National Library of Energy BETA

Sample records for forecast comparisons energy

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

    E-Print Network [OSTI]

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

    2000-01-01

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

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

    Broader source: Energy.gov [DOE]

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

  3. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

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

  4. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LISTStar2-0057-EA Jump to:ofEnia SpAFlex Fuels Energy JumpVyncke Jump to:Forecast

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

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

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

    SciTech Connect (OSTI)

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

    2012-07-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

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

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

    E-Print Network [OSTI]

    Mallet, Vivien

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

  16. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

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

  17. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

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

  18. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

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

  19. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

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

  20. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

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

  1. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

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

  2. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2005-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2008-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

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

  9. 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

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

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

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

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

    E-Print Network [OSTI]

    Hsieh, William

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

  12. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Heinemann, Detlev

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  15. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

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

  16. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center

    E-Print Network [OSTI]

    Washington at Seattle, University of

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

  17. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

    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.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

    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.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

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

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

    E-Print Network [OSTI]

    Hwang, Kai

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

  2. PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022

    E-Print Network [OSTI]

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

  3. Solar Energy Market Forecast | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS ReportEurope GmbH JumpSlough HeatMccoyProject-Energy

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

    SciTech Connect (OSTI)

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

    2005-02-09

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

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

    Reports and Publications (EIA)

    2010-01-01

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

  6. 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

  7. 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

  8. 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

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

    E-Print Network [OSTI]

    MacDonald, Mark

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28

    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.

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

    SciTech Connect (OSTI)

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

    2008-01-07

    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.

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

    E-Print Network [OSTI]

    Kolter, J. Zico

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

  14. Implementation of a Corporate Energy Accounting and Forecasting Model 

    E-Print Network [OSTI]

    Kympton, H. W.; Bowman, B. M.

    1981-01-01

    pieces of equipment which are used as energy performance 'yardsticks'. Monthly reports permit equitable comparisons of plant energy consumption and isolation of those plants with the lowest efficiencies. The financial impact of increasing energy...

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

    SciTech Connect (OSTI)

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

    2009-03-01

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

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

    SciTech Connect (OSTI)

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

    2011-03-28

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

  17. Wind Forecasting Improvement Project | Department of Energy

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LIST OFAMERICA'S FUTURE. regulatorsEnergyDepartmentEnergyWideWind

  18. 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

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

    E-Print Network [OSTI]

    Hwang, Kai

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

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

    E-Print Network [OSTI]

    Islam, M. Saif

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

  1. Fitting and forecasting non-linear coupled dark energy

    E-Print Network [OSTI]

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

    2015-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2004-01-01

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

  3. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark A.

    2010-01-01

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

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

    E-Print Network [OSTI]

    Bolinger, Mark

    2009-01-01

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

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  8. On-line economic optimization of energy systems using weather forecast information.

    SciTech Connect (OSTI)

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

    2009-01-01

    We establish an on-line optimization framework to exploit weather forecast information in the operation of energy systems. We argue that anticipating the weather conditions can lead to more proactive and cost-effective operations. The framework is based on the solution of a stochastic dynamic real-time optimization (D-RTO) problem incorporating forecasts generated from a state-of-the-art weather prediction model. The necessary uncertainty information is extracted from the weather model using an ensemble approach. The accuracy of the forecast trends and uncertainty bounds are validated using real meteorological data. We present a numerical simulation study in a building system to demonstrate the developments.

  9. Comparison of Various Deterministic Forecasting Techniques in Shale Gas Reservoirs with Emphasis on the Duong Method 

    E-Print Network [OSTI]

    Joshi, Krunal Jaykant

    2012-10-19

    There is a huge demand in the industry to forecast production in shale gas reservoirs accurately. There are many methods including volumetric, Decline Curve Analysis (DCA), analytical simulation and numerical simulation. Each one of these methods...

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

    SciTech Connect (OSTI)

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

    2015-01-01

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

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

    SciTech Connect (OSTI)

    Stoffel, T.

    2012-06-01

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

  12. European Wind Energy Conference -Brussels, Belgium, April 2008 Data mining for wind power forecasting

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    European Wind Energy Conference - Brussels, Belgium, April 2008 Data mining for wind power-term forecasting of wind energy produc- tion up to 2-3 days ahead is recognized as a major contribution the improvement of predic- tion systems performance is recognised as one of the priorities in wind energy research

  13. NREL: Energy Analysis - Energy Forecasting and Modeling Staff

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on771/6/14 Contact:NewsWebmasterWorkingElla Zhou Photo of EllaEnergy

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

    SciTech Connect (OSTI)

    Finley, Cathy

    2014-04-30

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

  15. MPC for Wind Power Gradients --Utilizing Forecasts, Rotor Inertia, and Central Energy Storage

    E-Print Network [OSTI]

    MPC for Wind Power Gradients -- Utilizing Forecasts, Rotor Inertia, and Central Energy Storage the control of a wind power plant, possibly consisting of many individual wind turbines. The goal. INTRODUCTION Today, wind power is the most important renewable energy source. For the years to come, many

  16. Bet and Energy -From Load Forecasting to Demand Response in a Web of Things

    E-Print Network [OSTI]

    Beigl, Michael

    Bet and Energy - From Load Forecasting to Demand Response in a Web of Things Yong Ding TECO (DSM) [7, 19]. Within DSM, mainly two principal activities i.e. load shifting (demand response programs) and load reduction (energy efficiency and conser- vation programs) can be realized [4]. 1.1 Demand Response

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

    E-Print Network [OSTI]

    Bolinger, Mark; Wiser, Ryan

    2006-01-01

    typical of an advanced combined cycle gas turbine), the $comparison between a combined cycle gas turbine and a fixed-

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

    SciTech Connect (OSTI)

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

    2005-10-31

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

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

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

  20. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

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

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

    SciTech Connect (OSTI)

    none,

    2014-08-29

    With declining production costs and increasing technical capabilities, LED adoption has recently gained momentum in general illumination applications. This is a positive development for our energy infrastructure, as LEDs use significantly less electricity per lumen produced than many traditional lighting technologies. The U.S. Department of Energy’s Energy Savings Forecast of Solid-State Lighting in General Illumination Applications examines the expected market penetration and resulting energy savings of light-emitting diode, or LED, lamps and luminaires from today through 2030.

  2. Energy: a historical perspective and 21st century forecast

    SciTech Connect (OSTI)

    Salvador, Amos [University of Texas, Austin, TX (United States)

    2005-07-01

    Contents are: Preface; Chapter 1: introduction, brief history, and chosen approach; Chapter 2: human population and energy consumption: the future; Chapter 4: sources of energy (including a section on coal); Chapter 5: electricity: generation and consumption; and Chapter 6: energy consumption and probable energy sources during the 21st century.

  3. Short-Term Energy Carbon Dioxide Emissions Forecasts August 2009

    Reports and Publications (EIA)

    2009-01-01

    Supplement to the Short-Term Energy Outlook. Short-term projections for U.S. carbon dioxide emissions of the three fossil fuels: coal, natural gas, and petroleum.

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

    E-Print Network [OSTI]

    Bouallegue, Zied Ben

    2015-01-01

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

  5. Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) | Open

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTIONRobertsdale, AlabamaETEC GmbH JumpEllenville, NewLtd EILEnergy Datadata TypeEnergyFocus IncEnergy

  6. Energy Department Forecasts Geothermal Achievements in 2015 | Department of

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataEnergyInformation Form EmployeeAvailableExplores Deep Direct Use

  7. New Forecasting Tools Enhance Wind Energy Integration In Idaho and Oregon

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i nAand DOEDepartment ofProgramImportsEnergyForecasting Tools Enhance Wind

  8. DOE Announces Webinars on Real Time Energy Management, Solar Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative FuelsofProgram:Y-12Power,5Energyof| DepartmentCell ElectricHurricane

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-Inspired Solar FuelTechnologyTel:FebruaryEIA's Today In Energy stories at

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergy A plug-in electricLaboratory | Department ofPotawatomi Community |Barrels3 study

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

    SciTech Connect (OSTI)

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

    2014-04-30

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

  12. Energy consumption and expenditure projections by population group on the basis of the annual energy outlook 1999 forecast

    SciTech Connect (OSTI)

    Poyer, D.A.; Balsley, J.H.

    2000-01-07

    This report presents an analysis of the relative impact of the base-case scenario used in Annual Energy Outlook 1999 on different population groups. Projections of energy consumption and expenditures, as well as energy expenditure as a share of income, from 1996 to 2020 are given. The projected consumption of electricty, natural gas, distillate fuel, and liquefied petroleum gas during this period is also reported for each population group. In addition, this report compares the findings of the Annual Energy Outlook 1999 report with the 1998 report. Changes in certain indicators and information affect energy use forecasts, and these effects are analyzed and discussed.

  13. Short-term energy outlook, annual supplement 1994

    SciTech Connect (OSTI)

    Not Available

    1994-08-01

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

  14. Short-term energy outlook annual supplement, 1993

    SciTech Connect (OSTI)

    1993-08-06

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

  15. Hawaii Energy Strategy: Program guide. [Contains special sections on analytical energy forecasting, renewable energy resource assessment, demand-side energy management, energy vulnerability assessment, and energy strategy integration

    SciTech Connect (OSTI)

    Not Available

    1992-09-01

    The Hawaii Energy Strategy program, or HES, is a set of seven projects which will produce an integrated energy strategy for the State of Hawaii. It will include a comprehensive energy vulnerability assessment with recommended courses of action to decrease Hawaii's energy vulnerability and to better prepare for an effective response to any energy emergency or supply disruption. The seven projects are designed to increase understanding of Hawaii's energy situation and to produce recommendations to achieve the State energy objectives of: Dependable, efficient, and economical state-wide energy systems capable of supporting the needs of the people, and increased energy self-sufficiency. The seven projects under the Hawaii Energy Strategy program include: Project 1: Develop Analytical Energy Forecasting Model for the State of Hawaii. Project 2: Fossil Energy Review and Analysis. Project 3: Renewable Energy Resource Assessment and Development Program. Project 4: Demand-Side Management Program. Project 5: Transportation Energy Strategy. Project 6: Energy Vulnerability Assessment Report and Contingency Planning. Project 7: Energy Strategy Integration and Evaluation System.

  16. Crude oil and alternate energy production forecasts for the twenty-first century: The end of the hydrocarbon era

    SciTech Connect (OSTI)

    Edwards, J.D.

    1997-08-01

    Predictions of production rates and ultimate recovery of crude oil are needed for intelligent planning and timely action to ensure the continuous flow of energy required by the world`s increasing population and expanding economies. Crude oil will be able to supply increasing demand until peak world production is reached. The energy gap caused by declining conventional oil production must then be filled by expanding production of coal, heavy oil and oil shales, nuclear and hydroelectric power, and renewable energy sources (solar, wind, and geothermal). Declining oil production forecasts are based on current estimated ultimate recoverable conventional crude oil resources of 329 billion barrels for the United States and close to 3 trillion barrels for the world. Peak world crude oil production is forecast to occur in 2020 at 90 million barrels per day. Conventional crude oil production in the United States is forecast to terminate by about 2090, and world production will be close to exhaustion by 2100.

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

    E-Print Network [OSTI]

    Cañizares, Claudio A.

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

  18. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Rutledge, Steven

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

  19. Comparison of Building Energy Modeling Programs: Building Loads

    E-Print Network [OSTI]

    LBNL-6034E Comparison of Building Energy Modeling Programs: Building Loads Dandan Zhu1 , Tianzhen Energy, the U.S.-China Clean Energy Research Center for Building Energy Efficiency, of the U;Comparison of Building Energy Modeling Programs: Building Loads A joint effort between Lawrence Berkeley

  20. FORECASTS ON THE DARK ENERGY AND PRIMORDIAL NON-GAUSSIANITY OBSERVATIONS WITH THE TIANLAI CYLINDER ARRAY

    SciTech Connect (OSTI)

    Xu, Yidong; Chen, Xuelei [National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China); Wang, Xin [Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218 (United States)

    2015-01-01

    The Tianlai experiment is dedicated to the observation of large-scale structures (LSS) by the 21 cm intensity mapping technique. In this paper, we make forecasts concerning its ability to observe or constrain the dark energy parameters and the primordial non-Gaussianity. From the LSS data, one can use the baryon acoustic oscillation (BAO) and growth rate derived from the redshift space distortion (RSD) to measure the dark energy density and equation of state. The primordial non-Gaussianity can be constrained either by looking for scale-dependent bias in the power spectrum, or by using the bispectrum. Here, we consider three cases: the Tianlai cylinder array pathfinder that is currently being built, an upgrade of the Pathfinder Array with more receiver units, and the full-scale Tianlai cylinder array. Using the full-scale Tianlai experiment, we expect ?{sub w{sub 0}}?0.082 and ?{sub w{sub a}}?0.21 from the BAO and RSD measurements, ?{sub f{sub N{sub L}{sup local}}}?14 from the power spectrum measurements with scale-dependent bias, and ?{sub f{sub N{sub L}{sup local}}}?22 and ?{sub f{sub N{sub L}{sup equil}}}?157 from the bispectrum measurements.

  1. Downscaling Extended Weather Forecasts for Hydrologic Prediction

    SciTech Connect (OSTI)

    Leung, Lai-Yung R.; Qian, Yun

    2005-03-01

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

  2. Testing Competing High-Resolution Precipitation Forecasts

    E-Print Network [OSTI]

    Gilleland, Eric

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

  3. 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...

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

    SciTech Connect (OSTI)

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

    2010-01-01

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

  5. Solar Forecasting

    Broader source: Energy.gov [DOE]

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

  6. Bidding wind energy exploiting wind speed forecasts Antonio Giannitrapani, Simone Paoletti,

    E-Print Network [OSTI]

    Garulli, Andrea

    -ahead generation profile for a wind power producer by exploiting wind speed forecasts provided by a meteorological service. In the con- sidered framework, the wind power producer is called to take part integration in the grid is causing serious problems to transmission and distribution system operators [2]. One

  7. Global Potential of Energy Efficiency Standards and Labeling Programs

    E-Print Network [OSTI]

    McNeil, Michael A

    2008-01-01

    together the forecasts of energy demand with unit savingsDemand Forecast . 73 Potential EnergyDemand Forecast A forecast of delivered energy demand is an

  8. Modeling and Forecasting Electric Daily Peak Loads

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

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

  9. Energy Forecast, ForskEL (Smart Grid Project) | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTIONRobertsdale, AlabamaETEC GmbH JumpEllenville, NewLtd EILEnergy Datadata TypeEnergyFocus Inc

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

    E-Print Network [OSTI]

    Burger, Eric M.; Moura, Scott J.

    2015-01-01

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

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

    SciTech Connect (OSTI)

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

    2013-01-01

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

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

    Energy Savers [EERE]

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

  13. Department of Energy award DE-SC0004164 Climate and National Security: Securing Better Forecasts

    SciTech Connect (OSTI)

    Reno Harnish

    2011-08-16

    The Climate and National Security: Securing Better Forecasts symposium was attended by senior policy makers and distinguished scientists. The juxtaposition of these communities was creative and fruitful. They acknowledged they were speaking past each other. Scientists were urged to tell policy makers about even improbable outcomes while articulating clearly the uncertainties around the outcomes. As one policy maker put it, we are accustomed to making these types of decisions. These points were captured clearly in an article that appeared on the New York Times website and can be found with other conference materials most easily on our website, www.scripps.ucsd.edu/cens/. The symposium, generously supported by the NOAA/JIMO, benefitted the public by promoting scientifically informed decision making and by the transmission of objective information regarding climate change and national security.

  14. California Baseline Energy Demands to 2050 for Advanced Energy Pathways

    E-Print Network [OSTI]

    McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

    2008-01-01

    CEC (2005b) Energy demand forecast methods report.growth in California energy demands forecast in the baseline2006-2016: Staff energy demand forecast (Revised September

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

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred [ORNL

    2008-01-01

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

  16. The Role of Multimodel Climate Forecasts in Improving Water and Energy Management over the Tana River Basin, Kenya

    E-Print Network [OSTI]

    Arumugam, Sankar

    - logical ensembles are used in a reservoir model to allocate water for power generation by ensuring clima. Retrospective reservoir analysis shows that inflow forecasts developed from single GCM and multiple GCMs perform the single- model inflow forecasts by reducing uncertainty and the overconfidence of individual model

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

    E-Print Network [OSTI]

    Heinemann, Detlev

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

  18. Automated Comparison of Building Energy Simulation Engines (Presentation)

    SciTech Connect (OSTI)

    Polly, B.; Horowitz, S.; Booten, B.; Kruis, N.; Christensen, C.

    2012-08-01

    This presentation describes the BEopt comparative test suite, which is a tool that facilitates the automated comparison of building energy simulation engines. It also demonstrates how the test suite is improving the accuracy of building energy simulation programs. Building energy simulation programs inform energy efficient design for new homes and energy efficient upgrades for existing homes. Stakeholders rely on accurate predictions from simulation programs. Previous research indicates that software tends to over-predict energy usage for poorly-insulated leaky homes. NREL is identifying, investigating, and resolving software inaccuracy issues. Comparative software testing is one method of many that NREL uses to identify potential software issues.

