Sample records for forecasting future values

  1. 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.

  2. Econometric model and futures markets commodity price forecasting

    E-Print Network [OSTI]

    Just, Richard E.; Rausser, Gordon C.

    1979-01-01T23:59:59.000Z

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

  3. Using Customers' Reported Forecasts to Predict Future Sales

    E-Print Network [OSTI]

    Gordon, Geoffrey J.

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

  4. 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

  5. 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

  6. 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

  7. 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...

  8. 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 ...

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

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

  10. 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...

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

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19T23:59:59.000Z

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

  15. Application of neural networking in live cattle futures market: an approach to price-forecasting

    E-Print Network [OSTI]

    Chou, Chien-Ju

    1993-01-01T23:59:59.000Z

    APPLICATION OF NEURAL NETWORKING IN LIVE CATTLE FUTURES MARKET: AN APPROACH TO PRICE-FORECASTING A Thesis by CHIEN-JU CHOU Submitted to the Office of Graduate Studies of Texas ARM University in partial fulfilhnent of the requirements... for the degree of MASTER OF SCIENCE August 1993 Major Subject: Animal Science APPLICATION OF NEURAL NETWORKING IN LIVE CATTLE FUTURES MARKET: AN APPROACH TO PRICE-FORECASTING A Thesis by CHIBN-JU CHOU Approved as to style and content by: John P. Walter...

  16. Abstract--Forecasting of future electricity demand is very important for decision making in power system operation and

    E-Print Network [OSTI]

    Ducatelle, Frederick

    Abstract--Forecasting of future electricity demand is very important for decision making in power industry, accurate forecasting of future electricity demand has become an important research area for secure operation, management of modern power systems and electricity production in the power generation

  17. Term Structure of Commodities Futures. Forecasting and Pricing. Marcos Escobar, Nicols Hernndez, Luis Seco

    E-Print Network [OSTI]

    Seco, Luis A.

    1 Term Structure of Commodities Futures. Forecasting and Pricing. Marcos Escobar, Nicolás Hernández that often exhibit sudden changes from backwardation into contango (such as energy, agricultural products generation purposes. It also provides the "risk neutral" processes needed for derivatives pricing, answering

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

    SciTech Connect (OSTI)

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04T23:59:59.000Z

    On December 14, 2009, the reference-case projections from Annual Energy Outlook 2010 were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in itigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings.

  19. 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

  20. 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

  1. 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

  2. Reconstruction of the Past and Forecast of the Future European and British Ice Sheets and Associated Sea–Level Change 

    E-Print Network [OSTI]

    Hagdorn, Magnus K M

    The aim of this project is to improve our understanding of the past European and British ice sheets as a basis for forecasting their future. The behaviour of these ice sheets is investigated by simulating them using a ...

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01T23:59:59.000Z

    Gas Price Forecast With natural gas prices significantlyto the EIA’s natural gas price forecasts in AEO 2004 and AEOon the AEO 2005 natural gas price forecasts will likely once

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

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

  6. Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Forecasting the conditional volatility of oil spot and futures prices with structural breaks of oil spot and futures prices using three GARCH-type models, i.e., linear GARCH, GARCH with structural that oil price fluctuations influence economic activity and financial sector (e.g., Jones and Kaul, 1996

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

    E-Print Network [OSTI]

    Katz, Richard

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

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

    E-Print Network [OSTI]

    Fievet, Lucas; Cauwels, Peter; Sornette, Didier

    2014-01-01T23:59:59.000Z

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

  9. 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.

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01T23:59:59.000Z

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

  13. 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.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28T23:59:59.000Z

    On December 17, 2008, the reference-case projections from Annual Energy Outlook 2009 (AEO 2009) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof), differences in capital costs and O&M expenses, or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired or nuclear generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers; and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal, uranium, and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

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

    SciTech Connect (OSTI)

    Bolinger, Mark A; Bolinger, Mark; Wiser, Ryan

    2008-01-07T23:59:59.000Z

    On December 12, 2007, the reference-case projections from Annual Energy Outlook 2008 (AEO 2008) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof) or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers (though its appeal has diminished somewhat as prices have increased); and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

  16. 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

    the Energy Information Administration’s (EIA) web site. Wein the past, compared the EIA’s reference case long-termgas price forecasts from the EIA. As such, we have concluded

  17. Forecasting the Standard & Poor's 500 stock index futures price: interest rates, dividend yields, and cointegration

    E-Print Network [OSTI]

    Fritsch, Roger Erwin

    1997-01-01T23:59:59.000Z

    forward price series is constructed using interest rate and dividend yield data. Out-of-sample forecasts from error correction models are compared to those from vector autoregressions (VAR) fit to levels and VARs fit to first differences. This comparison...

  18. Developing Louisiana's Forest Products Industry: Adding Value for the Future

    E-Print Network [OSTI]

    of a manufacturingThe increased value at each stage of a manufacturing assembly processassembly process Those and necessaryimportant and necessary Addition of net economic valueAddition of net economic value Value can be added through manufacturing orValue can be added through manufacturing or marketingmarketing Why Add Value

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

    SciTech Connect (OSTI)

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

    2012-09-01T23:59:59.000Z

    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.

  20. Forecasting model of the PEPCO service area economy. Volume 3

    SciTech Connect (OSTI)

    Not Available

    1984-03-01T23:59:59.000Z

    Volume III describes and documents the regional economic model of the PEPCO service area which was relied upon to develop many of the assumptions of future values of economic and demographic variables used in the forecast. The PEPCO area model is mathematically linked to the Wharton long-term forecast of the U.S. Volume III contains a technical discussion of the structure of the regional model and presents the regional economic forecast.

  1. Distribution Based Data Filtering for Financial Time Series Forecasting

    E-Print Network [OSTI]

    Bailey, James

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

  2. Agricultural commodity price forecasting accuracy: futures markets versus commercial econometric models

    E-Print Network [OSTI]

    Rausser, Gordon C.; Just, Richard E.

    1979-01-01T23:59:59.000Z

    versus commercial econometric models Gordon C. RausserMARKETS VERSUS COM4ERCIAL ECONOMETRIC IDDELS by Gordon C.Futures Markets, snd Econometric Models Deeember, 19'7'6,

  3. 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

    Update on Petroleum, Natural Gas, Heating Oil and Gasoline.of the Market for Natural Gas Futures. Energy Journal 16 (Modeling Forum. 2003. Natural Gas, Fuel Diversity and North

  4. A model for forecasting future air travel demand on the North Atlantic

    E-Print Network [OSTI]

    Taneja, Nawal K.

    1971-01-01T23:59:59.000Z

    Introduction: One of the key problems in the analysis and planning of any transport properties and facilities is estimating the future volume of traffic that may be expected to use these properties and facilities. Estimates ...

  5. Orphan drugs : future viability of current forecasting models, in light of impending changes to influential market factors

    E-Print Network [OSTI]

    Gottlieb, Joshua

    2011-01-01T23:59:59.000Z

    Interviews were conducted to establish a baseline for how orphan drug forecasting is currently undertaken by financial market and industry analysts with the intention of understanding the variables typically accounted for ...

  6. 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

  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. Management Forecast Quality and Capital Investment Decisions

    E-Print Network [OSTI]

    Goodman, Theodore H.

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

  9. Future Power Systems 20: The Smart Enterprise, its Objective...

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

    0: The Smart Enterprise, its Objective and Forecasting. Future Power Systems 20: The Smart Enterprise, its Objective and Forecasting. Future Power Systems 20: The Smart Enterprise,...

  10. 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...

  11. Developing and Implementing Sustainability Education through the Integration of Behavioral Science Achieving a sustainable future requires that individuals adopt different values,

    E-Print Network [OSTI]

    Hall, Sharon J.

    Developing and Implementing Sustainability Education through the Integration of Behavioral Science sustainability education, which can be used to guide the development and evaluation of action Abstract Achieving a sustainable future requires that individuals adopt different values, attitudes, habits

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

    E-Print Network [OSTI]

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

  13. 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.

  14. 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.

  15. 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:

  16. Mercury emissions from municipal solid waste combustors. An assessment of the current situation in the United States and forecast of future emissions

    SciTech Connect (OSTI)

    none,

    1993-05-01T23:59:59.000Z

    This report examines emissions of mercury (Hg) from municipal solid waste (MSW) combustion in the United States (US). It is projected that total annual nationwide MSW combustor emissions of mercury could decrease from about 97 tonnes (1989 baseline uncontrolled emissions) to less than about 4 tonnes in the year 2000. This represents approximately a 95 percent reduction in the amount of mercury emitted from combusted MSW compared to the 1989 mercury emissions baseline. The likelihood that routinely achievable mercury emissions removal efficiencies of about 80 percent or more can be assured; it is estimated that MSW combustors in the US could prove to be a comparatively minor source of mercury emissions after about 1995. This forecast assumes that diligent measures to control mercury emissions, such as via use of supplemental control technologies (e.g., carbon adsorption), are generally employed at that time. However, no present consensus was found that such emissions control measures can be implemented industry-wide in the US within this time frame. Although the availability of technology is apparently not a limiting factor, practical implementation of necessary control technology may be limited by administrative constraints and other considerations (e.g., planning, budgeting, regulatory compliance requirements, etc.). These projections assume that: (a) about 80 percent mercury emissions reduction control efficiency is achieved with air pollution control equipment likely to be employed by that time; (b) most cylinder-shaped mercury-zinc (CSMZ) batteries used in hospital applications can be prevented from being disposed into the MSW stream or are replaced with alternative batteries that do not contain mercury; and (c) either the amount of mercury used in fluorescent lamps is decreased to an industry-wide average of about 27 milligrams of mercury per lamp or extensive diversion from the MSW stream of fluorescent lamps that contain mercury is accomplished.

  17. The Value of Energy Performance and Green Attributes in Buildings: A Review of Existing Literature and Recommendations for Future Research

    E-Print Network [OSTI]

    Stuart, Elizabeth

    2012-01-01T23:59:59.000Z

    quantify the value of “green” and energy efficiency upgradesof homes with Build Green, ENERGY STAR or LEED for Homes major renovations, and energy or “green” upgrade projects.

  18. 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.

  19. The Value of Renewable Energy as a Hedge Against Fuel Price Risk: Analytic Contributions from Economic and Finance Theory

    E-Print Network [OSTI]

    Bolinger, Mark A

    2009-01-01T23:59:59.000Z

    placed on any one forecast of future natural gas prices, andreference case forecast of spot natural gas prices deliveredPrice Forecasts to Compare Renewable to Natural Gas- Fired

  20. 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

  1. Forecasting the underlying potential governing climatic time series

    E-Print Network [OSTI]

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

    2012-01-01T23:59:59.000Z

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

  2. Adaptive sampling and forecasting with mobile sensor networks

    E-Print Network [OSTI]

    Choi, Han-Lim

    2009-01-01T23:59:59.000Z

    This thesis addresses planning of mobile sensor networks to extract the best information possible out of the environment to improve the (ensemble) forecast at some verification region in the future. To define the information ...

  3. The Value of Energy Performance and Green Attributes in Buildings: A Review of Existing Literature and Recommendations for Future Research

    SciTech Connect (OSTI)

    Stuart, Elizabeth

    2011-09-07T23:59:59.000Z

    Labels, certifications, and rating systems for energy efficiency performance and “green” attributes of buildings have been available in the U.S. for over 10 years, and used extensively in the European Union and Australia for longer. Such certifications and ratings can make energy efficiency more visible, and could help spur demand for energy efficiency if these designations are shown to have a positive impact on sales or rental prices. This policy brief discusses the findings and methodologies from recent studies on this topic, and suggests recommendations for future research. Although there have been just a handful of studies within the last 10 years that have investigated these effects, a few key findings emerge: To maximize sales price impact, label or rating information must be disclosed early and visibly in the sales process; The approach to evaluating energy efficiency labels (e.g., ENERGY STAR) and general “green” certifications (e.g., LEED or GreenPoint Rated) may need to be different, depending on the type, vintage and market penetration of the label; Collaborative efforts to promote label adoption and build a large dataset of labeled buildings will be required to produce reliable study results.

  4. 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.

  5. Negotiating future climates for public policy: a critical assessment of the development of

    E-Print Network [OSTI]

    Hulme, Mike

    ) or of seasonal forecasting (a few months): Earth system models aim to simulate future climatic evolution over

  6. 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 . . . . . . . . . . . . .

  7. Betting on the Future: The authors compare natural gas forecaststo futures buys

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-01-20T23:59:59.000Z

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

  8. 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

  9. 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

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

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

  11. Naval petroleum reserves: Preliminary analysis of future net revenues from Elk Hills production

    SciTech Connect (OSTI)

    Not Available

    1986-01-01T23:59:59.000Z

    This is an interim report on the present value of the net revenues from Elk Hills Naval Petroleum Reserve. GAO calculated alternative present values of the net revenues applying (1) low, medium, and high forecasts of future crude oil prices and (2) alternative interest rates for discounting the future net revenues to their present values. The calculations are sensitive to both the oil price forecasts and discount rates used; they are preliminary and should be used with caution. They do not take into account possible added tax revenues collected by the government if Elk Hills were sold nor varying production levels and practices, which could either increase or decrease the total amount of oil that can be extracted.

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

    SciTech Connect (OSTI)

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

    2012-07-01T23:59:59.000Z

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

  13. Microsoft Word - Future Power Systems 20 - The Smart Enterprise...

    Office of Environmental Management (EM)

    all gives inefficient burn which costs more in fuel and emissions per kWh. Future Power Systems 20 The Smart Enterprise, its Objective and Forecasting. Steve...

  14. 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...

  15. 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...

  16. Long Term Forecast ofLong Term Forecast of TsunamisTsunamis

    E-Print Network [OSTI]

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

  17. Verification of hourly forecasts of wind turbine power output

    SciTech Connect (OSTI)

    Wegley, H.L.

    1984-08-01T23:59:59.000Z

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

  18. 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...

  19. 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

  20. 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...

  1. 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

  2. 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

  3. 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

  4. 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

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

    SciTech Connect (OSTI)

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

    2012-09-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01T23:59:59.000Z

    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

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

    SciTech Connect (OSTI)

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

    2005-07-01T23:59:59.000Z

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

  8. Application of Fast Marching Methods for Rapid Reservoir Forecast and Uncertainty Quantification

    E-Print Network [OSTI]

    Olalotiti-Lawal, Feyisayo

    2013-05-17T23:59:59.000Z

    Rapid economic evaluations of investment alternatives in the oil and gas industry are typically contingent on fast and credible evaluations of reservoir models to make future forecasts. It is often important to also quantify inherent risks...

  9. Validation of the Highway Performance Monitoring System for forecasting levels of traffic

    E-Print Network [OSTI]

    Bray, Rebecca Anne

    1995-01-01T23:59:59.000Z

    This thesis documents the results and studies conducted when determining the accuracy of the Texas Department of Transportation (TXDOT) methodology of forecasting future levels of traffic demand. The data that was used was the Federal Highway...

  10. 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.

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

    SciTech Connect (OSTI)

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

    2011-12-06T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Heinemann, Detlev

    SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS Detlev Heinemann Oldenburg.girodo@uni-oldenburg.de ABSTRACT Solar energy is expected to contribute major shares of the future global energy supply. Due to its and solar energy conversion processes has to account for this behaviour in respective operating strategies

  13. Clean Energy Program Policy Brief. The Value of Energy Performance and Green Attributes in Buildings: Review of Existing Literature and Recommendations for Future Research.

    E-Print Network [OSTI]

    Stuart, Elizabeth

    2013-01-01T23:59:59.000Z

    quantify the value of “green” and energy efficiency upgradesof homes with Build Green, ENERGY STAR or LEED for Homes major renovations, and energy or “green” upgrade projects.

  14. Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets

    SciTech Connect (OSTI)

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

    2005-02-09T23:59:59.000Z

    This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futures price. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futures price provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futures price underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003 and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futures price into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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)

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

    E-Print Network [OSTI]

    Cañizares, Claudio A.

    1 Forecasting the Hourly Ontario Energy Price by Multivariate Adaptive Regression Splines H. In this paper, the MARS technique is applied to forecast the hourly Ontario energy price (HOEP). The MARS models values of the latest pre- dispatch price and demand information, made available by the Ontario

  7. Subhourly wind forecasting techniques for wind turbine operations

    SciTech Connect (OSTI)

    Wegley, H.L.; Kosorok, M.R.; Formica, W.J.

    1984-08-01T23:59:59.000Z

    Three models for making automated forecasts of subhourly wind and wind power fluctuations were examined to determine the models' appropriateness, accuracy, and reliability in wind forecasting for wind turbine operation. Such automated forecasts appear to have value not only in wind turbine control and operating strategies, but also in improving individual wind turbine control and operating strategies, but also in improving individual wind turbine operating strategies (such as determining when to attempt startup). A simple persistence model, an autoregressive model, and a generalized equivalent Markhov (GEM) model were developed and tested using spring season data from the WKY television tower located near Oklahoma City, Oklahoma. The three models represent a pure measurement approach, a pure statistical method and a statistical-dynamical model, respectively. Forecasting models of wind speed means and measures of deviations about the mean were developed and tested for all three forecasting techniques for the 45-meter level and for the 10-, 30- and 60-minute time intervals. The results of this exploratory study indicate that a persistence-based approach, using onsite measurements, will probably be superior in the 10-minute time frame. The GEM model appears to have the most potential in 30-minute and longer time frames, particularly when forecasting wind speed fluctuations. However, several improvements to the GEM model are suggested. In comparison to the other models, the autoregressive model performed poorly at all time frames; but, it is recommended that this model be upgraded to an autoregressive moving average (ARMA or ARIMA) model. The primary constraint in adapting the forecasting models to the production of wind turbine cluster power output forecasts is the lack of either actual data, or suitable models, for simulating wind turbine cluster performance.

