National Library of Energy BETA

Sample records for forecast comparisons table

  1. 1997 MWD comparison tables

    SciTech Connect (OSTI)

    Wiseman, K.

    1997-05-01

    This year`s MWD Comparison Tables include a Quick Reference Guide listing MWD sensors by collar size for each manufacturer. Following the Quick Reference Guide are the comparison tables, which list general, directional, gamma ray, resistivity, density and neutron data for each tool. The MWD Tables should only be used as a reference source. System specifications frequently change as tools are refined and developed. Consult MWD marketing representatives prior to making final tool selections. A contact key for all the companies listed in the tables appears on the last page.

  2. 1996 MWD comparison tables

    SciTech Connect (OSTI)

    Gastineau, J.

    1996-05-01

    Petroleum Engineer International`s ninth annual Measurement While Drilling Tables compare the different operating capabilities of survey and logging tools from 13 MWD vendors. This year`s MWD Comparison Tables include a Quick Reference Guide listing MWD sensors by collar size for each manufacturer. Following the Quick Reference Guide are the comparison tables, listing general, directional, gamma ray, resistivity, density and neutron data for each tool. The MWD Tables should serve only as a reference source. System specifications can change rapidly as tools are refined and developed. Consultation with MWD marketing representatives before making a final tool selection is recommended. A contact key for all of the companies listed in the tables is provided.

  3. 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 ...

  4. 1998 MWD/LWD comparison tables

    SciTech Connect (OSTI)

    1998-05-01

    This year`s comparison tables feature an updated Quick Reference Guide listing MWD sensors by collar size for each manufacturer. Following the Quick Reference Guide are the comparison tables, which list general, directional, gamma ray, resistivity, density and neutron data for each tool. The MWD Tables should only be used as a reference source. System specifications frequently change as tools are refined and developed. Please consult representatives for each company prior to making final tool selections. A contact key for all the companies is included.

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

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

    SciTech Connect (OSTI)

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

    2012-07-01

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

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

    Broader source: Energy.gov [DOE]

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

    On December 12, 2005, the reference case projections from ''Annual Energy Outlook 2006'' (AEO 2006) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past five AEO releases (AEO 2001-AEO

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

    On December 5, 2006, the reference case projections from 'Annual Energy Outlook 2007' (AEO 2007) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past six years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past six years at least, levelized cost comparisons of fixed-price renewable generation with variable-price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are 'biased' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2007. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past six AEO releases (AEO 2001-AEO 2006), we

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

    SciTech Connect (OSTI)

    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.

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

    SciTech Connect (OSTI)

    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.

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

    SciTech Connect (OSTI)

    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.

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

    SciTech Connect (OSTI)

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

    2008-01-07

    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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

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

    SciTech Connect (OSTI)

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

    2005-02-09

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04

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

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

    SciTech Connect (OSTI)

    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.

  1. Comparison of BALON2 with cladding ballooning strain tables in NUREG-0630. [PWR; BWR

    SciTech Connect (OSTI)

    Resch, S.C.; Laats, E.T.

    1982-01-01

    For this comparison study, the two computer models used for calculating fuel rod cladding failure and the resulting permanent strains were compared against experiment data. The two models considered were the mechanistic BALON2 model and the empirical model described in the NUREG-0630 report. The purpose for making this comparison was simply to gain insight into the relative strengths and weaknesses of each model. The experiment data sample consisted of data from both single and bundle tests conducted sometimes in in-pile facilities, but mostly in out-of-pile facilities. Comparisons between models indicated that the empirical NUREG-0630 model more accurately calculated the local cladding temperature and pressure conditions at rupture, but the mechanistic BALON2 model more accurately calculated the resulting cladding permanent strain at the rupture location.

  2. Solar Forecasting

    Broader source: Energy.gov [DOE]

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

  3. Table 4

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

    112 70 83 98 99 117 150 5.89 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  4. Table 4

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

    125 43 101 95 99 130 149 8.25 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  5. Table 4

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

    125 69 112 131 137 158 7.36 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

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

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01

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

  7. Table 4

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

    10.8 0.3 0.8 1.6 2.0 2.2 4.0 11.94 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  8. Table 4

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

    10.8 0.9 2.9 1.9 2.8 2.3 9.84 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  9. Table 4

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

    0.6 0.8 0.6 1.4 2.3 1.9 2.5 12.69 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  10. Forecast Change

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

    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 (cents/kWh) 12.06 12.09 12.58 13.04 12.95 12.84 -0.9% Expenditures $415 $405 $393 $396 $408 $424 3.9% New England Usage (kWh) 2,122 2,188 2,173 1,930 1,992 2,082 4.5% Price (cents/kWh) 15.85 15.50 16.04 17.63 18.64 18.37 -1.5% Expenditures $336 $339 $348 $340 $371 $382 3.0% Mid-Atlantic Usage (kWh) 2,531 2,548 2,447 2,234 2,371 2,497 5.3% Price (cents/kWh) 16.39 15.63

  11. A = 5 General Tables

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

    5 General Tables The General Table for 5H is subdivided into the following categories: Cluster Model Hypernuclei Model Calculations Photodisintegration Pions The General Table for...

