul Y; Mofjeld, Harold O; Spillane, Michael C; Titov, Vasily V; Tolkova, Elena I

    2014-01-01

    U.S. Tsunami Warning Centers use real-time bottom pressure (BP) data transmitted from a network of buoys deployed in the Pacific and Atlantic Oceans to tune source coefficients of tsunami forecast models. For accurate coefficients and therefore forecasts, tides at the buoys must be accounted for. In this study, five methods for coefficient estimation are compared, each of which accounts for tides differently. The first three subtract off a tidal prediction based on (1) a localized harmonic analysis involving 29 days of data immediately preceding the tsunami event, (2) 68 pre-existing harmonic constituents specific to each buoy, and (3) an empirical orthogonal function fit to the previous 25 hrs of data. Method (4) is a Kalman smoother that uses method (1) as its input. These four methods estimate source coefficients after detiding. Method (5) estimates the coefficients simultaneously with a two-component harmonic model that accounts for the tides. The five methods are evaluated using archived data from eleven...

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

    SciTech Connect (OSTI)

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

    1997-01-07

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

  9. Managing Wind Power Forecast Uncertainty in Electric Grids Submitted in partial fulfillment of the requirements for

    E-Print Network [OSTI]

    Instituto de Sistemas e Robotica

    Managing Wind Power Forecast Uncertainty in Electric Grids Submitted in partial fulfillment;iii Abstract Electricity generated from wind power is both variable and uncertain. Wind forecasts prices. Wind power forecast errors for aggregated wind farms are often modeled with Gaussian

  10. Short-Term Load Forecasting at the Local Level using Smart Meter Data

    E-Print Network [OSTI]

    Tronci, Enrico

    ]; electric vehicle integration [8]; and microgrid and virtual power plant applications [7], [11]. In addition, forecast uncertainty, power demand. I. INTRODUCTION Short-Term Load Forecasting (STLF) is the forecasting is considered to be critical for power system operation, particularly for energy balancing, energy market

  11. Forecasting the Hourly Ontario Energy Price by Multivariate Adaptive Regression Splines

    E-Print Network [OSTI]

    Cañizares, Claudio A.

    for forecasting the Spanish electricity market prices. On the other hand, ARIMA, dynamic regression and transfer been used to forecast the Spanish market prices [7], [9], Californian market prices [9], Leipzig power have been used for forecasting the Spanish and Californian market prices [11] and the PJM market prices

  12. Quality Assessment of the Cobel-Isba Numerical Forecast System of Fog and Low Clouds

    E-Print Network [OSTI]

    Quality Assessment of the Cobel-Isba Numerical Forecast System of Fog and Low Clouds THIERRY BERGOT Abstract--Short-term forecasting of fog is a difficult issue which can have a large societal impact. Fog of the life cycle of fog (onset, development and dissipation) up to +6 h. The error on the forecast onset

  13. Atmospheric Environment 39 (2005) 13731382 A hierarchical Bayesian model to estimate and forecast ozone

    E-Print Network [OSTI]

    Irwin, Mark E.

    2005-01-01

    conditional on observed (or forecasted) meteorology including temperature, humidity, pressure, and wind speed, defining the spatial­temporal extent of episodes of dangerous air quality, forecasting urban and areaAtmospheric Environment 39 (2005) 1373­1382 A hierarchical Bayesian model to estimate and forecast

  14. A Comparison of Bayesian and Conditional Density Models in Probabilistic Ozone Forecasting

    E-Print Network [OSTI]

    Hsieh, William

    A Comparison of Bayesian and Conditional Density Models in Probabilistic Ozone Forecasting Song Cai to provide predictive distributions of daily maximum surface level ozone concentrations. Five forecast models forecasts for extreme events, namely poor air quality events defined as having ozone concentration 82 ppb

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

    E-Print Network [OSTI]

    Mallet, Vivien

    Ozone ensemble forecast with machine learning algorithms Vivien Mallet,1,2 Gilles Stoltz,3; published 13 March 2009. [1] We apply machine learning algorithms to perform sequential aggregation of ozone forecasts. The latter rely on a multimodel ensemble built for ozone forecasting with the modeling system

  16. Bias reduction in the Sea Surface Temperature (SST) forecasts based on GOES satellite data

    E-Print Network [OSTI]

    Kurapov, Alexander

    Bias reduction in the Sea Surface Temperature (SST) forecasts based on GOES satellite data Based on comparisons with infrared (GOES) and microwave (AMSE-R) satellite data, our coastal ocean forecast model set circulation model and satellite data helps to improve forecasting of ocean conditions (esp. currents and SST

  17. Short Term Electricity Price Forecasting in the Nordic Region Anders Lund Eriksrud

    E-Print Network [OSTI]

    Lavaei, Javad

    Short Term Electricity Price Forecasting in the Nordic Region Anders Lund Eriksrud May 11, 2014 Abstract This paper presents a survey of electricity price forecasting for the Nordic region, and performs that time series models more appropriate for forecasting electricity prices, compared to machine learning

  18. Influence of Spikes in the Short-term Electricity Price Forecasting

    E-Print Network [OSTI]

    Friedl, Herwig

    Influence of Spikes in the Short-term Electricity Price Forecasting Vika Koban, Milos Pantos of electricity price under normal conditions with the spike time series caused by extreme conditions in order to obtain a better forecast of the spot price. Short term electricity price forecasting has become

  19. Detrending Daily Natural Gas Consumption Series to Improve Short-Term Forecasts

    E-Print Network [OSTI]

    Povinelli, Richard J.

    Detrending Daily Natural Gas Consumption Series to Improve Short-Term Forecasts Ronald H. Brown1 that allows long-term natural gas demand signals to be used effect- ively to generate high quality short-term natural gas demand forecasting models. Short data sets in natural gas forecasting inadequately represent

  20. Large-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random Fields

    E-Print Network [OSTI]

    Kolter, J. Zico

    in a wide range of energy systems, including forecasting demand, renewable generation, and electricityLarge-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random demonstrated that in the context of electrical demand and wind power, probabilistic forecasts can offer

  1. Application of a new phenomenological coronal mass ejection model to space weather forecasting

    E-Print Network [OSTI]

    Howard, Tim

    to space weather forecasting T. A. Howard1 and S. J. Tappin2 Received 15 October 2009; revised 27 April with the Earth. Hence the model can be used for space weather forecasting. We present a preliminary evaluation to fully validate it for integration with existing tools for space weather forecasting. Citation: Howard, T

  2. Reprinted from: Proceedings, International Workshop on Observations/Forecasting of Meso-scale Severe Weather and

    E-Print Network [OSTI]

    Doswell III, Charles A.