  19. Comparison of energy efficiency between variable refrigerant flow systems and ground source heat pump systems

    E-Print Network [OSTI]

    Hong, Tainzhen

    2010-01-01

    Comparison of energy efficiency between variable refrigeranttheir superior energy efficiency. The variable refrigerantfew studies reporting the energy efficiency of VRF systems

  20. ENERGY & ENVIRONMENT DIVISION. ANNUAL REPORT FY 1980

    E-Print Network [OSTI]

    Authors, Various

    2010-01-01

    The results of the energy demand forecasts are presented inthe "low-growth" energy-demand forecasts that have recentlyprovide detailed forecasts of energy demand for the state's

  1. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

    McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

    2008-01-01

    2006-2016: Staff energy demand forecast (Revised SeptemberCEC (2005b) Energy demand forecast methods report.California energy demand 2003-2013 forecast. California

  2. A Comparison of Methods for Sizing Energy Storage Devices in Renewable Energy Systems Thomas Bailey

    E-Print Network [OSTI]

    Victoria, University of

    A Comparison of Methods for Sizing Energy Storage Devices in Renewable Energy Systems by Thomas of Methods for Sizing Energy Storage Devices in Renewable Energy Systems by Thomas Bailey B.Eng, University, storage technologies are proposed as a means to increase the penetration of renewable energy, to minimize

  3. Text-Alternative Version LED Lighting Forecast

    Broader source: Energy.gov [DOE]

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

  4. Comparison of Life Cycle Emissions and Energy Consumption for

    E-Print Network [OSTI]

    Clarens, Andres

    Comparison of Life Cycle Emissions and Energy Consumption for Environmentally Adapted Metalworking of environmentally adapted lubricants have been proposed in response to the environmental and health impacts/or deliver minimum quantities of lubricant in gas rather than water, with the former strategy being more

  5. Forecasting and Capturing Emission Reductions Using Industrial Energy Management and Reporting Systems 

    E-Print Network [OSTI]

    Robinson, J.

    2010-01-01

    The Mandatory 2010 Green House Gas (GHG) Reporting Regulations and pending climate change legislation has increased interest in Energy Management and Reporting Systems (EMRS) as a means of both reducing and reporting GHG emissions. This paper...

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

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on DeliciousMathematics And StatisticsProgramof-SA-02:Innovative Energy Apps BuiltSavers: Fireplaces EnergyApplications |

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

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

  8. Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards "Top-Runner Approach"

    E-Print Network [OSTI]

    Komiyama, Ryoichi

    2008-01-01

    developed a residential energy demand forecast for 2030, theIn order to forecast energy service demand based on energy

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

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n cEnergy (AZ,LocalEfficiency |<Technologies |CleanGeothermal

  10. Quantitative Comparison of Measured Plasma Sheet Electron Energy Flux and Remotely Sensed Auroral Electron Energy Flux

    E-Print Network [OSTI]

    Fillingim, Matthew

    Electron Energy Flux M. O. Fillingim1, (matt@ess.washington.edu), G. K. Parks2, D. Chua1, G. A. Germany3, R intensity ~ precipitating electron energy flux Peak energy flux "near" WIND fQuantitative Comparison of Measured Plasma Sheet Electron Energy Flux and Remotely Sensed Auroral

  11. Up and down: energy and cost comparison

    SciTech Connect (OSTI)

    Shapira, H.B.; Brite, S.E.; Yost, M.B.

    1981-01-01

    A study comparing cost and energy performance of equal aboveground and earth-sheltered homes is being conducted at the Oak Ridge National Laboratory. Five cities were selected to represent five regions of the US. A module of a basic 138 m/sup 2/ (1480-sq-ft) living unit was designed to adapt to both conventional, well-insulated housing and earth-sheltered (ES) housing. The homes were designed to represent the popular home on the market in the particular neighborhood. The designs vary to conform with regional requirements for heating and cooling loads as well as style, construction materials, finish, etc. Finished sets of detailed drawings were prepared for all the sites.

  12. Beyond "Partly Sunny": A Better Solar Forecast | Department of Energy

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirley Ann JacksonDepartment of EnergyResearchers atDayWhenBethany Sparn, M.S.Logo.jpg ThisworkingThe

  13. Methodologies for Estimating Building Energy Savings Uncertainty: Review and Comparison 

    E-Print Network [OSTI]

    Baltazar, J.C.; Sun, Y.; Claridge, D.

    2014-01-01

    CONFERENCE FOR ENHANCED BUILDING OPERATIONS TSINGHUA UNIVERSITY – BEIJING, CHINA –SEPTEMBER 14 -17, 2014 Methodologies for Estimating Building Energy Savings Uncertainty: Review and Comparison Juan-Carlos Baltazar PhD, PE, Yifu Sun EIT, and David Claridge... PhD, P.E. International Conference for Enhanced Building Operations Tsinghua University – Beijing, China –September 14 -17, 2014 ESL-IC-14-09-11a Proceedings of the 14th International Conference for Enhanced Building Operations, Beijing, China...

  14. 1993 Solid Waste Reference Forecast Summary

    SciTech Connect (OSTI)

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

    1993-08-01

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

  15. 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

  16. Wind Speed Forecasting for Power System Operation 

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22

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

  17. Energy consumption and expenditure projections by income quintile on the basis of the Annual Energy Outlook 1997 forecast

    SciTech Connect (OSTI)

    Poyer, D.A.; Allison, T.

    1998-03-01

    This report presents an analysis of the relative impacts of the base-case scenario used in the Annual Energy Outlook 1997, published by the US Department of Energy, Energy Information Administration, on income quintile groups. Projected energy consumption and expenditures, and projected energy expenditures as a share of income, for the period 1993 to 2015 are reported. Projected consumption of electricity, natural gas, distillate fuel, and liquefied petroleum gas over this period is also reported for each income group. 33 figs., 11 tabs.

  18. Distributed Energy Resource Optimization Using a Software as Service (SaaS) Approach at the University of California, Davis Campus

    E-Print Network [OSTI]

    Michael, Stadler

    2011-01-01

    18 Energy Demand Forecast for Week-Aheadon the PI system. Energy Demand Forecast for Week-AheadOnly load Figure 18 Forecast Energy Demand and Energy Demand

  19. ENERGY AND ENVIRONMENT DIVISION ANNUAL REPORT 1978

    E-Print Network [OSTI]

    Cairns, E.L.

    2011-01-01

    be incorporated in future energy demand forecasts and supplyshows two sets of energy demand forecasts for residential

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

    E-Print Network [OSTI]

    Kurapov, Alexander

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

  1. ENERGY ANALYSIS PROGRAM. CHAPTER FROM THE ENERGY AND ENVIRONMENT DIVISION ANNUAL REPORT 1978

    E-Print Network [OSTI]

    Various, Various,

    2011-01-01

    be incorporated in future energy demand forecasts and supplyshows two sets of energy demand forecasts for residential

  2. Comparison of Software Models for Energy Savings from Cool Roofs

    SciTech Connect (OSTI)

    New, Joshua Ryan; Miller, William A; Huang, Yu; Levinson, Ronnen

    2014-01-01

    A web-based Roof Savings Calculator (RSC) has been deployed for the United States Department of Energy as an industry-consensus tool to help building owners, manufacturers, distributors, contractors and researchers easily run complex roof and attic simulations. This tool employs modern web technologies, usability design, and national average defaults as an interface to annual simulations of hour-by-hour, whole-building performance using the world-class simulation tools DOE-2.1E and AtticSim in order to provide estimated annual energy and cost savings. In addition to cool reflective roofs, RSC simulates multiple roof and attic configurations including different roof slopes, above sheathing ventilation, radiant barriers, low-emittance roof surfaces, duct location, duct leakage rates, multiple substrate types, and insulation levels. A base case and energy-efficient alternative can be compared side-by-side to estimate monthly energy. RSC was benchmarked against field data from demonstration homes in Ft. Irwin, California; while cooling savings were similar, heating penalty varied significantly across different simulation engines. RSC results reduce cool roofing cost-effectiveness thus mitigating expected economic incentives for this countermeasure to the urban heat island effect. This paper consolidates comparison of RSC s projected energy savings to other simulation engines including DOE-2.1E, AtticSim, Micropas, and EnergyPlus, and presents preliminary analyses. RSC s algorithms for capturing radiant heat transfer and duct interaction in the attic assembly are considered major contributing factors to increased cooling savings and heating penalties. Comparison to previous simulation-based studies, analysis on the force multiplier of RSC cooling savings and heating penalties, the role of radiative heat exchange in an attic assembly, and changes made for increased accuracy of the duct model are included.

  3. Enduse Global Emissions Mitigation Scenarios (EGEMS): A New Generation of Energy Efficiency Policy Planning Models

    E-Print Network [OSTI]

    McNeil, Michael A.

    2010-01-01

    driver for the energy demand forecast. The basic assumptionglobal bottom-up energy demand forecasts, and a frameworkin modelling energy demand is to forecast activity. Activity

  4. Property:Data Comparison to Computational Models | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo, Maryland:NPIProtectio1975)EnergyFloorAreaOfficesCollaborators JumpData Comparison to

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

    E-Print Network [OSTI]

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

  6. Wind Power Forecasting Data

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

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

  7. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

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

  8. Forecasting Water Quality & Biodiversity

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

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

  9. Energy-Efficiency Comparison of Mobile Platforms and Applications: A Quantitative Approach

    E-Print Network [OSTI]

    Shi, Weisong

    Energy-Efficiency Comparison of Mobile Platforms and Applications: A Quantitative Approach Grace comparing mobile platforms and apps for energy efficiency. In addition, based on case studies that focus on energy efficiency comparison of different app cat- egories on the most popular platforms, the paper

  10. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    1996-08-01

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

  11. Forecasting Hot Water Consumption in Residential Houses

    E-Print Network [OSTI]

    MacDonald, Mark

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

  12. GOES Aviation Products Aviation Weather Forecasting

    E-Print Network [OSTI]

    Kuligowski, Bob

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

  13. Fuel Price Forecasts INTRODUCTION

    E-Print Network [OSTI]

    Fuel Price Forecasts INTRODUCTION Fuel prices affect electricity planning in two primary ways and water heating, and other end-uses as well. Fuel prices also influence electricity supply and price turbines. This second effect is the primary use of the fuel price forecast for the Council's Fifth Power

  14. Weather Forecasting Spring 2014

    E-Print Network [OSTI]

    Hennon, Christopher C.

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

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

    E-Print Network [OSTI]

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

  16. ENERGY INVESTMENTS UNDER CLIMATE POLICY: A COMPARISON OF GLOBAL MODELS

    SciTech Connect (OSTI)

    McCollum, David; Nagai, Yu; Riahi, Keywan; Marangoni, Giacomo; Calvin, Katherine V.; Pietzcker, Robert; Van Vliet, Jasper; van der Zwaan, Bob

    2013-11-01

    The levels of investment needed to mobilize an energy system transformation and mitigate climate change are not known with certainty. This paper aims to inform the ongoing dialogue and in so doing to guide public policy and strategic corporate decision making. Within the framework of the LIMITS integrated assessment model comparison exercise, we analyze a multi-IAM ensemble of long-term energy and greenhouse gas emissions scenarios. Our study provides insight into several critical but uncertain areas related to the future investment environment, for example in terms of where capital expenditures may need to flow regionally, into which sectors they might be concentrated, and what policies could be helpful in spurring these financial resources. We find that stringent climate policies consistent with a 2°C climate change target would require a considerable upscaling of investments into low-carbon energy and energy efficiency, reaching approximately $45 trillion (range: $30–$75 trillion) cumulative between 2010 and 2050, or about $1.1 trillion annually. This represents an increase of some $30 trillion ($10–$55 trillion), or $0.8 trillion per year, beyond what investments might otherwise be in a reference scenario that assumes the continuation of present and planned emissions-reducing policies throughout the world. In other words, a substantial "clean-energy investment gap" of some $800 billion/yr exists — notably on the same order of magnitude as present-day subsidies for fossil energy and electricity worldwide ($523 billion). Unless the gap is filled rather quickly, the 2°C target could potentially become out of reach.

  17. Forecasting wind speed financial return

    E-Print Network [OSTI]

    D'Amico, Guglielmo; Prattico, Flavio

    2013-01-01

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

  18. The addition of a US Rare Earth Element (REE) supply-demand model improves the characterization and scope of the United States Department of Energy's effort to forecast US REE Supply and Demand

    E-Print Network [OSTI]

    Mancco, Richard

    2012-01-01

    This paper presents the development of a new US Rare Earth Element (REE) Supply-Demand Model for the explicit forecast of US REE supply and demand in the 2010 to 2025 time period. In the 2010 Department of Energy (DOE) ...

  19. Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed

    E-Print Network [OSTI]

    2011-01-01

    solener.2011.02.014, Solar Energy. Lave, M. , Kleissl, J. ,smoothing. Submitted to Solar Energy. Linke, F. , 1922.24th European Photovoltaic Solar Energy Conference, Hamburg,

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

    E-Print Network [OSTI]

    Tronci, Enrico

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

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

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

  2. Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed

    E-Print Network [OSTI]

    2011-01-01

    from meteorological satellite data. Solar Energy 37, 31–39.16 independent data banks. Solar Energy 80, 468– 478.

  3. Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed

    E-Print Network [OSTI]

    2011-01-01

    solar irradiation in Brazil, Solar Energy, 68, 91- 107, ISSNmaps for Brazil under SWERA project, Solar Energy, 81, 517-

  4. Solar Forecast Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE)

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  6. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

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

  7. Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed

    E-Print Network [OSTI]

    2011-01-01

    smoothing. Submitted to Solar Energy. Linke, F. , 1922.24th European Photovoltaic Solar Energy Conference, Hamburg,solener.2011.02.014, Solar Energy. Lave, M. , Kleissl, J. ,

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

    E-Print Network [OSTI]

    MacDonald, Mark

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

  9. Bull. Astr. Soc. India (2010) 38, 147163 Comparison of energies between eruptive phenomena and

    E-Print Network [OSTI]

    Howard, Tim

    2010-01-01

    Bull. Astr. Soc. India (2010) 38, 147­163 Comparison of energies between eruptive phenomena the energy carried away by a coronal mass ejection (CME) and the radiative energy loss in associated flare plasma, with the decrease in magnetic free energy during a release in active region NOAA 10930

  10. PROCEEDINGS OF THE WORKSHOP ON NATIONAL/REGIONAL ENERGY-ENVIRONMENTAL MODELING CONCEPTS, MAY 30 - JUNE 1, 1979

    E-Print Network [OSTI]

    Ritschard, R.L.

    2010-01-01

    system with an energy demand forecast. T. R. Lakshmanan,economic and total energy demand forecasts. with basic

  11. Annual energy outlook 1995, with projections to 2010

    SciTech Connect (OSTI)

    1995-01-01

    The Annual Energy Outlook 1995 (AEO95) presents the midterm energy forecasts of the Energy Information Administration (EIA). This year`s report presents projections and analyses of energy supply, demand, and prices through 2010, based on results from the National Energy Modeling System (NEMS). Quarterly forecasts of energy supply and demand for 1995 and 1996 are published in the Short-Term Energy Outlook (February 1995). Forecast tables for the five cases examined in the AEO95 are provided in Appendixes A through C. Appendix A gives historical data and forecasts for selected years from 1992 through 2010 for the reference case. Appendix B presents two additional cases, which assume higher and lower economic growth than the reference case. Appendix C presents two cases that assume higher and lower world oil prices. Appendix D presents a summary of the forecasts in units of oil equivalence. Appendix E presents a summary of household energy expenditures. Appendix F provides detailed comparisons of the AEO95 forecasts with those of other organizations. Appendix G briefly describes NEMS and the major AEO95 forecast assumptions. Appendix H presents a stand-alone high electricity demand case. Appendix 1 provides a table of energy conversion factors and a table of metric conversion factors. 89 figs., 23 tabs.

