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Sample records for forecast comparisons energy

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

    Energy.gov [DOE]

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

  2. probabilistic energy production forecasts

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    energy production forecasts - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary ...

  3. Solar Energy Market Forecast | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast AgencyCompany Organization: United States Department of Energy Sector:...

  4. Acquisition Forecast | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Acquisition Forecast Acquisition Forecast Acquisition Forecast It is the policy of the U.S. Department of Energy (DOE) to provide timely information to the public regarding DOE's forecast of future prime contracting opportunities and subcontracting opportunities which are available via the Department's major site and facilities management contractors. This forecast has been expanded to also provide timely status information for ongoing prime contracting actions that are valued in excess of the

  5. Data Collection and Comparison with Forecasted Unit Sales of...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types PDF icon Data Collection ...

  6. Forecast Energy | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Zip: 94965 Region: Bay Area Sector: Services Product: Intelligent Monitoring and Forecasting Services Year Founded: 2010 Website: www.forecastenergy.net Coordinates:...

  7. energy data + forecasting | OpenEI Community

    OpenEI (Open Energy Information) [EERE & EIA]

    energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in...

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

    SciTech Connect

    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.

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

    SciTech Connect

    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.

  10. Energy Conservation Program: Data Collection and Comparison with...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

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

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

    Energy Saver

    Taking Wind Forecasting to New Heights DOE Taking Wind Forecasting to New Heights May 18, 2015 - 3:24pm Addthis A 2013 study conducted for the U.S. Department of Energy (DOE) by ...

  12. Acquisition Forecast Download | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Acquisition Forecast Download Acquisition Forecast Download Click on the link to download a copy of the DOE HQ Acquisition Forecast. Acquisition-Forecast-2016-11-10.xlsx (70.03 KB) More Documents & Publications National Nuclear Security Administration - Juliana Heynes Small Business Program Manager Directory EA-1900: Notice of Availability of a Draft Environmental Assessment

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical

  14. 2016 Solar Forecasting Workshop | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Solar Forecasting Workshop 2016 Solar Forecasting Workshop On August 3, 2016, the SunShot Initiative's systems integration subprogram hosted the Solar Forecasting Workshop to convene experts in the areas of bulk power system operations, distribution system operations, weather and solar irradiance forecasting, and photovoltaic system operation and modeling. The goal was to identify the technical challenges and opportunities in solar forecasting as a capability that can significantly reduce the

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

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Elizabeth Torres Clayton Barrows Dave Bielen Aaron Bloom Greg Brinkman Brian W Bush Stuart Cohen Wesley Cole Paul Denholm Nicholas DiOrio Aron Dobos Kelly Eurek Janine Freeman Bethany Frew Pieter Gagnon Elaine Hale

  16. DOE Publishes New Forecast of Energy Savings from LED Lighting...

    Office of Environmental Management (EM)

    Addthis Related Articles DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting DOE Publishes Pricing and Efficacy Trend Analysis for Utility Program ...

  17. Wind Forecasting Improvement Project | Department of Energy

    Energy Saver

    Forecasting Improvement Project Wind Forecasting Improvement Project October 3, 2011 - 12:12pm Addthis This is an excerpt from the Third Quarter 2011 edition of the Wind Program ...

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

    Energy.gov [DOE] (indexed site)

    The sixth iteration of the Energy Savings Forecast of Solid-State Lighting in General Illumination Applications compares the annual lighting energy consumption in the U.S. with and ...

  19. The Wind Forecast Improvement Project (WFIP). A Public-Private Partnership Addressing Wind Energy Forecast Needs

    SciTech Connect

    Wilczak, James M.; Finley, Cathy; Freedman, Jeff; Cline, Joel; Bianco, L.; Olson, J.; Djalaova, I.; Sheridan, L.; Ahlstrom, M.; Manobianco, J.; Zack, J.; Carley, J.; Benjamin, S.; Coulter, R. L.; Berg, Larry K.; Mirocha, Jeff D.; Clawson, K.; Natenberg, E.; Marquis, M.

    2015-10-30

    The Wind Forecast Improvement Project (WFIP) is a public-private research program, the goals of which are to improve the accuracy of short-term (0-6 hr) wind power forecasts for the wind energy industry and then to quantify the economic savings that accrue from more efficient integration of wind energy into the electrical grid. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that include the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models to improve model initial conditions; and second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the U.S. (the upper Great Plains, and Texas), and included 12 wind profiling radars, 12 sodars, 184 instrumented tall towers and over 400 nacelle anemometers (provided by private industry), lidar, and several surface flux stations. Results demonstrate that a substantial improvement of up to 14% relative reduction in power root mean square error (RMSE) was achieved from the combination of improved NOAA numerical weather prediction (NWP) models and assimilation of the new observations. Data denial experiments run over select periods of time demonstrate that up to a 6% relative improvement came from the new observations. The use of ensemble forecasts produced even larger forecast improvements. Based on the success of WFIP, DOE is planning follow-on field programs.

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Forecasts Geothermal Achievements in 2015 Energy Department Forecasts Geothermal Achievements in 2015 The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector, including Jay Nathwani, Acting Director of the Energy Department's Geothermal Technologies Office. Nathwani shared achievements and challenges in the program's technical portfolio. The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector,

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

    SciTech Connect

    Lantz, E.; Hand, M.

    2010-05-01

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

  2. Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Wind Energy Predictable: New Profilers Provide Hourly Forecasts Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts May 11, 2016 - 6:48pm Addthis Balancing the power grid is an art-or at least a scientific study in chaos-and the Energy Department is hoping wind energy can take a greater role in the act. Yet, the intermittency of wind-sometimes it's blowing, sometimes it's not-makes adding it smoothly to the nation's electrical grid a challenge. If wind

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

    SciTech Connect

    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.

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

    Reports and Publications

    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.

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

    SciTech Connect

    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

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

    SciTech Connect

    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

  7. Forecast of transportation energy demand through the year 2010

    SciTech Connect

    Mintz, M.M.; Vyas, A.D.

    1991-04-01

    Since 1979, the Center for Transportation Research (CTR) at Argonne National Laboratory (ANL) has produced baseline projections of US transportation activity and energy demand. These projections and the methodologies used to compute them are documented in a series of reports and research papers. As the lastest in this series of projections, this report documents the assumptions, methodologies, and results of the most recent projection -- termed ANL-90N -- and compares those results with other forecasts from the current literature, as well as with the selection of earlier Argonne forecasts. This current forecast may be used as a baseline against which to analyze trends and evaluate existing and proposed energy conservation programs and as an illustration of how the Transportation Energy and Emission Modeling System (TEEMS) works. (TEEMS links disaggregate models to produce an aggregate forecast of transportation activity, energy use, and emissions). This report and the projections it contains were developed for the US Department of Energy's Office of Transportation Technologies (OTT). The projections are not completely comprehensive. Time and modeling effort have been focused on the major energy consumers -- automobiles, trucks, commercial aircraft, rail and waterborne freight carriers, and pipelines. Because buses, rail passengers services, and general aviation consume relatively little energy, they are projected in the aggregate, as other'' modes, and used primarily as scaling factors. These projections are also limited to direct energy consumption. Projections of indirect energy consumption, such as energy consumed in vehicle and equipment manufacturing, infrastructure, fuel refining, etc., were judged outside the scope of this effort. The document is organized into two complementary sections -- one discussing passenger transportation modes, and the other discussing freight transportation modes. 99 refs., 10 figs., 43 tabs.

  8. OpenEI Community - energy data + forecasting

    OpenEI (Open Energy Information) [EERE & EIA]

  9. DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting

    Energy.gov [DOE]

    DOE has published a new report forecasting the energy savings of LED white-light sources compared with conventional white-light sources. The sixth iteration of the Energy Savings Forecast of Solid...

  10. Solar Forecast Improvement Project | Department of Energy

    Energy Saver

    Energy Systems Integration » Solar Energy Grid Integration Systems-Advanced Concepts Solar Energy Grid Integration Systems-Advanced Concepts On September 1, 2011, DOE announced $25.9 million to fund eight solar projects that are targeting ways to develop power electronics and build smarter, more interactive systems and components so that solar energy can be integrated into the electric power distribution and transmission grid at higher levels. Part of the SunShot Systems Integration

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

    SciTech Connect

    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

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

    SciTech Connect

    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.

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

    SciTech Connect

    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.

  14. LED Lighting Forecast | Department of Energy

    Energy Saver

    Research & Development » Technology Application R&D » LED Lighting Facts LED Lighting Facts LED lighting facts - A Program of the U.S. DOE DOE's LED Lighting Facts® program showcases LED products for general illumination from manufacturers who commit to testing products and reporting performance results according to industry standards. For lighting buyers, designers, and energy efficiency programs, the program provides information essential to evaluating SSL products. Central to the

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast December 7, 2012 - 10:00am Addthis The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods

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

    SciTech Connect

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

    2005-02-09

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

  17. Energy Savings Forecast of Solid-State Lighting in General Illuminatio...

    Energy Saver

    (1.54 MB) More Documents & Publications Energy Savings Potential of Solid-State Lighting in General Illumination Applications - Report 2016 SSL Forecast Report LED ADOPTION REPORT

  18. ANL Software Improves Wind Power Forecasting | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ANL Software Improves Wind Power Forecasting ANL Software Improves Wind Power Forecasting May 1, 2012 - 3:19pm Addthis This is an excerpt from the Second Quarter 2012 edition of the Wind Program R&D Newsletter. Since 2008, Argonne National Laboratory and INESC TEC (formerly INESC Porto) have conducted a research project to improve wind power forecasting and better use of forecasting in electricity markets. One of the main results from the project is ARGUS PRIMA (PRediction Intelligent

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

    SciTech Connect

    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.

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

    SciTech Connect

    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

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

    SciTech Connect

    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

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

    SciTech Connect

    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

  3. Draft forecast of the final report for the comparison to 40 CFR Part 191, Subpart B, for the Waste Isolation Pilot Plant

    SciTech Connect

    Bertram-Howery, S.G.; Marietta, M.G.; Anderson, D.R.; Gomez, L.S.; Rechard, R.P. ); Brinster, K.F.; Guzowski, R.V. )

    1989-12-01

    The United States Department of Energy is planning to dispose of transuranic wastes, which have been generated by defense programs, at the Waste Isolation Pilot Plant. The WIPP Project will assess compliance with the requirements of the United States Environmental Protection Agency. This report forecasts the planned 1992 document, Comparison to 40 CFR, Part 191, Subpart B, for the Waste Isolation Pilot Plant (WIPP). 130 refs., 36 figs., 11 tabs.

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Improve Wind Forecasting Energy Department Announces $2.5 Million to Improve Wind Forecasting January 8, 2015 - 12:00pm Addthis The Energy Department today announced $2.5 million for a new project to research the atmospheric processes that generate wind in mountain-valley regions. This in-depth research, conducted by Vaisala of Louisville, Colorado, will be used to improve the wind industry's weather models for short-term wind forecasts, especially for those issued less

  5. Energy Forecasting Framework and Emissions Consensus Tool (EFFECT...

    OpenEI (Open Energy Information) [EERE & EIA]

    Tool (EFFECT) EFFECT is an open, Excel-based modeling tool used to forecast greenhouse gas emissions from a range of development scenarios at the regional and national levels....

  6. Energy Conservation Program: Data Collection and Comparison with...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    forecasted unit sales of five lamp types is an action issued by the Department of Energy. ... with Forecasted Unit Sales of Five Lamp Types AGENCY: Office of Energy Efficiency ...

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

    Office of Energy Efficiency and Renewable Energy (EERE)

    Report forecasting the U.S. energy savings of LED white-light sources compared to conventional white-light sources (i.e., incandescent, halogen, fluorescent, and high-intensity discharge) over the...

  8. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect

    Not Available

    1993-12-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

  9. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect

    1995-01-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

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

    SciTech Connect

    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

    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. Final Report on California Regional Wind Energy Forecasting Project:Application of NARAC Wind Prediction System

    SciTech Connect

    Chin, H S

    2005-07-26

    Wind power is the fastest growing renewable energy technology and electric power source (AWEA, 2004a). This renewable energy has demonstrated its readiness to become a more significant contributor to the electricity supply in the western U.S. and help ease the power shortage (AWEA, 2000). The practical exercise of this alternative energy supply also showed its function in stabilizing electricity prices and reducing the emissions of pollution and greenhouse gases from other natural gas-fired power plants. According to the U.S. Department of Energy (DOE), the world's winds could theoretically supply the equivalent of 5800 quadrillion BTUs of energy each year, which is 15 times current world energy demand (AWEA, 2004b). Archer and Jacobson (2005) also reported an estimation of the global wind energy potential with the magnitude near half of DOE's quote. Wind energy has been widely used in Europe; it currently supplies 20% and 6% of Denmark's and Germany's electric power, respectively, while less than 1% of U.S. electricity is generated from wind (AWEA, 2004a). The production of wind energy in California ({approx}1.2% of total power) is slightly higher than the national average (CEC & EPRI, 2003). With the recently enacted Renewable Portfolio Standards calling for 20% of renewables in California's power generation mix by 2010, the growth of wind energy would become an important resource on the electricity network. Based on recent wind energy research (Roulston et al., 2003), accurate weather forecasting has been recognized as an important factor to further improve the wind energy forecast for effective power management. To this end, UC-Davis (UCD) and LLNL proposed a joint effort through the use of UCD's wind tunnel facility and LLNL's real-time weather forecasting capability to develop an improved regional wind energy forecasting system. The current effort of UC-Davis is aimed at developing a database of wind turbine power curves as a function of wind speed and

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

    SciTech Connect

    Hnilo, J J

    2006-03-17

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

  14. A comparison of model short-range forecasts and the ARM Microbase data

    SciTech Connect

    Hnilo, J J

    2006-09-22

    For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the 'Microbase' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both TWP and NSA. The Microbase data have been averaged to 35 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3hourly data for direct comparison to our model output.

  15. A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations

    SciTech Connect

    Hnilo, J.

    2006-03-17

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

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

    SciTech Connect

    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

  17. 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

    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.

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    New Forecasting Tools Enhance Wind Energy Integration in Idaho and Oregon Page 1 Under the American Recovery and Reinvestment Act of 2009, the U.S. Department of Energy and the electricity industry have jointly invested over $7.9 billion in 99 cost-shared Smart Grid Investment Grant projects to modernize the electric grid, strengthen cybersecurity, improve interoperability, and collect an unprecedented level of data on smart grid and customer operations. 1. Summary Idaho Power Company (IPC)

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

    SciTech Connect

    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.

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

    SciTech Connect

    Eisenberg, Joel F.

    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.

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

    Reports and Publications

    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.

  2. Report Summary: Energy Savings Forecast of SSL in General Illumination

    Energy Saver

    No. U.S. Department of Eney Release Date: WR-B-95-06 Office of Inspector General May 5, 1995 Report on Audit of Construction of Protective Force Training Faciliti at the Pantex Plant This report can be obtained from the U.S. Department of Energy Office of Scientific and Technical Information P.O. Box 62 Oak Ridge, Tennessee 37831 S tPrined wth soy ink n recycled pper U.S. DEPARTMENT OF ENERGY OFFICE OF INSPECTOR GENERAL AUDIT OF CONSTRUCTION OF PROTECTIVE FORCE TRAINING FACILITIES AT THE PANTEX

  3. Webinar: Forecasting Wind Energy Costs and Cost Drivers | Department of

    Energy Saver

    | Department of Energy Assistance Program (WAP) Closeout Frequently Asked Questions Weatherization Assistance Program (WAP) Closeout Frequently Asked Questions This document provides a list of frequently asked questions in regards to the Weatherization Assistance Program (WAP) Closeout procedures. wap_closeout_faqs.pdf (379.35 KB) More Documents & Publications WPN 12-3: Closeout Procedures for Recovery Act Grants Under the Weatherization Assistance Program CLOSEOUT PROCEDURES FOR

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

    SciTech Connect

    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.

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

    SciTech Connect

    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.

  6. Energy Conservation Program: Data Collection and Comparison with...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    unit sales of five lamp types, is a rulemaking action issued by the Department of Energy. ... with Forecasted Unit Sales of Five Lamp Types AGENCY: Office of Energy Efficiency ...

  7. Ocean thermal energy conversion: Historical highlights, status, and forecast

    SciTech Connect

    Dugger, G.L.; Avery, W.H.; Francis, E.J.; Richards, D.

    1983-07-01

    In 1881, d'Arsonval conceived the closed-Rankine-cycle ocean thermal energy conversion (OTEC) system in which a working fluid is vaporized by heat exchange with cold water drawn from a 700-1200 m depth. In 1930, Claude demonstrated an open-cycle process in Cuba. Surface water was flash-vaporized at 3 kPa to drive a turbine directly (no secondary working fluid) and then was condensed by direct contact with water drawn from a 700-m depth through a 1.6m-diam, 1.75-km-long cold-water pipe (CWP). From a delta T of 14/sup 0/C his undersized turbine generated 22 kW. In 1956 a French team designed a 3.5-MW (net) open-cycle plant for installation off Abidjan on the Ivory Coast of Africa and demonstrated the necessary CWP deployment. The at-sea demonstrations by Mini-OTEC and OTEC-1 and other recent advances in OTEC technology summarized herein represent great progress. All of the types of plants proposed for the DOE's PON program may be worthy of development; certainly work on a grazing plant is needed. Our estimates indicate that the U.S. goals established by Public Law 96-310 leading to 10 GW of OTEC power and energy product equivalents by 1999 are achievable, provided that adequate federal financial incentives are retained to assure the building of the first few plants.

  8. 3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    TIER Environmental Forecast Group Inc 3TIER Jump to: navigation, search Name: 3TIER Environmental Forecast Group Inc (3TIER) Place: Seattle, Washington Zip: 98121 Sector: Renewable...

  9. Notice of Intent to Issue Solar Forecasting 2 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Solar Forecasting 2 Notice of Intent to Issue Solar Forecasting 2 Subprogram: Systems Integration Funding Number: DE-FOA-0001658 Funding Amount: $10,000,000 The SunShot Initiative intends to release a funding opportunity announcement (FOA) to support advancements in solar forecasting to enable higher penetration of solar power in the electric grid. The Solar Forecasting 2 FOA will focus on improving solar forecasting skills, especially during challenging conditions, such as partly cloudy weather

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

    SciTech Connect

    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.

  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

    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. A Comparison of Model Short-Range Forecasts and the ARM Microbase Data Fourth Quarter ARM Science Metric

    SciTech Connect

    Hnilo, J.

    2006-09-19

    For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the “Microbase” value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both TWP and NSA. The Microbase data have been averaged to 35 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3hourly data for direct comparison to our model output.

  13. Short-term energy outlook annual supplement, 1993

    SciTech Connect

    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.

  14. Short-term energy outlook, annual supplement 1994

    SciTech Connect

    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.

  15. Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast -- Improvement via Situation Dependent Error Correction

    SciTech Connect

    Lu, Siyuan; Hwang, Youngdeok; Khabibrakhmanov, Ildar; Marianno, Fernando J.; Shao, Xiaoyan; Zhang, Jie; Hodge, Bri-Mathias; Hamann, Hendrik F.

    2015-07-15

    With increasing penetration of solar and wind energy to the total energy supply mix, the pressing need for accurate energy forecasting has become well-recognized. Here we report the development of a machine-learning based model blending approach for statistically combining multiple meteorological models for improving the accuracy of solar/wind power forecast. Importantly, we demonstrate that in addition to parameters to be predicted (such as solar irradiance and power), including additional atmospheric state parameters which collectively define weather situations as machine learning input provides further enhanced accuracy for the blended result. Functional analysis of variance shows that the error of individual model has substantial dependence on the weather situation. The machine-learning approach effectively reduces such situation dependent error thus produces more accurate results compared to conventional multi-model ensemble approaches based on simplistic equally or unequally weighted model averaging. Validation over an extended period of time results show over 30% improvement in solar irradiance/power forecast accuracy compared to forecasts based on the best individual model.

  16. Indicators of energy efficiency: An international comparison

    SciTech Connect

    Not Available

    1990-07-01

    The United States has long been accused of being energy inefficient based on a comparison of energy intensities among the industrialized countries. Energy intensity is commonly measured by computing the ratio of energy use per unit of Gross Domestic Product (GDP). This is not a true measure of efficiency, however, because it does not account for differences in the standard of living, differences in population densities, or other factors. After corrections are made to account for these factors, the United States often appears to be as efficient or more efficient than many of the other industrialized countries. In this analysis the industrialized economies considered are the Group of Seven (G7): the United States, Canada, Japan, France, Italy, West Germany, and the United Kingdom. In summary, since 1970 the United States has improved the efficiency of energy use as much or more than have the other G-7 countries. Frequently, the United States is more efficient in its use of energy than are other G-7 countries. Many of the differences in energy use result from the fact that the United States has the comparative advantage of abundant indigenous energy supplies which have been used to develop large energy intensive but not necessarily inefficient petrochemical, and primary metals industries. The United States continues to hold this advantage, producing 50 percent more energy in 1988 than did all the remaining G-7 countries combined. 12 figs.

  17. Distributed Wind Policy Comparison Tool Website | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    TOOL Name: Distributed Wind Policy Comparison Tool Website Focus Area: Renewable Energy Topics: Security & Reliability Website: www.eformativeoptions.comdwpolicytool...

  18. Ramping Effect on Forecast Use: Integrated Ramping as a Mitigation Strategy; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Diakov, Victor; Barrows, Clayton; Brinkman, Gregory; Bloom, Aaron; Denholm, Paul

    2015-06-23

    Power generation ramping between forecasted (net) load set-points shift the generation (MWh) from its scheduled values. The Integrated Ramping is described as a method that mitigates this problem.

  19. Solar Forecasting Technical Workshop

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Forecasting Technical Workshop August 3, 2016 901 D St SW, Suite #930, Washington, DC Agenda 8:00-8:30 Check-in 8:30-8:45 Welcome & Opening remarks Guohui Yuan, DOE 8:45-9:15 Overview of Motivation and Techniques for Solar Forecasting Jan Kleissl, UCSD 9:15-9:45 Collaborative Research on Solar Power Forecasting: Challenges, Methods, and Assessment Tara Jensen, NCAR 9:45-10:00 Break 10:00-10:30 Machine-learning Based Enhancements for Renewable Energy Forecasting: From Research to Applications

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

    SciTech Connect

    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

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

    SciTech Connect

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

    2010-09-01

    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 power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique

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

    Office of Scientific and Technical Information (OSTI)

    Title: Comparison of Software Models for Energy Savings from Cool Roofs A web-based Roof ... This tool employs modern web technologies, usability design, and national average defaults ...