    -scale Severe Weather and Technology of Reduction of Relevant Disasters (Tokyo, Japan), 22-26 February 1993, 181 on the ingredients for particular severe weather events, a focus is provided for the forecasting process of forecasters is discussed also, as a necessary component in a balanced approach to weather forecasting

  3. Nucleosynthesis: a field with still many open nuclear physics questions

    SciTech Connect (OSTI)

    Goriely, S. [Institut d'Astronomie et d'Astrophysique, Universite Libre de Bruxelles, Campus de la Plaine, CP 226 1050 Brussels (Belgium)

    2010-06-01

    Stellar nucleosynthesis is a vastly interdisciplinary field. There is a large number of different problems invoked calling for a variety of different and complementary research fields. Impressive progress has been made for the last decades in the various fields related to nucleosynthesis, especially in experimental and theoretical nuclear physics, as well as in ground-based or space astronomical observations and astrophysical modellings. In spite of that success, major problems and puzzles remain. The three major nucleosynthesis processes called for to explain the origin of the elements heavier than iron are described and the major pending questions discussed. As far as nuclear physics is concerned, good quality nuclear data is known to be a necessary condition for a reliable modelling of stellar nucleosynthesis. Through some specific examples, the need for further theoretical or experimental developments is also critically discussed in view of their impact on nucleosynthesis predictions.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

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

  5. Prima Facie Questions in Quantum Gravity

    E-Print Network [OSTI]

    C. J. Isham

    1993-10-22

    The long history of the study of quantum gravity has thrown up a complex web of ideas and approaches. The aim of this article is to unravel this web a little by analysing some of the {\\em prima facie\\/} questions that can be asked of almost any approach to quantum gravity and whose answers assist in classifying the different schemes. Particular emphasis is placed on (i) the role of background conceptual and technical structure; (ii) the role of spacetime diffeomorphisms; and (iii) the problem of time.

  6. Fermilab | Science | Questions for the Universe

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformation Current HABFES OctoberEvan Racah861MayArtQuestions for the Universe To discover

  7. Fermilab | Tritium at Fermilab | Frequently asked questions

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformation Current HABFES OctoberEvan Racah861MayArtQuestions forFeature photo

  8. Comments/Questions | Critical Materials Institute

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTechtail.Theory of raregovAboutRecoveryplanningCoal Glossary › FAQS ›Comments/Questions To

  9. Comments/Questions? | The Ames Laboratory

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTechtail.Theory of raregovAboutRecoveryplanningCoal Glossary › FAQS ›Comments/Questions

  10. Frequently Asked Questions | Photosynthetic Antenna Research Center

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformation Current HABFES OctoberEvanServicesAmesFour LosActFrequently Asked Questions

  11. A Question of Savings | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) 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 Center Home Page on Delicious Rank EERE: Alternative FuelsofProgram:Y-12 Beta-3 Racetracks25 AMO PeerServices6ProgramAA Path toA Question

  12. Some questions to be considered at the IRDR discussion meeting, 22nd March

    E-Print Network [OSTI]

    Guillas, Serge

    that the tsunami warning system and the high level of tsunami awareness and evacuation training worked as well to the Tohoku earthquake and tsunami, in Japan and worldwide · Questions specific to Japan: ­ It seems or desirable to further reduce casualties from future large, infrequent tsunamis? ­ What cultural factors need

  13. DIRECT COST REVIEW-JUSTIFICATION: PLEASE COMPLETE THIS FORM FOR JUSTIFICATION OF QUESTIONABLE DIRECT COSTS

    E-Print Network [OSTI]

    Finley Jr., Russell L.

    DIRECT COST REVIEW-JUSTIFICATION: PLEASE COMPLETE THIS FORM FOR JUSTIFICATION OF QUESTIONABLE DIRECT COSTS Provide the information below, plus any related attachments (copy of receipt, quote, etc the cost be specifically identified with a particular award with relative ease and accuracy? 2) Does

  14. Heating System Specification Specification of Heating System

    E-Print Network [OSTI]

    Day, Nancy

    Appendix A Heating System Specification /* Specification of Heating System (loosely based */ requestHeat : Room ­? bool; 306 #12; APPENDIX A. HEATING SYSTEM SPECIFICATION 307 /* user inputs */ living --- HEATERâ??ACTIVE --- ACTIVATINGâ??HEATER --- HEATERâ??RUNNING ; #12; APPENDIX A. HEATING SYSTEM SPECIFICATION

  15. Production Forecast, Analysis and Simulation of Eagle Ford Shale Oil 

    E-Print Network [OSTI]

    Alotaibi, Basel Z S Z J

    2014-12-02

    is to generate field-wide production forecast of the Eagle Ford Shale (EFS). This study considered oil production of the EFS only. More than 6 thousand oil wells were put online in the EFS basin between 2008 and December 2013. The method started by generating...

  16. Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts

    E-Print Network [OSTI]

    Garulli, Andrea

    profiles, raise major challenges to wind power integration into the electricity grid. In this work we studyOptimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts Antonio that the inherent variability in wind power generation and the related difficulty in predicting future generation

  17. Forecasting stock prices using Genetic Programming and Chance Discovery

    E-Print Network [OSTI]

    Fernandez, Thomas

    finance. GAs are algorithms that emulate evolution and natural selection to solve a problem. A populationForecasting stock prices using Genetic Programming and Chance Discovery Alma Lilia Garcia to financial problems. In particular, the use of Genetic Algorithms (GAs), for financial purposes, has

  18. Power Forecasting for Plug-in Electric Vehicles

    E-Print Network [OSTI]

    Lavaei, Javad

    Power Forecasting for Plug-in Electric Vehicles with Statistic Simulations Guangbin Li (gl2423) #12 of the most heated-discussed issues. Energy shortage and environment pollution are the main bottleneck the tradeoff between energy supply and environment pollution. As the international oil price was continuously

  19. Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will tak

    E-Print Network [OSTI]

    Islam, M. Saif

    is familiar with solar energy issues, we hope that you will take a few moments to answer this short survey on your needs for information on solar energy resources and forecasting. This survey is conducted with the California Solar Energy Collaborative (CSEC) and the California Solar Initiative (CSI) our objective

  20. Utilize cloud computing to support dust storm forecasting Qunying Huanga

    E-Print Network [OSTI]

    Chen, Songqing

    storm forecasting operational system should support a disruptive fashion by scaling up to enable high to save energy and costs. With the capability of providing a large, elastic, and virtualized pool and property damages since 1995 (Figure 1). Deaths and injuries are usually caused by car accidents, because

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

    SciTech Connect (OSTI)

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

    2009-03-01

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

  2. MET 416: TROPICAL ANALYSIS AND FORECASTING Spring Semester 2013

    E-Print Network [OSTI]

    current (nowcasting) and expected weather, using all available real-time operational weather data Exam 4/9 Summer trade-wind weather based on HaRP 4/11-16 Large-scale influences, Diurnal cycle to the development of tropical storm systems and mesoscale weather. Lectures will include a forecasting perspective

  3. A Hierarchical Pattern Learning Framework for Forecasting Extreme Weather Events

    E-Print Network [OSTI]

    Ding, Wei

    . Frequent pattern-based data representations have been used in various studies for abstracting climaticA Hierarchical Pattern Learning Framework for Forecasting Extreme Weather Events Dawei Wang, Wei@cs.umb.edu Abstract--Extreme weather events, like extreme rainfalls, are severe weather hazards and also the triggers

  4. ARM Processes and Their Modeling and Forecasting Methodology Benjamin Melamed

    E-Print Network [OSTI]

    Chapter 73 ARM Processes and Their Modeling and Forecasting Methodology Benjamin Melamed Abstract The class of ARM (Autoregressive Modular) processes is a class of stochastic processes, defined by a non- linear autoregressive scheme with modulo-1 reduction and additional transformations. ARM processes

  5. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    /Individuals Providing Comments California Natural Gas Vehicle Coalition/ Mike Eaves League of Women VotersCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY AND TRANSPORTATION DIVISION B. B. Blevins Executive Director DISCLAIMER This report was prepared by a California

  6. Detecting and Forecasting Economic Regimes in Automated Exchanges

    E-Print Network [OSTI]

    Ketter, Wolfgang

    Detecting and Forecasting Economic Regimes in Automated Exchanges Wolfgang Ketter , John Collins. of Mgmt., Erasmus University Dept. of Computer Science and Engineering, University of Minnesota Dept,gini,schrater}@cs.umn.edu, agupta@csom.umn.edu Abstract We present basic building blocks of an agent that can use observable market