  12. Table 7

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

    1 Table 7 Created on: 8/29/2016 8:24:42 AM Table 7. Marketed production of natural gas in selected states and the Federal Gulf of Mexico, 2011-2016 (million cubic feet) Year and Month Alaska Arkansas California Colorado Kansas Louisiana Montana New Mexico North Dakota Ohio 2011 Total 356,225 1,072,212 250,177 1,637,576 309,124 3,029,206 74,624 1,237,303 97,102 78,858 2012 Total 351,259 1,146,168 246,822 1,709,376 296,299 2,955,437 66,954 1,215,773 172,242 84,482 2013 Total 338,182 1,139,654

  13. A=19 Tables

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

    Tables for A = 19 Available in the following years: (1995), (1987), (1983), (1978), (1972), (1959) Adobe Reader Download Tables from (1995TI07): Introductory Table 3 in PS or PDF. Table 19.1 in PS or PDF. Table 19.2 in PS or PDF. Table 19.3 in PS or PDF. Table 19.4 in PS or PDF. Table 19.5 in PS or PDF. Table 19.6 in PS or PDF. Table 19.7 in PS or PDF. Table 19.8 in PS or PDF. Table 19.9 in PS or PDF. Table 19.10 in PS or PDF. Table 19.11 in PS or PDF. Table 19.12 in PS or PDF. Table 19.13 in PS

  14. A=20 Tables

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

    Tables for A = 20 Available in the following years: (1998), (1987), (1983), (1978), (1972), (1959) Adobe Reader Download Tables from (1998TI06): Introductory Table 3 in PS or PDF. Table 20.1 in PS or PDF. Table 20.2 in PS or PDF. Table 20.3 in PS or PDF. Table 20.4 in PS or PDF. Table 20.5 in PS or PDF. Table 20.6 in PS or PDF. Table 20.7 in PS or PDF. Table 20.8 in PS or PDF. Table 20.9 in PS or PDF. Table 20.10 in PS or PDF. Table 20.11 in PS or PDF. Table 20.12 in PS or PDF. Table 20.13 in PS

  15. 1999 CBECS Detailed Tables

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

    Commercial Buildings Energy Consumption Survey (CBECS) > Detailed Tables 1999 CBECS Detailed Tables Building Characteristics | Consumption & Expenditures Data from the 1999...

  16. 6Be General Tables

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

    6Be General Table The General Table for 6Be is subdivided into the following categories: Cluster Model Model Calculations...

  17. 8C General Tables

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

    C General Tables The General Table for 8C is subdivided into the following categories: Reviews Other Theoretical Work...

  18. A=18 Tables

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

    (1959) Adobe Reader Download Tables from (1995TI07): Introductory Table 3 in PS or PDF. Table 18.1 in PS or PDF. Table 18.2 in PS or PDF. Table 18.3 in PS or PDF. Table 18.4...

  19. 5He General Tables

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

    He General Table The General Table for 5He is subdivided into the following categories: Ground State Properties Theoretical Special States Model Discussions Shell Model Cluster...

  20. 6He General Tables

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

    He General Table The General Table for 6He is subdivided into the following categories: Ground State Properties Theoretical Special States Shell Model Cluster and alpha-particle...

  1. 7He General Tables

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

    He General Table The General Table for 7He is subdivided into the following categories: Experimental Theoretical Model Calculations Hypernuclei and Mesons Pions

  2. 9He General Tables

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

    He General Table The General Table for 9He is subdivided into the following categories: Shell Model Other Model Calculations Theoretical

  3. FY 2005 Statistical Table

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

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) Table of Contents Summary...................................................................................................... 1 Mandatory Funding....................................................................................... 3 Energy Supply.............................................................................................. 4 Non-Defense site acceleration

  4. A = 10 General Tables

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

    Table for 10He is subdivided into the following categories: Theoretical Shell Model Cluster Model Other Models Special States Electromagnetic Transitions The General Table for...

  5. 5H General Tables

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

    H General Table The General Table for 5H is subdivided into the following categories: Cluster Model Hypernuclei Model Calculations Photodisintegration Pions...

  6. 10He General Tables

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

    General Table The General Table for 10He is subdivided into the following categories: Theoretical Shell Model Cluster Model Other Models Special States Electromagnetic Transitions...

  7. 7Be General Tables

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

    Be General Table The General Table for 7Be is subdivided into the following categories: Reviews Experimental Work Shell Model Cluster Model Other Theoretical Work Model...

  8. 1995 Detailed Tables

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

    Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey > Detailed Tables 1995 Detailed Tables Data from the 1995 Commercial Buildings Energy Consumption...

  9. probabilistic energy production forecasts

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

  10. Wind Power Forecasting Data

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

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

  11. Forecasting Water Quality & Biodiversity

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

    Forecasting Water Quality & Biodiversity March 25, 2015 Cross-cutting Sustainability ... that measure feedstock production, water quality, water quantity, and biodiversity. ...

  12. Wind Power Forecasting

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

  13. NREL: Transmission Grid Integration - Forecasting

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

  14. 2016 Solar Forecasting Workshop

    Office of Energy Efficiency and Renewable Energy (EERE)

    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 integration cost of high levels of solar energy into the electricity grid. This will help SunShot to assess current technology and practices in this field and identify the gaps and needs for further research.

  15. CBECS Buildings Characteristics --Revised Tables

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

    Energy Sources and End Use Tables (27 pages, 152 kb) CONTENTS PAGES Table 18. Energy Sources, Number of Buildings, 1995 Table 19. Energy Sources, Floorspace, 1995 Table 20. Energy End Uses, Number of Buildings and Floorspace, 1995 Table 21. Space-Heating Energy Sources, Number of Buildings, 1995 Table 22. Space-Heating Energy Sources, Floorspace, 1995 Table 23. Primary Space-Heating Energy Sources, Number of Buildings, 1995 Table 24. Primary Space-Heating Energy Sources, Floorspace, 1995 Table

  16. CBECS Buildings Characteristics --Revised Tables

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

    End-Use Equipment Tables (27 pages, 151 kb) CONTENTS PAGES Table 33. Heating Equipment, Number of Buildings, 1995 Table 34. Heating Equipment, Floorspace, 1995 Table 35. Cooling Equipment,Number of Buildings, 1995 Table 36. Cooling Equipment, Floorspace, 1995 Table 37. Refrigeration Equipment, Number of Buildings and Floorspace, 1995 Table 38. Water-Heating Equipment, Number of Buildings and Floorspace, 1995 Table 39. Lighting Equipment, Number of Buildings, 1995 Table 40. Lighting Equipment,

  17. Today's Forecast: Improved Wind Predictions

    Broader source: Energy.gov [DOE]

    Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable.

  18. 6Li General Tables

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

    Li General Table The General Table for 6Li is subdivided into the following categories: Ground State Properties of 6Li Special States Theoretical Shell Model Cluster Models Complex...