  3. Comparison of software models for energy savings from cool roofs...

    Office of Scientific and Technical Information (OSTI)

    Comparison of software models for energy savings from cool roofs Citation Details In-Document Search This content will become publicly available on September 4, 2017 Title: ...

  4. 2016 SSL Forecast Report

    Energy.gov [DOE]

    The DOE report, Energy Savings Forecast of Solid-State Lighting in General Illumination Applications, is a biannual report which models the adoption of LEDs in the U.S. general-lighting market,...

  5. SSL Forecast Report

    Energy.gov [DOE]

    The DOE report, Energy Savings Forecast of Solid-State Lighting in General Illumination Applications, is the latest edition of a biannual report which models the adoption of LEDs in the U.S....

  6. An Energy Evolution:Alternative Fueled Vehicle Comparisons | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy An Energy Evolution:Alternative Fueled Vehicle Comparisons An Energy Evolution:Alternative Fueled Vehicle Comparisons Presented at the U.S. Department of Energy Light Duty Vehicle Workshop in Washington, D.C. on July 26, 2010. evolution_alternative_vehicle.pdf (2.22 MB) More Documents & Publications Fuel Cell and Battery Electric Vehicles Compared Low-Cost Hydrogen-from-Ethanol: A Distributed Production System Asia/ITS

  7. Seismic energy data analysis of Merapi volcano to test the eruption time prediction using materials failure forecast method (FFM)

    SciTech Connect

    Anggraeni, Novia Antika

    2015-04-24

    The test of eruption time prediction is an effort to prepare volcanic disaster mitigation, especially in the volcano’s inhabited slope area, such as Merapi Volcano. The test can be conducted by observing the increase of volcanic activity, such as seismicity degree, deformation and SO2 gas emission. One of methods that can be used to predict the time of eruption is Materials Failure Forecast Method (FFM). Materials Failure Forecast Method (FFM) is a predictive method to determine the time of volcanic eruption which was introduced by Voight (1988). This method requires an increase in the rate of change, or acceleration of the observed volcanic activity parameters. The parameter used in this study is the seismic energy value of Merapi Volcano from 1990 – 2012. The data was plotted in form of graphs of seismic energy rate inverse versus time with FFM graphical technique approach uses simple linear regression. The data quality control used to increase the time precision employs the data correlation coefficient value of the seismic energy rate inverse versus time. From the results of graph analysis, the precision of prediction time toward the real time of eruption vary between −2.86 up to 5.49 days.

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

    SciTech Connect

    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.

  9. EIA lowers forecast for summer gasoline prices

    Energy Information Administration (EIA) (indexed site)

    EIA lowers forecast for summer gasoline prices U.S. gasoline prices are expected to be ... according to the new monthly forecast from the U.S. Energy Information Administration. ...

  10. The Value of Wind Power Forecasting

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

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

  11. July 2016 Systems Integration Solar Forecasting:

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    2016 Systems Integration Solar Forecasting: Maximizing its value for grid integration Introduction The forecasting of power generated by variable energy resources such as wind and solar has been the focus of academic and industrial research and development for as long as significant amounts of these renewable energy resources have been connected to the electric grid. The progress of forecasting capabilities has largely followed the penetration of the respective resources, with wind forecasting

  12. Solar Forecasting

    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....

  13. DOE Announces Webinars on Real Time Energy Management, Solar Forecasting Metrics, and More

    Energy.gov [DOE]

    EERE offers webinars to the public on a range of subjects, from adopting the latest energy efficiency and renewable energy technologies to training for the clean energy workforce. Webinars are free; however, advanced registration is typically required. You can also watch archived webinars and browse previously aired videos, slides, and transcripts.

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

    SciTech Connect

    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.

  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

    Eisenberg, Joel Fred

    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. Funding Opportunity Announcement: Solar Forecasting 2 | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Solar Forecasting 2 Funding Opportunity Announcement: Solar Forecasting 2 Subprogram: Systems Integration Funding Number: DE-FOA-0001649 Funding Amount: $10 million Description The Solar Forecasting 2 funding program will support projects that enable grid operators to better forecast how much solar energy will be added to the grid and accelerate the integration of these forecasts into energy management systems used by grid operators and utility companies. These tools will enable grid

  17. Forecast Change

    Annual Energy Outlook

    Forecast Change 2011 2012 2013 2014 2015 2016 from 2015 United States Usage (kWh) 3,444 3,354 3,129 3,037 3,151 3,302 4.8% Price (centskWh) 12.06 12.09 12.58 13.04 12.95 12.84 ...

  18. Notice of Intent to Issue Solar Forecasting II | Department of Energy

    Energy Saver

    and Systems (PVRD2) | Department of Energy Photovoltaic Research and Development 2: Modules and Systems (PVRD2) Notice of Intent to Issue Photovoltaic Research and Development 2: Modules and Systems (PVRD2) Subprogram: Photovoltaics Funding Number: DE-FOA-0001657 Funding Amount: $25,000,000 The SunShot Initiative intends to release a funding opportunity announcement (FOA) to support improvements in photovoltaic module design as well as approaches to reduce installation and interconnection

  19. Up and down: energy and cost comparison

    SciTech Connect

    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.

  20. NREL: Resource Assessment and Forecasting Home Page

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    are used to plan and develop renewable energy technologies and support climate change research. Learn more about NREL's resource assessment and forecasting research:...

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations | Department of Energy 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 Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The Wind Forecast Improvement

  2. Comparison of software models for energy savings from cool roofs

    DOE PAGES [OSTI]

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

    2015-06-07

    For this study, 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. RSC simulates multiple roof and attic technologies for side-by-side comparison including reflective roofs, different roof slopes, above sheathing ventilation, radiant barriers, low-emittance roof surfaces, duct location, duct leakage rates, multiple substrate types, and insulation levels. Annual simulations of hour-by-hour, whole-building performance are used to provide estimated annual energy and cost savings from reduced HVAC use. While RSC reported similar cooling savingsmore » to other simulation engines, heating penalty varied significantly. RSC results show reduced 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. Also included are comparisons to previous simulation-based studies, analysis 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. Finally, radiant heat transfer and duct interaction not previously modeled is considered a major contributor to heating penalties.« less

  3. Comparison of software models for energy savings from cool roofs

    SciTech Connect

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

    2015-06-07

    For this study, 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. RSC simulates multiple roof and attic technologies for side-by-side comparison including reflective roofs, different roof slopes, above sheathing ventilation, radiant barriers, low-emittance roof surfaces, duct location, duct leakage rates, multiple substrate types, and insulation levels. Annual simulations of hour-by-hour, whole-building performance are used to provide estimated annual energy and cost savings from reduced HVAC use. While RSC reported similar cooling savings to other simulation engines, heating penalty varied significantly. RSC results show reduced 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. Also included are comparisons to previous simulation-based studies, analysis 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. Finally, radiant heat transfer and duct interaction not previously modeled is considered a major contributor to heating penalties.

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

    SciTech Connect

    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.

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

    SciTech Connect

    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.

  6. Intermediate future forecasting system

    SciTech Connect

    Gass, S.I.; Murphy, F.H.; Shaw, S.H.

    1983-12-01

    The purposes of the Symposium on the Department of Energy's Intermediate Future Forecasting System (IFFS) were: (1) to present to the energy community details of DOE's new energy market model IFFS; and (2) to have an open forum in which IFFS and its major elements could be reviewed and critiqued by external experts. DOE speakers discussed the total system, its software design, and the modeling aspects of oil and gas supply, refineries, electric utilities, coal, and the energy economy. Invited experts critiqued each of these topics and offered suggestions for modifications and improvement. This volume documents the proceedings (papers and discussion) of the Symposium. Separate abstracts have been prepared for each presentation for inclusion in the Energy Data Base.

  7. Text-Alternative Version LED Lighting Forecast

    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....

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

    SciTech Connect

    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 2C 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 2C target could potentially become out of reach.

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Comparison of Fuel Cell Technologies: Fact Sheet Comparison of Fuel Cell Technologies: Fact Sheet An overview comparison of fuel cell technologies by the Fuel Cell Technologies Office. Comparison of Fuel Cell Technologies (436.24 KB) More Documents & Publications Hydrogen and Fuel Cell Technologies Program: Fuel Cells Fact Sheet Fuel Cells Fact Sheet MCFC and PAFC R&D Workshop Summary Report

  10. Improving the Accuracy of Solar Forecasting Funding Opportunity |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Improving the Accuracy of Solar Forecasting Funding Opportunity Improving the Accuracy of Solar Forecasting Funding Opportunity Through the Improving the Accuracy of Solar Forecasting Funding Opportunity, DOE is funding solar projects that are helping utilities, grid operators, solar power plant owners, and other stakeholders better forecast when, where, and how much solar power will be produced at the desired locations in the United States. More accurate solar

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Funding Modalities High-Performance Computing Capabilities and Allocations User Facility Statistics Examples and Case Studies ENERGY U.S. DEPARTMENT OF Quadrennial Technology Review 2015 1 Quadrennial Technology Review 2015 A Comparison of Research Center Funding Modalities Chapter 9: Enabling Capabilities for Science and Energy A Comparison of Multi-disciplinary, Multi-scale Research Center Funding Modalities Three Department of Energy (DOE) research center modalities-the Energy Frontier

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Procedures | Department of Energy Comparison of Real World Energy Consumption to Models and DOE Test Procedures Comparison of Real World Energy Consumption to Models and DOE Test Procedures This study investigates the real-world 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 actually replicate real world conditions, whether performance degrades over time, and whether

  13. DOE Announces Webinars on Solar Forecasting Metrics, the DOE...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    DOE Announces Webinars on Solar Forecasting Metrics, the DOE ... from adopting the latest energy efficiency and renewable ... to liquids technology, advantages of using natural gas, ...

  14. Radar Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    forecasts for solar-energy applications and 2) to provide vertical profiling capabilities for the study of dynamics (i.e., vertical velocity) and hydrometeors in winter storms. ...

  15. Comparison of Fuel Cell Technologies | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Comparison of Fuel Cell Technologies Comparison of Fuel Cell Technologies Each fuel cell technology has advantages and challenges. See how fuel cell technologies compare with one another. This comparison chart is also available as a fact sheet. Fuel Cell Type Common Electrolyte Operating Temperature Typical Stack Size Electrical Efficiency (LHV) Applications Advantages Challenges Polymer Electrolyte Membrane (PEM) Perfluorosulfonic acid <120°C <1 kW-100 kW 60% direct H2;a 40% reformed

  16. Distributed Wind Policy Comparison Tool | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    URI: cleanenergysolutions.orgcontentdistributed-wind-policy-comparison-to Language: English Policies: "Deployment Programs,Financial Incentives,Regulations" is not in...

  17. Recently released EIA report presents international forecasting data

    SciTech Connect

    1995-05-01

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

  18. Funding Opportunity Announcement for Wind Forecasting Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    in Complex Terrain | Department of Energy Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain April 4, 2014 - 9:47am Addthis On April 4, 2014 the U.S. Department of Energy announced a $2.5 million funding opportunity entitled "Wind Forecasting Improvement Project in Complex Terrain." By researching the physical processes that take place in complex

  19. Issues in midterm analysis and forecasting, 1996

    SciTech Connect

    1996-08-01

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

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

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    and Performance Baseline for Fossil Energy Plants Volume 1: Bituminous Coal and Natural ... COST AND PERFORMANCE BASELINE FOR FOSSIL ENERGY PLANTS VOLUME 1: BITUMINOUS COAL AND ...

  1. U.S. Energy Information Administration | Short-Term Energy...

    Annual Energy Outlook

    This edition of the Short-Term Energy Outlook is the first to include forecasts ... For renewables, the forecast share of total U.S. Energy Information Administration | ...

  2. Wind Power Forecasting Data

    U.S. Department of Energy (DOE) - all 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...

  3. Wind Power Forecasting

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    data Presentations BPA Super Forecast Methodology Related Links Near Real-time Wind Animation Meteorological Data Customer Supplied Generation Imbalance Dynamic Transfer Limits...

  4. Annual energy outlook 1995, with projections to 2010

    SciTech Connect

    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.

  5. Pathways to Low-Cost Electrochemical Energy Storage: A Comparison of

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Aqueous and Nonaqueous Flow Batteries - Joint Center for Energy Storage Research September 16, 2014, Research Highlights Pathways to Low-Cost Electrochemical Energy Storage: A Comparison of Aqueous and Nonaqueous Flow Batteries Comparison of available design space for aqueous and nonaqueous flow batteries to meet long term stationary storage cost goals. The nonaqueous redox flow battery technology has a potentially wider range of chemistry options but takes on new constraints of active

  6. Comparison of International Energy Intensities across the G7...

    Energy Information Administration (EIA) (indexed site)

    Energy Intensities across the G7 and other parts of Europe, including Ukraine Elizabeth Sendich November 2014 Independent Statistics & Analysis www.eia.gov U.S. Energy Information ...

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

    OpenEI (Open Energy Information) [EERE & EIA]

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

  8. NREL: Transmission Grid Integration - Forecasting

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Forecasting NREL researchers use solar and wind resource assessment and forecasting techniques to develop models that better characterize the potential benefits and impacts of ...

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

    U.S. Department of Energy (DOE) - all 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...

  10. Pathways to Low-Cost Electrochemical Energy Storage: A Comparison...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    September 16, 2014, Research Highlights Pathways to Low-Cost Electrochemical Energy Storage: A ... and aqueous flow batteries for future and existing chemistries Analysis ...

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

    Office of Scientific and Technical Information (OSTI)

    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, ...

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

    Energy.gov [DOE] (indexed site)

    It first identifies and prioritizes the appliances to be evaluated. Then, the study determines whether real world energy consumption differed substantially from predictions and ...

  13. Comparison of the Department of Energy's 2007, 2008, & 2009 Annual...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    of Energy's 2007, 2008, & 2009 Annual Employee Survey Results Item Personal Work ...team leaders in my work unit support employee development. 2007 63% 18% 14% 5% 2009 ...

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

    U.S. Department of Energy (DOE) - all 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...

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report.pdf (15.76 MB) More Documents & Publications QER - Comment of Edison Electric Institute (EEI) 1 QER - Comment of Canadian Hydropower Association Team roster: Dan Paikowsky, Management; Christian Bain, Entrepreneurship; Noah Meunier, Mechanical Engineering &

  16. Module 6 - Metrics, Performance Measurements and Forecasting | Department

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    of Energy 6 - Metrics, Performance Measurements and Forecasting Module 6 - Metrics, Performance Measurements and Forecasting This module focuses on the metrics and performance measurement tools used in Earned Value. This module reviews metrics such as cost and schedule variance along with cost and schedule performance indices. In addition, this module will outline forecasting tools such as estimate to complete (ETC) and estimate at completion (EAC). Begin Module >> (471

  17. DOE Benefits Forecasts: Report of the External Peer Review Panel |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Benefits Forecasts: Report of the External Peer Review Panel DOE Benefits Forecasts: Report of the External Peer Review Panel A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts. Report of the External Peer Review Panel (777.84 KB) More Documents & Publications Industrial Technologies Funding Profile by Subprogram Survey of Emissions Models for Distributed Combined Heat and Power

  18. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Complex Terrain | Department of Energy Wind Forecasting Improvement Project in Complex Terrain Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain February 12, 2014 - 10:47am Addthis On February 11, 2014 the Wind Program announced a Notice of Intent to issue a funding opportunity entitled "Wind Forecasting Improvement Project in Complex Terrain." By researching the physical processes that take place in complex terrain, this funding would improve

  19. Deep Energy Retrofit Performance Metric Comparison: Eight California Case Studies

    SciTech Connect

    Walker, Iain; Fisher, Jeremy; Less, Brennan

    2014-06-01

    In this paper we will present the results of monitored annual energy use data from eight residential Deep Energy Retrofit (DER) case studies using a variety of performance metrics. For each home, the details of the retrofits were analyzed, diagnostic tests to characterize the home were performed and the homes were monitored for total and individual end-use energy consumption for approximately one year. Annual performance in site and source energy, as well as carbon dioxide equivalent (CO2e) emissions were determined on a per house, per person and per square foot basis to examine the sensitivity to these different metrics. All eight DERs showed consistent success in achieving substantial site energy and CO2e reductions, but some projects achieved very little, if any source energy reduction. This problem emerged in those homes that 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 selecting an appropriate metric to be used in guiding retrofit decisions. Also, due to the dynamic nature of DERs, with changes in occupancy, size, layout, and comfort, several performance metrics might be necessary to understand a project’s success.

  20. Issues in midterm analysis and forecasting 1998

    SciTech Connect

    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.

  1. Project Profile: Forecasting and Influencing Technological Progress in

    Energy Saver

    Solar Energy | Department of Energy Soft Costs » Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Logos of the University of North Carolina at Charlotte, Arizona State University, and the University of Oxford. -- This project is inactive -- The University of North Carolina at Charlotte, along with their partners at Arizona State University and the University of Oxford,

  2. Energy Use and Carbon Emissions: Some International Comparisons

    Reports and Publications

    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.

  3. Annual energy outlook 1994: With projections to 2010

    SciTech Connect

    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.

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

    SciTech Connect

    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.

  5. Wind speed forecasting in the central California wind resource area

    SciTech Connect

    McCarthy, E.F.

    1997-12-31

    A wind speed forecasting program was implemented in the summer seasons of 1985 - 87 in the Central California Wind Resource Area (WRA). The forecasting program is designed to use either meteorological observations from the WRA and local upper air observations or upper air observations alone to predict the daily average windspeed at two locations. Forecasts are made each morning at 6 AM and are valid for a 24 hour period. Ease of use is a hallmark of the program as the daily forecast can be made using data entered into a programmable HP calculator. The forecasting program was the first step in a process to examine whether the electrical energy output of an entire wind power generation facility or defined subsections of the same facility could be predicted up to 24 hours in advance. Analysis of the results of the summer season program using standard forecast verification techniques show the program has skill over persistence and climatology.

  6. Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings OIRA Comparison Document

    Office of Energy Efficiency and Renewable Energy (EERE)

    Document details the Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings in an OIRA Comparison Document.

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

    SciTech Connect

    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.

  8. Employment impacts of selected solar and conventional energy systems: a framework for comparisons and preliminary findings

    SciTech Connect

    Smeltzer, K.K.

    1980-01-01

    Preliminary comprehensive analyses of quantitative and qualitative employment effects of selected solar and conventional energy systems are presented. It proposes a framework for analyzing the direct, indirect, induced, displacement, disposable income, and qualitative employment effects of alternative energy systems. The analyses examine current research findings on these effects for a variety of solar and conventional energy sources and compare expected employment impacts. In general, solar energy systems have higher direct and indirect employment requirements than do conventional energy systems. In addition, employment displaced from conventional sources and employment effects due to changes in consumers' disposable income are highly significant variables in net employment comparisons. Analyses of the size and location of projected energy developments suggest that dispersed solar energy systems have a more beneficial impact on host communities than do large conventional facilities, regardless of the relative magnitude of employment per unit of energy output.

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

    SciTech Connect

    Schipper, L.; Ketoff, A.; Meyers, S.

    1981-05-01

    This summary report presents information on the end-uses of energy in the residential sector of seven major OECD countries over the period 1960-1978. Much of the information contained herein has never been published before. We present data on energy consumption by energy type and end-use for three to five different years for each country. Each year table is complemented by a set of indicators, which are assembled for the entire 20-year period at the end of each country listing. Finally, a set of key indicators from each country is displayed together in a table, allowing comparison for three periods: early (1960-63), pre-embargo (1970-73), and recent (1975-78). Analysis of these results, smoothing and interpolation of the data, addition of further data, and analytical comparison of in-country and cross-country trends will follow in the next phase of our work.

  10. OneidaTribe of Indians Energy Optimization Model Development...

    Office of Environmental Management (EM)

    ... thermal Bioenergy Biomass Thermal Electric Fuels CNG, biodiesel, electric Conventionals Strategy Energy history Energy forecast ...

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

    SciTech Connect

    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.

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

    SciTech Connect

    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.

  13. 1994 Solid waste forecast container volume summary

    SciTech Connect

    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.

  14. Contact Us - U.S. Energy Information Administration (EIA) - U.S. Energy

    Gasoline and Diesel Fuel Update

    Information Administration (EIA) Forecasting & Analysis Short-Term (STEO) Energy Forecast Experts Long-Term (AEO) Energy Forecast Experts International (IEO) Energy Forecast Experts Renewable Energy Forecast Experts Long-Term (AEO) Analysis and Forecasting Experts Fax: (202) 586-3045 Annual Energy Outlook General questions/Executive summary Angelina LaRose 202-586-6135 angelina.larose@eia.gov Carbon dioxide emissions Perry Lindstrom 202-586-0934 perry.lindstrom@eia.gov Coal supply and

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

    SciTech Connect

    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.

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

    Energy.gov [DOE] (indexed site)

    The Wind Forecast Improvement Project (WFIP) is a U. S. Department of Energy (DOE) sponsored research project whose overarching goals are to improve the accuracy of short-term wind ...

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

    SciTech Connect

    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.

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Expert Panel: Forecast Future Demand for Medical Isotopes Expert Panel: Forecast Future Demand for Medical Isotopes The Expert Panel has concluded that the Department of Energy and National Institutes of Health must develop the capability to produce a diverse supply of radioisotopes for medical use in quantities sufficient to support research and clinical activities. Such a capability would prevent shortages of isotopes, reduce American dependence on foreign radionuclide sources and

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

    SciTech Connect

    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.

  20. Making Wind Energy Predictable: New Profilers Provide Hourly...

    Energy Saver

    Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts May 11, 2016 - 6:48pm Addthis ...

  1. A comparison of energy intensity in the United States and Japan

    SciTech Connect

    McDonald, S.C.

    1990-12-01

    This report compares energy intensity in the US and Japan in 1985. Energy intensity is examined for each of the following end-use energy consuming sectors: residential and commercial, transportation, and industrial (manufacturing). In each sector, comparative measures of the relative energy intensity are developed. The comparison indicates that when adjustments are made for certain differences between the two countries, energy intensity in the US compares more favorably with Japan than when just the aggregate energy-to-gross-domestic-product ratio is used. For instance, climate and residential floor space explain a good portion of the difference between residential energy consumption in the US and Japan. Likewise, although the US requires about twice as much energy for passenger travel, it requires about half the energy for freight movement (when normalized for distance and vehicle capacity) compared with Japan. Finally, the US manufacturing sector, as a whole, is about equal to Japan in terms of the amount of energy consumed in producing a dollar's worth of goods, in current dollars and using 1985 exchange rates. 53 refs.

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

    SciTech Connect

    Rocha, Paula; Siddiqui, Afzal; Stadler, Michael

    2014-12-09

    In this study, 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.

