Sample records for monthly short-term forecasts

  1. Short-term planning and forecasting for petroleum. Master's thesis

    SciTech Connect (OSTI)

    Elkins, R.D.

    1988-06-01T23:59:59.000Z

    The Defense Fuel Supply Center (DFSC) has, in recent past, been unable to adequately forecast for short-term petroleum requirements. This has resulted in inaccurate replenishment quantities and required short-notice corrections, which interrupted planned resupply methods. The relationship between the annual CINCLANTFLT DFM budget and sales from the the Norfolk Defense Fuel Support Point (DFSP) is developed and the past sales data from the Norfolk DFSP is used to construct seasonality indices. Finally, the budget/sales relationship is combined with the seasonality indices to provide a new forecasting model. The model is then compared with the current one for FY-88 monthly forecasts. The comparison suggests that the new model can provide accurate, timely requirements data and improve resupply of the Norfolk Defense Fuel Support Point.

  2. A model for short term electric load forecasting

    E-Print Network [OSTI]

    Tigue, John Robert

    1975-01-01T23:59:59.000Z

    A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE, III Submitted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE May 1975 Major... Subject: Electrical Engineering A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE& III Approved as to style and content by: (Chairman of Committee) (Head Depart t) (Member) ;(Me r (Member) (Member) May 1975 ABSTRACT...

  3. Short term forecasting of solar radiation based on satellite data

    E-Print Network [OSTI]

    Heinemann, Detlev

    Short term forecasting of solar radiation based on satellite data Elke Lorenz, Annette Hammer University, D-26111 Oldenburg Forecasting of solar irradiance will become a major issue in the future integration of solar energy resources into existing energy supply structures. Fluctuations of solar irradiance

  4. 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

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

    E-Print Network [OSTI]

    Wickham, Richard Robert

    1995-01-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2014-05-01T23:59:59.000Z

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

  7. SHORT-TERM FORECASTING OF SOLAR RADIATION BASED ON SATELLITE DATA WITH STATISTICAL METHODS

    E-Print Network [OSTI]

    Heinemann, Detlev

    SHORT-TERM FORECASTING OF SOLAR RADIATION BASED ON SATELLITE DATA WITH STATISTICAL METHODS Annette governing the insolation, forecasting of solar radiation makes the description of development of the cloud

  8. ANN-based Short-Term Load Forecasting in Electricity Markets

    E-Print Network [OSTI]

    Cañizares, Claudio A.

    ANN-based Short-Term Load Forecasting in Electricity Markets Hong Chen Claudio A. Ca~nizares Ajit1 Abstract--This paper proposes an Artificial Neu- ral Network (ANN)-based short-term load forecasting, electricity markets, spot prices, Artificial Neural Networks (ANN) I. Introduction Short

  9. Short-term load forecasting using generalized regression and probabilistic neural networks in the electricity market

    SciTech Connect (OSTI)

    Tripathi, M.M.; Upadhyay, K.G.; Singh, S.N.

    2008-11-15T23:59:59.000Z

    For the economic and secure operation of power systems, a precise short-term load forecasting technique is essential. Modern load forecasting techniques - especially artificial neural network methods - are particularly attractive, as they have the ability to handle the non-linear relationships between load, weather temperature, and the factors affecting them directly. A test of two different ANN models on data from Australia's Victoria market is promising. (author)

  10. Short-term Forecasting of Offshore Wind Farm Production Developments of the Anemos Project

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Short-term Forecasting of Offshore Wind Farm Production ­ Developments of the Anemos Project J to the large dimensions of offshore wind farms, their electricity production must be known well in advance networks) models were calibrated on power data from two offshore wind farms: Tunoe and Middelgrunden

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

    SciTech Connect (OSTI)

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

    2012-09-01T23:59:59.000Z

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

  12. Probabilistic wind power forecasting -European Wind Energy Conference -Milan, Italy, 7-10 May 2007 Probabilistic short-term wind power forecasting

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Probabilistic wind power forecasting - European Wind Energy Conference - Milan, Italy, 7-10 May 2007 Probabilistic short-term wind power forecasting based on kernel density estimators J´er´emie Juban jeremie.juban@ensmp.fr; georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting tools

  13. Short-Term Energy Outlook Supplement: Uncertainties in the Short-Term Global Petroleum and Other Liquids Supply Forecast

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSettingUncertainties in the Short-Term

  14. Research on Short-term Load Forecasting of the Thermoelectric Boiler Based on a Dynamic RBF Neural Network 

    E-Print Network [OSTI]

    Dai, W.; Zou, P.; Yan, C.

    2006-01-01T23:59:59.000Z

    As thermal inertia is the key factor for the lag of thermoelectric utility regulation, it becomes very important to forecast its short-term load according to running parameters. In this paper, dynamic radial basis function (RBF) neural network...

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

    Reports and Publications (EIA)

    1998-01-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2007-12-01T23:59:59.000Z

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

  17. Short Term Hourly Load Forecasting Using Abductive Networks R. E. Abdel-Aal

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Physical Sciences, Research Institute, King Fahd University of Petroleum and Minerals, Dhahran, Saudi for forecasting next-day hourly loads have been developed. Evaluated on data for the 6th year, the models give. INTRODUCTION Accurate load forecasting is a key requirement for the planning and economic and secure operation

  18. Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Lew, D.; Milligan, M.

    2013-01-01T23:59:59.000Z

    Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of the day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.

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

    E-Print Network [OSTI]

    Boyer, Edmond

    of difficulties to the power system operation. This is due to the fluctuating nature of wind generation to the management of wind generation. Accurate and reliable forecasting systems of the wind production are widely

  20. Freeway Short-Term Traffic Flow Forecasting by Considering Traffic Volatility Dynamics and Missing Data Situations

    E-Print Network [OSTI]

    Zhang, Yanru

    2012-10-19T23:59:59.000Z

    , assuming constant variance when perform forecasting. This method does not consider the volatility nature of traffic flow data. This paper demonstrated that the variance part of traffic flow data is not constant, and dependency exists. A volatility model...

  1. Short-term Wind Power Forecasting Using Advanced Statistical T.S. Nielsen1

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    , in order to be able to absorb a large fraction of wind power in the electrical systems reliable short from refer- ence MET forecasts to the actual wind farm, wind farm power curve models, dynamical models of art wind power prediction system is outlined in Section 2. Numerical Weather Prediction (NWP

  2. Short-term forecasting through intermittent assimilation of data from Taiwan and mainland China coastal radars

    E-Print Network [OSTI]

    Xue, Ming

    ; published 29 March 2012. [1] Radial velocity (Vr) and reflectivity (Z) data from eight coastal operational, but the benefit is mostly lost within the first hour of forecast. Assimilating data from a single Doppler radar with a good coverage of the typhoon inner core region is also quite effective, but it takes one more cycle

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

    SciTech Connect (OSTI)

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

    2012-09-01T23:59:59.000Z

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

  4. Development of Short-term Demand Forecasting Model Application in Analysis of Resource Adequacy

    E-Print Network [OSTI]

    calculated. Peak load and energy load for all months were ranked and top 5th percentile load were used

  5. Experimental short-term climate forecasting procedure for US winter temperatures and its verification

    SciTech Connect (OSTI)

    Navato, A.R.

    1981-01-01T23:59:59.000Z

    A linear multivariate regression model for continental United States Januray surface air temperatures is presented. The predictors enter the regression equation at more than one lag if their effects on the predictand tend to be spread over several months rather than be completed in one month. The monthly mean surface tempertures for 12 cities were taken to be representative of temperatures for the regions around them. The predictand series then consisted of annual January values for each representative city. A separate regression equation was derived for the annual departures from the long term means for January for each city. The procedure therefore predicts the inter-annual variability for January. The regression equations for inter-annual variability were able to explain a much higher percentage of variance compared to the corresponding regression equations for monthly variability. The same procedure can be applied to obtain prediction equations for other months. The higher percentage is to be expected if it is considered that there must be differences in the operation of temperature-controlling physical mechanisms which are dependent on the march of the seasons.

  6. Prediction of wind speed profiles for short-term forecasting in the offshore environment R.J. Barthelmie and G. Giebel

    E-Print Network [OSTI]

    in planning of maintenance visits to offshore wind farms. In most cases the basis for the predictionPrediction of wind speed profiles for short-term forecasting in the offshore environment R wind farms. The main effects considered here are: wind speed gradients in the coastal zone, vertical

  7. Seismic Activity of the Earth, the Cosmological Vectorial Potential And Method of a Short-term Earthquakes Forecasting

    E-Print Network [OSTI]

    Yu. A. Baurov; Yu. A. Baurov; Yu. A. Baurov Jr.; A. A. Spitalnaya; A. A. Abramyan; V. A. Solodovnikov

    2008-08-20T23:59:59.000Z

    To the foundation of a principally new short-term forecasting method there has been laid down a theory of surrounding us world's creation and of physical vacuum as a result of interaction of byuons - discrete objects. The definition of the byuon contains the cosmological vector-potential A_g - a novel fundamental vector constant. This theory predicts a new anisotropic interaction of nature objects with the physical vacuum. A peculiar "tap" to gain new energy (giving rise to an earthquake) are elementary particles because their masses are proportional to the modulus of some summary potential A_sum that contains potentials of all known fields. The value of A_sum cannot be larger than the modulus of A_g. In accordance with the experimental results a new force associated with A_sum ejects substance from the area of the weakened A_sum along a conical formation with the opening of 100 +- 10 and the axis directed along the vector A_sum. This vector has the following coordinates in the second equatorial coordinate system: right ascension alpha = 293 +- 10, declination delta = 36 +- 10. Nearly 100% probability of an earthquake (earthquakes of 6 points strong and more by the Richter scale) arises when in the process of the earth rotation the zenith vector of a seismically dangerous region and/or the vectorial potential of Earth's magnetic fields are in a certain way oriented relative to the vector A_g. In the work, basic models and standard mechanisms of earthquakes are briefly considered, results of processing of information on the earthquakes in the context of global spatial anisotropy caused by the existence of the vector A_g, are presented, and an analysis of them is given.

  8. Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update (EIA)

    day Forecast -1.0 2012 2013 2014 OPEC countries North America Russia and Caspian Sea Latin America North Sea Other Non-OPEC Source: Short-Term Energy Outlook, November 2013 -1 0...

  9. Short-term energy outlook: Quarterly projections. Second quarter 1995

    SciTech Connect (OSTI)

    NONE

    1995-05-02T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent projections with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the second quarter of 1995 through the fourth quarter of 1996. Values for the first quarter of 1995, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data, compiled into the second quarter 1995 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service.

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

    SciTech Connect (OSTI)

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

    2014-04-30T23:59:59.000Z

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

  11. Improved water allocation utilizing probabilistic climate forecasts: Short-term water contracts in a risk management framework

    E-Print Network [OSTI]

    Arumugam, Sankar

    . Thus, integrated supply and demand management can be achieved. In this paper, a single period multiuser, forecast consumers, water managers and reservoir operators, have difficulty interpreting such products in a risk management framework A. Sankarasubramanian,1 Upmanu Lall,2 Francisco Assis Souza Filho,3

  12. Research on Short-term Load Forecasting of the Thermoelectric Boiler Based on a Dynamic RBF Neural Network

    E-Print Network [OSTI]

    Dai, W.; Zou, P.; Yan, C.

    2006-01-01T23:59:59.000Z

    is proposed based on the RBF neural network with the associated parameters of sample deviation and partial sample deviation, which are defined for the purpose of effective judgment of new samples. Also, in order to forecast the load of sample with large...

  13. Short-term energy outlook, January 1999

    SciTech Connect (OSTI)

    NONE

    1999-01-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares the Short-Term Energy Outlook (energy supply, demand, and price projections) monthly. The forecast period for this issue of the Outlook extends from January 1999 through December 2000. Data values for the fourth quarter 1998, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the January 1999 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the STIFS model. 28 figs., 19 tabs.

  14. Short-term energy outlook, July 1998

    SciTech Connect (OSTI)

    NONE

    1998-07-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares The Short-Term Energy Outlook (energy supply, demand, and price projections) monthly for distribution on the internet at: www.eia.doe.gov/emeu/steo/pub/contents.html. In addition, printed versions of the report are available to subscribers in January, April, July and October. The forecast period for this issue of the Outlook extends from July 1998 through December 1999. Values for second quarter of 1998 data, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the July 1998 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. 28 figs., 19 tabs.

  15. Short-Term Energy Outlook: Quarterly projections. Fourth quarter 1993

    SciTech Connect (OSTI)

    Not Available

    1993-11-05T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the fourth quarter of 1993 through the fourth quarter of 1994. Values for the third quarter of 1993, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications.

  16. Short-term energy outlook quarterly projections: First quarter 1993

    SciTech Connect (OSTI)

    Not Available

    1993-02-03T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.). The forecast period for this issue of the Outlook extends from the first quarter of 1993 through the fourth quarter of 1994. Values for the fourth quarter of 1992, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding.

  17. Short-term energy outlook: Quarterly projections, Third quarter 1992

    SciTech Connect (OSTI)

    Not Available

    1992-08-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The principal users of the Outlook are managers and energy analysts in private industry and government. The forecast period for this issue of the Outlook extends from the third quarter of 1992 through the fourth quarter of 1993. Values for the second quarter of 1992, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding.

  18. Short-term energy outlook, Quarterly projections. Third quarter 1993

    SciTech Connect (OSTI)

    NONE

    1993-08-04T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the third quarter of 1993 through the fourth quarter of 1994. Values for the second quarter of 1993, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding.

  19. Short-term energy outlook quarterly projections. First quarter 1994

    SciTech Connect (OSTI)

    Not Available

    1994-02-07T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short- term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets.

  20. 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 dedicated models to forecast the 12 individual months directly. Results indicate better performance is superior to naïve forecasts based on persistence and seasonality, and is better than results quoted

  1. Short-Term Energy Outlook September 2013

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

    day Forecast -0.9 2012 2013 2014 OPEC countries North America Russia and Caspian Sea Latin America North Sea Other Non-OPEC Source: Short-Term Energy Outlook, September 2013 -1...

  2. Short-term energy outlook: Quarterly projections, fourth quarter 1997

    SciTech Connect (OSTI)

    NONE

    1997-10-14T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly short-term energy supply, demand, and price projections for printed publication in January, April, July, and October in the Short-Term Energy Outlook. The details of these projections, as well as monthly updates on or about the 6th of each interim month, are available on the internet at: www.eia.doe.gov/emeu/steo/pub/contents.html. The forecast period for this issue of the Outlook extends from the fourth quarter of 1997 through the fourth quarter of 1998. Values for the fourth quarter of 1997, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the fourth quarter 1997 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. 19 tabs.

  3. Short-term energy outlook, annual supplement 1994

    SciTech Connect (OSTI)

    Not Available

    1994-08-01T23:59:59.000Z

    The Short-Term Energy Outlook Annual Supplement (Supplement) is published once a year as a complement to the Short-Term Energy Outlook (Outlook), Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts.

  4. Short-term energy outlook annual supplement, 1993

    SciTech Connect (OSTI)

    NONE

    1993-08-06T23:59:59.000Z

    The Short-Term Energy Outlook Annual Supplement (supplement) is published once a year as a complement to the Short-Term Energy Outlook (Outlook), Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts.

  5. Short-term energy outlook, April 1999

    SciTech Connect (OSTI)

    NONE

    1999-04-01T23:59:59.000Z

    The forecast period for this issue of the Outlook extends from April 1999 through December 2000. Data values for the first quarter 1999, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the April 1999 version of the Short-Term Integrated forecasting system (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the STIFS model. 25 figs., 19 tabs.

  6. Short-term energy outlook. Quarterly projections, first quarter 1995

    SciTech Connect (OSTI)

    Not Available

    1995-02-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). The forecast period for this issue of the Outlook extends from the first quarter of 1995 through the fourth quarter of 1996. Values for the fourth quarter of 1994, however, are preliminary EIA estimates or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data, compiled into the first quarter 1995 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service. The cases are produced using the Short-Term Integrated Forecasting System (STIFS). The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. The EIA model is available on computer tape from the National Technical Information Service.

  7. Short-term energy outlook: Quarterly projections, second quarter 1997

    SciTech Connect (OSTI)

    NONE

    1997-04-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly short-term energy supply, demand, and price projections for publication in January, April, July, and October in the Outlook. The forecast period for this issue of the Outlook extends from the second quarter of 1997 through the fourth quarter of 1998. Values for the first quarter of 1997, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the second quarter 1997 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the Short-Term Integrated Forecasting System (STIFS). 34 figs., 19 tabs.

  8. Short-term energy outlook. Quarterly projections, first quarter 1996

    SciTech Connect (OSTI)

    NONE

    1996-02-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Outlook. The forecast period for this issue of the Outlook extends from the first quarter of 1996 through the fourth quarter of 1997. Values for the fourth quarter of 1995, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data, compiled into the first quarter 1996 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service. The cases are produced using the Short-Term Integrated Forecasting System (STIFS). The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook.

  9. Short-term energy outlook. Quarterly projections, Third quarter 1994

    SciTech Connect (OSTI)

    Not Available

    1994-08-02T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202). The feature article for this issue is Demand, Supply and Price Outlook for Reformulated Gasoline, 1995.

  10. Short-term energy outlook. Quarterly projections, third quarter 1996

    SciTech Connect (OSTI)

    NONE

    1996-07-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in January, April, July, and October in the Outlook. The forecast period for this issue of the Outlook extends from the third quarter of 1996 through the fourth quarter of 1997. Values for the second quarter of 1996, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data, compiled in the third quarter 1996 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service.

  11. Short-term energy outlook. Quarterly projections, Third quarter 1995

    SciTech Connect (OSTI)

    NONE

    1995-08-02T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent projections with those of other forecasting services, and discusses current topics related to the short-term energy markets. The forecast period for this issue of the Outlook extends from the third quarter of 1995 through the fourth quarter of 1996. Values for the second quarter of 1995, however, are preliminary EIA estimates.

  12. Short-term energy outlook. Quarterly projections, 2nd quarter 1994

    SciTech Connect (OSTI)

    Not Available

    1994-05-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. The forecast period for this issue of the Outlook extends from the second quarter of 1994 through the fourth quarter of 1995. Values for the first quarter of 1994, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available. The historical energy data, compiled into the second quarter 1994 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service. The cases are produced using the STIFS. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. The EIA model is available on computer tape from the National Technical Information Service.

  13. 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 [WindLogics

    2014-04-30T23:59:59.000Z

    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. A comprehensive analysis of wind energy forecast errors for the various model-based power forecasts was presented for a suite of wind energy ramp definitions. The results compiled over the year-long study period showed that the power forecasts based on the research models (ESRL_RAP, HRRR) more accurately predict wind energy ramp events than the current operational forecast models, both at the system aggregate level and at the local wind plant level. At the system level, the ESRL_RAP-based forecasts most accurately predict both the total number of ramp events and the occurrence of the events themselves, but the HRRR-based forecasts more accurately predict the ramp rate. At the individual site level, the HRRR-based forecasts most accurately predicted the actual ramp occurrence, the total number of ramps and the ramp rates (40-60% improvement in ramp rates over the coarser resolution forecast

  14. Short-term energy outlook. Volume 2. Methodology

    SciTech Connect (OSTI)

    Not Available

    1982-05-01T23:59:59.000Z

    This volume updates models and forecasting methodologies used and presents information on new developments since November 1981. Chapter discusses the changes in forecasting methodology for motor gasoline demand, electricity sales, coking coal, and other petroleum products. Coefficient estimates, summary statistics, and data sources for many of the short-term energy models are provided. Chapter 3 evaluates previous short-term forecasts for the macroeconomic variables, total energy, petroleum supply and demand, coal consumption, natural gas, and electricity fuel shares. Chapter 4 reviews the relationship of total US energy consumption to economic activity between 1960 and 1981.

  15. Short-term energy outlook, quarterly projections, first quarter 1998

    SciTech Connect (OSTI)

    NONE

    1998-01-01T23:59:59.000Z

    The forecast period for this issue of the Outlook extends from the first quarter of 1998 through the fourth quarter of 1999. Values for the fourth quarter of 1997, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the first quarter 1998 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are adjusted by EIA to reflect EIA assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the STIFS model. 24 figs., 19 tabs.