  19. 8Be General Tables

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

    Be General Tables The General Table for 8Be is subdivided into the following categories: Reviews Ground State Properties Shell Model Cluster Model Other Models Photodisintegration Fission and Fusion Astrophysical b-decay Hypernuclei

  20. 8He General Tables

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

    He General Tables The General Table for 8He is subdivided into the following categories: Reviews Ground-state Properties Shell Model Cluster Model Other Theoretical Work Elastic and Inelastic Scattering b-decay

  1. 9B General Tables

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

    B General Table The General Table for 9B is subdivided into the following categories: Shell Model Cluster Model Theoretical Other Model Calculations Complex Reactions Beta-Decay Pions Light-ion and Neutron Induced Reactions Hypernuclei

  2. 9C General Tables

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

    C General Table The General Table for 9C is subdivided into the following categories: Shell Model Cluster Model Other Models Theoretical Beta-Decay Light-ion and Neutron Induced Reactions Astrophysical

  3. Tabled Execution in Scheme

    SciTech Connect (OSTI)

    Willcock, J J; Lumsdaine, A; Quinlan, D J

    2008-08-19

    Tabled execution is a generalization of memorization developed by the logic programming community. It not only saves results from tabled predicates, but also stores the set of currently active calls to them; tabled execution can thus provide meaningful semantics for programs that seemingly contain infinite recursions with the same arguments. In logic programming, tabled execution is used for many purposes, both for improving the efficiency of programs, and making tasks simpler and more direct to express than with normal logic programs. However, tabled execution is only infrequently applied in mainstream functional languages such as Scheme. We demonstrate an elegant implementation of tabled execution in Scheme, using a mix of continuation-passing style and mutable data. We also show the use of tabled execution in Scheme for a problem in formal language and automata theory, demonstrating that tabled execution can be a valuable tool for Scheme users.

  4. Solar Forecast Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  5. FY 2005 Laboratory Table

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

    Congressional Budget Request Laboratory Tables Preliminary Department of Energy FY 2005 Congressional Budget Request Office of Management, Budget and Evaluation/CFO February 2004 Laboratory Tables Preliminary Department of Energy Department of Energy FY 2005 Congressional Budget FY 2005 Congressional Budget Request Request Office of Management, Budget and Evaluation/CFO February 2004 Laboratory Tables Laboratory Tables Printed with soy ink on recycled paper Preliminary Preliminary The numbers

  6. FY 2005 State Table

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

    Office of Management, Budget and Evaluation/CFO February 2004 State Tables State Tables Preliminary Preliminary Department of Energy Department of Energy FY 2005 Congressional Budget FY 2005 Congressional Budget Request Request Office of Management, Budget and Evaluation/CFO February 2004 State Tables State Tables Printed with soy ink on recycled paper Preliminary Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The

  7. 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

  8. Hot cell examination table

    DOE Patents [OSTI]

    Gaal, Peter S.; Ebejer, Lino P.; Kareis, James H.; Schlegel, Gary L.

    1991-01-01

    A table for use in a hot cell or similar controlled environment for use in examining specimens. The table has a movable table top that can be moved relative to a table frame. A shaft is fixedly mounted to the frame for axial rotation. A shaft traveler having a plurality of tilted rollers biased against the shaft is connected to the table top such that rotation of the shaft causes the shaft traveler to roll along the shaft. An electromagnetic drive is connected to the shaft and the frame for controllably rotating the shaft.

  9. 1997 Housing Characteristics Tables Housing Unit Tables

    Gasoline and Diesel Fuel Update (EIA)

    Contact: Robert Latta, Survey Manager (rlatta@eia.doe.gov) World Wide Web: http:www.eia.doe.govemeuconsumption Table HC1-1a. Housing Unit Characteristics by Climate Zone, ...

  10. 10Li General Tables

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

    Li General Table The General Table for 10Li is subdivided into the following categories: Reviews Theoretical Ground State Properties Shell Model Cluster Model Other Models Special States Astrophysical Electromagnetic Transitions Hypernuclei Photodisintegration Light-Ion and Neutron Induced Reactions These General Tables correspond to the 2003 preliminary evaluation of ``Energy Levels of Light Nuclei, A = 10''. The prepublication version of A = 10 is available on this website in PDF format: A =

  11. Table of Contents

    Energy Savers [EERE]

    Table 10 Costs of Foreign Travel, IG-0397 Table 10 Costs of Foreign Travel, IG-0397 Table 10 Costs of Foreign Travel, IG-0397 Table 10 Costs of Foreign Travel, IG-0397 (242.36 KB) More Documents & Publications Inspection Report: IG-0397 Audit of Department of Energy International Charter Flights, IG-0397 John C. Layton: Before The Subcommittee on Oversight and Investigations Committee on Commerce

    U U . . S S . . D D E E P P A A R R T T M M E E N N T T O O F F E E N N E E R R G G Y Y O O F

  12. Description of Detailed Tables

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

    for the 1999 Commercial Buildings Energy Consumption Survey (CBECS) consists of building characteristics tables B1 through B39, which contain the number of buildings and...

  13. A = 9 General Tables

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

    The General Table for 9Li is subdivided into the following categories: Shell Model Cluster Model Theoretical Ground State Properties Special States Other Model Calculations...

  14. 5Li General Tables

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

    Table for 5Li is subdivided into the folowing categories: Ground State Properties Cluster Model Shell Model Special States Model Calculations Model Discussions Complex...

  15. 10N General Tables

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

    subdivided into the following categories: Reviews Ground-State Properties Shell Model Cluster Model Other Theoretical Work These General Tables correspond to "Energy Levels of...