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

    SciTech Connect (OSTI)

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

    2010-01-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2010-09-01T23:59:59.000Z

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. In this report, a new methodology to predict the uncertainty ranges for the required balancing capacity, ramping capability and ramp duration is presented. Uncertainties created by system load forecast errors, wind and solar forecast errors, generation forced outages are taken into account. The uncertainty ranges are evaluated for different confidence levels of having the actual generation requirements within the corresponding limits. The methodology helps to identify system balancing reserve requirement based on a desired system performance levels, identify system “breaking points”, where the generation system becomes unable to follow the generation requirement curve with the user-specified probability level, and determine the time remaining to these potential events. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (California ISO) real life data have shown the effectiveness of the proposed approach. A tool developed based on the new methodology described in this report will be integrated with the California ISO systems. Contractual work is currently in place to integrate the tool with the AREVA EMS system.

  10. 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

  11. 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

  12. Forecasting project progress and early warning of project overruns with probabilistic methods

    E-Print Network [OSTI]

    Kim, Byung Cheol

    2009-05-15T23:59:59.000Z

    project schedule progress with probabilistic methods. Currently available methods, for example, the critical path method (CPM) and earned value management (EVM) are deterministic and fail to account for the inherent uncertainty in forecasting and project...

  13. 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 ...

  14. A Kalman-filter bias correction of ozone deterministic, ensemble-averaged, and probabilistic forecasts

    SciTech Connect (OSTI)

    Monache, L D; Grell, G A; McKeen, S; Wilczak, J; Pagowski, M O; Peckham, S; Stull, R; McHenry, J; McQueen, J

    2006-03-20T23:59:59.000Z

    Kalman filtering (KF) is used to postprocess numerical-model output to estimate systematic errors in surface ozone forecasts. It is implemented with a recursive algorithm that updates its estimate of future ozone-concentration bias by using past forecasts and observations. KF performance is tested for three types of ozone forecasts: deterministic, ensemble-averaged, and probabilistic forecasts. Eight photochemical models were run for 56 days during summer 2004 over northeastern USA and southern Canada as part of the International Consortium for Atmospheric Research on Transport and Transformation New England Air Quality (AQ) Study. The raw and KF-corrected predictions are compared with ozone measurements from the Aerometric Information Retrieval Now data set, which includes roughly 360 surface stations. The completeness of the data set allowed a thorough sensitivity test of key KF parameters. It is found that the KF improves forecasts of ozone-concentration magnitude and the ability to predict rare events, both for deterministic and ensemble-averaged forecasts. It also improves the ability to predict the daily maximum ozone concentration, and reduces the time lag between the forecast and observed maxima. For this case study, KF considerably improves the predictive skill of probabilistic forecasts of ozone concentration greater than thresholds of 10 to 50 ppbv, but it degrades it for thresholds of 70 to 90 ppbv. Moreover, KF considerably reduces probabilistic forecast bias. The significance of KF postprocessing and ensemble-averaging is that they are both effective for real-time AQ forecasting. KF reduces systematic errors, whereas ensemble-averaging reduces random errors. When combined they produce the best overall forecast.

  15. U.S. Department of Energy Workshop Report: Solar Resources and Forecasting

    SciTech Connect (OSTI)

    Stoffel, T.

    2012-06-01T23:59:59.000Z

    This report summarizes the technical presentations, outlines the core research recommendations, and augments the information of the Solar Resources and Forecasting Workshop held June 20-22, 2011, in Golden, Colorado. The workshop brought together notable specialists in atmospheric science, solar resource assessment, solar energy conversion, and various stakeholders from industry and academia to review recent developments and provide input for planning future research in solar resource characterization, including measurement, modeling, and forecasting.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13T23:59:59.000Z

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

  17. 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

  18. The wind power probability density forecast problem can be formulated as: forecast the wind power pdf at time step t for each look-ahead time step t+k of a given time-horizon

    E-Print Network [OSTI]

    Kemner, Ken

    The wind power probability density forecast problem can be formulated as: forecast the wind power ahead) knowing a set of explanatory variables (e.g. numerical weather predictions (NWPs), wind power measured values). Translating this sentence to an equation, we have: where pt+k is the wind power

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

    SciTech Connect (OSTI)

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

    2009-03-01T23:59:59.000Z

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

  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. Radar-Derived Forecasts of Cloud-to-Ground Lightning Over Houston, Texas

    E-Print Network [OSTI]

    Mosier, Richard Matthew

    2011-02-22T23:59:59.000Z

    .1.6 Comparison to Previous Studies......................................................................59 3.2 VII Forecast Method...............................................................................................61 3.2.1 Percentile Value...) percentile values for the entire dataset (1997-2006) when considering only cells with a minimum track count of 2.......................................................................... 117 3.5 Same as Figure 3.4 for the POD values...

  3. 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

  4. 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.

  5. 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

  6. 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

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

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011AT&T,OfficeEnd of Year 2010Salt |Exelon Generation Company, LLC OrderExpanding

  8. Expert Panel: Forecast Future Demand for Medical Isotopes

    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 Chinaof EnergyImpactOn Chapter 42.15 - AttachmentExecutiveDepartment

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

    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 Chinaof EnergyImpactOn Chapter 42.15 - AttachmentExecutiveDepartmentEnergy Expert

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

    E-Print Network [OSTI]

    and the Ohio State University, and is supported by the National Weather Service. Model output is available 734-741-2235 www.glerl.noaa.gov PREDICTING WHAT'S HAPPENING IN THE NEARSHORE ZONE Most human Lakes coasts. To date, two high resolution grid experimental models have been developed for Lake

  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. 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.

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

    SciTech Connect (OSTI)

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

    2013-11-01T23:59:59.000Z

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

  14. Value Engineering

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

    2002-12-30T23:59:59.000Z

    To establish Department of Energy (DOE) value engineering policy that establishs and maintains cost-effective value procedures and processes.

  15. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE: Preprint

    SciTech Connect (OSTI)

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B. M.

    2014-09-01T23:59:59.000Z

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This study examines the value of improved solar power forecasting for the Independent System Operator-New England system. The results show how 25% solar power penetration reduces net electricity generation costs by 22.9%.

  16. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE (Presentation)

    SciTech Connect (OSTI)

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B.M.

    2014-11-01T23:59:59.000Z

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This presentation is an overview of a study that examines the value of improved solar forecasts on Bulk Power System Operations.

  17. Forecasting long-term gas production of dewatered coal seams and fractured gas shales

    SciTech Connect (OSTI)

    Spivey, J.P.; Semmelbeck, M.E.

    1995-12-31T23:59:59.000Z

    Production decline curves are routinely used by engineers to predict the future performance of oil and gas wells. Because the results of decline curve predictions are used for calculating asset value and estimating future revenue, they are one of the most important tools reservoir engineers use. There are numerous variations on the basic exponential or hyperbolic decline analysis method. Fetkovitch and other have extended the decline curve analysis method to handle gas wells properly and to be able to estimate reservoir properties from the analysis of these data. However, there has been considerable drilling activity in the last 10 years into unconventional reservoirs whose wells do not follow the traditional production decline characteristic shapes. Among these problem reservoirs are coalbed methane and fractured shale reservoirs. A procedure is presented which allows forecasting long range performance of dewatered coal and fractured gas shale reservoirs having nonlinear adsorption isotherms, using constant pressure solutions to the flow equation for slightly compressible liquids. A correlation is presented to show the range of applicability of this procedure.

  18. What Do Consumers Believe About Future Gasoline Soren T. Anderson

    E-Print Network [OSTI]

    Silver, Whendee

    What Do Consumers Believe About Future Gasoline Prices? Soren T. Anderson Michigan State University of consumers about their expectations of future gasoline prices. Overall, we find that consumer beliefs follow a random walk, which we deem a reasonable forecast of gasoline prices, but we find a deviation from

  19. Possible global warming futures Minh Ha-Duong

    E-Print Network [OSTI]

    Possible global warming futures Minh Ha-Duong Minh.Ha.Duong@cmu.edu CNRS, France HDGC, Carnegie Mellon Possible global warming futures ­ p.1/36 #12;SRES: Forecasts or scenarios? +5.5 C in 2100 the controversy using imprecise probabilities, a more general information theory. . . Possible global warming

  20. 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

  1. Forecasting project progress and early warning of project overruns with probabilistic methods

    E-Print Network [OSTI]

    Kim, Byung Cheol

    2008-10-10T23:59:59.000Z

    , the critical path method (CPM) and earned value management (EVM) are deterministic and fail to account for the inherent uncertainty in forecasting and project performance. The objective of this dissertation is to improve the predictive capabilities....4.1 Earned Value Management ................................................... 14 2.4.2 CPM ...................................................................................... 20 2.4.3 Monte Carlo Simulation...

  2. VALIDATION OF SHORT AND MEDIUM TERM OPERATIONAL SOLAR RADIATION FORECASTS IN THE US

    E-Print Network [OSTI]

    Perez, Richard R.

    VALIDATION OF SHORT AND MEDIUM TERM OPERATIONAL SOLAR RADIATION FORECASTS IN THE US Richard Perez This paper presents an initial validation of a solar radiation service that provides historical, as well observed solar radiation conditions based on immediate measured history: The position and impact of future

  3. 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...

  4. 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...

  5. 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.

  6. 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...

  7. 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

  8. 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

  9. 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

  10. 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.

  11. 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:

  12. 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...

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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.

  20. Using Wikipedia to forecast diseases

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

    said. "In the same way we check the weather each morning, individuals and public health officials can monitor disease incidence and plan for the future based on today's...

  1. Factors Affecting Option Premium Values

    E-Print Network [OSTI]

    Johnson, Jason; Smith, Jackie; Dhuyvetter, Kevin C.; Waller, Mark L.

    1999-06-23T23:59:59.000Z

    Factors Affecting Option Premium Values Jason Johnson, Jackie Smith, Kevin Dhuyvetter and Mark Waller* Put Options Hedging in the futures market with options is much like buying an insurance policy to protect commodity sellers against declining...

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. TOWARD RELIABLE BENCHMARKING OF SOLAR FLARE FORECASTING METHODS

    SciTech Connect (OSTI)

    Bloomfield, D. Shaun; Higgins, Paul A.; Gallagher, Peter T. [Astrophysics Research Group, School of Physics, Trinity College Dublin, College Green, Dublin 2 (Ireland); McAteer, R. T. James, E-mail: shaun.bloomfield@tcd.ie [Department of Astronomy, New Mexico State University, Las Cruces, NM 88003-8001 (United States)

    2012-03-10T23:59:59.000Z

    Solar flares occur in complex sunspot groups, but it remains unclear how the probability of producing a flare of a given magnitude relates to the characteristics of the sunspot group. Here, we use Geostationary Operational Environmental Satellite X-ray flares and McIntosh group classifications from solar cycles 21 and 22 to calculate average flare rates for each McIntosh class and use these to determine Poisson probabilities for different flare magnitudes. Forecast verification measures are studied to find optimum thresholds to convert Poisson flare probabilities into yes/no predictions of cycle 23 flares. A case is presented to adopt the true skill statistic (TSS) as a standard for forecast comparison over the commonly used Heidke skill score (HSS). In predicting flares over 24 hr, the maximum values of TSS achieved are 0.44 (C-class), 0.53 (M-class), 0.74 (X-class), 0.54 ({>=}M1.0), and 0.46 ({>=}C1.0). The maximum values of HSS are 0.38 (C-class), 0.27 (M-class), 0.14 (X-class), 0.28 ({>=}M1.0), and 0.41 ({>=}C1.0). These show that Poisson probabilities perform comparably to some more complex prediction systems, but the overall inaccuracy highlights the problem with using average values to represent flaring rate distributions.

  10. The value of valuing nature

    E-Print Network [OSTI]

    Adams, W. M.

    2014-10-31T23:59:59.000Z

     synthetic  biology.  Thus,  services  such  as  carbon  sequestration  may  in  future  be  provided  by  ecosystems  that  retain  little  of  their  original  diversity  (8).  Such  ecosystems  are...  ecosystem  services  in  the  watershed  of  the  Panama  Canal  found  that  timber  production  and  carbon  sequestration  increased  synergistically.  However,  contrary  to  managers’  expectations,  both...

  11. Earned Value Management

    E-Print Network [OSTI]

    Ferguson, J

    2002-01-01T23:59:59.000Z

    Earned Value Management is a methodology used to measure and communicate the real physical progress of a project and show its true cost situation. This tool was developed by the US Department of Defense in 1967 and later used successfully for monitoring DOE projects, in particular the US LHC accelerator project. A clear distinction must be made between an earned value management system and other tools under consideration or already existing at CERN which permit accurate predictions of the amount and date of future payments or a detailed follow up of contracts.

  12. 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

  13. 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...

  14. 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

  15. 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...

  16. 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....

  17. 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...

  18. Navy mobility fuels forecasting system report: World petroleum trade forecasts for the year 2000

    SciTech Connect (OSTI)

    Das, S.

    1991-12-01T23:59:59.000Z

    The Middle East will continue to play the dominant role of a petroleum supplier in the world oil market in the year 2000, according to business-as-usual forecasts published by the US Department of Energy. However, interesting trade patterns will emerge as a result of the democratization in the Soviet Union and Eastern Europe. US petroleum imports will increase from 46% in 1989 to 49% in 2000. A significantly higher level of US petroleum imports (principally products) will be coming from Japan, the Soviet Union, and Eastern Europe. Several regions, the Far East, Japan, Latin American, and Africa will import more petroleum. Much uncertainty remains about of the level future Soviet crude oil production. USSR net petroleum exports will decrease; however, the United States and Canada will receive some of their imports from the Soviet Union due to changes in the world trade patterns. The Soviet Union can avoid becoming a net petroleum importer as long as it (1) maintains enough crude oil production to meet its own consumption and (2) maintains its existing refining capacities. Eastern Europe will import approximately 50% of its crude oil from the Middle East.

  19. 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.

  20. Baseline data for the residential sector and development of a residential forecasting database

    SciTech Connect (OSTI)

    Hanford, J.W.; Koomey, J.G.; Stewart, L.E.; Lecar, M.E.; Brown, R.E.; Johnson, F.X.; Hwang, R.J.; Price, L.K.

    1994-05-01T23:59:59.000Z

    This report describes the Lawrence Berkeley Laboratory (LBL) residential forecasting database. It provides a description of the methodology used to develop the database and describes the data used for heating and cooling end-uses as well as for typical household appliances. This report provides information on end-use unit energy consumption (UEC) values of appliances and equipment historical and current appliance and equipment market shares, appliance and equipment efficiency and sales trends, cost vs efficiency data for appliances and equipment, product lifetime estimates, thermal shell characteristics of buildings, heating and cooling loads, shell measure cost data for new and retrofit buildings, baseline housing stocks, forecasts of housing starts, and forecasts of energy prices and other economic drivers. Model inputs and outputs, as well as all other information in the database, are fully documented with the source and an explanation of how they were derived.

  1. Value Engineering

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

    2004-01-07T23:59:59.000Z

    To establish Department of Energy (DOE) value engineering policy that meets the requirements of Public Law 104-106, Section 4306 as codified by 41 United States Code 432. Canceled by DOE N 251.94. Does not cancel other directives.

  2. Merged Sounding Value-Added Product

    SciTech Connect (OSTI)

    Troyan, D

    2010-03-03T23:59:59.000Z

    The Merged Sounding value-added product (VAP) uses a combination of observations from radiosonde soundings, the microwave radiometer (MWR), surface meteorological instruments, and European Centre for Medium-Range Weather Forecasts (ECMWF) model output with a sophisticated scaling/interpolation/smoothing scheme in order to define profiles of the atmospheric thermodynamic state at one-minute temporal intervals and a total of 266 altitude levels.

  3. Value Analysis of Alternative Diesel Particulate Filter (DPF...

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

    Value Analysis of Alternative Diesel Particulate Filter (DPF) Substrates for Future Diesel Aftertreatment Systems Value Analysis of Alternative Diesel Particulate Filter (DPF)...

  4. 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.

  5. Preliminary assessment of future refining impacts of the Clean Air Act Amendments of 1990

    SciTech Connect (OSTI)

    Hadder, G.R.

    1991-09-01T23:59:59.000Z

    A preliminary assessment of the future refining impacts of the Clean Air Act Amendments of 1990 has been performed with the Navy Mobility Fuels Forecasting Systems. The assessment suggests that gasoline reformulation costs in domestic coastal and near-coastal refining regions in the year 2000 could be 3.5 to 5.6 cents per gallon (in terms of 1989 currency). For heating value equivalent to one gallon of conventional gasoline, the regional total added costs (including reformulation costs) for reformulated gasoline could be 5.9 to 8.0 cents. In blending reformulated gasolines, the reduction of butane for lower Reid vapor pressure and the reduction of reformate for lower aromatics are generally compensated by increased percentages of alkylate and/or straight run naphthas. Relatively larger refinery process capacity additions are required for butane isomerization, alkylation, aromatics recovery, and distillate hydrotreating. 21 refs., 3 figs., 18 tabs.