  16. Short-Term Energy Outlook

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

    Chart Gallery for April 2015 Short-Term Energy Outlook U.S. Energy Information Administration Independent Statistics & Analysis 0 20 40 60 80 100 120 140 160 180 200 220 Jan 2014...

  17. Short-term energy outlook, October 1998. Quarterly projections, 1998 4. quarter

    SciTech Connect (OSTI)

    NONE

    1998-10-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares The Short-Term Energy Outlook (energy supply, demand, and price projections) monthly for distribution on the Internet at: www.eia.doe.gov/emeu/steo/pub/contents.html. In addition, printed versions of the report are available to subscribers in January, April, July and October. The forecast period for this issue of the Outlook extends from October 1998 through December 1999. Values for third quarter of 1998 data, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the October 1998 version of the Short-term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding.

  18. Short-term energy outlook. Quarterly projections, second quarter 1996

    SciTech Connect (OSTI)

    NONE

    1996-04-01T23:59:59.000Z

    The Energy Information Administration prepares quarterly, short-term energy supply, demand, and price projections. The forecasts in this issue cover the second quarter of 1996 through the fourth quarter of 1997. Changes to macroeconomic measures by the Bureau of Economic Analysis have been incorporated into the STIFS model used.

  19. Short-term energy outlook, Annual supplement 1995

    SciTech Connect (OSTI)

    NONE

    1995-07-25T23:59:59.000Z

    This supplement is published once a year as a complement to the Short- Term Energy Outlook, Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts. Chap. 2 analyzes the response of the US petroleum industry to the recent four Federal environmental rules on motor gasoline. Chap. 3 compares the EIA base or mid case energy projections for 1995 and 1996 (as published in the first quarter 1995 Outlook) with recent projections made by four other major forecasting groups. Chap. 4 evaluates the overall accuracy. Chap. 5 presents the methology used in the Short- Term Integrated Forecasting Model for oxygenate supply/demand balances. Chap. 6 reports theoretical and empirical results from a study of non-transportation energy demand by sector. The empirical analysis involves the short-run energy demand in the residential, commercial, industrial, and electrical utility sectors in US.

  20. Forecasting the monthly volume of orders for southern pine lumber - an econometric model

    E-Print Network [OSTI]

    Jackson, Ben Douglas

    1973-01-01T23:59:59.000Z

    the orders estimates should be minimal, and the benefits of forecasting should exceed the costs. Included in this matter of convenience is the mathematical simplicity of the computations and their evaluation. With these essential characteristics in mind... FORECASTING THE MONTHLY VOLUME OF ORDERS FOR SOUTHERN PINE LUMBER - AH ECONOMETRIC MODEL A Thesis by BEN DOUGLAS JACKSON Submitted to the Graduate College of Texas ASM University in Partial fulfillment of the requirement for the degree...

  1. Forecasting U.S. Hurricanes 6 Months in Advance James B. Elsner,1

    E-Print Network [OSTI]

    Elsner, James B.

    . A hurricane can make more than one landfall as hurricane Andrew did in striking southeast FloridaForecasting U.S. Hurricanes 6 Months in Advance James B. Elsner,1 Richard J. Murnane,2 Thomas H correspondence should be addressed; E-mail: jelsner@garnet.fsu.edu. [1] Hurricanes are a serious social

  2. Forecasting U.S. hurricanes 6 months in advance J. B. Elsner,1

    E-Print Network [OSTI]

    Elsner, James B.

    . A hurricane can make more than one landfall as hurricane Andrew did in striking southeast FloridaForecasting U.S. hurricanes 6 months in advance J. B. Elsner,1 R. J. Murnane,2 and T. H. Jagger1 is a grim reminder of the serious social and economic threat that hurricanes pose to the United States

  3. Electricity storage for short term power system service (Smart...

    Open Energy Info (EERE)

    storage for short term power system service (Smart Grid Project) Jump to: navigation, search Project Name Electricity storage for short term power system service Country Denmark...

  4. SHORT TERM PREDICTIONS FOR THE POWER OUTPUT OF ENSEMBLES OF WIND TURBINES AND PV-GENERATORS

    E-Print Network [OSTI]

    Heinemann, Detlev

    SHORT TERM PREDICTIONS FOR THE POWER OUTPUT OF ENSEMBLES OF WIND TURBINES AND PV-GENERATORS Hans the state of the art of power predictios for wind and solar power plants.with a time horizon of several market there is a need for a forecast of the power production of wind and solar generators with time

  5. Short-term energy outlook, quarterly projections, second quarter 1998

    SciTech Connect (OSTI)

    NONE

    1998-04-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares quarterly short-term energy supply, demand, and price projections. The details of these projections, as well as monthly updates, are available on the Internet at: www.eia.doe.gov/emeu/steo/pub/contents.html. The paper discusses outlook assumptions; US energy prices; world oil supply and the oil production cutback agreement of March 1998; international oil demand and supply; world oil stocks, capacity, and net trade; US oil demand and supply; US natural gas demand and supply; US coal demand and supply; US electricity demand and supply; US renewable energy demand; and US energy demand and supply sensitivities. 29 figs., 19 tabs.

  6. Short-Term Energy Outlook- May 2003

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSettingUncertainties in the3 1 Short-Term

  7. 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...

  8. Short-term energy outlook quarterly projections. Third quarter 1997

    SciTech Connect (OSTI)

    NONE

    1997-07-01T23:59:59.000Z

    This document presents the 1997 third quarter short term energy projections. Information is presented for fossil fuels and renewable energy.

  9. Semester, Academic Year and Short Term SUNY Programs

    E-Print Network [OSTI]

    Suzuki, Masatsugu

    Semester, Academic Year and Short Term SUNY Programs: Asia #12;1 Table of Contents How to Use Year 10 Japan Short-term 12 Korea Semester & Academic Year 13 Korea Short-term 17 Programs in Other Contact Information 23 How to Use this Booklet This handout contains listings of all the programs offered

  10. ORIGINAL PAPER Introduction to the Special Issues: Short-term

    E-Print Network [OSTI]

    Olufsen, Mette Sofie

    in short-term cardiovascular­respiratory regulation, (ii) to develop mathematical models that can improve involved in short-term cardio- vascular­respiratory control include auto-regulation of vasculature, controlORIGINAL PAPER Introduction to the Special Issues: Short-term Cardiovascular­Respiratory Control

  11. SUNY Programs: Semester, Academic Year and Short Term

    E-Print Network [OSTI]

    Suzuki, Masatsugu

    SUNY Programs: Italy Semester, Academic Year and Short Term #12;1 Table of Contents How to Use This Booklet 1 A Brief Overview 2 Semester and Academic Year Programs 3 Short Term Programs 8 Contact of programs offered in Italy by SUNY campuses. These listings provide a summary about the basic

  12. SUNY Programs: Semester, Academic Year and Short Term

    E-Print Network [OSTI]

    Suzuki, Masatsugu

    SUNY Programs: France Semester, Academic Year and Short Term #12;1 Table of Contents How to Use This Booklet 1 A Brief Overview 2 Semester and Academic Year Programs 3 Short Term Programs 6 SUNY Programs in Canada and other Francophone Locations 9 Recommended non-SUNY Program 11 Contact Information for all SUNY

  13. ORIGINAL CONTRIBUTION Ozone and Short-term Mortality

    E-Print Network [OSTI]

    Dominici, Francesca

    ORIGINAL CONTRIBUTION Ozone and Short-term Mortality in 95 US Urban Communities, 1987-2000 MichelleD E XPOSURE TO TROPOSPHERIC OZONE is widespread in the United States,1,2 occurring also outside southernCalifornia,whereozone formation was first recognized.3 Short- term exposure to ozone has been

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01T23:59:59.000Z

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

  15. Short-Term Load Forecasting This paper discusses the state of the art in short-term load fore-

    E-Print Network [OSTI]

    Gross, George

    spectrum of time intervals. In therange of seconds, when load variationsare small and random, the automatic by a number of generation control functions such as hydro scheduling, unit commitment, hydro-ther- mal present, functions such as fuel, hydro, and maintenance scheduling are performed to ensure that the load

  16. Short-term CO? abatement in the European power sector

    E-Print Network [OSTI]

    Delarue, Erik D.

    2008-01-01T23:59:59.000Z

    This paper focuses on the possibilities for short term abatement in response to a CO2 price through fuel switching in the European power sector. The model E-Simulate is used to simulate the electricity generation in Europe ...

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

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

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

  18. Rapid Re-Housing and Short-Term Rental

    E-Print Network [OSTI]

    Snider, Barry B.

    Rapid Re-Housing and Short-Term Rental Vouchers for Homeless Families: Summary Report of a Pilot of numerous reports and publications, such as Bridges and Barriers to Housing for Chronically Homeless Street Dwellers; Accessing Housing: Exploring the Impact of Medical and Substance Abuse Services; The First Two

  19. Management and Conservation Short-Term Impacts of Wind Energy

    E-Print Network [OSTI]

    Beck, Jeffrey L.

    Management and Conservation Short-Term Impacts of Wind Energy Development on Greater Sage associated with wind energy development on greater sage-grouse populations. We hypothesized that greater sage-grouse nest, brood, and adult survival would decrease with increasing proximity to wind energy infrastructure

  20. Word learning, phonological short-term memory, phonotactic probability and

    E-Print Network [OSTI]

    Gupta, Prahlad

    for thinking about various types of studies of word learning. We then review a number of themes that in recent as a useful organizing scheme for thinking about various types of studies of word learning. In §2, we reviewWord learning, phonological short-term memory, phonotactic probability and long-term memory

  1. ANALYSIS OF SHORT-TERM SOLAR RADIATION DATA Gayathri Vijayakumar

    E-Print Network [OSTI]

    Wisconsin at Madison, University of

    ANALYSIS OF SHORT-TERM SOLAR RADIATION DATA Gayathri Vijayakumar Sanford A. Klein William A beckman@engr.wisc.edu ABSTRACT Solar radiation data are available for many locations on an hourly basis annual performance, although solar radiation can exhibit wide variations during an hour. Variations

  2. Future stand conditions: Short term: Many aspen whips will sprout

    E-Print Network [OSTI]

    Future stand conditions: Short term: Many aspen whips will sprout from the roots of cut trees. Pine, aspen, birch, and basswood. What's Going on Here? Active management is being used to fulfill trees (aspen and birch) Economic goals: Generate revenue to help maintain the forest, trails and other

  3. SHORT-TERM GENERATION ASSET VALUATION: A REAL OPTIONS APPROACH

    E-Print Network [OSTI]

    Tseng, Chung-Li

    using real options to value power plants with unit commitment constraints over a short-term period. We forward-moving Monte Carlo simulation with backward-moving dynamic programming. We assume that the power significantly overvalue a power plant. With deregulation of the electricity industry a global trend, utilities

  4. RESEARCH ARTICLE Empirical assessment of short-term variability from

    E-Print Network [OSTI]

    -term variability; PV plant ramp rate; daily aggregate ramp rate; inverter shells *Correspondence Rob van HaarenRESEARCH ARTICLE Empirical assessment of short-term variability from utility-scale solar PV plants and the output from 390 inverters. We use a simple metric, "daily aggregate ramp rate" to quantify, categorize

  5. ASPECT OBJECTIVE SHORT TERM TARGET by 2015 (unless otherwise stated)

    E-Print Network [OSTI]

    Chittka, Lars

    the remainder. Completion of Waste Management Strategy by the end of 2012. Implementation of the short term actions of the WMS by 2015 and long term actions by 2020. Development of a Waste Management Strategy (WMS costs per student (FTE). Estates and Facilities and Sustainability Committee 3 Energy consumed and used

  6. SUNY Programs: Semester, Academic Year and Short Term

    E-Print Network [OSTI]

    Suzuki, Masatsugu

    SUNY Programs: Spain Semester, Academic Year and Short Term #12;1 Table of Contents How to Use of programs offered in Spain by SUNY campuses. These listings provide a summary about the characteristics by the SUNY campuses in Spain. In addition, there are some excellent programs in Spain outside the SUNY system

  7. analyzing short-term noise: Topics by E-print Network

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

    122 Short term effects of moderate carbon prices on land use in the New Zealand emissions trading Environmental Sciences and Ecology Websites Summary: Short term effects of...

  8. Measuring Short-term Air Conditioner Demand Reductions for Operations and Settlement

    E-Print Network [OSTI]

    Bode, Josh

    2013-01-01T23:59:59.000Z

    Measuring Short-term Air Conditioner Demand Reductions forMeasuring Short-term Air Conditioner Demand Reductions forpilots have shown that air conditioner (AC) electric loads

  9. Estimating long-term mean winds from short-term wind data

    SciTech Connect (OSTI)

    Barchet, W.R.; Davis, W.E.

    1983-08-01T23:59:59.000Z

    The estimation of long-term mean winds from short-term data is especially important in the area of wind energy. It is desirable to obtain reliable estimates of the long-term wind speed from as short a period of on-site measurements as possible. This study examined seven different methods of estimating the long-term average wind speed and compared the performance of these techniques. Three linear, three weather pattern, and one eigenvector methods were compared for measurement periods ranging from 3 months to 36 months. Average errors, both relative and absolute, and the rms errors in the techniques were determined. The best technique for less than 12 months of measurement was the eigenvector method using weekly mean wind speeds. However, this method was only slightly better than the linear adjusted method. When 12 or more months of data were used, the difference in errors between techniques was found to be slight.

  10. Short-Term Operation Scheduling in Renewable-Powered Microgrids

    E-Print Network [OSTI]

    Bornemann, Jens

    existing algorithms; 2) an energy storage system (ESS) with suitable capacity contributes to the self. Cold start-up cost of a unit. Dual function. Forecasted demand in time interval . Emission function of a unit. CDF of wind power forecast error. Fuel cost function of a unit. Hot start-up cost of a unit. L

  11. Energy Information Administration/Short-Term Energy Outlook - August 2005

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.MajorMarkets EnergyConsumption5 1 Short-Term Energy

  12. Energy Information Administration/Short-Term Energy Outlook - February 2005

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.MajorMarkets EnergyConsumption5 1 Short-Term

  13. Energy Information Administration/Short-Term Energy Outlook - January 2005

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.MajorMarkets EnergyConsumption5 1 Short-TermJanuary

  14. Energy Information Administration/Short-Term Energy Outlook - June 2005

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.MajorMarkets EnergyConsumption5 15 1 Short-Term

  15. Energy Information Administration/Short-Term Energy Outlook - May 2005

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.MajorMarkets EnergyConsumption5 15 1 Short-Term5 1

  16. Energy Information Administration/Short-Term Energy Outlook - October 2005

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.MajorMarkets EnergyConsumption5 15 1 Short-Term5 15 1

  17. Energy Information Administration/Short-Term Energy Outlook - September 2005

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S.MajorMarkets EnergyConsumption5 15 1 Short-Term5 15

  18. Short-Term Energy and Winter Fuels Outlook October 2013

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSettingUncertainties in the3 1 Short-Term3 1

  19. SHORT-TERM SOLAR FLARE PREDICTION USING MULTIRESOLUTION PREDICTORS

    SciTech Connect (OSTI)

    Yu Daren; Huang Xin; Hu Qinghua; Zhou Rui [Harbin Institute of Technology, No. 92 West Da-Zhi Street, Harbin, Heilongjiang Province (China); Wang Huaning [National Astronomical Observatories, 20A Datun Road, Chaoyang District, Beijing (China); Cui Yanmei, E-mail: huangxinhit@yahoo.com.c [Center for Space Science and Applied Research, No. 1 Nanertiao, Zhongguancun, Haidian District, Beijing (China)

    2010-01-20T23:59:59.000Z

    Multiresolution predictors of solar flares are constructed by a wavelet transform and sequential feature extraction method. Three predictors-the maximum horizontal gradient, the length of neutral line, and the number of singular points-are extracted from Solar and Heliospheric Observatory/Michelson Doppler Imager longitudinal magnetograms. A maximal overlap discrete wavelet transform is used to decompose the sequence of predictors into four frequency bands. In each band, four sequential features-the maximum, the mean, the standard deviation, and the root mean square-are extracted. The multiresolution predictors in the low-frequency band reflect trends in the evolution of newly emerging fluxes. The multiresolution predictors in the high-frequency band reflect the changing rates in emerging flux regions. The variation of emerging fluxes is decoupled by wavelet transform in different frequency bands. The information amount of these multiresolution predictors is evaluated by the information gain ratio. It is found that the multiresolution predictors in the lowest and highest frequency bands contain the most information. Based on these predictors, a C4.5 decision tree algorithm is used to build the short-term solar flare prediction model. It is found that the performance of the short-term solar flare prediction model based on the multiresolution predictors is greatly improved.

  20. Short-Term Test Results: Multifamily Home Energy Efficiency Retrofit

    SciTech Connect (OSTI)

    Lyons, J.

    2013-01-01T23:59:59.000Z

    Multifamily deep energy retrofits (DERs) represent great potential for energy savings, while also providing valuable insights on research-generated efficiency measures, cost-effectiveness metrics, and risk factor strategies for the multifamily housing industry. The Bay Ridge project is comprised of a base scope retrofit with a goal of achieving 30% savings (relative to pre-retrofit), and a DER scope with a goal of 50% savings (relative to pre-retrofit). The base scope has been applied to the entire complex, except for one 12-unit building which underwent the DER scope. Findings from the implementation, commissioning, and short-term testing at Bay Ridge include air infiltration reductions of greater than 60% in the DER building; a hybrid heat pump system with a Savings to Investment Ratio (SIR) > 1 (relative to a high efficiency furnace) which also provides the resident with added incentive for energy savings; and duct leakage reductions of > 60% using an aerosolized duct sealing approach. Despite being a moderate rehab instead of a gut rehab, the Bay Ridge DER is currently projected to achieve energy savings ? 50% compared to pre-retrofit, and the short-term testing supports this estimate.

  1. aneurysm repair short-term: Topics by E-print Network

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

    is socially excessive. The empirical analysis shows that the short-term debt to reserves ratio is a robust predictor of -nancial crises, and that greater short-term...

  2. Short-term exploitative competition can explain human foraging patterns

    E-Print Network [OSTI]

    Saavedra, Serguei; Switanek, Nicholas; Uzzi, Brian

    2012-01-01T23:59:59.000Z

    Theory purports that animal foraging choices evolve to maximize returns, such as net energy intake. Empirical research in both human and nonhuman animals reveals that many times foraging choices are context dependent and affected by the foraging choices of others. Yet, broad empirical facts on the link between optimal foraging patterns, competition and context-dependent information are only now emerging due to the complication of gathering field data or constructing experiments. Here, we analyze foraging choices by a cohort of professional day traders who face the trade-off of trading the same stock multiple times in a row---patch exploitation---or switching to a different stock---patch exploration---with potentially higher returns. Our findings indicate that traders' foraging patterns are characterized by short-term comparative returns that decrease in proportion to patch exploitation and exploration, a novel measure that captures the difference between a trader's resource intake and the competitors' expecte...

  3. III. -ECONOMY Pig production : short-term prospects

    E-Print Network [OSTI]

    Boyer, Edmond

    feed. The main price formation mechanisms on these markets are explained : the relationships between on the E.E.C. scene, formation of soyabean meal prices within the « oil and protein crop complexand price forecasting H. MAROUBY LT.P., Service Economie, 34, bd de la Gare, 3150!0 Toulouse As pig price

  4. Forecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices

    E-Print Network [OSTI]

    Kulkarni, Siddhivinayak

    2009-01-01T23:59:59.000Z

    This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal of attention was paid on finding the optimal ANN model structure. In addition, several methods of data pre-processing were tested. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futures prices for 1, 2, 3,and four months to maturity, one by one and also altogether. The results on the benchmark suggest that a dynamic model of 13 lags is the optimal to forecast spot price direction for the short-term. Further, the forecast accuracy of the direction of the market was 78%, 66%, and 53% for one, two, and three days in future conclusively. For all the experiments, that include futures data as an input, the results show that on the short-term, futures prices do hold new information on the spot price direction. The results obtained will generate comprehensive understanding of the cr...