  16. Comparison

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

  17. 7Li General Tables

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

    Li General Table The General Table for 7Li is subdivided into the following categories: Reviews Ground State Properties Shell Model Cluster Model Other Theoretical Work Model Calculations Photodisintegration Polarization Fission and Fusion Elastic and Inelastic Scattering Projectile Fragmentation and Multifragmentation Astrophysical Hyperfine Structure b-decay Muons Hypernuclei and Mesons Hypernuclei and Baryons Pion, Kaon and Eta-Mesons Other Work Applications

  18. 8B General Tables

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

    B General Tables The General Table for 8B is subdivided into the following categories: Reviews Ground State Properties Shell Model Cluster Model Other Models Photodisintegration and Coulomb Dissociation Elastic and Inelastic Scattering Fragmentation Reactions Astrophysical b Decay Nucleon Spatial Distribution

  19. 8Li General Tables

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

    Li General Tables The General Table for 8Li is subdivided into the following categories: Reviews Ground State Properties Shell Model Cluster Model Other Models Photodissociation Fusion and Fission Elastic and Inelastic Scattering Fragmentation Reactions Astrophysical b Decay Hypernuclei Pions, Kaons and h-mesons

  20. 9Li General Tables

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

    Li General Table The General Table for 9Li is subdivided into the following categories: Shell Model Cluster Model Theoretical Ground State Properties Special States Other Model Calculations Complex Reactions Beta-Decay Pions Muons Photodisintegration Elastic and Inelastic Scattering Electromagnetic Transitions Astrophysical

  1. 1995 CECS C&E Tables

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

    Fuel Oil Tables (10 pages, 58 kb) CONTENTS PAGES Table 26. Total Fuel Oil Consumption and Expenditures, 1995 Table 27. Fuel Oil Consumption and Expenditure Intensities, 1995 Table...

  2. Microsoft Word - 2012 RCRA CRP comment table.docx

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

    Notice - June 2011 Independent Statistics & Analysis U.S. Energy Information Administration June 2011 Short-Term Energy Outlook Notice: Suspension of Regional Residential Heating Oil and Propane Price Forecasts Because of fiscal year 2011 budget reductions, the U.S. Energy Information Administration (EIA) has suspended surveys that were the source of historical price data published in Tables 12-15 and 34-38 of the Petroleum Marketing Monthly (PMM) that supported the residential retail

  3. All Consumption Tables.vp

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

    4) June 2007 State Energy Consumption Estimates 1960 Through 2004 2004 Consumption Summary Tables Table S1. Energy Consumption Estimates by Source and End-Use Sector, 2004...

  4. table11.xls

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

    ... 14.1 NA 17.9 18.3 19.6 20.1 Table 11. Fuel Economy, Selected Survey Years (Miles Per Gallon) Survey Years Page A-1 of A-5 1983 1985 1988...

  5. table3.2

    Gasoline and Diesel Fuel Update (EIA)

    ... NAICS Code(a) Subsector and Industry Total Net Electricity(b... RSE Row Factors Table 3.2 Fuel Consumption, 2002; Level: ... of Energy Markets and End Use, Energy Consumption ...

  6. Building Materials Property Table

    SciTech Connect (OSTI)

    2010-04-16

    This information sheet describes a table of some of the key technical properties of many of the most common building materials taken from ASHRAE Fundamentals - 2001, Moisture Control in Buildings, CMHC, NRC/IRC, IEA Annex 24, and manufacturer data.

  7. TABLE OF CONTENTS

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

    008 High Temperature Superconductivity for Electric Systems Peer Review Final Report i TABLE OF CONTENTS High Temperature Superconductivity for Electric Systems Program Overview ...... 1 The Peer Review................................................................................................................ 3 Review Criteria ................................................................................................................. 5 Guidelines

  8. Table_of_Contents

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

    Table of Contents 1. Physical Security .............................................................................................................................. 1-1 101. Headquarters Security Badges ........................................................................................ 101-1 102. HSPD-12 Badges and the PIV Process ........................................................................... 102-1 103. Prohibited Articles

  9. Table G3

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

    May 28, 2010 Voluntary Reporting of Greenhouse Gases 14 Table G3. Decision Chart for a ... Form EIA-1605 Voluntary Reporting of Greenhouse Gases Form Approved OMB No. 1905-0194 ...

  10. TABLE OF CONTENTS

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

    3, Revision 0 i TABLE OF CONTENTS 1.0 Summary .............................................................................................................................. 1 2.0 Introduction .......................................................................................................................... 1 3.0 Discussion ............................................................................................................................ 4 3.1 Selection of Tanks for Level Decrease

  11. TABLE OF CONTENTS

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

    4, Revision 0 i TABLE OF CONTENTS 1.0 Summary .............................................................................................................................. 1 2.0 Introduction .......................................................................................................................... 1 3.0 Discussion ............................................................................................................................ 4 3.1 Selection of Tanks for Level Decrease

  12. TABLE OF CONTENTS

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

    5, Revision 0 i TABLE OF CONTENTS 1.0 Summary .............................................................................................................................. 1 2.0 Introduction .......................................................................................................................... 1 3.0 Discussion ............................................................................................................................ 4 3.1 Selection of Tanks for Level Decrease

  13. A = 7 General Tables

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

    Hyperfine Structure b-decay Muons Hypernuclei and Baryons Pion, Kaon and Eta-Mesons Other Work Applications The General Table for 7Be is subdivided into the following categories:...

  14. Tables of Energy Levels

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

    of Energy Levels The Image Map below will direct you to the table of energy levels PDF format only for that particular nuclide from the most recent publication found within...

  15. Torque/Moab vs. SLURM Comparisons

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

    Users TorqueMoab vs. SLURM Comparisons TorqueMoab vs. SLURM Comparisons TORQUE vs. SLURM Comparison Tables MoabTorque vs. Slurm Environment Variables Description MoabTorque ...