  7. Detecting and Forecasting Economic Regimes in Automated Exchanges

    E-Print Network [OSTI]

    Ketter, Wolfgang

    Detecting and Forecasting Economic Regimes in Automated Exchanges Wolfgang Ketter # , John Collins, Rotterdam Sch. of Mgmt., Erasmus University + Dept. of Computer Science and Engineering, University wketter@rsm.nl, {jcollins,gini,schrater}@cs.umn.edu, agupta@csom.umn.edu Abstract We present basic

  8. URBAN OZONE CONCENTRATION FORECASTING WITH ARTIFICIAL NEURAL NETWORK IN CORSICA

    E-Print Network [OSTI]

    Boyer, Edmond

    Perceptron; Ozone concentration. 1. Introduction Tropospheric ozone is a major air pollution problem, both, Ajaccio, France, e-mail: balu@univ-corse.fr Abstract: Atmospheric pollutants concentration forecasting is an important issue in air quality monitoring. Qualitair Corse, the organization responsible for monitoring air

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

    SciTech Connect (OSTI)

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

    2011-03-28

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

  10. A comparison study of data assimilation algorithms for ozone forecasts

    E-Print Network [OSTI]

    Mallet, Vivien

    A comparison study of data assimilation algorithms for ozone forecasts Lin Wu,1,2 V. Mallet,1,2 M assimilation schemes with the aim of designing suitable assimilation algorithms for short- range ozone but stable systems with high uncertainties (e.g., over 20% for ozone daily peaks (Hanna et al., 1998; Mallet

  11. 1. Introduction Users of weather forecasts, particularly paying cus-

    E-Print Network [OSTI]

    1. Introduction Users of weather forecasts, particularly paying cus- tomers, are operating within Kingdom out of a total budget of approximately £140 million for winter road maintenance. It is difficult rely on a simple set of statistics provided by the weather service providers. The current guidance

  12. Forecasting Hourly Electricity Load Profile Using Neural Networks

    E-Print Network [OSTI]

    Koprinska, Irena

    Forecasting Hourly Electricity Load Profile Using Neural Networks Mashud Rana and Irena Koprinska--We present INN, a new approach for predicting the hourly electricity load profile for the next day from a time series of previous electricity loads. It uses an iterative methodology to make the predictions

  13. Journey data based arrival forecasting for bicycle hire schemes

    E-Print Network [OSTI]

    Imperial College, London

    Journey data based arrival forecasting for bicycle hire schemes Marcel C. Guenther and Jeremy T. The global emergence of city bicycle hire schemes has re- cently received a lot of attention of future bicycle migration trends, as these assist service providers to ensure availability of bicycles

  14. Numerical Weather Forecasting at the Savannah River Site

    SciTech Connect (OSTI)

    Buckley, R.L.

    1999-01-26

    Facilities such as the Savannah River Site (SRS), which contain the potential for hazardous atmospheric releases, rely on the predictive capabilities of dispersion models to assess possible emergency response actions. The operational design in relation to domain size and forecast time is presented, along with verification of model results over extended time periods with archived surface observations.

  15. Forecasting Hospital Bed Availability Using Simulation and Neural Networks

    E-Print Network [OSTI]

    Kuhl, Michael E.

    Forecasting Hospital Bed Availability Using Simulation and Neural Networks Matthew J. Daniels, NY 14623 Elisabeth Hager Hager Consulting Pittsford, NY 14534 Abstract The availability of beds is a critical factor for decision-making in hospitals. Bed availability (or alternatively the bed occupancy

  16. FORECASTING SOLAR RADIATION PRELIMINARY EVALUATION OF AN APPROACH

    E-Print Network [OSTI]

    Perez, Richard R.

    a limited evaluation of its performance against ground-measured and satellite-derived irradiances in AlbanyFORECASTING SOLAR RADIATION -- PRELIMINARY EVALUATION OF AN APPROACH BASED UPON THE NATIONAL NREL, 1617 Cole Blvd. Golden, CO 80841 stephen_wilcox@nrel.gov Antoine Zelenka Meteosuisse

  17. Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems

    E-Print Network [OSTI]

    Shenoy, Prashant

    Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems Navin Sharma,gummeson,irwin,shenoy}@cs.umass.edu Abstract--To sustain perpetual operation, systems that harvest environmental energy must carefully regulate their usage to satisfy their demand. Regulating energy usage is challenging if a system's demands

  18. Leveraging Weather Forecasts in Renewable Energy Navin Sharmaa,

    E-Print Network [OSTI]

    Shenoy, Prashant

    Leveraging Weather Forecasts in Renewable Energy Systems Navin Sharmaa, , Jeremy Gummesonb , David, Binghamton, NY 13902 Abstract Systems that harvest environmental energy must carefully regulate their us- age to satisfy their demand. Regulating energy usage is challenging if a system's demands are not elastic, since

  19. Short-Term Solar Energy Forecasting Using Wireless Sensor Networks

    E-Print Network [OSTI]

    Cerpa, Alberto E.

    Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Stefan Achleitner, Tao Liu an advantage for output power prediction. Solar Energy Prediction System Our prediction model is based variability of more then 100 kW per minute. For practical usage of solar energy, predicting times of high

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

    SciTech Connect (OSTI)

    Vrugt, Jasper A; Wohling, Thomas

    2008-01-01

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

  1. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

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

    2011-11-29

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

  2. Frequently Asked Questions about Natural Gas Regulation

    Office of Energy Efficiency and Renewable Energy (EERE)

    Can I get a copy of (a specific application, order, quarterly report, etc.)?Yes. All documents submitted to and developed by us are available online to the public. We do ask that you keep your...

  3. Assessing forecast uncertainties in a VECX model for Switzerland: an exercise in forecast combination across models and observation windows

    E-Print Network [OSTI]

    Assenmacher-Wesche, Katrin; Pesaran, M. Hashem

    horizons of up to eight quarters ahead since this is the rele- vant time horizon for central banks when setting interest rates. Table 6 shows the RMSFE, the bias and the hit rate of forecasts based on the VECX*(2,2) model for the longest estimation window...

  4. Forecasting future oil production in Norway and the UK: a general improved methodology

    E-Print Network [OSTI]

    Fievet, Lucas; Cauwels, Peter; Sornette, Didier

    2014-01-01

    We present a new Monte-Carlo methodology to forecast the crude oil production of Norway and the U.K. based on a two-step process, (i) the nonlinear extrapolation of the current/past performances of individual oil fields and (ii) a stochastic model of the frequency of future oil field discoveries. Compared with the standard methodology that tends to underestimate remaining oil reserves, our method gives a better description of future oil production, as validated by our back-tests starting in 2008. Specifically, we predict remaining reserves extractable until 2030 to be 188 +/- 10 million barrels for Norway and 98 +/- 10 million barrels for the UK, which are respectively 45% and 66% above the predictions using the standard methodology.

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2000-08-31

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

  6. Assessment and added value estimation of an ensemble approach with a focus on global radiation forecasts

    E-Print Network [OSTI]

    Bouallegue, Zied Ben

    2015-01-01

    The assessment of the high-resolution ensemble weather prediction system COSMO-DE-EPS is achieved with the perspective of using it for renewable energy applications. The performance of the ensemble forecast is explored focusing on global radiation, the main weather variable affecting solar power production, and on quantile forecasts, key probabilistic products for the energy sector. First, the ability of the ensemble system to capture and resolve the observation variability is assessed. Secondly, the potential benefit of the ensemble forecasting strategy compared to a single forecast approach is quantitatively estimated. A new metric called ensemble added value is proposed, aiming at a fair comparison of an ensemble forecast with a single forecast, when optimized to the users' needs. Hourly mean forecasts are verified against pyranometer measurements over verification periods covering 2013. The results show in particular that the added value of the ensemble approach is season-dependent and increases with the ...