  5. Short-Term Energy Outlook Supplement: Energy Price Volatility and Forecast Uncertainty

    Reports and Publications (EIA)

    2009-01-01T23:59:59.000Z

    It is often noted that energy prices are quite volatile, reflecting market participants' adjustments to new information from physical energy markets and/or markets in energy-related financial derivatives. Price volatility is an indication of the level of uncertainty, or risk, in the market. This paper describes how markets price risk and how the marketclearing process for risk transfer can be used to generate "price bands" around observed futures prices for crude oil, natural gas, and other commodities.

  6. SULFURIC ACID REMOVAL PROCESS EVALUATION: SHORT-TERM RESULTS

    SciTech Connect (OSTI)

    Gary M. Blythe; Richard McMillan

    2002-03-04T23:59:59.000Z

    The objective of this project is to demonstrate the use of alkaline reagents injected into the furnace of coal-fired boilers as a means of controlling sulfuric acid emissions. Sulfuric acid controls are becoming of increasing interest to utilities with coal-fired units for a number of reasons. Sulfuric acid is a Toxic Release Inventory species, a precursor to acid aerosol/condensable emissions, and can cause a variety of plant operation problems such as air heater plugging and fouling, back-end corrosion, and plume opacity. These issues will likely be exacerbated with the retrofit of SCR for NOX control on some coal-fired plants, as SCR catalysts are known to further oxidize a portion of the flue gas SO{sub 2} to SO{sub 3}. The project is testing the effectiveness of furnace injection of four different calcium- and/or magnesium-based alkaline sorbents on full-scale utility boilers. These reagents have been tested during four one- to two-week tests conducted on two FirstEnergy Bruce Mansfield Plant units. One of the sorbents tested was a magnesium hydroxide slurry produced from a wet flue gas desulfurization system waste stream, from a system that employs a Thiosorbic{reg_sign} Lime scrubbing process. The other three sorbents are available commercially and include dolomite, pressure-hydrated dolomitic lime, and commercial magnesium hydroxide. The dolomite reagent was injected as a dry powder through out-of-service burners, while the other three reagents were injected as slurries through air-atomizing nozzles into the front wall of upper furnace, either across from the nose of the furnace or across from the pendant superheater tubes. After completing the four one- to two-week tests, the most promising sorbents were selected for longer-term (approximately 25-day) full-scale tests. The longer-term tests are being conducted to confirm the effectiveness of the sorbents tested over extended operation and to determine balance-of-plant impacts. This reports presents the results of the short-term tests; the long-term test results will be reported in a later document. The short-term test results showed that three of the four reagents tested, dolomite powder, commercial magnesium hydroxide slurry, and byproduct magnesium hydroxide slurry, were able to achieve 90% or greater removal of sulfuric acid compared to baseline levels. The molar ratio of alkali to flue gas sulfuric acid content (under baseline conditions) required to achieve 90% sulfuric acid removal was lowest for the byproduct magnesium hydroxide slurry. However, this result may be confounded because this was the only one of the three slurries tested with injection near the top of the furnace across from the pendant superheater platens. Injection at the higher level was demonstrated to be advantageous for this reagent over injection lower in the furnace, where the other slurries were tested.

  7. SULFURIC ACID REMOVAL PROCESS EVALUATION: SHORT-TERM RESULTS

    SciTech Connect (OSTI)

    Gary M. Blythe; Richard McMillan

    2002-02-04T23:59:59.000Z

    The objective of this project is to demonstrate the use of alkaline reagents injected into the furnace of coal-fired boilers as a means of controlling sulfuric acid emissions. Sulfuric acid controls are becoming of increasing interest to utilities with coal-fired units for a number of reasons. Sulfuric acid is a Toxic Release Inventory species, a precursor to acid aerosol/condensable emissions, and can cause a variety of plant operation problems such as air heater plugging and fouling, back-end corrosion, and plume opacity. These issues will likely be exacerbated with the retrofit of SCR for NO{sub x} control on some coal-fired plants, as SCR catalysts are known to further oxidize a portion of the flue gas SO{sub 2} to SO{sub 3}. The project is testing the effectiveness of furnace injection of four different calcium- and/or magnesium-based alkaline sorbents on full-scale utility boilers. These reagents have been tested during four one- to two-week tests conducted on two First Energy Bruce Mansfield Plant units. One of the sorbents tested was a magnesium hydroxide slurry produced from a wet flue gas desulfurization system waste stream, from a system that employs a Thiosorbic{reg_sign} Lime scrubbing process. The other three sorbents are available commercially and include dolomite, pressure-hydrated dolomitic lime, and commercial magnesium hydroxide. The dolomite reagent was injected as a dry powder through out-of-service burners, while the other three reagents were injected as slurries through air-atomizing nozzles into the front wall of upper furnace, either across from the nose of the furnace or across from the pendant superheater tubes. After completing the four one- to two-week tests, the most promising sorbents were selected for longer-term (approximately 25-day) full-scale tests. The longer-term tests are being conducted to confirm the effectiveness of the sorbents tested over extended operation and to determine balance-of-plant impacts. This reports presents the results of the short-term tests; the long-term test results will be reported in a later document. The short-term test results showed that three of the four reagents tested, dolomite powder, commercial magnesium hydroxide slurry, and byproduct magnesium hydroxide slurry, were able to achieve 90% or greater removal of sulfuric acid compared to baseline levels. The molar ratio of alkali to flue gas sulfuric acid content (under baseline conditions) required to achieve 90% sulfuric acid removal was lowest for the byproduct magnesium hydroxide slurry. However, this result may be confounded because this was the only one of the three slurries tested with injection near the top of the furnace across from the pendant superheater platens. Injection at the higher level was demonstrated to be advantageous for this reagent over injection lower in the furnace, where the other slurries were tested.

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

    E-Print Network [OSTI]

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

  9. Short term thermal energy storage Institut fr Kernenergetik und Energiesysteme, University of Stuttgart, Stuttgart, FRG

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    477 Short term thermal energy storage A. Abhat Institut für Kernenergetik und Energiesysteme the problem of short term thermal energy storage for low temperature solar heating applications. The techniques of sensible and latent heat storage are discussed, with particular emphasis on the latter

  10. Premium Ventilation Package Testing Short-Term Monitoring Report Task 7

    E-Print Network [OSTI]

    Premium Ventilation Package Testing Short-Term Monitoring Report ­ Task 7 Review Draft Submittal. 00038702 RTU AirCarePlus & Premium Ventilation Program COTR - Jack Callahan (503) 230-4496 / jmcallahan Ventilation Package Testing PECI Short-Term Monitoring Report ­ Task 7 REVIEW DRAFT: 9/14/2009 2 Table

  11. Short-Term Generation Asset Valuation Chung-Li Tseng, Graydon Barz

    E-Print Network [OSTI]

    Short-Term Generation Asset Valuation Chung-Li Tseng, Graydon Barz Department of Civil Engineering 94305, USA chungli@eng.umd.edu, gbarz@leland.stanford.edu Abstract In this paper we present a method for valuing a power plant over a short-term period using Monte Carlo sim- ulation. The power plant valuation

  12. An Exploration of Participant Motives and Motivational Tensions in Short-Term Medical Service Trips

    E-Print Network [OSTI]

    Sykes, Kevin James

    2014-05-31T23:59:59.000Z

    Short-term medical service trips (MSTs) are an increasingly popular, although not new, way for healthcare providers from high-income countries (HICs) to provide healthcare in low- and middle-income countries (LMICs). In ...

  13. Short-term Migration, Rural Workfare Programs and Urban Labor Markets: Evidence from India

    E-Print Network [OSTI]

    Bandyopadhyay, Antar

    , a simple calibration exercise reveals that small changes in short-term migration can have large impacts of migration in developing countries (Banerjee and Duo, 2007; Badiani and Sar, 2009; Morten, 2012). In 2007

  14. Short-Term Effects of Air Pollution on Wheeze in Asthmatic Children in Fresno, California

    E-Print Network [OSTI]

    2010-01-01T23:59:59.000Z

    Short-Term Effects of Air Pollution on Wheeze in Asthmaticchanges in ambient air pollution. Our data suggest the need2004. The effect of air pollution on lung development from

  15. SPE 124332 (revised) Hierarchical Long-Term and Short-Term Production Optimization

    E-Print Network [OSTI]

    Van den Hof, Paul

    . In our study we used a 3-dimensional reservoir in a fluvial depositional environment with a production at maximizing short-term production. The optimal life-cycle waterflooding strategy that includes short

  16. 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 meteorological data from sites upwind of wind farms can be efficiently used to improve short-term forecasts acknowledges the support of PPM Energy, Inc. The data used in this work were obtained from Oregon State

  17. Characterizing short-term stability for Boolean networks over any distribution of transfer functions

    E-Print Network [OSTI]

    C. Seshadhri; Andrew M. Smith; Yevgeniy Vorobeychik; Jackson Mayo; Robert C. Armstrong

    2014-09-15T23:59:59.000Z

    We present a characterization of short-term stability of random Boolean networks under \\emph{arbitrary} distributions of transfer functions. Given any distribution of transfer functions for a random Boolean network, we present a formula that decides whether short-term chaos (damage spreading) will happen. We provide a formal proof for this formula, and empirically show that its predictions are accurate. Previous work only works for special cases of balanced families. It has been observed that these characterizations fail for unbalanced families, yet such families are widespread in real biological networks.

  18. Short-term effects of Gamma Ray Bursts on oceanic photosynthesis

    E-Print Network [OSTI]

    Penate, Liuba; Cardenas, Rolando; Agusti, Susana

    2010-01-01T23:59:59.000Z

    We continue our previous work on the potential short-term influence of a gamma ray bursts on Earth's biosphere, focusing on the only important short-term effect on life: the ultraviolet flash which occurs as a result of the retransmission of the {\\gamma} radiation through the atmosphere. Thus, in this work we calculate the ultraviolet irradiances penetrating the first hundred meters of the water column, for Jerlov's ocean water types I, II and III. Then we estimate the UV flash potential for photosynthesis inhibition, showing that it can be important in a considerable part of the water column with light enough for photosynthesis to be done, the so called photic zone.

  19. Forecasting sudden changes in environmental pollution patterns

    E-Print Network [OSTI]

    Olascoaga, Maria Josefina

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

  20. Determining Long-Term Performance of Cool Storage Systems from Short-Term Tests, Final Report

    E-Print Network [OSTI]

    Reddy, T. A.; Elleson, J.; Haberl, J. S.

    2000-01-01T23:59:59.000Z

    This is the final report for ASHRAE Research Project 1004-RP: Determining Long-Term Performance of Cool Storage Systems from Short-Term Tests. This report presents the results of the development and application of the methodology to Case Study #2...

  1. Short term effects of moderate carbon prices on land use in the New Zealand emissions trading

    E-Print Network [OSTI]

    Silver, Whendee

    Short term effects of moderate carbon prices on land use in the New Zealand emissions trading Zealand Emissions Trading Scheme (NZ ETS) was introduced through the Climate Change Response Act............................................................................ 14 #12;1 1 Introduction The New Zealand Emissions Trading Scheme (NZ ETS) was legislated through

  2. Primal-Dual Interior Point Method Applied to the Short Term Hydroelectric Scheduling Including a

    E-Print Network [OSTI]

    Oliveira, Aurélio R. L.

    that minimizes losses in the transmission and costs in the generation of a hydroelectric power system, formulated such perturbing parameter. Keywords-- Hydroelectric power system, Network flow, Predispatch, Primal-dual interiorPrimal-Dual Interior Point Method Applied to the Short Term Hydroelectric Scheduling Including

  3. Short-term and long-term reliability studies in the deregulated power systems

    E-Print Network [OSTI]

    Li, Yishan

    2006-04-12T23:59:59.000Z

    for the new structure to maintain system reliability. Power system reliability is comprised of two basic components, adequacy and security. In terms of the time frame, power system reliability can mean short-term reliability or long-term reliability. Short...

  4. Longitudinal Analysis of Short term Bronchiolitis Air Pollution Association using Semi Parametric Models

    E-Print Network [OSTI]

    Mesbah, Mounir

    1 Longitudinal Analysis of Short term Bronchiolitis Air Pollution Association using Semi Parametric of ambient air pollution on infant bronchiolitis hospital consultations. Infant bronchiolitis is a frequent pollution, semi parametric models. 1.1 Introduction Time-series studies of air pollution and health

  5. Instructions for use Short-term Glacier Velocity Changes at West Kunlun

    E-Print Network [OSTI]

    Tsunogai, Urumu

    to global warming could further accelerate glacier15 flow and potentially lead to significant lossInstructions for use #12;Short-term Glacier Velocity Changes at West Kunlun Shan, Northwest Tibet. Abstract Seasonal glacier velocity changes across the High Arctic, including the Green- land Ice Sheet

  6. SHORT-TERM THERMAL RESISTANCE OF ZOEAE OF 10 SPECIES OF CRABS FROM PUGET SOUND, WASHINGTON

    E-Print Network [OSTI]

    SHORT-TERM THERMAL RESISTANCE OF ZOEAE OF 10 SPECIES OF CRABS FROM PUGET SOUND, WASHINGTON BENJAMIN to protect the most sensitive species studied is 24OC for the Puget Sound area. Thermal resistance of marine species of Puget INorthwest and Alaska Fisheries Center, National Marine Fisheries Service, NOAA, 2725

  7. Ethical Considerations for Short-term Experiences by Trainees in Global Health

    E-Print Network [OSTI]

    Tipple, Brett

    -constrained health care set- tings, trainees from resource-replete environments may have inflated ideas aboutCOMMENTARY Ethical Considerations for Short-term Experiences by Trainees in Global Health John A. Crump, MB, ChB, DTM&H Jeremy Sugarman, MD, MPH, MA A CADEMIC GLOBAL HEALTH PROGRAMS ARE BURGEON- ing.1

  8. Managing Short-Term Electricity Contracts Under Uncertainty: A Minimax Approach

    E-Print Network [OSTI]

    Ahmed, Shabbir

    Managing Short-Term Electricity Contracts Under Uncertainty: A Minimax Approach Samer Takriti Heights, New York 10598, USA, takriti@us.ibm.com School of Industrial & Systems Engineering, Georgia Institute of Technology, 765 Ferst Drive, Atlanta, Georgia 30332, USA, sahmed@isye.gatech.edu. The work

  9. PRIMARY RESEARCH PAPER Short-term responses of decomposers to flow restoration

    E-Print Network [OSTI]

    LeRoy, Carri J.

    most stream restoration projects, lack pre-restoration data and clearly defined goals, making et al., 2005; Bernhardt et al., 2005). Biotic recovery in response to stream restoration can be rapidPRIMARY RESEARCH PAPER Short-term responses of decomposers to flow restoration in Fossil Creek

  10. Short-Term Hurricane Impacts on a Neotropical Community of Marked Birds and Implications for Early-

    E-Print Network [OSTI]

    Winker, Kevin

    Short-Term Hurricane Impacts on a Neotropical Community of Marked Birds and Implications for Early- Stage Community Resilience Andrew B. Johnson1,2 , Kevin Winker1 * 1 University of Alaska Museum birds, following this community through the catastrophic destruction of its forest habitat by Hurricane

  11. Behavioral/Systems/Cognitive Short-Term Synaptic Depression Causes a Non-Monotonic

    E-Print Network [OSTI]

    Parga, Néstor

    Behavioral/Systems/Cognitive Short-Term Synaptic Depression Causes a Non-Monotonic Response to the postsynaptic cell because a large fraction of the spikes fail to elicit a synaptic response. In addition, short of incoming spikes as these are first converted into synaptic current and afterward into the cell response

  12. SHORT-TERM EFFECTS OF SOIL AMENDMENT WITH TREE LEGUME BIOMASS ON CARBON AND NITROGEN

    E-Print Network [OSTI]

    Lehmann, Johannes

    SHORT-TERM EFFECTS OF SOIL AMENDMENT WITH TREE LEGUME BIOMASS ON CARBON AND NITROGEN IN PARTICLE-to-N ratio of the added plant material seems to control the eects of soil amendment with tree legume biomass to the total quantity of C and N pre- sent. Physical fractionation of SOM can help to identify more active

  13. Short-term effects of air pollution: a panel study of blood markers in patients with chronic pulmonary disease

    E-Print Network [OSTI]

    2009-01-01T23:59:59.000Z

    Short-term effects of air pollution: a panel study of bloodindicates that ambient air pollution is associated withto daily changes in air pollution in Erfurt, Germany. 12

  14. Short-term measurements for the determination of envelope retrofit performance

    SciTech Connect (OSTI)

    Subbarao, K.; Mort, D.; Burch, J.

    1985-06-01T23:59:59.000Z

    Short-term monitoring for estimating thermal parameters of a building, along with an analytical technique to (1) determine the long-term performance and (2) calculate the parameters from a building description, has many valuable applications, which include energy ratings, diagnostics, and retrofit analysis. In this paper we address issues relating to reducing uncertainties in estimating thermal parameters with emphasis on retrofit applications. In general, it is necessary to impose a known heat flow with a suitable profile to reliably estimate the parameters. This is demonstrated with test cell measurements taken before and after changes were made to the test cell. The eventual goal of this project is to develop a practical methodology to determine long-term retrofit performance from short-term tests.

  15. Short-Term Energy Tests of a Credit Union Building in Idaho (Draft)

    SciTech Connect (OSTI)

    Subbarao, K.; Balcomb, J. D.

    1993-01-01T23:59:59.000Z

    This report describes tests and results of the energy performance of a credit union building in Idaho. The building is in the Energy Edge Program administered by the Bonneville Power Administration (BPA). BPA provided incentives to incorporate innovative features designed to conserve energy use by the building. It is of interest to determine the actual performance of these features. The objective of this project was to evaluate the applicability of the SERI short-term energy monitoring (STEM) method to nonresidential buildings.

  16. Short term generation scheduling in photovoltaic-utility grid with battery storage

    SciTech Connect (OSTI)

    Marwali, M.K.C.; Ma, H.; Shahidehpour, S.M. [Illinois Inst. of Tech., Chicago, IL (United States). Dept. of Electrical and Computer Engineering] [Illinois Inst. of Tech., Chicago, IL (United States). Dept. of Electrical and Computer Engineering; Abdul-Rahman, K.H. [Siemens Energy and Automation, Brooklyn Park, MN (United States)] [Siemens Energy and Automation, Brooklyn Park, MN (United States)

    1998-08-01T23:59:59.000Z

    This paper presents an efficient approach to short term resource scheduling for an integrated thermal and photovoltaic-battery generation. The proposed model incorporated battery storage for peak load shaving. Several constraints including battery capacity, minimum up/down time and ramp rates for thermal units, as well as natural photovoltaic (PV) capacity are considered in the proposed model. A case study composed of 26 thermal units and a PV-battery plant is presented to test the efficiency of the method.

  17. Performance and nutrient utilization of steers fed short term reconstituted grains

    E-Print Network [OSTI]

    Simpson, Edward James

    1982-01-01T23:59:59.000Z

    experiment. The ration's were composed on a dry basis of 86X grain and 14X of the same protein supplement used in the feeding experiment. Eight Beefmaster crossbred steers of the same origin and weight as those used in the growth trial were assigned...PERFORMANCE AND NUTRIENT UTILIZATION OF STEERS FED SHORT TERM RECONSTITUTED GRAINS A Thesis by EDWARD JAMES SIMPSON, JR. Submitted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree...