  12. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

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

    1994-09-01

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

  13. Integration of Renewable Distributed Energy Resources into Microgrids

    E-Print Network [OSTI]

    Huang, Rui

    2015-01-01

    Francisco, “Forecast of hourly average wind speed with armawind turbine with energy storage management, the development of forecast-

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

    SciTech Connect (OSTI)

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

    2005-07-01

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

  15. ENERGY ANALYSIS PROGRAM FY-1979.

    E-Print Network [OSTI]

    Authors, Various

    2013-01-01

    of 25 years energy demand forecasts, and for a preliminary13143) In addition, energy demand forecasts will be reviseddemand forecasts as well as severly limiting their utility in assessing impacts of energy

  16. Improving automotive battery sales forecast

    E-Print Network [OSTI]

    Bulusu, Vinod

    2015-01-01

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

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

    E-Print Network [OSTI]

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

  18. Energy Comparison and Optimization of Wireless Body-Area Network Technologies

    E-Print Network [OSTI]

    Zhong, Lin

    1 Energy Comparison and Optimization of Wireless Body-Area Network Technologies Le Yan , Lin Zhong/O devices. We investigate an energy-efficient computing model, called wireless device driver, for low of tunable parameters of the wireless device driver on connection latency and energy consumption for both

  19. Analysing protein energy data by a stochastic model for cooperative interactions: comparison and

    E-Print Network [OSTI]

    Roma Tor Vergata, Università di

    Analysing protein energy data by a stochastic model for cooperative interactions: comparison deal here with estimation of unknown parameters from protein energy data. One of these parameters. We analyse both simulated data of the Markov chain, and protein energy data obtained by molecular dy

  20. Final Map Draft Comparison Report WIND ENERGY RESOURCE MODELING AND MEASUREMENT PROJECT

    E-Print Network [OSTI]

    II Final Map Draft Comparison Report #12;WIND ENERGY RESOURCE MODELING AND MEASUREMENT PROJECT Tel: 978-749-9591 Fax: 978-749-9713 mbrower@awstruewind.com August 10, 2004 #12;2 WIND ENERGY RESOURCE issues. 1 Background In Task 2 of the project, five promising areas of the state for wind energy

  1. Comparison of two optimization methods to derive energy parameters for protein folding

    E-Print Network [OSTI]

    Domany, Eytan

    Comparison of two optimization methods to derive energy parameters for protein folding: perceptron potential, perceptron, Z­score 1 #12; Abstract Two methods were proposed recently to derive energy, by means of a perceptron learning scheme, energy parameters such that the native conformations have lower

  2. Comparison groups on bills: Automated, personalized energy information

    E-Print Network [OSTI]

    Iyer, Maithili

    2008-01-01

    Summer Study on Energy Efficiency in Buildings. Berkeley,Summer Study on Energy Efficiency in Buildings. Berkeley,Summer Study on Energy Efficiency in Buildings. Berkeley,

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

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

  4. Comparison of Building Energy Modeling Programs: Building Loads

    E-Print Network [OSTI]

    Zhu, Dandan

    2014-01-01

    Energy Management System ), External Interface, FMI ( Functional Mockup Interface ) Interoperability

  5. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

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

  6. 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

  7. The Energy Return on Energy Investment (EROI) of Photovoltaics: Methodology and Comparisons with Fossil Fuel Life Cycles

    E-Print Network [OSTI]

    1 The Energy Return on Energy Investment (EROI) of Photovoltaics: Methodology and Comparisons National Photovoltaic Environmental Research Center, Brookhaven National Laboratory, Upton, NY 11973, USA higher than those of renewable energy life-cycles, and specifically of photovoltaics (PVs). We show

  8. METEOROLOGICAL Weather and Forecasting

    E-Print Network [OSTI]

    Collett Jr., Jeffrey L.

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

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

    E-Print Network [OSTI]

    Kockelman, Kara M.

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

  10. Solar Energy 74 (2003) 157173 Comparison between ray-tracing simulations and bi-directional

    E-Print Network [OSTI]

    2003-01-01

    Solar Energy 74 (2003) 157­173 Comparison between ray-tracing simulations and bi-Louis Scartezzini a Solar Energy and Building Physics Laboratory LESO-PB, Swiss Federal Institute of Technology EPFL Cyclotron Road, MS 2-300, Berkeley, CA 94720-8134, USA Abstract Evaluation of solar heat gain and daylight

  11. Master thesis Solar Energy Meteorology Comparison of different methods to estimate cloud height for solar

    E-Print Network [OSTI]

    Peinke, Joachim

    Master thesis ­ Solar Energy Meteorology Comparison of different methods to estimate cloud height: · Interest in meteorology and solar energy · Experiences with data handling and analysis · Good programming for solar irradiance calculations In order to derive incoming solar irradiance at the earths surface

  12. Energy Disposal in the O3 P + HCl Reaction: Classical Dynamics and Comparison

    E-Print Network [OSTI]

    Ramachandran, Bala (Ramu)

    Energy Disposal in the O3 P + HCl Reaction: Classical Dynamics and Comparison to Experiment B The energy disposal in the O3 P + HClv = 2;j = 1;6;9 ! OHv0;j0 + Cl reaction is analyzed using the results distributions. A careful examination of several reactive trajectories suggests that a a direct abstraction mecha

  13. Annual energy outlook 1994: With projections to 2010

    SciTech Connect (OSTI)

    Not Available

    1994-01-01

    The Annual Energy Outlook 1994 (AEO94) presents the midterm energy forecasts of the Energy Information Administration (EIA). This year`s report presents projects and analyses of energy supply, demand, and prices through 2010, based for the first time on results from the National Energy Modeling System (NEMS). NEMS is the latest in a series of computer-based energy modeling systems used over the past 2 decades by EIA and its predecessor organization, the Federal Energy Administration, to analyze and forecast energy consumption and supply in the midterm period (about 20 years). Quarterly forecasts of energy supply and demand for 1994 and 1995 are published in the Short-Term Energy Outlook (February 1994). Forecast tables for 2000, 2005, and 2010 for each of the five scenarios examined in the AEO94 are provided in Appendices A through E. The five scenarios include a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices. Appendix F provides detailed comparisons of the AEO94 forecasts with those of other organizations. Appendix G briefly described the NEMS and the major AEO94 forecast assumptions. Appendix H summarizes the key results for the five scenarios.

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

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast Energy Demand .............................................................. 23 Electricity Demand Growth in the West............................................................................................................................... 28 Estimating Electricity Demand in Data Centers

  15. ENERGY & ENVIRONMENT DIVISION ANNUAL REPORT 1979

    E-Print Network [OSTI]

    Cairns, E.J.

    2010-01-01

    of 25 years energy demand forecasts, and for a preliminaryIn addition, energy demand forecasts will be revised to takedemand forecasts as well as severly limiting their utility in assessing impacts of energy

  16. The water consumption of energy production: an international comparison

    E-Print Network [OSTI]

    Marks, David H.

    Producing energy resources requires significant quantities of fresh water. As an energy sector changes or expands, the mix of technologies deployed to produce fuels and electricity determines the associated burden on ...

  17. Comparison of Energy Efficiency Incentive Programs: Rebates and...

    Open Energy Info (EERE)

    Energy Efficiency, - Utility Topics: Environmental Website: www.sciencedirect.comsciencearticlepiiS0957178709000460 Equivalent URI: cleanenergysolutions.orgcontent...

  18. Forecasting Turbulent Modes with Nonparametric Diffusion Models

    E-Print Network [OSTI]

    Tyrus Berry; John Harlim

    2015-01-27

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

  19. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01

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

  20. Comparison of Real World Energy Consumption to Models and DOE...

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

    energy performance of appliances and equipment as it compares with models and test procedures. The study looked to determine whether DOE and industry test procedures...

  1. Deep Energy Retrofit Performance Metric Comparison: Eight California...

    Office of Scientific and Technical Information (OSTI)

    switched from natural gas to electricity for heating and hot water, resulting in energy consumption dominated by electricity use. This demonstrates the crucial importance of...

  2. Cost and Performance Comparison Baseline for Fossil Energy Power...

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

    blocks together into a new, revolutionary concept for future coal-based power and energy production. Objective To establish baseline performance and cost estimates for today's...

  3. Pathways to low-cost electrochemical energy storage: a comparison...

    Office of Scientific and Technical Information (OSTI)

    States); Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Chemical Engineering Joint Center for Energy Storage Research (United States);...

  4. Comparison of Building Energy Modeling Programs: Building Loads

    E-Print Network [OSTI]

    Zhu, Dandan

    2014-01-01

    Shruti Kaserekar (2010). Solar gain and cooling loadcoefficient assumptions, the solar position calculation, andthe sky diffuse solar models. 2. DeST and EnergyPlus both

  5. Cost and Performance Comparison Baseline for Fossil Energy Plants...

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

    energy security. A broad portfolio of technologies is being developed within the Clean Coal Program to accomplish this objective. Ever increasing technological enhancements...

  6. Wind Power Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentricNCubicthe FOIA?ResourceMeasurement BuoyForecasting Sign

  7. Comparison of Building Energy Modeling Programs: HVAC Systems

    E-Print Network [OSTI]

    Zhou, Xin

    2014-01-01

    energy balance on the water and air sides of the air/watercurves and performed on the water and air side of thebalance on the water and outdoor air web-bulb air/water

  8. Energy Use and Carbon Emissions: Some International Comparisons

    Reports and Publications (EIA)

    1994-01-01

    Presents energy use and carbon emissions patterns in a world context. The report contrasts trends in economically developed and developing areas of the world since 1970, presents a disaggregated view of the "Group of Seven" (G7) key industrialized countries (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) and examines sectoral energy use patterns within each of the G7 countries.

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Kleissl, Jan

    2011-01-01

    and validation.   Solar Energy.   73:5, 307? Perez, R. , irradiance forecasts for solar energy applications based on using satellite data.   Solar Energy 67:1?3, 139?150.  

  10. Price forecasting for notebook computers 

    E-Print Network [OSTI]

    Rutherford, Derek Paul

    1997-01-01

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

  11. Multivariate Forecast Evaluation And Rationality Testing

    E-Print Network [OSTI]

    Komunjer, Ivana; OWYANG, MICHAEL

    2007-01-01

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

  12. Comparison of Energy Needed to Heat Greenhouses and Insulated Frame Buildings Used in Aquaculture1

    E-Print Network [OSTI]

    Hill, Jeffrey E.

    initial cost. Building material costs for the structure can be as low as $1 per square foot, but plastic for this type of structure can be as low as $4 to $6 per square foot. Construction costs for wood or metal frameCIR1198 Comparison of Energy Needed to Heat Greenhouses and Insulated Frame Buildings Used

  13. Comparison of low-energy radiation effects in polyethylene and cellulose Jussi Polvi, Kai Nordlund

    E-Print Network [OSTI]

    Nordlund, Kai

    Comparison of low-energy radiation effects in polyethylene and cellulose Jussi Polvi, Kai Nordlund, for a carbon atom in polyethylene chain, and for one of the carbon atoms in cellulose chain. Our analysis shows and on average slightly higher for the carbon atoms in the polyethylene chain than for the target carbon atom

  14. Performance Comparison of Hybrid Vehicle Energy Management Controllers on Real-World Drive Cycle Data

    E-Print Network [OSTI]

    Grizzle, Jessy W.

    Performance Comparison of Hybrid Vehicle Energy Management Controllers on Real-World Drive Cycle's highly accurate proprietary vehicle model over large numbers of real- world drive cycles, and compared of Michigan Transportation Research Institute (UMTRI) for providing drive cycle data. of this work focuses

  15. Comparison of energy efficiency between variable refrigerant flow systems and ground source heat pump systems

    SciTech Connect (OSTI)

    Hong, Tainzhen; Liu, Xaiobing

    2009-11-01

    With the current movement toward net zero energy buildings, many technologies are promoted with emphasis on their superior energy efficiency. The variable refrigerant flow (VRF) and ground source heat pump (GSHP) systems are probably the most competitive technologies among these. However, there are few studies reporting the energy efficiency of VRF systems compared with GSHP systems. In this article, a preliminary comparison of energy efficiency between the air-source VRF and GSHP systems is presented. The computer simulation results show that GSHP system is more energy efficient than the air-source VRF system for conditioning a small office building in two selected US climates. In general, GSHP system is more energy efficient than the air-source VRV system, especially when the building has significant heating loads. For buildings with less heating loads, the GSHP system could still perform better than the air-source VRF system in terms of energy efficiency, but the resulting energy savings may be marginal.

  16. Learning Energy Demand Domain Knowledge via Feature Transformation

    E-Print Network [OSTI]

    Povinelli, Richard J.

    -- Domain knowledge is an essential factor for forecasting energy demand. This paper introduces a method knowledge substantially improves energy demand forecasting accuracy. However, domain knowledge may differ. The first stage automatically captures energy demand forecasting domain knowledge through nonlinear

  17. Behavioral Aspects in Simulating the Future US Building Energy Demand

    E-Print Network [OSTI]

    Stadler, Michael

    2011-01-01

    Floor-space forecast to 2050 Gross demand for energy Macro-Floor-space forecast to 2050 Gross demand for energy Macro-Floor-space forecast to 2050 Gross demand for energy Macro-

  18. Comparison of Fuel Cell Technologies: Fact Sheet | Department of Energy

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i p aDepartment ofCommercial GradeDepartment of Energyfuel cellAn

  19. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

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

    2011-02-23

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

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

  1. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

    the cloud index,” Solar Energy, vol. 81, no. 2, pp. 280 –Cover Indices,” ASME Journal of Solar Energy Engineering (inHorizontal Irradiance,” submitted to Solar Energy, 2012.

  2. Comparison of Fuel Cell Technologies | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataEnergy Webinar:I DueBETOofforCompany Template (Fixed Support)

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

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

  4. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

    the role of energy storage in the smart grid,” in Power andof energy storage, and the balance between grid flexibility

  5. Distributed Wind Policy Comparison Tool | Department of Energy

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i Framing DocumentUnits at Eight-< Back EligibilityDepartmentReport

  6. Comparison Table of Department of Energy Mentor-Protege Program |

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels Data Center HomeVehicleDepartment of Energy Programs » Mentor-Protégé

  7. Comparison of Two Statistical Approaches to Detect Abnormal Building Energy Consumption with Simulation Test 

    E-Print Network [OSTI]

    Lin, G.; Claridge, D.

    2012-01-01

    :?How?to?keep?the?optimal?building?energy? performance?after?Cx? ? Solution:?Whole?building?fault?detection? ? A?process?of?identifying?abnormal?energy?consumption ? Alert?operators?early?after?the?onset?of?significant? increases/decreases?in?consumption 2 Paper Model Fault Detection Dodier and...?Kreider (1999) Neural?network |Energy consumption index| > 1 Seem (2007) Historical measurement Outliers identification Lee and Claridge (2007) Calibrated simulation model (ASHRAE SEAP) Visual?comparison?of?E_Meas and?E_Sim Curtin (2007): ABCAT Calibrated...

  8. Comparison of building energy use data between the United States and China

    SciTech Connect (OSTI)

    Xia , Jianjun; Hong , Tianzhen; Shen, Qi; Feng , Wei; Yang, Le; Im , Piljae; Lu, Alison; Bhandari , Mahabir

    2013-10-30

    Buildings in the United States and China consumed 41percent and 28percent of the total primary energy in 2011, respectively. Good energy data are the cornerstone to understanding building energy performance and supporting research, design, operation, and policy making for low energy buildings. This paper presents initial outcomes from a joint research project under the U.S.-China Clean Energy Research Center for Building Energy Efficiency. The goal is to decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders. This paper first reviews and compares several popular existing building energy monitoring systems in both countries. Next a standard energy data model is presented. A detailed, measured building energy data comparison was conducted for a few office buildings in both countries. Finally issues of data collection, quality, sharing, and analysis methods are discussed. It was found that buildings in both countries performed very differently, had potential for deep energy retrofit, but that different efficiency measures should apply.

  9. Statement from Secretary of Energy Samuel W. Bodman Regarding...

    Energy Savers [EERE]

    Energy Outlook which forecasts to 2030: "EIA's updated forecast projecting higher oil prices and increased demand reinforces the Department of Energy's commitment to the...

  10. DOE Announces Webinars on Real Time Energy Management, Solar...

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

    Real Time Energy Management, Solar Forecasting Metrics, and More DOE Announces Webinars on Real Time Energy Management, Solar Forecasting Metrics, and More January 31, 2014 -...

  11. ESTIMATING RISK TO CALIFORNIA ENERGY INFRASTRUCTURE FROM PROJECTED CLIMATE CHANGE

    E-Print Network [OSTI]

    Sathaye, Jayant

    2011-01-01

    California Energy Demand 2010-2020: Adopted Forecast. CEC-energy infrastructure. Franco and Sanstad (2006) provide an overview and a methodology for demand forecasts

  12. China's Energy and Carbon Emissions Outlook to 2050

    E-Print Network [OSTI]

    Zhou, Nan

    2011-01-01

    effects. The forecast of energy demand underlying bothEnergy demand in residential buildings has been rising very fast in recent years. The forecast

  13. Comparison of efficiency: Cogeneration vs. utility-supplied energy

    SciTech Connect (OSTI)

    Kolanowski, B.F.

    1996-06-01

    In order to understand the benefits of cogeneration -- the on site production of electricity and hot water -- it is beneficial to know the overall efficiency of the energy media presently being used when compared to cogeneration. Virtually every commercial and industrial establishment purchases their electricity from the local utility company and heat their water by using on site boilers and hot water heaters fired by natural gas or propane -- which they also purchase from an outside supplier. When on-site cogeneration is compared to purchased power the results in fuel usage efficiency are: cogeneration -- 89.2%; purchased power -- 52.6%. The overall result of on site, properly applied cogeneration is an economical, environmental, and conservational tool that preserves an establishment`s cash, helps reduce pollution and conserves a precious natural resource.

  14. Power Forecasting for Plug-in Electric Vehicles

    E-Print Network [OSTI]

    Lavaei, Javad

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

  15. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01

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

  16. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

    of solar- radiation data,” Solar Energy, vol. 19, no. 6, pp.16 independent data banks,” Solar Energy, vol. 80, no. 4,data,” Final Report of International Energy Agency Solar

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

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01

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

  18. Resource Information and Forecasting Group; Electricity, Resources, & Building Systems Integration (ERBSI) (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2009-11-01

    Researchers in the Resource Information and Forecasting group at NREL provide scientific, engineering, and analytical expertise to help characterize renewable energy resources and facilitate the integration of these clean energy sources into the electricity grid.