  3. Comparison

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Comparison of ion temperature diagnostics on the Madison symmetric torus reversed-field pinch J. C. Reardon, a) D. Craig, D. J. Den Hartog, G. Fiksel, and S. C. Prager Department of Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706 ͑Presented on 9 July 2002͒ There have been three ion temperature diagnostics operating on the Madison symmetric torus ͑MST͒ for the past two years: ͑i͒ Charge-exchange recombination spectroscopy ͑CHERS͒, which measures the temperature of fully

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

    SciTech Connect

    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

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

    SciTech Connect

    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

  6. LED ADOPTION REPORT | Department of Energy

    Energy Saver

    Energy Savings Forecast of Solid-State Lighting in General Illumination Applications 2015 SSL TECHNOLOGY DEVELOPMENT WORKSHOP PRESENTATIONS - Day 1 2016 SSL Forecast Report

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

    DOE PAGES [OSTI]

    Rocha, Paula; Siddiqui, Afzal; Stadler, Michael

    2014-12-09

    In this study, 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,more » 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.« less

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

    SciTech Connect

    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.

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Operations | Department of Energy Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Clean Power Research logo.jpg This project will address the need for a more accurate approach to forecasting net utility load by taking into consideration the contribution of customer-sited PV energy generation. Tasks within the project are designed to integrate novel PV power

  10. Final Report - Integration of Behind-the-Meter PV Fleet Forecasts into

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Utility Grid System Operations | Department of Energy Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Final Report - Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Awardee: Clean Power Research Location: Napa, CA Subprogram: Systems Integration Funding Program: Solar Utility Networks: Replicable Innovations in Solar Energy (SUNRISE) Project: Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid

  11. Baseline and Target Values for PV Forecasts: Toward Improved...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

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

  12. Using Wikipedia to forecast diseases

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Using Wikipedia to forecast diseases Using Wikipedia to forecast diseases Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. November 13, 2014 Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Contact Nancy Ambrosiano Communications Office (505)

  13. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National

    Office of Scientific and Technical Information (OSTI)

    Laboratory (Technical Report) | SciTech Connect 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory Citation Details In-Document Search Title: 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory When considering the amount of shortwave radiation incident on a photovoltaic solar array and, therefore, the amount and stability of the energy output from the system, clouds represent the greatest source of short-term (i.e., scale of minutes to

  14. 1980 annual report to Congress: Volume three, Forecasts: Summary

    SciTech Connect

    Not Available

    1981-05-27

    This report presents an overview of forecasts of domestic energy consumption, production, and prices for the year 1990. These results are selected from more detailed projections prepared and published in Volume 3 of the Energy Information Administration 1980 Annual Report to Congress. This report focuses specifically upon the 1980's and concentrates upon similarities and differences in the domestic energy system, as forecast, compared to the national experience in the years immediately following the 1973--1974 oil embargo. Interest in the 1980's stems not only from its immediacy in time, but also from its importance as a time in which certain adjustments to higher energy prices are expected to take place. The forecasts presented do not attempt to account for all of this wide range of potentially important forces that could conceivably alter the energy situation. Instead, the projections are based on a particular set of assumptions that seems reasonable in light of what is currently known. 9 figs., 25 tabs.

  15. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect

    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.

  16. The forecast calls for flu

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Science on the Hill: The forecast calls for flu Using mathematics, computer programs, ... We're getting close. Using mathematics, computer programs, statistics and information ...

  17. A Comparison of Water Vapor Quantities from Model Short-Range...

    Office of Scientific and Technical Information (OSTI)

    Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations Citation Details In-Document Search Title: A Comparison of Water Vapor Quantities from ...

  18. A survey on wind power ramp forecasting.

    SciTech Connect

    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.

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Wind Forecasting Improvement Project in Complex Terrain Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain February 12, 2014 - 10:47am ...

  20. Short-term energy outlook, Annual supplement 1995

    SciTech Connect

    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.

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

    SciTech Connect

    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.

  2. U.S. Crude Oil Production Forecast-Analysis of Crude Types

    Energy Information Administration (EIA) (indexed site)

    of Energy Washington, DC 20585 U.S. Energy Information Administration | U.S. Crude Oil Production Forecast-Analysis of Crude Types i This report was prepared by the U.S....

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

    SciTech Connect

    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.

  4. Science on Tap - Forecasting illness

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Science on Tap - Forecasting illness Science on Tap - Forecasting illness WHEN: Mar 17, 2016 5:30 PM - 7:00 PM WHERE: UnQuarked Wine Room 145 Central Park Square, Los Alamos, New Mexico 87544 USA CONTACT: Linda Anderman (505) 665-9196 CATEGORY: Bradbury INTERNAL: Calendar Login Event Description Mark your calendars for this event held every third Thursday from 5:30 to 7 p.m. A short presentation is followed by a lively discussion on a different subject each month. Forecasting the flu (and other

  5. Short-Term Energy Outlook

    Reports and Publications

    2016-01-01

    Short-term energy supply, demand, and price projections through 2015 for the United States and international oil forecasts.

  6. Onsemble | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Colorado Zip: 80302 Region: Rockies Area Sector: Wind energy Product: wind energy forecasting Website: www.onsemble.ws Coordinates: 40.010492, -105.276843 Show Map Loading...

  7. 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

    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

  8. Value of Wind Power Forecasting

    SciTech Connect

    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.

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

    SciTech Connect

    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.

  10. Selected papers on fuel forecasting and analysis

    SciTech Connect

    Gordon, R.L.; Prast, W.G.

    1983-05-01

    Of the 19 presentations at this seminar, covering coal, uranium, oil, and gas issues as well as related EPRI research projects, eleven papers are published in this volume. Nine of the papers primarily address coal-market analysis, coal transportation, and uranium supply. Two additional papers provide an evaluation and perspective on the art and use of coal-supply forecasting models and on the relationship between coal and oil prices. The authors are energy analysts and EPRI research contractors from academia, the consulting profession, and the coal industry. A separate abstract was prepared for each of the 11 papers.

  11. California's 6th congressional district: Energy Resources | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    in California's 6th congressional district A10 Power Akuacom Alternative Energy Inc Bio Energy Systems LLC Bioil Energy Matters LLC Enphase Energy Inc Forecast Energy Geysers...

  12. Voluntary Green Power Market Forecast through 2015

    SciTech Connect

    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.

  13. Energy Efficiency and Renewable Energy Benefits

    Energy.gov [DOE] (indexed site)

    Canyons Trading Post History Renewable Energy Energy Efficiency Comparisons Conclusion 2 Objective Benefits of renewable energy & energy efficiency Energy ...

  14. 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

    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)

  15. Aerial Measuring System (AMS)/Israel Atomic Energy Commission (IAEC) Joint Comparison Study Report

    SciTech Connect

    Wasiolek, P.; Halevy, I.

    2013-12-23

    Under the 13th Bilateral Meeting to Combat Nuclear Terrorism conducted on January 8–9, 2013, the committee approved the development of a cost-effective proposal to conduct a Comparison Study of the Aerial Measuring System (AMS) of the U.S. Department of Energy (DOE), National Nuclear Security Administration (NNSA) and Israel Atomic Energy Commission (IAEC). The study was to be held at the Remote Sensing Laboratory (RSL), Nellis Air Force Base, Las Vegas, Nevada, with measurements at the Nevada National Security Site (NNSS). The goal of the AMS and the IAEC joint survey was to compare the responses of the two agencies’ aerial radiation detection systems to varied radioactive surface contamination levels and isotopic composition experienced at the NNSS, and the differing data processing techniques utilized by the respective teams. Considering that for the comparison both teams were using custom designed and built systems, the main focus of the short campaign was to investigate the impact of the detector size and data analysis techniques used by both teams. The AMS system, SPectral Advanced Radiological Computer System, Model A (SPARCS-A), designed and built by RSL, incorporates four different size sodium iodide (NaI) crystals: 1" × 1", 2" × 4" × 4", 2" × 4" ×16", and an “up-looking” 2" × 4" × 4". The Israel AMS System, Air RAM 2000, was designed by the IAEC Nuclear Research Center – Negev (NRCN) and built commercially by ROTEM Industries (Israel) and incorporates two 2" diameter × 2" long NaI crystals. The operational comparison was conducted at RSL-Nellis in Las Vegas, Nevada, during week of June 24–27, 2013. The Israeli system, Air RAM 2000, was shipped to RSL-Nellis and mounted together with the DOE SPARCS on a DOE Bell-412 helicopter for a series of aerial comparison measurements at local test ranges, including the Desert Rock Airport and Area 3 at the NNSS. A 4-person Israeli team from the IAEC NRCN supported the activity together with 11

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

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

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

  17. Picture of the Week: Forecasting Flu

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    3 Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? March 6, 2016 flu epidemics modellled using social media Watch the video on YouTube. Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? Using real-time data from Wikipedia and social media, Sara del

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

    SciTech Connect

    1996-02-01

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

  19. Short-Term Energy Outlook September 2013

    Annual Energy Outlook

    The U.S. Energy Information Administration's (EIA) forecast for Brent crude oil spot ... of 2013 and 96 per barrel during 2014. Energy price forecasts are highly uncertain and ...

  20. Assessment and comparison of waste management costs for nuclear and fossil energy sources

    SciTech Connect

    Long, F.G.; Zaccai, H.; Ward, R.D.; McNicholas, P.; Albers, R.W.

    1993-12-31

    This paper presents the key results of an assessment of waste management costs undertaken by a group of international experts on behalf of the IAEA, Vienna. The objective of this work is to provide an assessment and comparison of the impact of waste management on the cost of electricity production from nuclear and other energy sources. The study focuses on the cost of managing wastes arising from the production of electricity from a PWR, with and without reprocessing, a coal-fueled conventional steam cycle, and a gas-fueled combined cycle; using data available in the open literature. This study has only assessed the impact of those waste management costs which are typically internalized by an electric utility and passed on as part of the price charged to customers. The data utilized in the study is typically in range form, reflecting worldwide experience with such factors as technology, regulatory requirements and economic parameters. To the extent that estimates can be identified in the literature the study has attempted to include costs associated with waste management from all stages of the fuel cycles. This paper also includes a discussion of future developments which may influence the results of this work including the effect of technology advances and changes in regulatory requirements.

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

    SciTech Connect

    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.

  2. Recent Trends in Variable Generation Forecasting and Its Value to the Power System

    DOE PAGES [OSTI]

    Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; Sharp, Justin; Wilczak, James M.; Freedman, Jeffrey; Haupt, Sue Ellen; Cline, Joel; Bartholomy, Obadiah; Hamann, Hendrik F.; et al

    2014-12-23

    We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value ofmore » adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.« less

  3. Recent Trends in Variable Generation Forecasting and Its Value to the Power System

    SciTech Connect

    Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; Sharp, Justin; Wilczak, James M.; Freedman, Jeffrey; Haupt, Sue Ellen; Cline, Joel; Bartholomy, Obadiah; Hamann, Hendrik F.; Hodge, Bri-Mathias; Finley, Catherine; Nakafuji, Dora; Peterson, Jack L.; Maggio, David; Marquis, Melinda

    2014-12-23

    We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value of adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.

  4. Property:ProgramSector | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    + AGI-32 + Energy + ANL Wind Power Forecasting and Electricity Markets + Energy + APEC-Alternative Transport Fuels: Implementation Guidelines + Energy + APFED-Good Practice...

  5. NREL: Energy Analysis - Carolyn Davidson

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Carolyn Davidson Photo of Carolyn Davidson Carolyn Davidson is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Economic Analyst On...

  6. Short-Term Energy Outlook

    Annual Energy Outlook

    ... U.S. Energy Information Administration | Short-Term Energy Outlook June 2015 2 * The National Oceanic and Atmospheric Administration (NOAA) forecasts warmer summer temperatures ...

  7. Use of wind power forecasting in operational decisions.

    SciTech Connect

    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

  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 Laboratory This presentation does not contain any proprietary, confidential, or otherwise restricted information 2015 DOE Bioenergy Technologies Office (BETO) Project Peer Review Goal Statement Addresses the following MYPP BETO goals:  Advance scientific methods and models for measuring and understanding

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

    SciTech Connect

    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.

  10. Comparison of DOE 10 CFR 851 and OSHA 29 CFR 1926 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Comparison of DOE 10 CFR 851 and OSHA 29 CFR 1926 Comparison of DOE 10 CFR 851 and OSHA 29 CFR 1926 September 28, 2016 Presenter: Craig Schumann, Argonne Site Office Topics Covered: Similarities of DOE 10 CFR 851 and OSHA 29 CFR 1926 Differences between the two requirements Contrast the ES&H emphasis of each requirement individually Which two primary ES&H areas do both requirements directly highlight Comparison of DOE 10 CFR 851 and OSHA 29 CFR 1926 (3.16 MB) More Documents &

  11. U.S. oil production forecast revised up for 2016 and 2017

    Energy Information Administration (EIA) (indexed site)

    oil production forecast revised up for 2016 and 2017 U.S. crude oil production is expected to be higher this year and in 2017 than previously forecast, because of a slower decline in onshore production. In its new monthly forecast, the U.S. Energy Information Administration revised up its estimate for domestic oil production by about 110,000 barrels per day for 2016 and by 150,000 barrels per day next year. EIA said increased drilling activity in the Permian Basin area located in West Texas and

  12. World oil inventories forecast to grow significantly in 2016 and 2017

    Energy Information Administration (EIA) (indexed site)

    World oil inventories forecast to grow significantly in 2016 and 2017 Global oil inventories are expected to continue strong growth over the next two years which should keep oil prices low. In its new monthly forecast, the U.S. Energy Information Administration said world oil stocks are likely to increase by 1.6 million barrels per day this year and by 600,000 barrels per day next year. The higher forecast for inventory builds are the result of both higher global oil production and less oil

  13. Forecasting Wind and Solar Generation: Improving System Operations, Greening the Grid

    SciTech Connect

    Tian; Tian; Chernyakhovskiy, Ilya

    2016-01-01

    This document discusses improving system operations with forecasting and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.

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

    SciTech Connect

    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.

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

    SciTech Connect

    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.

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

    SciTech Connect

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

    2005-06-30

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

  17. July 2016 Systems Integration Solar Forecasting:

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ... Those costs comprise fuel costs from expensive generators ... an improved-accuracy forecast of the solar power generation. ... analog ensemble for short-term probabilistic solar power ...

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

    Energy.gov [DOE] (indexed site)

    There is no cost to participate and all applicants are encouraged to attend. To join the ... Related Articles Upcoming Funding Opportunity for Wind Forecasting Improvement Project in ...

  19. Module 6 - Metrics, Performance Measurements and Forecasting...

    Energy.gov [DOE] (indexed site)

    This module reviews metrics such as cost and schedule variance along with cost and schedule performance indices. In addition, this module will outline forecasting tools such as ...

  20. Development and Demonstration of Advanced Forecasting, Power...

    Energy.gov [DOE] (indexed site)

    Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices 63wateruseoptimizationprojectanlgasper.ppt (7.72 MB) More ...

  1. NREL: Resource Assessment and Forecasting - Webmaster

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    email address: Your message: Send Message Printable Version Resource Assessment & Forecasting Home Capabilities Facilities Working with Us Research Staff Data & Resources Did...

  2. Forecast and Funding Arrangements - Hanford Site

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Annual Waste Forecast and Funding Arrangements About Us Hanford Site Solid Waste Acceptance Program What's New Acceptance Criteria Acceptance Process Becoming a new Hanford...

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

    Energy Saver

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

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

    SciTech Connect

    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.

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

    SciTech Connect

    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.

  6. Energy requirements for metals production: comparison between ocean nodules and land-based resources. Final report

    SciTech Connect

    Not Available

    1980-09-01

    A methodology was developed to compare the energy requirements of technologies for production of metals from ocean nodules with production of same metals from land based ores using conventional processes. The energy requirements for production of copper, nickel, cobalt, and manganese from ocean nodules are based on an ocean mining operation of 3 million tons per year of dry nodules. A linear relationship exists between the amount of nodules processed and the total energy so that the energy can be easily converted to other processing rates if desired.

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

    SciTech Connect

    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%.

  8. Sensing, Measurement, and Forecasting | Grid Modernization | NREL

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Sensing, Measurement, and Forecasting NREL measures weather resources and power systems, forecasts renewable resources and grid conditions, and converts measurements into operational intelligence to support a modern grid. Photo of solar resource monitoring equipment Modernizing the grid involves assessing its health in real time, predicting its behavior and potential disruptions, and quickly responding to events-which requires understanding vital parameters throughout the electric

  9. Office of Energy Efficiency and Renewable Energy Fiscal Year...

    Energy.gov [DOE] (indexed site)

    ... optimization studies for wind systems and operational forecasting tool development to understand and reduce costs associated with integrating variable wind energy into the ...

  10. Forecasting photovoltaic array power production subject to mismatch losses

    SciTech Connect

    Picault, D.; Raison, B.; Bacha, S.; de la Casa, J.; Aguilera, J.

    2010-07-15

    The development of photovoltaic (PV) energy throughout the world this last decade has brought to light the presence of module mismatch losses in most PV applications. Such power losses, mainly occasioned by partial shading of arrays and differences in PV modules, can be reduced by changing module interconnections of a solar array. This paper presents a novel method to forecast existing PV array production in diverse environmental conditions. In this approach, field measurement data is used to identify module parameters once and for all. The proposed method simulates PV arrays with adaptable module interconnection schemes in order to reduce mismatch losses. The model has been validated by experimental results taken on a 2.2 kW{sub p} plant, with three different interconnection schemes, which show reliable power production forecast precision in both partially shaded and normal operating conditions. Field measurements show interest in using alternative plant configurations in PV systems for decreasing module mismatch losses. (author)

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

    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...

  12. Buildings Energy Data Book: 1.5 Generic Fuel Quad and Comparison

    Buildings Energy Data Book

    1 Key Definitions Quad: Quadrillion Btu (10^15 or 1,000,000,000,000,000 Btu) Generic Quad for the Buildings Sector: One quad of primary energy consumed in the buildings sector (includes the residential and commercial sectors), apportioned between the various primary fuels used in the sector according to their relative consumption in a given year. To obtain this value, electricity is converted into its primary energy forms according to relative fuel contributions (or shares) used to produce

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

    SciTech Connect

    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.

  14. Buildings Energy Data Book: 1.5 Generic Fuel Quad and Comparison

    Buildings Energy Data Book

    2 Consumption Comparisons in 2010 One quad equals: - 50.2 million short tons of coal = enough coal to fill a train of railroad cars 4,123 miles long (about one and a half times across the U.S.) - 974.7 billion cubic feet natural gas - 8.2 billion gallons of gasoline = 21.2 days of U.S. gasoline use = 22.89 million passenger cars each driven 12,400 miles = 20.12 million light-duty vehicles each driven 12,200 miles = all new passenger cars sold, each driven 50,000 miles = 13.69 million stock

  15. Buildings Energy Data Book: 1.5 Generic Fuel Quad and Comparison

    Buildings Energy Data Book

    3 Carbon Emission Comparisons One million metric tons of carbon dioxide-equivalent emissions equals: - the combustion of 530 thousand short tons of coal - the coal input to 1 coal plant (200-MW) in about 1 year - the combustion of 18 billion cubic feet of natural gas - the combustion of 119 million gallons of gasoline = the combustion of gasoline for 7 hours in the U.S. = 323 thousand new cars, each driven 12,400 miles = 282 thousand new light-duty vehicles, each driven 12,200 miles = 274

  16. NREL: Energy Analysis - Liz Torres

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    and Visualization Group Energy Forecasting and Modeling Group Market and Policy Impact Analysis Group Technology Systems and Sustainability Analysis Group Washington D.C....

  17. NREL: Energy Analysis - Heidi Pawlowski

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    and Visualization Group Energy Forecasting and Modeling Group Market and Policy Impact Analysis Group Technology Systems and Sustainability Analysis Group Washington D.C....

  18. NREL: Energy Analysis - Melissa Hudman

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    and Visualization Group Energy Forecasting and Modeling Group Market and Policy Impact Analysis Group Technology Systems and Sustainability Analysis Group Washington D.C....

  19. NREL: Energy Analysis - Michael Bahl

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    and Visualization Group Energy Forecasting and Modeling Group Market and Policy Impact Analysis Group Technology Systems and Sustainability Analysis Group Washington D.C....

  20. AL PRO | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    search Name: AL-PRO Place: Grossheide, Lower Saxony, Germany Zip: 26532 Sector: Wind energy Product: AL-PRO is an inndependent expert office for wind forecasts, wind...

  1. Past Opportunities | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Access Greater Wind Resources and Lower Costs 4172015 6042015 RFI: Research and ... Energy 062514 072514 Wind Forecasting Improvement Project in Complex Terrain ...

  2. RES Anatolia | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    navigation, search Name: RES Anatolia Place: Istanbul, Turkey Zip: 34398 Sector: Solar, Wind energy Product: Istanbul-based subsidiary formed due to positive forecasts for the...

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

    SciTech Connect

    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 νμ → νμ disappearance experiments operating in different energy 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.

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

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Metrics for Evaluating the Accuracy of Solar Power Forecasting Preprint J. Zhang, B.-M. Hodge, and A. Florita National Renewable Energy Laboratory S. Lu and H. F. Hamann IBM TJ Watson Research Center V. Banunarayanan U.S. Department of Energy To be presented at 3rd International Workshop on Integration of Solar Power into Power Systems London, England October 21 - 22, 2013 Conference Paper NREL/CP-5500-60142 October 2013 NOTICE The submitted manuscript has been offered by an employee of the

  5. Study forecasts disappearance of conifers due to climate change

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Study forecasts disappearance of conifers due to climate change Study forecasts disappearance of conifers due to climate change New results, reported in a paper released today in ...

  6. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen MJ ... Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen, ...

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

    DOE PAGES [OSTI]

    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

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

    SciTech Connect

    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 aqueous 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.

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

    DOE PAGES [OSTI]

    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 νμ → νμ 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

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

    SciTech Connect

    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.

  11. Comparison of energy expenditures by elderly and non-elderly households: 1975 and 1985

    SciTech Connect

    Siler, A.

    1980-05-01

    The relative position of the elderly in the population is examined and their characteristic use of energy in relation to the total population and their non-elderly counterparts is observed. The 1985 projections are based on demographic, economic, and socio-economic, and energy data assumptions contained in the 1978 Annual Report to Congress. The model used for estimating household energy expenditure is MATH/CHRDS - Micro-Analysis of Transfers to Households/Comprehensive Human Resources Data System. Characteristics used include households disposable income, poverty status, location by DOE region and Standard Metropolitan Statistical Area (SMSA), and race and sex of the household head as well as age. Energy use by fuel type will be identified for total home fuels, including electricity, natural gas, bottled gas and fuel oil, and for all fuels, where gasoline use is also included. Throughout the analysis, both income and expenditure-dollar amounts for 1975 and 1985 are expressed in constant 1978 dollars. Two appendices contain statistical information.