  18. ORIGINAL PAPER Short-term effect of tillage intensity on N2O and CO2 emissions

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    ORIGINAL PAPER Short-term effect of tillage intensity on N2O and CO2 emissions Pascal Boeckx negative to positive. We studied the short-term effect of tillage intensity on N2O and CO2 emissions. We site, an intermediately aerated Luvisol in Belgium, were similar. Nitrous oxide and CO2 emissions were

  19. 3818 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 28, NO. 4, NOVEMBER 2013 Short-Term Load Forecasting: The Similar Shape

    E-Print Network [OSTI]

    Sapatinas, Theofanis

    to electricity authorities worldwide to use as far as possible the low functionality cost machines for covering is performed by means of a weighted average of past daily load segments, the shape of which is similar is an integrable process in the design of power systems faced by electricity authorities world- wide. It involves

  20. Cloud tracking with optical flow for short-term solar forecasting Philip Wood-Bradley, Jos Zapata, John Pye

    E-Print Network [OSTI]

    , photovoltaic systems, and grid regulation (Mathiesen & Kleissl, 2011; Martínez López, et al, 2002). A method apart with a size of 640 by 480 pixels, were processed to determine the time taken for clouds to reach irradiance is essential for the effective operation of many solar applications such as solar thermal systems

  1. DOBEIA-0202(83/4Q) Short-Term Energy Outlook Quarterly Projections

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline prices4ConsumptionDOBEIA-0202(83/4Q) Short-Term

  2. DOE/EIA-0202(84/3Q) Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2Yonthly Energy : 4 aI la3Q) Short-Term

  3. Short-Term Energy Outlook Supplement: Weather Sensitivity in Natural Gas Markets

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19.Data Series: ProvedShort-Term

  4. Advanced statistical methods for shortterm wind power forecasting Research proposal draft

    E-Print Network [OSTI]

    Barnett, Alex

    Barnett July 2001 1 Background Over the last decade wind power has become a cost­effective alternative at a turbine) using linear or nonlinear time­series analysis (Alex­ iadis 1999), or 2) forecasting windAdvanced statistical methods for short­term wind power forecasting Research proposal draft Alex

  5. Using futures prices to filter short-term volatility and recover a latent, long-term price series for oil

    E-Print Network [OSTI]

    Herce, Miguel Angel

    2006-01-01T23:59:59.000Z

    Oil prices are very volatile. But much of this volatility seems to reflect short-term,transitory factors that may have little or no influence on the price in the long run. Many major investment decisions should be guided ...

  6. Implications of Wide-Area Geographic Diversity for Short- Term Variability of Solar Power

    SciTech Connect (OSTI)

    Mills, Andrew; Wiser, Ryan

    2010-08-23T23:59:59.000Z

    Worldwide interest in the deployment of photovoltaic generation (PV) is rapidly increasing. Operating experience with large PV plants, however, demonstrates that large, rapid changes in the output of PV plants are possible. Early studies of PV grid impacts suggested that short-term variability could be a potential limiting factor in deploying PV. Many of these early studies, however, lacked high-quality data from multiple sites to assess the costs and impacts of increasing PV penetration. As is well known for wind, accounting for the potential for geographic diversity can significantly reduce the magnitude of extreme changes in aggregated PV output, the resources required to accommodate that variability, and the potential costs of managing variability. We use measured 1-min solar insolation for 23 time-synchronized sites in the Southern Great Plains network of the Atmospheric Radiation Measurement program and wind speed data from 10 sites in the same network to characterize the variability of PV with different degrees of geographic diversity and to compare the variability of PV to the variability of similarly sited wind. The relative aggregate variability of PV plants sited in a dense 10 x 10 array with 20 km spacing is six times less than the variability of a single site for variability on time scales less than 15-min. We find in our analysis of wind and PV plants similarly sited in a 5 x 5 grid with 50 km spacing that the variability of PV is only slightly more than the variability of wind on time scales of 5-15 min. Over shorter and longer time scales the level of variability is nearly identical. Finally, we use a simple approximation method to estimate the cost of carrying additional reserves to manage sub-hourly variability. We conclude that the costs of managing the short-term variability of PV are dramatically reduced by geographic diversity and are not substantially different from the costs for managing the short-term variability of similarly sited wind in this region.

  7. Short-term Variations in the Galactic Environment of the Sun

    E-Print Network [OSTI]

    Priscilla C. Frisch; Jonathan D. Slavin

    2006-01-17T23:59:59.000Z

    The galactic environment of the Sun varies over short timescales as the Sun and interstellar clouds travel through space. Small variations in the dynamics, ionization, density, and magnetic field strength of the interstellar medium (ISM) surrounding the Sun yield pronounced changes in the heliosphere. We discuss essential information required to understand short-term variations in the galactic environment of the Sun, including the distribution and radiative transfer properties of nearby ISM, and variations in the boundary conditions of the heliosphere as the Sun traverses clouds. The most predictable transitions are when the Sun emerged from the Local Bubble interior and entered the cluster of local interstellar clouds flowing past the Sun, within the past 140,000 years, and again when the Sun entered the local interstellar cloud now surrounding and inside of the solar system, sometime during the past 44,000 years.

  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. Short-Term Energy Monitoring (STEM): Application of the PSTAR method to a residence in Fredericksburg, Virginia

    SciTech Connect (OSTI)

    Subbarao, K.; Burch, J.D.; Hancock, C.E.; Lekov, A.; Balcomb, J.D.

    1988-09-01T23:59:59.000Z

    This report describes a project to assess the thermal quality of a residential building based on short-term tests during which a small number of data channels are measured. The project is called Short- Term Energy Monitoring (STEM). Analysis of the data provides extrapolation to long-term performance. The test protocol and analysis are based on a unified method for building simulations and short-term testing called Primary and Secondary Terms Analysis and Renormalization (PSTAR). In the PSTAR method, renormalized parameters are introduced for the primary terms such that the renormalized energy balance is best satisfied in the least squares sense; hence, the name PSTAR. The mathematical formulation of PSTAR is detailed in earlier reports. This report describes the short-term tests and data analysis performed using the PSTAR method on a residential building in Fredricksburg, Virginia. The results demonstrate the ability of the PSTAR method to provide a realistically complex thermal model of a building, and determine from short-term tests the statics as well as the dynamics of a building, including solar dynamics. 10 refs., 12 figs., 2 tabs.

  10. Short-term and creep shear characteristics of a needlepunched thermally locked geosynthetic clay liner

    SciTech Connect (OSTI)

    Siebken, J.R. [National Seal Co., Galesburg, IL (United States). Technical Services; Swan, R.H. Jr.; Yuan, Z. [GeoSyntec Consultants, Atlanta, GA (United States). Soil-Geosynthetic Interaction Testing Lab.

    1997-11-01T23:59:59.000Z

    A series of constant-rate direct shear tests were conducted on a needlepunched thermally locked geosynthetic clay liner (GCL) in accordance with ASTM Test Method for Determining the Coefficient of Soil and Geosynthetic or Geosynthetic and Geosynthetic Friction by the Direct Shear Method (D 5321). The test results demonstrate that the needlepunched thermally locked reinforcing fibers provide substantial short-term shear strength to a GCL. However, there is a growing concern that the long-term shear strength to a GCL. However, there is a growing concern that the long-term shear strength of this type of GCL can be affected due to the potential of creep within the reinforcing fibers under sustained constant loads which occur in the field. An attempt was made to address this concern through an incrementally-loaded creep shear test conducted in a newly developed constant-load (creep) shear testing device. The results of the creep shear test to date show that the GCL has undergone relatively small shear displacements with incremental shear rates decreasing with time within each loading phase.

  11. European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind Generation by a Dynamic

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind. Abstract-Short-term wind power forecasting is recognized nowadays as a major requirement for a secure and economic integration of wind power in a power system. In the case of large-scale integration, end users

  12. Paper presented at EWEC 2008, Brussels, Belgium (31 March-03 April) Uncertainty Estimation of Wind Power Forecasts

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    -Antipolis, France Abstract--Short-term wind power forecasting tools providing "single-valued" (spot) predictions associated to the future wind power produc- tion for performing more efficiently functions such as reserves and modelling architec- tures for probabilistic wind power forecasting. Then, a comparison is carried out

  13. Short Term Irradiation Test of Fuel Containing Minor Actinides Using the Experimental Fast Reactor Joyo

    SciTech Connect (OSTI)

    Sekine, Takashi; Soga, Tomonori; Koyama, Shin-ichi; Aoyama, Takafumi [Oarai Research and Development Center, Japan Atomic Energy Agency. 4002 Narita, Oarai, Ibaraki 311-1393 (Japan); Wootan, David [Pacific Northwest National Laboratoy, M/S K8-34, P.O. Box 999 Richland, WA 99352 (United States)

    2007-07-01T23:59:59.000Z

    A mixed oxide containing minor actinides (MA-MOX) fuel irradiation program is being conducted using the experimental fast rector Joyo of the Japan Atomic Energy Agency to research early thermal behavior of MA-MOX fuel. Two irradiation experiments were conducted as part of the short-term phase of this program in May and August 2006. Six prepared fuel pins included MOX fuel containing 3% or 5% americium (Am-MOX), and MOX fuel containing 2% americium and 2% neptunium (Np/Am-MOX). The first test was conducted with high linear heat rates of approximately 430 W/cm maintained during only 10 minutes. After 10 minutes irradiation test, the test subassembly was transferred to the hot cell facility and an Am-MOX pin and a Np/Am-MOX pin were replaced with dummy pins with neutron dosimeters. The test subassembly loaded with the remaining four fuel pins was re-irradiated in Joyo for 24-hours in August 2006 at nearly the same linear power to obtain re-distribution data on MA-MOX fuel. The linear heat rate for each MA-MOX test fuel pin was calculated using the Monte Carlo calculation code MCNP. The calculated fission rates were compared with the measured data based on the Nd-148 method. The maximum linear heat rate was approximately 444{+-}19 W/cm at the actual reactor power of 119.6 MWt. Post irradiation examination of these pins to confirm the absence of fuel melting and the local concentration under irradiation of NpO{sub 2-x} or AmO{sub 2-x}, in the (U,Pu)0{sub 2-x}, fuel are underway. The test results are expected to reduce uncertainties on the margin in the thermal design for MA-MOX fuel. (authors)

  14. Image-Guided Techniques Improve the Short-term Outcome of Autologous Osteochondral Cartilage Repair Surgeries -An

    E-Print Network [OSTI]

    Stewart, James

    Image-Guided Techniques Improve the Short-term Outcome of Autologous Osteochondral Cartilage Repair and deliver osteochondral grafts remains problematic. We investigated whether image-guided methods (optically-guided and template-guided) can improve the outcome of mo- saic arthroplasty procedures. Methods: Fifteen sheep were

  15. Short-term Wind Power Prediction for Offshore Wind Farms -Evaluation of Fuzzy-Neural Network Based Models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Short-term Wind Power Prediction for Offshore Wind Farms - Evaluation of Fuzzy-Neural Network Based of offshore farms and their secure integration to the grid. Modeling the behavior of large wind farms presents the new considerations that have to be made when dealing with large offshore wind farms

  16. Short-term effects of oestradiol, T3 or insulin infusions on plasma concentrations and estimated hepatic balances

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Short-term effects of oestradiol, T3 or insulin infusions on plasma concentrations and estimated infusions on interme- diary and hepatic metabolism were studied in 4 preruminant male calves fed milk replac/kg BW), infused during the first h after feeding. Metabolite concentrations were determined

  17. 1256 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 18, NO. 4, NOVEMBER 2003 Short-Term Hydrothermal Generation Scheduling

    E-Print Network [OSTI]

    Catholic University of Chile (Universidad Católica de Chile)

    long and mid-term models, have been used to optimize the amount of hydro energy to be used during1256 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 18, NO. 4, NOVEMBER 2003 Short-Term Hydrothermal are obtained for each of both hydro and thermal units. Future cost curves of hydro generation, obtained from

  18. Neurocomputing 70 (2007) 16261629 A biophysical model of short-term plasticity at the calyx of Held

    E-Print Network [OSTI]

    Graham, Bruce

    2007-01-01T23:59:59.000Z

    dynamics, which include passive and activity-dependent recycling, calcium-dependent exocytosis activity-dependent vesicle recycling and a limited number of vesicle docking sites at each active zone. r- and postsynaptic factors. Earlier work has led to the vesicle depletion model for short-term synaptic depression

  19. Session 4: "Short-Term Energy Prices - What Drivers Matter Most?"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. AverageForecastEnergyEnwgy1:4:

  20. Use of short-term test systems for the prediction of the hazard represented by potential chemical carcinogens

    SciTech Connect (OSTI)

    Glass, L.R.; Jones, T.D.; Easterly, C.E.; Walsh, P.J.

    1990-10-01T23:59:59.000Z

    It has been hypothesized that results from short-term bioassays will ultimately provide information that will be useful for human health hazard assessment. Historically, the validity of the short-term tests has been assessed using the framework of the epidemiologic/medical screens. In this context, the results of the carcinogen (long-term) bioassay is generally used as the standard. However, this approach is widely recognized as being biased and, because it employs qualitative data, cannot be used to assist in isolating those compounds which may represent a more significant toxicologic hazard than others. In contrast, the goal of this research is to address the problem of evaluating the utility of the short-term tests for hazard assessment using an alternative method of investigation. Chemicals were selected mostly from the list of carcinogens published by the International Agency for Research on Carcinogens (IARC); a few other chemicals commonly recognized as hazardous were included. Tumorigenicity and mutagenicity data on 52 chemicals were obtained from the Registry of Toxic Effects of Chemical Substances (RTECS) and were analyzed using a relative potency approach. The data were evaluated in a format which allowed for a comparison of the ranking of the mutagenic relative potencies of the compounds (as estimated using short-term data) vs. the ranking of the tumorigenic relative potencies (as estimated from the chronic bioassays). Although this was a preliminary investigation, it offers evidence that the short-term tests systems may be of utility in ranking the hazards represented by chemicals which may contribute to increased carcinogenesis in humans as a result of occupational or environmental exposures. 177 refs., 8 tabs.

  1. CHANGES IN THE ELECTRICAL SURFACE CHARGE AND TRANSPLANTATION PROPERTIES OF TA3 ASCITES TUMOR CELLS DURING SHORT-TERM MAINTENANCE IN AN ISOTONIC SALT SOLUTION

    E-Print Network [OSTI]

    Tenforde, T.S.

    2013-01-01T23:59:59.000Z

    CELLS DURING SHORT-TERM MAINTENANCE IN AN ISOTONIC SALTcells. In conclusion, the maintenance of TA3 ascites cellslhort-term tumor cell maintenance in vitro. REFERENCES

  2. PSTAR: Primary and secondary terms analysis and renormalization: A unified approach to building energy simulations and short-term monitoring

    SciTech Connect (OSTI)

    Subbarao, K.

    1988-09-01T23:59:59.000Z

    This report presents a unified method of hourly simulation of a building and analysis of performance data. The method is called Primary and Secondary Terms Analysis and Renormalization (PSTAR). In the PSTAR method, renormalized parameters are introduced for the primary terms such that the renormalized energy balance equation is best satisfied in the least squares sense, hence, the name PSTAR. PSTAR allows extraction of building characteristics from short-term tests on a small number of data channels. These can be used for long-term performance prediction (''ratings''), diagnostics, and control of heating, ventilating, and air conditioning systems (HVAC), comparison of design versus actual performance, etc. By combining realistic building models, simple test procedures, and analysis involving linear equations, PSTAR provides a powerful tool for analyzing building energy as well as testing and monitoring. It forms the basis for the Short-Term Energy Monitoring (STEM) project at SERI.

  3. A Calibration Methodology for Retrofit Projects Using Short-Term Monitoring and Disaggregated Energy Use Data

    E-Print Network [OSTI]

    Soebarto, V. I.; Degelman, L. O.

    1996-01-01T23:59:59.000Z

    show that the differences between the disaggregated energy use based the monthly utility records and measured data are only 0.3% for the fan energy and 0.08% for lights and receptacles. SD. Wim DM So. Coolim Fm Liphtitq .Meawed Daa ODiszggrag...

  4. Methodology for Analyzing Energy and Demand Savings From Energy Services Performance Contract Using Short-Term Data

    E-Print Network [OSTI]

    Liu, Z.; Haberl, J. S.; Cho, S.; Lynn, B.; Cook, M.

    2006-01-01T23:59:59.000Z

    . New methods, which were developed to measure hourly demand savings from short-term data, were also discussed. INTRODUCTION The Fort Hood Army Base has selected an Energy Services Performance Contract (ESPC) contractor to help achieve its... energy reduction goals as mandated by Executive Order. This ESPC is expected to be a $3.8 million, 20 year contract, which includes five primary types of Energy Conservation Measures (ECMs) in 58 buildings, including: boiler insulation, control...

  5. Short term effects of commercial polychlorinated biphenyl (PCB) mixtures and individual PCB congeners in female Sprague-Dawley rats

    E-Print Network [OSTI]

    Chen, Yu-Chyu

    1992-01-01T23:59:59.000Z

    fulfillment of the requirements for the degree of MASTER OF SCIENCE December 1992 Major subject: Toxicology SHORT TERM EFFECTS OF COMMERCIAL POLYCHLORINATED BIPHENYL (PCB) MIXTURES AND INDIVIDUAL PCB CONGENERS IN FEMALE SPRAGUE-DAWLEY RATS A Thesis... of isomers 3 12 24 42 46 42 24 12 3 1 209 This thesis followed the format and style of Toxicology and Applied Pharmacology. isomers and congeners in which there are differences with respect to the number of halogen atoms and their substitution...

  6. Paper accepted for presentation at 2003 IEEE Bologna PowerTech Conference, June 23-26, Bologna, Italy Wind Power Forecasting using Fuzzy Neural Networks

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    , Italy Wind Power Forecasting using Fuzzy Neural Networks Enhanced with On-line Prediction Risk) as input, to predict the power production of wind park8 48 hours ahead. The prediction system integrates of the numerical weather predictions. Index Term-Wind power, short-term forecasting, numerical weather predictions

  7. System model Scope of Work Short term power constraint Long term power constraint Imperfect CSIR Prediction Summary Spatial and Temporal Power Allocation for MISO

    E-Print Network [OSTI]

    Bhashyam, Srikrishna

    System model Scope of Work Short term power constraint Long term power constraint Imperfect CSIR Prediction Summary Spatial and Temporal Power Allocation for MISO Systems with Delayed Feedback Srikrishna) feedback #12;System model Scope of Work Short term power constraint Long term power constraint Imperfect

  8. Dose-Escalated Radiotherapy for High-Risk Prostate Cancer: Outcomes in Modern Era With Short-Term Androgen Deprivation Therapy

    SciTech Connect (OSTI)

    Liauw, Stanley L., E-mail: sliauw@radonc.uchicago.ed [Department of Radiation and Cellular Oncology, University of Chicago Pritzker School of Medicine, Chicago, IL (United States); Stadler, Walter M. [Department of Medical Oncology, University of Chicago Pritzker School of Medicine, Chicago, IL (United States); Correa, David B.S.; Weichselbaum, Ralph R. [Department of Radiation and Cellular Oncology, University of Chicago Pritzker School of Medicine, Chicago, IL (United States); Jani, Ashesh B. [Department of Radiation Oncology, Emory University, Atlanta, GA (United States)

    2010-05-01T23:59:59.000Z

    Purpose: Randomized data have supported the use of long-term androgen deprivation therapy (ADT) combined with radiotherapy (RT) for men with high-risk prostate cancer. The present study reviewed the outcomes of intermediate- and high-risk men treated with RT and short-term ADT. Materials and Methods: A total of 184 men with any single risk factor of prostate-specific antigen >=10 ng/mL, clinical Stage T2b or greater, or Gleason score >=7 were treated with primary external beam RT for nonmetastatic adenocarcinoma of the prostate. The median radiation dose was 74 Gy; 55% were treated with intensity-modulated RT. All patients received ADT for 1 to 6 months (median, 4), consisting of a gonadotropin-releasing hormone analog. Univariate and multivariable analyses were performed for risk factors, including T stage, Gleason score, radiation dose, and prostate-specific antigen level. Results: With a median follow-up of 51 months, the 4-year freedom from biochemical failure (FFBF) using the nadir plus 2 ng/mL definition was 83% for all patients. Clinical Stage T3 disease was the only variable tested associated with FFBF on univariate (4-year FFBF rate, 46% vs. 87% for Stage T1-T2c disease; p = .0303) and multivariable analysis (hazard ratio, 3.9; p = .0016). On a subset analysis of high-risk patients (National Comprehensive Cancer Network criteria), those with clinical Stage T3 disease (4-year FFBF rate, 46% vs. 80%; p = .0303) and a radiation dose <74 Gy (4-year FFBF rate, 64% vs. 80%) had a poorer outcome on univariate analysis. However, clinical Stage T3 disease and radiation dose were not significant on multivariable analysis, although a statistical multivariable trend was seen for both (p = .0650 and p = .0597, respectively). Conclusion: Short-term ADT and RT might be acceptable for men with intermediate- and high-risk prostate cancer, especially for clinically localized disease treated with doses of >=74 Gy.