  6. Thirty-year solid waste generation forecast for facilities at SRS

    SciTech Connect (OSTI)

    Not Available

    1994-07-01T23:59:59.000Z

    The information supplied by this 30-year solid waste forecast has been compiled as a source document to the Waste Management Environmental Impact Statement (WMEIS). The WMEIS will help to select a sitewide strategic approach to managing present and future Savannah River Site (SRS) waste generated from ongoing operations, environmental restoration (ER) activities, transition from nuclear production to other missions, and decontamination and decommissioning (D&D) programs. The EIS will support project-level decisions on the operation of specific treatment, storage, and disposal facilities within the near term (10 years or less). In addition, the EIS will provide a baseline for analysis of future waste management activities and a basis for the evaluation of the specific waste management alternatives. This 30-year solid waste forecast will be used as the initial basis for the EIS decision-making process. The Site generates and manages many types and categories of waste. With a few exceptions, waste types are divided into two broad groups-high-level waste and solid waste. High-level waste consists primarily of liquid radioactive waste, which is addressed in a separate forecast and is not discussed further in this document. The waste types discussed in this solid waste forecast are sanitary waste, hazardous waste, low-level mixed waste, low-level radioactive waste, and transuranic waste. As activities at SRS change from primarily production to primarily decontamination and decommissioning and environmental restoration, the volume of each waste s being managed will change significantly. This report acknowledges the changes in Site Missions when developing the 30-year solid waste forecast.

  7. Saving for the future self: Neural measures of future self-continuity predict temporal discounting

    E-Print Network [OSTI]

    Knutson, Brian

    Saving for the future self: Neural measures of future self-continuity predict temporal discounting not increased their rate of saving. In a phenomenon known as `temporal discounting', people value immediate and treat the future self differently from the present self, and so might fail to save for their future

  8. Framtidens lantbruk / Future Agriculture Future Agriculture

    E-Print Network [OSTI]

    Framtidens lantbruk / Future Agriculture Future Agriculture ­ Livestock, Crops and Land Use Report from a multidisciplinary research platform. Phase I (2009 ­ 2012) #12;Future Agriculture ­ Livestock Waldenström Utgivningsĺr: 2012, Uppsala Utgivare: SLU, Framtidens lantbruk/Future Agriculture Layout: Pelle

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

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast Role of the Economic Forecast..................................................................................................................................... 2 Economic Growth Assumptions

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

    E-Print Network [OSTI]

    Singhal, Gaurav

    2012-10-19T23:59:59.000Z

    disaster, Cook Inlet (CI) and Prince William Sound (PWS) are regions that suffer from a lack of accurate wave forecast information. This dissertation develops high- resolution integrated wave forecasting schemes for these regions in order to meet...

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

    E-Print Network [OSTI]

    Datta, Shoumen

    2008-07-31T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Washington at Seattle, University of

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

  13. The effect of multinationality on management earnings forecasts

    E-Print Network [OSTI]

    Runyan, Bruce Wayne

    2005-08-29T23:59:59.000Z

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

  14. A first large-scale flood inundation forecasting model

    SciTech Connect (OSTI)

    Schumann, Guy J-P; Neal, Jeffrey C.; Voisin, Nathalie; Andreadis, Konstantinos M.; Pappenberger, Florian; Phanthuwongpakdee, Kay; Hall, Amanda C.; Bates, Paul D.

    2013-11-04T23:59:59.000Z

    At present continental to global scale flood forecasting focusses on predicting at a point discharge, with little attention to the detail and accuracy of local scale inundation predictions. Yet, inundation is actually the variable of interest and all flood impacts are inherently local in nature. This paper proposes a first large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas and at continental scales. The model was built for the Lower Zambezi River in southeast Africa to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. The inundation model domain has a surface area of approximately 170k km2. ECMWF meteorological data were used to force the VIC (Variable Infiltration Capacity) macro-scale hydrological model which simulated and routed daily flows to the input boundary locations of the 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of many river channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst at the same time representing the floodplain at an appropriate and efficient scale. The modeling system was first calibrated using water levels on the main channel from the ICESat (Ice, Cloud, and land Elevation Satellite) laser altimeter and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of about 1 km (one model resolution) compared to an observed flood edge of the event. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2. However, initial model test runs in forecast mode revealed that it is crucial to account for basin-wide hydrological response time when assessing lead time performances notwithstanding structural limitations in the hydrological model and possibly large inaccuracies in precipitation data.

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

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Boyer, Edmond

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

  17. FORECASTING SOLAR RADIATION PRELIMINARY EVALUATION OF AN APPROACH

    E-Print Network [OSTI]

    Perez, Richard R.

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

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

    E-Print Network [OSTI]

    Povinelli, Richard J.

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

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

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural dedicated models to forecast the 12 individual months directly. Results indicate better performance is superior to naĂŻve forecasts based on persistence and seasonality, and is better than results quoted

  20. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Lang, K.

    1982-01-01T23:59:59.000Z

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

  3. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    , Gary Occhiuzzo, and Keith O'Brien prepared the historical energy consumption data. Nahid Movassagh forecasted consumption for the agriculture and water pumping sectors. Don Schultz and Doug Kemmer developed. California Energy Commission, Electricity Supply Analysis Division. Publication Number: CEC2002012001CMFVI

  4. Facebook IPO updated valuation and user forecasting

    E-Print Network [OSTI]

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

  5. Modeling of Uncertainty in Wind Energy Forecast

    E-Print Network [OSTI]

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

  6. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    NONE

    1998-07-01T23:59:59.000Z

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

  7. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Sripada, Yaji

    for generating textual summaries. Our algorithm has been implemented in a weather forecast generation system. 1 presentation, aid human understanding of the underlying data sets. SUMTIME is a research project aiming turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP

  8. Forecasting sudden changes in environmental pollution patterns

    E-Print Network [OSTI]

    Olascoaga, Maria Josefina

    Forecasting sudden changes in environmental pollution patterns MarĂ­a 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

  9. New Concepts in Wind Power Forecasting Models

    E-Print Network [OSTI]

    Kemner, Ken

    New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, Joăo Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind characteristics (mainly speed and direction) in wind parks connected to a power grid. Renyi's Entropy is combined

  10. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand, EndUser Natural Gas Demand, and Energy Efficiency DECEMBER 2013 CEC2002013004SFV1 CALIFORNIA and expertise of numerous California Energy Commission staff members in the Demand Analysis Office. In addition

  11. SIMULATION AND FORECASTING IN INTERMODAL CONTAINER TERMINAL

    E-Print Network [OSTI]

    Gambardella, Luca Maria

    SIMULATION AND FORECASTING IN INTERMODAL CONTAINER TERMINAL Luca Maria Gambardella1 , Gianluca@idsia.ch 2 LCST, La Spezia Container Terminal, La Spezia (IT) 3 DSP, Data System & Planning sa, Manno (CH working in intermodal container terminals. INTRODUCTION The amount of work a container terminal deals

  12. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    NONE

    1996-08-01T23:59:59.000Z

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

  13. Forecast Technical Document Felling and Removals

    E-Print Network [OSTI]

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

  14. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27T23:59:59.000Z

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

  15. 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

  16. Addressing an Uncertain Future Using Scenario Analysis

    SciTech Connect (OSTI)

    Siddiqui, Afzal S.; Marnay, Chris

    2006-12-15T23:59:59.000Z

    The Office of Energy Efficiency and Renewable Energy (EERE) has had a longstanding goal of introducing uncertainty into the analysis it routinely conducts in compliance with the Government Performance and Results Act (GPRA) and for strategic management purposes. The need to introduce some treatment of uncertainty arises both because it would be good general management practice, and because intuitively many of the technologies under development by EERE have a considerable advantage in an uncertain world. For example, an expected kWh output from a wind generator in a future year, which is not exposed to volatile and unpredictable fuel prices, should be truly worth more than an equivalent kWh from an alternative fossil fuel fired technology. Indeed, analysts have attempted to measure this value by comparing the prices observed in fixed-price natural gas contracts compared to ones in which buyers are exposed to market prices (see Bolinger, Wiser, and Golove and (2004)). In addition to the routine reasons for exploring uncertainty given above, the history of energy markets appears to have exhibited infrequent, but troubling, regime shifts, i.e., historic turning points at which the center of gravity or fundamental nature of the system appears to have abruptly shifted. Figure 1 below shows an estimate of how the history of natural gas fired generating costs has evolved over the last three decades. The costs shown incorporate both the well-head gas price and an estimate of how improving generation technology has gradually tended to lower costs. The purpose of this paper is to explore scenario analysis as a method for introducing uncertainty into EERE's forecasting in a manner consistent with the preceding observation. The two questions are how could it be done, and what is its academic basis, if any. Despite the interest in uncertainty methods, applying them poses some major hurdles because of the heavy reliance of EERE on forecasting tools that are deterministic in nature, such as the Energy Information Administration's (EIA's) National Energy Modeling System (NEMS). NEMS is the source of the influential Annual Energy Outlook whose business-as-usual (BAU) case, the Reference Case, forms the baseline for most of the U.S. energy policy discussion. NEMS is an optimizing model because: 1. it iterates to an equilibrium among modules representing the supply, demand, and energy conversion subsectors; and 2. several subsectoral models are individually solved using linear programs (LP). Consequently, it is deeply rooted in the recent past and any effort to simulate the consequences of a major regime shift as depicted in Figure 1 must come by applying an exogenously specified scenario. And, more generally, simulating futures that lie outside of our recent historic experience, even if they do not include regime switches suggest some form of scenario approach. At the same time, the statistical validity of scenarios that deviate significantly outside the ranges of historic inputs should be questioned.

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    1983-07-01T23:59:59.000Z

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

  20. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

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

    2014-12-30T23:59:59.000Z

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

  1. 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.

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

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01T23:59:59.000Z

    it can generate as much or more energy that it needs ? Building activities need N kWhrs per day (solar panels, heating, etc) ? Harvested from solar panels & passive solar. Amount depends on weather ? NWP models forecast DSWRF @ surface (MJ/m2...://collaboration.cmc.ec.gc.ca/cmc/cmoi/SolarScribe/SolarScribe/ CMC NWP datasets for Day 2 Forecasts ? Regional Deterministic Prediction System (RDPS) ? RDPS raw model data ? 10 km resolution, North America, 000-054 forecasts ? Data at: http...

  3. Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

    SciTech Connect (OSTI)

    Jacobs, John M.; Rhodes, M.; Brown, C. W.; Hood, Raleigh R.; Leight, A.; Long, Wen; Wood, R.

    2014-11-01T23:59:59.000Z

    The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.

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

    SciTech Connect (OSTI)

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

    2012-09-01T23:59:59.000Z

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

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

    Office of Environmental Management (EM)

    Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report.pdf More Documents & Publications Computational Advances in Applied...

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

    E-Print Network [OSTI]

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

    2011-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

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

  8. Sandia National Laboratories: Solar Energy Forecasting and Resource...

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

    & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource Assessment, provides an authoritative voice on the...

  9. 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...

  10. Optimization Online - Data Assimilation in Weather Forecasting: A ...

    E-Print Network [OSTI]

    M. Fisher

    2007-02-14T23:59:59.000Z

    Feb 14, 2007 ... Data Assimilation in Weather Forecasting: A Case Study in PDE-Constrained Optimization. M. Fisher(Mike.Fisher ***at*** ecmwf.int)

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

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

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

  12. Natural Priors, CMSSM Fits and LHC Weather Forecasts

    E-Print Network [OSTI]

    Ben C Allanach; Kyle Cranmer; Christopher G Lester; Arne M Weber

    2007-07-05T23:59:59.000Z

    Previous LHC forecasts for the constrained minimal supersymmetric standard model (CMSSM), based on current astrophysical and laboratory measurements, have used priors that are flat in the parameter tan beta, while being constrained to postdict the central experimental value of MZ. We construct a different, new and more natural prior with a measure in mu and B (the more fundamental MSSM parameters from which tan beta and MZ are actually derived). We find that as a consequence this choice leads to a well defined fine-tuning measure in the parameter space. We investigate the effect of such on global CMSSM fits to indirect constraints, providing posterior probability distributions for Large Hadron Collider (LHC) sparticle production cross sections. The change in priors has a significant effect, strongly suppressing the pseudoscalar Higgs boson dark matter annihilation region, and diminishing the probable values of sparticle masses. We also show how to interpret fit information from a Markov Chain Monte Carlo in a frequentist fashion; namely by using the profile likelihood. Bayesian and frequentist interpretations of CMSSM fits are compared and contrasted.

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

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01T23:59:59.000Z

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

  14. Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    of two methods to forecast natural gas prices: using theof two methods to forecast natural gas prices is performed:accurate average forecast of natural gas prices than the

  15. 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 ...

  16. Expected Future Value Decomposition Based Bid Price Generation ...

    E-Print Network [OSTI]

    2009-11-15T23:59:59.000Z

    to 5 minutes for large-scale problem instances (up to 2.6 million variables and 2.3 million constraints). Keywords: .... They focus on examining different methods.

  17. Renewable Forecast Min-Max2020.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiation Protection Technical s o Freiberge s 3 c/)RenewableRenewable EnergyForecast of

  18. Forecast and Funding Arrangements - Hanford Site

    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 Science (SC) Environmental Assessments (EA)Budget(DANCE) Target 1Annual Waste Forecast and Funding

  19. 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 

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

    SciTech Connect (OSTI)

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

    2014-10-27T23:59:59.000Z

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

  1. 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

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

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Hansens, Jim

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

  4. RESERVOIR INFLOW FORECASTING USING NEURAL NETWORKS CHANDRASHEKAR SUBRAMANIAN

    E-Print Network [OSTI]

    Manry, Michael

    a mixture of hydroelectric and non- hydroelectric power, the economics of the hydroelectric plants depend, and to economically allocate the load between various non-hydroelectric plants. Neural networks provide an attractive technology for inflow forecasting, because of (1) their success in power load forecasting 1- 6 , and (2

  5. Introducing the Canadian Crop Yield Forecaster Aston Chipanshi1

    E-Print Network [OSTI]

    Miami, University of

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

  6. Wind-Wave Probabilistic Forecasting based on Ensemble

    E-Print Network [OSTI]

    have to be jointly taken into account in some decision-making problems, e.g. offshore wind farmWind-Wave Probabilistic Forecasting based on Ensemble Predictions Maxime FORTIN Kongens Lyngby 2012.imm.dtu.dk IMM-PhD-2012-86 #12;Summary Wind and wave forecasts are of a crucial importance for a number

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

    E-Print Network [OSTI]

    Kemner, Ken

    Wind Power Forecasting: State-of-the-Art 2009 ANL/DIS-10-1 Decision and Information Sciences about Argonne and its pioneering science and technology programs, see www.anl.gov. #12;Wind Power................................................ 14 2.2.3 Critical Processes for Wind Forecast

  8. PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022

    E-Print Network [OSTI]

    PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA for electric vehicles. #12;ii #12;iii ABSTRACT The Preliminary California Energy Demand Forecast 2012 includes three full scenarios: a high energy demand case, a low energy demand case, and a mid energy demand

  9. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST, and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption STAFFFINALREPORT NOVEMBER 2007 CEC-200-2007-015-SF2 Arnold Schwarzenegger, Governor #12;CALIFORNIA ENERGY

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

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Manager Kae Lewis Acting Manager Demand Analysis Office Valerie T. Hall Deputy Director Energy Efficiency Demand Forecast report is the product of the efforts of many current and former California Energy

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

    E-Print Network [OSTI]

    i Managing Wind Power Forecast Uncertainty in Electric Grids Brandon Keith Mauch Co for the modeled wind- CAES system would not cover annualized capital costs. We also estimate market prices-ahead market is roughly $100, with large variability due to electric power prices. Wind power forecast errors

  12. Draft for Public Comment Appendix A. Demand Forecast

    E-Print Network [OSTI]

    in the planning process. Electricity demand is forecast to grow from 20,080 average megawatts in 2000 to 25 forecast of electricity demand is a required component of the Council's Northwest Regional Conservation and Electric Power Plan.1 Understanding growth in electricity demand is, of course, crucial to determining

  13. FORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS

    E-Print Network [OSTI]

    Keller, Arturo A.

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

  14. Forecasting Uncertainty Related to Ramps of Wind Power Production

    E-Print Network [OSTI]

    Boyer, Edmond

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

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

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

  16. Forecasting Building Occupancy Using Sensor Network James Howard

    E-Print Network [OSTI]

    Hoff, William A.

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

  17. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01T23:59:59.000Z

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

  18. The future of terrestrial mammals in the Mediterranean basin under climate change

    E-Print Network [OSTI]

    Zimmermann, Niklaus E.

    Research The future of terrestrial mammals in the Mediterranean basin under climate change Luigi climate change model outputs for two climate scenarios. Overall, a substantial number of Mediterranean in climate. For 181 terrestrial mammals (68% of all Mediterranean mammals), we used an ensemble forecasting

  19. Active stewardship: sustainable future

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

    Active stewardship: sustainable future Active stewardship: sustainable future Energy sustainability is a daunting task: How do we develop top-notch innovations with some of the...

  20. Living a Sustainable Future

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

    solve the energy crisis through biological methods, including genetically engineering algae and cyanobacteria. Create a Sustainable Future: Living Living a Sustainable Future How...