  7. ENERGY-SPECIFIC SOLAR RADIATION DATA FROM MSG: CURRENT STATUS OF THE HELIOSAT-3 PROJECT

    E-Print Network [OSTI]

    Heinemann, Detlev

    ENERGY-SPECIFIC SOLAR RADIATION DATA FROM MSG: CURRENT STATUS OF THE HELIOSAT-3 PROJECT Marion Solar energy technologies such as photovoltaics, solar thermal power plants, passive solar heating and operating of solar energy systems and as basis data set for electricity load forecasting. Both long term

  8. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatist...

    E-Print Network [OSTI]

    Raftery, Adrian

    permission. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatist... Yulia Gel; Adrian

  9. 10 Questions for a Chemical Engineer: Alan Zacher | Department...

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

    10 Questions for a Chemical Engineer: Alan Zacher 10 Questions for a Chemical Engineer: Alan Zacher March 24, 2011 - 1:39pm Addthis Chemical engineer Alan Zacher Chemical engineer...

  10. 10 Questions for a Materials Scientist: Mr. Rare Earth -- Dr...

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

    10 Questions for a Materials Scientist: Mr. Rare Earth -- Dr. Karl A. Gschneidner, Jr. 10 Questions for a Materials Scientist: Mr. Rare Earth -- Dr. Karl A. Gschneidner, Jr. April...

  11. Have a Question About Energy Efficiency or Renewable Energy?...

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

    a Question About Energy Efficiency or Renewable Energy? Ask Ener-Gee Whiz Have a Question About Energy Efficiency or Renewable Energy? Ask Ener-Gee Whiz May 26, 2009 - 4:37pm...

  12. What Questions Do You Have About 'Energy Basics'?

    Broader source: Energy.gov [DOE]

    Energy Basics is a resource to help answer all of your "basic" questions about energy efficiency and renewable energy technologies.

  13. Questions and Answers from Storage Pre-Solicitation Meeting

    Broader source: Energy.gov [DOE]

    Questions and Answers from "Grand Challenge" Hydrogen Storage Pre-Solicitation Meeting held June 19, 2003 in Washington, DC

  14. Oceanic stochastic parametrizations in a seasonal forecast system

    E-Print Network [OSTI]

    Andrejczuk, M; Juricke, S; Palmer, T N; Weisheimer, A; Zanna, L

    2015-01-01

    We study the impact of three stochastic parametrizations in the ocean component of a coupled model, on forecast reliability over seasonal timescales. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the Stochastically Perturbed Parametrization Tendency (SPPT) scheme - which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely the western boundary currents and the Southern Ocean. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error. Whilst there are good grounds for implementing stochastic schemes in ocean models, our results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.

  15. Numerical Weather Forecasting at the Savannah River Site

    SciTech Connect (OSTI)

    Buckley, R.L. [Westinghouse Savannah River Company, AIKEN, SC (United States)

    1998-11-01

    Weather forecasts at the Savannah River Site (SRS) are important for applications to emergency response. The fate of accidentally-released radiological materials and toxic chemicals can be determined by providing wind and turbulence input to atmospheric transport models. This operation has been routinely performed at SRS using the WIND System, a system of computer models and monitors which collect data from towers situated throughout the SRS. However, the information provided to these models is spatially homogeneous (in one or two dimensions) with an elementary forecasting capability. This paper discusses the use of an advanced three-dimensional prognostic numerical model to provide space and time-dependent meteorological data for use in the WIND System dispersion models. The extensive meteorological data collection at SRS serves as a ground truth for further model development as well as for use in other applications.

  16. Questions and Answers For PON-10-604

    E-Print Network [OSTI]

    in this program. 4. QUESTION: Where can interested parties find information regarding incentives for CNG vehicles in vehicle applications where ARB certifies the engine rather than the vehicle. 6. QUESTION: Are CNG street sweepers (30,000 ~ 32,000 lbs GVWR) eligible for the $32,000 incentive? ANSWER: Yes. 7. QUESTION: Are CNG

  17. Weather Forecast Data an Important Input into Building Management Systems 

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01

    Implementation and Operational Services Section Canadian Meteorological Centre, Dorval, Qc National Prediction Operations Division ICEBO 2013, Montreal, Qc October 10 2013 Version 2013-09-27 Weather Forecast Data An Important Input into Building..., Martin Fradette Environment Canada RPN ? Recherche en Pr?vision num?rique Dr. Wei Yu, Dr. Paul Vaillancourt, Dr. Sylvie Leroyer Natural Resources Canada ? Canmet Energy Dr. Jos? A. Candanedo Overview ? Building management and weather information...

  18. Numerical weather forecasting at the Savannah River Site

    SciTech Connect (OSTI)

    Buckley, R.L. [Westinghouse Savannah River Site, Aiken, SC (United States)

    1998-12-31

    Weather forecasts at the Savannah River Site (SRS) are important for applications to emergency response. The fate of accidentally released radiological materials and toxic chemicals can be determined by providing wind and turbulence input to atmospheric transport models. This operation has been routinely performed at SRS using the WIND system, a system of computer models and monitors that collects data from towers situated throughout the SRS. However, the information provided to these models is spatially homogeneous (in one or two dimensions) with an elementary forecasting capability. This paper discusses the use of an advanced three-dimensional prognostic numerical model to provide space- and time-dependent meteorological data for use in the WIND system dispersion models. The extensive meteorological data collection at SRS serves as a ground truth for further model development as well as for use in other applications. A prognostic mesoscale model, the regional atmospheric modeling system (RAMS), is used to provide these forecasts. Use of RAMS allows for incorporation of mesoscale features such as the sea breeze, which has been shown to affect local weather conditions. This paper discusses the mesoscale model and its configuration for the operational simulation, as well as an application using a dispersion model at the SRS.

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

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

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

  20. Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill

    SciTech Connect (OSTI)

    Shukla, Shraddhanand; Voisin, Nathalie; Lettenmaier, D. P.

    2012-08-15

    We investigated the contribution of medium range weather forecasts with lead times up to 14 days to seasonal hydrologic prediction skill over the Conterminous United States (CONUS). Three different Ensemble Streamflow Prediction (ESP)-based experiments were performed for the period 1980-2003 using the Variable Infiltration Capacity (VIC) hydrology model to generate forecasts of monthly runoff and soil moisture (SM) at lead-1 (first month of the forecast period) to lead-3. The first experiment (ESP) used a resampling from the retrospective period 1980-2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast) or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts, for runoff (SM) forecasts generally varies from 0 to 0.8 (0 to 0.5) as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

  1. Incorporation of 3D Shortwave Radiative Effects within the Weather Research and Forecasting Model

    SciTech Connect (OSTI)

    O'Hirok, W.; Ricchiazzi, P.; Gautier, C.