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

    SciTech Connect (OSTI)

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

    2013-05-01T23:59:59.000Z

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

  10. EWEC 2006 Scientific Track Advanced Forecast Systems for the Grid Integration of 25 GW

    E-Print Network [OSTI]

    Heinemann, Detlev

    forecasts, smoothing effects Abstract The economic success of offshore wind farms in liberalised electricity of offshore wind farms, their electricity production must be known well in advance to allow an efficient Oldenburg, Germany Key words: Offshore wind power, grid integration, short-term prediction, regional

  11. Skill forecasting from ensemble predictions of wind power P. Pinson,a

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Skill forecasting from ensemble predictions of wind power P. Pinson,a , H.Aa. Nielsena , H. Madsena with the commonly provided short-term wind power point predictions. Alternative approaches for the use uncertainty (and potential energy imbalances). Wind power ensemble predictions are derived from the conversion

  12. HyperionOpexModule Budget/8MonthReview

    E-Print Network [OSTI]

    Hitchcock, Adam P.

    HyperionOpexModule­ Budget/8MonthReview #12;Hyperion Opex Module ­ Budget/8 Month Review 1 ................................................................................................................................................... 6 Step 4 ­ Enter the Forecast and Budget .............................................................................................................................. 14 Copy 8 Month Review into next year's budget

  13. Short-Term Energy Outlook Supplement: Status of Libyan Loading Ports and Oil and Natural Gas Fields

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctoberOutlookShort-Term

  14. Short term Variability of the Sun Earth System: An Overview of Progress Made during the CAWSES II Period

    E-Print Network [OSTI]

    Gopalswamy, Nat; Yan, Yihua

    2015-01-01T23:59:59.000Z

    This paper presents an overview of results obtained during the CAWSES II period on the short term variability of the Sun and how it affects the near Earth space environment. CAWSES II was planned to examine the behavior of the solar terrestrial system as the solar activity climbed to its maximum phase in solar cycle 24. After a deep minimum following cycle 23, the Sun climbed to a very weak maximum in terms of the sunspot number in cycle 24 (MiniMax24), so many of the results presented here refer to this weak activity in comparison with cycle 23. The short term variability that has immediate consequence to Earth and geospace manifests as solar eruptions from closed field regions and high speed streams from coronal holes. Both electromagnetic (flares) and mass emissions (coronal mass ejections, CMEs) are involved in solar eruptions, while coronal holes result in high speed streams that collide with slow wind forming the so called corotating interaction regions (CIRs). Fast CMEs affect Earth via leading shocks ...

  15. Prediction of short-term and long-term VOC emissions from SBR bitumen-backed carpet under different temperatures

    SciTech Connect (OSTI)

    Yang, S.; Chen, Q. [Massachusetts Inst. of Tech., Cambridge, MA (United States). Building Technology Program; Bluyssen, P.M. [TNO Building and Construction Research, Delft (Netherlands)

    1998-12-31T23:59:59.000Z

    This paper presents two models for volatile organic compound (VOC) emissions from carpet. One is a numerical model using the computational fluid dynamics (CFD) technique for short-term predictions, the other an analytical model for long-term predictions. The numerical model can (1) deal with carpets that are not new, (2) calculate the time-dependent VOC distributions in a test chamber or room, and (3) consider the temperature effect on VOC emissions. Based on small-scale chamber data, both models were used to examine the VOC emissions under different temperatures from polypropene styrene-butadiene rubber (SBR) bitumen-backed carpet. The short-term predictions show that the VOC emissions under different temperatures can be modeled solely by changing the carpet diffusion coefficients. A formulation of the Arrhenius relation was used to correlate the dependence of carpet diffusion coefficient with temperature. The long-term predictions show that it would take several years to bake out the VOCs, and temperature would have a major impact on the bake-out time.

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18T23:59:59.000Z

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

  17. An evaluation of the Gilian TRACEAIR Organic Vapor Monitoring Diffusive Badge in measuring short-term exposure levels of benzene under field conditions 

    E-Print Network [OSTI]

    Pierce, Mark Edward

    1996-01-01T23:59:59.000Z

    The objective of this research is to evaluate the performance of the Gilian TRACEAIR Organic Vapor Monitoring I (OVMI) Diffusive Badge in measuring short-term benzene exposures under field conditions. In general, a diffusive badge is a device which...

  18. Determining Long-Term Performance of Cool Storage Systems from Short-Term Tests; Literature Review and Site Selection, Nov. 1997 (Revised Feb. 1998)

    E-Print Network [OSTI]

    Haberl, J. S.; Claridge, D. E.; Reddy, T. A.; Elleson, J.

    1997-01-01T23:59:59.000Z

    This is the preliminary report contains the literature review and site selection recommendations for ASHRAE Research Project RP 1004 — "Determining Long-term Performance of Cool Storage Systems From Short-term Tests"....

  19. Visualization of short-term heart period variability with network tools as a method for quantifying autonomic drive

    E-Print Network [OSTI]

    Makowiec, Danuta; Kaczkowska, Agnieszka; Graff, Grzegorz; Wejer, Dorota; Wdowczyk, Joanna; Zarczynska-Buchowiecka, Marta; Gruchala, Marcin; Struzik, Zbigniew R

    2014-01-01T23:59:59.000Z

    Signals from heart transplant recipients can be considered to be a natural source of information for a better understanding of the impact of the autonomic nervous system on the complexity of heart rate variability. Beat-to-beat heart rate variability can be represented as a network of increments between subsequent $RR$-intervals, which makes possible the visualization of short-term heart period fluctuations. A network is constructed of vertices representing increments between subsequent $RR$-intervals, and edges which connect adjacent $RR$-increments. Two modes of visualization of such a network are proposed. The method described is applied to nocturnal Holter signals recorded from healthy young people and from cardiac transplant recipients. Additionally, the analysis is performed on surrogate data: shuffled RR-intervals (to display short-range dependence), and shuffled phases of the Fourier Transform of RR-intervals (to filter out linear dependences). Important nonlinear properties of autonomic nocturnal reg...

  20. International Statistical Review (2012), 80, 1, 223 doi:10.1111/j.1751-5823.2011.00168.x Short-Term Wind Speed Forecasting

    E-Print Network [OSTI]

    Genton, Marc G.

    2012-01-01T23:59:59.000Z

    the overall energy consumption by 20% through improved energy efficiency by 2020; see European Union (EU of Statistics, Texas A&M University, College Station, TX 77843-3143, USA E-mails: xzhu@stat.tamu.edu, genton@stat.tamu.edu Summary The emphasis on renewable energy and concerns about the environment have led to large-scale wind

  1. Microstructural evolution of delta ferrite in SAVE12 steel under heat treatment and short-term creep

    SciTech Connect (OSTI)

    Li, Shengzhi, E-mail: lishengzhi@sjtu.edu.cn [School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)] [School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China); Eliniyaz, Zumrat; Zhang, Lanting; Sun, Feng [School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)] [School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China); Shen, Yinzhong [School of Nuclear Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)] [School of Nuclear Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China); Shan, Aidang, E-mail: adshan@sjtu.edu.cn [School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)] [School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)

    2012-11-15T23:59:59.000Z

    This research focused on the formation and microstructural evolution of delta ferrite phase in SAVE12 steel. The formation of delta ferrite was due to the high content of ferrite forming alloy elements such as Cr, W, and Ta. This was interpreted through either JMatPro-4.1 computer program or Cr{sub eq} calculations. Delta ferrite was found in bamboo-like shape and contained large amount of MX phase. It was surrounded by Laves phases before creep or aging treatment. Annealing treatments were performed under temperatures from 1050 Degree-Sign C to 1100 Degree-Sign C and various time periods to study its dissolution kinetics. The result showed that most of the delta ferrite can be dissolved by annealing in single phase austenitic region. Dissolution process of delta ferrite may largely depend on dissolution kinetic factors, rather than on thermodynamic factors. Precipitation behavior during short-term (1100 h) creep was investigated at temperature of 600 Degree-Sign C under a stress of 180 MPa. The results demonstrated that delta ferrite became preferential nucleation sites for Laves phase at the early stage of creep. Laves phase on the boundary around delta ferrite showed relatively slower growth and coarsening rate than that inside delta ferrite. - Highlights: Black-Right-Pointing-Pointer Delta ferrite is systematically studied under heat treatment and short-term creep. Black-Right-Pointing-Pointer Delta ferrite contains large number of MX phase and is surrounded by Laves phases before creep or aging treatment. Black-Right-Pointing-Pointer Formation of delta ferrite is interpreted by theoretical and empirical methods. Black-Right-Pointing-Pointer Most of the delta ferrite is dissolved by annealing in single phase austenitic region. Black-Right-Pointing-Pointer Delta ferrite becomes preferential nucleation sites for Laves phase at the early stage of creep.

  2. Ichno-sedimentological record of short-term climate-controlled redox events and cycles in organic-rich strata

    SciTech Connect (OSTI)

    Savrda, C.E. (Auburn Univ., AL (USA)); Bottjher, D.J. (Univ. of Southern California, Los Angeles (USA)); Ozalas, K. (Auburn Univ., AL (USA))

    1990-05-01T23:59:59.000Z

    Reduced rates of biochemical degradation of organic matter in oxygen-depleted marine settings generally result in the accumulation of laminated strata with high hydrocarbon source potential. Periods of improved oxygenation, during which the quantity and quality of organic matter are effectively reduced, are reflected by interbedded bioturbated intervals. Such benthic redox excursions may reflect variable paleooceanographic responses to climatic events or cycles. The potential role of climate in the short-term modulation of source rock potential is exemplified by bioturbated intervals within three predominantly laminated organic-rich units. The Jurassic Posidonia Shale (Germany) contains bioturbated beds whose ichnologic characteristics reflect a spectrum from short, low-magnitude redox events to longer episodes of greater magnitude. The character and distribution of these event beds appear to be controlled by sea level mediated variations in the frequency and intensity of storm-induced basin turnover. Bioturbated beds of the Upper Cretaceous Niobrara Formation (Colorado) are characterized by four oxygen-related ichnocoenoses, the distribution of which reflects cyclic variations in redox conditions. Relationships between paleooxygenation and organic-carbon and carbonate contents, and estimated cycle periodicities, suggest that redox variations were controlled by wet-dry climatic cycles modulated by the Milankovitch cycle of axial precession. Bioturbated beds within slope and basinal facies of the Miocene Monterey Formation (California) are variable in character, reflecting differences in duration and magnitude of associated oxygenation episodes, and may be in response to short-term variations in wind-stress-induced upwelling and/or ice-volume-controlled eustatic sea level changes.

  3. Effects of various uranium leaching procedures on soil: Short-term vegetation growth and physiology. Progress report, April 1994

    SciTech Connect (OSTI)

    Edwards, N.T.

    1994-08-01T23:59:59.000Z

    Significant volumes of soil containing elevated levels of uranium exist in the eastern United States. The contamination resulted from the development of the nuclear industry in the United States requiring a large variety of uranium products. The contaminated soil poses a collection and disposal problem of a magnitude that justifies the development of decontamination methods. Consequently, the Department of Energy (DOE) Office of Technology Development formed the Uranium Soils Integrated Demonstration (USID) program to address the problem. The fundamental goal of the USID task group has been the selective extraction/leaching or removal of uranium from soil faster, cheaper, and safer than what can be done using current conventional technologies. The objective is to selectively remove uranium from soil without seriously degrading the soil`s physicochemical characteristics and without generating waste that is difficult to manage and/or dispose of. However, procedures developed for removing uranium from contaminated soil have involved harsh chemical treatments that affect the physicochemical properties of the soil. The questions are (1) are the changes in soil properties severe enough to destroy the soil`s capacity to support and sustain vegetation growth and survival? and (2) what amendments might be made to the leached soil to return it to a reasonable vegetation production capacity? This study examines the vegetation-support capacity of soil that had been chemically leached to remove uranium. The approach is to conduct short-term germination and phytotoxicity tests for evaluating soils after they are subjected to various leaching procedures followed by longer term pot studies on successfully leached soils that show the greatest capacity to support plant growth. This report details the results from germination and short-term phytotoxicity testing of soils that underwent a variety of leaching procedures at the bench scale at ORNL and at the pilot plant at Fernald.

  4. Space-time forecasting and evaluation of wind speed with statistical tests for comparing accuracy of spatial predictions

    E-Print Network [OSTI]

    Hering, Amanda S.

    2010-10-12T23:59:59.000Z

    High-quality short-term forecasts of wind speed are vital to making wind power a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information...

  5. Solid low-level waste forecasting guide

    SciTech Connect (OSTI)

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

    1995-03-01T23:59:59.000Z

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

  6. European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. State-of-the-Art on Methods and Software Tools for Short-Term

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. State-of-the-Art on Methods and Software Tools for Short-Term Prediction of Wind Energy Production G. Giebel*, L. Landberg, Risoe National Roskilde, Denmark Abstract: The installed wind energy capacity in Europe today is 20 GW, while

  7. Oxygen isotope content of CO2 in nocturnal ecosystem respiration: 2. Short-term dynamics of foliar and soil component fluxes in an

    E-Print Network [OSTI]

    Ehleringer, Jim

    Oxygen isotope content of CO2 in nocturnal ecosystem respiration: 2. Short-term dynamics of foliar; accepted 29 October 2003; published 23 December 2003. [1] The oxygen isotope contents (d18 O) of soil showed enrichment over a 2-week sampling period as the weather became hot and dry (leaves 0.9 to 15

  8. A Methodology to Characterize Ideal Short-term Counting Conditions and Improve AADT Estimation Accuracy Using a Regression-based Correcting

    E-Print Network [OSTI]

    Bertini, Robert L.

    -established and robust with clear guidelines to collect short-term count data, to analyze data and develop annual average a statewide system of non-motorized data. From a planning point of view, a key measure of traffic volumes continuous counts comes from the AASHTO Guidelines for Traffic Data Programs, prepared in 1992 (AASHTO, 1992

  9. Determining Long-Term Performance of Cool Storage Systems from Short-Term Tests, Progress Report, 6-99, Revised 12-99

    E-Print Network [OSTI]

    Reddy, T. A.; Elleson, J.; Haberl, J. S.

    1999-01-01T23:59:59.000Z

    This is the Spring 1999 progress report on ASHRAE Research Project RP 1004: Determining Long-Term Performance of Cool Storage Systems from Short-Term Tests. This report presents an update concerning the work that has been accomplished since the June...

  10. Estimation of original gas in place from short-term shut-in pressure data for commingled tight gas reservoirs with no crossflow 

    E-Print Network [OSTI]

    Khuong, Chan Hung

    1995-01-01T23:59:59.000Z

    gas production (GP) under these circumstances. This research studies different empirical methods to estimate the original gas in place (OGIP) for one-layer or commingled two-layer tight gas reservoirs without crossflow, from short-term (72-hour) shut...

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

    E-Print Network [OSTI]

    Statton, James Cody

    2012-07-16T23:59:59.000Z

    . 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%....

  12. 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

  13. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

    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:

  14. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

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

    2011-02-23T23:59:59.000Z

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

  15. A Solution Approach for Optimizing Long-and Short-term Production Scheduling at LKAB's Kiruna Mine

    E-Print Network [OSTI]

    mine located in northern Sweden. The model min- imizes deviations from monthly preplanned production a production schedule 1 Introduction LKAB's Kiruna iron ore mine, located in northern Sweden, satisfies

  16. Multi-color Near Infra-red Intra-day and Short Term Variability of the Blazar S5 0716+714

    E-Print Network [OSTI]

    Alok C. Gupta; Sang-Mok Cha; Sungho Lee; Ho Jin; Soojong Pak; Seoung-hyun Cho; Bongkon Moon; Youngsik Park; In-Soo Yuk; Uk-won Nam; Jaemann Kyeong

    2008-09-19T23:59:59.000Z

    In this paper, we report results of our near-infrared (NIR) photometric variability studies of the BL Lacertae object S5 0716+714. NIR photometric observations spread over 7 nights during our observing run April 2-9, 2007 at 1.8 meter telescope equipped with KASINICS (Korea Astronomy and Space Science Institute Near Infrared Camera System) and J, H, and Ks filters at Bohyunsan Optical Astronomy Observatory (BOAO), South Korea. We searched for intra-day variability, short term variability and color variability in the BL Lac object. We have not detected any genuine intra-day variability in any of J, H, and Ks passbands in our observing run. Significant short term variability ~ 32.6%, 20.5% and 18.2% have been detected in J, H, Ks passbands, respectively, and ~ 11.9% in (J-H) color.

  17. Modification of the pattern informatics method for forecasting large earthquake events using complex eigenvectors

    E-Print Network [OSTI]

    Holliday, J R; Klein, B; Rundle, J B; Tiampo, K F

    2006-01-01T23:59:59.000Z

    Recent studies have shown that real-valued principal component analysis can be applied to earthquake fault systems for forecasting and prediction. In addition, theoretical analysis indicates that earthquake stresses may obey a wave-like equation, having solutions with inverse frequencies for a given fault similar to those that characterize the time intervals between the largest events on the fault. It is therefore desirable to apply complex principal component analysis to develop earthquake forecast algorithms. In this paper we modify the Pattern Informatics method of earthquake forecasting to take advantage of the wave-like properties of seismic stresses and utilize the Hilbert transform to create complex eigenvectors out of measured time series. We show that Pattern Informatics analyses using complex eigenvectors create short-term forecast hot-spot maps that differ from hot-spot maps created using only real-valued data and suggest methods of analyzing the differences and calculating the information gain.

  18. arXiv:1007.3122v2[q-bio.NC]30Jan2013 Robust Short-Term Memory without Synaptic

    E-Print Network [OSTI]

    Johnson, Samuel

    been stored in samuel.johnson@imperial.ac.uk 1 #12;our brains previously (not very credible). Here wearXiv:1007.3122v2[q-bio.NC]30Jan2013 Robust Short-Term Memory without Synaptic Learning Samuel Johnson1,2, , J. Marro3 , and Joaqu´in J. Torres3 1 Department of Mathematics, Imperial College London, SW

  19. An assay of duck hepatitis virus induced interferon, produced in duck embryo fibro-blasts which have experienced short term treatment with DDT

    E-Print Network [OSTI]

    Bauder, Richard Burgess

    1973-01-01T23:59:59.000Z

    AN ASSAY OP DUCK HEPATITIS VIRUS INDUCED INTERFERON, PRODUCED IN DUCK EMBRYO FIBROBLASTS WHICH HAVE EXPERIENCED SHORT TERM TREATMENT WITH DDT A Thesis by BURGESS BAUDER Submitted to the Graduate College of Texas A&M University in Partial... WITH DDT A Thesi. s by /'. ". " . "i BURGESS BAUDER Approved as to style and content by: (Chairm of Committee) (Head of Depar ent) (Member) (Member) (Member) August 1973 ABSTRACT An Assay of Duck Hepatitis Virus Induced Interferon, Produced...

  20. PSTAR: Primary and secondary terms analysis and renormalization: A unified approach to building energy simulations and short-term monitoring: A summary

    SciTech Connect (OSTI)

    Subbarao, K.

    1988-09-01T23:59:59.000Z

    This report summarizes a longer report entitled PSTAR - Primary and Secondary Terms Analysis and Renormalization. A Unified Approach to Building Energy Simulations and Short-Term Monitoring. These reports highlight short-term testing for predicting long-term performance of residential buildings. In the PSTAR method, renormalized parameters are introduced for the primary terms such that the renormalized energy balance equation is best satisfied in the least squares sense; hence, the name PSTAR. Testing and monitoring the energy performance of buildings has several important applications, among them: extrapolation to long-term performance, refinement of design tools through feedback from comparing design versus actual parameters, building-as-a-calorimeter for heating, ventilating, and air conditioning (HVAC) diagnostics, and predictive load control. By combining realistic building models, simple test procedures, and analysis involving linear equations, PSTAR provides a powerful tool for analyzing building energy as well as testing and monitoring. It forms the basis for the Short-Term Energy Monitoring (STEM) project at SERI. 3 figs., 1 tab.