  19. QUALIFIED FORECAST OF ENSEMBLE POWER PRODUCTION BY SPATIALLY DISPERSED GRID-CONNECTED PV SYSTEMS

    E-Print Network [OSTI]

    Heinemann, Detlev

    , Energy Meteorology Group, D-26111 Oldenburg, Germany, elke.lorenz@uni-oldenburg.de + UniversityQUALIFIED FORECAST OF ENSEMBLE POWER PRODUCTION BY SPATIALLY DISPERSED GRID- CONNECTED PV SYSTEMS Schneider° * University of Oldenburg, Institute of Physics, Energy and Semiconductor Research Laboratory

  20. Comparison of Optical, Radio, and Acoustical Detectors for Ultrahigh-Energy Neutrinos

    E-Print Network [OSTI]

    P. B. Price

    1995-10-24

    For electromagnetic cascades induced by electron-neutrinos in South Pole ice, the effective volume per detector element (phototube, radio antenna, or acoustic transducer) as a function of cascade energy is estimated, taking absorption and scattering into account. A comparison of the three techniques shows that the optical technique is most effective for energies below ~0.5 PeV, that the radio technique shows promise of being the most effective for higher energies, and that the acoustic method is not competitive. Due to the great transparency of ice, the event rate of AGN ne-induced cascades is an order of magnitude greater than in water. For hard source spectra, the rate of Glashow resonance events may be much greater than the rate for non-resonant energies. The radio technique will be particularly useful in the study of Glashow events and in studies of sources with very hard energy spectra.

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

    E-Print Network [OSTI]

    Goto, Susumu

    2007-01-01

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

  2. 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; Pavan, Alessandro Massi

    2010-05-15

    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)

  3. An international comparison of government expenditures for energy conservation research and development:

    SciTech Connect (OSTI)

    McDonald, S.C.

    1988-03-01

    This study provides a comparison of US and foreign government spending for energy conservation research and development (R and D). The countries included in this analysis are: the United States, United Kingdom, France, Sweden, West Germany, and Japan. The approach of this paper was to compare the research program of each country at a high level of aggregation with the US Department of Energy (DOE) program structure. This paper does not allow for differences in the way each country defines or accounts for research.

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

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

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

  5. Energy use in Poland, 1970--1991: Sectoral analysis and international comparison

    SciTech Connect (OSTI)

    Meyers, S.; Schipper, L.; Salay, J.

    1993-07-01

    This report provides an analysis of how and why energy use has changed in Poland since the 1970s, with particular emphasis on changes since the country began its transition from a centrally planned to a market economy in 1989. The most important factors behind the large decline in Polish energy use in 1990 were a sharp fall in industrial output and a huge drop in residential coal use driven by higher prices. The structural shift away from heavy industry was slight. Key factors that worked to increase energy use were the rise in energy intensity in many heavy industries and the shift toward more energy intensive modes of transport. The growth in private activities in 1991 was nearly sufficient to balance out continued decline in industrial energy use in that year. We compared energy use in Poland and the factors that shape it with similar elements in the West. We made a number of modifications to the Polish energy data to bring it closer to a Western energy accounting framework, and augmented these with a variety of estimates in order to construct a sufficiently detailed portrait of Polish energy use to allow comparison with Western data. Per capita energy use in Poland was not much below W. European levels despite Poland`s much lower GDP per capita. Poland has comparatively high energy intensities in manufacturing and residential space heating, and a large share of heavy industries in manufacturing output, all factors that contribute to higher energy use per capita. The structure of passenger and freight transportation and the energy intensity of automobiles contribute to lower energy use per capita in Poland than in Western Europe, but the patterns in Poland are moving closer to those that prevail in the West.

  6. Performance comparison of U.K. low-energy cooling systems by energy simulation

    E-Print Network [OSTI]

    Olsen, Erik L. (Erik Lee), 1979-

    2002-01-01

    Building energy simulation is an important tool for evaluating the energy consumption of a building and can provide guidance in the design of a building and its mechanical systems. EnergyPlus is a new energy simulation ...

  7. Comparison Between Air and Helium for Use as Working Fluids in the Energy-Conversion Cycle of the MPBR

    E-Print Network [OSTI]

    Galen, T. A.

    A comparison between air and helium for use as working fluids in the energy-conversion cycle of the MPBR is presented. To date, helium has been selected in the MPBR indirect-cycle working reference design. Air open- and ...

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

    E-Print Network [OSTI]

    Mathiesen, Patrick James

    2013-01-01

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

  9. Comparison of Software Models for Energy Savings from Cool Roofs Joshua New, Oak Ridge National Laboratory (United States)

    E-Print Network [OSTI]

    Tennessee, University of

    , multiple substrate types, and insulation levels. A base case and energy-efficient alternative canComparison of Software Models for Energy Savings from Cool Roofs Joshua New, Oak Ridge National Department of Energy as an industry-consensus tool to help building owners, manufacturers, distributors

  10. Comparison of Energy Efficiency in PSTN and VoIP Florin Bota, Faheem Khuhawar, Marco Mellia, Michela Meo

    E-Print Network [OSTI]

    Comparison of Energy Efficiency in PSTN and VoIP Systems Florin Bota, Faheem Khuhawar, Marco Mellia.lastname@polito.it ABSTRACT The importance of deploying energy efficient networks has vastly increased due to the rapidly to existing networks that could prove to be energy efficient. In this paper, two telephone net- works namely

  11. A monetary comparison of energy recovered from microbial fuel cells and microbial electrolysis cells fed winery or

    E-Print Network [OSTI]

    A monetary comparison of energy recovered from microbial fuel cells and microbial electrolysis a c t Microbial fuel (MFCs) and electrolysis cells (MECs) can be used to recover energy directly electrical energy directly from the wastewater. BES such as microbial fuel cells (MFCs) and microbial

  12. Energy efficiency and the cost of GHG abatement: A comparison of bottom-up and hybrid models for the US

    E-Print Network [OSTI]

    Energy efficiency and the cost of GHG abatement: A comparison of bottom-up and hybrid models February 2011 Accepted 16 August 2011 Available online 17 September 2011 Keywords: Energy efficiency that a large potential for profitable energy efficiency exists in the US, and that substantial greenhouse gas

  13. Comparison of a Clean Energy Standard and other Mandates with a Carbon Tax Kemal Sarica and Wallace E. Tyner

    E-Print Network [OSTI]

    Ginzel, Matthew

    according to Annual Energy Outlook 2010 and is further enhanced with data generated from a global generalComparison of a Clean Energy Standard and other Mandates with a Carbon Tax Kemal Sarica and Wallace E. Tyner Purdue University Abstract To deal with Greenhouse Gas (GHG) emissions and other energy

  14. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

    and operation of solar power plants and the model- ing offor application to solar ther- mal power plants energy

  15. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01

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

  16. Japan's Long-term Energy Demand and Supply Scenario to 2050 - Estimation for the Potential of Massive CO2 Mitigation

    E-Print Network [OSTI]

    Komiyama, Ryoichi

    2010-01-01

    Framework Energy supply/demand forecasts change greatlyThis analysis makes energy supply/demand forecasts for theEnergy Demand (Reference Scenario) In millions of tons oil equivalent (Mtoe) I l f Results* •Forecasts *

  17. Energy Efficiency in Western Utility Resource Plans: Impacts on Regional Resources Assessment and Support for WGA Policies

    E-Print Network [OSTI]

    Hopper, Nicole; Goldman, Charles; Schlegal, Jeff

    2006-01-01

    2006-2016 Staff Energy Demand Forecast: Revised Septemberforecast. 2004–05 energy and peak demand forecast data were016-0: “Actual and Forecast Demands, Net Energy for Load,

  18. Solar forecasting review

    E-Print Network [OSTI]

    Inman, Richard Headen

    2012-01-01

    2.1.2 European Solar Radiation Atlas (ESRA)synthetic hourly radiation,” Solar Energy, vol. 49, pp. 67–for supplementing solar radiation network data,” Final

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

    E-Print Network [OSTI]

    Chen, Songqing

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

  20. 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 ...

  1. 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 ...

  2. Forecasting consumer products using prediction markets

    E-Print Network [OSTI]

    Trepte, Kai

    2009-01-01

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

  3. FORECASTING THE ROLE OF RENEWABLES IN HAWAII

    E-Print Network [OSTI]

    Sathaye, Jayant

    2013-01-01

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

  4. On the comparison of energy sources: feasibility of radio frequency and ambient light harvesting

    E-Print Network [OSTI]

    Korotkevich, Alexander O; Lavrova, Olga; Coutsias, Evangelos

    2015-01-01

    With growing interest in multi source energy harvesting including integrated microchips we propose a comparison of radio frequency (RF) and solar energy sources in a typical city. Harvesting devices for RF and solar energy will be competing for space of a compact micro or nano device as well as for orientation with respect to the energy source. This is why it is important to investigate importance of every source of energy and make a decision whether it will be worthwhile to include such harvesters. We considered theoretically possible irradiance by RF signal in different situations, typical for the modern urban environment and compared it with ambient solar energy sources available through the night, including moon light. Our estimations show that solar light energy dominates by far margin practically all the time, even during the night, if there is a full moon in the absence of clouds. At the same time, in the closed compartments or at the new moon RF harvesting can be beneficial as a source of "free" energ...

  5. NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS

    E-Print Network [OSTI]

    Mohaghegh, Shahab

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

  6. 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

  7. Short-term energy outlook, Annual supplement 1995

    SciTech Connect (OSTI)

    1995-07-25

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

  8. A Comparison of Iron and Steel Production Energy Use and Energy Intensity in China and the U.S.

    SciTech Connect (OSTI)

    Hasanbeigi, Ali; Price, Lynn; Aden, Nathaniel; Chunxia, Zhang; Xiuping, Li; Fangqin, Shangguan

    2011-06-15

    Production of iron and steel is an energy-intensive manufacturing process. In 2006, the iron and steel industry accounted for 13.6% and 1.4% of primary energy consumption in China and the U.S., respectively (U.S. DOE/EIA, 2010a; Zhang et al., 2010). The energy efficiency of steel production has a direct impact on overall energy consumption and related carbon dioxide (CO2) emissions. The goal of this study is to develop a methodology for making an accurate comparison of the energy intensity (energy use per unit of steel produced) of steel production. The methodology is applied to the steel industry in China and the U.S. The methodology addresses issues related to boundary definitions, conversion factors, and indicators in order to develop a common framework for comparing steel industry energy use. This study uses a bottom-up, physical-based method to compare the energy intensity of China and U.S. crude steel production in 2006. This year was chosen in order to maximize the availability of comparable steel-sector data. However, data published in China and the U.S. are not always consistent in terms of analytical scope, conversion factors, and information on adoption of energy-saving technologies. This study is primarily based on published annual data from the China Iron & Steel Association and National Bureau of Statistics in China and the Energy Information Agency in the U.S. This report found that the energy intensity of steel production is lower in the United States than China primarily due to structural differences in the steel industry in these two countries. In order to understand the differences in energy intensity of steel production in both countries, this report identified key determinants of sector energy use in both countries. Five determinants analyzed in this report include: share of electric arc furnaces in total steel production, sector penetration of energy-efficiency technologies, scale of production equipment, fuel shares in the iron and steel industry, and final steel product mix in both countries. The share of lower energy intensity electric arc furnace production in each country was a key determinant of total steel sector energy efficiency. Overall steel sector structure, in terms of average plant vintage and production capacity, is also an important variable though data were not available to quantify this in a scenario. The methodology developed in this report, along with the accompanying quantitative and qualitative analyses, provides a foundation for comparative international assessment of steel sector energy intensity.

  9. Forecasting phenology under global warming

    E-Print Network [OSTI]

    Silander Jr., John A.

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

  10. 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

  11. The Revised Austin Energy Code and Comparisons with the Texas State Energy Standard 

    E-Print Network [OSTI]

    Crow, G.

    1992-01-01

    For the past two years the City of Austin Energy Code has been under review using the State Energy Standard and ASHRAE 90.2P as models for the revised Austin Energy Code. The major changes to these documents are presented in this paper....

  12. A Buildings Module for the Stochastic Energy Deployment System

    E-Print Network [OSTI]

    Marnay, Chris

    2008-01-01

    forecast is used, thereby eliminating any discrepancies. The final energy demandenergy results as well as the AEO- 07 forecasts for total natural gas demand

  13. Comparison of building energy use data between the United States and China

    E-Print Network [OSTI]

    Xia Ph.D., Jianjun

    2014-01-01

    pipes, etc. Annual Electricity Consumption Comparison OtherFig. 7. Annual electricity consumption comparison of case-the total annual electricity consumption, Buildings A and B

  14. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

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

    2011-11-29

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

  15. Energy, cost, and CO 2 emission comparison between radiant wall panel systems and radiator systems

    E-Print Network [OSTI]

    Milorad Boji?; Dragan Cvetkovi?; Marko Mileti?; Jovan Maleševi?; Harry Boyer

    2012-12-18

    The main goal of this paper is to evaluate the possibility of application or replacement of radiators with low-temperature radiant panels. This paper shows the comparison results of operations of 4 space heating systems: the low-temperature radiant panel system without any additional thermal insulation of external walls (PH-WOI), the low-temperature radiant panel system with additional thermal insulation of external walls (PH-WI), the radiator system without any additional thermal insulation of external walls (the classical heating system) (RH-WOI), and the radiator system with additional thermal insulation of external walls (RH-WI). The operation of each system is simulated by software EnergyPlus. The investigation shows that the PH-WI gives the best results. The RH-WOI has the largest energy consumption, and the largest pollutant emission. However, the PH-WI requires the highest investment.

  16. Energy Performance Comparison of Heating and Air Conditioning Systems for Multi-Family Residential Buildings

    SciTech Connect (OSTI)

    Wang, Weimin; Zhang, Jian; Jiang, Wei; Liu, Bing

    2011-07-31

    The type of heating, ventilation and air conditioning (HVAC) system has a large impact on the heating and cooling energy consumption in multifamily residential buildings. This paper compares the energy performance of three HVAC systems: a direct expansion (DX) split system, a split air source heat pump (ASHP) system, and a closed-loop water source heat pump (WSHP) system with a boiler and an evaporative fluid cooler as the central heating and cooling source. All three systems use gas furnace for heating or heating backup. The comparison is made in a number of scenarios including different climate conditions, system operation schemes and applicable building codes. It is found that with the minimum code-compliant equipment efficiency, ASHP performs the best among all scenarios except in extremely code climates. WSHP tends to perform better than the split DX system in cold climates but worse in hot climates.

  17. Improving energy efficiency via smart building energy management systems. A comparison with policy measures

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

    Rocha, Paula; Siddiqui, Afzal; Stadler, Michael

    2014-12-09

    To foster the transition to more sustainable energy systems, policymakers have been approving measures to improve energy efficiency as well as promoting smart grids. In this setting, building managers are encouraged to adapt their energy operations to real-time market and weather conditions. Yet, most fail to do so as they rely on conventional building energy management systems (BEMS) that have static temperature set points for heating and cooling equipment. In this paper, we investigate how effective policy measures are at improving building-level energy efficiency compared to a smart BEMS with dynamic temperature set points. To this end, we present anmore »integrated optimisation model mimicking the smart BEMS that combines decisions on heating and cooling systems operations with decisions on energy sourcing. Using data from an Austrian and a Spanish building, we find that the smart BEMS results in greater reduction in energy consumption than a conventional BEMS with policy measures.« less

  18. Improving energy efficiency via smart building energy management systems. A comparison with policy measures

    SciTech Connect (OSTI)

    Rocha, Paula; Siddiqui, Afzal; Stadler, Michael

    2014-12-09

    To foster the transition to more sustainable energy systems, policymakers have been approving measures to improve energy efficiency as well as promoting smart grids. In this setting, building managers are encouraged to adapt their energy operations to real-time market and weather conditions. Yet, most fail to do so as they rely on conventional building energy management systems (BEMS) that have static temperature set points for heating and cooling equipment. In this paper, we investigate how effective policy measures are at improving building-level energy efficiency compared to a smart BEMS with dynamic temperature set points. To this end, we present an integrated optimisation model mimicking the smart BEMS that combines decisions on heating and cooling systems operations with decisions on energy sourcing. Using data from an Austrian and a Spanish building, we find that the smart BEMS results in greater reduction in energy consumption than a conventional BEMS with policy measures.

  19. Subscriber Services Complete Forecast

    E-Print Network [OSTI]

    funded solar energy, then cut funding off, heavily funded electric vehicles, then cut funding off produce no long-lived radioactive waste. In the 1980s, scientists planned to build a major fusion countries have now taken the lead in fusion research. France will build the ITER with Japan as a major

  20. A physically meaningful method for the comparison of potential energy functions

    E-Print Network [OSTI]

    J. L. Alonso; Pablo Echenique

    2005-12-07

    In the study of the conformational behavior of complex systems, such as proteins, several related statistical measures are commonly used to compare two different potential energy functions. Among them, the Pearson's correlation coefficient r has no units and allows only semi-quantitative statements to be made. Those that do have units of energy and whose value may be compared to a physically relevant scale, such as the root mean square deviation (RMSD), the mean error of the energies (ER), the standard deviation of the error (SDER) or the mean absolute error (AER), overestimate the distance between potentials. Moreover, their precise statistical meaning is far from clear. In this article, a new measure of the distance between potential energy functions is defined which overcomes the aforementioned difficulties. In addition, its precise physical meaning is discussed, the important issue of its additivity is investigated and some possible applications are proposed. Finally, two of these applications are illustrated with practical examples: the study of the van der Waals energy, as implemented in CHARMM, in the Trp-Cage protein (PDB code 1L2Y) and the comparison of different levels of the theory in the ab initio study of the Ramachandran map of the model peptide HCO-L-Ala-NH2.