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

    SciTech Connect (OSTI)

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

    2011-10-01T23:59:59.000Z

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

  2. The house of the future

    SciTech Connect (OSTI)

    2010-05-13T23:59:59.000Z

    Learn what it will take to create tomorrow's net-zero energy home as scientists reveal the secrets of cool roofs, smart windows, and computer-driven energy control systems. The net-zero energy home: Scientists are working to make tomorrow's homes more than just energy efficient -- they want them to be zero energy. Iain Walker, a scientist in the Lab's Energy Performance of Buildings Group, will discuss what it takes to develop net-zero energy houses that generate as much energy as they use through highly aggressive energy efficiency and on-site renewable energy generation. Talking back to the grid: Imagine programming your house to use less energy if the electricity grid is full or price are high. Mary Ann Piette, deputy director of Berkeley Lab's building technology department and director of the Lab's Demand Response Research Center, will discuss how new technologies are enabling buildings to listen to the grid and automatically change their thermostat settings or lighting loads, among other demands, in response to fluctuating electricity prices. The networked (and energy efficient) house: In the future, your home's lights, climate control devices, computers, windows, and appliances could be controlled via a sophisticated digital network. If it's plugged in, it'll be connected. Bruce Nordman, an energy scientist in Berkeley Lab's Energy End-Use Forecasting group, will discuss how he and other scientists are working to ensure these networks help homeowners save energy.

  3. The house of the future

    ScienceCinema (OSTI)

    None

    2010-09-01T23:59:59.000Z

    Learn what it will take to create tomorrow's net-zero energy home as scientists reveal the secrets of cool roofs, smart windows, and computer-driven energy control systems. The net-zero energy home: Scientists are working to make tomorrow's homes more than just energy efficient -- they want them to be zero energy. Iain Walker, a scientist in the Lab's Energy Performance of Buildings Group, will discuss what it takes to develop net-zero energy houses that generate as much energy as they use through highly aggressive energy efficiency and on-site renewable energy generation. Talking back to the grid: Imagine programming your house to use less energy if the electricity grid is full or price are high. Mary Ann Piette, deputy director of Berkeley Lab's building technology department and director of the Lab's Demand Response Research Center, will discuss how new technologies are enabling buildings to listen to the grid and automatically change their thermostat settings or lighting loads, among other demands, in response to fluctuating electricity prices. The networked (and energy efficient) house: In the future, your home's lights, climate control devices, computers, windows, and appliances could be controlled via a sophisticated digital network. If it's plugged in, it'll be connected. Bruce Nordman, an energy scientist in Berkeley Lab's Energy End-Use Forecasting group, will discuss how he and other scientists are working to ensure these networks help homeowners save energy.

  4. NatioNal aNd Global Forecasts West VirGiNia ProFiles aNd Forecasts

    E-Print Network [OSTI]

    Mohaghegh, Shahab

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

  5. Sustainable value analysis tool for value creation

    E-Print Network [OSTI]

    Yang, Miying; Vladimirova, Doroteya; Rana, Padmakshi; Evans, Steve

    2014-01-01T23:59:59.000Z

    opportunities in the company. For example, the waste of low-grade heat and water was identified to be a major value uncaptured in the MOL, and the value opportunity is that it can be used to produce electricity or drive the compressor, or vaporize the liquid O2... to environment and society. However, the concept of value missed needs further clarity – value currently squandered, wasted or inadequately captured by a current business model. Besides, selling service is intangible, flexible and unpredictable, therefore...

  6. Renewable Electricity Futures Study

    E-Print Network [OSTI]

    Renewable Electricity Futures Study Exploration of High-Penetration Renewable Electricity Futures PDF Volume 4 PDF #12;Renewable Electricity Futures Study Edited By Hand, M.M. National Renewable Citations Renewable Electricity Futures Study (Entire Report) National Renewable Energy Laboratory. (2012

  7. Incorporating Forecast Uncertainty in Utility Control Center

    SciTech Connect (OSTI)

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

    2014-07-09T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Shyy, Wei

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

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

    E-Print Network [OSTI]

    Feinberg, Eugene A.

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

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Lantz, E.; Hand, M.

    2010-05-01T23:59:59.000Z

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

  12. 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

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

    Broader source: Energy.gov [DOE]

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

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

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01T23:59:59.000Z

    GEPS 21 members ? Provides probabilistic forecasts ? Can give useful outlooks for longer term weather forecasts ? Scribe matrix from GDPS ? includes UMOS post processed model data ? Variables like Temperature, humidity post processed by UMOS ? See...://collaboration.cmc.ec.gc.ca/cmc/cmoi/cmc-prob-products/ ? Link to experimental 3-day outlook of REPS quilts ? http://collaboration.cmc.ec.gc.ca/cmc/cmoi/cmc-prob-products.reps Users can also make their own products from ensemble forecast data? Sample ascii matrix of 2m temperature could be fed...

  15. Natural Priors, CMSSM Fits and LHC Weather Forecasts

    E-Print Network [OSTI]

    Allanach, B C; Cranmer, Kyle; Lester, Christopher G; Weber, Arne M

    2007-08-07T23:59:59.000Z

    ar X iv :0 70 5. 04 87 v3 [ he p- ph ] 5 J ul 20 07 Preprint typeset in JHEP style - HYPER VERSION DAMTP-2007-18 Cavendish-HEP-2007-03 MPP-2007-36 Natural Priors, CMSSM Fits and LHC Weather Forecasts Benjamin C Allanach1, Kyle Cranmer2... ’s likely discoveries. There are big differences between nature of the questions answered by a forecast, and the ques- tions that will be answered by the experiments themselves when they have acquired compelling data. A weather forecast predicting “severe...

  16. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01T23:59:59.000Z

    of a range of world oil prices for future energy demand andTo examine the ef feet of oil prices on energy demand andprojections of world oil prices. Th and demand. determined

  17. Electricity Bill Savings from Residential Photovoltaic Systems: Sensitivities to Changes in Future Electricity Market Conditions

    SciTech Connect (OSTI)

    Darghouth, Naim; Barbose, Galen; Wiser, Ryan

    2013-01-09T23:59:59.000Z

    This scoping study investigates the impact of, and interactions among, three key sources of uncertainty in the future value of bill savings from customer-sited PV, focusing in particular on residential customers. These three sources of uncertainty are: changes to electricity market conditions that would affect retail electricity prices, changes to the types of retail rate structures available to residential customers with PV, and shifts away from standard net-metering toward other compensation mechanisms for residential PV. We investigate the impact of a range of electricity market scenarios on retail electricity prices and rate structures, and the resulting effects on the value of bill savings from PV. The scenarios include various levels of renewable and solar energy deployment, high and low natural gas prices, the possible introduction of carbon pricing, and greater or lesser reliance on utility-scale storage and demand response. We examine the bill savings from PV with time-invariant, flat residential retail rates, as well as with time-varying retail rates, including time-of-use (TOU) rates and real-time pricing (RTP). In addition, we explore a flat rate with increasing-block pricing (IBP). We evaluate the bill savings from PV with net metering, as currently allowed in many states, as well as scenarios with hourly netting, a partial form of net metering. This scoping study is the first known effort to evaluate these types of interactions in a reasonably comprehensive fashion, though by no means have we considered every possible change to electricity market conditions, retail rate structures, or PV compensation mechanisms. It focuses solely on the private value of bill savings for residential PV and does not seek to quantify the broader social or economic cost or value of solar electricity. Our analysis applies assumptions based loosely on California’s electricity market in a future year (2030); however, it is neither intended to forecast California’s future market, nor are our conclusions intended to have implications specific only to the California market. That said, some of the findings are unique to our underlying assumptions, as described further within the main body of the report, along with other key limitations.

  18. Optimally controlling hybrid electric vehicles using path forecasting

    E-Print Network [OSTI]

    Katsargyri, Georgia-Evangelina

    2008-01-01T23:59:59.000Z

    Hybrid Electric Vehicles (HEVs) with path-forecasting belong to the class of fuel efficient vehicles, which use external sensory information and powertrains with multiple operating modes in order to increase fuel economy. ...

  19. Recently released EIA report presents international forecasting data

    SciTech Connect (OSTI)

    NONE

    1995-05-01T23:59:59.000Z

    This report presents information from the Energy Information Administration (EIA). Articles are included on international energy forecasting data, data on the use of home appliances, gasoline prices, household energy use, and EIA information products and dissemination avenues.

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

    E-Print Network [OSTI]

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

    2015-03-29T23:59:59.000Z

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  1. OCTOBER-NOVEMBER FORECAST FOR 2014 CARIBBEAN BASIN HURRICANE ACTIVITY

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    and hurricanes, but instead predicts both hurricane days and Accumulated Cyclone Energy (ACE). Typically, while) tropical cyclone (TC) activity. We have decided to issue this forecast, because Klotzbach (2011) has

  2. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07T23:59:59.000Z

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

  3. A methodology for forecasting carbon dioxide flooding performance

    E-Print Network [OSTI]

    Marroquin Cabrera, Juan Carlos

    1998-01-01T23:59:59.000Z

    A methodology was developed for forecasting carbon dioxide (CO2) flooding performance quickly and reliably. The feasibility of carbon dioxide flooding in the Dollarhide Clearfork "AB" Unit was evaluated using the methodology. This technique is very...

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

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01T23:59:59.000Z

    Agency: 1982-2005a, Annual Energy Outlook, EIA, Washington,Agency: 2004, Annual Energy Outlook Forecast Evaluation,Agency: 2005b, Annual Energy Outlook, EIA, Washington, D.C.

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

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01T23:59:59.000Z

    2005a, Annual Energy Outlook, EIA, Washington, D.C. Energy2005b, Annual Energy Outlook, EIA, Washington, D.C. Granger,Paper ???? The Rationality of EIA Forecasts under Symmetric

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

    E-Print Network [OSTI]

    Simmons, Joshua T. (Joshua Thomas)

    2007-01-01T23:59:59.000Z

    This thesis addresses the problem of forecasting demand for Life Limited Parts (LLPs) in the gas turbine engine aftermarket industry. It is based on work performed at Pratt & Whitney, a major producer of turbine engines. ...

  7. Optimally Controlling Hybrid Electric Vehicles using Path Forecasting

    E-Print Network [OSTI]

    Kolmanovsky, Ilya V.

    The paper examines path-dependent control of Hybrid Electric Vehicles (HEVs). In this approach we seek to improve HEV fuel economy by optimizing charging and discharging of the vehicle battery depending on the forecasted ...

  8. Post-Construction Evaluation of Forecast Accuracy Pavithra Parthasarathi1

    E-Print Network [OSTI]

    Levinson, David M.

    Post-Construction Evaluation of Forecast Accuracy Pavithra Parthasarathi1 David Levinson 2 February, the assumed networks to the actual in-place networks and other travel behavior assumptions that went

  9. africa conditional forecasts: Topics by E-print Network

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

    forecasts had the potential to improve resource management but instead played only a marginal role in real-world decision making. 1 A widespread perception that the quality of the...

  10. accident risk forecasting: Topics by E-print Network

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

    forecasts had the potential to improve resource management but instead played only a marginal role in real-world decision making. 1 A widespread perception that the quality of the...

  11. Forecasting Volatility in Stock Market Using GARCH Models

    E-Print Network [OSTI]

    Yang, Xiaorong

    2008-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Romo, Juan

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

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

    E-Print Network [OSTI]

    Adut, Davit

    2004-09-30T23:59:59.000Z

    Financial analysts are an important group of information intermediaries in the capital markets. Their reports, including both earnings forecasts and stock recommendations, are widely transmitted and have a significant impact on stock prices (Womack...

  14. FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007

    E-Print Network [OSTI]

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

  15. An econometric analysis and forecasting of Seoul office market

    E-Print Network [OSTI]

    Kim, Kyungmin

    2011-01-01T23:59:59.000Z

    This study examines and forecasts the Seoul office market, which is going to face a big supply in the next few years. After reviewing several previous studies on the Dynamic model and the Seoul Office market, this thesis ...

  16. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

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

  17. Variable Selection and Inference for Multi-period Forecasting Problems

    E-Print Network [OSTI]

    Pesaran, M Hashem; Pick, Andreas; Timmermann, Allan

    Variable Selection and Inference for Multi-period Forecasting Problems? M. Hashem Pesaran Cambridge University and USC Andreas Pick De Nederlandsche Bank and Cambridge University, CIMF Allan Timmermann UC San Diego and CREATES January 26, 2009...

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

    E-Print Network [OSTI]

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

    2015-01-01T23:59:59.000Z

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

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

    E-Print Network [OSTI]

    Adut, Davit

    2004-09-30T23:59:59.000Z

    Financial analysts are an important group of information intermediaries in the capital markets. Their reports, including both earnings forecasts and stock recommendations, are widely transmitted and have a significant impact on stock prices (Womack...

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

    E-Print Network [OSTI]

    Ham, Joy L

    2002-01-01T23:59:59.000Z

    Over the past decade, ensemble forecasting has emerged as a powerful tool for numerical weather prediction. Not only does it produce the best estimate of the state of the atmosphere, it also could quantify the uncertainties associated with the best...

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    as opposed to coal-fired generation, for example), forprojects much more coal-fired generation (and consequently

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    the Energy Information Administration’s (EIA) web site. Wein the past, compared the EIA’s reference-case long-termfuel price projection from the EIA or some other long-term

  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

    the Energy Information Administration’s (EIA) web site. Wein the past, compared the EIA’s reference-case long-termfuel price projection from the EIA or some other long-term

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01T23:59:59.000Z

    the Energy Information Administration’s (EIA) web site. Wein the past, compared the EIA’s reference-case long-termfuel price projection from the EIA or some other long-term

  5. The Future of the Earth's Climate: Frontiers in Forecasting (LBNL Summer Lecture Series)

    ScienceCinema (OSTI)

    Collins, Bill

    2011-04-28T23:59:59.000Z

    Summer Lecture Series 2007: Berkeley Lab's Bill Collins discusses how observations show that the Earth is warming at a rate unprecedented in recent history, and that human-induced changes in atmospheric chemistry are probably the main culprits. He suggests a need for better observations and understanding of the carbon and hydrological cycles.

  6. 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

    Figure 2 for 5-year price projections), the EIA has, in AEOgenerators to the same price projections from AEO 2001-2006.Strip to AEO 2007 Gas Price Projection Picking the Correct

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    market-based forward price projections argues for furtherAEO 2008 and NYMEX price projections. Nominal ˘/kWh (at 7000that exceed the AEO price projection) described above. If

  8. 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

    range of different plausible price projections, using eitherreference-case fuel price projection from the EIA or someprices and the AEO gas price projections over the past two

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01T23:59:59.000Z

    range of different plausible price projections, using eitherreference-case fuel price projection from the EIA or someHenry Hub to the same price projections from AEO 2007-2008.

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01T23:59:59.000Z

    to electricity generators to the same price projections fromPrices Delivered to Electricity Generators, Nominal $/MMBtu Each AEO projection

  11. 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

    to electricity generators to the same price projections fromPrices Delivered to Electricity Generators, Nominal $/MMBtu Each AEO projection

  12. Forecasting Using Time Varying Meta-Elliptical Distributions with a Study of Commodity Futures Prices

    E-Print Network [OSTI]

    Sancetta, Alessio; Nikanrova, Arina

    2006-03-14T23:59:59.000Z

    that might arise from the roll over of contracts. The commodities studied are crude oil, gas oil (IPE), heating oil, natural gas, propane, un- leaded gas, cocoa, coffee, sugar, orange juice, soybean, corn, rice, oats, wheat and cotton. Assum- ing the data... possess suitable ergodic properties, we report sample summary statistics in Table I. Table I. 15 Table I. Sample Summary Statistics Mean Var Skew Kurt Min 1stQu Median 3rdQu Max CRUDE OIL 0.02 5.18 -0.27 4.07 -16.54 -1.15 0.00 1.29 14.23 GAS OIL (IPE) 0...

  13. Review/Verify Strategic Skills Needs/Forecasts/Future Mission Shifts

    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 PossibleRadiation Protection TechnicalResonant Soft X-RayReview/Verify Strategic Skills

  14. Streamflow forecasting for large-scale hydrologic systems

    E-Print Network [OSTI]

    Awwad, Haitham Munir

    1991-01-01T23:59:59.000Z

    STREAMFLOW FORECASTING FOR LARGE-SCALE HYDROLOGIC SYSTEMS A Thesis by HAITHAM MUNIR AWWAD Submitted to the Office of Graduate Studies of Texas AkM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May... 1991 Major Subject: Civil Engineering STREAMFLOW FORECASTING FOR LARGE-SCALE HYDROLOGIC SYSTEMS A Thesis by HAITHAM MUNIR AWWAD Approved as to style and content by: uan B. Valdes (Chair of Committee) alph A. Wurbs (Member) Marshall J. Mc...

  15. 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...

  16. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M. M.