  1. 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

    2015-08-01T23:59:59.000Z

    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. This information is then applied to stitch images together into largermore »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

  2. Monthly Teleconferences

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > The EnergyCenterDioxide CaptureSee the Foundry's fullMonthly NUG

  3. Winchester/Camberley Homes New Construction Test House Design, Construction, and Short-Term Testing in a Mixed-Humid Climate

    SciTech Connect (OSTI)

    Mallav, D.; Wiehagen, J.; Wood, A.

    2012-10-01T23:59:59.000Z

    The NAHB Research Center partnered with production builder Winchester/Camberley Homes to build a DOE Building America New Construction Test House (NCTH). This single family, detached house, located in the mixed-humid climate zone of Silver Spring, MD, was completed in June 2011. The primary goal for this house was to improve energy efficiency by 30% over the Building America B10 benchmark by developing and implementing an optimized energy solutions package design that could be cost effectively and reliably constructed on a production basis using quality management practices. The intent of this report is to outline the features of this house, discuss the implementation of the energy efficient design, and report on short-term testing results. During the interactive design process of this project, numerous iterations of the framing, air sealing, insulation, and space conditioning systems were evaluated for energy performance, cost, and practical implementation. The final design featured numerous advanced framing techniques, high levels of insulation, and the HVAC system entirely within conditioned space. Short-term testing confirmed a very tight thermal envelope and efficient and effective heating and cooling. In addition, relevant heating, cooling, humidity, energy, and wall cavity moisture data will be collected and presented in a future long-term report.

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

    SciTech Connect (OSTI)

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

    1995-05-01T23:59:59.000Z

    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.

  5. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

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

  6. Technology Forecasting Scenario Development

    E-Print Network [OSTI]

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

  7. Rainfall-River Forecasting

    E-Print Network [OSTI]

    US Army Corps of Engineers

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

  8. ANNOUNCEMENT Short-Term Course

    E-Print Network [OSTI]

    Srivastava, Kumar Vaibhav

    to reduction in underground-based carbon resources. This has propelled the development of advanced engine-treatment such as selective catalyst reduction and NOx storage catalysts · Oxidation catalysts for VOC, and hydrocarbon-2). There will be a book exhibition on one evening. The first day of the course i.e. 28th June will be for the field visit

  9. ANNOUNCEMENT Short-Term Course

    E-Print Network [OSTI]

    Srivastava, Kumar Vaibhav

    to reduction in underground-based carbon resources. This has propelled the development of advanced engine traps · Selective catalytic reduction technique · NOx storage catalysts · engine system strategies will be for the field visit to Engine Development Directorate, RDSO Lucknow, Ministry of Railways (Not compulsory

  10. ANNOUNCEMENT Short-Term Course

    E-Print Network [OSTI]

    Srivastava, Kumar Vaibhav

    to reduction in underground- based carbon resources. This has propelled the development of advanced engine traps · Selective catalytic reduction technique · NOx storage catalysts · engine system strategies will be for the field visit to Engine Development Directorate, RDSO Lucknow, Ministry of Railways (Not compulsory

  11. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del Sol HomeFacebookScholarship Fund scholarshipsShedding LightShinyShorei

  12. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del Sol HomeFacebookScholarship Fund scholarshipsShedding LightShinyShorei

  13. Short-Term Energy Outlook

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19.Data Series: Proved Reserves

  14. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13 13 13

  15. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13 13 133 1

  16. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13 13

  17. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13 13(STEO)

  18. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13

  19. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13 1 December

  20. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13 1

  1. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13 1(STEO)

  2. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13

  3. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13June 2014 1

  4. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13June 2014

  5. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13June 2014

  6. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13June

  7. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13June(STEO)

  8. Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13June(STEO)4

  9. Short-Term Energy Outlook

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17 3400, U.S. DEPARTMENT OF ENERGY OMB No.Despite dropnatural

  10. Effect of short-term exposure to dichlorvos on synaptic plasticity of rat hippocampal slices: Involvement of acylpeptide hydrolase and {alpha}{sub 7} nicotinic receptors

    SciTech Connect (OSTI)

    Olmos, Cristina; Sandoval, Rodrigo [Laboratory of Environmental Neurotoxicology, Department of Biomedical Sciences, Faculty of Medicine, Universidad Catolica del Norte, Larrondo 1281, 178-1421 Coquimbo (Chile); Rozas, Carlos [Laboratory of Neurosciences, Department of Biology, Faculty of Chemistry and Biology, Universidad de Santiago de Chile, Alameda 3363, Santiago (Chile); Navarro, Sebastian [Laboratory of Environmental Neurotoxicology, Department of Biomedical Sciences, Faculty of Medicine, Universidad Catolica del Norte, Larrondo 1281, 178-1421 Coquimbo (Chile); Wyneken, Ursula [Laboratory of Neurosciences, Faculty of Medicine, Universidad de Los Andes, San Carlos de Apoquindo 2200, Santiago (Chile); Zeise, Marc [School of Psychology, Faculty of Humanities, University of Santiago de Chile, Alameda 3363, Santiago (Chile); Morales, Bernardo [Laboratory of Neurosciences, Department of Biology, Faculty of Chemistry and Biology, Universidad de Santiago de Chile, Alameda 3363, Santiago (Chile); Pancetti, Floria [Laboratory of Environmental Neurotoxicology, Department of Biomedical Sciences, Faculty of Medicine, Universidad Catolica del Norte, Larrondo 1281, 178-1421 Coquimbo (Chile)], E-mail: pancetti@ucn.cl

    2009-07-01T23:59:59.000Z

    Dichlorvos is the active molecule of the pro-drug metrifonate used to revert the cognitive deficits associated with Alzheimer's disease. A few years ago it was reported that dichlorvos inhibits the enzyme acylpeptide hydrolase at lower doses than those necessary to inhibit acetylcholinesterase to the same extent. Therefore, the aim of our investigation was to test the hypothesis that dichlorvos can enhance synaptic efficacy through a mechanism that involves acylpeptide hydrolase instead of acetylcholinesterase inhibition. We used long-term potentiation induced in rat hippocampal slices as a model of synaptic plasticity. Our results indicate that short-term exposures (20 min) to 50 {mu}M dichlorvos enhance long-term potentiation in about 200% compared to the control condition. This effect is correlated with approximately 60% inhibition of acylpeptide hydrolase activity, whereas acetylcholinesterase activity remains unaffected. Paired-pulse facilitation and inhibition experiments indicate that dichlorvos does not have any presynaptic effect in the CA3 {yields} CA1 pathway nor affect gabaergic interneurons. Interestingly, the application of 100 nM methyllicaconitine, an {alpha}{sub 7} nicotinic receptor antagonist, blocked the enhancing effect of dichlorvos on long-term potentiation. These results indicate that under the exposure conditions described above, dichlorvos enhances long-term potentiation through a postsynaptic mechanism that involves (a) the inhibition of the enzyme acylpeptide hydrolase and (b) the modulation of {alpha}{sub 7} nicotinic receptors.

  11. Probabilistic manpower forecasting

    E-Print Network [OSTI]

    Koonce, James Fitzhugh

    1966-01-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2012-08-15T23:59:59.000Z

    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.

  13. UPF Forecast | Y-12 National Security Complex

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

    Uranium Processing Facility UPF Forecast UPF Forecast UPF Procurement provides the following forecast of subcontracting opportunities. Keep in mind that these requirements may be...

  14. Long Term Forecast ofLong Term Forecast of TsunamisTsunamis

    E-Print Network [OSTI]

    : ImproveImprove NOAANOAA''ss understandingunderstanding and forecast capabilityand forecast capability inin

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

    SciTech Connect (OSTI)

    Eisenberg, Joel F. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2005-10-31T23:59:59.000Z

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

  16. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 14 SEPTEMBER 27, 2011

    E-Print Network [OSTI]

    that we are trying to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index of tropical cyclone activity starting in early August. We have decided to discontinue our individual monthly for ACE using three categories as defined in Table 1. Table 1: ACE forecast definition. Parameter

  17. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 14 SEPTEMBER 27, 2012

    E-Print Network [OSTI]

    Gray, William

    that we are trying to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index of tropical cyclone activity starting in early August. We have decided to discontinue our individual monthly for ACE using three categories as defined in Table 1. Table 1: ACE forecast definition. Parameter

  18. INFRARED OBSERVATIONS OF THE MILLISECOND PULSAR BINARY J1023+0038: EVIDENCE FOR THE SHORT-TERM NATURE OF ITS INTERACTING PHASE IN 2000-2001

    SciTech Connect (OSTI)

    Wang, Xuebing; Wang, Zhongxiang [Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 80 Nandan Road, Shanghai 200030 (China)] [Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 80 Nandan Road, Shanghai 200030 (China); Morrell, Nidia [Las Campanas Observatory, Observatories of the Carnegie Institution of Washington, La Serena (Chile)] [Las Campanas Observatory, Observatories of the Carnegie Institution of Washington, La Serena (Chile)

    2013-02-20T23:59:59.000Z

    We report our multi-band infrared (IR) imaging of the transitional millisecond pulsar system J1023+0038, a rare pulsar binary known to have an accretion disk in 2000-2001. The observations were carried out with ground-based and space telescopes from near-IR to far-IR wavelengths. We detected the source in near-IR JH bands and Spitzer 3.6 and 4.5 {mu}m mid-IR channels. Combined with the previously reported optical spectrum of the source, the IR emission is found to arise from the companion star, with no excess emission detected in the wavelength range. Because our near-IR fluxes are nearly equal to those obtained by the 2MASS all-sky survey in 2000 February, the result indicates that the binary did not contain the accretion disk at the time, whose existence would have raised the near-IR fluxes to twice larger values. Our observations have thus established the short-term nature of the interacting phase seen in 2000-2001: the accretion disk existed for at most 2.5 yr. The binary was not detected by the WISE all-sky survey carried out in 2010 at its 12 and 22 {mu}m bands and our Herschel far-IR imaging at 70 and 160 {mu}m. Depending on the assumed properties of the dust, the resulting flux upper limits provide a constraint of <3 Multiplication-Sign 10{sup 22}-3 Multiplication-Sign 10{sup 25} g on the mass of the dust grains that possibly exist as the remnants of the previously seen accretion disk.

  19. Comparison of MELCOR modeling techniques and effects of vessel water injection on a low-pressure, short-term, station blackout at the Grand Gulf Nuclear Station

    SciTech Connect (OSTI)

    Carbajo, J.J.

    1995-06-01T23:59:59.000Z

    A fully qualified, best-estimate MELCOR deck has been prepared for the Grand Gulf Nuclear Station and has been run using MELCOR 1.8.3 (1.8 PN) for a low-pressure, short-term, station blackout severe accident. The same severe accident sequence has been run with the same MELCOR version for the same plant using the deck prepared during the NUREG-1150 study. A third run was also completed with the best-estimate deck but without the Lower Plenum Debris Bed (BH) Package to model the lower plenum. The results from the three runs have been compared, and substantial differences have been found. The timing of important events is shorter, and the calculated source terms are in most cases larger for the NUREG-1150 deck results. However, some of the source terms calculated by the NUREG-1150 deck are not conservative when compared to the best-estimate deck results. These results identified some deficiencies in the NUREG-1150 model of the Grand Gulf Nuclear Station. Injection recovery sequences have also been simulated by injecting water into the vessel after core relocation started. This marks the first use of the new BH Package of MELCOR to investigate the effects of water addition to a lower plenum debris bed. The calculated results indicate that vessel failure can be prevented by injecting water at a sufficiently early stage. No pressure spikes in the vessel were predicted during the water injection. The MELCOR code has proven to be a useful tool for severe accident management strategies.

  20. Monthly energy review

    SciTech Connect (OSTI)

    Not Available

    1988-03-01T23:59:59.000Z

    The U.S. energy market for the first quarter of 1988 is discussed. Production, energy consumption, imports, price adjustments, and forecasts for the rest of the year are given.

  1. Steam System Forecasting and Management

    E-Print Network [OSTI]

    Mongrue, D. M.; Wittke, D. O.

    1982-01-01T23:59:59.000Z

    '. This and the complex and integrated nature of the plants energy balance makes steam system forecasting and management essential for optimum use of the plant's energy. This paper discusses the method used by Union carbide to accomplish effective forecasting...

  2. ORSSAB Monthly Board Meeting

    Broader source: Energy.gov [DOE]

    The ORSSAB Monthly Board meeting is open to the public. This month, participants will be briefed on the East Tennessee Technology Park Zone 1 Soils Proposed Plan.

  3. ORSSAB monthly board meeting

    Broader source: Energy.gov [DOE]

    The ORSSAB monthly board meeting is open to the public. This month, participants will receive an update on the U-233 Project.

  4. National Women's History Month

    Broader source: Energy.gov [DOE]

    NATIONAL WOMEN’S HISTORY MONTH is an annual declared month that highlights the contributions of women to events in history and contemporary society.

  5. 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

  6. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16T23:59:59.000Z

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

  7. timber quality Modelling and forecasting

    E-Print Network [OSTI]

    Forest and timber quality in Europe Modelling and forecasting yield and quality in Europe Forest and timber quality in Europe Modelling and forecasting yield and quality in Europe M E F Y Q U E #12;Valuing and the UK ­ are working closely together to develop a model to help forecast timber growth, yield, quality

  8. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    electricity demand forecast means that the region's electricity needs would grow by 5,343 average megawattsDemand 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

  9. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    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

  10. Fuel Price Forecasts INTRODUCTION

    E-Print Network [OSTI]

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

  11. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2013-09-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

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

  14. Forecasting oilfield economic performance

    SciTech Connect (OSTI)

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

    1994-11-01T23:59:59.000Z

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

  15. Electricity Monthly Update

    Gasoline and Diesel Fuel Update (EIA)

    Declining coal stockpiles are a normal pattern most years from January to February as coal-fired generators meet winter electricity demand. The month-to-month stockpile change...

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

    SciTech Connect (OSTI)

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

    2011-08-15T23:59:59.000Z

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

  17. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01T23:59:59.000Z

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

  18. ELECTRICITY DEMAND FORECAST COMPARISON REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005.................................................................................................................................3 PACIFIC GAS & ELECTRIC PLANNING AREA ........................................................................................9 Commercial Sector

  19. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

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

  20. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    Energy Commission's final forecasts for 2012­2022 electricity consumption, peak, and natural gas demand Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand

  1. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    the California Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand

  2. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak, and natural Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility

  3. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

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

  4. Conservation The Northwest ForecastThe Northwest Forecast

    E-Print Network [OSTI]

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

  5. Natural gas monthly

    SciTech Connect (OSTI)

    NONE

    1998-01-01T23:59:59.000Z

    The Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the Natural Gas Monthly features articles designed to assist readers in using and interpreting natural gas information.

  6. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400. Hall Deputy Director Energy Efficiency and Demand Analysis Division Scott W. Matthews Acting Executive

  7. Mathematical Forecasting Donald I. Good

    E-Print Network [OSTI]

    Boyer, Robert Stephen

    Mathematical Forecasting Donald I. Good Technical Report 47 September 1989 Computational Logic Inc the physical behavior of computer programs can reduce these risks for software engineering in the same way that it does for aerospace and other fields of engineering. Present forecasting capabilities for computer

  8. Regional-seasonal weather forecasting

    SciTech Connect (OSTI)

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

    1980-08-01T23:59:59.000Z

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

  9. ORSSAB monthly meeting

    Broader source: Energy.gov [DOE]

    This month's ORSSAB board meeting will focus on the ETTP Zone 1 soils proposed plan. The meeting is open to the public.

  10. Native American Heritage Month

    Broader source: Energy.gov [DOE]

    This month, we celebrate the rich heritage and myriad contributions of American Indians and Alaska Natives, and we rededicate ourselves to supporting tribal sovereignty, tribal self-determination,...

  11. Electricity Monthly Update

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

    Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains...

  12. Electricity Monthly Update

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

    month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO...

  13. National Osteoporosis Prevention Month

    E-Print Network [OSTI]

    MAY National Osteoporosis Prevention Month JUNE National Dairy Month Texas AgriLife Extension - Bone Health Power Point # P4-1 Eat Smart for Bone Health # P4-2 Osteoporosis Disease Statistics # P4-3 Osteoporosis = Porous Bones # P4-4 Risk Factors # P4-5 Risk Factors (continued) # P4-6 Steps to Prevention # P4

  14. National Women's History Month

    Broader source: Energy.gov [DOE]

    During Women's History Month, we recall that the pioneering legacy of our grandmothers and great-grandmothers is revealed not only in our museums and history books, but also in the fierce...

  15. ORSSAB monthly board meeting

    Broader source: Energy.gov [DOE]

    The ORSSAB monthly board meeting is open to the public. The board will receive an update on the Community Reuse Organization of East Tennessee efforts at the East Tennessee Technology Park.

  16. Electricity Monthly Update

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

    New England and New York City. In the electricity markets, 12-month lows were set at all pricing points except Louisiana and Northwest. Even more unique is that these low prices...

  17. Disability Employment Awareness Month

    Broader source: Energy.gov [DOE]

    Utilizing the talents of all Americans is essential for our Nation to out-innovate, out-educate, and out-build the rest of the world.  During National Disability Employment Awareness Month, we...

  18. Electricity Monthly Update

    Gasoline and Diesel Fuel Update (EIA)

    while warm weather caused low demand levels in the West. The natural gas price for New York City (Transco Zone 6 NY) saw a significant increase in price from the previous month,...

  19. Black History Month

    Broader source: Energy.gov [DOE]

    During National African American History Month, we pay tribute to the contributions of past generations and reaffirm our commitment to keeping the American dream alive for the next generation.  In...

  20. BLACK HISTORY MONTH

    Broader source: Energy.gov [DOE]

    Black History Month is an annual celebration of achievements by black Americans and a time for recognizing the central role of African Americans in U.S. history. The event grew out of “Negro History Week,” created by historian Carter G. Woodson and other prominent African Americans. Other countries around the world, including Canada and the United Kingdom, also devote a month to celebrating black history.

  1. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

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

  2. Arnold Schwarzenegger INTEGRATED FORECAST AND

    E-Print Network [OSTI]

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

  3. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01T23:59:59.000Z

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

  5. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

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

  6. MSC Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12electron 9November 6, InaprilU . S . D e p3 Monthly5 Monthly

  7. MSC Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12electron 9November 6, InaprilU . S . D e p3 Monthly5 Monthly

  8. September 2015 Monthly Planner

    E-Print Network [OSTI]

    Acton, Scott

    Tuesday Wednesday Thursday Friday Saturday 1 All HR/Payroll Responsibilities On Monthly Pay Day 2 All HR/Payroll Responsibilities On 3 All HR/Payroll Responsibilities On 4 All HR/Payroll Responsibilities On 5 All HR/Payroll Responsibilities On 6 All HR/Payroll Responsibilities On BW PPE Sch Disabled @5:00pm - HRMS Specialist - Fac

  9. Monthly energy review

    SciTech Connect (OSTI)

    Not Available

    1989-08-01T23:59:59.000Z

    The Monthly Energy Review presents current data on production, consumption, stocks, imports, exports, and prices of the principal energy commodities in the United States. Also included are data on international production of crude oil, consumption of petroleum products, petroleum stocks, and production of electricity from nuclear-powered facilities.

  10. Monthly energy review

    SciTech Connect (OSTI)

    Not Available

    1992-04-01T23:59:59.000Z

    The Monthly Energy Review is prepared by the Energy Information Administration. Statistical data and information are provided on the topics of energy consumption, petroleum, natural gas, oil and gas resource development, coal, electricity, nuclear energy, energy prices, and international energy. (VC)

  11. Monthly Energy Review

    SciTech Connect (OSTI)

    NONE

    1996-05-28T23:59:59.000Z

    This publication presents an overview of the Energy information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. Two brief ``energy plugs`` (reviews of EIA publications) are included, as well.

  12. Monthly energy review

    SciTech Connect (OSTI)

    NONE

    1997-12-01T23:59:59.000Z

    This document presents an overview of the Energy Information Administration`s (EIA) recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors.

  13. Energy Action Month

    Broader source: Energy.gov [DOE]

    The Federal Energy Management Program (FEMP) supports Energy Action Month by offering materials that promote energy- and water-saving practices in Federal facilities. This year's outreach materials call on Federal employees to take action and empower leadership, innovation, and excellence to realize a secure energy future.