  16. FY 2006 Laboratory Table

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

    Laboratory Tables Preliminary Department of Energy FY 2006 Congressional Budget Request Office of Management, Budget and Evaluation/CFO February 2005 Laboratory Tables Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals,

  17. FY 2006 State Table

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

    State Tables Preliminary Department of Energy FY 2006 Congressional Budget Request Office of Management, Budget and Evaluation/CFO February 2005 State Tables Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or

  18. FY 2007 Laboratory Table

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

    Laboratory tables preliminary Department of Energy FY 2007 Congressional Budget Request February 2006 Printed with soy ink on recycled paper Office of Chief Financial Officer Laboratory tables preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or other

  19. FY 2007 State Table

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

    state tables preliminary Department of Energy FY 2007 Congressional Budget Request February 2006 Printed with soy ink on recycled paper Office of Chief Financial Officer state tables preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or other

  20. FY 2008 Laboratory Table

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

    Laboratory Table Preliminary Department of Energy FY 2008 Congressional Budget Request February 2007 Office of Chief Financial Officer Laboratory Table Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or other

  1. FY 2008 State Table

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

    State Table Preliminary Department of Energy FY 2008 Congressional Budget Request February 2007 Office of Chief Financial Officer State Table Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or other adjustments

  2. FY 2010 Laboratory Table

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

    Laboratory Tables Preliminary May 2009 Office of Chief Financial Officer FY 2010 Congressional Budget Request Laboratory Tables Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, use of prior year balances, deferrals, rescissions, or other adjustments appropriated as offsets to the DOE appropriations by

  3. FY 2011 Laboratory Table

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

    Laboratory Tables Department of Energy FY 2011 Congressional Budget Request DOE/CF-0055 March 2010 Office of Chief Financial Officer Laboratory Tables Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, use of prior year balances, deferrals, rescissions, or other adjustments

  4. FY 2011 State Table

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

    State Tables Department of Energy FY 2011 Congressional Budget Request DOE/CF-0054 March 2010 Office of Chief Financial Officer State Tables Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, use of prior year balances, deferrals, rescissions, or other adjustments appropriated

  5. FY 2012 State Table

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

    6 Department of Energy FY 2012 Congressional Budget Request State Tables P li i Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0066 Department of Energy FY 2012 Congressional Budget Request State Tables P li i Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They displayed. The figures include both the discretionary and

  6. Fy 2009 Laboratory Table

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

    Laboratory Tables Preliminary February 2008 Office of Chief Financial Officer Department of Energy FY 2009 Congressional Budget Request Laboratory Tables Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, use of prior year balances, deferrals, rescissions, or other adjustments appropriated as offsets to

  7. FY 2013 State Table

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

    9 Department of Energy FY 2013 Congressional Budget Request State Tables P li i Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0079 Department of Energy FY 2013 Congressional Budget Request State Tables P li i Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They displayed. The figures include both the discretionary and

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

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

  9. Using Wikipedia to forecast diseases

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

  10. 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 ...

  11. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

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

  12. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01

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

  13. The forecast calls for flu

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

  14. CPMS Tables | Department of Energy

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

    Program Management » Quality Assurance » CPMS Tables CPMS Tables EM Quality Assurance Corporate Performance Metrics table. CPMS Tables (233.47 KB) More Documents & Publications EM Corporate QA Performance Metrics QA Corporate Board Meeting - July 2008 QA Corporate Board Meeting - November 2008

  15. CBECS Buildings Characteristics --Revised Tables

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

    Structure Tables (16 pages, 93 kb) CONTENTS PAGES Table 8. Building Size, Number of Buildings, 1995 Table 9. Building Size, Floorspace, 1995 Table 10. Year Constructed, Number of Buildings, 1995 Table 11. Year Constructed, Floorspace, 1995 These data are from the 1995 Commercial Buildings Energy Consumption Survey (CBECS), a national probability sample survey of commercial buildings sponsored by the Energy Information Administration, that provides information on the use of energy in commercial

  16. FY 2012 Laboratory Table

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

    5 Department of Energy FY 2012 Congressional Budget Request Laboratory Tables y Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0065 Department of Energy FY 2012 Congressional Budget Request Laboratory Tables P li i Preliminary h b d i d i hi d h l l f b d h i f h The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider

  17. FY 2013 Laboratory Table

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

    8 Department of Energy FY 2013 Congressional Budget Request Laboratory Tables y Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0078 Department of Energy FY 2013 Congressional Budget Request Laboratory Tables P li i Preliminary h b d i d i hi d h l l f b d h i f h The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider

  18. Appendix B: Summary Tables

    Gasoline and Diesel Fuel Update (EIA)

    U.S. Energy Information Administration | Analysis of Impacts of a Clean Energy Standard as requested by Chairman Bingaman Appendix B: Summary Tables Table B1. The BCES and alternative cases compared to the Reference case, 2025 2009 2025 Ref Ref BCES All Clean Partial Credit Revised Baseline Small Utilities Credit Cap 2.1 Credit Cap 3.0 Stnds + Cds Generation (billion kilowatthours) Coal 1,772 2,049 1,431 1,305 1,387 1,180 1,767 1,714 1,571 1,358 Petroleum 41 45 43 44 44 44 45 45 45 43 Natural

  19. Microsoft Word - table_01

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

    U.S. Energy Information Administration | Natural Gas Monthly 3 Table 1 Table 1. Summary of natural gas supply and disposition in the United States, 2011-2016 (billion cubic feet) Year and Month Gross Withdrawals Marketed Production NGPL Production a Dry Gas Production b Supplemental Gaseous Fuels c Net Imports Net Storage Withdrawals d Balancing Item e Consumption f 2011 Total 28,479 24,036 1,134 22,902 60 1,963 -354 -94 24,477 2012 Total 29,542 25,283 1,250 24,033 61 1,519 -9 -66 25,538 2013

  20. Microsoft Word - table_08

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

    3 Table 8 Created on: 8/26/2016 3:14:08 PM Table 8. Underground natural gas storage - all operators, 2011-2016 (volumes in billion cubic feet) Year and Month Natural Gas in Underground Storage at End of Period Change in Working Gas from Same Period Previous Year Storage Activity Base Gas Working Gas Total a Volume Percent Injections Withdrawals Net Withdrawals b 2011 Total c -- -- -- -- -- 3,422 3,074 -348 2012 Total c -- -- -- -- -- 2,825 2,818 -7 2013 Total c -- -- -- -- -- 3,156 3,702 546