    2012-09-01T23:59:59.000Z

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  17. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-10-01T23:59:59.000Z

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  18. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-11-01T23:59:59.000Z

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  19. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2013-04-01T23:59:59.000Z

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  20. FutureGen Project Report

    SciTech Connect (OSTI)

    Cabe, Jim; Elliott, Mike

    2010-09-30T23:59:59.000Z

    This report summarizes the comprehensive siting, permitting, engineering, design, and costing activities completed by the FutureGen Industrial Alliance, the Department of Energy, and associated supporting subcontractors to develop a first of a kind near zero emissions integrated gasification combined cycle power plant and carbon capture and storage project (IGCC-CCS). With the goal to design, build, and reliably operate the first IGCC-CCS facility, FutureGen would have been the lowest emitting pulverized coal power plant in the world, while providing a timely and relevant basis for coal combustion power plants deploying carbon capture in the future. The content of this report summarizes key findings and results of applicable project evaluations; modeling, design, and engineering assessments; cost estimate reports; and schedule and risk mitigation from initiation of the FutureGen project through final flow sheet analyses including capital and operating reports completed under DOE award DE-FE0000587. This project report necessarily builds upon previously completed siting, design, and development work executed under DOE award DE-FC26- 06NT4207 which included the siting process; environmental permitting, compliance, and mitigation under the National Environmental Policy Act; and development of conceptual and design basis documentation for the FutureGen plant. For completeness, the report includes as attachments the siting and design basis documents, as well as the source documentation for the following: • Site evaluation and selection process and environmental characterization • Underground Injection Control (UIC) Permit Application including well design and subsurface modeling • FutureGen IGCC-CCS Design Basis Document • Process evaluations and technology selection via Illinois Clean Coal Review Board Technical Report • Process flow diagrams and heat/material balance for slurry-fed gasifier configuration • Process flow diagrams and heat/material balance for dry-fed gasifier configuration • Full capital cost report and cost category analysis (CAPEX) • Full operating cost report and assumptions (OPEX) Comparative technology evaluations, value engineering exercises, and initial air permitting activities are also provided; the report concludes with schedule, risk, and cost mitigation activities as well as lessons learned such that the products of this report can be used to support future investments in utility scale gasification and carbon capture and sequestration. Collectively, the FutureGen project enabled the comprehensive site specific evaluation and determination of the economic viability of IGCC-CCS. The project report is bound at that determination when DOE formally proposed the FutureGen 2.0 project which focuses on repowering a pulverized coal power plant with oxy-combustion technology including CCS.

  1. CHARTING BC'S ECONOMIC FUTURE

    E-Print Network [OSTI]

    Kavanagh, Karen L.

    CHARTING BC'S ECONOMIC FUTURE discussionguide 100communityconversations #12;1 Thank you for agreeing to participate in this Community Conversation about BC's economic future. Each year Simon Fraser is "Charting BC's Economic Future". Faced with an increasingly competitive global economy, it is more important

  2. Renewable Electricity Futures Study

    E-Print Network [OSTI]

    Renewable Electricity Futures Study Executive Summary NREL is a national laboratory of the U for Sustainable Energy, LLC. Volume 2 PDF Volume 3 PDF Volume 1 PDF Volume 4 PDF #12;Renewable Electricity Futures. National Renewable Energy Laboratory Suggested Citations Renewable Electricity Futures Study (Entire Report

  3. Renewable Electricity Futures Study

    E-Print Network [OSTI]

    Renewable Electricity Futures Study End-use Electricity Demand Volume 3 of 4 Volume 2 PDF Volume 3;Renewable Electricity Futures Study Edited By Hand, M.M. National Renewable Energy Laboratory Baldwin, S. U Sandor, D. National Renewable Energy Laboratory Suggested Citations Renewable Electricity Futures Study

  4. Renewable Electricity Futures Study

    E-Print Network [OSTI]

    Renewable Electricity Futures Study Bulk Electric Power Systems: Operations and Transmission by the Alliance for Sustainable Energy, LLC. #12;Renewable Electricity Futures Study Edited By Hand, M.M. National Suggested Citations Renewable Electricity Futures Study (Entire Report) National Renewable Energy Laboratory

  5. FUTURE LOGISTICS LIVING LABORATORY

    E-Print Network [OSTI]

    Heiser, Gernot

    FUTURE LOGISTICS LIVING LABORATORY Delivering Innovation The Future Logistics Living Lab that will provide logistics solutions for the future. The Living Lab is a demonstration, exhibition and work space by a group of logistics companies, research organisations, universities, and IT providers that includes NICTA

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

    E-Print Network [OSTI]

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

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

  7. Value of Concentrating Solar Power and Thermal Energy Storage

    SciTech Connect (OSTI)

    Sioshansi, R.; Denholm, P.

    2010-02-01T23:59:59.000Z

    This paper examines the value of concentrating solar power (CSP) and thermal energy storage (TES) in four regions in the southwestern United States. Our analysis shows that TES can increase the value of CSP by allowing more thermal energy from a CSP plant?s solar field to be used, by allowing a CSP plant to accommodate a larger solar field, and by allowing CSP generation to be shifted to hours with higher energy prices. We analyze the sensitivity of CSP value to a number of factors, including the optimization period, price and solar forecasting, ancillary service sales, capacity value and dry cooling of the CSP plant. We also discuss the value of CSP plants and TES net of capital costs.

  8. 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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-01-01T23:59:59.000Z

    vs. AEO 2001 Price Forecast Natural Gas Price (nominal $/if forwards forecasts) or natural gas-fired generation (ifs reference case forecast of natural gas prices delivered to

  10. Options for Kentucky's Energy Future

    SciTech Connect (OSTI)

    Larry Demick

    2012-11-01T23:59:59.000Z

    Three important imperatives are being pursued by the Commonwealth of Kentucky: ? Developing a viable economic future for the highly trained and experienced workforce and for the Paducah area that today supports, and is supported by, the operations of the US Department of Energy’s (DOE’s) Paducah Gaseous Diffusion Plant (PGDP). Currently, the PGDP is scheduled to be taken out of service in May, 2013. ? Restructuring the economic future for Kentucky’s most abundant indigenous resource and an important industry – the extraction and utilization of coal. The future of coal is being challenged by evolving and increasing requirements for its extraction and use, primarily from the perspective of environmental restrictions. Further, it is important that the economic value derived from this important resource for the Commonwealth, its people and its economy is commensurate with the risks involved. Over 70% of the extracted coal is exported from the Commonwealth and hence not used to directly expand the Commonwealth’s economy beyond the severance taxes on coal production. ? Ensuring a viable energy future for Kentucky to guarantee a continued reliable and affordable source of energy for its industries and people. Today, over 90% of Kentucky’s electricity is generated by burning coal with a delivered electric power price that is among the lowest in the United States. Anticipated increased environmental requirements necessitate looking at alternative forms of energy production, and in particular electricity generation.

  11. Transportation Energy Futures Series: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future

    SciTech Connect (OSTI)

    Grenzeback, L. R.; Brown, A.; Fischer, M. J.; Hutson, N.; Lamm, C. R.; Pei, Y. L.; Vimmerstedt, L.; Vyas, A. D.; Winebrake, J. J.

    2013-03-01T23:59:59.000Z

    Freight transportation demand is projected to grow to 27.5 billion tons in 2040, and to nearly 30.2 billion tons in 2050. This report describes the current and future demand for freight transportation in terms of tons and ton-miles of commodities moved by truck, rail, water, pipeline, and air freight carriers. It outlines the economic, logistics, transportation, and policy and regulatory factors that shape freight demand, the trends and 2050 outlook for these factors, and their anticipated effect on freight demand. After describing federal policy actions that could influence future freight demand, the report then summarizes the capabilities of available analytical models for forecasting freight demand. This is one in a series of reports produced as a result of the Transportation Energy Futures project, a Department of Energy-sponsored multi-agency effort to pinpoint underexplored strategies for reducing GHGs and petroleum dependence related to transportation.

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

    SciTech Connect (OSTI)

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

    1997-01-07T23:59:59.000Z

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

  13. Long-term Industrial Energy Forecasting (LIEF) model (18-sector version)

    SciTech Connect (OSTI)

    Ross, M.H. [Univ. of Michigan, Ann Arbor, MI (US). Dept. of Physics; Thimmapuram, P.; Fisher, R.E.; Maciorowski, W. [Argonne National Lab., IL (US)

    1993-05-01T23:59:59.000Z

    The new 18-sector Long-term Industrial Energy Forecasting (LIEF) model is designed for convenient study of future industrial energy consumption, taking into account the composition of production, energy prices, and certain kinds of policy initiatives. Electricity and aggregate fossil fuels are modeled. Changes in energy intensity in each sector are driven by autonomous technological improvement (price-independent trend), the opportunity for energy-price-sensitive improvements, energy price expectations, and investment behavior. Although this decision-making framework involves more variables than the simplest econometric models, it enables direct comparison of an econometric approach with conservation supply curves from detailed engineering analysis. It also permits explicit consideration of a variety of policy approaches other than price manipulation. The model is tested in terms of historical data for nine manufacturing sectors, and parameters are determined for forecasting purposes. Relatively uniform and satisfactory parameters are obtained from this analysis. In this report, LIEF is also applied to create base-case and demand-side management scenarios to briefly illustrate modeling procedures and outputs.

  14. Standardized Software for Wind Load Forecast Error Analyses and Predictions Based on Wavelet-ARIMA Models - Applications at Multiple Geographically Distributed Wind Farms

    SciTech Connect (OSTI)

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

    2013-03-19T23:59:59.000Z

    Given the multi-scale variability and uncertainty of wind generation and forecast errors, it is a natural choice to use time-frequency representation (TFR) as a view of the corresponding time series represented over both time and frequency. Here we use wavelet transform (WT) to expand the signal in terms of wavelet functions which are localized in both time and frequency. Each WT component is more stationary and has consistent auto-correlation pattern. We combined wavelet analyses with time series forecast approaches such as ARIMA, and tested the approach at three different wind farms located far away from each other. The prediction capability is satisfactory -- the day-ahead prediction of errors match the original error values very well, including the patterns. The observations are well located within the predictive intervals. Integrating our wavelet-ARIMA (‘stochastic’) model with the weather forecast model (‘deterministic’) will improve our ability significantly to predict wind power generation and reduce predictive uncertainty.

  15. Future natural gas supply and demand balance. Final report

    SciTech Connect (OSTI)

    Hall, G.R.

    1983-01-01T23:59:59.000Z

    This study assesses the future price and availability of natural gas as a boiler fuel in the United States. Analysis focuses on various forecasts for natural gas production and consumption through the year 2000. The forecasts reviewed predict that conventional lower-48 production will decline through the year 2000, but there is a wide divergence of opinion on the future availability of gas from unconventional sources of supply. Future gas prices are also uncertain, but as deregulation proceeds, the rolling-in of high cost sources of supply will diminish and gas will be priced more competitively with oil. Analysis presented in the report implies that it will be prudent to maintain the planning assumption that gas will be phased out as a boiler fuel. Gas should, however, remain attractive to utilities for a variety of specific uses. Fluctuating fuel prices may make it advantageous to use gas for short periods of time, and gas may also prove to be attractive in less price sensitive applications.

  16. Residential sector end-use forecasting with EPRI-Reeps 2.1: Summary input assumptions and results

    SciTech Connect (OSTI)

    Koomey, J.G.; Brown, R.E.; Richey, R. [and others

    1995-12-01T23:59:59.000Z

    This paper describes current and projected future energy use by end-use and fuel for the U.S. residential sector, and assesses which end-uses are growing most rapidly over time. The inputs to this forecast are based on a multi-year data compilation effort funded by the U.S. Department of Energy. We use the Electric Power Research Institute`s (EPRI`s) REEPS model, as reconfigured to reflect the latest end-use technology data. Residential primary energy use is expected to grow 0.3% per year between 1995 and 2010, while electricity demand is projected to grow at about 0.7% per year over this period. The number of households is expected to grow at about 0.8% per year, which implies that the overall primary energy intensity per household of the residential sector is declining, and the electricity intensity per household is remaining roughly constant over the forecast period. These relatively low growth rates are dependent on the assumed growth rate for miscellaneous electricity, which is the single largest contributor to demand growth in many recent forecasts.

  17. Multi-path transportation futures study : vehicle characterization and scenario analyses.

    SciTech Connect (OSTI)

    Plotkin, S. E.; Singh, M. K.; Energy Systems; TA Engineering; ORNL

    2009-12-03T23:59:59.000Z

    Projecting the future role of advanced drivetrains and fuels in the light vehicle market is inherently difficult, given the uncertainty (and likely volatility) of future oil prices, inadequate understanding of likely consumer response to new technologies, the relative infancy of several important new technologies with inevitable future changes in their performance and costs, and the importance - and uncertainty - of future government marketplace interventions (e.g., new regulatory standards or vehicle purchase incentives). This Multi-Path Transportation Futures (MP) Study has attempted to improve our understanding of this future role by examining several scenarios of vehicle costs, fuel prices, government subsidies, and other key factors. These are projections, not forecasts, in that they try to answer a series of 'what if' questions without assigning probabilities to most of the basic assumptions.

  18. Climate Science for a Sustainable Energy Future Atmospheric Radiation Measurement Best Estimate (CSSEFARMBE)

    SciTech Connect (OSTI)

    Riihimaki, Laura D.; Gaustad, Krista L.; McFarlane, Sally A.

    2012-09-28T23:59:59.000Z

    The Climate Science for a Sustainable Energy Future (CSSEF) project is working to improve the representation of the hydrological cycle in global climate models, critical information necessary for decision-makers to respond appropriately to predictions of future climate. In order to accomplish this objective, CSSEF is building testbeds to implement uncertainty quantification (UQ) techniques to objectively calibrate and diagnose climate model parameterizations and predictions with respect to local, process-scale observations. In order to quantify the agreement between models and observations accurately, uncertainty estimates on these observations are needed. The DOE Atmospheric Radiation Measurement (ARM) program takes atmospheric and climate related measurements at three permanent locations worldwide. The ARM VAP called the ARM Best Estimate (ARMBE) [Xie et al., 2010] collects a subset of ARM observations, performs quality control checks, averages them to one hour temporal resolution, and puts them in a standard format for ease of use by climate modelers. ARMBE has been widely used by the climate modeling community as a summary product of many of the ARM observations. However, the ARMBE product does not include uncertainty estimates on the data values. Thus, to meet the objectives of the CSSEF project and enable better use of this data with UQ techniques, we created the CSSEFARMBE data set. Only a subset of the variables contained in ARMBE is included in CSSEFARMBE. Currently only surface meteorological observations are included, though this may be expanded to include other variables in the future. The CSSEFARMBE VAP is produced for all extended facilities at the ARM Southern Great Plains (SGP) site that contain surface meteorological equipment. This extension of the ARMBE data set to multiple facilities at SGP allows for better comparison between model grid boxes and the ARM point observations. In the future, CSSEFARMBE may also be created for other ARM sites. As each site has slightly different instrumentation, this will require additional development to understand the uncertainty characterization associated with instrumentation at those sites. The uncertainty assignment process is implemented into the ARM program’s new Integrated Software Development Environment (ISDE) so that many of the key steps can be used in the future to screen data based on ARM Data Quality Reports (DQRs), propagate uncertainties when transforming data from one time scale into another, and convert names and units into NetCDF Climate and Forecast (CF) standards. These processes are described in more detail in the following sections.

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2000-08-31T23:59:59.000Z

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

  20. Stress Testing Projected Capitalized Farmland Values 

    E-Print Network [OSTI]

    Gao, Bo 1988-

    2012-11-12T23:59:59.000Z

    values in each state as well as regional averages over the 2012-2015 period. These projections reflect alternative assumptions regarding future trends in real net farm income at the state level as well as the rate on 10-year constant maturity U...

  1. Measuring value added characteristics in feeder cattle

    E-Print Network [OSTI]

    Mathews, Crystal Dawn

    2009-05-15T23:59:59.000Z

    , cyclical effects, lot size, weight, breed type, sex, commingling, fed cattle futures price, and corn price were all found to have an impact on the sale price of feeder cattle. Feeder calves sold through MFA Health Track Beef Alliance and other value added...

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01T23:59:59.000Z

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

  3. My Amazing Future 2012

    ScienceCinema (OSTI)

    None

    2013-05-28T23:59:59.000Z

    Idaho National Laboratory's My Amazing Future program gives 8th grade women the opportunity to experience careers in science and engineering.

  4. Future City Competition

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

    Competition is an unique opportunity for middle school children to combine skills in engineering, environmental science, and art to create a vision for the future. Exercising your...

  5. California climate change, hydrologic response, and flood forecasting

    SciTech Connect (OSTI)

    Miller, Norman L.

    2003-11-11T23:59:59.000Z

    There is strong evidence that the lower atmosphere has been warming at an unprecedented rate during the last 50 years, and it is expected to further increase at least for the next 100 years. Warmer air mass implies a higher capacity to hold water vapor and an increased likelihood of an acceleration of the global water cycle. This acceleration is not validated and considerable new research has gone into understanding aspects of the water cycle (e.g. Miller et al. 2003). Several significant findings on the hydrologic response to climate change can be reported. It is well understood that the observed and expected warming is related to sea level rise. In a recent seminar at Lawrence Berkeley National Laboratory, James Hansen (Director of the Institute for Space Studies, National Aeronautics and Space Administration) stressed that a 1.25 Wm{sup -2} increase in radiative forcing will lead to an increase in the near surface air temperature by 1 C. This small increase in temperature from 2000 levels is enough to cause very significant impacts to coasts. Maury Roos (Chief Hydrologist, California Department of Water Resources) has shown that a 0.3 m rise in sea level shifts the San Francisco Bay 100-year storm surge flood event to a 10-year event. Related coastal protection costs for California based on sea level rise are shown. In addition to rising sea level, snowmelt-related streamflow represents a particular problem in California. Model studies have indicated that there will be approximately a 50% decrease in snow pack by 2100. This potential deficit must be fully recognized and plans need to be put in place well in advance. In addition, the warmer atmosphere can hold more water vapor and result in more intense warm winter-time precipitation events that result in flooding. During anticipated high flow, reservoirs need to release water to maintain their structural integrity. California is at risk of water shortages, floods, and related ecosystem stresses. More research needs to be done to further improve our ability to forecast weather events at longer time scales. Seasonal predictions have been statistical and only recently have studies begun to use ensemble simulations and historical observations to constrain such predictions. Understanding the mechanisms of large-scale atmospheric dynamics and its local impacts remain topics of intensive research. The ability to predict extreme events and provide policy makers with this information, along with climate change and hydrologic response information, will help to guide planning to form a more resilient infrastructure in the future.