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

    SciTech Connect (OSTI)

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

    2012-10-01

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

  2. Inter-Machine Comparison of the Termination Phase and Energy Conversion in Tokamak Disruptions with Runaway Current Plateau Formation and Implications for ITER

    E-Print Network [OSTI]

    Inter-Machine Comparison of the Termination Phase and Energy Conversion in Tokamak Disruptions with Runaway Current Plateau Formation and Implications for ITER

  3. Comparison of Real World Energy Consumption to Models and Department of Energy Test Procedures

    SciTech Connect (OSTI)

    Goetzler, William; Sutherland, Timothy; Kar, Rahul; Foley, Kevin

    2011-09-01

    This study investigated the real-world energy performance of appliances and equipment as it compared with models and test procedures. The study looked to determine whether the U.S. Department of Energy and industry test procedures actually replicate real world conditions, whether performance degrades over time, and whether installation patterns and procedures differ from the ideal procedures. The study first identified and prioritized appliances to be evaluated. Then, the study determined whether real world energy consumption differed substantially from predictions and also assessed whether performance degrades over time. Finally, the study recommended test procedure modifications and areas for future research.

  4. Improving Inventory Control Using Forecasting

    E-Print Network [OSTI]

    Balandran, Juan

    2005-12-16

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

  5. International Comparison of Energy Labeling and Standards for Energy Efficient and Green Buildings 

    E-Print Network [OSTI]

    Hennicke, P.; Shrestha, S.; Schleicher, T.

    2011-01-01

    This paper discusses the approaches of the European Union, Germany and India to reduce GHG- emissions and mitigate climate change impacts from buildings through the establishment of energy performance standards and green building...

  6. SUMMARY OF 2013 ATLANTIC TROPICAL CYCLONE ACTIVITY AND VERIFICATION OF AUTHORS' SEASONAL AND TWO-WEEK FORECASTS

    E-Print Network [OSTI]

    Connors, Daniel A.

    -WEEK FORECASTS The 2013 Atlantic hurricane season was much quieter than predicted in our seasonal outlooks. While as past forecasts and verifications are available via the World Wide Web at http Cyclone Energy (ACE) (92) 165 165 142 30 32% Net Tropical Cyclone Activity (NTC) (103%) 175 175 150 43 42

  7. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Rayner, Steve; Lach, Denise; Ingram, Helen

    2005-01-01

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

  9. The Preservation of Physical Fashion Forecasts

    E-Print Network [OSTI]

    Kosztowny, Alexander John

    2015-01-01

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

  10. Promotional forecasting in the grocery retail business

    E-Print Network [OSTI]

    Koottatep, Pakawkul

    2006-01-01

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

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

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

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

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

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

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

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

    E-Print Network [OSTI]

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

  14. 1Bureau of Meteorology | Water Information > INFORMATION SHEET 6 > Flood Forecasting and Warning Services Flood Forecasting

    E-Print Network [OSTI]

    Greenslade, Diana

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

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

    SciTech Connect (OSTI)

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

    2013-05-01

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

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

    E-Print Network [OSTI]

    Poulin, L.

    2013-01-01

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

  17. Financial Analysis of Incentive Mechanisms to Promote Energy Efficiency: Case Study of a Prototypical Southwest Utility

    E-Print Network [OSTI]

    Cappers, Peter

    2009-01-01

    s retail energy sales forecasts and peak demand levels aredemand forecasts represents our “business-as-usual” scenario if energyenergy efficient measures at the end of their useful lifetime, the utility’s load and peak demand forecast

  18. NREL: Transmission Grid Integration - Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines lightGeospatial ToolkitSMARTS -BeingFuture forForecasting NREL researchers

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

    E-Print Network [OSTI]

    Parsons, Simon

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

  20. 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

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

    E-Print Network [OSTI]

    Raftery, Adrian

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

  2. Fostering a Renewable Energy Technology Industry: An International Comparison of Wind Industry Policy Support Mechanisms

    E-Print Network [OSTI]

    Lewis, Joanna; Wiser, Ryan

    2005-01-01

    Renewable Energy. Renewable Energy Policy Project ResearchIndustrial Policy and Renewable Energy Technology.Development of Renewable Energy. Energy Policy, 31, 799-812.

  3. 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

  4. INTELLIGENT HANDLING OF WEATHER FORECASTS Stephan Kerpedjiev

    E-Print Network [OSTI]

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

  5. Smooth Calibration, Leaky Forecasts, and Finite Recall

    E-Print Network [OSTI]

    Hart, Sergiu

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

  6. Multivariate Time Series Forecasting in Incomplete Environments

    E-Print Network [OSTI]

    Roberts, Stephen

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

  7. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

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

  8. Weather and Forecasting EARLY ONLINE RELEASE

    E-Print Network [OSTI]

    Johnson, Richard H.

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

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

    SciTech Connect (OSTI)

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

    2013-11-01

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

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

    SciTech Connect (OSTI)

    Not Available

    1995-02-01

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

  11. Optimal Real-time Dispatch for Integrated Energy Systems

    E-Print Network [OSTI]

    Firestone, Ryan Michael

    2007-01-01

    current and forecasted energy prices, energy demand, and DERarises in energy loads, energy prices and IES equipmentenergy loads, and energy prices, regulatory constraints on

  12. Fostering a Renewable Energy Technology Industry: An International Comparison of Wind Industry Policy Support Mechanisms

    E-Print Network [OSTI]

    Lewis, Joanna; Wiser, Ryan

    2005-01-01

    and Renewable Energy, Wind & Hydropower Technologiesand Renewable Energy, Wind & Hydropower Technologies2004. International Wind Energy Development, World Market

  13. A Comparison of Iron and Steel Production Energy Intensity in China and the U.S

    E-Print Network [OSTI]

    Price, Lynn

    2014-01-01

    Statistics Press. International Energy Agency (IEA). 2005.Energy Statistics Manual. Paris: IEA. http://www.iea.org/International Energy Agency (IEA). 2008. Key World Energy

  14. Comparison of building energy use data between the United States and China

    E-Print Network [OSTI]

    Xia Ph.D., Jianjun

    2014-01-01

    Summer Study on Energy Efficiency in Buildings, 2002. [19]Summer Study on Energy Efficiency in Buildings, 2000. [18]Standard for Energy Efficiency of Public Buildings, Energy

  15. Earthquake Forecast via Neutrino Tomography

    E-Print Network [OSTI]

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

    2011-03-29

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

  16. CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY

    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 CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY FORECAST Volume 1

  17. Conservation The Northwest ForecastThe Northwest Forecast

    E-Print Network [OSTI]

    EfficiencyEnergy Efficiency Dominates ResourceDominates Resource DevelopmentDevelopment Tom EckmanTom Eckman Energy Efficiency as a Resource Conference2005 ACEEE Energy Efficiency as a Resource Conference #12;slide Programs 1635 aMW 56% #12;slide 5 Northwest Power and Conservation Council Energy Efficiency ResourcesEnergy

  18. Forecasting Random Walks Under Drift Instability

    E-Print Network [OSTI]

    Pesaran, M Hashem; Pick, Andreas

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

  19. An Activity-Based Assessment of the Potential Impacts of Plug-In Hybrid Electric Vehicles on Energy and Emissions Using One-Day Travel Data

    E-Print Network [OSTI]

    Recker, W. W.; Kang, J. E.

    2010-01-01

    regarding demand or emission, they can forecast energy orenergy efficiency with increased PHEV charging demand, the previous results can be used to forecast

  20. Review and comparison of web- and disk-based tools for residential energy analysis

    E-Print Network [OSTI]

    Mills, Evan

    2002-01-01

    Advisor) and the Home Energy Saver. While not a criticalEnergy Adivsor), Home Energy Saver, HomeEnergy Software,old”) whereas the Home Energy Saver Due to cost or other

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  2. Wind-Wave Probabilistic Forecasting based on Ensemble

    E-Print Network [OSTI]

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  4. A theoretical comparison of x-ray angiographic image quality using energy-dependent and conventional subtraction methods

    SciTech Connect (OSTI)

    Tanguay, Jesse; Kim, Ho Kyung; Cunningham, Ian A.

    2012-01-15

    Purpose: X-ray digital subtraction angiography (DSA) is widely used for vascular imaging. However, the need to subtract a mask image can result in motion artifacts and compromised image quality. The current interest in energy-resolving photon-counting (EPC) detectors offers the promise of eliminating motion artifacts and other advanced applications using a single exposure. The authors describe a method of assessing the iodine signal-to-noise ratio (SNR) that may be achieved with energy-resolved angiography (ERA) to enable a direct comparison with other approaches including DSA and dual-energy angiography for the same patient exposure. Methods: A linearized noise-propagation approach, combined with linear expressions of dual-energy and energy-resolved imaging, is used to describe the iodine SNR. The results were validated by a Monte Carlo calculation for all three approaches and compared visually for dual-energy and DSA imaging using a simple angiographic phantom with a CsI-based flat-panel detector. Results: The linearized SNR calculations show excellent agreement with Monte Carlo results. While dual-energy methods require an increased tube heat load of 2x to 4x compared to DSA, and photon-counting detectors are not yet ready for angiographic imaging, the available iodine SNR for both methods as tested is within 10% of that of conventional DSA for the same patient exposure over a wide range of patient thicknesses and iodine concentrations. Conclusions: While the energy-based methods are not necessarily optimized and further improvements are likely, the linearized noise-propagation analysis provides the theoretical framework of a level playing field for optimization studies and comparison with conventional DSA. It is concluded that both dual-energy and photon-counting approaches have the potential to provide similar angiographic image quality to DSA.

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

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

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

  6. Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

    E-Print Network [OSTI]

    Dudley, Junqiao Han

    2010-01-01

    Performance with an EnergyPlus Model in a Low Energy CampusPerformance with an EnergyPlus Model in a Low Energy Campusevents. In this paper, an EnergyPlus model of the building

  7. Load Forecast For use in Resource Adequacy

    E-Print Network [OSTI]

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

  8. New product forecasting in volatile markets

    E-Print Network [OSTI]

    Baldwin, Alexander (Alexander Lee)

    2014-01-01

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

  9. 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 ...

  10. Comparison of the ENERGYGAUGE USA and BEopt Building Energy Simulation Programs

    SciTech Connect (OSTI)

    Parker, Danny S.; Cummings, Jamie E.

    2009-08-01

    This report compares two hourly energy simulation softwares, BEopt and Energy Gauge USA, to ensure accuracy and evaluate agreement on the impact of various energy efficiency improvements.

  11. Fostering a Renewable Energy Technology Industry: An International Comparison of Wind Industry Policy Support Mechanisms

    E-Print Network [OSTI]

    Lewis, Joanna; Wiser, Ryan

    2005-01-01

    2004. International Wind Energy Development, World Market2005. International Wind Energy Development, World Market2004, March 2005. Canadian Wind Energy Association (CanWEA),

  12. Comparison of building energy use data between the United States and China

    E-Print Network [OSTI]

    Xia Ph.D., Jianjun

    2014-01-01

    2011, respectively. Good energy data are the cornerstone toanalyze good building energy data to provide valuable andcountries. Next a standard energy data model is presented. A

  13. Fostering a Renewable Energy Technology Industry: An International Comparison of Wind Industry Policy Support Mechanisms

    E-Print Network [OSTI]

    Lewis, Joanna; Wiser, Ryan

    2005-01-01

    of Renewable Energy Technologies: Wind Power in the UnitedRenewable Energy, Wind & Hydropower Technologies Program, ofRenewable Energy, Wind & Hydropower Technologies Program, of

  14. A COMPARISON OF THE CONDUCTOR REQUIREMENTS FOR ENERGY STORAGE DEVICES MADE WITH IDEAL COIL GEOMETRIES

    E-Print Network [OSTI]

    Hassenzahl, W.

    2011-01-01

    Superconducting Magnetic Energy Storage Program," Los AlamosWisconsin Superconductive Energy Storage Project. Y2!.l,J. J. Stekly, "Magnetic Energy Storage Using Superconducting

  15. International Comparison of Energy Efficiency Awards for Appliance Manufacturers and Retailers

    E-Print Network [OSTI]

    Zhou, Nan

    2014-01-01

    s Congress (NPC), 2007, “Energy Conservation Law”, http://files/China_Energy_Conservation_Law_amended_28_Oct_07_MCC .Additionally, the Energy Conservation Law, which was amended

  16. Comparison of the energy spectra and number fluxes from a simple flare model to observations

    E-Print Network [OSTI]

    Hannah, Iain G; Fletcher, L

    2006-01-01

    column) and the kinetic energy gain (right- hand column) forcolumn) and the kinetic energy gain (right- hand column) forcolumn) and the kinetic energy gain (right- hand column) for

  17. Energy Efficiency Design Options for Residential Water Heaters: Economic Impacts on Consumers

    E-Print Network [OSTI]

    Lekov, Alex

    2011-01-01

    Administration. 2010. Annual Energy Outlook 2010 withthe price forecasts in EIA’s Annual Energy Outlook 2010. The

  18. Comparisons of HVAC Simulations between EnergyPlus and DOE-2.2 for Data Centers

    E-Print Network [OSTI]

    Hong, Tianzhen

    2009-01-01

    Company. USDOE. 2007. EnergyPlus 2.1 Input Output Referenceof Energy. USDOE. 2007. EnergyPlus 2.1 Engineering Manual.Hitchcock . 2006. Using EnergyPlus for California Title-24

  19. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01

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

  20. Comparison of energy efficiency between variable refrigerant flow systems and ground source heat pump systems

    E-Print Network [OSTI]

    Hong, Tainzhen

    2010-01-01

    the current movement toward net zero energy buildings, manyThe movement towards net zero energy buildings brings

  1. A Comparison of Iron and Steel Production Energy Use and Energy Intensity in China and the U.S.

    E-Print Network [OSTI]

    Hasanbeigi, Ali

    2012-01-01

    in this analysis. Export products energy consumption (values indicate the energy use by export products wasproduction of net exports of pig iron Energy used for the

  2. A Comparison of Iron and Steel Production Energy Use and Energy Intensity in China and the U.S.

    E-Print Network [OSTI]

    Hasanbeigi, Ali

    2012-01-01

    sources of total energy consumption data for China’s ironprovide national energy consumption data up to 2003. Thecollection after 2005 Energy consumption data by process in

  3. Three Essays on Energy Economics and Forecasting 

    E-Print Network [OSTI]

    Shin, Yoon Sung

    2012-02-14

    and producer surplus in the transport fuel market will decrease. In the third essay, the Regression - Seasonal Autoregressive Integrated Moving Average (REGSARIMA) model is employed to predict the impact of air temperature on daily peak load demand...

  4. LED Lighting Forecast | Department of Energy

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on DeliciousMathematics AndBeryllium Disease | Department of0 Inspection BEFORE THE3, 2011:Kenneth G.KristenMarket Studies

  5. energy data + forecasting | OpenEI Community

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX ECoop IncIowa (UtilityMichigan)data book Home Graham7781'semissions Homeenergy data +

  6. OpenEI Community - energy data + forecasting

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsourceII JumpQuarterly Smart Grid Data available for download onst,/0 en BigArtby<div

  7. INTERNATIONAL COMPARISON OF RESIDENTIAL ENERGY USE: INDICATORS OF RESIDENTIAL ENERGY USE AND EFFICIENCY PART ONE: THE DATA BASE

    E-Print Network [OSTI]

    Schipper, L.

    2013-01-01

    the housing and energy consumption data is a detailed studyConventions 6 All energy consumption data refer energy,Italian residential energy consumption data by end use. Unt

  8. Renewable Energy RFPs | OpenEI Community

    Open Energy Info (EERE)

    Renewable Energy RFPs Home > Renewable Energy RFPs > Posts by term > Renewable Energy RFPs Content Group Activity By term Q & A Feeds Term: Drilling Fluids Market Forecast Type...

  9. Renewable Energy RFPs | OpenEI Community

    Open Energy Info (EERE)

    Renewable Energy RFPs Home > Renewable Energy RFPs > Posts by term > Renewable Energy RFPs Content Group Activity By term Q & A Feeds Term: Fuel Cells Market Forecast Type Term...

  10. Coupling Renewable Energy Supply with Deferrable Demand

    E-Print Network [OSTI]

    Papavasiliou, Anthony

    2011-01-01

    forecasting for wind energy: Temperature dependence andlarge amounts of wind energy with a small electric system.Large scale integration of wind energy in the european power

  11. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

    McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

    2008-01-01

    Forecasts of California transportation energy demand, 2005-alternative transportation energy pathways on California’salternative transportation energy pathways on California’s

  12. Water Requirements for Future Energy production in California

    E-Print Network [OSTI]

    Sathaye, J.A.