  12. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.

    SciTech Connect

    United States. Bonneville Power Administration.

    1994-02-01

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

  13. Cost and energy comparison study of above- and below-ground dwellings

    SciTech Connect

    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.

  14. Overall Energy Considerations for Algae Species Comparison and Selection in Algae-to-Fuels Processes

    SciTech Connect

    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

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

    SciTech Connect

    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.

  16. Hybrid Vehicle Comparison Testing Using Ultracapacitor vs. Battery Energy Storage (Presentation)

    SciTech Connect

    Gonder, J.; Pesaran, A.; Lustbader, J.; Tataria, H.

    2010-02-01

    With support from General Motors, NREL researchers converted and tested a hybrid electric vehicle (HEV) with three energy storage configurations: a nickel metal-hydride battery and two ultracapacitor (Ucap) modules. They found that the HEV equipped with one Ucap module performed as well as or better than the HEV with a stock NiMH battery configuration. Thus, Ucaps could increase the market penetration and fuel savings of HEVs.

  17. SU-E-I-98: Dose Comparison for Pulmonary Embolism CT Studies: Single Energy Vs. Dual Energy

    SciTech Connect

    Mahmood, U; Erdi, Y

    2014-06-01

    Purpose: The purpose of this study was to assess and compare the size specific dose estimate (SSDE), dose length product (DLP) and noise relationship for pulmonary embolism studies evaluated by single source dual energy computed tomography (DECT) against conventional CT (CCT) studies in a busy cancer center and to determine the dose savings provided by DECT. Methods: An IRB-approved retrospective study was performed to determine the CTDIvol and DLP from a subset of patients scanned with both DECT and CCT over the past five years. We were able to identify 30 breast cancer patients (6 male, 24 female, age range 24 to 81) who had both DECT and CCT studies performed. DECT scans were performed with a GE HD 750 scanner (140/80 kVp, 480 mAs and 40 mm) and CCT scans were performed with a GE Lightspeed 16 slice scanner (120 kVp, 352 mAs, 20 mm). Image noise was measured by placing an ROI and recording the standard deviation of the mean HU along the descending aorta. Results: The average DECT patient size specific dose estimate was to be 14.2 1.7 mGy as compared to 22.4 2.7 mGy from CCT PE studies, which is a 37% reduction in the SSDE. The average DECT DLP was 721.8 84.6 mGy-cm as compared to 981.8 106.1 mGy-cm for CCT, which is a 26% decrease. Compared to CCT the image noise was found to decrease by 19% when using DECT for PE studies. Conclusion: DECT SSDE and DLP measurements indicate dose savings and image noise reduction when compared to CCT. In an environment that heavily debates CT patient doses, this study confirms the effectiveness of DECT in PE imaging.

  18. EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Improved by 30% | Department of Energy Forecasting Gets a Boost from Watson, Accuracy Improved by 30% EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM Youtube Video | Courtesy of IBM Remember when IBM's super computer Watson defeated Jeopardy! champions Ken Jennings and Brad Rutter? With funding from the U.S. Department of Energy SunShot Initiative, IBM researchers are using Watson-like technology to improve solar

  19. ARM - Field Campaign - Radar Wind Profiler for Cloud Forecasting at BNL

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    govCampaignsRadar Wind Profiler for Cloud Forecasting at BNL Campaign Links Field Campaign Report ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Radar Wind Profiler for Cloud Forecasting at BNL 2013.07.15 - 2015.08.06 Lead Scientist : Michael Jensen For data sets, see below. Abstract In support of recent activities funded by the DOE Energy Efficiency and Renewable Energy (EERE) to produce short-term

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

    SciTech Connect

    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.

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

    SciTech Connect

    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. Offshore Lubricants Market Forecast | OpenEI Community

    OpenEI (Open Energy Information) [EERE & EIA]

    Offshore Lubricants Market Forecast Home There are currently no posts in this category. Syndicate...

  3. Coal Fired Power Generation Market Forecast | OpenEI Community

    OpenEI (Open Energy Information) [EERE & EIA]

    Coal Fired Power Generation Market Forecast Home There are currently no posts in this category. Syndicate...

  4. OSTIblog Articles in the maps Topic | OSTI, US Dept of Energy...

    Office of Scientific and Technical Information (OSTI)

    Energy in the Forecast by Daphne Evans 13 Aug, 2012 in Science Communications 4273 Wind%20Power%20Map.png Energy in the Forecast Read more about 4273 If you can accurately predict ...

  5. OSTIblog Articles in the weather Topic | OSTI, US Dept of Energy...

    Office of Scientific and Technical Information (OSTI)

    Energy in the Forecast by Daphne Evans 13 Aug, 2012 in Science Communications 4273 Wind%20Power%20Map.png Energy in the Forecast Read more about 4273 If you can accurately predict ...

  6. ENTROPY VS. ENERGY WAVEFORM PROCESSING: A COMPARISON ON THE HEAT EQUATION

    SciTech Connect

    Hughes, Michael S.; McCarthy, John; Bruillard, Paul J.; Marsh, Jon N.; Wicklines, Samuel A.

    2015-05-25

    Virtually all modern imaging devices function by collecting either electromagnetic or acoustic backscattered waves and using the energy carried by these waves to determine pixel values that build up what is basically an ”energy” picture. However, waves also carry ”informa- tion” that also may be used to compute the pixel values in an image. We have employed several measures of information, all of which are based on different forms of entropy. Numerous published studies have demonstrated the advantages of entropy, or “information imaging”, over conventional methods for materials characterization and medical imaging. Similar results also have been obtained with microwaves. The most sensitive information measure appears to be the joint entropy of the backscattered wave and a reference signal. A typical study is comprised of repeated acquisition of backscattered waves from a specimen that is changing slowing with acquisition time or location. The sensitivity of repeated experimental observations of such a slowly changing quantity may be defined as the mean variation (i.e., observed change) divided by mean variance (i.e., observed noise). We compute the sensitivity for joint entropy and signal energy measurements assuming that noise is Gaussian and using Wiener integration to compute the required mean values and variances. These can be written as solutions to the Heat equation, which permits estimation of their 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.

  7. Flood Forecasting in River System Using ANFIS

    SciTech Connect

    Ullah, Nazrin; Choudhury, P.

    2010-10-26

    The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.

  8. ARM - CARES - Tracer Forecast for CARES

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    News & Press Backgrounder (PDF, 1.45MB) G-1 Aircraft Fact Sheet (PDF, 1.3MB) Contacts Rahul Zaveri, Lead Scientist Tracer Forecasts for CARES This webpage contains 72-hr...

  9. Cost comparison of energy projects: discounted cash flow and revenue requirement methods

    SciTech Connect

    Phung, D.L.

    1980-05-01

    Both the discounted-cash-flow (DCF) and the revenue-requirement (RR) methods are frequently used in the cost analysis of energy projects. Each is uniquely needed in special circumstances, but in the early stages of most ventures, the RR method appears to be more useful. This paper provides simple formulations for the two methods and some special cases of interest to costing practices. Both formulations are applicable to either free or regulated enterprises and in constant or inflated dollars. It is stressed that the interpretation of cost results depends on the selection of cash-flow streams and/or the intent of revenue requirements. Several numerical examples are given.

  10. Comparison of Energy Efficiency and Power Density in Pressure Retarded Osmosis and Reverse Electrodialysis

    SciTech Connect

    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

  11. Departments of Energy and Commerce Announce New Partnership to Further

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Cooperation on Renewable Energy Modeling and Forecasting | Department of Energy Commerce Announce New Partnership to Further Cooperation on Renewable Energy Modeling and Forecasting Departments of Energy and Commerce Announce New Partnership to Further Cooperation on Renewable Energy Modeling and Forecasting January 24, 2011 - 12:00am Addthis WASHINGTON - The Department of Energy and the Department of Commerce today announced a new agreement to further collaboration between the agencies on

  12. Industrial end-use forecasting that incorporates DSM and air quality

    SciTech Connect

    Tutt, T.; Flory, J.

    1995-05-01

    The California Energy Commission (CEC) and major enregy utilities in California have generally depended on simple aggregate intensity or economic models to forecast energy use in the process industry sector (which covers large industries employing basic processes to transform raw materials, such as paper mills, glass plants, and cement plants). Two recent trends suggests that the time has come to develop a more disaggregate process industry forecasting model. First, recent efforts to improve air quality, especially by the South Coast Air Quality Management District (SCAQMD), could significantly affect energy use by the process industry by altering the technologies and processes employed in order to reduce emissions. Second, there is a renewed interest in Demand-Side Management (DSM), not only for utility least-cost planning, but also for improving the economic competitiveness and environmental compliance of the pro{minus}cess industries. A disaggregate forecasting model is critical to help the CEC and utilities evaluate both the air quality and DSM impacts on energy use. A crucial obstacle to the development and use of these detailed process industry forecasting models is the lack of good data about disaggregate energy use in the sector. The CEC is nearing completion of a project to begin to overcome this lack of data. The project is testing methds of developing detailed energy use data, collecting an initial database for a large portion of southern California, and providing recommendations and direction for further data collection efforts.

  13. Sensitivity to Energy Technology Costs: A Multi-model comparison analysis

    SciTech Connect

    Bosetti, Valentina; Marangoni, Giacomo; Borgonovo, Emanuele; Anadon, Laura Diaz; Barron, Robert W.; McJeon, Haewon C.; Politis, Savvas; Friley, Paul

    2015-05-01

    In the present paper we use the output of multiple expert elicitation surveys on the future cost of key low-carbon technologies and use it as input of three Integrated Assessment models, GCAM, MARKAL_US and WITCH. By means of a large set of simulations we aim to assess the implications of these subjective distributions of technological costs over key model outputs. We are able to detect what sources of technology uncertainty are more influential, how this differs across models, and whether and how results are affected by the time horizon, the metric considered or the stringency of the climate policy. In unconstrained emission scenarios, within the range of future technology performances considered in the present analysis, the cost of nuclear energy is shown to dominate all others in affecting future emissions. Climate-constrained scenarios, stress the relevance, in addition to that of nuclear energy, of biofuels, as they represent the main source of decarbonization of the transportation sector and bioenergy, since the latter can be coupled with CCS to produce negative emissions.

  14. Entropy vs. energy waveform processing: A comparison based on the heat equation

    SciTech Connect

    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 defined 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.

  15. Wind Levelized Cost of Energy: A Comparison of Technical and Financing Input Variables

    SciTech Connect

    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.

  16. Entropy vs. energy waveform processing: A comparison based on the heat equation

    DOE PAGES [OSTI]

    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

  17. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect

    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.

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

    SciTech Connect

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

    1994-05-01

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

  19. 4273 | OSTI, US Dept of Energy Office of Scientific and Technical

    Office of Scientific and Technical Information (OSTI)

    Information 3 Energy in the Forecast Public Image File(s): Wind%20Power%20Map

  20. January 2013 Short-Term Energy Outlook (STEO)

    Gasoline and Diesel Fuel Update

    flat gasoline and jet fuel consumption. ... EIA expects the Henry Hub natural gas spot price... below this forecast. U.S. Energy Information Administration | Short-Term Energy ...

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

    Energy.gov [DOE] (indexed site)

    to Solicit Input on Solar Forecasting Metrics Webinar Sponsor: EERE's SunShot Initiative The Energy Department will ... on the National Geothermal Data System, Energy Efficiency ...

  2. Press Room - Press Releases - U.S. Energy Information Administration...

    Gasoline and Diesel Fuel Update

    1, 2015 MEDIA ADVISORY: EIA to Release Updated Energy Forecasts to 2040 WHO: Adam Sieminski, Administrator U.S. Energy Information Administration (EIA) WHAT: EIA presents cases ...

  3. EIA revises up forecast for U.S. 2013 crude oil production by 70,000 barrels per day

    Energy Information Administration (EIA) (indexed site)

    EIA revises up forecast for U.S. 2013 crude oil production by 70,000 barrels per day The forecast for U.S. crude oil production keeps going higher. The U.S. Energy Information Administration revised upward its projection for crude oil output in 2013 by 70,000 barrels per day and for next year by 190,000 barrels per day. U.S. oil production is now on track to average 7.5 million barrels per day this year and rise to 8.4 million barrels per day in 2014, according to EIA's latest monthly forecast.

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

    Reports and Publications

    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.

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

    SciTech Connect

    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.

  6. Interpolating Low Time-Resolution Forecast Data

    Energy Science and Technology Software Center

    2015-11-03

    data segment; 7. Add the selected variability pattern in each window to set F to get the high time-resolution data (set G) with variability observed from historical data set A; a coefficient k can be multiplied to the selected variability pattern to reflect the potential difference in variability between forecast set E and historical data set A caused by installation capacity and other factors. 8. After set G is constructed, variability statistics can be checked for set A and set G for comparison. Adjust the coefficient k if necessary to achieve desired variability in the reconstructed data.« less

  7. Brookhaven National Laboratory - OU III VOC | Department of Energy

    Office of Environmental Management (EM)

    "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast December 7, 2012 - 10:00am Addthis The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods

  8. Department of Energy Spent Fuel Shipping Campaigns: Comparisons of Transportation Plans and Lessons Learned

    SciTech Connect

    Holm, Judith A.; Thrower, Alex W.; Antizzo, Karen

    2003-02-27

    Over the last 30 years, the U.S. Department of Energy (DOE) has successfully and safely transported shipments of spent nuclear fuel over America's highways and railroads. During that time, an exemplary safety record has been established with no identifiable fatalities, injuries, or environmental damage caused by the radioactive nature of the shipments. This paper evaluates some rail and truck shipping campaigns, planning processes, and selected transportation plans to identify lessons learned in terms of planning and programmatic activities. The intent of this evaluation is to document best practices from current processes and previous plans for DOE programs preparing or considering future plans. DOE's National Transportation Program (NTP) reviewed 13 plans, beginning with core debris shipments from Three Mile Island to current, ongoing fuel campaigns. This paper describes lessons learned in the areas of: emergency planning, planning information, security, shipment prenotification, emergency notification/response, terrorism/sabotage risk, and recovery and cleanup, as well as routing, security, carrier/driver requirements, transportation operational contingencies, tracking, inspections and safe parking.

  9. A Chronological Reliability Model Incorporating Wind Forecasts to Assess Wind Plant Reserve Allocation: Preprint

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    * NREL/CP-500-32210 A Chronological Reliability Model Incorporating Wind Forecasts to Assess Wind Plant Reserve Allocation Preprint Michael Milligan To be presented at the American Wind Energy Association WindPower 2002 Conference Portland, Oregon June 3 - June 5, 2002 National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401-3393 NREL is a U.S. Department of Energy Laboratory Operated by Midwest Research Institute * Battelle * Bechtel Contract No. DE-AC36-99-GO10337

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

    SciTech Connect

    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.

  11. Comparison of the Energy Efficiency Prescribed by ASHRAE/ANSI/IESNA Standard 90.1-1999 and ASHRAE/ANSI/IESNA Standard 90.1-2004

    SciTech Connect

    Halverson, Mark A.; Liu, Bing; Richman, Eric E.; Winiarski, David W.

    2006-12-01

    This document presents the qualitative comparison of DOE’s formal determination of energy savings of ANSI/ASHRAE/IESNA Standard 90.1-2004. The term “qualitative” is used in the sense of identifying whether or not changes have a positive, negative, or neutral impact on energy efficiency of the standard, with no attempt made to quantify that impact. A companion document will present the quantitative comparison of DOE’s determination. The quantitative comparison will be based on whole building simulation of selected building prototypes in selected climates. This document presents a comparison of the energy efficiency requirements in ANSI/ASHRAE/IESNA 90.1-1999 (herein referred to as Standard 90.1-1999) and ANSI/ASHRAE/IESNA 90.1-2004 (herein referred to as Standard 90.1-2004). The comparison was done through a thorough review of all addenda to Standard 90.1-1999 that were included in the published ANSI/ASHRAE/IESNA Standard 90.1-2001 (herein referred to as Standard 90.1-2001) and also all addenda to Standard 90.1-2001 that were included in the published Standard 90.1-2004. A summary table showing the impact of each addendum is provided. Each addendum to both Standards 90.1-1999 and 90.1-2001 was evaluated as to its impact on the energy efficiency requirements of the standard (greater efficiency, lesser efficiency) and as to significance. The final section of this document summarizes the impacts of the various addenda and proposes which addenda should be included in the companion quantitative portion of DOE’s determination. Addenda are referred to with the nomenclature addendum 90.1-xxz, where “xx” is either “99” for 1999 or “01” for 2001, and z is the ASHRAE letter designation for the addendum. Addenda names are shown in bold face in text. DOE has chosen not to prepare a separate evaluation of Standard 90.1-2001 as that standard does not appear to improve energy efficiency in commercial buildings. What this means for the determination of energy

  12. Summer gasoline price forecast slightly higher, but drivers still pay less than last year

    Energy Information Administration (EIA) (indexed site)

    Summer gasoline price forecast slightly higher, but drivers still pay less than last year Rising crude oil prices are likely to be passed on to consumers at the pump, but U.S. drivers are still expected to pay the lowest summer gasoline prices since 2004, and for all of 2016 the average household will spend $900 less on gasoline than it did two years ago." In its new monthly forecast, the U.S. Energy Information Administration said the retail price for regular grade gasoline will average

  13. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

    SciTech Connect

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

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was 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 in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.

  14. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

    DOE PAGES [OSTI]

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

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based onmore » state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.« less

  15. Short-Term Energy Outlook

    Annual Energy Outlook

    This edition of the Short-Term Energy Outlook is the first to include forecasts ... to an average of 2.72gal in 2016. U.S. Energy Information Administration | Short-Term ...

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

    SciTech Connect

    Das, S.

    1991-12-01

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

  17. The Value of Improved Short-Term Wind Power Forecasting

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    ... up-ramp reserves c down cost in MWh of down-ramp reserves R down MW range for ... power forecasting and the increased gas usage that comes with less-accurate forecasting. ...

  18. Solar Forecasting Gets a Boost from Watson, Accuracy Improved...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM ...

  19. PBL FY 2003 Second Quarter Review Forecast of Generation Accumulated...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    the rate period (i.e., FY 2002-2006), a forecast of that end-of-year Accumulated Net Revenue (ANR) will be completed. If the ANR at the end of the forecast year falls below the...

  20. Short-Term Energy Outlook - U.S. Energy Information Administration...

    Annual Energy Outlook

    to the Natural Gas Storage Regions December 2015 PDF ... Forecast February 2014 PDF Energy-weighted Industrial ... Probabilities of Possible Future Prices April 2010 PDF ...

  1. Short-Term Energy Outlook - U.S. Energy Information Administration...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Sales, revenue and prices, power plants, fuel use, stocks, ... Maps by energy source and topic, includes forecast maps. ... Figures Tables Custom Table Builder Real Price Viewer ...

  2. Short-Term Energy Outlook - U.S. Energy Information Administration...

    Annual Energy Outlook

    Data Figures Tables Custom Table Builder Real Prices Viewer Forecast Changes (PDF) Special ... Power Producer (IPP) consumption. c Renewable energy includes minor components of ...

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

    SciTech Connect

    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.

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

    SciTech Connect

    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)

  5. Combined Heat And Power Installation Market Forecast | OpenEI...

    OpenEI (Open Energy Information) [EERE & EIA]

    Combined Heat And Power Installation Market Forecast Home There are currently no posts in this category. Syndicate...

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

    SciTech Connect

    Hodge, B. M.; Milligan, M.

    2011-07-01

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

  7. NREL: Energy Analysis - David Palchak

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Palchak Photo of David Palchak David Palchak is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Energy Systems Engineer On staff since September 2012 Phone number: 303-384-7456 E-mail: david.palchak@nrel.gov Areas of expertise Electrical load forecasting with artificial neural networks Demand-side management optimization with Matlab Primary research interests Demand response and renewable energy deployment modeling (PLEXOS) Education and background

  8. Short-Term Energy Outlook January 2014

    Annual Energy Outlook

    This edition of the Short-Term Energy Outlook is the first to include forecasts ... U.S. Energy Information Administration | Short-Term Energy Outlook January 2014 2 Global ...

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

    SciTech Connect

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

    2015-10-05

    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.

  10. Energy

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency ...

  11. Energy

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    3 - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion ...

  12. Energy

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    2 - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion ...

  13. Comparison of Methods for Estimating the NOx Emission Impacts of Energy Efficiency and Renewable Energy Projects: Shreveport, Louisiana Case Study (Revised)

    SciTech Connect

    Chambers, A.; Kline, D. M.; Vimmerstedt, L.; Diem, A.; Dismukes, D.; Mesyanzhinov, D.

    2005-07-01

    This is a case study comparing methods of estimating the NOx emission impacts of energy efficiency and renewable energy projects in Shreveport, Louisiana.

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

    SciTech Connect

    Not Available

    1994-02-07

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

  15. OSTI, US Dept of Energy Office of Scientific and Technical Information...

    Office of Scientific and Technical Information (OSTI)

    in the Forecast by Daphne Evans on Mon, August 13, 2012 4273 Wind%20Power%20Map.png Energy in the Forecast Read more about 4273 If you can accurately predict the weather, you may ...

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

    SciTech Connect

    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.

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

    SciTech Connect

    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.

  18. DOE Announces Webinars on Getting Buy-In for Energy Efficiency...

    Energy.gov [DOE] (indexed site)

    to compute annualized energy and energy-cost savings, maintenance savings, greenhouse ... More DOE Announces Webinars on Solar Forecasting Metrics, the DOE Wind Vision, and More ...

  19. OSTI, US Dept of Energy, Office of Scientific and Technical Informatio...

    Office of Scientific and Technical Information (OSTI)

    That was one objective of the "Great Plains Wind Energy Transmission Development Project," completed in 2011, to "develop a wind energy forecast system, and demonstrate its ...