  14. November 2010 monthly report

    SciTech Connect (OSTI)

    Neff, Warren E [Los Alamos National Laboratory

    2010-12-07T23:59:59.000Z

    These viewgraphs are to be provided to NNSA to update the status of the B61 Life Extension Project work and activities. The viewgraphs cover such issues as budget, schedule, scope, and the like. They are part of the monthly reporting process.

  15. Electric power monthly

    SciTech Connect (OSTI)

    NONE

    1995-08-01T23:59:59.000Z

    The Energy Information Administration (EIA) prepares the Electric Power Monthly (EPM) for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. This publication provides monthly statistics for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source, consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead.

  16. Electric power monthly

    SciTech Connect (OSTI)

    Not Available

    1992-05-01T23:59:59.000Z

    The Electric Power Monthly is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the national, Census division, and State levels for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, cost of fuel, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fuel are also displayed for the North American Electric Reliability Council (NERC) regions. Additionally, statistics by company and plant are published in the EPM on capability of new plants, new generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fuel.

  17. Petroleum marketing monthly

    SciTech Connect (OSTI)

    NONE

    1996-07-01T23:59:59.000Z

    Petroleum Marketing Monthly (PPM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o. b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

  18. Petroleum marketing monthly

    SciTech Connect (OSTI)

    NONE

    1995-08-01T23:59:59.000Z

    The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

  19. Petroleum marketing monthly

    SciTech Connect (OSTI)

    NONE

    1996-02-01T23:59:59.000Z

    The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

  20. Forecasting consumer products using prediction markets

    E-Print Network [OSTI]

    Trepte, Kai

    2009-01-01T23:59:59.000Z

    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 ...

  1. 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 ...

  2. 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 ...

  3. QIP Short Term Course Application of Renewable

    E-Print Network [OSTI]

    Kumar, M. Jagadesh

    Delhi - 110016, India Course contents · Fundamentals of solar radiation · Solar cell material · CO2 mitigation and credit · PV modules/arrays · Batteries · Hybrid systems (wind, hydro etc.) · Life cycle cost

  4. APPLICATION FORM Short term course on

    E-Print Network [OSTI]

    Srivastava, Kumar Vaibhav

    Address: Prof. Tapan K. Sengupta High Performance Computing Lab Department of Aerospace Venue : IIT Kanpur, Kanpur Organized by: High Performance Computing Lab, Dept. of Aerospace Engineering

  5. Short-Term Energy Outlook May 2014

    Gasoline and Diesel Fuel Update (EIA)

    by the U.S. Supreme Court reversing a lower court opinion that vacated the Cross-State Air Pollution Rule (CSAPR). CSAPR will replace the Clean Air Interstate Rule (CAIR). The...

  6. Short-Term Energy Outlook January 2014

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard ErrorsSeptember 24, 2014 MEMORANDUM7,5:January

  7. Short-Term Energy Outlook April 2014

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

    -0.5 0.0 0.5 1.0 1.5 2013 2014 2015 OPEC countries North America Russia and Caspian Sea Latin America North Sea Other Non-OPEC World Crude Oil and Liquid Fuels Production Growth...

  8. August 2012 Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline prices4 OilU.S.5AreOil andMarket Module

  9. September 2012 Short-Term Energy Outlook

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillionNovember 20006 Table

  10. Short Term Energy Outlook ,November 2002

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillionNovemberData

  11. Short Term Energy Outlook ,October 2002

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillionNovemberDataOctober 2002 1

  12. Short Term Energy Outlook, December 2002

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillionNovemberDataOctober 2002

  13. Short Term Energy Outlook, February 2003

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13 1

  14. Short Term Energy Outlook, January 2003

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13 13 1

  15. Short Term Energy Outlook, March 2003

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002 13 13 13 1

  16. Short-Term Energy Outlook April 2014

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002‹00

  17. Short-Term Energy Outlook February 2014

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002‹004 1

  18. Short-Term Energy Outlook January 2014

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002‹004 1(STEO)

  19. Short-Term Energy Outlook July 2013

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002‹004

  20. Short-Term Energy Outlook June 2013

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002‹0041 June

  1. Short-Term Energy Outlook March 2014

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002‹0041

  2. Short-Term Energy Outlook May 2014

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober 2002‹0041(STEO)

  3. Short-Term Energy Outlook September 2013

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctober

  4. Short-Term Energy Outlook September 2014

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our Instagram Secretary Moniz9 SeptemberSetting theSheldonOctoberOutlook September

  5. Monthly energy review

    SciTech Connect (OSTI)

    Not Available

    1983-02-01T23:59:59.000Z

    This issue of the Monthly Energy Review contains preliminary energy summary data for 1982. A 4.3% decline in total energy consumption marked the third year in a row that domestic energy consumption fell. Decreases in the consumption of petroleum, natural gas, and coal contributed to the decline but were offset somewhat by increased use of hydroelectric and nuclear power. Because demand for energy was down, a lower level of imports was sufficient to meet US energy needs.

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

    E-Print Network [OSTI]

    Kemner, Ken

    forecasting methods and better integration of advanced wind power forecasts into system and plant operations and wind power plants) ­ Review and assess current practices Propose and test new and improved approachesWind Power Forecasting andWind Power Forecasting and Electricity Market Operations Audun Botterud

  7. 1995 shipment review & five year forecast

    SciTech Connect (OSTI)

    Fetherolf, D.J. Jr. [East Penn Manufacturing Co., Inc., Lyon Station, PA (United States)

    1996-01-01T23:59:59.000Z

    This report describes the 1995 battery shipment review and five year forecast for the battery market. Historical data is discussed.

  8. 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

  9. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 2: Electricity Demand by Utility Planning Area Energy Policy Report. The forecast includes three full scenarios: a high energy demand case, a low

  10. ASAP progress and expenditure report for the month of February 1--29, 1996

    SciTech Connect (OSTI)

    Twogood, R.E.; Brase, J.M.; Chambers, D.H.; Mantrom, D.M.; Miller, M.G.; Newman, M.J.; Robey, H.F.; Vigars, M.

    1996-03-20T23:59:59.000Z

    This is the ASAP progress and expenditure report for the month of February, 1996. The individual projects` report includes the sponsoring organization, the project identification, the principal investigator, long term objectives, short term objectives, accomplishments this reporting period, identification of issues or concerns, project budget estimate for the fiscal year, and monthly actual and year to date expenditures. The research project concerns a joint US/UK program to develop a high-priority radar system based on real aperture and synthetic aperature radar. Topics being researched include airborne RAR/SAR; radar data processor; ground-based SAR signal processing workstation; static airborne radar; radar field experiments; data analysis and detection theory; program management; modeling and analysis; UCSB wave tank; stratified wave tank; and experiments in a thermo-stratified tank at the Institute of Applied Physics, Russia.

  11. 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

  12. Calculator simplifies field production forecasting

    SciTech Connect (OSTI)

    Bixler, B.

    1982-05-01T23:59:59.000Z

    A method of forecasting future field production from an assumed average well production schedule and drilling schedule has been programmed for the HP-41C hand-held programmable computer. No longer must tedious row summations be made by hand for staggered well production schedules. Details of the program are provided.

  13. Petroleum marketing monthly

    SciTech Connect (OSTI)

    NONE

    1995-11-01T23:59:59.000Z

    The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data.

  14. Electricity Monthly Update

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,128 2,469DecadeOrigin State1,237ContactElectricity Monthly

  15. Project of the Month

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

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy China 2015of 2005UNS Electric,RM Exit Procedures.docTheproject-of-the-month Office of

  16. Monthly Biodiesel Production Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14 Jan-15LiquidBG 0 20 40Monthly Biodiesel

  17. Monthly Biodiesel Production Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14 Jan-15LiquidBG 0 20 40Monthly BiodieselU.S.

  18. Monthly Biodiesel Production Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14 Jan-15LiquidBG 0 20 40Monthly BiodieselU.S.U.S.

  19. Monthly Biodiesel Production Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14 Jan-15LiquidBG 0 20 40Monthly

  20. Monthly Biodiesel Production Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14 Jan-15LiquidBG 0 20 40MonthlyBiodiesel producers

  1. Monthly Biodiesel Production Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14 Jan-15LiquidBG 0 20 40MonthlyBiodiesel

  2. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJuly 28,September 25,1Monthly

  3. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJuly 28,September 25,1Monthly3

  4. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.1 Monthly

  5. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.1 Monthly0

  6. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.1 Monthly02

  7. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.1 Monthly025

  8. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.1 Monthly0256

  9. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.19 Monthly

  10. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.19 Monthly1

  11. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.19 Monthly13

  12. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.19 Monthly132

  13. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.197 Monthly

  14. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.197 Monthly4

  15. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.197 Monthly46

  16. Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010 F.19749 Monthly

  17. Monthly Reports 2014

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'.Solar Thermal SolarJulyOctober 2010Monthly Reports

  18. MSC Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12electron 9November 6, InaprilU . S . D e p3 Monthly

  19. MSC Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12electron 9November 6, InaprilU . S . D e p3 Monthly5

  20. MSC Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12electron 9November 6, InaprilU . S . D e p3 Monthly5

  1. MSC Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12electron 9November 6, InaprilU . S . D e p3 Monthly52

  2. MSC Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12electron 9November 6, InaprilU . S . D e p3 Monthly521

  3. MSC Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12electron 9November 6, InaprilU . S . D e p3 Monthly5218

  4. MSC Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12electron 9November 6, InaprilU . S . D e p3 Monthly52180

  5. MSC Monthly Performance Report

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12electron 9November 6, InaprilU . S . D e p3 Monthly521806

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

    SciTech Connect (OSTI)

    Martin Wilde, Principal Investigator

    2012-12-31T23:59:59.000Z

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

  7. An adaptive neural network approach to one-week ahead load forecasting

    SciTech Connect (OSTI)

    Peng, T.M. (Pacific Gas and Electric Co., San Francisco, CA (United States)); Hubele, N.F.; Karady, G.G. (Arizona State Univ., Tempe, AZ (United States))

    1993-08-01T23:59:59.000Z

    A new neural network approach is applied to one-week ahead load forecasting. This approach uses a linear adaptive neuron or adaptive linear combiner called Adaline.'' An energy spectrum is used to analyze the periodic components in a load sequence. The load sequence mainly consists of three components: base load component, and low and high frequency load components. Each load component has a unique frequency range. Load decomposition is made for the load sequence using digital filters with different passband frequencies. After load decomposition, each load component can be forecasted by an Adaline. Each Adaline has an input sequence, an output sequence, and a desired response-signal sequence. It also has a set of adjustable parameters called the weight vector. In load forecasting, the weight vector is designed to make the output sequence, the forecasted load, follow the actual load sequence; it also has a minimized Least Mean Square error. This approach is useful in forecasting unit scheduling commitments. Mean absolute percentage errors of less than 3.4 percent are derived from five months of utility data, thus demonstrating the high degree of accuracy that can be obtained without dependence on weather forecasts.

  8. Hybrid methodology for hourly global radiation forecasting in Mediterranean area

    E-Print Network [OSTI]

    Voyant, Cyril; Paoli, Christophe; Nivet, Marie Laure

    2012-01-01T23:59:59.000Z

    The renewable energies prediction and particularly global radiation forecasting is a challenge studied by a growing number of research teams. This paper proposes an original technique to model the insolation time series based on combining Artificial Neural Network (ANN) and Auto-Regressive and Moving Average (ARMA) model. While ANN by its non-linear nature is effective to predict cloudy days, ARMA techniques are more dedicated to sunny days without cloud occurrences. Thus, three hybrids models are suggested: the first proposes simply to use ARMA for 6 months in spring and summer and to use an optimized ANN for the other part of the year; the second model is equivalent to the first but with a seasonal learning; the last model depends on the error occurred the previous hour. These models were used to forecast the hourly global radiation for five places in Mediterranean area. The forecasting performance was compared among several models: the 3 above mentioned models, the best ANN and ARMA for each location. In t...

  9. 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible for Renewable Energy: Grid IntegrationReport AvailableForecasting NREL researchers use

  10. Monthly energy review, August 1986

    SciTech Connect (OSTI)

    Not Available

    1986-11-24T23:59:59.000Z

    Statistics are cumulated monthly and annually for production, consumption, and imports for petroleum, natural gas, coal and electric power.

  11. Petroleum Supply Monthly

    SciTech Connect (OSTI)

    NONE

    1996-02-01T23:59:59.000Z

    The Petroleum Supply Monthly (PSM) is one of a family of four publications produced by the Petroleum Supply Division within the Energy Information Administration (EIA) reflecting different levels of data timeliness and completeness. The other publications are the Weekly Petroleum Status Report (WPSR), the Winter Fuels Report, and the Petroleum Supply Annual (PSA). Data presented in the PSM describe the supply and disposition of petroleum products in the United States and major U.S. geographic regions. The data series describe production, imports and exports, inter-Petroleum Administration for Defense (PAD) District movements, and inventories by the primary suppliers of petroleum products in the United States (50 States and the District of Columbia). The reporting universe includes those petroleum sectors in primary supply. Included are: petroleum refiners, motor gasoline blenders, operators of natural gas processing plants and fractionators, inter-PAD transporters, importers, and major inventory holders of petroleum products and crude oil. When aggregated, the data reported by these sectors approximately represent the consumption of petroleum products in the United States. Data presented in the PSM are divided into two sections: Summary Statistics and Detailed Statistics.

  12. Petroleum supply monthly

    SciTech Connect (OSTI)

    NONE

    1995-10-01T23:59:59.000Z

    The Petroleum Supply Monthly (PSM) is one of a family of four publications produced by the Petroleum Supply Division within the Energy Information Administration (EIA) reflecting different levels of data timeliness and completeness. The other publications are the Weekly Petroleum Status Report (WPSR), the Winter Fuels Report, and the Petroleum Supply Annual (PSA). Data presented in the PSM describe the supply and disposition of petroleum products in the United States and major US geographic regions. The data series describe production, imports and exports, inter-Petroleum Administration for Defense (PAD) District movements, and inventories by the primary suppliers of petroleum products in the United States (50 States and the District of Columbia). The reporting universe includes those petroleum sectors in primary supply. Included are: petroleum refiners, motor gasoline blends, operators of natural gas processing plants and fractionators, inter-PAD transporters, importers, and major inventory holders of petroleum products and crude oil. When aggregated, the data reported by these sectors approximately represent the consumption of petroleum products in the United States.

  13. Monthly energy review, August 1997

    SciTech Connect (OSTI)

    NONE

    1997-08-01T23:59:59.000Z

    The Monthly Energy Review for the month of August 1997, presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors.

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

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

    collects data on a variety of physical processes that impact the wind forecasts used by wind farms, system operators and other industry professionals. By having access to...

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

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

    collects data on a variety of physical processes that impact the wind forecasts used by wind farms, system operators and other industry professionals. By having access to...

  16. Geothermal wells: a forecast of drilling activity

    SciTech Connect (OSTI)

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

    1981-07-01T23:59:59.000Z

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

  17. Online Forecast Combination for Dependent Heterogeneous Data

    E-Print Network [OSTI]

    Sancetta, Alessio

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

  18. The Value of Wind Power Forecasting

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

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

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

    E-Print Network [OSTI]

    Kamat, Vineet R.

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

  20. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

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

  1. 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

  2. 1992 five year battery forecast

    SciTech Connect (OSTI)

    Amistadi, D.

    1992-12-01T23:59:59.000Z

    Five-year trends for automotive and industrial batteries are projected. Topic covered include: SLI shipments; lead consumption; automotive batteries (5-year annual growth rates); industrial batteries (standby power and motive power); estimated average battery life by area/country for 1989; US motor vehicle registrations; replacement battery shipments; potential lead consumption in electric vehicles; BCI recycling rates for lead-acid batteries; US average car/light truck battery life; channels of distribution; replacement battery inventory end July; 2nd US battery shipment forecast.

  3. 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluating A PotentialJumpGermanFife Energy Park atFisiaFlorida:Forecast Energy Jump to:

  4. Monthly energy review, January 1998

    SciTech Connect (OSTI)

    NONE

    1998-01-01T23:59:59.000Z

    This report presents an overview of recent monthly energy statistics. Major activities covered include production, consumption, trade, stocks, and prices for fossil fuels, electricity, and nuclear energy.

  5. Monthly energy review, December 1992

    SciTech Connect (OSTI)

    Not Available

    1992-12-22T23:59:59.000Z

    The Monthly Energy Review contains summary data on energy consumption, petroleum, natural gas, oil and gas resource development, coal, electricity, nuclear energy, energy prices, and international energy.

  6. Monthly energy review, January 1993

    SciTech Connect (OSTI)

    Not Available

    1993-01-26T23:59:59.000Z

    The Monthly Energy Review contains summary data on energy consumption, petroleum, natural gas, oil and gas resource development, coal, electricity, nuclear energy, energy prices, and international energy.

  7. Monthly energy review. May 1998

    SciTech Connect (OSTI)

    NONE

    1998-05-01T23:59:59.000Z

    This report presents recent energy monthly statistics on the production, consumption, trade, stocks, and prices of petroleum, natural gas, coal, electricity, and nuclear energy.

  8. Natural Gas Monthly, October 1993

    SciTech Connect (OSTI)

    Not Available

    1993-11-10T23:59:59.000Z

    The (NGM) Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. This month`s feature articles are: US Production of Natural Gas from Tight Reservoirs: and Expanding Rule of Underground Storage.

  9. Natural gas monthly, July 1997

    SciTech Connect (OSTI)

    NONE

    1997-07-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The feature article this month is entitled ``Intricate puzzle of oil and gas reserves growth.`` A special report is included on revisions to monthly natural gas data. 6 figs., 24 tabs.

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

    E-Print Network [OSTI]

    Heinemann, Detlev

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

  11. Short-Term Exchange Financial Statement Non-degree, Short-Term, Special Students

    E-Print Network [OSTI]

    for tuition with the estimated cost of your program. Do the same for each category A-G even if you to discuss Visa alternatives. STUDENT INFORMATION LAST/FAMILY NAME, capitalized First/Given Name Middle Name information regarding health insurance visit the ISSS website at http://www.vanderbilt.edu/isss/resources

  12. Alternative methods for forecasting GDP Dominique Gugan

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    analysis. Better forecast performance for macroeconomic variables will lead to Paris School of Economics the speed of computers that can develop search algorithms from appropriate selection criteria, Devroye. 1 Introduction Forecasting macroeconomic variables such as GDP and inflation play an important role

  13. A NEW APPROACH FOR EVALUATING ECONOMIC FORECASTS

    E-Print Network [OSTI]

    Vertes, Akos

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

  14. 2013 Midyear Economic Forecast Sponsorship Opportunity

    E-Print Network [OSTI]

    de Lijser, Peter

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

  15. Dynamic Algorithm for Space Weather Forecasting System

    E-Print Network [OSTI]

    Fischer, Luke D.

    2011-08-08T23:59:59.000Z

    /effective forecasts, and we have performed preliminary benchmarks on this algorithm. The preliminary benchmarks yield surprisingly effective results thus far?forecasts have been made 8-16 hours into the future with significant magnitude and trend accuracy, which is a...

  16. 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

  17. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand, EndUser Natural Gas Demand, and Energy Efficiency SEPTEMBER 2013 CEC2002013004SDV1REV CALIFORNIA The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 1: Statewide Electricity Demand and Methods

  18. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1994-02-01T23:59:59.000Z

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

  19. Monthly energy review, May 1999

    SciTech Connect (OSTI)

    NONE

    1999-05-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 61 tabs.

  20. Monthly energy review: April 1996

    SciTech Connect (OSTI)

    NONE

    1996-04-01T23:59:59.000Z

    This monthly report presents an overview of energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. A section is also included on international energy. The feature paper which is included each month is entitled ``Energy equipment choices: Fuel costs and other determinants.`` 37 figs., 59 tabs.

  1. Monthly energy review, November 1996

    SciTech Connect (OSTI)

    NONE

    1996-11-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 75 tabs.

  2. Monthly energy review, November 1997

    SciTech Connect (OSTI)

    NONE

    1997-11-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 91 tabs.

  3. Monthly energy review, June 1998

    SciTech Connect (OSTI)

    NONE

    1998-06-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 36 figs., 61 tabs.

  4. Monthly energy review, July 1998

    SciTech Connect (OSTI)

    NONE

    1998-07-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs. 73 tabs.