    2005-03-18

    A principal goal of the Atmospheric Radiation Measurement (ARM) Program is to understand the 3D cloud-radiation problem from scales ranging from the local to the size of global climate model (GCM) grid squares. For climate models using typical cloud overlap schemes, 3D radiative effects are minimal for all but the most complicated cloud fields. However, with the introduction of ''superparameterization'' methods, where sub-grid cloud processes are accounted for by embedding high resolution 2D cloud system resolving models within a GCM grid cell, the impact of 3D radiative effects on the local scale becomes increasingly relevant (Randall et al. 2003). In a recent study, we examined this issue by comparing the heating rates produced from a 3D and 1D shortwave radiative transfer model for a variety of radar derived cloud fields (O'Hirok and Gautier 2005). As demonstrated in Figure 1, the heating rate differences for a large convective field can be significant where 3D effects produce areas o f intense local heating. This finding, however, does not address the more important question of whether 3D radiative effects can alter the dynamics and structure of a cloud field. To investigate that issue we have incorporated a 3D radiative transfer algorithm into the Weather Research and Forecasting (WRF) model. Here, we present very preliminary findings of a comparison between cloud fields generated from a high resolution non-hydrostatic mesoscale numerical weather model using 1D and 3D radiative transfer codes.

  2. PScout: Analyzing the Android Permission Specification Kathy Wain Yee Au

    E-Print Network [OSTI]

    Lie, David

    PScout: Analyzing the Android Permission Specification by Kathy Wain Yee Au A thesis submitted PScout: Analyzing the Android Permission Specification Kathy Wain Yee Au Master of Applied Science of the Android permission system in an attempt to begin answering some of the questions that have arisen about

  3. Streams of Steam The Steam Boiler Specification Case Study

    E-Print Network [OSTI]

    Streams of Steam ­ The Steam Boiler Specification Case Study Manfred Broy, Franz Regensburger-tuned con- cepts of FOCUS by its application of the requirements specification of a steam boiler, see [Abr96-studies. In this context, applying FOCUS to the steam boiler case study ([Abr96]) led us to a couple of questions re- #12

  4. Specific Group Hardware

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

    Specific Group Hardware Specific Group Hardware ALICE palicevo1 The Virtual Organization (VO) server. Serves as gatekeeper for ALICE jobs. It's duties include getting assignments...

  5. Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

    2012-09-01

    Historically, a number of wind energy integration studies have investigated the value of using day-ahead wind power forecasts for grid operational decisions. These studies have shown that there could be large cost savings gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter-term (0 to 6-hour-ahead) wind power forecasts. In 2010, the Department of Energy and National Oceanic and Atmospheric Administration partnered to fund improvements in short-term wind forecasts and to determine the economic value of these improvements to grid operators, hereafter referred to as the Wind Forecasting Improvement Project (WFIP). In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined, then the economic results of a production cost model simulation are analyzed.

  6. Log-normal distribution based EMOS models for probabilistic wind speed forecasting

    E-Print Network [OSTI]

    Baran, Sándor

    2014-01-01

    Ensembles of forecasts are obtained from multiple runs of numerical weather forecasting models with different initial conditions and typically employed to account for forecast uncertainties. However, biases and dispersion errors often occur in forecast ensembles, they are usually under-dispersive and uncalibrated and require statistical post-processing. We present an Ensemble Model Output Statistics (EMOS) method for calibration of wind speed forecasts based on the log-normal (LN) distribution, and we also show a regime-switching extension of the model which combines the previously studied truncated normal (TN) distribution with the LN. Both presented models are applied to wind speed forecasts of the eight-member University of Washington mesoscale ensemble, of the fifty-member ECMWF ensemble and of the eleven-member ALADIN-HUNEPS ensemble of the Hungarian Meteorological Service, and their predictive performances are compared to those of the TN and general extreme value (GEV) distribution based EMOS methods an...

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

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01

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

  8. Research in thermal biology: Burning questions for coldwater stream fishes

    SciTech Connect (OSTI)

    McCullough, Dr. Dale [University of California, Berkeley; Bartholow, Dr. John [U.S. Department of Fish and Wildlife; Jager, Yetta [ORNL; al., et. [Various Institutes

    2009-01-01

    With the increasing appreciation of global warming impacts on ecological systems in addition to the myriad of land management effects on water quality, the number of literature citations dealing with the effects of water temperature on freshwater fish has escalated in the past decade. Given the many biological scales at which water temperature effects have been studied and the growing need to integrate knowledge from multiple disciplines of thermal biology to fully protect beneficial uses, we held that a survey of the most promising recent developments and an expression of some of the remaining unanswered questions with significant management implications would best be approached collectively by a diverse research community. We have identified five specific topic areas of renewed research where new techniques and critical thought could benefit coldwater stream fishes (particularly salmonids): molecular, organism, population/species, community and ecosystem, and policy issues in water quality. Our hope is that information gained through examination of recent research fronts linking knowledge at various scales will prove useful in managing water quality at a basin level to protect fish populations and whole ecosystems. Standards of the past were based largely on incipient lethal and optimum growth rate temperatures for fish species, while future standards should consider all integrated thermal impacts to the organism and ecosystem.

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

    Broader source: Energy.gov [DOE]

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

  10. Risk analysis for species introductions: forecasting population growth of Eurasian ruffe

    E-Print Network [OSTI]

    Risk analysis for species introductions: forecasting population growth of Eurasian ruffe productivity (Leung et al. 2002). Risk-analysis methodology for intentional and unintentional introductions

  11. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    Numerical Weather Prediction (NWP), Solar Forecasting  1.   to more accurate prediction of solar  irradiance, given a to create daily solar electricity predictions accurate to 

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

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01

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

  13. 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 .............................................................. 23 Electricity Demand Growth in the West............................................................................................................................... 28 Estimating Electricity Demand in Data Centers

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

    SciTech Connect (OSTI)

    2009-01-18

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

  15. Skill evaluation of water supply forecasts in western Sierra Nevada and Colorado River basins

    E-Print Network [OSTI]

    Harrison, Brent

    2014-01-01

    streamflow predictions for water supply forecasting in theAn assessment of seasonal water supply outlooks in thepaper, Dept. of Hydrology and Water Resources, University of

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

    approach to evaluating price risk would be to use suchthe base-case natural gas price forecast, but to alsorange of different plausible price projections, using either

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01

    range of different plausible price projections, using eitherthat renewables can provide price certainty over even longerof AEO 2009 Natural Gas Price Forecast to NYMEX Futures

  18. Neural network based short-term load forecasting using weather compensation

    SciTech Connect (OSTI)

    Chow, T.W.S.; Leung, C.T. [City Univ. of Hong Kong, Kowloon (Hong Kong). Dept. of Electronic Engineering] [City Univ. of Hong Kong, Kowloon (Hong Kong). Dept. of Electronic Engineering

    1996-11-01

    This paper presents a novel technique for electric load forecasting based on neural weather compensation. The proposed method is a nonlinear generalization of Box and Jenkins approach for nonstationary time-series prediction. A weather compensation neural network is implemented for one-day ahead electric load forecasting. The weather compensation neural network can accurately predict the change of actual electric load consumption from the previous day. The results, based on Hong Kong Island historical load demand, indicate that this methodology is capable of providing a more accurate load forecast with a 0.9% reduction in forecast error.

  19. Generating day-of-operation probabilistic capacity scenarios from weather forecasts

    E-Print Network [OSTI]

    Buxi, Gurkaran

    2012-01-01

    user needs for convective weather forecasts," in AmericanJ. Andrews M. Weber, "Weather Information Requirements forInt. Conf. on Aviation Weather, Paris, France. [5] NASDAC. (

  20. Conceptual Learning in Social Studies Classroom: An Analysis of Texas Assessment of Knowledge and Skills (TAKS) Social Studies Questions with and without Concept 

    E-Print Network [OSTI]

    Kilinc, Emin

    2012-07-16

    attainment is a cornerstone of social studies to help students to make informed and reasonable decisions and therefore is a fundamental and challenging aspect of social studies content. Previous studies had not focused specifically on concept questions...