  1. Microsoft Word - table_09

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

    5 Table 9 Created on: 8/26/2016 3:14:26 PM Table 9. Underground natural gas storage - by season, 2014-2016 (volumes in billion cubic feet) Year, Season, and Month Natural Gas in Underground Storage at End of Period Change in Working Gas from Same Period Previous Year Storage Activity Base Gas Working Gas Total Volume Percent Injections Withdrawals Net Withdrawals a 2014 Refill Season April 4,357 1,066 5,423 -789 -42.5 323 105 -217 May 4,353 1,548 5,901 -722 -31.8 529 51 -478 June 4,358 2,005

  2. Microsoft Word - table_11

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

    7 Table 11 Created on: 8/26/2016 3:15:09 PM Table 11. Underground natural gas storage - storage fields other than salt caverns, 2011-2016 (volumes in billion cubic feet) Year and Month Natural Gas in Underground Storage at End of Period Change in Working Gas from Same Period Previous Year Storage Activity Base Gas Working Gas Total Volume Percent Injections Withdrawals Net Withdrawals a 2011 Total b -- -- -- -- -- 2,889 2,634 -255 2012 Total b -- -- -- -- -- 2,360 2,373 12 2013 Total b -- -- --

  3. Microsoft Word - table_13

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

    U.S. Energy Information Administration | Natural Gas Monthly 33 Table 13 Table 13. Activities of underground natural gas storage operators, by state, June 2016 (volumes in million cubic feet) State Field Count Total Storage Capacity Working Gas Storage Capacity Natural Gas in Underground Storage at End of Period Change in Working Gas from Same Period Previous Year Storage Activity Base Gas Working Gas Total Volume Percent Injections Withdrawals Alabama 2 43,600 33,150 10,450 23,615 34,065 3,085

  4. 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 ...

  5. Solar Energy Market Forecast | Open Energy Information

    Open Energy Info (EERE)

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

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

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

    Soft Costs Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Project Profile: Forecasting and Influencing Technological Progress in Solar ...

  7. National Oceanic and Atmospheric Administration Provides Forecasting...

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

    ... will share their expertise with CLASIC and CHAPS forecasters and project leaders as they consult on the forecast that will determine the day's operations plan. -- Storm Prediction ...

  8. Intermediate future forecasting system

    SciTech Connect (OSTI)

    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.

  9. FY 2006 Statistical Table

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

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) FY 2004 FY 2005 FY 2006 Comparable Comparable Request to FY 2006 vs. FY 2005 Approp Approp Congress Discretionary Summary By Appropriation Energy And Water Development Appropriation Summary: Energy Programs Energy supply Operation and maintenance................................................. 787,941 909,903 862,499 -47,404 -5.2% Construction......................................................................... 6,956

  10. FY 2013 Statistical Table

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

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) FY 2011 FY 2012 FY 2013 Current Enacted Congressional Approp. Approp. * Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy........................................ 1,771,721 1,809,638 2,337,000 +527,362 +29.1% Electricity delivery and energy reliability.........................................

  11. Table of Contents

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

    COMMUNICATIONS REQUIREMENTS OF SMART GRID TECHNOLOGIES October 5, 2010 i Table of Contents I. Introduction and Executive Summary.......................................................... 1 a. Overview of Smart Grid Benefits and Communications Needs................. 2 b. Summary of Recommendations .................................................................... 5 II. Federal Government Smart Grid Initiatives ................................................ 7 a. DOE Request for Information

  12. TABLE OF CONTENTS

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

    DE-EM0001840 Page 2 of 108 WIPP Transportation Services Table of Contents SECTION B - SUPPLIES OR SERVICES AND PRICES/COSTS ................................................................ 3 SECTION C - DESCRIPTION/SPECIFICTIONS ....................................................................................... 10 SECTION D -PACKAGING AND MARKING .............................................................................................. 34 SECTION E - INSPECTION AND ACCEPTANCE

  13. TABLE OF CONTENTS

    National Nuclear Security Administration (NNSA)

    AC05-00OR22800 TABLE OF CONTENTS Contents Page # TOC - i SECTION A - SOLICITATION/OFFER AND AWARD ......................................................................... A-i SECTION B - SUPPLIES OR SERVICES AND PRICES/COSTS ........................................................ B-i B.1 SERVICES BEING ACQUIRED ....................................................................................B-2 B.2 TRANSITION COST, ESTIMATED COST, MAXIMUM AVAILABLE FEE, AND AVAILABLE FEE (Modification 295,

  14. 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 ...

  15. Science on Tap - Forecasting illness

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

  16. 1995 CECS C&E Tables

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

    Electricity Tables (35 pages, 218 kb) CONTENTS PAGES Table 9. Total Electricity Consumption and Expenditures, 1995 Table 10. Electricity Consumption and Expenditure Intensities,...

  17. 1995 CECS C&E Tables

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

    kb) CONTENTS PAGES Table 1. Total Energy Consumption by Major Fuel, 1995 Table 9. Total Electricity Consumption and Expenditures, 1995 Table 20. Total Natural Gas Consumption and...

  18. 1995 CECS C&E Tables

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

    pages, 95 kb) CONTENTS PAGES Table 3. Consumption for Sum of Major Fuels, 1995 Table 10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas...

  19. 1995 CECS C&E Tables

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

    kb) CONTENTS PAGES Table 2. Total Energy Expenditures by Major Fuel, 1995 Table 9. Total Electricity Consumption and Expenditures, 1995 Table 20. Total Natural Gas Consumption and...

  20. 1995 CECS C&E Tables

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

    pages, 95 kb) CONTENTS PAGES Table 4. Expenditures for Sum of Major Fuels, 1995 Table10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas...

  1. table3.5_02

    Gasoline and Diesel Fuel Update (EIA)

    ... Wood Chips, Bark Table 3.5 Selected Byproducts in Fuel Consumption, 2002; Level: National ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ...