  6. A Literature Review on Value Stream Mapping with a Case Study of Applying Value Stream Mapping on Research Process

    E-Print Network [OSTI]

    Li, Xiaoqi

    2014-04-23T23:59:59.000Z

    this research study and the value stream mapping of my thesis writing process. The value stream mapping process helps visualize the work and target waste, which enables future improvement toward a better state. As a result, the improved value stream maps can...

  7. The Relation Between Rents and Agricultural Land Values in Theory and in Practice.

    E-Print Network [OSTI]

    Buechel, F. A. (Frederick Anthony)

    1924-01-01T23:59:59.000Z

    carefully weighs all the factors involved in land valuation, calling to his aid the most improved statistical methods that will enable h to raticnally forecast future tendencies. Such a speculator v buy when prices are relatively too low and sell when... the factors entering into land valuation are extremely complex, land speculators who know how to interpret these factors may exert a steadying influence upon prices of land and thus render a great social service. Men in the public service, as for example...

  8. 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.

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

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price.................................................................................................................................. 27 INTRODUCTION The Council prepares and periodically updates a 20-year forecast of wholesale to forecast wholesale power prices. AURORAxmp® provides the ability to inco

  10. 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

    and validation.   Solar Energy.   73:5, 307? Perez, R. , forecast database.   Solar Energy.   81:6, 809?812.  forecasts in the US.   Solar Energy.   84:12, 2161?2172.  

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

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

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

  12. 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%....

  13. 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

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

    E-Print Network [OSTI]

    ............................................................................................................................... 12 Oil Price Forecast Range. The price of crude oil was $25 a barrel in January of 2000. In July 2008 it averaged $127, even approachingSixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast Introduction

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

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01T23:59:59.000Z

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

  16. Solar Variability and Forecasting Jan Kleissl, Chi Chow, Matt Lave, Patrick Mathiesen,

    E-Print Network [OSTI]

    Homes, Christopher C.

    Forecasting Benefits Use of state-of-art wind and solar forecasts reduces WECC operating costs by up to 14/MWh of wind and solar generation). WECC operating costs could be reduced by an additional $500 million

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01T23:59:59.000Z

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

  18. 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

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

    E-Print Network [OSTI]

    Newton, Nathan J.

    2013-06-26T23:59:59.000Z

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

  20. Forecasting the demand for electric vehicles: accounting for attitudes and perceptions

    E-Print Network [OSTI]

    Bierlaire, Michel

    prediction, transportation, attitudes and perceptions, hybrid choice models, fractional factorial design: survey design, model estimation and forecasting. We develop a stated preferences (SP) survey with issues related to the application of models designed to forecast demand for new alternatives, most

  1. Price forecasting for U.S. cattle feeders: which technique to apply?

    E-Print Network [OSTI]

    Hicks, Geoff Cody

    1997-01-01T23:59:59.000Z

    both feeder cattle costs and corn costs, and maximizing fed cattle prices. This research strives to evaluate the accuracy of six distinct price forecasting techniques over an eleven year period. The forecast techniques selected for this analysisare...

  2. Streamflow Forecasting Based on Statistical Applications and Measurements Made with Rain Gage and Weather Radar

    E-Print Network [OSTI]

    Hudlow, M.D.

    Techniques for streamflow forecasting are developed and tested for the Little Washita River in Oklahoma. The basic input for streamflow forecasts is rainfall. the rainfall amounts may be obtained from several sources; however, this study...

  3. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-08-01T23:59:59.000Z

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It was presented in a Power Systems Engineering Research Center webinar on September 4, 2012.

  4. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M.; Mai, T.

    2012-08-01T23:59:59.000Z

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It was presented in an Union of Concerned Scientists webinar on June 12, 2012.

  5. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-08-01T23:59:59.000Z

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. This presentation was presented in a Wind Powering America webinar on August 15, 2012 and is now available through the Wind Powering America website.

  6. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M.

    2012-10-01T23:59:59.000Z

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It is being presented at the Utility Variable-Generation Integration Group Fall Technical Workshop on October 24, 2012.

  7. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M. M.

    2012-08-01T23:59:59.000Z

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It was presented in a webinar given by the California Energy Commission.

  8. The Hanford Story: Future

    Broader source: Energy.gov [DOE]

    The Future Chapter of the Hanford Story illustrates the potential and possibilities offered by a post-cleanup Hanford. From land use plans and preservation at Hanford to economic development and tourism opportunities, the Future chapter touches on a variety of local economic, cultural and environmental perspectives.

  9. Forecast of contracting and subcontracting opportunities. Fiscal year 1996

    SciTech Connect (OSTI)

    NONE

    1996-02-01T23:59:59.000Z

    This forecast of prime and subcontracting opportunities with the U.S. Department of Energy and its MAO contractors and environmental restoration and waste management contractors, is the Department`s best estimate of small, small disadvantaged and women-owned small business procurement opportunities for fiscal year 1996. The information contained in the forecast is published in accordance with Public Law 100-656. It is not an invitation for bids, a request for proposals, or a commitment by DOE to purchase products or services. Each procurement opportunity is based on the best information available at the time of publication and may be revised or cancelled.

  10. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01T23:59:59.000Z

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

  12. Photovoltaics: Helping Power Our Clean Energy Future

    E-Print Network [OSTI]

    Firestone, Jeremy

    Photovoltaics: Helping Power Our Clean Energy Future Dick Swanson #12;Safe Harbor Statement Certain of efficiency ­ Improved efficiency leverages entire value chain 2. Reduce manufacturing cost at all points: 50% by 2012 10 $/Watt 2006 Downstream Panel Cell Silicon Efficiency 2012 25% 5 % 5 % 10% 15% Target

  13. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 15 SEPTEMBER 28, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the second year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  14. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 27 OCTOBER 10, 2013

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fifth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  15. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 16 AUGUST 29, 2013

    E-Print Network [OSTI]

    that we are trying to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index This is the fifth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early for ACE using three categories as defined in Table 1. Table 1: ACE forecast definition. Parameter

  16. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 3 AUGUST 16, 2012

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fourth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  17. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 12 OCTOBER 25, 2012

    E-Print Network [OSTI]

    Gray, William

    to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined This is the fourth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting for individual event parameters such as named storms and hurricanes. We issue forecasts for ACE using three

  18. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 28 OCTOBER 11, 2012

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fourth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  19. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 13 SEPTEMBER 26, 2013

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fifth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  20. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 18 AUGUST 31, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the second year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  1. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 11 OCTOBER 24, 2013

    E-Print Network [OSTI]

    Gray, William

    to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined This is the fifth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting for individual event parameters such as named storms and hurricanes. We issue forecasts for ACE using three

  2. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 2 AUGUST 15, 2013

    E-Print Network [OSTI]

    Gray, William

    that we are trying to predict with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index This is the fifth year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting for ACE using three categories as defined in Table 1. Table 1: ACE forecast definition. Parameter

  3. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 31 SEPTEMBER 13, 2012

    E-Print Network [OSTI]

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fourth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  4. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 17 AUGUST 30, 2012

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fourth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  5. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 4 AUGUST 17, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the second year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  6. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 29 OCTOBER 12, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the second year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  7. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 11 SEPTEMBER 24, 2014

    E-Print Network [OSTI]

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the sixth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  8. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 30 SEPTEMBER 12, 2013

    E-Print Network [OSTI]

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the fifth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  9. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 31 SEPTEMBER 13, 2011

    E-Print Network [OSTI]

    Birner, Thomas

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the third year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  10. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 28 SEPTEMBER 10, 2014

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the sixth year that we have issued shorter-term forecasts of tropical cyclone activity starting in early such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

  11. COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 13 OCTOBER 26, 2010

    E-Print Network [OSTI]

    Gray, William

    with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all This is the second year that we have issued shorter-term forecasts of tropical cyclone (TC) activity starting such as named storms and hurricanes. We issue forecasts for ACE using three categories as defined in Table 1

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

    E-Print Network [OSTI]

    Kolter, J. Zico

    -Gaussian case using the copula transform. On a wind power forecasting task, we show that this probabilisticLarge-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random high-dimensional conditional Gaussian distributions to forecasting wind power and extend it to the non

  13. EUROBRISA: A EURO-BRazilian Initiative for improving South American seasonal forecasts

    E-Print Network [OSTI]

    EUROBRISA: A EURO-BRazilian Initiative for improving South American seasonal forecasts by Caio A. S. van Oldenborgh, 2006: Towards an integrated seasonal forecasting system for South America. J. Climate and promote exchange of expertise and information between European and South American seasonal forecasters

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

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    ANNGSF) and for forecasting the one-hour-ahead heat load for a district heat load network (Seppälä et al and network analysis functions in power utilities. Since high-low temperature forecasts are usually provided-Rohani & Maratukulam, 1998). In other agricultural and environmental applications, even high-low temperature forecasts

  15. Development, testing, and applications of site-specific tsunami inundation models for real-time forecasting

    E-Print Network [OSTI]

    can the forecasts completely cover the evolution of earthquake-generated tsunami waves: generationDevelopment, testing, and applications of site-specific tsunami inundation models for real and applications of site-specific tsunami inundation models (forecast models) for use in NOAA's tsunami forecast

  16. Forecast of the electricity consumption by aggregation of specialized experts; application to Slovakian and French

    E-Print Network [OSTI]

    Forecast of the electricity consumption by aggregation of specialized experts; application-term forecast of electricity consumption based on ensemble methods. That is, we use several possibly independent´erieure and CNRS. hal-00484940,version1-19May2010 #12;Forecast of the electricity consumption by aggregation

  17. 2008 European PV Conference, Valencia, Spain COMPARISON OF SOLAR RADIATION FORECASTS FOR THE USA

    E-Print Network [OSTI]

    Perez, Richard R.

    2008 European PV Conference, Valencia, Spain COMPARISON OF SOLAR RADIATION FORECASTS FOR THE USA J models 1 INTRODUCTION Solar radiation and PV production forecasts are becoming increasingly important/) three teams of experts are benchmarking their solar radiation forecast against ground truth data

  18. Robust Pareto Optimum Routing of Ships Deterministic and Ensemble Weather Forecasts

    E-Print Network [OSTI]

    Berlin,Technische Universität

    Robust Pareto ­ Optimum Routing of Ships utilizing Deterministic and Ensemble Weather Forecasts the SEAROUTES project, who provided me with exquisite weather forecasts, and who inspired me to apply ensemble ship operation. The more reliable weather forecasts and performance simulation of ships in a seaway

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

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

  20. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    DeMeo, E.

    2012-08-01T23:59:59.000Z

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It was presented at Wind Powering America States Summit. The Summit, which follows the American Wind Energy Association's (AWEA's) annual WINDPOWER Conference and Exhibition, provides state Wind Working Groups, state energy officials, U.S. Energy Department and national laboratory representatives, and professional and institutional partners an opportunity to review successes, opportunities, and challenges for wind energy and plan future collaboration.

  1. High coking value pitch

    SciTech Connect (OSTI)

    Miller, Douglas J.; Chang, Ching-Feng; Lewis, Irwin C.; Lewis, Richard T.

    2014-06-10T23:59:59.000Z

    A high coking value pitch prepared from coal tar distillate and has a low softening point and a high carbon value while containing substantially no quinoline insolubles is disclosed. The pitch can be used as an impregnant or binder for producing carbon and graphite articles.

  2. Future Grid: The Environment Future Grid Initiative White Paper

    E-Print Network [OSTI]

    Future Grid: The Environment Future Grid Initiative White Paper Power Systems Engineering Research Center Empowering Minds to Engineer the Future Electric Energy System #12;Future Grid: The Environment Prepared for the Project "The Future Grid to Enable Sustainable Energy Systems" Funded by the U

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

    E-Print Network [OSTI]

    Choi, Ji Won

    2007-09-17T23:59:59.000Z

    , the Construction Industry Institute (CII) formed a research team to develop a new tool that can forecast the potential risk of not meeting specific project outcomes based on assessing leading indicators. Thus, the leading indicators were identified and then the new...

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

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    1 Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets Qun Zhou--In current restructured wholesale power markets, the short length of time series for prices makes are fitted between D&O and wholesale power prices in order to obtain price scenarios for a specified time

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

    SciTech Connect (OSTI)

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

    2011-03-28T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    de Freitas, Nando

    economy. Commodity prices are key economical20 drivers in the market. Raw products such as oil, gold 15 1 Introduction16 17 1.1 Forecasting the commodities market18 The commodities market focuses of prices in both the short and long-term view25 point to help market participants gage a greater

  7. Optimal Storage Policies with Wind Forecast Uncertainties [Extended Abstract

    E-Print Network [OSTI]

    Dalang, Robert C.

    Optimal Storage Policies with Wind Forecast Uncertainties [Extended Abstract] Nicolas Gast EPFL, IC generation. The use of energy storage compensates to some extent these negative effects; it plays a buffer role between demand and production. We revisit a model of real storage proposed by Bejan et al.[1]. We

  8. 1994 battery shipment review and five-year forecast report

    SciTech Connect (OSTI)

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

    1995-12-31T23:59:59.000Z

    This paper presents a 1994 battery shipment review and five year forecast report. Data is presented on replacement battery shipments, battery shipments, car and truck production, truck sales, original equipment, shipments for passenger cars and light commercial vehicles, and ten year battery service life trend.

  9. The Galactic Center Weather Forecast M. Moscibrodzka1

    E-Print Network [OSTI]

    Gammie, Charles F.

    The Galactic Center Weather Forecast M. Mo´scibrodzka1 , H. Shiokawa2 , C. F. Gammie2,3 , J*. The > 3M cloud will #12;­ 2 ­ interact strongly with gas near nominal pericenter at rp 300AU 8000GM/c2 transient phase while the flow circularizes-- accompanied by transient emission--it is natural to think

  10. GenForecast(26yr)(avg).PDF

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

    SLCAIP Historical & Forecast Generation at Plant Total Range of Hydrology 0 2,000,000,000 4,000,000,000 6,000,000,000 8,000,000,000 10,000,000,000 12,000,000,000 1 9 7 0 1 9 7 2 1...

  11. WIND POWER ENSEMBLE FORECASTING Henrik Aalborg Nielsen1

    E-Print Network [OSTI]

    WIND POWER ENSEMBLE FORECASTING Henrik Aalborg Nielsen1 , Henrik Madsen1 , Torben Skov Nielsen1. In this paper we address the problems of (i) transforming the mete- orological ensembles to wind power ensembles the uncertainty which follow from historical (climatological) data. However, quite often the actual wind power

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

    E-Print Network [OSTI]

    Boyer, Edmond

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

  13. Navy Mobility Fuels Forecasting System. Phase I report

    SciTech Connect (OSTI)

    Davis, R.M.; Hadder, G.R.; Singh, S.P.N.; Whittle, C.

    1985-07-01T23:59:59.000Z

    The Department of the Navy (DON) requires an improved capability to forecast mobility fuel availability and quality. The changing patterns in fuel availability and quality are important in planning the Navy's Mobility Fuels R and D Program. These changes come about primarily because of the decline in the quality of crude oil entering world markets as well as the shifts in refinery capabilities domestically and worldwide. The DON requested ORNL's assistance in assembling and testing a methodology for forecasting mobility fuel trends. ORNL reviewed and analyzed domestic and world oil reserve estimates, production and price trends, and recent refinery trends. Three publicly available models developed by the Department of Energy were selected as the basis of the Navy Mobility Fuels Forecasting System. The system was used to analyze the availability and quality of jet fuel (JP-5) that could be produced on the West Coast of the United States under an illustrative business-as-usual and a world oil disruption scenario in 1990. Various strategies were investigated for replacing the lost JP-5 production. This exercise, which was strictly a test case for the forecasting system, suggested that full recovery of lost fuel production could be achieved by relaxing the smoke point specifications or by increasing the refiners' gate price for the jet fuel. A more complete analysis of military mobility fuel trends is currently under way.

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

    E-Print Network [OSTI]

    Raftery, Adrian

    the chance of winds high enough to pose dangers for boats or aircraft. In situations calling for a cost/loss analysis, the probabilities of different outcomes need to be known. For wind speed, this issue often arisesProbabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging J. Mc

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

    E-Print Network [OSTI]

    Shenoy, Prashant

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

  16. Leveraging Weather Forecasts in Renewable Energy Navin Sharmaa,

    E-Print Network [OSTI]

    Shenoy, Prashant

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

  17. Risk Forecasting with GARCH, Skewed t Distributions, and Multiple Timescales

    E-Print Network [OSTI]

    Risk Forecasting with GARCH, Skewed t Distributions, and Multiple Timescales Alec N. Kercheval describe how the histori- cal data can first be GARCH filtered and then used to calibrate parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.2 Data and Stylized Facts . . . . . . . . . . . . . . . . . . . . . . . 16 3.3 GARCH Filter

  18. Forecasting Hospital Bed Availability Using Simulation and Neural Networks

    E-Print Network [OSTI]

    Kuhl, Michael E.

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

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

    E-Print Network [OSTI]

    Cerpa, Alberto E.