  1. Forecast of Contracting and Subcontracting Opportunities, Fiscal year 1995

    SciTech Connect (OSTI)

    Not Available

    1995-02-01

    Welcome to the US Department of Energy`s Forecast of Contracting and Subcontracting Opportunities. This forecast, which is published pursuant to Public Low 100--656, ``Business Opportunity Development Reform Act of 1988,`` is intended to inform small business concerns, including those owned and controlled by socially and economically disadvantaged individuals, and women-owned small business concerns, of the anticipated fiscal year 1995 contracting and subcontracting opportunities with the Department of Energy and its management and operating contractors and environmental restoration and waste management contractors. This document will provide the small business contractor with advance notice of the Department`s procurement plans as they pertain to small, small disadvantaged and women-owned small business concerns.Opportunities contained in the forecast support the mission of the Department, to serve as advocate for the notion`s energy production, regulation, demonstration, conservation, reserve maintenance, nuclear weapons and defense research, development and testing, when it is a national priority. The Department`s responsibilities include long-term, high-risk research and development of energy technology, the marketing of Federal power, and maintenance of a central energy data collection and analysis program. A key mission for the Department is to identify and reduce risks, as well as manage waste at more than 100 sites in 34 states and territories, where nuclear energy or weapons research and production resulted in radioactive, hazardous, and mixed waste contamination. Each fiscal year, the Department establishes contracting goals to increase contracts to small business concerns and meet our mission objectives.

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

    SciTech Connect (OSTI)

    Valero, O.J.

    1996-10-03

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

  3. Streamflow forecasting for large-scale hydrologic systems 

    E-Print Network [OSTI]

    Awwad, Haitham Munir

    1991-01-01

    Farland (Member) J esTR ao (Head of Department) May 1991 ABSTRACT Streamflow Forecasting for Large-Scale Hydrologic Systems. (May 1991) Haitham Munir Awwad, B. S. , University of Jordan Chair of Advisory Committee: Dr. Juan B. Valdes An on-line streamflow... thankful to Dr. Ralph A. Wurbs and Dr. Marshall J. McFarland for their assistance on my advisory committee. Support for this thesis by the Department of Civil Engineering through the Engineering Excellence Fund, and by the U, S. Army Corps of Engineers...

  4. Frequently Asked Questions about the CALiPER Program

    Office of Energy Efficiency and Renewable Energy (EERE)

    This page addresses many of the questions manufacturers, testing laboratories, consumers, retailers, and energy efficiency program sponsors may have about the DOE SSL Commercially Available LED...

  5. Questions and Answers for the Smart Grid Investment Grant Program...

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

    Questions and answers related to the reporting of meter installations in the SmartGrid Integrated Project Reporting Information System (SIPRIS), both for the intial report and...

  6. Questions and Answers for the Smart Grid Investment Grant Program...

    Office of Environmental Management (EM)

    Retained in SIPRIS Questions and answers related to the reporting of jobs in the SmartGrid Integrated Project Reporting Information System (SIPRIS), both for the intial report...

  7. Sample Questions | U.S. DOE Office of Science (SC)

    Office of Science (SC) Website

    For Success Sample Questions Middle School Attending National Event Volunteers 2015 Competition Results News Media WDTS Home Contact Information National Science Bowl...

  8. Frequently Asked Questions (FAQs) for Fiscal Year (FY) 14 Brownfields...

    Open Energy Info (EERE)

    search OpenEI Reference LibraryAdd to library PermittingRegulatory Guidance - GuideHandbook: Frequently Asked Questions (FAQs) for Fiscal Year (FY) 14 Brownfields Assessment,...

  9. Microsoft Word - Amendment 000002 - Question & Answers.docx

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

    force weapons will be employed other than those listed. Question: The computer based training (CBT) modules that are required on the job, will they require additional coverage...

  10. Council on Environmental Quality - Forty Most Asked Questions...

    Open Energy Info (EERE)

    Council on Environmental Quality - Forty Most Asked Questions Concerning CEQ's NEPA Regulations Jump to: navigation, search OpenEI Reference LibraryAdd to library Memorandum:...

  11. #AskEnergySaver: Answering Your Fuel Efficiency Questions | Department...

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

    Laboratories, our scientists and engineers are looking for ways to help Americans save money by saving energy. These experts are answering your questions and sharing their...

  12. Facilitated Discussion Questions (in blue font) and input from...

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

    and summarized by the Facilitator (in black font) Question 1: Biggest challenge to integration and alignment- For information exchange to prosper between buildings devices,...

  13. Asking the Right Questions for a NEPA Review: An Environmental...

    Office of Environmental Management (EM)

    for a NEPA Review: An Environmental Questionnaire for Funding Proposals Asking the Right Questions for a NEPA Review: An Environmental Questionnaire for Funding Proposals...

  14. Inclusion of In-Situ Velocity Measurements into the UCSD Time-Dependent Tomography to Constrain and Better-Forecast Remote-Sensing Observations

    E-Print Network [OSTI]

    Jackson, B. V.; Hick, P. P.; Bisi, M. M.; Clover, J. M.; Buffington, A.

    2010-01-01

    time”. The solar-wind velocity forecast 24 hours ahead of72-hour forecast volume using the extant solar-wind model.forecast. In-situ data have been the primary measurements available for study of solar-wind

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

    SciTech Connect (OSTI)

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

    1994-05-01

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

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

    SciTech Connect (OSTI)

    Finley, Cathy

    2014-04-30

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

  17. Fitting and forecasting non-linear coupled dark energy

    E-Print Network [OSTI]

    Casas, Santiago; Baldi, Marco; Pettorino, Valeria; Vollmer, Adrian

    2015-01-01

    We consider cosmological models in which dark matter feels a fifth force mediated by the dark energy scalar field, also known as coupled dark energy. Our interest resides in estimating forecasts for future surveys like Euclid when we take into account non-linear effects, relying on new fitting functions that reproduce the non-linear matter power spectrum obtained from N-body simulations. We obtain fitting functions for models in which the dark matter-dark energy coupling is constant. Their validity is demonstrated for all available simulations in the redshift range $z=0-1.6$ and wave modes below $k=10 \\text{h/Mpc}$. These fitting formulas can be used to test the predictions of the model in the non-linear regime without the need for additional computing-intensive N-body simulations. We then use these fitting functions to perform forecasts on the constraining power that future galaxy-redshift surveys like Euclid will have on the coupling parameter, using the Fisher matrix method for galaxy clustering (GC) and w...

  18. 6.9 A NEW APPROACH TO FIRE WEATHER FORECASTING AT THE TULSA WFO

    E-Print Network [OSTI]

    6.9 A NEW APPROACH TO FIRE WEATHER FORECASTING AT THE TULSA WFO Sarah J. Taylor* and Eric D. Howieson NOAA/National Weather Service Tulsa, Oklahoma 1. INTRODUCTION The modernization of the National then providesthemeteorologistanopportunitytoadjustmodel forecasts for local biases and terrain effects. The Tulsa, Oklahoma WFO has been a test office

  19. FORECASTING EMPLOYMENT & POPULATION IN TEXAS: An Investigation on TELUM Requirements, Assumptions, and Results, including a Study

    E-Print Network [OSTI]

    Kockelman, Kara M.