  20. NOAA Teams Up with Department of Energy & Industry to Improve Wind

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Forecasts | Department of Energy NOAA Teams Up with Department of Energy & Industry to Improve Wind Forecasts NOAA Teams Up with Department of Energy & Industry to Improve Wind Forecasts July 2, 2014 - 3:51pm Addthis The growth of wind-generated power in the United States is creating greater demand for improved wind forecasts. To address this need, the Department of Energy is working with NOAA and industry on the Wind Forecast Improvement Project, funded and led by DOE. "Our

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

    SciTech Connect

    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

  2. Development of Energy Balances for the State of California

    SciTech Connect

    Murtishaw, Scott; Price, Lynn; de la Rue du Can, Stephane; Masanet, Eric; Worrell, Ernst; Sahtaye, Jayant

    2005-12-01

    Analysts assessing energy policies and energy modelers forecasting future trends need to have access to reliable and concise energy statistics. Lawrence Berkeley National Laboratory evaluated several sources of California energy data, primarily from the California Energy Commission and the U.S. Energy Information Administration, to develop the California Energy Balance Database (CALEB). This database manages highly disaggregated data on energy supply, transformation, and end-use consumption for each type of energy commodity from 1990 to the most recent year available (generally 2001) in the form of an energy balance, following the methodology used by the International Energy Agency. This report presents the data used for CALEB and provides information on how the various data sources were reconciled. CALEB offers the possibility of displaying all energy flows in numerous ways (e.g.,physical units, Btus, petajoules, different levels of aggregation), facilitating comparisons among the different types of energy commodities and different end-use sectors. In addition to displaying energy data, CALEB can also be used to calculate state-level energy-related carbon dioxide emissions using the methodology of the Intergovernmental Panel on Climate Change.

  3. Compiler Comparisons

    U.S. Department of Energy (DOE) - all 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...

  4. Forecasting hotspots using predictive visual analytics approach

    SciTech Connect

    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.

  5. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect

    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.

  6. Global disease monitoring and forecasting with Wikipedia

    DOE PAGES [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: 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

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

    SciTech Connect

    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. Federal Finance Facilities Available for Energy Efficiency Upgrades...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ... Junta, Chief Distributions Branch H. Robert Lash, Chief Transmissions Branch Gerard Moore, Chief Energy Forecasting Branch Victor Vu, Director Power Supply Division Vacant ...

  9. Visiting Speaker Program - July 28, 2010 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Robert Atkinson Panelists More Documents & Publications Expert Panel: Forecast Future Demand for Medical Isotopes Clark Atlanta Universities (CAU) Energy Related Research...

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

    Energy Saver

    "EIA's updated forecast projecting higher oil prices and increased demand reinforces the Department of Energy's commitment to the development of safe, clean, affordable, and ...

  11. U.S. Energy Information Administration (EIA) - Ap

    Energy Information Administration (EIA) (indexed site)

    Market Prices and Uncertainty Report This monthly supplement to the Short-Term Energy Outlook addresses price volatility and forecast uncertainty for crude oil and natural gas ...

  12. International Energy Outlook 2014

    Gasoline and Diesel Fuel Update

    Household heating bills expected to be higher than last winter, mainly driven by colder weather U.S. households are expected to pay higher heating bills this winter compared to last winter mainly because the weather is forecast to be colder than the relatively mild weather seen last winter and fuel prices are forecast to be higher. In its new forecast, the U.S. Energy Information Administration said households using heating oil will see a 38% jump in their heating fuel expenditures while propane

  13. Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.

    SciTech Connect

    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.

  14. Hawaii energy strategy: Executive summary, October 1995

    SciTech Connect

    1995-10-01

    This is an executive summary to a report on the Hawaii Energy Strategy Program. The topics of the report include the a description of the program including an overview, objectives, policy statement and purpose and objectives; energy strategy policy development; energy strategy projects; current energy situation; modeling Hawaii`s energy future; energy forecasts; reducing energy demand; scenario assessment, and recommendations.

  15. Hawaii energy strategy report, October 1995

    SciTech Connect

    1995-10-01

    This is a report on the Hawaii Energy Strategy Program. The topics of the report include the a description of the program including an overview, objectives, policy statement and purpose and objectives; energy strategy policy development; energy strategy projects; current energy situation; modeling Hawaii`s energy future; energy forecasts; reducing energy demand; scenario assessment, and recommendations.

  16. Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

    Office of Scientific and Technical Information (OSTI)

    (BNL) Field Campaign Report (Technical Report) | SciTech Connect Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report Citation Details In-Document Search Title: Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report The Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) [http://www.arm.gov/campaigns/osc2013rwpcf] campaign was scheduled to take place from 15 July

  17. Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

    Office of Scientific and Technical Information (OSTI)

    (BNL) Field Campaign Report (Technical Report) | SciTech Connect Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report Citation Details In-Document Search Title: Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report The Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) [http://www.arm.gov/campaigns/osc2013rwpcf] campaign was scheduled to take place from 15 July

  18. Regional Analysis of Building Distributed Energy Costs and CO2 Abatement: A U.S. - China Comparison

    SciTech Connect

    Mendes, Goncalo; Feng, Wei; Stadler, Michael; Steinbach, Jan; Lai, Judy; Zhou, Nan; Marnay, Chris; Ding, Yan; Zhao, Jing; Tian, Zhe; Zhu, Neng

    2014-04-09

    The following paper conducts a regional analysis of the U.S. and Chinese buildings? potential for adopting Distributed Energy Resources (DER). The expected economics of DER in 2020-2025 is modeled for a commercial and a multi-family residential building in different climate zones. The optimal building energy economic performance is calculated using the Distributed Energy Resources Customer Adoption Model (DER CAM) which minimizes building energy costs for a typical reference year of operation. Several DER such as combined heat and power (CHP) units, photovoltaics, and battery storage are considered. The results indicate DER have economic and environmental competitiveness potential, especially for commercial buildings in hot and cold climates of both countries. In the U.S., the average expected energy cost savings in commercial buildings from DER CAM?s suggested investments is 17percent, while in Chinese buildings is 12percent. The electricity tariffs structure and prices along with the cost of natural gas, represent important factors in determining adoption of DER, more so than climate. High energy pricing spark spreads lead to increased economic attractiveness of DER. The average emissions reduction in commercial buildings is 19percent in the U.S. as a result of significant investments in PV, whereas in China, it is 20percent and driven by investments in CHP. Keywords: Building Modeling and Simulation, Distributed Energy Resources (DER), Energy Efficiency, Combined Heat and Power (CHP), CO2 emissions 1. Introduction The transition from a centralized and fossil-based energy paradigm towards the decentralization of energy supply and distribution has been a major subject of research over the past two decades. Various concerns have brought the traditional model into question; namely its environmental footprint, its structural inflexibility and inefficiency, and more recently, its inability to maintain acceptable reliability of supply. Under such a troubled setting

  19. Market penetration of new energy technologies

    SciTech Connect

    Packey, D.J.

    1993-02-01

    This report examines the characteristics, advantages, disadvantages, and, for some, the mathematical formulas of forecasting methods that can be used to forecast the market penetration of renewable energy technologies. Among the methods studied are subjective estimation, market surveys, historical analogy models, cost models, diffusion models, time-series models, and econometric models. Some of these forecasting methods are more effective than others at different developmental stages of new technologies.

  20. Minority energy assessment report

    SciTech Connect

    Teotia, A.P.S.; Poyer, D.A.; Lampley, L.; Anderson, J.L.

    1992-12-01

    The purpose of this research is to project household energy consumption, energy expenditure, and energy expenditure as share of income for five population groups from 1991 to 2009. The approach uses the Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory for the US Department of Energy's Office of Minority Economic Impact. The MEAM provides a framework that can be used to forecast regional energy consumption and energy expenditure for majority, black, Hispanic, poor, and nonpoor households. The forecasts of key macroeconomic and energy variables used as exogenous variables in the MEAM were obtained from the Data Resources, Inc., Macromodel and Energy Model. Generally, the projections of household energy consumption, expenditure, and energy expenditure as share of income vary across population groups and census regions.

  1. Short-Term Energy Outlook January 2014

    Energy Information Administration (EIA) (indexed site)

    4 1 January 2014 Short-Term Energy Outlook (STEO) Highlights This edition of the Short-Term Energy Outlook is the first to include forecasts for 2015. After falling to the...

  2. Recent Federal Register Notices | Department of Energy

    Office of Environmental Management (EM)

    ... 80FR52210 08272015 Average Unit Cost of Energy N Notice of forecasting the representative average unit costs of energy 80FR52039 08262015 Commercial Fans and Blowers N Notice ...

  3. Short-Term Energy Outlook June 2013

    Annual Energy Outlook

    1 June 2013 Short-Term Energy Outlook (STEO) Highlights * After increasing to 119 per ... in 2013 and to 3.37 per gallon in 2014. Energy price forecasts are highly uncertain, and ...

  4. National forecast for geothermal resource exploration and development with techniques for policy analysis and resource assessment

    SciTech Connect

    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.

  5. Validation of Global Weather Forecast and Climate Models Over...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Validation of Global Weather Forecast and Climate Models Over the North Slope of Alaska Xie, Shaocheng Lawrence Livermore National Laboratory Klein, Stephen Lawrence Livermore ...

  6. NREL: Resource Assessment and Forecasting - Data and Resources

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Data and Resources National Solar Radiation Database NREL resource assessment and forecasting research information is available from the following sources. Renewable Resource Data ...

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

    SciTech Connect

    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.

  8. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis

    SciTech Connect

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

    2015-10-02

    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.

  9. FY 2004 Second Quarter Review Forecast of Generation Accumulated...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Bonneville Power Administration Power Business Line Generation (PBL) Accumulated Net Revenue Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net...

  10. PBL FY 2003 Third Quarter Review Forecast of Generation Accumulated...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    2003 Bonneville Power Administration Power Business Line Generation Accumulated Net Revenue Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net...

  11. Improving the Accuracy of Solar Forecasting Funding Opportunity...

    Energy Saver

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

  12. Turbulence-driven coronal heating and improvements to empirical forecasting of the solar wind

    SciTech Connect

    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 Alfvn 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.

  13. Comparison of measurements and particle-in-cell simulations of ion energy distribution functions in a capacitively coupled radio-frequency discharge

    SciTech Connect

    O'Connell, D.; Zorat, R.; Ellingboe, A. R.; Turner, M. M.

    2007-10-15

    The ion dynamics in the high-voltage sheath of a capacitively coupled radio-frequency plasma has been investigated using mass-resolved ion energy analysis in combination with a two-dimensional particle-in-cell (PIC) code. A symmetric confined discharge is designed allowing highly accurate comparisons of measured ion energy distribution functions in high-voltage sheaths with simulation results. Under the conditions investigated, the sheaths are not only collisional, but also chemically complex. This situation is common in applications but rare in laboratory experiments. Excellent agreement has been found for a hydrogen discharge benchmarking the code. Hydrogen is of particular interest since its light mass gives detailed insight into sheath dynamics, and an extensive database of collisional cross sections is available. The H{sub 3}{sup +} ion was found to be the dominant ion in the sheaths and the plasma bulk under most conditions investigated. H{sub 3}{sup +} exhibits the typical saddle-shaped ion energy distribution function indicative of ions created in the plasma bulk and traversing the entire sheath potential. H{sup +} and H{sub 2}{sup +} are predominantly formed through collisions in the high-voltage sheath. H{sub 2}{sup +} ion energy distribution functions show structures resulting from symmetric charge exchange collisions with the background gas. Minor discrepancies between the experimental results and PIC simulations indicate slightly lower plasma densities in the simulation, resulting in larger sheath width.

  14. Comparison of the Supplement to the 2004 IECC to the Current New York Energy Conservation Code - Residential Buildings

    SciTech Connect

    Lucas, Robert G.

    2004-09-01

    The New York State Department of State requested the U.S. Department of Energy (DOE) to prepare a report consisting of two components. The first component is an analysis comparing the effects on energy usage as a result of implementation of the 2004 Supplement to the IECC with the current New York code. The second component is an engineering analysis to determine whether additional costs of compliance with the proposal would be equal to or less than the present value of anticipated energy savings over a 10-year period. Under DOE's direction, Pacific Northwest National Laboratory (PNNL) completed the requested assessment of the potential code upgrade.

  15. Developing an industrial end-use forecast: A case study at the Los Angeles department of water and power

    SciTech Connect

    Mureau, T.H.; Francis, D.M.

    1995-05-01

    The Los Angeles Department of Water and Power (LADWP) uses INFORM 1.0 to forecast industrial sector energy. INFORM 1.0 provides an end-use framework that can be used to forecast electricity, natural gas or other fuels consumption. Included with INFORM 1.0 is a default date set including the input data and equations necessary to solve each model. LADWP has substituted service area specific data for the default data wherever possible. This paper briefly describes the steps LADWP follows in developing those inputs and application in INFORM 1.0.

  16. A Comparison of the 2003 and 2006 International Energy Conservation Codes to Determine the Potential Impact on Residential Building Energy Efficiency

    SciTech Connect

    Stovall, Therese K; Baxter, Van D

    2008-03-01

    The IECC was updated in 2006. As required in the Energy Conservation and Production Act of 1992, Title 3, DOE has a legislative requirement to "determine whether such revision would improve energy efficiency in residential buildings" within 12 months of the latest revision. This requirement is part of a three-year cycle of regular code updates. To meet this requirement, an independent review was completed using personnel experienced in building science but not involved in the code development process.

  17. Comparison of energy consumption between displacement and mixing ventilation systems for different U.S. buildings and climates

    SciTech Connect

    Hu, S.; Chen, Q.; Glicksman, L.R.

    1999-07-01

    A detailed computer simulation method was used to compare the energy consumption of a displacement ventilation system with that of a mixing ventilation system for three types of US buildings: a small office, a classroom, and an industrial workshop. The study examined five typical climatic regions as well as different building zones. It was found that a displacement ventilation system may use more fan energy and less chiller and boiler energy than a mixing ventilation system. The total energy consumption is slightly less using a displacement ventilation system. Both systems can use a similarly sized boiler. However, a displacement ventilation system requires a larger air-handling unit and a smaller chiller than the mixing ventilation system. The overall first costs are lower for the displacement ventilation if the system is applied for the core region of a building.

  18. Solar energy adoption patterns in the United States

    SciTech Connect

    Sawyer, S.W.; Sorrentino, A.; Wirtshafter, R.M.

    1984-01-01

    The paper reviews the status of solar energy commercialization in the United States for residential domestic water- and space-heating systems. Utilizing tax claims submitted to the Internal Revenue Service and U.S. Department of Energy data, adoption patterns in each state are determined and analyzed. The analyses include comparison with forecasts of solar feasibility and with other state characteristics. The solar market was found to be well established, although less active than suggested by life-cycle cost advantages. The national installation rate for 1980 and 1981 averaged 31 per 10,000 single family dwelling units. Major regional variations exist with highest rates in the West and the lowest in the central and southeast states. Adoption rates were found to be inversely related to the states' residential energy consumption levels and directly related to their petroleum dependency and insolation availability.

  19. Solar-energy adoption patterns in the United States

    SciTech Connect

    Sawyer, S.W.; Sorrentino, A.; Wirtshafter, R.M.

    1984-01-01

    This paper reviews the status of solar energy commercialization in the United States for residential domestic water- and space-heating systems. Utilizing tax claims submitted to the Internal Revenue Service and US Department of Energy data, adoption patterns in each state are determined and analyzed. The analyses include comparison with forecasts of solar feasibility and with other state characteristics. The solar market was found to be well established, although less active than suggested by life-cycle cost advantages. The national installation rate for 1980 and 1981 averaged 31 per 10,000 single family dwelling units. Major regional variations exist with highst rates in the West and the lowest in the central and southeast states. Adoption rates were found to be inversely related to the states' residential energy consumption levels and directly related to their petroleum dependency and insolation availability. 21 references, 1 figure, 4 tables.

  20. Waste generation forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1995-FY 2002, September 1994 revision

    SciTech Connect

    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.

  1. Technical analysis in short-term uranium price forecasting

    SciTech Connect

    Schramm, D.S.

    1990-03-01

    As market participants anticipate the end of the current uranium price decline and its subsequent reversal, increased attention will be focused upon forecasting future price movements. Although uranium is economically similar to other mineral commodities, it is questionable whether methodologies used to forecast price movements of such commodities may be successfully applied to uranium.

  2. A comparison of global optimization algorithms with standard benchmark functions and real-world applications using Energy Plus

    SciTech Connect

    Kamph, Jerome Henri; Robinson, Darren; Wetter, Michael

    2009-09-01

    There is an increasing interest in the use of computer algorithms to identify combinations of parameters which optimise the energy performance of buildings. For such problems, the objective function can be multi-modal and needs to be approximated numerically using building energy simulation programs. As these programs contain iterative solution algorithms, they introduce discontinuities in the numerical approximation to the objective function. Metaheuristics often work well for such problems, but their convergence to a global optimum cannot be established formally. Moreover, different algorithms tend to be suited to particular classes of optimization problems. To shed light on this issue we compared the performance of two metaheuristics, the hybrid CMA-ES/HDE and the hybrid PSO/HJ, in minimizing standard benchmark functions and real-world building energy optimization problems of varying complexity. From this we find that the CMA-ES/HDE performs well on more complex objective functions, but that the PSO/HJ more consistently identifies the global minimum for simpler objective functions. Both identified similar values in the objective functions arising from energy simulations, but with different combinations of model parameters. This may suggest that the objective function is multi-modal. The algorithms also correctly identified some non-intuitive parameter combinations that were caused by a simplified control sequence of the building energy system that does not represent actual practice, further reinforcing their utility.

  3. The Role Of IC Engines In Future Energy Use | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Of IC Engines In Future Energy Use The Role Of IC Engines In Future Energy Use Reviews future market trends and forecasts, and future engine challenges and research focus PDF icon ...

  4. Comparison of ground-derived and satellite-derived surface energy fluxes from a shrub-steppe site

    SciTech Connect

    Kirkham, R.R.; Gee, G.W. [Pacific Northwest Lab., Richland, WA (United States); Fritschen, L.J. [Washington Univ., Seattle, WA (United States)

    1994-03-01

    Efforts to measure evapotranspiration (ET) remotely are common in agriculture, and the application of such data to irrigation scheduling is readily apparent. Extending this methodology to arid environments is primarily of use as a mechanism for validation of ET algorithms used in large-scale watershed and global climate change modeling efforts. To facilitate testing of the remote sensing method for ET, measurements of sensible and latent heat flux were made at four sites located on the US Department of Energy`s Hanford Site using a combination of lysimeter and Bowen Ratio Energy Balance (BREB) stations. The objective was to calibrate an aerodynamic transport equation that relates sensible heat flux to radiant surface temperature, and to map sensible heat flux using Landsat data.

  5. Calculating the free energy of transfer of small solutes into a model lipid membrane: Comparison between metadynamics and umbrella sampling

    SciTech Connect

    Bochicchio, Davide; Panizon, Emanuele; Ferrando, Riccardo; Rossi, Giulia; Monticelli, Luca

    2015-10-14

    We compare the performance of two well-established computational algorithms for the calculation of free-energy landscapes of biomolecular systems, umbrella sampling and metadynamics. We look at benchmark systems composed of polyethylene and polypropylene oligomers interacting with lipid (phosphatidylcholine) membranes, aiming at the calculation of the oligomer water-membrane free energy of transfer. We model our test systems at two different levels of description, united-atom and coarse-grained. We provide optimized parameters for the two methods at both resolutions. We devote special attention to the analysis of statistical errors in the two different methods and propose a general procedure for the error estimation in metadynamics simulations. Metadynamics and umbrella sampling yield the same estimates for the water-membrane free energy profile, but metadynamics can be more efficient, providing lower statistical uncertainties within the same simulation time.

  6. 2007 Wholesale Power Rate Case Final Proposal : Market Price Forecast Study.

    SciTech Connect

    United States. Bonneville Power Administration.

    2006-07-01

    This study presents BPA's market price forecasts for the Final Proposal, which are based on AURORA modeling. AURORA calculates the variable cost of the marginal resource in a competitively priced energy market. In competitive market pricing, the marginal cost of production is equivalent to the market-clearing price. Market-clearing prices are important factors for informing BPA's power rates. AURORA was used as the primary tool for (a) estimating the forward price for the IOU REP Settlement benefits calculation for fiscal years (FY) 2008 and 2009, (b) estimating the uncertainty surrounding DSI payments and IOU REP Settlements benefits, (c) informing the secondary revenue forecast and (d) providing a price input used for the risk analysis. For information about the calculation of the secondary revenues, uncertainty regarding the IOU REP Settlement benefits and DSI payment uncertainty, and the risk run, see Risk Analysis Study WP-07-FS-BPA-04.

  7. Spectromicroscopy of poly(ethylene terephthalate): Comparison of spectra and radiation damage rates in X-ray absorption and electron energy loss

    SciTech Connect

    Rightor, E.G.; Hitchcock, A.P.; Urquhart, S.G.

    1997-03-13

    The C 1s and O 1s X-ray absorption spectra of poly(ethylene terephthalate) (PET) have been recorded using transmission, fluorescence, and electron yield detection. The corresponding electron energy loss spectra (EELS) have been recorded in a scanning transmission electron microscope. These results are compared to the C 1s and O 1s spectra of gas phase 1,4-dimethyl terephthalate (the monomer of PET) recorded using EELS. The comparison of monomer and polymer materials in different phases and with different techniques has aided the understanding of the relative strengths and limitations of each technique as well as assisting the spectral interpretation. Good agreement is found in the overall shape and the energies of the spectral features. Relatively minor differences in intensities can be understood in terms of the properties of the individual spectroscopic techniques. The critical dose for radiation damage by 100 keV electrons incident on PET at 100 K is found to be (1.45{+-}0.15)x10{sup 3} eV nm{sup -3}. In contrast, the critical dose for radiation damage by 302 eV X-rays incident on PET at 300 K is (1.2{+-}0.6)x10{sup 4} eV nm{sup -3}. A figure of merit involving the product of critical energy dose and spectral efficiency (as expressed by the appropriate G value) is developed. 59 refs., 5 figs., 4 tabs.

  8. ANL Wind Power Forecasting and Electricity Markets | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    Company Organization Argonne National Laboratory Partner Institute for Systems and Computer Engineering of Porto (INESC Porto) in Portugal, Midwest Independent System Operator...

  9. ENERGY

    Energy.gov [DOE] (indexed site)

    U.S. Department of ENERGY Department of Energy Quadrennial Technology Review-2015 Framing Document http:energy.govqtr 2015-01-13 Page 2 The United States faces serious ...

  10. Incorporating Forecast Uncertainty in Utility Control Center

    SciTech Connect

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

    2014-07-09

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

  11. Energy

    Office of Legacy Management (LM)

    Energy Washington; DC 20585 : . ' , - o" ' ' ,' DEC ?; ;y4,,, ' . The Honorable ... Dear,Mayor 'Kalwitz: " . " Secretary of Energy Hazel' O'Leary has announceha new,approach ...

  12. Using contingent valuation to explore willingness to pay for renewable energy: A comparison of collective and voluntary payment vehicles

    SciTech Connect

    Wiser, Ryan H.