    2011-01-01

    CALIFORNIA WATER RESOURCES. Water Demand Energy Suppon future forecasts of of Water energy predicted energy aunder these PHASE II: WATER ENERGY REQUIREMENTS FOR FUTURE

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

    Reports and Publications (EIA)

    1998-01-01

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

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

    E-Print Network [OSTI]

    Queener, Benjamin Daniel

    2012-01-01

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

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

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01

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

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

    E-Print Network [OSTI]

    Golden, Kenneth M.

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

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

    SciTech Connect (OSTI)

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

    2014-05-01

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

  18. Forecasting Prices andForecasting Prices and Congestion forCongestion for

    E-Print Network [OSTI]

    Tesfatsion, Leigh

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

  19. Compiler Comparisons

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

    Comparisons Compiler Comparisons Compiler Comparisons on Hopper There are five compilers available to users on Hopper, the NERSC XE6. All of the compilers on this system are...

  20. Comparison of building energy use data between the United States and China

    E-Print Network [OSTI]

    Xia Ph.D., Jianjun

    2014-01-01

    building operations, Energy and Buildings 33 (2001) [22]and large public building energy consumption statisticalsystems iSagy iSagy EPP Pulse Energy 1 hour 1 hour 15 min 15

  1. Fostering a Renewable Energy Technology Industry: An International Comparison of Wind Industry Policy Support Mechanisms

    E-Print Network [OSTI]

    Lewis, Joanna; Wiser, Ryan

    2005-01-01

    in the United States. Energy Policy. 33, 1397- BTM ConsultSources in Brazil. Energy Policy, 33, 1745-1752. Cerveny, M,the Netherlands and Denmark. Energy Policy, 32, 1625-1637.

  2. Determinants of energy intensity in industrialized countries : a comparison of China and India

    E-Print Network [OSTI]

    Huang, Feiya

    2006-01-01

    The amount of final energy per unit of economic output (usually in terms of gross domestic product, or GDP), known as energy intensity, is often used to measure the effectiveness of energy use and the consumption patterns ...

  3. Comparison of energy efficiency between variable refrigerant flow systems and ground source heat pump systems

    E-Print Network [OSTI]

    Hong, Tainzhen

    2010-01-01

    GSHP system is more energy efficient than the air-source VRFGSHP system is more energy efficient than the air-source VRVintended to be as energy efficient as required by current

  4. Fostering a Renewable Energy Technology Industry: An International Comparison of Wind Industry Policy Support Mechanisms

    E-Print Network [OSTI]

    Lewis, Joanna; Wiser, Ryan

    2005-01-01

    of the Politics of Wind Energy Innovation in California andon Grid Connected Wind Energy in China. http://www.nrel.gov/Jansen, J. , 1999. Indian Wind Energy Programme: Performance

  5. Alternative energy systems for Puerto Rico : analysis and comparison of anaerobic waste digestion

    E-Print Network [OSTI]

    Cuevas, Emil A. (Emil André Cuevas Meléndez)

    2006-01-01

    Energy prices in Puerto Rico are increasing constantly, making evident the need for alternative energy sources. Several methods to produce power have been developed as alternatives to burning petroleum, such as solar energy ...

  6. Load Forecasting of Supermarket Refrigeration

    E-Print Network [OSTI]

    @compute.dtu.dk www.compute.dtu.dk M.Sc.-2013-87 #12;Summary (English) The Danish power production coming from energy system. Observed refrigeration load and local ambient temperature from a Danish su- permarket renewable energy, is increasing, therefore a flexible energy system is needed. In the present Thesis

  7. National Renewable Energy Laboratory Pyrheliometer Comparisons: 24 September - 5 October 2012 (NPC-2012)

    SciTech Connect (OSTI)

    Stoffel, T.; Reda, I.

    2013-05-01

    The NREL Pyrheliometer Comparisons for 2012 (NPC-2012) were held at the Solar Radiation Research Laboratory in Golden, Colorado, from September 24 through October 5 for the purpose of transferring the World Radiometric Reference (WRR) to participating instrument. Twenty scientists and engineers operated 32 absolute cavity radiometers and 18 conventional thermopile-based pyrheliometers to simultaneously measure clear-sky direct normal irradiance during the comparisons. The transfer standard group of reference radiometers for NPC-2012 consisted of four NREL radiometers with direct traceability to the WRR, having participated in the Eleventh International Pyrheliometer Comparisons (IPC-XI) hosted by the World Radiation Center in the fall of 2010. As the result of NPC-2012, each participating absolute cavity radiometer was assigned a new WRR transfer factor, computed as the reference irradiance computed by the transfer standard group divided by the observed irradiance from the participating radiometer. The performance of the transfer standard group during NPC-2012 was consistent with previous comparisons, including IPC-XI. The measurement performance of the transfer standard group allowed the transfer of the WRR to each participating radiometer with an estimated uncertainty of +/- 0.33% with respect to the International System of Units.

  8. A Comparison of Iron and Steel Production Energy Use and Energy Intensity in China and the U.S.

    E-Print Network [OSTI]

    Hasanbeigi, Ali

    2012-01-01

    and CO2 Emissions. Paris: IEA. http://www.iea.org/w/id=298 International Energy Agency (IEA). 2008a. Energy2008 Edition. Paris: IEA. International Energy Agency (IEA).

  9. Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

    E-Print Network [OSTI]

    Dudley, Junqiao Han

    2010-01-01

    Study of Energy Efficiency in Buildings, Pacific Grove, CA,Study of Energy Efficiency in Buildings, Pacific Grove, CA,Study of Energy Efficiency in Buildings, Pacific Grove, CA,

  10. INTERNATIONAL COMPARISON OF RESIDENTIAL ENERGY USE: INDICATORS OF RESIDENTIAL ENERGY USE AND EFFICIENCY PART ONE: THE DATA BASE

    E-Print Network [OSTI]

    Schipper, L.

    2013-01-01

    sur . !. ! demande 5!. ' energie ~ long terme, sous-groupePour les Economies d' Energie (AEE). Anon. (ENI),1979. Endd'Etudes Regionales sur 1 'Energie" (CEREN) was formed. This

  11. INTERNATIONAL COMPARISON OF RESIDENTIAL ENERGY USE: INDICATORS OF RESIDENTIAL ENERGY USE AND EFFICIENCY PART ONE: THE DATA BASE

    E-Print Network [OSTI]

    Schipper, L.

    2013-01-01

    central heating. II-C-3 GERMANY Energy Use Indicators Unitelec/DI,(kWh/DM) II-C-9 GERMANY Energy Use Indicators NOTESYear: 1978 SFD: 49% GERMANY RESIDENTIAL ENERGY USE - GERMANY

  12. Review and comparison of web- and disk-based tools for residential energy analysis

    E-Print Network [OSTI]

    Mills, Evan

    2002-01-01

    cost and payback Twenty Percent Solution Western Massachusetts Online Energy Calculator Your California

  13. INTERNATIONAL COMPARISON OF RESIDENTIAL ENERGY USE: INDICATORS OF RESIDENTIAL ENERGY USE AND EFFICIENCY PART ONE: THE DATA BASE

    E-Print Network [OSTI]

    Schipper, L.

    2013-01-01

    Statistics, 1969-79, I 22. ETSU, Energy Technology Supportthe Department of Energy" (ETSU). Unfortunately, there arebeen recently calculated by ETSU (22). We have combined the

  14. Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

    E-Print Network [OSTI]

    Dudley, Junqiao Han

    2010-01-01

    2009. “Chilled Water Thermal Storage System and Demandwater supplied by thermal energy storage in the centralchilled water thermal energy storage (TES) tank provides

  15. Projections of Full-Fuel-Cycle Energy and Emissions Metrics

    E-Print Network [OSTI]

    Coughlin, Katie

    2013-01-01

    Laboratory. CAPP. 2011. Crude Oil Forecast, Markets &petroleum use per barrel of crude oil input. Refinery energy

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

    E-Print Network [OSTI]

    Heinemann, Detlev

    for the sum of on- and offshore production in Germany with a total capacity of 50GW would benefit fromShort-term Forecasting of Offshore Wind Farm Production ­ Developments of the Anemos Project J , R. A. Brownsword5 , I. Waldl6 1 ForWind ­ Center for Wind Energy Research, Institute of Physics

  17. Comparison of Real World Energy Consumption to Models and DOE Test Procedures

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based Fuels|Programs |ChartPresentations:UlJmately , the1Report 2009Comparison

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

    E-Print Network [OSTI]

    Raftery, Adrian

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

  19. New directions for forecasting air travel passenger demand

    E-Print Network [OSTI]

    Garvett, Donald Stephen

    1974-01-01

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

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

    E-Print Network [OSTI]

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

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

  1. The effect of multinationality on management earnings forecasts 

    E-Print Network [OSTI]

    Runyan, Bruce Wayne

    2005-08-29

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

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

    E-Print Network [OSTI]

    Chevis, Gia Marie

    2004-11-15

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

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

    E-Print Network [OSTI]

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

    2005-01-01

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

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

    E-Print Network [OSTI]

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

  5. Comparisons of HVAC Simulations between EnergyPlus and DOE-2.2 for Data Centers

    E-Print Network [OSTI]

    Hong, Tianzhen

    2009-01-01

    kWh) DOE?2.2 EnergyPlus % Difference Figure 7 – Monthly Cooling Electricity Consumption for Phoenix kWh) DOE?2.2 EnergyPlus % Difference Figure 8 – Monthly Cooling Electricity Consumption for Phoenix 

  6. Comparison of House and Senate Clean Energy Deployment Administration (CEDA) provisions

    E-Print Network [OSTI]

    Laughlin, Robert B.

    , and manufacturing technologies. Nuclear power and coal are eligible under the definition of "clean energy- Nuclear and Advanced Technologies of the American Clean Energy and Security Act (H.R. 2454) in the House makes the stabilization of greenhouse gases an option, by defining "clean energy technologies

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

    SciTech Connect (OSTI)

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

    2010-04-01

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

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

    SciTech Connect (OSTI)

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

    2010-04-15

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

  9. Transportation Energy Futures

    E-Print Network [OSTI]

    Sperling, Daniel

    1989-01-01

    s values, forecasts of future energy prices and politicalYergin, D. , eds. 1979. Energy Future: Report of the Energy02, Sacramento, Calif. ENERGY FUTURES 103. Ullman, T. L. ,

  10. Quantifying the credibility of energy projections from trends in

    E-Print Network [OSTI]

    Shlyakhter, Ilya

    probabilities. The outputs of energy supply and demand models and forecasts are frequently used as input Alexander I. Shlyakhter, Daniel M. Kammen, Claire L. Broido and Richard Wilson For energy forecasts the actual errors in past forecasts of over 170 energy pro- ducing and consuming sectors of the US eco- nomy

  11. Managerial Career Concerns and Earnings Forecasts SARAH SHAIKH

    E-Print Network [OSTI]

    Tipple, Brett

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

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

    E-Print Network [OSTI]

    McBurney, Peter

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

  13. Neural Network forecasts of the tropical Pacific sea surface temperatures

    E-Print Network [OSTI]

    Hsieh, William

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

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

    E-Print Network [OSTI]

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

  15. Forecasting Uncertainty Related to Ramps of Wind Power Production

    E-Print Network [OSTI]

    Boyer, Edmond

    Forecasting Uncertainty Related to Ramps of Wind Power Production Arthur Bossavy, Robin Girard - The continuous improvement of the accuracy of wind power forecasts is motivated by the increasing wind power. This paper presents two methods focusing on forecasting large and sharp variations in power output of a wind

  16. Choosing Words in Computer-Generated Weather Forecasts

    E-Print Network [OSTI]

    Reiter, Ehud

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

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

    E-Print Network [OSTI]

    Raftery, Adrian

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

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

    E-Print Network [OSTI]

    Heinemann, Detlev

    Accuracy of near real time updates in wind power forecasting with regard to different weather October 2007 #12;EMS/ECAM 2007 ­ Nadja Saleck Outline · Study site · Wind power forecasting - method #12;EMS/ECAM 2007 ­ Nadja Saleck Wind power forecast data observed wind power input (2004 ­ 2006

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

    E-Print Network [OSTI]

    Raftery, Adrian

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

  20. Forecasting Building Occupancy Using Sensor Network James Howard

    E-Print Network [OSTI]

    Hoff, William A.

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

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

    E-Print Network [OSTI]

    Claypool, Mark

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

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

    E-Print Network [OSTI]

    Claypool, Mark

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

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

    E-Print Network [OSTI]

    Doswell III, Charles A.

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

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

    E-Print Network [OSTI]

    Robock, Alan

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

  5. Energy dispatch schedule optimization and cost benefit analysis for grid-connected, photovoltaic-battery storage systems

    E-Print Network [OSTI]

    Nottrott, A.; Kleissl, J.; Washom, B.

    2013-01-01

    PV systems using storage and controls, Solar Energy 81(7) (of solar and load forecasting in demand side energy storageEnergy storage, Forecasting, Optimal scheduling, Solar power

  6. A Comparison of Iron and Steel Production Energy Use and Energy Intensity in China and the U.S.

    E-Print Network [OSTI]

    Hasanbeigi, Ali

    2012-01-01

    Intensity GJ/t kgce/t Primary Energy Intensity* GJ/t kgce/tIntensity GJ/t kgce/t Primary Energy Intensity* GJ/t kgce/Scenarios 1, 4 and 6 the primary energy value includes T&D

  7. Online short-term solar power forecasting

    SciTech Connect (OSTI)

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

    2009-10-15

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

  8. GENETIC ALGORITHM FORECASTING FOR TELECOMMUNICATIONS PRODUCTS

    E-Print Network [OSTI]

    Havlicek, Joebob

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

  9. Solar Forecasting System and Irradiance Variability Characterization

    E-Print Network [OSTI]

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

  10. Segmenting Time Series for Weather Forecasting

    E-Print Network [OSTI]

    Reiter, Ehud

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

  11. "FLIGHT PLAN" FORECASTS SEATTLE/TACOMA AND

    E-Print Network [OSTI]

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

  12. 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

  13. Stochastic Weather Generator Based Ensemble Streamflow Forecasting

    E-Print Network [OSTI]

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

  14. Comparison of the calorimetric and kinematic methods of neutrino energy reconstruction in disappearance experiments

    E-Print Network [OSTI]

    Ankowski, Artur M; Coloma, Pilar; Huber, Patrick; Jen, Chun-Min; Mariani, Camillo; Meloni, Davide; Vagnoni, Erica

    2015-01-01

    To be able to achieve their physics goals, future neutrino-oscillation experiments will need to reconstruct the neutrino energy with very high accuracy. In this work, we analyze how the energy reconstruction may be affected by realistic detection capabilities, such as energy resolutions, efficiencies, and thresholds. This allows us to estimate how well the detector performance needs to be determined a priori in order to avoid a sizable bias in the measurement of the relevant oscillation parameters. We compare the kinematic and calorimetric methods of energy reconstruction in the context of two muon-neutrino disappearance experiments operating in different energy regimes. For the calorimetric reconstruction method, we find that the detector performance has to be estimated with a ~10% accuracy to avoid a significant bias in the extracted oscillation parameters. On the other hand, in the case of kinematic energy reconstruction, we observe that the results exhibit less sensitivity to an overestimation of the dete...

  15. Comparisons of HVAC Simulations between EnergyPlus and DOE-2.2 for Data Centers

    SciTech Connect (OSTI)

    Hong, Tianzhen; Sartor, Dale; Mathew, Paul; Yazdanian, Mehry

    2008-08-13

    This paper compares HVAC simulations between EnergyPlus and DOE-2.2 for data centers. The HVAC systems studied in the paper are packaged direct expansion air-cooled single zone systems with and without air economizer. Four climate zones are chosen for the study - San Francisco, Miami, Chicago, and Phoenix. EnergyPlus version 2.1 and DOE-2.2 version 45 are used in the annual energy simulations. The annual cooling electric consumption calculated by EnergyPlus and DOE-2.2 are reasonablely matched within a range of -0.4percent to 8.6percent. The paper also discusses sources of differences beween EnergyPlus and DOE-2.2 runs including cooling coil algorithm, performance curves, and important energy model inputs.

  16. Departments of Energy and Commerce Announce New Partnership to...

    Energy Savers [EERE]

    Departments of Energy and Commerce Announce New Partnership to Further Cooperation on Renewable Energy Modeling and Forecasting Departments of Energy and Commerce Announce New...

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

    E-Print Network [OSTI]

    Webster, Peter J.