    -convex, non-linear optimization problem, which maximizes the entropy and thus the likelihood of the data and then compared with the district-based forecasts. The comparison showed some stark differences. For example distribution of low income households in Austin was completely different for district- and TAZ-based forecasts

  20. MM5 Contrail Forecasting in Alaska Martin Stuefer, Xiande Meng and Gerd Wendler

    E-Print Network [OSTI]

    Stuefer, Martin

    MM5 Contrail Forecasting in Alaska Martin Stuefer, Xiande Meng and Gerd Wendler Geophysical Institute, University of Alaska, Fairbanks 1. Abstract Fifth-generation mesoscale model (MM5) is being used air. Algorithm input data are MM5 forecasted temperature and humidity values at defined pressure

  1. Next Generation Short-Term Forecasting of Wind Power Overview of the ANEMOS Project.

    E-Print Network [OSTI]

    Boyer, Edmond

    1 Next Generation Short-Term Forecasting of Wind Power ­ Overview of the ANEMOS Project. G outperform current state-of-the-art methods, for onshore and offshore wind power forecasting. Advanced and evaluation at a local, regional and national scale. Finally, the project demonstrates the value of wind

  2. Forecasting the Growth of Green Power Markets in the United States

    E-Print Network [OSTI]

    Forecasting the Growth of Green Power Markets in the United States October 2001 · NREL/TP-620-99-GO10337 October 2001 · NREL/TP-620-30101 · LBNL-48611 Forecasting the Growth of Green Power Markets, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any

  3. 1 Ozone pollution forecasting 3 Herve Cardot, Christophe Crambes and Pascal Sarda.

    E-Print Network [OSTI]

    Crambes, Christophe

    Contents 1 Ozone pollution forecasting 3 Herv´e Cardot, Christophe Crambes and Pascal Sarda. 1;1 Ozone pollution forecasting using conditional mean and conditional quantiles with functional covariates Herv´e Cardot, Christophe Crambes and Pascal Sarda. 1.1 Introduction Prediction of Ozone pollution

  4. FORECASTING OF ATLANTIC TROPICAL CYCLONES USING A KILO-MEMBER ENSEMBLE

    E-Print Network [OSTI]

    Schubert, Wayne H.

    system using an efficient multigrid barotropic vorticity equation model (MBAR). Five perturbation classes Advisor Department Head ii #12;ABSTRACT OF THESIS FORECASTING OF ATLANTIC TROPICAL CYCLONES USING A KILO forecasts. These increases have been largely driven by improved numerical weather prediction models

  5. Seasonal Sensitivity on COBEL-ISBA Local Forecast System for Fog and Low Clouds

    E-Print Network [OSTI]

    Seasonal Sensitivity on COBEL-ISBA Local Forecast System for Fog and Low Clouds STEVIE ROQUELAURE of uncertainty that lead to dispersion. Key words: Local numerical forecast system, fog and low clouds, seasonal prediction system. 1. Introduction Accurate prediction of fog and low clouds is one of the main issues

  6. FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2014

    E-Print Network [OSTI]

    Connors, Daniel A.

    1 FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND LANDFALL STRIKE PROBABILITY FOR 2014 We are higher than normal, and vertical wind shear throughout the Atlantic basin has been much stronger than-period average values. (as of 31 July 2014) By Philip J. Klotzbach1 and William M. Gray2 This forecast as well

  7. Forecast of solar ejecta arrival at 1 AU from radial speed S. Dasso1,2

    E-Print Network [OSTI]

    Dasso, Sergio

    Forecast of solar ejecta arrival at 1 AU from radial speed S. Dasso1,2 , N. Gopalswamy1 and A. Lara of the major requirements to forecast the space weather conditions in the terrestrial envi- ronment. Several properties, such as the background solar wind speed, and the density of the ejecta. However, only a few

  8. Global and multi-scale features of solar wind-magnetosphere coupling: From modeling to forecasting

    E-Print Network [OSTI]

    Sitnov, Mikhail I.

    Global and multi-scale features of solar wind-magnetosphere coupling: From modeling to forecasting issue. This paper presents a data-derived model of the solar wind-magnetosphere coupling that combines of solar wind-magnetosphere coupling: From modeling to forecasting, Geophys. Res. Lett., 31, L08802, doi:10

  9. Continuous Motion Planning for Information Forecast Han-Lim Choi and Jonathan P. How

    E-Print Network [OSTI]

    Continuous Motion Planning for Information Forecast Han-Lim Choi and Jonathan P. How Abstract-- This paper addresses planning of continuous paths for mobile sensors to improve long-term forecast of the process noise. Utilizing the spatial interpolation technique to relate the sensor movement

  10. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

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

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

    2015-06-23

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

  11. A Novel Forecasting System for Solar Particle Events and Flares (FORSPEF)

    E-Print Network [OSTI]

    Anastasiadis, Anastasios

    A Novel Forecasting System for Solar Particle Events and Flares (FORSPEF) A Papaioannou1 Energetic Particles (SEPs) result from intense solar eruptive events such as solar flares and coronal mass. In this work, we present FORSPEF (Forecasting Solar Particle Events and Flares), a novel dual system, designed

  12. Impact of forecasting error on the performance of capacitated multi-item production systems

    E-Print Network [OSTI]

    Xie, Jinxing

    in manufacturing planning and control. The quality of the master production schedule (MPS) can significantly managers optimize their production plans by selecting more reasonable forecasting methods and scheduling forecasting, order entry and production planning activities on the one hand, and the detailed planning

  13. Employment Forecasts for Ohio's Primary Metals Manufacturing and Administrative and Support Services Industries

    E-Print Network [OSTI]

    Illinois at Chicago, University of

    that are outperforming the industry average. Additional research shows that the industry is reactive to manufacturingEmployment Forecasts for Ohio's Primary Metals Manufacturing and Administrative and Support, the primary metals manufacturing industry (NAICS 331000) employment in Ohio is forecasted to decline by 21

  14. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching

    E-Print Network [OSTI]

    Genton, Marc G.

    Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at a wind energy site and fits a conditional predictive model for each regime. Geographically dispersed was applied to 2-hour-ahead forecasts of hourly average wind speed near the Stateline wind energy center

  15. Ensemble-based air quality forecasts: A multimodel approach applied to ozone

    E-Print Network [OSTI]

    Mallet, Vivien

    Ensemble-based air quality forecasts: A multimodel approach applied to ozone Vivien Mallet1 21 September 2006. [1] The potential of ensemble techniques to improve ozone forecasts ozone-monitoring networks. We found that several linear combinations of models have the potential

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  17. Hourly Temperature Forecasting Using Abductive Networks R. E. Abdel-Aal

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Review Copy 1 Hourly Temperature Forecasting Using Abductive Networks R. E. Abdel-Aal Center temperatures, Artificial intelligence. Dr. R. E. Abdel-Aal, P. O. Box 1759, KFUPM, Dhahran 31261 Saudi Arabia e; Khotanzad, Afkhami-Rohani & Maratukulam, 1998; Sharif & Taylor, 2000; Xu & Chen, 1999). Such forecasts

  18. Biennial Assessment of the Fifth Power Plan Interim Report on Electric Price Forecasts

    E-Print Network [OSTI]

    Biennial Assessment of the Fifth Power Plan Interim Report on Electric Price Forecasts Electricity prices in the Council's Power Plan are forecast using the AURORATM Electricity Market Model of the entire prices at several pricing points in the West, four of which are in the Pacific Northwest. The one most

  19. Tiree Energy Pulse: Exploring Renewable Energy Forecasts on the Edge of the Grid

    E-Print Network [OSTI]