    2002-07-28

    Some of the most basic questions about the organization and functioning of society involve issues raised by the existence of public goods. With respect to environmental public goods, how should funds used to support environmental improvement be collected and used? In particular, are collective, mandatory payments superior to voluntary, charitable payments due to the possibility of free riding? And to what degree should the government be involved in spending these funds: should the government directly fund environmental improvement projects or should the private sector be used to collect funds and determine funding priorities? This report explores these questions from the perspective of renewable energy: wind, geothermal, biomass, hydropower, and solar. In particular, this report analyzes the payment preferences of U.S. households through the implementation of a large-scale contingent valuation (CV) survey of willingness to pay (WTP) for renewable energy. Renewable energy can be supported through a mandatory ''tax'' on electric bills or through voluntary payments via green power marketing; the government may or may not be heavily involved in the collection and expenditure of such funds. The question of how households prefer to pay for renewable energy is therefore highly relevant. The primary objective of this study is to explore variations in stated WTP for renewable energy under the following four payment and provision contexts: (1) A mandatory increase in the electricity bills of all customers, the funds from which are collected and spent by the government on renewable energy projects. (2) A voluntary increase in the electricity bills of those customers who choose to pay, the funds from which are collected and spent by the government on renewable energy projects. (3) A voluntary increase in the electricity bills of those customers who choose to pay, the funds from which are collected and spent by electricity suppliers on renewable energy projects. (4) A mandatory

  13. Comparison of the incentives used to stimulate energy production in Japan, France, West Germany, and the United States

    SciTech Connect

    Cole, R.J.; Sommers, P.; Eschbach, C.; Sheppard, W.J.; Lenerz, D.E.; Huelshoff, M.; Marcus, A.A.

    1981-09-01

    This volume represents the culmination of a five-year research effort examining the incentives used to stimulate energy production in four countries, and the incentives used to stimulate energy consumption in one country. Following the theoretical approach developed for studying US energy incentives, the researchers in each country classified incentives into the following six categories: (1) Taxation, including exemption from or reduction of existing taxes; (2) Disbursements, in which the national government distributes money without requiring anything in return; (3) Requirements, including demands made by the government, backed by civil or criminal sanctions; (4) Traditional Services, including those almost always provided exclusively by a governmental entity; (5) Nontraditional Services, including those sometimes performed by non-governmental entities, as well as governmental entities (e.g., research and development); and (6) Market Activities, including government involvement in the market under conditions similar to those faced by non-governmental producers or consumers. A complete list of research reports prepared in the Federal Incentives series is provided in the Appendix.

  14. Energy Standard

    Gasoline and Diesel Fuel Update

    Standard as requested by Chairman Bingaman November 2011 Analysis of Impacts of a Clean www.eia.gov U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as

  15. Comparison of approaches to Total Quality Management. Including an examination of the Department of Energy`s position on quality management

    SciTech Connect

    Bennett, C.T.

    1994-03-01

    This paper presents a comparison of several qualitatively different approaches to Total Quality Management (TQM). The continuum ranges from management approaches that are primarily standards -- with specific guidelines, but few theoretical concepts -- to approaches that are primarily philosophical, with few specific guidelines. The approaches to TQM discussed in this paper include the International Organization for Standardization (ISO) 9000 Standard, the Malcolm Baldrige National Quality Award, Senge`s the Learning Organization, Watkins and Marsick`s approach to organizational learning, Covey`s Seven Habits of Highly Successful People, and Deming`s Fourteen Points for Management. Some of these approaches (Deming and ISO 9000) are then compared to the DOE`s official position on quality management and conduct of operations (DOE Orders 5700.6C and 5480.19). Using a tabular format, it is shown that while 5700.6C (Quality Assurance) maps well to many of the current approaches to TQM, DOE`s principle guide to management Order 5419.80 (Conduct of Operations) has many significant conflicts with some of the modern approaches to continuous quality improvement.

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

    SciTech Connect

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J.

    2011-12-06

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios

  17. Energy

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Energy Energy National security depends on science and technology. The United States relies on Los Alamos National Laboratory for the best of both. No place on Earth pursues a broader array of world-class scientific endeavors. Energy Overview Charlie McMillan, Director of Los Alamos National Laboratory 0:50 Director McMillan on energy security With energy use increasing across the nation and the world, Los Alamos National Laboratory is using its world-class scientific capabilities to enhance

  18. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema

    Gonzalez, Frank

    2016-07-12

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

  19. Uncle Sam Turns to SAM for Solar Modeling | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    and read the GAO report. Addthis Related Articles Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% Solar Energy to Benefit from New FERC Interconnection...

  20. Short-Term Energy Outlook Model Documentation: Coal Supply, Demand, and Prices

    Reports and Publications

    2016-01-01

    The coal module of the Short-Term Energy Outlook (STEO) model is designed to provide forecasts of U.S. production, consumption, imports, exports, inventories, and prices.

  1. A Field Study Comparison of the Energy and Moisture Performance Characteristics of Ventilated Versus Sealed Crawl Spaces in the South

    SciTech Connect

    Bruce Davis; Cyrus Dastur; William E. Warren; Shawn Fitzpatrick; Christine Maurer; Rob Stevens; Terry Brennan; William Rose

    2005-06-22

    This study compared the performance of closed crawl spaces, which had sealed foundation wall vents, a sealed polyethylene film liner and various insulation and drying strategies, to traditional wall-vented crawl spaces with perimeter wall vents and polyethylene film covering 100% of the ground surface. The study was conducted at 12 owner-occupied, all electric, single-family detached houses with the same floor plan located on one cul-de-sac in the southeastern United States. Using the matched pairs approach, the houses were divided into three study groups of four houses each. Comparative data was recorded for each house to evaluate sub-metered heat pump energy consumption, relative humidity, wood moisture content, duct infiltration, house infiltration, temperature, radon, and bioaerosol levels. Findings indicated that in the humid conditions of the southeastern United States, a properly closed crawl space is a robust construction measure that produces a substantially drier crawl space and significantly reduces occupied space conditioning energy use on an annual basis.

  2. A comparison of ion beam measurements by retarding field energy analyzer and laser induced fluorescence in helicon plasma devices

    SciTech Connect

    Gulbrandsen, N. Fredriksen, Å.; Carr, J.; Scime, E.

    2015-03-15

    Both Laser-Induced Fluorescence (LIF) and Retarding Field Energy Analyzers (RFEA) have been applied to the investigation of beams formed in inductively coupled helicon plasmas. While the LIF technique provides a direct measurement of the velocity distribution in the plasma, the RFEA measures ion flux as a function of a retarding potential. In this paper, we present a method to compare the two techniques, by converting the LIF velocity distribution to an equivalent of a RFEA measurement. We applied this method to compare new LIF and RFEA measurements in two different experiments; the Hot Helicon Experiment (HELIX) - Large Experiment on Instabilities and Anisotropies (LEIA) at West Virginia University and Njord at University of Tromsø. We find good agreement between beam energies of the two methods. In agreement with earlier observations, the RFEA is found to measure ion beams with densities too low for the LIF to resolve. In addition, we present measurements of the axial development of the ion beam in both experiments. Beam densities drop exponentially with distance from the source, both in LIF and RFEA measurements. The effective quenching cross section from LIF in LEIA is found to be σ{sub b,*}=4×10{sup −19} m{sup 2}, and the effective beam collisional cross sections by RFEA in Njord to be σ{sub b}=1.7×10{sup −18} m{sup 2}.

  3. Evaluation of Forecasted Southeast Pacific Stratocumulus in the NCAR, GFDL and ECMWF Models

    SciTech Connect

    Hannay, C; Williamson, D L; Hack, J J; Kiehl, J T; Olson, J G; Klein, S A; Bretherton, C S; K?hler, M

    2008-01-24

    We examine forecasts of Southeast Pacific stratocumulus at 20S and 85W during the East Pacific Investigation of Climate (EPIC) cruise of October 2001 with the ECMWF model, the Atmospheric Model (AM) from GFDL, the Community Atmosphere Model (CAM) from NCAR, and the CAM with a revised atmospheric boundary layer formulation from the University of Washington (CAM-UW). The forecasts are initialized from ECMWF analyses and each model is run for 3 days to determine the differences with the EPIC field data. Observations during the EPIC cruise show a stable and well-mixed boundary layer under a sharp inversion. The inversion height and the cloud layer have a strong and regular diurnal cycle. A key problem common to the four models is that the forecasted planetary boundary layer (PBL) height is too low when compared to EPIC observations. All the models produce a strong diurnal cycle in the Liquid Water Path (LWP) but there are large differences in the amplitude and the phase compared to the EPIC observations. This, in turn, affects the radiative fluxes at the surface. There is a large spread in the surface energy budget terms amongst the models and large discrepancies with observational estimates. Single Column Model (SCM) experiments with the CAM show that the vertical pressure velocity has a large impact on the PBL height and LWP. Both the amplitude of the vertical pressure velocity field and its vertical structure play a significant role in the collapse or the maintenance of the PBL.

  4. Asia-Pacific energy database

    SciTech Connect

    1997-06-01

    Statistical data is presented in graphic and tabular form on the petroleum market in Asia and Pacific nations. Seven major categories are reported: (1) primary energy production and consumption; (2) historical petroleum product demand and forecasts; (3) crude oil production and exports; (4) import dependence; (5) crude and product pricing assumptions; (6) market share of refined products by suppliers in selected countries; and (7) refining margins. Petroleum demand and forecasts and crude oil production and exports are reported by country. Historical data are presented from 1970 through 1996, and forecasts are made through 2010.

  5. Comparison of TG-43 and TG-186 in breast irradiation using a low energy electronic brachytherapy source

    SciTech Connect

    White, Shane A.; Landry, Guillaume; Reniers, Brigitte; Fonseca, Gabriel Paiva; Beaulieu, Luc; Verhaegen, Frank

    2014-06-15

    Purpose: The recently updated guidelines for dosimetry in brachytherapy in TG-186 have recommended the use of model-based dosimetry calculations as a replacement for TG-43. TG-186 highlights shortcomings in the water-based approach in TG-43, particularly for low energy brachytherapy sources. The Xoft Axxent is a low energy (<50 kV) brachytherapy system used in accelerated partial breast irradiation (APBI). Breast tissue is a heterogeneous tissue in terms of density and composition. Dosimetric calculations of seven APBI patients treated with Axxent were made using a model-based Monte Carlo platform for a number of tissue models and dose reporting methods and compared to TG-43 based plans. Methods: A model of the Axxent source, the S700, was created and validated against experimental data. CT scans of the patients were used to create realistic multi-tissue/heterogeneous models with breast tissue segmented using a published technique. Alternative water models were used to isolate the influence of tissue heterogeneity and backscatter on the dose distribution. Dose calculations were performed using Geant4 according to the original treatment parameters. The effect of the Axxent balloon applicator used in APBI which could not be modeled in the CT-based model, was modeled using a novel technique that utilizes CAD-based geometries. These techniques were validated experimentally. Results were calculated using two dose reporting methods, dose to water (D{sub w,m}) and dose to medium (D{sub m,m}), for the heterogeneous simulations. All results were compared against TG-43-based dose distributions and evaluated using dose ratio maps and DVH metrics. Changes in skin and PTV dose were highlighted. Results: All simulated heterogeneous models showed a reduced dose to the DVH metrics that is dependent on the method of dose reporting and patient geometry. Based on a prescription dose of 34 Gy, the average D{sub 90} to PTV was reduced by between ?4% and ?40%, depending on the scoring

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

    Energy.gov [DOE]

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

  7. Comparisons of neutrino event generators from an oscillation...

    Office of Scientific and Technical Information (OSTI)

    of high energy physics data, ideally giving a baseline comparison between the state-of-art theoretical models and experimental data. Presented here is a comparison between three...

  8. Fuel Cell Comparison of Distributed Power Generation Technologies

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    4 Fuel Cycle Comparison of Distributed Power Generation Technologies Energy Systems ... or UChicago Argonne, LLC. ANLESD08-4 Fuel Cycle Comparison of Distributed Power ...

  9. Issues in Midterm Analysis and Forecasting

    Reports and Publications

    1999-01-01

    Final issue of this report. Presents a series of eight papers, which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1999, as well as other significant issues in midterm energy markets.

  10. NREL: Energy Analysis - Paul Denholm

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Denholm Photo of Paul Denholm Paul Denholm is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Senior Analyst On staff since October 2004 Phone number: 303-384-7488 E-mail: paul.denholm@nrel.gov Areas of expertise Modeling of electric power systems, including interaction of renewable and conventional energy technologies Analysis of energy storage including thermal energy storage Primary research interests Effects of large-scale renewable energy

  11. Solar Trackers Market Forecast | OpenEI Community

    OpenEI (Open Energy Information) [EERE & EIA]

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

  12. Value of Improved Short-Term Wind Power Forecasting

    SciTech Connect

    Hodge, B. M.; Florita, A.; Sharp, J.; Margulis, M.; Mcreavy, D.

    2015-02-01

    This report summarizes an assessment of improved short-term wind power forecasting in the California Independent System Operator (CAISO) market and provides a quantification of its potential value.

  13. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect

    Yoo, Wucherl; Sim, Alex

    2014-07-07

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

  14. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    U.S. DEPARTMENT OF HP IENERGY Office of Science DOESC-ARM-15-024 915-MHz Wind Profiler ... M Jensen et al., March 2016, DOESC-ARM-15-024 915-MHz Wind Profiler for Cloud Forecasting ...

  15. PBL FY 2002 Second Quarter Review Forecast of Generation Accumulated...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Slice true-ups, and actual expense levels. Any variation of these can change the net revenue situation. FY 2002 Forecasted Second Quarter Results 170 (418) FY 2002 Unaudited...

  16. Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels

    Reports and Publications

    2003-01-01

    This paper presents a short-term monthly forecasting model of West Texas Intermediate crude oil spot price using Organization for Economic Cooperation and Development (OECD) petroleum inventory levels.

  17. Treatment planning for radiotherapy with very high-energy electron beams and comparison of VHEE and VMAT plans

    SciTech Connect

    Bazalova-Carter, Magdalena; Qu, Bradley; Palma, Bianey; Jensen, Christopher; Maxim, Peter G. E-mail: BWLoo@Stanford.edu; Loo, Billy W. E-mail: BWLoo@Stanford.edu; Hårdemark, Björn; Hynning, Elin

    2015-05-15

    Purpose: The aim of this work was to develop a treatment planning workflow for rapid radiotherapy delivered with very high-energy electron (VHEE) scanning pencil beams of 60–120 MeV and to study VHEE plans as a function of VHEE treatment parameters. Additionally, VHEE plans were compared to clinical state-of-the-art volumetric modulated arc therapy (VMAT) photon plans for three cases. Methods: VHEE radiotherapy treatment planning was performed by linking EGSnrc Monte Carlo (MC) dose calculations with inverse treatment planning in a research version of RayStation. In order to study the effect of VHEE treatment parameters on VHEE dose distributions, a MATLAB graphical user interface (GUI) for calculation of VHEE MC pencil beam doses was developed. Through the GUI, pediatric case MC simulations were run for a number of beam energies (60, 80, 100, and 120 MeV), number of beams (13, 17, and 36), pencil beam spot (0.1, 1.0, and 3.0 mm) and grid (2.0, 2.5, and 3.5 mm) sizes, and source-to-axis distance, SAD (40 and 50 cm). VHEE plans for the pediatric case calculated with the different treatment parameters were optimized and compared. Furthermore, 100 MeV VHEE plans for the pediatric case, a lung, and a prostate case were calculated and compared to the clinically delivered VMAT plans. All plans were normalized such that the 100% isodose line covered 95% of the target volume. Results: VHEE beam energy had the largest effect on the quality of dose distributions of the pediatric case. For the same target dose, the mean doses to organs at risk (OARs) decreased by 5%–16% when planned with 100 MeV compared to 60 MeV, but there was no further improvement in the 120 MeV plan. VHEE plans calculated with 36 beams outperformed plans calculated with 13 and 17 beams, but to a more modest degree (<8%). While pencil beam spacing and SAD had a small effect on VHEE dose distributions, 0.1–3 mm pencil beam sizes resulted in identical dose distributions. For the 100 MeV VHEE pediatric

  18. A Comparison of the Performance Capabilities of Radioisotope Energy Conversion Systems, Betavoltaic Cells, and other Nuclear Batteries

    SciTech Connect

    Steinfelds, Eric V; Prelas, Mark A.; Sudarshan, Loyalka K.; Tompson, Robert V.

    2006-07-01

    In this paper we compare the potential performance capabilities of several types of nuclear batteries to the Radioisotope Thermocouple Generators (RTG's) currently in use. There have been theoretical evaluations of, and some experimental testing of, several types of nuclear batteries including Radioisotope Energy Conversion Systems (RECS), Direct Energy Conversion (DEC) systems, and Betavoltaic Power Cells (BPC's). It has been theoretically shown, and to some extent experimentally demonstrated, that RECS, capacitive DEC systems, and possibly BPC's are all potentially capable of efficiencies well above the 9% maximum efficiency demonstrated to date in RTG's customized for deep space probe applications. Even though RTG's have proven their reliability and have respectable power to mass ratios, it is desirable to attain efficiencies of at least 25% in typical applications. High fuel efficiency is needed to minimize the quantities of radioisotopic or nuclear fuels in the systems, to maximize power to mass ratios, and to minimize housing requirements. It has been shown that RECS can attain electric power generation efficiencies greater than 18% for devices which use Sr-90 fuel and where the accompanying material is less than roughly twice the mass of the Sr-90 fuel. Other radioisotopic fuels such as Pu-238 or Kr-85 can also be placed into RECS in order to attain efficiencies over 18%. With the likely exception of one fuel investigated by the authors, all of the promising candidates for RECS fuels can attain electric power to mass ratios greater than 15 W kg{sup -1}. It has been claimed recently [1] that the efficiency of tritium-fueled BPC's can be as high as 25%. While this is impressive and tritium has the benefit of being a 'soft' radioisotopic fuel, the silicon wafer that holds the tritium would have to be considerably more massive than the tritium contained within it and immediately adjacent to the wafer. Considering realistic mass requirements for the presence of

  19. Study forecasts disappearance of conifers due to climate change

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Study forecasts disappearance of conifers due to climate change Study forecasts disappearance of conifers due to climate change New results, reported in a paper released today in the journal Nature Climate Change, suggest that global models may underestimate predictions of forest death. December 21, 2015 Los Alamos scientist Nate McDowell discusses how climate change is killing trees with PBS NewsHour reporter Miles O'Brien. Los Alamos scientist Nate McDowell discusses how climate change is

  20. Update from the Director: David Conrad | Department of Energy

    Energy Saver

    Complex Terrain | Department of Energy Wind Forecasting Improvement Project in Complex Terrain Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain February 12, 2014 - 10:47am Addthis On February 11, 2014 the Wind Program announced a Notice of Intent to issue a funding opportunity entitled "Wind Forecasting Improvement Project in Complex Terrain." By researching the physical processes that take place in complex terrain, this funding would improve

  1. Short-Term Energy Outlook

    Gasoline and Diesel Fuel Update

    6 1 October 2016 Short-Term Energy Outlook (STEO) Forecast highlights Winter Fuels Outlook  EIA projects average U.S. household expenditures for natural gas, heating oil, electricity, and propane will increase this winter (October 1 through March 31) compared with last winter. Based on projections from the National Oceanic and Atmospheric Administration (NOAA), forecast temperatures this winter, measured using heating degree days, are 3% warmer than the previous 10-year average but colder

  2. Regional Short-Term Energy Model (RSTEM) Overview

    Reports and Publications

    2009-01-01

    The Regional Short-Term Energy Model (RSTEM) utilizes estimated econometric relationships for demand, inventories and prices to forecast energy market outcomes across key sectors and selected regions throughout the United States.

  3. Weather-based forecasts of California crop yields

    SciTech Connect

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

    2005-09-26

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

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

    SciTech Connect

    Koomey, J.G.; Brown, R.E.; Richey, R.

    1995-12-01

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

  5. U.S. Energy Information Administration (EIA)

    Gasoline and Diesel Fuel Update

    | PricesDemandSupply | Storage In the News: EIA projects lower natural gas use this winter The U.S. Energy Information Administration (EIA) forecasts that reduced natural gas...

  6. Lawrence Livermore National Laboratory | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    4.7 Geothermal 4.8 Wind forecasting 4.9 Underground coal gasification 4.10 Geologic carbon sequestration 4.11 Vehicle aerodynamics 5 Analysis in energy and environment 5.1...

  7. NREL: Resource Assessment and Forecasting - Capabilities

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Best Practices Handbook Helps Industry Collect and Interpret Solar Resource Data Read about this ... staff provides expertise in renewable energy measurement and instrumentation. ...

  8. AVLIS: a technical and economic forecast

    SciTech Connect

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

    1986-01-01

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

  9. Control and Size Energy Storage for Managing Energy balance of Variable Generation Resources

    SciTech Connect

    Ke, Xinda; Lu, Ning; Jin, Chunlian

    2015-01-01

    This paper presents control algorithms and sizing strategies for using energy storage to manage energy balance for variable generation resources. The control objective is to minimize the hourly generation imbalance between the actual and the scheduled generation of the wind farm. Three control algorithms are compared: tracking power imbalance, post-compensation, and pre-compensation. Measurement data from a wind farm located in South-central Washington State are used in the study. The results show that tracking power imbalance yields the best performance by keeping the hourly energy imbalances zero. However, the energy storage system (ESS) will be significantly oversized. Post-compensation reduces power rating of the ESS but the hourly imbalance may not be kept as zero when large and long-lasting energy imbalances occur. A linear regression forecasting algorithm is developed for the pre-compensation algorithm to pre-charge or pre-discharge the ESS based on predicted energy imbalances. The performance comparison shows that the pre-compensation method significantly reduces the size of the ESS while maintaining satisfactory performance.