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

  18. Comparison of energy efficiency between variable refrigerant flow systems and ground source heat pump systems

    E-Print Network [OSTI]

    Hong, Tainzhen

    2010-01-01

    dual compressor available on the market Compared with the selected building, a more energy efficient building will have lower space cooling and heating

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

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01

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

  20. Comparison of the calorimetric and kinematic methods of neutrino energy reconstruction in disappearance experiments

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

    Ankowski, Artur M.; Benhar, Omar; Coloma, Pilar; Huber, Patrick; Jen, Chun -Min; Mariani, Camillo; Meloni, Davide; Vagnoni, Erica

    2015-10-22

    To be able to achieve their physics goals, future neutrino-oscillation experiments will need to reconstruct the neutrino energy with very high accuracy. In this work, we analyze how the energy reconstruction may be affected by realistic detection capabilities, such as energy resolutions, efficiencies, and thresholds. This allows us to estimate how well the detector performance needs to be determined a priori in order to avoid a sizable bias in the measurement of the relevant oscillation parameters. We compare the kinematic and calorimetric methods of energy reconstruction in the context of two ?? ? ?? disappearance experiments operating in different energymore »regimes. For the calorimetric reconstruction method, we find that the detector performance has to be estimated with an O(10%) accuracy to avoid a significant bias in the extracted oscillation parameters. Thus, in the case of kinematic energy reconstruction, we observe that the results exhibit less sensitivity to an overestimation of the detector capabilities.« less

  1. Comparison of 2006 IECC and 2009 IECC Commercial Energy Code Requirements for Kansas City, MO

    SciTech Connect (OSTI)

    Huang, Yunzhi; Gowri, Krishnan

    2011-03-22

    This report summarizes code requirements and energy savings of commercial buildings in climate zone 4 built to the 2009 IECC when compared to the 2006 IECC. In general, the 2009 IECC has higher insulation requirements for exterior walls, roof, and windows and have higher efficiency requirements for HVAC equipment (HVAC equipment efficiency requirements are governed by National Appliance Conversion Act of 1987 (NAECA), and are applicable irrespective of the IECC version adopted). The energy analysis results show that residential and nonresidential commercial buildings meeting the 2009 IECC requirements save between 6.1% and 9.0% site energy, and between 6.4% and 7.7% energy cost when compared to 2006 IECC. Analysis also shows that semiheated buildings have energy and cost savings of 3.9% and 5.6%.

  2. Comparison of the 1984 DOE/EIA annual energy outlook and the 1984 GRI baseline projection

    SciTech Connect (OSTI)

    Ashby, A.; Holtberg, P.; Woods, T.

    1985-01-01

    A comparative analysis of the Gas Research Institute (GRI) Baseline Projection of US Energy Supply and Demand with the DOE/EIA 1984 Annual Energy Outlook shows many similar assumptions, but many cases of widening differences between the projections of primary energy consumption and sector-specific energy consumption. The DOE/EIA expects a faster and more significant decline in the electricity to natural gas price ratio, lower sector-specific end-use prices of refined petroleum products, and a faster growth in industrial raw material energy demand. In contrast to the GRI report, it also omits an estimate of industrial cogeneration and does not retire any exisiting generating capacity. The report examines the basic assumptions and results of both projections using five scenarios. 17 tables.

  3. Combinatorial Evolution and Forecasting of Communication Protocol ZigBee

    E-Print Network [OSTI]

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

    2012-01-01

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

  4. Comparison of explosive and vibroseis source energy penetration during COCORP deep seismic reflection profiling in the Williston basin

    SciTech Connect (OSTI)

    Steer, D.N.; Brown, L.D.; Knapp, J.H.; Baird, D.J. [Cornell Univ., Ithaca, NY (United States)] [Cornell Univ., Ithaca, NY (United States)

    1996-01-01

    Comparison of high-fold (50) vibroseis recordings with coincident low-fold (6) explosive source data from deep reflection surveys in the Williston Basin indicates that while vibroseis generated energy decays to ambient noise levels at 7--9 s two-way traveltime (twtt) (20--30 km depth), energy from explosive sources remains above ambient levels to 35--60 s twtt (105--180 km depth). Moreover, single, moderately sized (30 kg) and well-placed charges proved to be as effective as larger (90 kg) sources at penetrating to mantle traveltimes in this area. However, the explosive source energy proved highly variable, with source-to-ground coupling being a major limiting factor in shot efficacy. Stacked results from the vibroseis sources provide superior imagery of shallow and moderate crustal levels by virtue of greater redundancy and shot-to-shot uniformity; shot statics, low fold, and ray-path distortion across the relatively large (24--30 km aperture) spreads used during the explosive recording have proven to be especially problematic in producing conventional seismic sections. In spite of these complications, the explosive source recording served its primary purpose in confirming Moho truncation and the presence of a dipping reflection fabric in the upper mantle along the western flank of the Trans-Hudson orogen buried beneath the Williston Basin.

  5. Chapter 9: Enabling Capabilities for Science and Energy | A Comparison of Research Funding Modalities

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on DeliciousMathematicsEnergy Headquarters Categorical| Department of Energy5: Lighting,ActionsEnergy 9 -9:9:

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

  7. Comparison of simplified models of urban climate for improved prediction of building energy use in cities

    E-Print Network [OSTI]

    Street, Michael A. (Michael Anthony)

    2013-01-01

    Thermal simulation of buildings is a requisite tool in the design of low-energy buildings, yet, definition of weather boundary conditions during simulation of urban buildings suffers from a lack of data that accounts for ...

  8. Optimisation and comparison of integrated models of direct-drive linear machines for wave energy conversion 

    E-Print Network [OSTI]

    Crozier, Richard Carson

    2014-06-30

    Combined electrical and structural models of five types of permanent magnet linear electrical machines suitable for direct-drive power take-off on wave energy applications are presented. Electromagnetic models were ...

  9. Comparison of energy efficiency between variable refrigerant flow systems and ground source heat pump systems

    E-Print Network [OSTI]

    Hong, Tainzhen

    2010-01-01

    tool for geothermal water loop heat pump systems, 9thInternational IEA Heat Pump Conference, Zürich, Switzerland,of ground source heat pump system in a near-zero energy

  10. Comparison of Building Energy Efficiency and Life Span for Different Envelopes 

    E-Print Network [OSTI]

    Li, Z.; Li, D.; Li, L.; Zhang, G.; Liu, J.

    2006-01-01

    life and provide occupants a more comfortable indoor climate. At the same time, this heat preservation technology can ensure building energy efficiency and economy. It is reasonable to adopt the external heat preservation wall mode to make the building...

  11. IMPLICATIONS OF INTERNATIONAL COMPARISONS OF ENERGY USE: THE SWEDISH/AMERICAN CASE REVIEWED

    E-Print Network [OSTI]

    Schipper, Lee

    2013-01-01

    Swedish experience 1s district heating, by which blocks (orfrom central plants. district heating save energy? How doesdistrict heat is produced with electricity depends on the charac- teristics of the heating

  12. BIOENERGIZEME INFOGRAPHIC CHALLENGE: Comparison of Bio-fuels to Other Commonly Used Forms of Energy

    Broader source: Energy.gov [DOE]

    This infographic was created by students from Sun Valley High School in Aston, PA, as part of the U.S. Department of Energy-BioenergizeME Infographic Challenge. The BioenergizeME Infographic...

  13. Improved Building Energy Performance Modelling through Comparison of Measured Data with Simulated Results 

    E-Print Network [OSTI]

    Bambrook, S.; Jacob, D.

    2008-01-01

    the building and comparing simulated results to the measured data. The simulated building energy performance results achieved in the first stage of computer modelling show a reasonable correlation with measured data, however, further work is required to create...

  14. Pathways to low-cost electrochemical energy storage: a comparison of aqueous and nonaqueous flow batteries

    E-Print Network [OSTI]

    Darling, Robert M.

    Energy storage is increasingly seen as a valuable asset for electricity grids composed of high fractions of intermittent sources, such as wind power or, in developing economies, unreliable generation and transmission ...

  15. Model documentation Natural Gas Transmission and Distribution Model of the National Energy Modeling System. Volume 1

    SciTech Connect (OSTI)

    1996-02-26

    The Natural Gas Transmission and Distribution Model (NGTDM) of the National Energy Modeling System is developed and maintained by the Energy Information Administration (EIA), Office of Integrated Analysis and Forecasting. This report documents the archived version of the NGTDM that was used to produce the natural gas forecasts presented in the Annual Energy Outlook 1996, (DOE/EIA-0383(96)). The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic approach, and provides detail on the methodology employed. Previously this report represented Volume I of a two-volume set. Volume II reported on model performance, detailing convergence criteria and properties, results of sensitivity testing, comparison of model outputs with the literature and/or other model results, and major unresolved issues.

  16. 1 Forecasting Greenhouse Gas Emissions from Urban Regions: 2 Microsimulation of Land Use and Transport Patterns in Austin, Texas

    E-Print Network [OSTI]

    Kockelman, Kara M.

    use electricity, natural gas and other energy sources regularly52 for space conditioning and powering1 Forecasting Greenhouse Gas Emissions from Urban Regions: 2 Microsimulation of Land Use 2030 household energy 26 demands and GHG emissions estimates are compared under five different land use

  17. A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height ADAM J. DEPPE AND WILLIAM A. GALLUS JR.

    E-Print Network [OSTI]

    McCalley, James D.

    University, Ames, Iowa (Manuscript received 2 October 2011, in final form 15 May 2013) ABSTRACT The Weather Research and Forecasting Model (WRF) with 10-km horizontal grid spacing was used to explore improvements.S. Department of Energy goal of having 20% of the nation's electrical energy from wind by 2030 will require

  18. FORECAST OF ENSEMBLE POWER PRODUCTION BY GRID-CONNECTED PV SYSTEMS Elke Lorenz*, Detlev Heinemann*, Hashini Wickramarathne*, Hans Georg Beyer +

    E-Print Network [OSTI]

    Heinemann, Detlev

    of Physics, Energy and Semiconductor Research Laboratory, Energy Meteorology Group, 26111 Oldenburg, GermanyH, Spicherer Straße 48, D-86157 Augsburg, Germany ABSTRACT: The contribution of power production by PV systemsFORECAST OF ENSEMBLE POWER PRODUCTION BY GRID-CONNECTED PV SYSTEMS Elke Lorenz*, Detlev Heinemann

  19. Using Wikipedia to forecast disease

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentric viewing system for light collectionEnergy

  20. Pathways to low-cost electrochemical energy storage: a comparison of aqueous and nonaqueous flow batteries

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

    Darling, Robert M.; Gallagher, Kevin G.; Kowalski, Jeffrey A.; Ha, Seungbum; Brushett, Fikile R.

    2014-11-01

    Energy storage is increasingly seen as a valuable asset for electricity grids composed of high fractions of intermittent sources, such as wind power or, in developing economies, unreliable generation and transmission services. However, the potential of batteries to meet the stringent cost and durability requirements for grid applications is largely unquantified. We investigate electrochemical systems capable of economically storing energy for hours and present an analysis of the relationships among technological performance characteristics, component cost factors, and system price for established and conceptual aqueous and nonaqueous batteries. We identified potential advantages of nonaqueous flow batteries over those based on aqueousmore »electrolytes; however, new challenging constraints burden the nonaqueous approach, including the solubility of the active material in the electrolyte. Requirements in harmony with economically effective energy storage are derived for aqueous and nonaqueous systems. The attributes of flow batteries are compared to those of aqueous and nonaqueous enclosed and hybrid (semi-flow) batteries. Flow batteries are a promising technology for reaching these challenging energy storage targets owing to their independent power and energy scaling, reliance on facile and reversible reactants, and potentially simpler manufacture as compared to established enclosed batteries such as lead–acid or lithium-ion.« less

  1. Comparisons on thin and thick neutron target for low energy proton beam

    SciTech Connect (OSTI)

    Zhong, B.; Yu, G.; Wang, X.; Wang, K. [Dept. of Engineering Physics, Tsinghua Univ., Beijing 100084 (China)

    2012-07-01

    As the progress on accelerator physics and neutronics, the compact neutron sources driven by low energy and high intensity beam are becoming extensively developed and researched all around the world. The neutron target of an accelerator driven neutron source is one of the key components, and the stability of the neutron target affect the operation and performance of the neutron facility. When a low energy proton is projected to the beryllium target, the main reaction is the inelastic scattering between the proton and extra-nuclear electrons. As the decreasing of proton energy, the rate of elastic scattering between proton and target nucleus begins to increase. When the energy of proton is very low, the pickup charge reaction begins to appear. Focus on the problems brought by high intensity proton beam such as proton implantation, radiation damages, heat deposition and gas production, we performed sufficient numerical simulations for both thin and thick target determined by proton range. The results show that the critical problem for thick target is the proton implantation, causing the forming of bubbles and beryllium flaked in vacuum. The thin target sacrifices a little neutron yield, but avoid the proton stopped in target, and decrease the radiation damage and energy deposition. (authors)

  2. A Comparison of Iron and Steel Production Energy Use and Energy Intensity in China and the U.S.

    E-Print Network [OSTI]

    Hasanbeigi, Ali

    2012-01-01

    f) and the NCV for each type of coal used (coal used as fueltonnes. Mt 10 9 kJ Energy type Raw coal Cleaned coal Otherin China (2006) Fuel Type Raw Coal Cleaned Coal Other

  3. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

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

    2014-12-30

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

  4. Two techniques for forecasting clear air turbulence 

    E-Print Network [OSTI]

    Arbeiter, Randolph George

    1977-01-01

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

  5. Comparison of Real World Energy Consumption to Models and DOE Test

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i p aDepartment ofCommercial GradeDepartment of Energyfuel

  6. Comparison of the Department of Energy's 2007, 2008, & 2009 Annual Employee Survey Results

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i n c i p aDepartment ofCommercial GradeDepartment of EnergyfuelDepartment

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

    SciTech Connect (OSTI)

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

    2015-08-05

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

  8. Fostering a Renewable Energy Technology Industry: An InternationalComparison of Wind Industry Policy Support Mechanisms

    SciTech Connect (OSTI)

    Lewis, Joanna; Wiser, Ryan

    2005-11-15

    This article examines the importance of national and sub-national policies in supporting the development of successful global wind turbine manufacturing companies. We explore the motivations behind establishing a local wind power industry, and the paths that different countries have taken to develop indigenous large wind turbine manufacturing industries within their borders. This is done through a cross-country comparison of the policy support mechanisms that have been employed to directly and indirectly promote wind technology manufacturing in twelve countries. We find that in many instances there is a clear relationship between a manufacturer's success in its home country market and its eventual success in the global wind power market. Whether new wind turbine manufacturing entrants are able to succeed will likely depend in part on the utilization of their turbines in their own domestic market, which in turn will be influenced by the annual size and stability of that market. Consequently, policies that support a sizable, stable market for wind power, in conjunction with policies that specifically provide incentives for wind power technology to be manufactured locally, are most likely to result in the establishment of an internationally competitive wind industry.

  9. Solar Wind Forecasting with Coronal Holes

    E-Print Network [OSTI]

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

    2007-01-09

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

  10. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

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

    2014-11-13

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

  11. Global disease monitoring and forecasting with Wikipedia

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

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

    2014-11-13

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

  12. Bloomberg New Energy Finance Carbon Markets formerly New Energy...

    Open Energy Info (EERE)

    Product: London-based carbon markets division of New Energy Finance which provides analysis, price forecasting, consultancy and risk management services relating to carbon....

  13. Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

    SciTech Connect (OSTI)

    Dudley, Junqiao Han; Black, Doug; Apte, Mike; Piette, Mary Ann; Berkeley, Pam

    2010-05-14

    We have studied a low energy building on a campus of the University of California. It has efficient heating, ventilation, and air conditioning (HVAC) systems, consisting of a dual-fan/dual-duct variable air volume (VAV) system. As a major building on the campus, it was included in two demand response (DR) events in the summers of 2008 and 2009. With chilled water supplied by thermal energy storage in the central plant, cooling fans played a critical role during DR events. In this paper, an EnergyPlus model of the building was developed and calibrated. We compared both whole-building and HVAC fan energy consumption with model predictions to understand why demand savings in 2009 were much lower than in 2008. We also used model simulations of the study building to assess pre-cooling, a strategy that has been shown to improve demand saving and thermal comfort in many types of building. This study indicates a properly calibrated EnergyPlus model can reasonably predict demand savings from DR events and can be useful for designing or optimizing DR strategies.

  14. CALIFORNIA ENERGY CALIFORNIA ENERGY DEMAND 2010-2020

    E-Print Network [OSTI]

    , and utilities. Ted Dang, Steven Mac, and Libbie Bessman prepared the historical energy consumption data. Miguel CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2010-2020 ADOPTED FORECAST Schwarzenegger, Governor #12; #12; CALIFORNIA ENERGY COMMISSION Chris Kavalec Tom Gorin

  15. Overall Energy Considerations for Algae Species Comparison and Selection in Algae-to-Fuels Processes

    SciTech Connect (OSTI)

    Link, D.; Kail, B.; Curtis, W.; Tuerk,A.