    MacDonald, Mark

    Tiree Energy Pulse: Exploring Renewable Energy Forecasts on the Edge of the Grid Will Simm1 , Maria energy consumption with supply, and together built a prototype renewable energy forecast display. A num local renewable energy was expected to be available, despite having no financial in- centive to do so

  20. Improving Energy Use Forecast for Campus Micro-grids using Indirect Indicators Department of Computer Science

    E-Print Network [OSTI]

    Hwang, Kai

    peak demand periods using pricing incentives. Reliable building energy forecast models can help predictImproving Energy Use Forecast for Campus Micro-grids using Indirect Indicators Saima Aman prasanna@usc.edu Abstract--The rising global demand for energy is best addressed by adopting and promoting

  1. DEGREE DAYS AND WEATHER NOTES Weather Forecast: Chance of showers and storms through

    E-Print Network [OSTI]

    Isaacs, Rufus

    1 DEGREE DAYS AND WEATHER NOTES Weather Forecast: Chance of showers and storms through Thursday by ~225. Complete weather summaries and forecasts are at available enviroweather.msu.edu GDD (from March 1.isaacslab.ent.msu.edu/blueberryscout/blueberryscout.htm Contents · Crop Stages · Weather Notes · Disease Update · Scouting the Major Diseases of Highbush

  2. Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization

    E-Print Network [OSTI]

    Nocedal, Jorge

    Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization M. Fisher J weather prediction centers to produce the initial conditions for 7- to 10-day weather fore- casts, with particular reference to the system in operation at the European Centre for Medium-Range Weather Forecasts. 1

  3. NH13A: No-source tsunami forecasting for Alaska communities

    E-Print Network [OSTI]

    Tolkova, Elena

    NH13A: No-source tsunami forecasting for Alaska communities Dmitry Nicolsky (UAF) djnicolsky://nctr.pmel.noaa.gov/ Wave trains to Alaska: direction structure (time history) tsunami source R E S P and accurate regional tsunami forecasts · A deep-ocean detector and a coastal site can be connected

  4. Towards Long-lead Forecasting of Extreme Flood Events: A Data Mining Framework for Precipitation Cluster

    E-Print Network [OSTI]

    Ding, Wei

    Towards Long-lead Forecasting of Extreme Flood Events: A Data Mining Framework for Precipitation of precipitation events occurring over from several days to several weeks. Though precise short- term forecasting of precipitation clusters can be attempted by identifying persistent atmospheric regimes that are conducive

  5. Extendedrange seasonal hurricane forecasts for the North Atlantic with a hybrid dynamicalstatistical model

    E-Print Network [OSTI]

    Webster, Peter J.

    Extendedrange seasonal hurricane forecasts for the North Atlantic with a hybrid 20 September 2010; published 9 November 2010. [1] A hybrid forecast model for seasonal hurricane between the number of seasonal hurricane and the large scale variables from ECMWF hindcasts. The increase

  6. Truth in Mathematics: The Question of Peter Koellner

    E-Print Network [OSTI]

    Koellner, Peter

    Truth in Mathematics: The Question of Pluralism Peter Koellner ". . . before us lies the boundless. This will involve mapping out some mathematical scenarios (using recent results proved jointly with Hugh Woodin notational questions), both his pluralism in physics and his pluralism in mathematics are untenable

  7. 2Name ________________________________ Question 1: What is the usable area

    E-Print Network [OSTI]

    the area of a satellite solar panel and estimate the total electrical power that can be generated. Students, the maximum panel area is 12,240 sq. cm, so (8100/12240)x100% = 66% of the panel is covered by solar cells shown below? Question 2: What electrical power can be generated by the panel? Question 3: If there are 8

  8. THE JIKITOU BIOMEDICAL QUESTION ANSWERING SYSTEM: FACILITATINGTHE NEXT STAGE IN

    E-Print Network [OSTI]

    Berleant, Daniel

    THE JIKITOU BIOMEDICAL QUESTION ANSWERING SYSTEM: FACILITATINGTHE NEXT STAGE IN THE EVOLUTION by Michael Anton Bauer 2013 #12;This thesis, The Jikitou Biomedical Question Answering System: Facilitating, M.D. Associate Professor and Chief in Division of Biomedical Informatics Radhakrishnan Nagarajan, Ph

  9. Probabilistic Precipitation Forecast Skill as a Function of Ensemble Size and Spatial Scale in a Convection-Allowing Ensemble

    E-Print Network [OSTI]

    Xue, Ming

    Probabilistic Precipitation Forecast Skill as a Function of Ensemble Size and Spatial Scale decreases. These results appear to reflect the broadening of the forecast probability distribution function lead time. They also illustrate that efficient allocation of computing resources for convection

  10. Comment on `Testing earthquake prediction methods: "The West Pacific short-term forecast of earthquakes with magnitude MwHRV >= 5.8"' by V. G. Kossobokov

    E-Print Network [OSTI]

    Kagan, Yan Y; Jackson, David D

    2006-01-01

    tensor solutions for 1087 earthquakes, Phys. Earth Planet.and time-independent earthquake forecast models for southernKagan, 1999. Testable earthquake forecasts for 1999, Seism.

  11. Load forecasting for active distribution networks Simone Paoletti, Member, IEEE, Marco Casini, Member, IEEE, Antonio Giannitrapani, Member, IEEE,

    E-Print Network [OSTI]

    Giannitrapani, Antonello

    forecasting for distribution networks with Active Demand (AD), a new concept in smart-grids introduced within

  12. Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01

    System (REEPS 2.1) , developed by the Electric Power Research Institute (EPRI), is a forecasting model

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

    Broader source: Energy.gov [DOE]

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

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2005-08-17

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

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

    SciTech Connect (OSTI)

    Thomas, L.C.

    1994-10-01

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

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

    SciTech Connect (OSTI)

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

    2005-02-09

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

  17. UNH Cooperative Extension Info Line Question of the Week Question: How can I control poison ivy without using chemical herbicides?

    E-Print Network [OSTI]

    New Hampshire, University of

    UNH Cooperative Extension Info Line Question of the Week Poison Ivy Question: How can I control poison ivy without using chemical herbicides? Answer: Controlling poison ivy is difficult, and it may goats or sheep feed on your poison ivy. This can keep plants from getting too big. One way to manage

  18. Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications

    E-Print Network [OSTI]

    Niyogi, Dev

    (GEM) for Mesoscale Weather Forecasting Applications DEV NIYOGI Department of Agronomy, and Department form 13 May 2008) ABSTRACT Current land surface schemes used for mesoscale weather forecast models use model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM

  19. J2.6 A SPATIAL DATA MINING APPROACH FOR VERIFICATION AND UNDERSTANDING OF ENSEMBLE PRECIPITATION FORECASTING

    E-Print Network [OSTI]

    Gruenwald, Le

    FORECASTING Xuechao Yu* 1,2 and Ming Xue 2,3 1 NOAA/NWS/WDTB Cooperative Institute for Mesoscale is placed on meso- scale ensemble forecasting in recent years [e.g., the Storm and Mesoscale Ensemble complicated for mesoscale quantitative precipitation forecast (QPF), since QPF is a discontinuous field. Em

  20. Towards a Self-Configurable Weather Research and Forecasting System Khalid Saleem, S. Masoud Sadjadi, Shu-Ching Chen

    E-Print Network [OSTI]

    Chen, Shu-Ching

    Towards a Self-Configurable Weather Research and Forecasting System Khalid Saleem, S. Masoud, Miami FL {ksale002, sadjadi,chens}@cs.fiu.edu ABSTRACT Current weather forecast and visualization systems lack the scalability to support numerous customized requests for weather research and forecasting