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

    SciTech Connect

    1995-08-02

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

  11. U.S. Energy Information Administration (EIA)

    Gasoline and Diesel Fuel Update

    January 9, 2013 | Release date: January 10, 2013 | Next release: January 17, 2013 | Previous weeks JUMP TO: In The News | Overview | Prices/Supply/Demand | Storage In the News: EIA forecasts continued growth in Lower 48 onshore natural gas production through 2014. EIA's January Short-Term Energy Outlook (STEO), released on January 7, now includes EIA's forecast of energy consumption, supply, and prices through 2014. STEO expects continued growth in natural gas production, driven largely by

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

    SciTech Connect

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

    1997-01-07

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

  13. Forecasting the 2013–2014 influenza season using Wikipedia

    DOE PAGES [OSTI]

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

    2015-05-14

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

  14. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect

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

    2015-05-14

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

  15. NREL: Energy Analysis - Greg Brinkman

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Greg Brinkman Photo of Greg Brinkman Greg Brinkman is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Energy Analysis Engineer On staff since May 2009 Phone number: 303-384-7390 E-mail: gregory.brinkman@nrel.gov Areas of expertise Unit commitment and dispatch modeling of electric power systems Emission estimation from electric power systems Air quality modeling Primary research interests Integration of renewable energy, energy efficiency, and

  16. NREL: Energy Analysis - Jennie Jorgenson

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Jennie Jorgenson Photo of Jennie Jorgenson Jennie Jorgenson is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Energy Systems Modeling Engineer On staff since September 2012 Phone number: 303-275-3103 E-mail: jennie.jorgenson@nrel.gov Areas of expertise Energy systems modeling with SAM Unit commitment and dispatch modeling Integrating concentrating solar power, energy storage, and demand response into power grid models Quantitative/statistical

  17. Validation of a 20-year forecast of US childhood lead poisoning: Updated prospects for 2010

    SciTech Connect

    Jacobs, David E. . E-mail: dejacobs@starpower.net; Nevin, Rick

    2006-11-15

    We forecast childhood lead poisoning and residential lead paint hazard prevalence for 1990-2010, based on a previously unvalidated model that combines national blood lead data with three different housing data sets. The housing data sets, which describe trends in housing demolition, rehabilitation, window replacement, and lead paint, are the American Housing Survey, the Residential Energy Consumption Survey, and the National Lead Paint Survey. Blood lead data are principally from the National Health and Nutrition Examination Survey. New data now make it possible to validate the midpoint of the forecast time period. For the year 2000, the model predicted 23.3 million pre-1960 housing units with lead paint hazards, compared to an empirical HUD estimate of 20.6 million units. Further, the model predicted 498,000 children with elevated blood lead levels (EBL) in 2000, compared to a CDC empirical estimate of 434,000. The model predictions were well within 95% confidence intervals of empirical estimates for both residential lead paint hazard and blood lead outcome measures. The model shows that window replacement explains a large part of the dramatic reduction in lead poisoning that occurred from 1990 to 2000. Here, the construction of the model is described and updated through 2010 using new data. Further declines in childhood lead poisoning are achievable, but the goal of eliminating children's blood lead levels {>=}10 {mu}g/dL by 2010 is unlikely to be achieved without additional action. A window replacement policy will yield multiple benefits of lead poisoning prevention, increased home energy efficiency, decreased power plant emissions, improved housing affordability, and other previously unrecognized benefits. Finally, combining housing and health data could be applied to forecasting other housing-related diseases and injuries.

  18. Electric-utility DSM programs: 1990 data and forecasts to 2000

    SciTech Connect

    Hirst, E.

    1992-06-01

    In April 1992, the Energy Information Administration (EIA) released data on 1989 and 1990 electric-utility demand-site management (DMS) programs. These data represent a census of US utility DSM programs, with reports of utility expenditures, energy savings, and load reductions caused by these programs. In addition, EIA published utility estimates of the costs and effects of these programs from 1991 to 2000. These data provide the first comprehensive picture of what utilities are spending and accomplishing by utility, state, and region. This report presents, summarizes, and interprets the 1990 data and the utility forecasts of their DSM-program expenditures and impacts to the year 2000. Only utilities with annual sales greater than 120 GWh were required to report data on their DSM programs to EIA. Of the 1194 such utilities, 363 reported having a DSM program that year. These 363 electric utilities spent $1.2 billion on their DSM programs in 1990, up from $0.9 billion in 1989. Estimates of energy savings (17,100 GWh in 1990 and 14,800 GWh in 1989) and potential reductions in peak demand (24,400 MW in 1990 and about 19,400 MW in 1989) also showed substantial increases. Overall, utility DSM expenditures accounted for 0.7% of total US electric revenues, while the reductions in energy and demand accounted for 0.6% and 4.9% of their respective 1990 national totals. The investor-owned utilities accounted for 70 to 90% of the totals for DSM costs, energy savings, and demand reductions. The public utilities reported larger percentage reductions in peak demand and energy smaller percentage DSM expenditures. These averages hide tremendous variations across utilities. Utility forecasts of DSM expenditures and effects show substantial growth in both absolute and relative terms.

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

    SciTech Connect

    BARCOT, R.A.

    2000-08-31

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

  20. Long History of IAM Comparisons

    SciTech Connect

    Smith, Steven J.; Clarke, Leon E.; Edmonds, James A.; Kejun, Jiang; Kriegler, Elmar; Masui, Toshihiko; Riahi, Keywan; Shukla, Priyadarshi R.; Tavoni, Massimo; Van Vuuren, Detlef; Weyant, John

    2015-04-23

    Correspondence to editor: We agree with the editors that the assumptions behind models of all types, including integrated assessment models (IAMs), should be as transparent as possible. The editors were in error, however, when they implied that the IAM community is just “now emulating the efforts of climate researchers by instigating their own model inter-comparison projects (MIPs).” In fact, model comparisons for integrated assessment and climate models followed a remarkably similar trajectory. Early General Circulation Model (GCM) comparison efforts, evolved to the first Atmospheric Model Inter-comparison Project (AMIP), which was initiated in the early 1990s. Atmospheric models evolved to coupled atmosphere-ocean models (AOGCMs) and results from the first Coupled Model Inter-Comparison Project (CMIP1) become available about a decade later. Results of first energy model comparison exercise, conducted under the auspices of the Stanford Energy Modeling Forum, were published in 1977. A summary of the first comparison focused on climate change was published in 1993. As energy models were coupled to simple economic and climate models to form IAMs, the first comparison exercise for IAMs (EMF-14) was initiated in 1994, and IAM comparison exercises have been on-going since this time.

  1. Energy

    Annual Energy Outlook

    M onthly Energy Re< view Ila A a m 0 II 8 IIIW *g U In this issue: New data on nuclear electricity in Eastern Europe (Table 10.4) 9'Ij a - Ordering Information This publication...

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

    SciTech Connect

    Porter, K.; Rogers, J.

    2012-04-01

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

  3. Compiler Comparisons

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Compiler 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 provided by Cray, and they are invoked with wrapper modules that ensure that each compiler links with the proper system and MPI libraries. Each of the compilers have a wide variety of options that control the level of optimization of the exectuable code they produce. We have collected several optimization

  4. A Scenario Generation Method for Wind Power Ramp Events Forecasting

    SciTech Connect

    Cui, Ming-Jian; Ke, De-Ping; Sun, Yuan-Zhang; Gan, Di; Zhang, Jie; Hodge, Bri-Mathias

    2015-07-03

    Wind power ramp events (WPREs) have received increasing attention in recent years due to their significant impact on the reliability of power grid operations. In this paper, a novel WPRE forecasting method is proposed which is able to estimate the probability distributions of three important properties of the WPREs. To do so, a neural network (NN) is first proposed to model the wind power generation (WPG) as a stochastic process so that a number of scenarios of the future WPG can be generated (or predicted). Each possible scenario of the future WPG generated in this manner contains the ramping information, and the distributions of the designated WPRE properties can be stochastically derived based on the possible scenarios. Actual data from a wind power plant in the Bonneville Power Administration (BPA) was selected for testing the proposed ramp forecasting method. Results showed that the proposed method effectively forecasted the probability of ramp events.

  5. CCPP-ARM Parameterization Testbed Model Forecast Data

    DOE Data Explorer

    Klein, Stephen

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

  6. CCPP-ARM Parameterization Testbed Model Forecast Data

    DOE Data Explorer

    Klein, Stephen

    2008-01-15

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

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

    Gasoline and Diesel Fuel Update

    5 1 Short-Term Energy Outlook August 2005 Short-Term Energy Outlook - Regional Enhancements Starting with this edition of the Short-Term Energy Outlook (STEO), EIA is introducing regional projections (the scope of which will vary by fuel) of energy prices, consumption, and production. The addition of regional data and forecasts will allow us to examine regional fuel demands and prices, regional fuel inventory trends, the interaction between regional electricity demand shifts, and regional

  8. Are there Gains from Pooling Real-Time Oil Price Forecasts?

    Energy Information Administration (EIA) (indexed site)

    ... Gamma and that of Q is inverse Wishart. 5 Our forecasts take into account that the model parameters continue to drift over the forecast horizon according to their law of motion. ...

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

    SciTech Connect

    Piwko, R.; Jordan, G.

    2011-11-01

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

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

    SciTech Connect

    Porter, K.; Rogers, J.

    2010-04-01

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

  11. Final Report - Integration of Behind-the-Meter PV Fleet Forecasts...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

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

  12. NREL: Energy Analysis - Clayton Barrows

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Clayton Barrows Photo of Clayton Barrows Clayton Barrows is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Electric System Modeler On staff since January 2013 Phone number: 303-275-3921 E-mail: clayton.barrows@nrel.gov Areas of expertise Power system modeling Primary research interests Power and energy systems Complex system optimization Network science Education and background training Ph.D. in energy and mineral engineering, Penn State, 2013 B.S.

  13. NREL: Energy Analysis - Daniel Steinberg

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Steinberg Photo of Daniel Steinberg Daniel Steinberg is a section supervisor of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Senior Policy and Economic Analyst - Electricity Planning Section Supervisor On staff since September 2009 Phone number: 303-275-4287 E-mail: daniel.steinberg@nrel.gov Areas of expertise Energy policy and regulatory analysis Econometric analysis Modeling of interactions between climate change and the energy sector Primary research

  14. NREL: Energy Analysis - Dave Bielen

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Dave Bielen Photo of Dave Bielen Dave Bielen is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Energy and Environmental Policy Analyst On staff since June 2015 Phone number: 303-275-4921 E-mail: david.bielen@nrel.gov Areas of expertise Environmental policy design Dynamic programming Time series and microeconometric analysis Primary research interests Distributional impact analysis of environmental and energy policy GHG emissions mitigation in the

  15. NREL: Energy Analysis - Janine Freeman

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Janine Freeman Photo of Janine Freeman Janine Freeman is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Energy System Modeling Engineer On staff since March 2013 Phone number: 303-275-4694 E-mail: janine.freeman@nrel.gov Areas of expertise Solar instrumentation PV energy production modeling Solar resource estimates Vertical axis wind turbine analysis/wind tunnel experimentation PVsyst CAD modeling Campbell Scientific LoggerNet Matlab Primary

  16. NREL: Energy Analysis - Laura Vimmerstedt

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Laura Vimmerstedt Photo of Laura Vimmerstedt Laura Vimmerstedt is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Senior Environmental Analyst - Transportation, Fuels, and Environmental Impacts Section Supervisor On staff since 1994 Phone number: 303-384-7346 E-mail: laura.vimmerstedt@nrel.gov Areas of expertise Climate change policy analysis Renewable energy modeling Air-quality regulatory implications for energy technologies Primary research

  17. EIA - Energy Conferences & Presentations.

    Gasoline and Diesel Fuel Update

    5 EIA Conference 2010 Session 5: Energy and the Economy Moderator: Adam Sieminski, Deutsche Bank Speakers: Stephen P. A. Brown, Resources for the Future Donald L. Paul, University of Southern California Energy Institute Moderator and Speaker Biographies Adam Sieminski is the Chief Energy Economist for Deutsche Bank, working with the Bank's global commodities research and trading units. Drawing on extensive industry, government and academic sources, Mr. Sieminski forecasts energy market trends

  18. Electric power transmission for a Hanford Nuclear Energy Center (HNEC)

    SciTech Connect

    Harty, H.; Dowis, W.J.

    1983-06-01

    The original study of transmission for a Hanford Nuclear Energy Center (HNEC), which was completed in September 1975, was updated in June 1978. The present 1983 revision takes cognizance of recent changes in the electric power situation of the PNW with respect to: (1) forecasts of load growth, (2) the feasibility of early use of 1100 kV transmission, and (3) the narrowing opportunities for siting nuclear plants in the region. The purpose of this update is to explore and describe additions to the existing transmission system that would be necessary to accommodate three levels of generation at HNEC. Comparisons with a PNW system having new thermal generating capacity distributed throughout the marketing region are not made as was done in earlier versions.

  19. Energy Markets

    Gasoline and Diesel Fuel Update

    Cyclical and Structural Changes in Oil Markets for Columbia University January 29, 2016 | New York, NY by Adam Sieminski, Administrator U.S. Energy Information Administration Forecast -2 -1 0 1 2 3 4 5 6 7 82 84 86 88 90 92 94 96 98 100 2011-Q1 2012-Q1 2013-Q1 2014-Q1 2015-Q1 2016-Q1 2017-Q1 Implied stock change and balance (right axis) World production (left axis) World consumption (left axis) world supply and demand million barrels per day implied stock change million barrels per day Oil

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

    SciTech Connect

    Porter, K.; Rogers, J.

    2009-12-01

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

  1. Minority energy assessment report. Fall 1992

    SciTech Connect

    Teotia, A.P.S.; Poyer, D.A.; Lampley, L.; Anderson, J.L.

    1992-12-01

    The purpose of this research is to project household energy consumption, energy expenditure, and energy expenditure as share of income for five population groups from 1991 to 2009. The approach uses the Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory for the US Department of Energy`s Office of Minority Economic Impact. The MEAM provides a framework that can be used to forecast regional energy consumption and energy expenditure for majority, black, Hispanic, poor, and nonpoor households. The forecasts of key macroeconomic and energy variables used as exogenous variables in the MEAM were obtained from the Data Resources, Inc., Macromodel and Energy Model. Generally, the projections of household energy consumption, expenditure, and energy expenditure as share of income vary across population groups and census regions.

  2. U.S. Energy Information Administration (EIA)

    Gasoline and Diesel Fuel Update

    13, 2016 | Release date: January 14, 2016 | Next release: January 21, 2016 | Previous weeks JUMP TO: In The News | Overview | Prices/Supply/Demand | Storage In the News: EIA forecasts that the United States will be a net exporter of natural gas in mid 2017 Driven by new liquefied natural gas (LNG) export capacity, the United States is forecast to be a net exporter of natural gas by mid-2017, according to EIA's January Short-Term Energy Outlook. Forecasts for continuing declines of U.S. pipeline

  3. Risk-Based Comparison of Carbon Capture Technologies

    SciTech Connect

    Engel, David W.; Dalton, Angela C.; Dale, Crystal; Jones, Edward

    2013-05-01

    In this paper, we describe an integrated probabilistic risk assessment methodological framework and a decision-support tool suite for implementing systematic comparisons of competing carbon capture technologies. Culminating from a collaborative effort among national laboratories under the Carbon Capture Simulation Initiative (CCSI), the risk assessment framework and the decision-support tool suite encapsulate three interconnected probabilistic modeling and simulation components. The technology readiness level (TRL) assessment component identifies specific scientific and engineering targets required by each readiness level and applies probabilistic estimation techniques to calculate the likelihood of graded as well as nonlinear advancement in technology maturity. The technical risk assessment component focuses on identifying and quantifying risk contributors, especially stochastic distributions for significant risk contributors, performing scenario-based risk analysis, and integrating with carbon capture process model simulations and optimization. The financial risk component estimates the long-term return on investment based on energy retail pricing, production cost, operating and power replacement cost, plan construction and retrofit expenses, and potential tax relief, expressed probabilistically as the net present value distributions over various forecast horizons.

  4. Weather Research and Forecasting Model with the Immersed Boundary Method

    Energy Science and Technology Software Center

    2012-05-01

    The Weather Research and Forecasting (WRF) Model with the immersed boundary method is an extension of the open-source WRF Model available for wwww.wrf-model.org. The new code modifies the gridding procedure and boundary conditions in the WRF model to improve WRF's ability to simutate the atmosphere in environments with steep terrain and additionally at high-resolutions.

  5. NREL: Energy Analysis - Matthew O'Connell

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Matthew O'Connell Photo of Matthew O'Connell. Matthew O'Connell is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Energy Systems Engineer On staff since December 2014 Phone number: 303-384-7445 E-mail: matthew.oconnell@nrel.gov Areas of expertise Wind ramp detection methods Energy storage systems for renewable energy generation Statistical data analysis and modeling Primary research interests Increased renewable energy penetration in the electric

  6. Mesoscale and Large-Eddy Simulations for Wind Energy

    SciTech Connect

    Marjanovic, N

    2011-02-22

    Operational wind power forecasting, turbine micrositing, and turbine design require high-resolution simulations of atmospheric flow over complex terrain. The use of both Reynolds-Averaged Navier Stokes (RANS) and large-eddy (LES) simulations is explored for wind energy applications using the Weather Research and Forecasting (WRF) model. To adequately resolve terrain and turbulence in the atmospheric boundary layer, grid nesting is used to refine the grid from mesoscale to finer scales. This paper examines the performance of the grid nesting configuration, turbulence closures, and resolution (up to as fine as 100 m horizontal spacing) for simulations of synoptically and locally driven wind ramping events at a West Coast North American wind farm. Interestingly, little improvement is found when using higher resolution simulations or better resolved turbulence closures in comparison to observation data available for this particular site. This is true for week-long simulations as well, where finer resolution runs show only small changes in the distribution of wind speeds or turbulence intensities. It appears that the relatively simple topography of this site is adequately resolved by all model grids (even as coarse as 2.7 km) so that all resolutions are able to model the physics at similar accuracy. The accuracy of the results is shown in this paper to be more dependent on the parameterization of the land-surface characteristics such as soil moisture rather than on grid resolution.

  7. Compiler Comparisons

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Comparisons Compiler Comparisons Using a set of benchmarks described below, different optimization options for the different compilers on Edison are compared. The compilers are also compared against one another on the benchmarks. Benchmarks used Using a set of benchmarks described below, different optimization options for the different compilers on Edison. The compilers are also compared against one another on the benchmarks. NERSC6 Benchmarks We used these benchmarks from the NERSC6

  8. EM Major Procurements | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Major Procurements EM Major Procurements Following is a listing of major procurement actions currently being competed by the Office of Environmental Management. Information contained in the report is based on publicly available information available published on the DOE Acquisition Forecast and other public sources. EM Major Procurements (32.46 KB) More Documents & Publications Department of Energy Environmental Management Workshop Acquisition Forecast Download Los Alamos Legacy Cleanup

  9. OSTI, US Dept of Energy Office of Scientific and Technical Information...

    Office of Scientific and Technical Information (OSTI)

    Wind%20Power%20Map.png Energy in the Forecast Read more about 4273 If you can accurately predict the weather, you may be able to predict how much energy can be generated from wind ...

  10. Building Energy Asset Score | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Commercial Buildings » Analysis Tools » Building Energy Asset Score Building Energy Asset Score Building Energy Asset Score The U.S. Department of Energy's Building Energy Asset Score (Asset Score) is a national standardized tool for assessing the physical and structural energy efficiency of commercial and multifamily residential buildings. The Asset Score generates a simple energy efficiency rating that enables comparison among buildings, and identifies opportunities to invest in energy

  11. STATEMENT OF ADAM SIEMINSKI ADMINISTRATOR U.S. ENERGY INFORMATION...

    Annual Energy Outlook

    EIA is the Nation's primary source of energy information and, by law, its data, analyses, and forecasts are independent of approval by any other officer or employee of the United ...

  12. LNG markets: Implications of a low energy price environment for...

    Annual Energy Outlook

    low energy price environment for demand and U.S. exports LNG: Long-Term Competitiveness in ... is a substitution fuel competing in the ... China: LCOE Forecast (MWh) 9 What does it ...

  13. Short-Term Energy Outlook Supplement: Summer 2013 Outlook for...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Electric bill and price data are not adjusted for ... June 2013 Short-Term Energy Outlook. Forecast -6% -3% 0% 3% 6% 9% ... resulting from fuel costs often occur more ...

  14. Text Transcript of the Tribal Energy and Economic Development...

    Energy.gov [DOE] (indexed site)

    ... look at the next day, put together a load forecast. ... a long term fixed price hedge on your energy and end capacity over that period. What you no longer have are fuel cost ...

  15. Solar Energy Resource Center | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Resource Center Solar Energy Resource Center Solar Mapping Resources Featured Article There's a Map for That National laboratories and private companies have developed a number of tools to forecast the solar potential of homes and businesses. Learn more Icon of a person giving a presentation. Educating Consumers Tools designed to meet individual consumer needs Icon of a trending chart. Market Analysis State- and local-level challenges and solutions for establishing a thriving solar market Icon

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

    SciTech Connect

    Valero, O.J.

    1996-10-03

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

  17. NREL: Energy Analysis - Aaron Bloom

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Bloom Photo of Aaron Bloom Aaron Bloom is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Project Manager/Engineer - Electricity Section Supervisor On staff since 2012 Phone number: 303-384-7032 E-mail: aaron.bloom@nrel.gov Areas of expertise Stakeholder engagement Project management Primary research interests Market design under high penetrations of renewable energy Operational impacts of renewable technologies on the power system Evaluating market

  18. NREL: Energy Analysis - Brady Stoll

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Brady Stoll Photo of Brady Stoll Brady Stoll is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Postdoctoral Researcher On staff since May 2015 Phone number: 303-275-4104 E-mail: brady.stoll@nrel.gov Areas of expertise Renewable energy integration Electricity system modeling Primary research interests Capacity expansion modeling and optimization Demand response modeling within the electricity sector Education and background training Ph.D. in

  19. NREL: Energy Analysis - Elaine Hale

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Elaine Hale Photo of Elaine Hale Elaine Hale is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Senior Engineer On staff since February 2008 Phone number: 303-384-7812 E-mail: elaine.hale@nrel.gov Areas of expertise Mathematical modeling, simulation, and optimization of complex engineering systems Computer programming and software tool development Grid integration analysis, building energy analysis Optimization algorithms for large-scale and

  20. NREL: Energy Analysis - Owen Zinaman

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Owen Zinaman Photo of Owen Zinaman Owen Zinaman is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. International Policy and Regulatory Specialist On staff since March 2012 Phone number: 303-275-4589 E-mail: owen.zinaman@nrel.gov Areas of expertise Executes program of international collaboration with South Africa power sector stakeholders under the 21st Century Power Partnership Coordinates NREL support for the Clean Energy Regulators Initiative Grid

  1. NREL: Energy Analysis - Paul Schwabe

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Schwabe Photo of Paul Schwabe Paul Schwabe is a member of the Market and Policy Impact Analysis Group in the Strategic Energy Analysis Center. Energy and Financial Analyst On staff since August 2008 Phone number: 303-384-7468 E-mail: paul.schwabe@nrel.gov Areas of expertise Electricity market financial analysis Natural gas volume and revenue forecasting Energy efficiency and conservation, including electric and natural gas rate decoupling Primary research interests Market penetration and

  2. NREL: Energy Analysis - Pieter Gagnon

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Pieter Gagnon Photo of Pieter Gagnon Pieter Gagnon is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Engineering Analyst of Solar Policy and Technoeconomics On staff since June 2015 Phone number: 303-275-4910 E-mail: Pieter.Gagnon@nrel.gov Areas of expertise Design and economic analysis of solar photovoltaic systems Energy system modeling in the hydraulic, pneumatic, mechanical, and solar domains Primary research interests Characterizing modern

  3. NREL: Energy Analysis - Venkat Kirshnan

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Venkat Krishnan Photo of Venkat K. Krishnan Venkat Krishnan is a member of the Energy Forecasting and Modeling Group in the Strategic Energy Analysis Center. Energy System Analyst On staff since August 11, 2014 Phone number: 303-275-3237 E-mail: Venkat.Krishnan@nrel.gov Areas of expertise Interdependent infrastructure planning Power system operational planning and stability assessment Statistical simulation and data mining Primary research interests Co-optimization of transmission and supply

  4. A comparison of model short-range forecasts and the ARM Microbase...

    Office of Scientific and Technical Information (OSTI)

    For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the 'Microbase' value added product (referred to as OBS, within ...