  2. Energy.gov Data Tables

    Broader source: Energy.gov [DOE]

    Follow these guidelines for creating Section 508-compliant data tables in the Energy.gov Drupal environment.

  3. Advanced Vehicle Technologies Awards Table

    Broader source: Energy.gov [DOE]

    The table contains a listing of the applicants, their locations, the amounts of the awards, and description of each project.

  4. 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-2016-07-20.xlsx (72.85 KB) More Documents & Publications Small Business Program Manager Directory EA-1900: Notice of Availability of a Draft Environmental Assessment Assessment Report: OAS-V-15-01

  5. 2003 CBECS Detailed Tables: Summary

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

    c32.pdf c32.xls c32.html Fuel Oil (Tables C33-C36) set12-pdf Table C33. Total Fuel Oil Consumption and Expenditures c33-pdf c33.xls c33.html Table C34. Fuel Oil Consumption...

  6. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01

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

  7. TABLE OF CONTENTS

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

    irecusa.org | LMI Guidelines | 0 www.irecusa.org | LMI Guidelines | i TABLE OF CONTENTS Executive Summary iv Content Overview vii Introduction 1 I. Identifying LMI Customers and Designing Facilities to Serve LMI Customers 5 A. LMI Customers 5 B. Designing Facilities to Serve LMI Customers 6 II. Barriers to Adoption and Opportunities for Engagement 11 A. Financial Barriers 11 B. Ownership Barriers and Split Incentives 14 C. Marketing, Education, and Outreach Barriers 15 D. Opportunities for

  8. Description of Energy Intensity Tables (12)

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

    3. Description of Energy Intensity Data Tables There are 12 data tables used as references for this report. Specifically, these tables are categorized as tables 1 and 2 present...

  9. International Program Action Table - October 2012 | Department...

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

    Communication & Engagement International Programs International Program Action Table - October 2012 International Program Action Table - October 2012 International Program ...

  10. National Targets Table

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

    Nov 2011 For instructions on how to use the table and footnotes, see page 2 Education 144 63% 58 K-12 School College/University (campus level) 244 63% 104 Food Sales 570 86% 193 Grocery Store/Food Market Convenience store (with or without gas station) 657 90% 228 Food Service 575 59% 267 Restaurant/Cafeteria 434 53% 207 Fast Food 1170 64% 418 Inpatient Health Care (Hospital) Lodging 163 61% 72 Dormitory/Fraternity/Sorority Hotel/Motel/Inn Mall (Strip and Enclosed) 247 71% 94 Nursing/Assisted

  11. Microsoft Word - table_10

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

    6 Created on: 8/26/2016 3:14:45 PM Table 10. Underground natural gas storage - salt cavern storage fields, 2011-2016 (volumes in billion cubic feet) Year and Month Natural Gas in Underground Storage at End of Period Change in Working Gas from Same Period Previous Year Storage Activity Base Gas Working Gas Total Volume Percent Injections Withdrawals Net Withdrawals a 2011 Total b -- -- -- -- -- 533 440 -92 2012 Total b -- -- -- -- -- 465 445 -20 2013 Total b -- -- -- -- -- 492 521 29 2014 January

  12. 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 ...

  13. Picture of the Week: Forecasting Flu

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

  14. Sandia Unstructured Triangle Table Generator

    Energy Science and Technology Software Center (OSTI)

    2013-09-16

    The software generates data tables for thermodynamic and transport properties of materials as described by a set of input models. For each input model parameterization, an associated table is created on an unstructured triangular grid. These grids all conform to the same topology. A statistical accuracy guarantee is provided for the tabular representation of the model. Details of the model and table specification are given in a XML input deck.

  15. table3.6_02

    Gasoline and Diesel Fuel Update (EIA)

    ... Selected Wood and Wood-Related Products in Fuel Consumption, 2002; Level: National and ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ...

  16. MECS 1991 Publications and Tables

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

    Capability To Switch Fuels Appendices Appendix A. Detailed Tables Appendix B. Survey Design, Implementation, and Estimates (file size 141,211 bytes) pages: 22. Appendix C....

  17. Health Care Buildings: Subcategories Table

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

    Subcategories Table Selected Data by Type of Health Care Building Number of Buildings (thousand) Percent of Buildings Floorspace (million square feet) Percent of Floorspace Square...

  18. Health Care Buildings: Equipment Table

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

    Equipment Table Buildings, Size and Age Data by Equipment Types for Health Care Buildings Number of Buildings (thousand) Percent of Buildings Floorspace (million square feet)...

  19. Table 1. Crude Oil Prices

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

    from Table 24. Refiner acquisition costs -- Energy Information Administration, Form FEA-P110-M-1, "Refiners' Monthly Cost Allocation Report," January 1978 through June 1978;...

  20. The Value of Wind Power Forecasting

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

    ... day-ahead wind generation forecasts yields an average of 195M savings in annual operating costs. Figure 6 shows how operating cost savings vary with improvements in forecasting. ...

  1. EIA lowers forecast for summer gasoline prices

    U.S. 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. ...

  2. Wind Forecasting Improvement Project | Department of Energy

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

    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 R&D Newsletter. In July, the Department of Energy launched a $6 million project with the National Oceanic and Atmospheric Administration (NOAA) and private partners to improve wind forecasting. Wind power forecasting allows system operators to anticipate the electrical output of wind plants and adjust the electrical

  3. UPF Forecast | Y-12 National Security Complex

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

    Subcontracting / Subcontracting Forecasts / UPF Forecast UPF Forecast UPF Procurement provides the following forecast of subcontracting opportunities. Keep in mind that these requirements may be revised or cancelled, depending on program budget funding or departmental needs. If you have questions or would like to express an interest in any of the opportunities listed below, contact UPF Procurement. Descriptiona Methodb NAICS Est. Dollar Range RFP release/ Award datec Buyer/ Phone Commodities

  4. Microsoft Word - table_03

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

    7 Created on: 8/26/2016 3:17:42 PM Table 3. Selected national average natural gas prices, 2011-2016 (dollars per thousand cubic feet, except where noted) Year and Month NGPL Composite Spot Price a Natural Gas Spot Price b Citygate Price Delivered to Consumers Electric Power Price d Residential Commercial Industrial Price % of Total c Price % of Total c Price % of Total c 2011 Annual Average 15.12 4.00 5.63 11.03 96.2 8.91 67.3 5.13 16.3 4.89 2012 Annual Average 10.98 2.75 4.73 10.65 95.8 8.10

  5. QTR table of respondents | Department of Energy

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

    table of respondents QTR table of respondents (108.44 KB) More Documents & Publications Table of QTR comments in response to Federal Register RFI Table of QTR comments in response to Federal Register RFI Table of QTR comments in response to Federal Register RFI

  6. 1999 Commercial Building Characteristics--Detailed Tables--Principal...