    2011-01-01

    The controlled growth of microalgae as a feedstock for alternative transportation fuel continues to receive much attention. Microalgae have the characteristics of rapid growth rate, high oil (lipid) content, and ability to be grown in unconventional scenarios. Algae have also been touted as beneficial for CO{sub 2} reuse, as algae can be grown using CO{sub 2} emissions from fossil-based energy generation. Moreover, algae does not compete in the food chain, lessening the 'food versus fuel' debate. Most often, it is assumed that either rapid production rate or high oii content should be the primary factor in algae selection for algae-to-fuels production systems. However, many important characteristics of algae growth and lipid production must be considered for species selection, growth condition, and scale-up. Under light limited, high density, photoautotrophic conditions, the inherent growth rate of an organism does not affect biomass productivity, carbon fixation rate, and energy fixation rate. However, the oil productivity is organism dependent, due to physiological differences in how the organisms allocate captured photons for growth and oil production and due to the differing conditions under which organisms accumulate oils. Therefore, many different factors must be considered when assessing the overall energy efficiency of fuel production for a given algae species. Two species, Chlorella vulgaris and Botryococcus braunii, are popular choices when discussing algae-to-fuels systems. Chlorella is a very robust species, often outcompeting other species in mixed-culture systems, and produces a lipid that is composed primarily of free fatty acids and glycerides. Botryococcus is regarded as a slower growing species, and the lipid that it produces is characterized by high hydrocarbon content, primarily C28-C34 botryococcenes. The difference in growth rates is often considered to be an advantage oiChlorella. However, the total energy captured by each algal species in the same photobioreactor system should be similar at light limited growth conditions based on photon flux. It is how the algae 'allocate' this energy captured that will vary: Data will be presented that shows that Botryococcus invests greater energy in oil production than Chlorella under these growth conditions. In essence, the Chlorella can grow 'fast and lean' or can be slowed to grow 'slow and fat'. The overall energy potential between the Chlorella and Botryococcus, then, becomes much more equivalent on a per-photon basis. This work will indicate an interesting relationship between two very different algae species, in terms of growth rate, lipid content and composition, and energy efficiency of the overall process. The presentation will indicate that in light-limited growth, it cannot be assumed that either rapid growth rate or lipid production rate can be used as stand-alone indicators of which species-lipid relationships will truly be more effective in algae-to-fuels scenarios.

  16. Cost and energy comparison study of above- and below-ground dwellings

    SciTech Connect (OSTI)

    Shapira, H.B.; Cristy, G.A.; Brite, S.E.; Yost, M.B.

    1983-08-01

    Designs of earth-sheltered (ES) homes were examined and compared with identical aboveground (AG) homes. The homes are identical except where changes were necessitated by earth-sheltering and energy conservation. The study involved design, construction costing, energy analysis, and life-cycle costing (LCC). It was concluded from this study that under present market conditions, if aboveground and earth-sheltered dwellings of equal size and quality are built on similar lots, the construction cost of the earth-sheltered structure compares poorly with that of the aboveground structure. Lowered operation and maintenance costs, including the lower fuel bills of the earth-sheltered structure, are outweighed by the current high interest rates, which cause an increase in monthly payments. 24 references.

  17. Low density expansion and isospin dependence of nuclear energy functional: comparison between relativistic and Skyrme models

    E-Print Network [OSTI]

    C. Providencia; D. P. Menezes; L. Brito; Ph. Chomaz

    2007-04-26

    In the present work we take the non relativistic limit of relativistic models and compare the obtained functionals with the usual Skyrme parametrization. Relativistic models with both constant couplings and with density dependent couplings are considered. While some models present very good results already at the lowest order in the density, models with non-linear terms only reproduce the energy functional if higher order terms are taken into account in the expansion.

  18. Entropy vs. energy waveform processing: A comparison based on the heat equation

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

    Hughes, Michael S.; McCarthy, John E.; Bruillard, Paul J.; Marsh, Jon N.; Wickline, Samuel A.

    2015-05-25

    Virtually all modern imaging devices collect electromagnetic or acoustic waves and use the energy carried by these waves to determine pixel values to create what is basically an “energy” picture. However, waves also carry “information”, as quantified by some form of entropy, and this may also be used to produce an “information” image. Numerous published studies have demonstrated the advantages of entropy, or “information imaging”, over conventional methods. The most sensitive information measure appears to be the joint entropy of the collected wave and a reference signal. The sensitivity of repeated experimental observations of a slowly-changing quantity may be definedmore »as the mean variation (i.e., observed change) divided by mean variance (i.e., noise). Wiener integration permits computation of the required mean values and variances as solutions to the heat equation, permitting estimation of their relative magnitudes. There always exists a reference, such that joint entropy has larger variation and smaller variance than the corresponding quantities for signal energy, matching observations of several studies. Moreover, a general prescription for finding an “optimal” reference for the joint entropy emerges, which also has been validated in several studies.« less

  19. Regional Analysis of Building Distributed Energy Costs and CO2 Abatement: A U.S. - China Comparison

    E-Print Network [OSTI]

    Mendes, Goncalo

    2014-01-01

    Study on Energy Efficiency in Buildings, Pacific Grove,Study on Energy Efficiency in Buildings, Pacific Grove,DOE), Energy Efficiency & Renewable Energy, Buildings Energy

  20. Turbulence-driven coronal heating and improvements to empirical forecasting of the solar wind

    SciTech Connect (OSTI)

    Woolsey, Lauren N.; Cranmer, Steven R.

    2014-06-01

    Forecasting models of the solar wind often rely on simple parameterizations of the magnetic field that ignore the effects of the full magnetic field geometry. In this paper, we present the results of two solar wind prediction models that consider the full magnetic field profile and include the effects of Alfvén waves on coronal heating and wind acceleration. The one-dimensional magnetohydrodynamic code ZEPHYR self-consistently finds solar wind solutions without the need for empirical heating functions. Another one-dimensional code, introduced in this paper (The Efficient Modified-Parker-Equation-Solving Tool, TEMPEST), can act as a smaller, stand-alone code for use in forecasting pipelines. TEMPEST is written in Python and will become a publicly available library of functions that is easy to adapt and expand. We discuss important relations between the magnetic field profile and properties of the solar wind that can be used to independently validate prediction models. ZEPHYR provides the foundation and calibration for TEMPEST, and ultimately we will use these models to predict observations and explain space weather created by the bulk solar wind. We are able to reproduce with both models the general anticorrelation seen in comparisons of observed wind speed at 1 AU and the flux tube expansion factor. There is significantly less spread than comparing the results of the two models than between ZEPHYR and a traditional flux tube expansion relation. We suggest that the new code, TEMPEST, will become a valuable tool in the forecasting of space weather.

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

    E-Print Network [OSTI]

    Adib, P.

    1992-01-01

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

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

    SciTech Connect (OSTI)

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

    2009-11-20

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

  3. Comparison between two methods of solution of coupled equations for low-energy scattering

    E-Print Network [OSTI]

    K. Amos; S. Karataglidis; D. van der Knijff; L. Canton; G. Pisent; J. P. Svenne

    2005-10-28

    Cross sections from low-energy neutron-nucleus scattering have been evaluated using a coupled channel theory of scattering. Both a coordinate-space and a momentum-space formalism of that coupled-channel theory are considered.A simple rotational model of the channel interaction potentials is used to find results using two relevant codes, ECIS97 and MCAS, so that they may be compared. The very same model is then used in the MCAS approach to quantify the changes that occur when allowance is made for effects of the Pauli principle.

  4. Comparison of Energy Efficiency and Power Density in Pressure Retarded Osmosis and Reverse Electrodialysis

    SciTech Connect (OSTI)

    Yip, NY; Elimelech, M

    2014-09-16

    Pressure retarded osmosis (PRO) and reverse electrodialysis (RED) are emerging membrane-based technologies that can convert chemical energy in salinity gradients to useful work. The two processes have intrinsically different working principles: controlled mixing in PRO is achieved by water permeation across salt-rejecting membranes, whereas RED is driven by ion flux across charged membranes. This study compares the energy efficiency and power density performance of PRO and RED with simulated technologically available membranes for natural, anthropogenic, and engineered salinity gradients (seawater-river water, desalination brine-wastewater, and synthetic hypersaline solutions, respectively). The analysis shows that PRO can achieve both greater efficiencies (54-56%) and higher power densities (2.4-38 W/m(2)) than RED (18-38% and 0.77-1.2 W/m(2)). The superior efficiency is attributed to the ability of PRO membranes to more effectively utilize the salinity difference to drive water permeation and better suppress the detrimental leakage of salts. On the other hand, the low conductivity of currently available ion exchange membranes impedes RED ion flux and, thus, constrains the power density. Both technologies exhibit a trade-off between efficiency and power density: employing more permeable but less selective membranes can enhance the power density, but undesired entropy production due to uncontrolled mixing increases and some efficiency is sacrificed. When the concentration difference is increased (i.e., natural -> anthropogenic -> engineered salinity gradients), PRO osmotic pressure difference rises proportionally but not so for RED Nernst potential, which has logarithmic dependence on the solution concentration. Because of this inherently different characteristic, RED is unable to take advantage of larger salinity gradients, whereas PRO power density is considerably enhanced. Additionally, high solution concentrations suppress the Donnan exclusion effect of the charged RED membranes, severely reducing the permselectivity and diminishing the energy conversion efficiency. This study indicates that PRO is more suitable to extract energy from a range of salinity gradients, while significant advancements in ion exchange membranes are likely necessary for RED to be competitive with PRO.

  5. Max Tech Appliance Design: Potential for Maximizing U.S. Energy Savings through Standards

    E-Print Network [OSTI]

    Garbesi, Karina

    2011-01-01

    Administration, Annual Energy Outlook. Can be downloaded at:forecasts in its Annual Energy Outlook (AEO) [2], based onaeo/overview/). In its Annual Energy Outlook (AEO) (http://

  6. Wind Levelized Cost of Energy: A Comparison of Technical and Financing Input Variables

    SciTech Connect (OSTI)

    Cory, K.; Schwabe, P.

    2009-10-01

    The expansion of wind power capacity in the United States has increased the demand for project development capital. In response, innovative approaches to financing wind projects have emerged and are proliferating in the U.S. renewable energy marketplace. Wind power developers and financiers have become more efficient and creative in structuring their financial relationships, and often tailor them to different investor types and objectives. As a result, two similar projects may use very different cash flows and financing arrangements, which can significantly vary the economic competitiveness of wind projects. This report assesses the relative impact of numerous financing, technical, and operating variables on the levelized cost of energy (LCOE) associated with a wind project under various financing structures in the U.S. marketplace. Under this analysis, the impacts of several financial and technical variables on the cost of wind electricity generation are first examined individually to better understand the relative importance of each. Then, analysts examine a low-cost and a high-cost financing scenario, where multiple variables are modified simultaneously. Lastly, the analysis also considers the impact of a suite of financial variables versus a suite of technical variables.

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

    E-Print Network [OSTI]

    Auffhammer, Maximilian

    2005-01-01

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

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

    E-Print Network [OSTI]

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

    2011-01-01

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

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

    E-Print Network [OSTI]

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

    2005-01-01

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

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

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

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

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

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

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

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

    SciTech Connect (OSTI)

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

    2015-12-08

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

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

    E-Print Network [OSTI]

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

    2006-01-01

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

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

    Office of Science (SC) Website

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

  15. The new Athens Center applied to Space Weather Forecasting

    SciTech Connect (OSTI)

    Mavromichalaki, H.; Sarlanis, C.; Souvatzoglou, G.; Mariatos, G.; Gerontidou, M.; Plainaki, C.; Papaioannou, A.; Tatsis, S. [University of Athens, Physics Department, Section of Nuclear and Particle Physics, Zografos 15771 Athens (Greece); Belov, A.; Eroshenko, E.; Yanke, V. [IZMIRAN, Russian Academy of Science, 1420092 Moscow (Russian Federation)

    2006-08-25

    The Sun provides most of the initial energy driving space weather and modulates the energy input from sources outside the solar system, but this energy undergoes many transformations within the various components of the solar-terrestrial system, which is comprised of the solar wind, magnetosphere and radiation belts, the ionosphere, and the upper and lower atmospheres of Earth. This is the reason why an Earth's based neutron monitor network can be used in order to produce a real time forecasting of space weather phenomena.Since 2004 a fully functioned new data analysis Center in real-time is in operation in Neutron Monitor Station of Athens University (ANMODAP Center) suitable for research applications. It provides a multi sided use of twenty three neutron monitor stations distributing in all world and operating in real-time given crucial information on space weather phenomena. In particular, the ANMODAP Center can give a preliminary alert of ground level enhancements (GLEs) of solar cosmic rays which can be registered around 20 to 30 minutes before the main part of lower energy particles. Therefore these energetic solar cosmic rays provide the advantage of forth warning. Moreover, the monitoring of the precursors of cosmic rays gives a forehand estimate on that kind of events should be expected (geomagnetic storms and/or Forbush decreases)

  16. Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.

    SciTech Connect (OSTI)

    Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M.

    2009-10-09

    We present a computational framework for integrating the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.

  17. Departments of Energy and Commerce Announce New Partnership to...

    Office of Environmental Management (EM)

    to further collaboration between the agencies on renewable energy modeling and weather forecasting, which will help enable the nation's renewable energy resources to be...

  18. EIA lowers forecast for summer gasoline prices

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural GasNatural GasEIA lowers forecast for summer gasoline prices

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

    E-Print Network [OSTI]

    Matson, David Michael

    1993-01-01

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

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

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01

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

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

    E-Print Network [OSTI]

    Jamieson, Bruce

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

  2. National forecast for geothermal resource exploration and development with techniques for policy analysis and resource assessment

    SciTech Connect (OSTI)

    Cassel, T.A.V.; Shimamoto, G.T.; Amundsen, C.B.; Blair, P.D.; Finan, W.F.; Smith, M.R.; Edeistein, R.H.

    1982-03-31

    The backgrund, structure and use of modern forecasting methods for estimating the future development of geothermal energy in the United States are documented. The forecasting instrument may be divided into two sequential submodels. The first predicts the timing and quality of future geothermal resource discoveries from an underlying resource base. This resource base represents an expansion of the widely-publicized USGS Circular 790. The second submodel forecasts the rate and extent of utilization of geothermal resource discoveries. It is based on the joint investment behavior of resource developers and potential users as statistically determined from extensive industry interviews. It is concluded that geothermal resource development, especially for electric power development, will play an increasingly significant role in meeting US energy demands over the next 2 decades. Depending on the extent of R and D achievements in related areas of geosciences and technology, expected geothermal power development will reach between 7700 and 17300 Mwe by the year 2000. This represents between 8 and 18% of the expected electric energy demand (GWh) in western and northwestern states.

  3. The Quality of a 48-Hours Wind Power Forecast Using the German and Danish Weather Prediction Model

    E-Print Network [OSTI]

    Heinemann, Detlev

    In countries showing high wind energy shares in the elec- trical power supply grid, a "wind power weatherThe Quality of a 48-Hours Wind Power Forecast Using the German and Danish Weather Prediction Model Laboratory, P.O. box 49, DK-4000 Roskilde, Tel/Fax: +45 4677 5095 / 5970 Gregor.Giebel@Risoe.DK Wind power

  4. A Framework of Short-Term Activity-Aware Load Forecasting Yong Ding, Martin Neumann and Michael Beigl

    E-Print Network [OSTI]

    Beigl, Michael

    the best use of electric energy and relieve the conflict between supply and demand [Niu et al., 2010]. However, inaccurate load forecasts will lead to not only monetary losses but also grid security losses), such as weather factors, climatic conditions, social activi- ties, and seasonal factors, past usage patterns

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

    E-Print Network [OSTI]

    Hering, Amanda S.

    2010-10-12

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

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

    E-Print Network [OSTI]

    Lawrence, Ramon

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

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

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

  8. Draft for Public Comment Appendix A. Demand Forecast

    E-Print Network [OSTI]

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

  9. A Deep Hybrid Model for Weather Forecasting Aditya Grover

    E-Print Network [OSTI]

    Horvitz, Eric

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

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

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

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

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

    E-Print Network [OSTI]

    Tesfatsion, Leigh

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

  13. Probabilistic forecasting of solar flares from vector magnetogram data

    E-Print Network [OSTI]

    Barnes, Graham

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

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

    E-Print Network [OSTI]

    Singhal, Gaurav

    2012-10-19

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

  15. Human Trajectory Forecasting In Indoor Environments Using Geometric Context

    E-Print Network [OSTI]

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

  16. MAINTENANCE, UPGRADE AND VERIFICATION OF OPERATIONAL FORECASTS OF

    E-Print Network [OSTI]

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

  17. Airplanes Aloft as a Sensor Network for Wind Forecasting

    E-Print Network [OSTI]

    Horvitz, Eric

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

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

    E-Print Network [OSTI]

    Freitas, Nando de

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

  19. Waste generation forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1995-FY 2002, September 1994 revision

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

    A comprehensive waste-forecasting task was initiated in FY 1991 to provide a consistent, documented estimate of the volumes of waste expected to be generated as a result of U.S. Department of Energy-Oak Ridge Operations (DOE-ORO) Environmental Restoration (ER) OR-1 Project activities. Continual changes in the scope and schedules for remedial action (RA) and decontamination and decommissioning (D&D) activities have required that an integrated data base system be developed that can be easily revised to keep pace with changes and provide appropriate tabular and graphical output. The output can then be analyzed and used to drive planning assumptions for treatment, storage, and disposal (TSD) facilities. The results of this forecasting effort and a description of the data base developed to support it are provided herein. The initial waste-generation forecast results were compiled in November 1991. Since the initial forecast report, the forecast data have been revised annually. This report reflects revisions as of September 1994.

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

    E-Print Network [OSTI]

    Marquez, Ricardo

    2012-01-01

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