  5. A Comparison of Model Short-Range Forecasts and the ARM Microbase...

    Office of Scientific and Technical Information (OSTI)

    ARM Science Metric For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the "Microbase" value added product ...

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

    SciTech Connect

    Pennock, K.

    2012-10-01

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

  7. A Comparison

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Comparison of Monte-Carlo Simulations and Data from MicroBooNE - Public Note - MICROBOONE-NOTE-1014-PUB The MicroBooNE Collaboration July 5, 2016 Abstract This note presents a first comparison of data and Monte-Carlo (MC) simulation at the MicroBooNE experiment, a surface-level liquid argon time projection chamber (LArTPC) located in the Booster Neutrino Beam (BNB) at Fermi National Accelerator Laboratory. Before any analysis can be validated, it is important to ensure understanding of both the

  8. Cloudy Sky RRTM Shortwave Radiative Transfer and Comparison to the Revised ECMWF Shortwave Model

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Cloudy Sky RRTM Shortwave Radiative Transfer and Comparison to the Revised ECMWF Shortwave Model M. J. Iacono, J. S. Delamere, E. J. Mlawer, and S. A. Clough Atmospheric and Environmental Research, Inc. Lexington, Massachusetts J.-J. Morcrette European Centre for Medium-Range Weather Forecasts Reading, United Kingdom Introduction An important step toward improving radiative transfer codes in general circulation models (GCMs) is their thorough evaluation by comparison to measurements directly, or

  9. Audit Report: IG-0499 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    9 Audit Report: IG-0499 April 2, 2001 Department of Energy's Super Energy Savings Performance Contracts As you recently noted in both testimony before the Congress and in public statements, the United States is facing the most serious energy supply situation since the 1970s. And, current forecasts suggest that the demand for energy is increasing. As one of the largest energy consumers in the United States, the Federal Government has established several programs to reduce demand, specifically, by

  10. Toward a science of tumor forecasting for clinical oncology

    DOE PAGES [OSTI]

    Yankeelov, Thomas E.; Quaranta, Vito; Evans, Katherine J.; Rericha, Erin C.

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapiesmore » is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.« less

  11. Toward a science of tumor forecasting for clinical oncology

    SciTech Connect

    Yankeelov, Thomas E.; Quaranta, Vito; Evans, Katherine J.; Rericha, Erin C.

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.

  12. Towards a Science of Tumor Forecast for Clinical Oncology

    DOE PAGES [OSTI]

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

    2015-01-01

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

  13. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect

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

    2015-01-01

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

  14. Short-Term Energy Outlook - U.S. Energy Information Administration (EIA)

    Energy Information Administration (EIA) (indexed site)

    ‹ Analysis & Projections Short-Term Energy Outlook Release Date: November 8, 2016 | Next Release Date: December 6, 2016 | Full Report | Text Only | All Tables | All Figures Glossary › FAQS › Forecasts All Highlights Prices Global Liquid Fuels U.S. Liquid Fuels Natural Gas Coal Electricity Renewables and Carbon Dioxide Emissions Notable Forecast Changes Markets review Crude Oil Petroleum Products Natural Gas Data Figures Tables Custom Table Builder Real Price Viewer Supplements Feature

  15. Short-Term Energy Outlook - U.S. Energy Information Administration (EIA)

    Energy Information Administration (EIA) (indexed site)

    ‹ Analysis & Projections Short-Term Energy Outlook Release Date: November 8, 2016 | Next Release Date: December 6, 2016 | Full Report | Text Only | All Tables | All Figures Glossary › FAQS › Forecasts All Highlights Prices Global Liquid Fuels U.S. Liquid Fuels Natural Gas Coal Electricity Renewables and Carbon Dioxide Emissions Notable Forecast Changes Markets review Crude Oil Petroleum Products Natural Gas Data Figures Tables Custom Table Builder Real Price Viewer Supplements Feature

  16. Short-Term Energy Outlook - U.S. Energy Information Administration (EIA)

    Gasoline and Diesel Fuel Update

    ‹ Analysis & Projections Short-Term Energy Outlook Release Date: November 8, 2016 | Next Release Date: December 6, 2016 | Full Report | Text Only | All Tables | All Figures Glossary › FAQS › Forecasts All Highlights Prices Global Liquid Fuels U.S. Liquid Fuels Natural Gas Coal Electricity Renewables and Carbon Dioxide Emissions Notable Forecast Changes Markets review Crude Oil Petroleum Products Natural Gas Data Figures Tables Custom Table Builder Real Price Viewer Supplements Feature

  17. Short-Term Energy Outlook - U.S. Energy Information Administration (EIA)

    Gasoline and Diesel Fuel Update

    ‹ Analysis & Projections Short-Term Energy Outlook Release Date: November 8, 2016 | Next Release Date: December 6, 2016 | Full Report | Text Only | All Tables | All Figures Glossary › FAQS › Forecasts All Highlights Prices Global Liquid Fuels U.S. Liquid Fuels Natural Gas Coal Electricity Renewables and Carbon Dioxide Emissions Notable Forecast Changes Markets review Crude Oil Petroleum Products Natural Gas Data Figures Tables Custom Table Builder Real Price Viewer Supplements Feature

  18. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 1. Wind and Turbulence

    DOE PAGES [OSTI]

    Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott

    2015-09-25

    We found that numerical-weather-prediction models are often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense horizontally- and vertically-resolved geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City and the simulated fields important to transport and dispersion models were compared to measurements from a number of sodars, tower-based sonic anemometers, and balloon soundings located in the greater metropolitan area. Time histories of computed windmore » speed, wind direction, turbulent kinetic energy (e), friction velocity (u* ), and reciprocal Obukhov length (1 / L) were compared to measurements over the 1-month field campaign. Vertical profiles of wind speed, potential temperature (θ ), and e were compared during short intensive operating periods. The WRF model was typically able to replicate the measured diurnal variation of the wind fields, but with an average absolute wind direction and speed difference of 35° and 1.9 m s-1 , respectively. Then, using the Mellor-Yamada-Janjic (MYJ) surface-layer scheme, the WRF model was found to generally underpredict surface-layer TKE but overpredict u* that was observed above a suburban region of Oklahoma City. The TKE-threshold method used by the WRF model’s MYJ surface-layer scheme to compute the boundary-layer height (h) consistently overestimated h derived from a θ gradient method whether using observed or modelled θ profiles.« less

  19. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 1. Wind and Turbulence

    SciTech Connect

    Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott

    2015-09-25

    We found that numerical-weather-prediction models are often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense horizontally- and vertically-resolved geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City and the simulated fields important to transport and dispersion models were compared to measurements from a number of sodars, tower-based sonic anemometers, and balloon soundings located in the greater metropolitan area. Time histories of computed wind speed, wind direction, turbulent kinetic energy (e), friction velocity (u* ), and reciprocal Obukhov length (1 / L) were compared to measurements over the 1-month field campaign. Vertical profiles of wind speed, potential temperature (? ), and e were compared during short intensive operating periods. The WRF model was typically able to replicate the measured diurnal variation of the wind fields, but with an average absolute wind direction and speed difference of 35 and 1.9 m s-1 , respectively. Then, using the Mellor-Yamada-Janjic (MYJ) surface-layer scheme, the WRF model was found to generally underpredict surface-layer TKE but overpredict u* that was observed above a suburban region of Oklahoma City. The TKE-threshold method used by the WRF models MYJ surface-layer scheme to compute the boundary-layer height (h) consistently overestimated h derived from a ? gradient method whether using observed or modelled ? profiles.

  20. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 1. Wind and Turbulence

    SciTech Connect

    Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott

    2015-09-25

    We found that numerical-weather-prediction models are often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense horizontally- and vertically-resolved geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City and the simulated fields important to transport and dispersion models were compared to measurements from a number of sodars, tower-based sonic anemometers, and balloon soundings located in the greater metropolitan area. Time histories of computed wind speed, wind direction, turbulent kinetic energy (e), friction velocity (u* ), and reciprocal Obukhov length (1 / L) were compared to measurements over the 1-month field campaign. Vertical profiles of wind speed, potential temperature (θ ), and e were compared during short intensive operating periods. The WRF model was typically able to replicate the measured diurnal variation of the wind fields, but with an average absolute wind direction and speed difference of 35° and 1.9 m s-1 , respectively. Then, using the Mellor-Yamada-Janjic (MYJ) surface-layer scheme, the WRF model was found to generally underpredict surface-layer TKE but overpredict u* that was observed above a suburban region of Oklahoma City. The TKE-threshold method used by the WRF model’s MYJ surface-layer scheme to compute the boundary-layer height (h) consistently overestimated h derived from a θ gradient method whether using observed or modelled θ profiles.

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

    SciTech Connect

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

    1994-05-01

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

  2. Apples with apples: accounting for fuel price risk in comparisons of gas-fired and renewable generation

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan

    2003-12-18

    For better or worse, natural gas has become the fuel of choice for new power plants being built across the United States. According to the US Energy Information Administration (EIA), natural gas combined-cycle and combustion turbine power plants accounted for 96% of the total generating capacity added in the US between 1999 and 2002--138 GW out of a total of 144 GW. Looking ahead, the EIA expects that gas-fired technology will account for 61% of the 355 GW new generating capacity projected to come on-line in the US up to 2025, increasing the nationwide market share of gas-fired generation from 18% in 2002 to 22% in 2025. While the data are specific to the US, natural gas-fired generation is making similar advances in other countries as well. Regardless of the explanation for (or interpretation of) the empirical findings, however, the basic implications remain the same: one should not blindly rely on gas price forecasts when comparing fixed-price renewable with variable-price gas-fired generation contracts. If there is a cost to hedging, gas price forecasts do not capture and account for it. Alternatively, if the forecasts are at risk of being biased or out of tune with the market, then one certainly would not want to use them as the basis for resource comparisons or investment decisions if a more certain source of data (forwards) existed. Accordingly, assuming that long-term price stability is valued, the most appropriate way to compare the levelized cost of these resources in both cases would be to use forward natural gas price data--i.e. prices that can be locked in to create price certainty--as opposed to uncertain natural gas price forecasts. This article suggests that had utilities and analysts in the US done so over the sample period from November 2000 to November 2003, they would have found gas-fired generation to be at least 0.3-0.6 cents/kWh more expensive (on a levelized cost basis) than otherwise thought. With some renewable resources, in particular wind

  3. Comparison of Test Procedures and Energy Efficiency Criteria in Selected International Standards & Labeling Programs for Copy Machines, External Power Supplies, LED Displays, Residential Gas Cooktops and Televisions

    SciTech Connect

    Zheng, Nina; Zhou, Nan; Fridley, David

    2012-03-01

    This report presents a technical review of international minimum energy performance standards (MEPS), voluntary and mandatory energy efficiency labels and test procedures for five products being considered for new or revised MEPS in China: copy machines, external power supply, LED displays, residential gas cooktops and flat-screen televisions. For each product, an overview of the scope of existing international standards and labeling programs, energy values and energy performance metrics and description and detailed summary table of criteria and procedures in major test standards are presented.

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

    SciTech Connect

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

    2012-08-15

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

  5. Direct Drive Wave Energy Buoy

    SciTech Connect

    Rhinefrank, Ken

    2011-11-02

    Presentation from the 2011 Water Peer Review in which principal investigator discusses project progress and results for this project which will be used to inform the utility-scale design process, improve cost estimates, accurately forecast energy production and to observe system operation and survivability.

  6. Energy Forecast, ForskEL (Smart Grid Project) | Open Energy Informatio...

    OpenEI (Open Energy Information) [EERE & EIA]

    meeting both the clients' demand for cost stability and at the same time encourages a demand response. 2. Lack of information and awareness about the possibilities and...

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

    SciTech Connect

    Not Available

    1994-08-02

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

  8. Statement from Secretary of Energy Samuel W. Bodman Regarding EIA's Updated

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Annual Energy Outlook | Department of Energy Regarding EIA's Updated Annual Energy Outlook Statement from Secretary of Energy Samuel W. Bodman Regarding EIA's Updated Annual Energy Outlook December 12, 2007 - 4:44pm Addthis WASHINGTON, DC - Earlier today the Department of Energy's Energy Information Administration released their Annual Energy Outlook 2008. Energy Secretary Samuel Bodman made the following statement regarding the EIA's Annual Energy Outlook which forecasts to 2030:

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

    SciTech Connect

    BARCOT, R.A.

    2005-08-17

    This report provides up-to-date life cycle information about the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: (1) an overview of Hanford-wide solid waste to be managed by the WM Project; (2) multi-level and waste class-specific estimates; (3) background information on waste sources; and (4) comparisons to previous forecasts and other national data sources. The focus of this report is low-level waste (LLW), mixed low-level waste (MLLW), and transuranic waste, both non-mixed and mixed (TRU(M)). Some details on hazardous waste are also provided, however, this information is not considered comprehensive. This report includes data requested in December, 2004 with updates through March 31,2005. The data represent a life cycle forecast covering all reported activities from FY2005 through the end of each program's life cycle and are an update of the previous FY2004.1 data version.

  10. Coal supply/demand, 1980 to 2000. Task 3. Resource applications industrialization system data base. Final review draft. [USA; forecasting 1980 to 2000; sector and regional analysis

    SciTech Connect

    Fournier, W.M.; Hasson, V.

    1980-10-10

    This report is a compilation of data and forecasts resulting from an analysis of the coal market and the factors influencing supply and demand. The analyses performed for the forecasts were made on an end-use-sector basis. The sectors analyzed are electric utility, industry demand for steam coal, industry demand for metallurgical coal, residential/commercial, coal demand for synfuel production, and exports. The purpose is to provide coal production and consumption forecasts that can be used to perform detailed, railroad company-specific coal transportation analyses. To make the data applicable for the subsequent transportation analyses, the forecasts have been made for each end-use sector on a regional basis. The supply regions are: Appalachia, East Interior, West Interior and Gulf, Northern Great Plains, and Mountain. The demand regions are the same as the nine Census Bureau regions. Coal production and consumption in the United States are projected to increase dramatically in the next 20 years due to increasing requirements for energy and the unavailability of other sources of energy to supply a substantial portion of this increase. Coal comprises 85 percent of the US recoverable fossil energy reserves and could be mined to supply the increasing energy demands of the US. The NTPSC study found that the additional traffic demands by 1985 may be met by the railways by the way of improved signalization, shorter block sections, centralized traffic control, and other modernization methods without providing for heavy line capacity works. But by 2000 the incremental traffic on some of the major corridors was projected to increase very significantly and is likely to call for special line capacity works involving heavy investment.

  11. Global Insight Energy Group

    Gasoline and Diesel Fuel Update

    Outlook Mary Novak Managing Director IHS Global Insight Copyright © 2010 IHS Global Insight, Inc. Overview: Energy Sector Transformation Underway * The recession has hit energy demand hard, and aggregate energy demand is not expected to return to 2007 levels until 2018. * Oil and natural gas prices will both rise over the long-term, but the price trends will diverge with natural gas prices rising slowly due to the development of shale gas. * This forecast does not include a GHG cap-and-trade

  12. Energy Analysis Program 1990 annual report

    SciTech Connect

    Not Available

    1992-01-01

    The Energy Analysis Program has played an active role in the analysis and discussion of energy and environmental issues at several levels. (1) at the international level, with programs as developing scenarios for long-term energy demand in developing countries and organizing leading an analytic effort, ``Energy Efficiency, Developing Countries, and Eastern Europe,`` part of a major effort to increase support for energy efficiency programs worldwide; (2) at national level, the Program has been responsible for assessing energy forecasts and policies affecting energy use (e.g., appliance standards, National Energy Strategy scenarios); and (3) at the state and utility levels, the Program has been a leader in promoting integrated resource utility planning; the collaborative process has led to agreement on a new generation of utility demand-site programs in California, providing an opportunity to use knowledge and analytic techniques of the Program`s researchers. We continue to place highest on analyzing energy efficiency, with particular attention given to energy use in buildings. The Program continues its active analysis of international energy issues in Asia (including China), the Soviet Union, South America, and Western Europe. Analyzing the costs and benefits of different levels of standards for residential appliances continues to be the largest single area of research within the Program. The group has developed and applied techniques for forecasting energy demand (or constructing scenarios) for the United States. We have built a new model of industrial energy demand, are in the process of making major changes in our tools for forecasting residential energy demand, have built an extensive and documented energy conservation supply curve of residential energy use, and are beginning an analysis of energy-demand forecasting for commercial buildings.

  13. Energy Analysis Program 1990 annual report

    SciTech Connect

    Not Available

    1992-01-01

    The Energy Analysis Program has played an active role in the analysis and discussion of energy and environmental issues at several levels. (1) at the international level, with programs as developing scenarios for long-term energy demand in developing countries and organizing leading an analytic effort, Energy Efficiency, Developing Countries, and Eastern Europe,'' part of a major effort to increase support for energy efficiency programs worldwide; (2) at national level, the Program has been responsible for assessing energy forecasts and policies affecting energy use (e.g., appliance standards, National Energy Strategy scenarios); and (3) at the state and utility levels, the Program has been a leader in promoting integrated resource utility planning; the collaborative process has led to agreement on a new generation of utility demand-site programs in California, providing an opportunity to use knowledge and analytic techniques of the Program's researchers. We continue to place highest on analyzing energy efficiency, with particular attention given to energy use in buildings. The Program continues its active analysis of international energy issues in Asia (including China), the Soviet Union, South America, and Western Europe. Analyzing the costs and benefits of different levels of standards for residential appliances continues to be the largest single area of research within the Program. The group has developed and applied techniques for forecasting energy demand (or constructing scenarios) for the United States. We have built a new model of industrial energy demand, are in the process of making major changes in our tools for forecasting residential energy demand, have built an extensive and documented energy conservation supply curve of residential energy use, and are beginning an analysis of energy-demand forecasting for commercial buildings.

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

    SciTech Connect

    Rogers, J.; Porter, K.

    2011-03-01

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

  15. Full Fuel-Cycle Comparison of Forklift Propulsion Systems

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    3 Full Fuel-Cycle Comparison of Forklift Propulsion Systems Energy Systems Division About ... UChicago Argonne, LLC. ANLESD08-3 Full Fuel-Cycle Comparison of Forklift Propulsion ...

  16. Material World: Forecasting Household Appliance Ownership in a Growing Global Economy

    SciTech Connect

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

    Over the past years the Lawrence Berkeley National Laboratory (LBNL) has developed an econometric model that predicts appliance ownership at the household level based on macroeconomic variables such as household income (corrected for purchase power parity), electrification, urbanization and climate variables. Hundreds of data points from around the world were collected in order to understand trends in acquisition of new appliances by households, especially in developing countries. The appliances covered by this model are refrigerators, lighting fixtures, air conditioners, washing machines and televisions. The approach followed allows the modeler to construct a bottom-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residential sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time. This serves two important functions with regard to evaluation of the impact of energy efficiency policies. First, it provides insight into which end uses will be responsible for the largest share of demand growth, and therefore should be policy priorities. Second, it provides a characterization of the rate at which policies affecting new equipment penetrate the appliance stock. Over the past 3 years, this method has been used to support the development of energy demand forecasts at the country, region or global level.

  17. Supplement to the annual energy outlook 1994

    SciTech Connect

    1994-03-01

    This report is a companion document to the Annual Energy Outlook 1994 (AEO94), (DOE/EIA-0383(94)), released in Jan. 1994. Part I of the Supplement presents the key quantitative assumptions underlying the AEO94 projections, responding to requests by energy analysts for additional information on the forecasts. In Part II, the Supplement provides regional projections and other underlying details of the reference case projections in the AEO94. The AEO94 presents national forecasts of energy production, demand and prices through 2010 for five scenarios, including a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices. These forecasts are used by Federal, State, and local governments, trade associations, and other planners and decisionmakers in the public and private sectors.

  18. Comparison of Test Procedures and Energy Efficiency Criteria in Selected International Standards and Labeling Programs for Clothes Washers, Water Dispensers, Vending Machines and CFLs

    SciTech Connect

    Fridley, David; Zheng, Nina; Zhou, Nan

    2010-06-01

    Since the late 1970s, energy labeling programs and mandatory energy performance standards have been used in many different countries to improve the efficiency levels of major residential and commercial equipment. As more countries and regions launch programs covering a greater range of products that are traded worldwide, greater attention has been given to harmonizing the specific efficiency criteria in these programs and the test methods for measurements. For example, an international compact fluorescent light (CFL) harmonization initiative was launched in 2006 to focus on collaboration between Australia, China, Europe and North America. Given the long history of standards and labeling programs, most major energy-consuming residential appliances and commercial equipment are already covered under minimum energy performance standards (MEPS) and/or energy labels. For these products, such as clothes washers and CFLs, harmonization may still be possible when national MEPS or labeling thresholds are revised. Greater opportunity for harmonization exists in newer energy-consuming products that are not commonly regulated but are under consideration for new standards and labeling programs. This may include commercial products such as water dispensers and vending machines, which are only covered by MEPS or energy labels in a few countries or regions. As China continues to expand its appliance standards and labeling programs and revise existing standards and labels, it is important to learn from recent international experiences with efficiency criteria and test procedures for the same products. Specifically, various types of standards and labeling programs already exist in North America, Europe and throughout Asia for products in China's 2010 standards and labeling programs, namely clothes washers, water dispensers, vending machines and CFLs. This report thus examines similarities and critical differences in energy efficiency values, test procedure specifications and other

  19. Monthly energy review, April 1994

    SciTech Connect

    Not Available

    1994-04-01

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

  20. ARM - PI Product - CCPP-ARM Parameterization Testbed Model Forecast Data

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    ProductsCCPP-ARM Parameterization Testbed Model Forecast Data ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : CCPP-ARM Parameterization Testbed Model Forecast Data Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are