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

  20. Development and Deployment of an Advanced Wind Forecasting Technique

    E-Print Network [OSTI]

    Kemner, Ken

    findings. Part 2 addresses how operators of wind power plants and power systems can incorporate advanced the output of advanced wind energy forecasts into decision support models for wind power plant and power and applications of power market simulation models around the world. Argonne's software tools are used extensively

  1. Integrating agricultural pest biocontrol into forecasts of energy biomass production

    E-Print Network [OSTI]

    Gratton, Claudio

    Analysis Integrating agricultural pest biocontrol into forecasts of energy biomass production T), University of Lome, 114 Rue Agbalepedogan, BP: 20679, Lome, Togo e Center for Agricultural & Energy Policy model of potential biomass supply that incorporates the effect of biological control on crop choice

  2. Radiation fog forecasting using a 1-dimensional model

    E-Print Network [OSTI]

    Peyraud, Lionel

    2001-01-01T23:59:59.000Z

    The importance of fog forecasting to the aviation community, to road transportation and to the public at large is irrefutable. The deadliest aviation accident in history was in fact partly a result of fog back on 27 March 1977. This has, along...

  3. Classification and forecasting of load curves Nolwen Huet

    E-Print Network [OSTI]

    Cuesta, Juan Antonio

    Classification and forecasting of load curves Nolwen Huet Abstract The load curve, which gives of electricity customer uses. This load curve is only available for customers with automated meter reading. For the others, EDF must estimate this curve. Usually a clustering of the load curves is performed, followed

  4. What constrains spread growth in forecasts ini2alized from

    E-Print Network [OSTI]

    Hamill, Tom

    1 What constrains spread growth in forecasts ini2alized from ensemble Kalman filters? Tom from manner in which ini2al condi2ons are generated, some due to the model (e.g., stochas2c physics as error; part of spread growth from manner in which ini2al condi2ons are generated, some due

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

    E-Print Network [OSTI]

    de Lijser, Peter

    CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE - APRIL 2014 Anil Puri, Ph.D. -- Director-year increase in the debt ceiling -- both of which proceeded without the usual drama. Second, the private sector, corporate coffers are flush with cash, and low US energy prices have dramatically improved the global

  6. Exploiting weather forecasts for sizing photovoltaic energy bids

    E-Print Network [OSTI]

    Giannitrapani, Antonello

    1 Exploiting weather forecasts for sizing photovoltaic energy bids Antonio Giannitrapani, Simone for a photovoltaic (PV) power producer taking part into a competitive electricity market characterized by financial set from an Italian PV plant. Index Terms--Energy market, bidding strategy, photovoltaic power

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

    E-Print Network [OSTI]

    Prasanna, Viktor K.

    1 Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids Yogesh Simmhan, prasanna}@usc.edu I. INTRODUCTION Smart Power Grids exemplify an emerging class of Cyber Physical-on paradigm to support operational needs. Smart Grids are an outcome of instrumentation, such as Phasor

  8. TRANSPORTATION ENERGY FORECASTS AND ANALYSES FOR THE 2009

    E-Print Network [OSTI]

    Page Manager FOSSIL FUELS OFFICE Mike Smith Deputy Director FUELS AND TRANSPORTATION DIVISION Melissa, Weights and Measurements/Gary Castro, Allan Morrison, John Mough, Ed Williams Clean Energy FuelsCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS AND ANALYSES FOR THE 2009 INTEGRATED

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

    E-Print Network [OSTI]

    Giannitrapani, Antonello

    bid is computed by exploiting the forecast energy price for the day ahead market, the historical wind renewable energy resources, such as wind and photovoltaic, has grown rapidly. It is well known the problem of optimizing energy bids for an independent Wind Power Producer (WPP) taking part

  10. Detecting and Forecasting Economic Regimes in Automated Exchanges

    E-Print Network [OSTI]

    Ketter, Wolfgang

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

  11. Detecting and Forecasting Economic Regimes in Automated Exchanges

    E-Print Network [OSTI]

    Ketter, Wolfgang

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

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

    E-Print Network [OSTI]

    energy-using devices in the average U.S. household that used over 4,700 kWh of electricity, natural gas-using devices to energy price, household income, and the cost of these devices. This analysis findsTHE DESIRE TO ACQUIRE: FORECASTING THE EVOLUTION OF HOUSEHOLD ENERGY SERVICES by Steven Groves BASc

  13. Probabilistic Quantitative Precipitation Forecasting Using Bayesian Model Averaging

    E-Print Network [OSTI]

    Washington at Seattle, University of

    February 24, 2006 1J. McLean Sloughter is Graduate Research Assistant, Adrian E. Raftery is BlumsteinProbabilistic Quantitative Precipitation Forecasting Using Bayesian Model Averaging J. McLean Sloughter, Adrian E. Raftery and Tilmann Gneiting 1 Department of Statistics, University of Washington

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

    E-Print Network [OSTI]

    Raftery, Adrian

    : J. McLean Sloughter, Department of Mathematics, Seattle University, 901 12th Ave., P.O. Box 222000Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging J. MCLEAN SLOUGHTER Seattle University, Seattle, Washington TILMANN GNEITING Heidelberg University, Heidelberg

  15. air pollution forecast: Topics by E-print Network

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

    air pollution forecast First Page Previous Page 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 1 ENVIRONMENTAL INFORMATION SYSTEM...

  16. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

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

    2011-11-29T23:59:59.000Z

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

  17. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M. M.

    2012-08-01T23:59:59.000Z

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It was presented to the 2012 Western Conference of Public Service Commissioners, during their June, 2012, meeting. The Western Conference of Public Service Commissioners is a regional association within the National Association of Regulatory Utility Commissioners (NARUC).

  18. Buying Hedge with Futures

    E-Print Network [OSTI]

    Welch, Mark; Kastens, Terry L.

    2009-01-07T23:59:59.000Z

    Agricultural Economist, Kansas State University Agricultural Experiment Station and Cooperative Extension Service. Many bulk purchasers of agricultural com- modities need price risk management tools to help stabilize input prices. Livestock feeders... anticipating future feed needs or grain export- ers making commitments to sell grain are two users of agricultural commodities who could benefit from input price management strate- gies. A common tool is a buying, or long, hedge using futures. Producers...

  19. Navy Mobility Fuels Forecasting System report: Navy fuel production in the year 2000

    SciTech Connect (OSTI)

    Hadder, G.R.; Davis, R.M.

    1991-09-01T23:59:59.000Z

    The Refinery Yield Model of the Navy Mobility Fuels Forecasting System has been used to study the feasibility and quality of Navy JP-5 jet fuel and F-76 marine diesel fuel for two scenarios in the year 2000. Both scenarios account for environmental regulations for fuels produced in the US and assume that Eastern Europe, the USSR, and the People's Republic of China have free market economies. One scenario is based on business-as-usual market conditions for the year 2000. The second scenario is similar to first except that USSR crude oil production is 24 percent lower. During lower oil production in the USSR., there are no adverse effects on Navy fuel availability, but JP-5 is generally a poorer quality fuel relative to business-as-usual in the year 2000. In comparison with 1990, there are two potential problems areas for future Navy fuel quality. The first problem is increased aromaticity of domestically produced Navy fuels. Higher percentages of aromatics could have adverse effects on storage, handling, and combustion characteristics of both JP-5 and F-76. The second, and related, problem is that highly aromatic light cycle oils are blended into F-76 at percentages which promote fuel instability. It is recommended that the Navy continue to monitor the projected trend toward increased aromaticity in JP-5 and F-76 and high percentages of light cycle oils in F-76. These potential problems should be important considerations in research and development for future Navy engines.

  20. Navy Mobility Fuels Forecasting System report: Navy fuel production in the year 2000

    SciTech Connect (OSTI)

    Hadder, G.R.; Davis, R.M.

    1991-09-01T23:59:59.000Z

    The Refinery Yield Model of the Navy Mobility Fuels Forecasting System has been used to study the feasibility and quality of Navy JP-5 jet fuel and F-76 marine diesel fuel for two scenarios in the year 2000. Both scenarios account for environmental regulations for fuels produced in the US and assume that Eastern Europe, the USSR, and the People`s Republic of China have free market economies. One scenario is based on business-as-usual market conditions for the year 2000. The second scenario is similar to first except that USSR crude oil production is 24 percent lower. During lower oil production in the USSR., there are no adverse effects on Navy fuel availability, but JP-5 is generally a poorer quality fuel relative to business-as-usual in the year 2000. In comparison with 1990, there are two potential problems areas for future Navy fuel quality. The first problem is increased aromaticity of domestically produced Navy fuels. Higher percentages of aromatics could have adverse effects on storage, handling, and combustion characteristics of both JP-5 and F-76. The second, and related, problem is that highly aromatic light cycle oils are blended into F-76 at percentages which promote fuel instability. It is recommended that the Navy continue to monitor the projected trend toward increased aromaticity in JP-5 and F-76 and high percentages of light cycle oils in F-76. These potential problems should be important considerations in research and development for future Navy engines.

  1. A comparison of water vapor quantities from model short-range forecasts and ARM observations

    SciTech Connect (OSTI)

    Hnilo, J J

    2006-03-17T23:59:59.000Z

    Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the 'Merged-sounding' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.

  2. EWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology The Anemos Wind Power Forecasting Platform Technology -

    E-Print Network [OSTI]

    Boyer, Edmond

    the fluctuating output from wind farms into power plant dispatching and energy trading, wind power predictionsEWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology 1 The Anemos Wind Power a professional, flexible platform for operating wind power prediction models, laying the main focus on state

  3. Initial Value Predictability of Intrinsic Oceanic Modes and Implications for Decadal Prediction over North America

    SciTech Connect (OSTI)

    Branstator, Grant

    2014-12-09T23:59:59.000Z

    The overall aim of our project was to quantify and characterize predictability of the climate as it pertains to decadal time scale predictions. By predictability we mean the degree to which a climate forecast can be distinguished from the climate that exists at initial forecast time, taking into consideration the growth of uncertainty that occurs as a result of the climate system being chaotic. In our project we were especially interested in predictability that arises from initializing forecasts from some specific state though we also contrast this predictability with predictability arising from forecasting the reaction of the system to external forcing – for example changes in greenhouse gas concentration. Also, we put special emphasis on the predictability of prominent intrinsic patterns of the system because they often dominate system behavior. Highlights from this work include: • Development of novel methods for estimating the predictability of climate forecast models. • Quantification of the initial value predictability limits of ocean heat content and the overturning circulation in the Atlantic as they are represented in various state of the artclimate models. These limits varied substantially from model to model but on average were about a decade with North Atlantic heat content tending to be more predictable than North Pacific heat content. • Comparison of predictability resulting from knowledge of the current state of the climate system with predictability resulting from estimates of how the climate system will react to changes in greenhouse gas concentrations. It turned out that knowledge of the initial state produces a larger impact on forecasts for the first 5 to 10 years of projections. • Estimation of tbe predictability of dominant patterns of ocean variability including well-known patterns of variability in the North Pacific and North Atlantic. For the most part these patterns were predictable for 5 to 10 years. • Determination of especially predictable patterns in the North Atlantic. The most predictable of these retain predictability substantially longer than generic patterns, with some being predictable for two decades.

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

    E-Print Network [OSTI]

    Raftery, Adrian

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

  5. Economic Value of Agricultural

    E-Print Network [OSTI]

    Economic Value of Agricultural Research Public Investment in Texas Agricultural Research Yields Significant Economic Returns #12;Texas agricultural producers and especially consumers benefit directly from public investment in agricultural research. According to a 2006 study (Huffman and Evenson), the overall

  6. Photovoltaics Value Analysis

    SciTech Connect (OSTI)

    Contreras, J.L.; Frantzis, L.; Blazewicz, S.; Pinault, D.; Sawyer, H.

    2008-02-01T23:59:59.000Z

    The goals of this report are to identify best practices in methodologies for estimating the value of distributed PV technologies, identify gaps in existing knowledge, and outline R&D opportunities.

  7. Value of Information References

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

    Morency, Christina

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

  8. Value of Information References

    SciTech Connect (OSTI)

    Morency, Christina

    2014-12-12T23:59:59.000Z

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

  9. Water for future Mars astronauts?

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

    Water for future Mars astronauts? Water for future Mars astronauts? Within its first three months on Mars, NASA's Curiosity Rover saw a surprising diversity of soils and sediments...

  10. DOE: Quantifying the Value of Hydropower in the Electric Grid

    SciTech Connect (OSTI)

    None

    2012-12-31T23:59:59.000Z

    The report summarizes research to Quantify the Value of Hydropower in the Electric Grid. This 3-year DOE study focused on defining value of hydropower assets in a changing electric grid. Methods are described for valuation and planning of pumped storage and conventional hydropower. The project team conducted plant case studies, electric system modeling, market analysis, cost data gathering, and evaluations of operating strategies and constraints. Five other reports detailing these research results are available a project website, www.epri.com/hydrogrid. With increasing deployment of wind and solar renewable generation, many owners, operators, and developers of hydropower have recognized the opportunity to provide more flexibility and ancillary services to the electric grid. To quantify value of services, this study focused on the Western Electric Coordinating Council region. A security-constrained, unit commitment and economic dispatch model was used to quantify the role of hydropower for several future energy scenarios up to 2020. This hourly production simulation considered transmission requirements to deliver energy, including future expansion plans. Both energy and ancillary service values were considered. Addressing specifically the quantification of pumped storage value, no single value stream dominated predicted plant contributions in various energy futures. Modeling confirmed that service value depends greatly on location and on competition with other available grid support resources. In this summary, ten different value streams related to hydropower are described. These fell into three categories; operational improvements, new technologies, and electricity market opportunities. Of these ten, the study was able to quantify a monetary value in six by applying both present day and future scenarios for operating the electric grid. This study confirmed that hydropower resources across the United States contribute significantly to operation of the grid in terms of energy, capacity, and ancillary services. Many potential improvements to existing hydropower plants were found to be cost-effective. Pumped storage is the most likely form of large new hydro asset expansions in the U.S. however, justifying investments in new pumped storage plants remains very challenging with current electricity market economics. Even over a wide range of possible energy futures, up to 2020, no energy future was found to bring quantifiable revenues sufficient to cover estimated costs of plant construction. Value streams not quantified in this study may provide a different cost-benefit balance and an economic tipping point for hydro. Future studies are essential in the quest to quantify the full potential value. Additional research should consider the value of services provided by advanced storage hydropower and pumped storage at smaller time steps for integration of variable renewable resources, and should include all possible value streams such as capacity value and portfolio benefits i.e.; reducing cycling on traditional generation.

  11. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-08-01T23:59:59.000Z

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It was presented at the 2012 RE AMP Annual Meeting. RE-AMP is an active network of 144 nonprofits and foundations across eight Midwestern states working on climate change and energy policy with the goal of reducing global warming pollution economy-wide 80% by 2050.

  12. Introduction to Futures Markets

    E-Print Network [OSTI]

    Mintert, James R.; Welch, Mark

    2009-01-07T23:59:59.000Z

    are some terms and definitions. Figure 1. Marking-to-Market Buyer and Seller Accounts at Exchange Clearinghouse. Buyer (Long) Date Action Price Day 1 Buy at $6.00/bu Day 2 No action (but price increases) $6.10/bu $0.10/bu gain x 5,000 bu... $500 gain from day 1 Seller (Short) Date Action Price Day 1 Sell at $6.00/bu Day 2 No action (but price increases) $6.10/bu $0.10/bu loss x 5,000 bu $500 loss from day 1 Long A buyer of a futures contract. Someone who buys a futures...

  13. Value Proposition for High Lifetime (p-type) and Thin Silicon Materials in Solar PV Applications: Preprint

    SciTech Connect (OSTI)

    Goodrich, A.; Woodhouse, M.; Hacke, P.

    2012-06-01T23:59:59.000Z

    Most silicon PV road maps forecast a continued reduction in wafer thickness, despite rapid declines in the primary incentive for doing so -- polysilicon feedstock price. Another common feature of most silicon-technology forecasts is the quest for ever-higher device performance at the lowest possible costs. The authors present data from device-performance and manufacturing- and system-installation cost models to quantitatively establish the incentives for manufacturers to pursue advanced (thin) wafer and (high efficiency) cell technologies, in an age of reduced feedstock prices. This analysis exhaustively considers the value proposition for high lifetime (p-type) silicon materials across the entire c-Si PV supply chain.

  14. Value of Information spreadsheet

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

    Trainor-Guitton, Whitney

    This spreadsheet represents the information posteriors derived from synthetic data of magnetotellurics (MT). These were used to calculate value of information of MT for geothermal exploration. Information posteriors describe how well MT was able to locate the "throat" of clay caps, which are indicative of hidden geothermal resources. This data is full explained in the peer-reviewed publication: Trainor-Guitton, W., Hoversten, G. M., Ramirez, A., Roberts, J., Júlíusson, E., Key, K., Mellors, R. (Sept-Oct. 2014) The value of spatial information for determining well placement: a geothermal example, Geophysics.

  15. Value of Information spreadsheet

    SciTech Connect (OSTI)

    Trainor-Guitton, Whitney

    2014-05-12T23:59:59.000Z

    This spreadsheet represents the information posteriors derived from synthetic data of magnetotellurics (MT). These were used to calculate value of information of MT for geothermal exploration. Information posteriors describe how well MT was able to locate the "throat" of clay caps, which are indicative of hidden geothermal resources. This data is full explained in the peer-reviewed publication: Trainor-Guitton, W., Hoversten, G. M., Ramirez, A., Roberts, J., Júlíusson, E., Key, K., Mellors, R. (Sept-Oct. 2014) The value of spatial information for determining well placement: a geothermal example, Geophysics.

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

    SciTech Connect (OSTI)

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

    1994-05-01T23:59:59.000Z

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

  17. 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.