  5. Monthly energy review, November 1998

    SciTech Connect (OSTI)

    NONE

    1998-11-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 61 tabs.

  6. Monthly Energy Review, February 1996

    SciTech Connect (OSTI)

    NONE

    1996-02-26T23:59:59.000Z

    This monthly publication presents an overview of EIA`s recent monthly energy statistics, covering the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. Two brief descriptions (`energy plugs`) on two EIA publications are presented at the start.

  7. Monthly energy review, January 1999

    SciTech Connect (OSTI)

    NONE

    1999-01-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 61 tabs.

  8. Monthly energy review, March 1999

    SciTech Connect (OSTI)

    NONE

    1999-03-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 74 tabs.

  9. Monthly energy review, February 1999

    SciTech Connect (OSTI)

    NONE

    1999-02-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 73 tabs.

  10. Natural gas monthly, January 1999

    SciTech Connect (OSTI)

    NONE

    1999-02-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. 6 figs., 28 tabs.

  11. Natural gas monthly, November 1998

    SciTech Connect (OSTI)

    NONE

    1998-11-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. 6 figs., 27 tabs.

  12. Natural gas monthly, February 1999

    SciTech Connect (OSTI)

    NONE

    1999-02-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. 6 figs., 28 tabs.

  13. Monthly energy review, October 1998

    SciTech Connect (OSTI)

    NONE

    1998-10-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 61 tabs.

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

    SciTech Connect (OSTI)

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

    2005-06-30T23:59:59.000Z

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

  15. SUMMARY OF 2007 ATLANTIC TROPICAL CYCLONE ACTIVITY AND VERIFICATION OF AUTHOR'S SEASONAL AND MONTHLY FORECASTS

    E-Print Network [OSTI]

    Gray, William

    10 12.25 8 5.75 Accumulated Cyclone Energy (ACE) (96.2) 130 170 170 150 148 100 68 Net Tropical't press us too hard on future events!!" 3 #12;DEFINITIONS Accumulated Cyclone Energy ­ (ACE) A measureSUMMARY OF 2007 ATLANTIC TROPICAL CYCLONE ACTIVITY AND VERIFICATION OF AUTHOR'S SEASONAL

  16. NOAA Air Resources Laboratory Monthly Activity Report

    E-Print Network [OSTI]

    with GSD's Homeland Security Project. The Earth System Research Laboratory's Global Systems Division (GSD's Homeland Security Project 2. Wildfire Smoke Forecasts 3. HYSPLIT Modifications for NOAA's Homeland Security Change Science Program (CCSP) Synthesis and Assessment Product (SAP) 3.2 10. Air Quality Forecast Model

  17. NOAA ARL Monthly Activity Report September 2006

    E-Print Network [OSTI]

    on the Relationships between Air Quality and Human Health 18. TEXAQS-II: Smart Balloon 19. Real-time Tracer Analysis forecast models currently reach grid sizes as small as 4 km. Such models forecast the "skimming" flow over the city, above the influence of individual structures. UrbaNet sites and the simpler but much more

  18. Natural gas monthly, June 1996

    SciTech Connect (OSTI)

    NONE

    1996-06-24T23:59:59.000Z

    The natural gas monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The feature article for this month is Natural Gas Industry Restructuring and EIA Data Collection.

  19. Natural gas monthly, January 1994

    SciTech Connect (OSTI)

    Not Available

    1994-02-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The featured article for this month is on US coalbed methane production.

  20. Natural gas monthly, May 1997

    SciTech Connect (OSTI)

    NONE

    1997-05-01T23:59:59.000Z

    The Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The feature article this month is ``Restructuring energy industries: Lessons from natural gas.`` 6 figs., 26 tabs.

  1. Natural gas monthly, December 1997

    SciTech Connect (OSTI)

    NONE

    1997-12-01T23:59:59.000Z

    The Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The article this month is entitled ``Recent Trends in Natural Gas Spot Prices.`` 6 figs., 27 tabs.

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

    SciTech Connect (OSTI)

    Chiswell, S

    2009-01-11T23:59:59.000Z

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

  3. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST

    E-Print Network [OSTI]

    procurement process at the California Public Utilities Commission. This forecast was produced with the Energy Commission demand forecast models. Both the staff draft energy consumption and peak forecasts are slightly and commercial sectors. Keywords Electricity demand, electricity consumption, demand forecast, weather

  4. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    and water pumping sectors. Mark Ciminelli forecasted energy for transportation, communication and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data at the California Public Utilities Commission. This forecast was produced with the Energy Commission demand forecast

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

    SciTech Connect (OSTI)

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

    2011-10-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

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

  7. 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

    Page 1 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 take a few moments to answer this short survey

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

    E-Print Network [OSTI]

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

  9. 1993 Solid Waste Reference Forecast Summary

    SciTech Connect (OSTI)

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

    1993-08-01T23:59:59.000Z

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

  10. Monthly energy review, August 1996

    SciTech Connect (OSTI)

    NONE

    1996-08-01T23:59:59.000Z

    This report presents an overview of recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, coal, natural gas, electricity, and nuclear energy.

  11. Monthly energy review, July 1997

    SciTech Connect (OSTI)

    NONE

    1997-07-01T23:59:59.000Z

    This document presents an overview of recent monthly energy statistics. Activities covered include: U.S. production, consumption, trade, stock, and prices for petroleum, coal, natural gas, electricity, and nuclear energy.

  12. Monthly Energy Review, July 1992

    SciTech Connect (OSTI)

    none,

    1992-07-27T23:59:59.000Z

    The Monthly Energy Review is prepared by the Energy Information Administration. Topics discussed include: Energy Overview, Energy Consumption, Petroleum, Natural Gas, Oil and Gas Resource Development, Coal, Electricity, Nuclear Energy, Energy Prices, International Energy. (VC)

  13. Monthly energy review, August 1993

    SciTech Connect (OSTI)

    Not Available

    1993-08-26T23:59:59.000Z

    This publication presents information for the month of August, 1993 on the following: Energy overview; energy consumption; petroleum; natural gas; oil and gas resource development; coal; electricity; nuclear energy; energy prices, and international energy.

  14. Monthly energy review, March 1991

    SciTech Connect (OSTI)

    Not Available

    1991-03-28T23:59:59.000Z

    This document is a monthly report by the Energy Information Administration on the production, consumption, stocks, imports, and prices of the principal energy commodities in the United States. International energy data is also presented. 46 figs., 58 tabs.

  15. Monthly energy review, January 1992

    SciTech Connect (OSTI)

    Not Available

    1992-01-28T23:59:59.000Z

    Monthly Energy Review contains statistical information on energy sources including petroleum, natural gas, coal and nuclear energy. Information on energy consumption, oil and gas resource development, electricity, energy prices and international energy is provided. (VC)

  16. Monthly energy review, April 1999

    SciTech Connect (OSTI)

    NONE

    1999-04-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public.

  17. Monthly Energy Review, August 1988

    SciTech Connect (OSTI)

    Not Available

    1988-11-28T23:59:59.000Z

    The Monthly Energy Review presents current data on production, consumption, stocks, imports, exports, and prices of the principal energy commodities in the United States. Also included are data on international production of crude oil, consumption of petroleum products, petroleum stocks, and production of electricity from nuclear-powered facilities. The Monthly Energy Review is intended to provide timely energy information to members of Congress, to federal and state agencies, and to the general public.

  18. Monthly energy review, January 1989

    SciTech Connect (OSTI)

    Not Available

    1989-04-25T23:59:59.000Z

    The Monthly Energy Review presents current data on production, consumption, stocks, imports, exports, and prices of the principal energy commodities in the United States. Also included are data on international production of crude oil, consumption of petroleum products, petroleum stocks, and production of electricity from nuclear-powered facilities. The Monthly Energy Review is intended to provide timely energy information to Members of Congress, to Federal and State agencies, and to the general public.

  19. Natural gas monthly, May 1999

    SciTech Connect (OSTI)

    NONE

    1999-05-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 27 tabs.

  20. Natural gas monthly, August 1994

    SciTech Connect (OSTI)

    Not Available

    1994-08-24T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  1. Natural gas monthly, October 1998

    SciTech Connect (OSTI)

    NONE

    1998-10-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 27 tabs.

  2. Natural gas monthly, June 1999

    SciTech Connect (OSTI)

    NONE

    1999-06-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 25 tabs.

  3. Natural gas monthly: December 1993

    SciTech Connect (OSTI)

    Not Available

    1993-12-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. Articles are included which are designed to assist readers in using and interpreting natural gas information.

  4. Natural gas monthly, April 1994

    SciTech Connect (OSTI)

    Not Available

    1994-04-26T23:59:59.000Z

    The National Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  5. Natural gas monthly, June 1993

    SciTech Connect (OSTI)

    Not Available

    1993-06-22T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  6. Natural gas monthly, July 1993

    SciTech Connect (OSTI)

    Not Available

    1993-07-27T23:59:59.000Z

    The Natural Gas Monthly NGM highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  7. Natural gas monthly, November 1993

    SciTech Connect (OSTI)

    Not Available

    1993-11-29T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground state data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  8. Natural gas monthly, July 1998

    SciTech Connect (OSTI)

    NONE

    1998-07-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 25 tabs.

  9. Natural gas monthly, April 1995

    SciTech Connect (OSTI)

    NONE

    1995-04-27T23:59:59.000Z

    The Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 31 tabs.

  10. Monthly energy review, April 1998

    SciTech Connect (OSTI)

    NONE

    1998-04-01T23:59:59.000Z

    This report presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy data. A brief summary of the monthly and historical comparison data is provided in Section 1 of the report. A highlight section of the report provides an assessment of summer 1997 motor gasoline price increases.

  11. Natural Gas Monthly, March 1996

    SciTech Connect (OSTI)

    NONE

    1996-03-25T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  12. Natural gas monthly, June 1998

    SciTech Connect (OSTI)

    NONE

    1998-06-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 27 tabs.

  13. Monthly energy review, August 1998

    SciTech Connect (OSTI)

    NONE

    1998-08-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. 37 figs., 73 tabs.

  14. Natural gas monthly, September 1998

    SciTech Connect (OSTI)

    NONE

    1998-09-01T23:59:59.000Z

    The National Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 27 tabs.

  15. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    supervised data preparation. Steven Mac and Keith O'Brien prepared the historical energy consumption data. Nahid Movassagh forecasted consumption for the agriculture and water pumping sectors. Cynthia Rogers generation, conservation, energy efficiency, climate zone, investorowned, public, utilities, additional

  16. Wind Speed Forecasting for Power System Operation 

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

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

  17. 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

  18. Wind Speed Forecasting for Power System Operation

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

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

  19. 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 ...

  20. 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....

  1. Essays in International Macroeconomics and Forecasting

    E-Print Network [OSTI]

    Bejarano Rojas, Jesus Antonio

    2012-10-19T23:59:59.000Z

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

  2. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01T23:59:59.000Z

    gas price forecasts with contemporaneous natural gas pricesreference-case natural gas price forecast, and that have notof AEO 2009 Natural Gas Price Forecast to NYMEX Futures

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01T23:59:59.000Z

    Gas Price Forecast W ith natural gas prices significantlyof AEO 2006 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEO

  5. Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    to accurately forecast natural gas prices. Many policyseek alternative methods to forecast natural gas prices. Thethe accuracy of forecasts for natural gas prices as reported

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    gas price forecasts with contemporaneous natural gas pricesreference-case natural gas price forecast, and that have notof AEO 2008 Natural Gas Price Forecast to NYMEX Futures

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    the base-case natural gas price forecast, but to alsogas price forecasts with contemporaneous natural gas pricesof AEO 2010 Natural Gas Price Forecast to NYMEX Futures

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01T23:59:59.000Z

    Natural Gas Price Forecast Although natural gas prices areof AEO 2007 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEO

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

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred [ORNL

    2008-01-01T23:59:59.000Z

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

  10. Electric power monthly, April 1994

    SciTech Connect (OSTI)

    Not Available

    1994-04-01T23:59:59.000Z

    The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. This publication provides monthly statistics at the U.S., Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. This April 1994 issue contains 1993 year-end data and data through January 1994.

  11. Electric power monthly, August 1993

    SciTech Connect (OSTI)

    Not Available

    1993-08-13T23:59:59.000Z

    The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EPM is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions.

  12. Electric power monthly, September 1993

    SciTech Connect (OSTI)

    Not Available

    1993-09-17T23:59:59.000Z

    The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. The EPM is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions.

  13. Natural gas monthly, April 1998

    SciTech Connect (OSTI)

    NONE

    1998-04-01T23:59:59.000Z

    This issue of the Natural Gas Monthly presents the most recent estimates of natural gas data from the Energy Information Administration (EIA). Estimates extend through April 1998 for many data series. The report highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, feature articles are presented designed to assist readers in using and interpreting natural gas information. This issue contains the special report, ``Natural Gas 1997: A Preliminary Summary.`` This report provides information on natural gas supply and disposition for the year 1997, based on monthly data through December from EIA surveys. 6 figs., 28 tabs.

  14. Electric power monthly, May 1994

    SciTech Connect (OSTI)

    Not Available

    1994-05-01T23:59:59.000Z

    The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. This publication provides monthly statistics for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Statistics by company and plant are published on the capability of new generating units, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fossil fuels.

  15. Electric power monthly, May 1993

    SciTech Connect (OSTI)

    Not Available

    1993-05-25T23:59:59.000Z

    The Electric Power Monthly (EPM) is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions.

  16. Electric power monthly, July 1993

    SciTech Connect (OSTI)

    Not Available

    1993-07-29T23:59:59.000Z

    The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.

  17. Electric power monthly, April 1993

    SciTech Connect (OSTI)

    Not Available

    1993-05-07T23:59:59.000Z

    The Electric Power Monthly is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions.

  18. Electric power monthly, June 1994

    SciTech Connect (OSTI)

    Not Available

    1994-06-01T23:59:59.000Z

    The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.

  19. Natural gas monthly, October 1997

    SciTech Connect (OSTI)

    NONE

    1997-10-01T23:59:59.000Z

    The Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The feature article in this issue is a special report, ``Comparison of Natural Gas Storage Estimates from the EIA and AGA.`` 6 figs., 26 tabs.

  20. Monthly energy review, June 1999

    SciTech Connect (OSTI)

    NONE

    1999-06-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the MER and in other EIA publications. 37 figs., 61 tabs.

  1. Monthly energy review, July 1999

    SciTech Connect (OSTI)

    NONE

    1999-07-01T23:59:59.000Z

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the MER and in other EIA publications. 37 figs., 75 tabs.

  2. Natural gas monthly, October 1996

    SciTech Connect (OSTI)

    NONE

    1996-10-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) is prepared in the Data Operations Branch of the Reserves and Natural Gas Division, Office of Oil and Gas, Energy Information Administration (EIA), U.S. Department of Energy (DOE). The NGM highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  3. Natural gas monthly, April 1999

    SciTech Connect (OSTI)

    NONE

    1999-05-06T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. There are two feature articles in this issue: Natural gas 1998: Issues and trends, Executive summary; and Special report: Natural gas 1998: A preliminary summary. 6 figs., 28 tabs.

  4. Natural gas monthly, April 1997

    SciTech Connect (OSTI)

    NONE

    1997-04-01T23:59:59.000Z

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are present3ed each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The feature article is entitled ``Natural gas pipeline and system expansions.`` 6 figs., 27 tabs.

  5. Natural gas monthly, March 1994

    SciTech Connect (OSTI)

    Not Available

    1994-03-22T23:59:59.000Z

    The Natural Gas Monthly (NGM) is prepared in the Data Operations Branch of the Reserves and Natural Gas Division, Office of Oil and Gas, Energy Information Administration (EIA), US Department of energy (DOE). The NGM highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  6. Natural gas monthly, August 1993

    SciTech Connect (OSTI)

    Not Available

    1993-08-25T23:59:59.000Z

    The Natural Gas Monthly (NGM) is prepared in the Data Operations Branch of the Reserves and Natural Gas Division, Office of Oil and Gas, Energy Information Administration (EIA), US Department of Energy (DOE). The NGM highhghts activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  7. Natural gas monthly, September 1993

    SciTech Connect (OSTI)

    Not Available

    1993-09-27T23:59:59.000Z

    The Natural Gas Monthly (NGM) is prepared in the Data Operations Branch of the Reserves and Natural Gas Division, Office of Oil and Gas, Energy Information Administration (EIA), US Department of Energy (DOE). The NGM highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  8. Electric power monthly, August 1994

    SciTech Connect (OSTI)

    Not Available

    1994-08-24T23:59:59.000Z

    The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.

  9. Petroleum marketing monthly, May 1994

    SciTech Connect (OSTI)

    Not Available

    1994-05-26T23:59:59.000Z

    The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

  10. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

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

    1994-09-01T23:59:59.000Z

    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.

  11. Monthly energy review, June 1993

    SciTech Connect (OSTI)

    Not Available

    1993-06-25T23:59:59.000Z

    The Monthly Energy Review provides an overview of the production, distribution, and consumption of energy derived from petroleum, natural gas, coal, electricity, and nuclear energy. It also discusses oil and gas resource development, energy prices, and issues relevant to international energy markets.

  12. Monthly energy review, February 1994

    SciTech Connect (OSTI)

    Not Available

    1994-02-24T23:59:59.000Z

    The Monthly Energy Review gives information on production, distribution, consumption, prices, imports, and exports for the following US energy sources: petroleum; petroleum products; natural gas; coal; electricity; and nuclear energy. The section on international energy contains data for world crude oil production and consumption, petroleum stocks in OECD countries, and nuclear electricity gross generation.

  13. Monthly energy review, April 1997

    SciTech Connect (OSTI)

    NONE

    1997-04-01T23:59:59.000Z

    This report presents an overview of monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. International energy and thermal metric conversion factors are included.

  14. Monthly energy review, January 1996

    SciTech Connect (OSTI)

    NONE

    1996-01-01T23:59:59.000Z

    This document presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum,natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal metric conversion factors.

  15. Monthly energy review, November 1995

    SciTech Connect (OSTI)

    NONE

    1995-11-01T23:59:59.000Z

    This document presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. International energy and thermal and metric conversion factors are included.

  16. Monthly energy review, October 1993

    SciTech Connect (OSTI)

    Not Available

    1993-10-26T23:59:59.000Z

    The Monthly Energy Review gives information on production, distribution, and consumption for various energy sources, e.g. petroleum, natural gas, oil, coal, electricity, and nuclear energy. Some data is also included on international energy sources and supplies, the import of petroleum products into the US and pricing and reserves data (as applicable) for the various sources of energy listed above.

  17. Monthly energy review, April 1994

    SciTech Connect (OSTI)

    Not Available

    1994-04-01T23:59:59.000Z

    The Monthly Energy Review contains statistical data on the following: energy consumption, petroleum, natural gas, oil and gas resource development, coal, electricity, nuclear energy, energy prices, and international energy. In addition, an energy overview is provided, and, for the April issue, Energy use and carbon emissions; Some international comparisons.

  18. Monthly energy review, May 1993

    SciTech Connect (OSTI)

    Not Available

    1993-05-01T23:59:59.000Z

    The Monthly Energy Review provides an overview of the production, distribution, and consumption of energy derived from petroleum natural gas, coal, electricity, and nuclear energy. It also discusses oil and gas resource development, energy prices, and issues relevant to international energy markets.

  19. Monthly energy review, March 1994

    SciTech Connect (OSTI)

    Not Available

    1994-03-29T23:59:59.000Z

    The Monthly Energy Review provides information on production, distribution, consumption, prices, imports, and exports for the following US energy sources: petroleum; petroleum products; natural gas; coal; electricity; and nuclear energy. The section on international energy contains data for world crude oil production and consumption, petroleum stocks in OECD countries, and nuclear electricity gross generation.

  20. Monthly energy review, November 1993

    SciTech Connect (OSTI)

    Not Available

    1993-11-24T23:59:59.000Z

    The Monthly Energy Review gives information on production, distribution, and consumption for various energy sources, e.g. petroleum, natural gas, oil, coal, electricity, and nuclear energy. Some data is also included on international energy sources and supplies, the import of petroleum products into the US and pricing and reserves data (as applicable) for the various sources of energy listed above.