  18. Pressure Normalization of Production Rates Improves Forecasting Results

    E-Print Network [OSTI]

    Lacayo Ortiz, Juan Manuel

    2013-08-07T23:59:59.000Z

    reservoir conditions, psi 2/cp ?wf Pseudopressure at flowing conditions, psi 2/cp ? Characteristic time parameter for SEPD model, D ?g Gas viscosity, cp ?o Oil viscosity, cp Acronyms BDF Boundary-Dominated Flow DCA Decline Curve Analysis EUR..., as the advanced analytical and numerical models depend on copious inputs, there is a high probability that different combinations of those parameters could generate equivalent and acceptable history matches, but different production forecasts and EUR...

  19. Future Fixed Target Facilities

    SciTech Connect (OSTI)

    Melnitchouk, Wolodymyr

    2009-01-01T23:59:59.000Z

    We review plans for future fixed target lepton- and hadron-scattering facilities, including the 12 GeV upgraded CEBAF accelerator at Jefferson Lab, neutrino beam facilities at Fermilab, and the antiproton PANDA facility at FAIR. We also briefly review recent theoretical developments which will aid in the interpretation of the data expected from these facilities.

  20. Quantum motor and future

    E-Print Network [OSTI]

    Evgeny G. Fateev

    2013-01-20T23:59:59.000Z

    In a popular language, the possibilities of the Casimir expulsion effect are presented, which can be the basis of quantum motors. Such motors can be in the form of a special multilayer thin film with periodic and complex nanosized structures. Quantum motors of the type of the Casimir platforms can be the base of transportation, energy and many other systems in the future.

  1. 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...

  2. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

    Yankeelov, Tom [Vanderbilt University, Nashville; Quaranta, Vito [Vanderbilt University, Nashville; Evans, Katherine J [ORNL; Rericha, Erin [Vanderbilt University, Nashville

    2015-01-01T23:59:59.000Z

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

  3. 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.

  4. A 24-h forecast of solar irradiance using artificial neural network: Application for performance prediction of a grid-connected PV plant at Trieste, Italy

    SciTech Connect (OSTI)

    Mellit, Adel [Department of Electronics, Faculty of Sciences and Technology, LAMEL, Jijel University, Ouled-aissa, P.O. Box 98, Jijel 18000 (Algeria); Pavan, Alessandro Massi [Department of Materials and Natural Resources, University of Trieste Via A. Valerio, 2 - 34127 Trieste (Italy)

    2010-05-15T23:59:59.000Z

    Forecasting of solar irradiance is in general significant for planning the operations of power plants which convert renewable energies into electricity. In particular, the possibility to predict the solar irradiance (up to 24 h or even more) can became - with reference to the Grid Connected Photovoltaic Plants (GCPV) - fundamental in making power dispatching plans and - with reference to stand alone and hybrid systems - also a useful reference for improving the control algorithms of charge controllers. In this paper, a practical method for solar irradiance forecast using artificial neural network (ANN) is presented. The proposed Multilayer Perceptron MLP-model makes it possible to forecast the solar irradiance on a base of 24 h using the present values of the mean daily solar irradiance and air temperature. An experimental database of solar irradiance and air temperature data (from July 1st 2008 to May 23rd 2009 and from November 23rd 2009 to January 24th 2010) has been used. The database has been collected in Trieste (latitude 45 40'N, longitude 13 46'E), Italy. In order to check the generalization capability of the MLP-forecaster, a K-fold cross-validation was carried out. The results indicate that the proposed model performs well, while the correlation coefficient is in the range 98-99% for sunny days and 94-96% for cloudy days. As an application, the comparison between the forecasted one and the energy produced by the GCPV plant installed on the rooftop of the municipality of Trieste shows the goodness of the proposed model. (author)

  5. Alternative future scenarios for the SPS comparative assessment

    SciTech Connect (OSTI)

    Ayres, R.U.; Ridker, R.G.; Watson, W.D. Jr.; Arnold, J.; Tayi, G.

    1980-08-01T23:59:59.000Z

    The objective of the comparative assessment is to develop an initial understanding of the SPS with respect to a limited set of energy alternatives. A comparative methodology report describes the multi-step process in the comparative assessment. The first step is the selection and characterization of alternative energy systems. Terrestrial alternatives are selected, and their cost, performance, and environmental and social attributes are specified for use in the comparison with the SPS in the post-2000 era. Data on alternative technologies were sought from previous research and from other comparisons. The object of this study is to provide a futures framework for evaluating SPS (i.e., factor prices, primary energy prices, and energy demands for the US from 1980 to 2030). The economic/energy interactions are discussed, and a number of specific modelling schemes that have been used for long-range forecasting purposes are described. This discussion provides the rationale for the choice of a specific model and methodology, which is described. Long-range cost assumptions used in the forecast are detailed, and the basis for the selection of specific scenarios follows. Results of the analysis are detailed. (WHK)

  6. Measuring Value in Healthcare

    E-Print Network [OSTI]

    Gardner, Christopher

    2008-01-01T23:59:59.000Z

    A statistical description and model of individual healthcare expenditures in the US has been developed for measuring value in healthcare. We find evidence that healthcare expenditures are quantifiable as an infusion-diffusion process, which can be thought of intuitively as a steady change in the intensity of treatment superimposed on a random process reflecting variations in the efficiency and effectiveness of treatment. The arithmetic mean represents the net average annual cost of healthcare; and when multiplied by the arithmetic standard deviation, which represents the effective risk, the result is a measure of healthcare cost control. Policymakers, providers, payors, or patients that decrease these parameters are generating value in healthcare. The model has an average absolute prediction error of approximately 10-12% across the range of expenditures which spans 6 orders of magnitude over a nearly 10-year period. For the top 1% of the population with the largest expenditures, representing 20%-30% of total ...

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

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01T23:59:59.000Z

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

  8. FUTURES with Jaime Escalante

    SciTech Connect (OSTI)

    NONE

    1996-08-01T23:59:59.000Z

    The United States Department of Energy awarded the Foundation for Advancements in Science and Education (FASE) $826,000 as support to produce the second set of FUTURES segments consisting of 12, 15-minute programs. The programs provide motivation for students to study math by connecting math to the work place and real-life problem scenarios. The programs are broadcast in 50 states through PBS Elementary and Secondary Service (E/SS). The grant term ended on December 16, 1993 and this final report documents program and financial activity results. The 12 episodes are titled: Animal Care, Meteorology, Mass Communication, Advanced Energy, Oceanography, Graphic Design, Future Habitats, Environmental Science & Technology, Fitness & Physical Performance, Interpersonal Communications, Advanced Transportation and Product Design. Each program addresses as many as ten careers or job types within the broader field named. Minority and gender-balanced role models appear throughout the programs.

  9. Future directions for QCD

    SciTech Connect (OSTI)

    Bjorken, J.D.

    1996-10-01T23:59:59.000Z

    New directions for exploring QCD at future high-energy colliders are sketched. These include jets within jets. BFKL dynamics, soft and hard diffraction, searches for disoriented chiral condensate, and doing a better job on minimum bias physics. The new experimental opportunities include electron-ion collisions at HERA, a new collider detector at the C0 region of the TeVatron, and the FELIX initiative at the LHC.

  10. Steganography: Past, Present, Future

    SciTech Connect (OSTI)

    Judge, J C

    2001-12-01T23:59:59.000Z

    Steganography (a rough Greek translation of the term Steganography is secret writing) has been used in various forms for 2500 years. It has found use in variously in military, diplomatic, personal and intellectual property applications. Briefly stated, steganography is the term applied to any number of processes that will hide a message within an object, where the hidden message will not be apparent to an observer. This paper will explore steganography from its earliest instances through potential future application.

  11. Buildings of the Future

    Broader source: Energy.gov [DOE]

    The U.S. Department of Energy (DOE) and the Pacific Northwest National Laboratory are developing a vision for future buildings—at least one hundred years from today—based on the collective views of thought leaders. As part of this effort, we will explore technology and demographic trends that could revolutionize the built environment across energy, water, environment, resilient design, health, security, and productivity.

  12. Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    2 2. Annual Energy Outlook (Administration’s Annual Energy Outlook forecasted price (of Energy, Annual Energy Outlook 2004 with Projections to

  13. 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

    Downward surface solar radiation  data released at 12 UTC forecast shortwave radiation with data obtained from the radiation:   A statistical approach using satellite data.   

  14. FAA (federal Aviation Administration) aviation forecasts - fiscal years 1983-1994

    SciTech Connect (OSTI)

    Not Available

    1983-02-01T23:59:59.000Z

    This report contains the Fiscal Years 1983-1994 Federal Aviation Administration (FAA) forecasts of aviation activity at FAA facilities. These include airports with FAA control towers, air route traffic control centers, and flight service stations. Detailed forecasts were made for the four major users of the national aviation system: air carriers, air taxi/commuters, general aviation and the military. The forecasts have been prepared to meet the budget and planning needs of the constituent units of the FAA and to provide information that can be used by state and local authorities, by the aviation industry and the general public. The overall outlook for the forecast period is for moderate economic growth, relatively stable real fuel prices, and decreasing inflation. Based upon these assumptions, aviation activity is forecast to increase by Fiscal Year 1994 by 97 percent at towered airports, 50 percent at air route traffic control centers, and 54 percent in flight services performed. Hours flown by general aviation is forecast to increase 56 percent and helicopter hours flown 80 percent. Scheduled domestic revenue passenger miles (RPM's) are forecast to increase 81 percent, with scheduled international RPM's forecast to increase by 80 percent and commuter RPM's forecast to increase by 220 percent.

  15. The Past as Prologue? Business Cycles and Forecasting since the 1960s

    E-Print Network [OSTI]

    Bardhan, Ashok Deo; Hicks, Daniel; Kroll, Cynthia A.; Yu, Tiffany

    2010-01-01T23:59:59.000Z

    a unique sampling of articles, we examine academic and mediaSample Articles Prediction Source Academic and Trade Totalshow that articles reporting on academic forecasts have

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

    E-Print Network [OSTI]

    Buxi, Gurkaran

    2012-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Liu, Chang

    2009-05-15T23:59:59.000Z

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

  18. Hanford Advisory Board Values

    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 Science (SC) EnvironmentalGyroSolé(tm) Harmonic EngineHIV andApril 8-9, Advisory BoardPageValues

  19. The Value of Information in Inventory Management

    E-Print Network [OSTI]

    2008-04-08T23:59:59.000Z

    (high, low or moderate) of the product and knows range forecasts for the demand in each ... of the market response at such an early stage of the product lifecycle.

  20. Bioenergy: America's Energy Future

    ScienceCinema (OSTI)

    Nelson, Bruce; Volz, Sara; Male, Johnathan; Wolfson, Johnathan; Pray, Todd; Mayfield, Stephen; Atherton, Scott; Weaver, Brandon

    2014-08-12T23:59:59.000Z

    Bioenergy: America's Energy Future is a short documentary film showcasing examples of bioenergy innovations across the biomass supply chain and the United States. The film highlights a few stories of individuals and companies who are passionate about achieving the promise of biofuels and addressing the challenges of developing a thriving bioeconomy. This outreach product supports media initiatives to expand the public's understanding of the bioenergy industry and sustainable transportation and was developed by the U.S. Department of Energy Bioenergy Technologies Office (BETO), Oak Ridge National Laboratory, Green Focus Films, and BCS, Incorporated.

  1. Bioenergy: America's Energy Future

    SciTech Connect (OSTI)

    Nelson, Bruce; Volz, Sara; Male, Johnathan; Wolfson, Johnathan; Pray, Todd; Mayfield, Stephen; Atherton, Scott; Weaver, Brandon

    2014-07-31T23:59:59.000Z

    Bioenergy: America's Energy Future is a short documentary film showcasing examples of bioenergy innovations across the biomass supply chain and the United States. The film highlights a few stories of individuals and companies who are passionate about achieving the promise of biofuels and addressing the challenges of developing a thriving bioeconomy. This outreach product supports media initiatives to expand the public's understanding of the bioenergy industry and sustainable transportation and was developed by the U.S. Department of Energy Bioenergy Technologies Office (BETO), Oak Ridge National Laboratory, Green Focus Films, and BCS, Incorporated.

  2. ARM - Future Trends

    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 1,006Datastreamstwrcam40m DocumentationJanuary 9, 2009 [Events, Feature StoriesgovCampaignsSurfacegovFrontFuture

  3. Future Mobility in Maryland

    National Nuclear Security Administration (NNSA)

    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 742EnergyOn AprilA Approved:AdministrationAnalysisDarby/%2AO 474.2Y-12 Press98918,FUTURE

  4. Future City Competition

    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 Science (SC) Environmental AssessmentsGeoffrey Campbell is theOpportunities HighFusionFusionFuture

  5. Milk Futures, Options and Basis

    E-Print Network [OSTI]

    Haigh, Michael; Stockton, Matthew; Anderson, David P.; Schwart Jr., Robert B.

    2001-10-12T23:59:59.000Z

    The milk futures and options market enables producers and processors to manage price risk. This publication explains hedging, margin accounts, basis and how to track it, and other fundamentals of the futures and options market....

  6. Core Values | Department of Energy

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

    Core Values Core Values People - People are our most important resource. We respect and use our experience and skills and appreciate our diversity. Business Excellence - We are...

  7. ARM - Value-Added Products (VAP)

    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 Office511041cloth DocumentationProducts (VAP) VAP Update Information on new, existing, and future value-added

  8. The research programme Future Agriculture

    E-Print Network [OSTI]

    The research programme Future Agriculture ­ livestock, crops and land use Welcome to a lunch.slu.se/futureagriculture For questions, please contact KatarinaVrede (katarina.vrede@slu.se) About Future Agriculture ­ livestock, crops and land use The changes and challenges facing agriculture in the future will be substantial, not only

  9. Transportation Energy Futures Series: Potential for Energy Efficiency Improvement Beyond the Light-Duty-Vehicle Sector

    SciTech Connect (OSTI)

    Vyas, A. D.; Patel, D. M.; Bertram, K. M.

    2013-03-01T23:59:59.000Z

    Considerable research has focused on energy efficiency and fuel substitution options for light-duty vehicles, while much less attention has been given to medium- and heavy-duty trucks, buses, aircraft, marine vessels, trains, pipeline, and off-road equipment. This report brings together the salient findings from an extensive review of literature on future energy efficiency options for these non-light-duty modes. Projected activity increases to 2050 are combined with forecasts of overall fuel efficiency improvement potential to estimate the future total petroleum and greenhouse gas (GHG) emissions relative to current levels. This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency project initiated to pinpoint underexplored strategies for abating GHGs and reducing petroleum dependence related to transportation.

  10. Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results

    E-Print Network [OSTI]

    Koomey, Jonathan G.

    2010-01-01T23:59:59.000Z

    End-Use Forecasting with EPRI-REEPS 2.1. Lawrence BerkeleyEnd-Use Forecasting with EPRI-REEPS 2.1. Lawrence BerkeleyPower Research Institute. EPRI Research Project Meier, Alan

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

    E-Print Network [OSTI]

    Modlin, Norman Ray

    1993-01-01T23:59:59.000Z

    are found to have the majority of RMS growth on day I while poor forecasts do not experience rapid error growth until days 3 and 4. For poor forecasts, the leading EOFs reveal a wave pattern down stream of the Rocky Mountains. This pattern evolves...

  12. Extendedrange seasonal hurricane forecasts for the North Atlantic with a hybrid dynamicalstatistical model

    E-Print Network [OSTI]

    Webster, Peter J.

    Extendedrange seasonal hurricane forecasts for the North Atlantic with a hybrid 20 September 2010; published 9 November 2010. [1] A hybrid forecast model for seasonal hurricane between the number of seasonal hurricane and the large scale variables from ECMWF hindcasts. The increase

  13. Using meteorological data to forecast seasonal runoff on the River Jhelum, Pakistan

    E-Print Network [OSTI]

    Fowler, Hayley

    Using meteorological data to forecast seasonal runoff on the River Jhelum, Pakistan D.R. Archer a of Pakistan. Seasonal forecasts of spring and summer flow provide the opportunity for planning and would of Control between In- dia and Pakistan. The Jhelum then flows through the plains of the Punjab, where

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

    E-Print Network [OSTI]

    Genton, Marc G.

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

  15. he long-term economic forecast calls for the continuation of the

    E-Print Network [OSTI]

    Hemmers, Oliver

    T he long-term economic forecast calls for the continuation of the economic recovery in 2014 predicts a steady economic recovery for Southern Nevada from 2014 onward. The Las Vegas economy-Term Economic Forecast Figure 1: Total Employment (1990-2050) Source: Center for Business and Economic Research

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

    E-Print Network [OSTI]

    Illinois at Chicago, University of

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

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

    E-Print Network [OSTI]

    Boyer, Edmond

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

  18. Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering P : 10.1016/j.jweia.2008.03.013 #12;2 Abstract This paper studies the application of Kalman filtering forecasts. The application of Kalman filter to these data leads to the elimination of any possible

  19. Forecasting change of the magnetic field using core surface flows and ensemble Kalman filtering

    E-Print Network [OSTI]

    Forecasting change of the magnetic field using core surface flows and ensemble Kalman filtering C-based observatories. We therefore present a method using Ensemble Kalman Filtering (EnKF) to produce an optimal (2009), Forecasting change of the magnetic field using core surface flows and ensemble Kalman filtering

  20. Model bias correction for dust storm forecast using ensemble Kalman filter

    E-Print Network [OSTI]

    Model bias correction for dust storm forecast using ensemble Kalman filter Caiyan Lin,1,2 Jiang Zhu Kalman filter (EnKF) assimilation targeting heavy dust episodes during the period of 15­24 March 2002. Wang (2008), Model bias correction for dust storm forecast using ensemble Kalman filter, J. Geophys