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

    Principal Building Activities > Detailed Tables-Principal Building Activities Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Principal Building Activities Table B1....

  7. 1999 Commercial Building Characteristics--Detailed Tables--Year...

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

    Year Constructed > Detailed Tables-Year Constructed Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Year Constructed Table B8. Year Constructed, Number of Buildings...

  8. EM International Program Action Table - June 2014 | Department...

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

    Action Table - June 2014 EM International Program Action Table - June 2014 EM International Program Action Table - June 2014 PDF icon EM International Program Action Table - June ...

  9. Annual Energy Outlook (AEO) 2006 - Supplemental Tables - All Tables

    SciTech Connect (OSTI)

    2009-01-18

    Tables describing regional energy consumption and prices by sector; residential, commercial, and industrial demand sector data; transportation demand sector; electricity and renewable fuel; and petroleum, natural gas, and coal data.

  10. 1995 CECS C&E Tables

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

    Building Level Intensities (percentile) (6 pages, 39 kb) CONTENTS PAGES Table 10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas Consumption and...

  11. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Census Region for Sum of Major Fuels, 1995 Table 11. Electricity Consumption and Conditional Energy Intensity by Census Region, 1995 Table 22....

  12. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Year Constructed for Sum of Major Fuels, 1995 Table 14. Electricity Consumption and Conditional Energy Intensity by Year Constructed, 1995 Table...

  13. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Building Size for Sum of Major Fuels, 1995 Table13. Electricity Consumption and Conditional Energy Intensity by Building Size, 1995 Table 24....

  14. Commerial Buildings Characteristics, 1995 (Table of Contents...

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

    Number of Buildings and Relative Standard Errors, 1995 Table I.2. Participation in Energy Conservation Programs, Floorspace and Relative Standard Errors, 1995 Table J.1....

  15. Trends in Commercial Buildings--Table

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

    Home > Trends in Commercial Buildings > Energy Consumption - Part 1> Site Energy Consumption Tables Table 1. Total site energy consumption, relative standard errors, and 95%...

  16. 1995 CECS C&E Tables

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

    Category (6 pages, 36 kb) CONTENTS PAGES Table 17. Peak Electricity Demand Category, Number of Buildings, 1995 Table 18. Peak Electricity Demand Category, Floorspace, 1995 These...

  17. Appendix B: Technical Projection Tables, Bioenergy Technologies...

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

    Tables B-2 Last updated: November 2014 Table B-2: Terrestrial Feedstock Supply and Logistics Costs to Supply Feedstock to a Pyrolysis Conversion Process Processing Area Cost...

  18. Precision Flow Table | Open Energy Information

    Open Energy Info (EERE)

    Table Jump to: navigation, search Basic Specifications Facility Name Flow Table Overseeing Organization United States Army Corp of Engineers (ERDC) Hydrodynamic Testing Facility...

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

    SciTech Connect (OSTI)

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

    2013-01-01

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

  20. Supply Forecast and Analysis (SFA)

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

    Matthew Langholtz Science Team Leader Oak Ridge National Laboratory DOE Bioenergy Technologies Office (BETO) 2015 Project Peer Review Supply Forecast and Analysis (SFA) 2 | Bioenergy Technologies Office Goal Statement * Provide timely and credible estimates of feedstock supplies and prices to support - the development of a bioeconomy; feedstock demand analysis of EISA, RFS2, and RPS mandates - the data and analysis of other projects in Analysis and Sustainability, Feedstock Supply and Logistics,

  1. Table of tables: A database design tool for SYBASE

    SciTech Connect (OSTI)

    Brown, B.C.; Coulter, K.; Glass, H.D.; Glosson, R.; Hanft, R.W.; Harding, D.J.; Trombly-Freytag, K.; Walbridge, D.G.C.; Wallis, D.B. ); Allen, M.E. )

    1991-01-04

    The Table of Tables' application system captures in a set of SYBASE tables the basic design specification for a database schema. Specification of tables, columns (including the related defaults and rules for the stored values) and keys is provided. The feature which makes this application specifically useful for SYBASE is the ability to automatically generate SYBASE triggers. A description field is provided for each database object. Based on the data stored, SQL scripts for creating complete schema including the tables, their defaults and rules, their indexes, and their SYBASE triggers, are written by TOT. Insert, update and delete triggers are generated from TOT to guarantee integrity of data relations when tables are connected by single column foreign keys. The application is written in SYBASE's APT-SQL and includes a forms based data entry system. Using the features of TOT we can create a complete database schema for which the data integrity specified by our design is guaranteed by the SYBASE triggers generated by TOT. 3 refs.

  2. table1.4_02

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

    ... products (e.g., crude oil converted to residual and distillate fuel oils) are excluded. ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ...

  3. Health Care Buildings: Consumption Tables

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

    Consumption Tables Sum of Major Fuel Consumption by Size and Type of Health Care Building Total (trillion Btu) per Building (million Btu) per Square Foot (thousand Btu) Dollars per...

  4. Microsoft Word - table_19.doc

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

    7 Table 19. Natural gas delivered to industrial consumers for the account of others by state, 2010-2014 (volumes in million cubic feet) Alabama 109,031 75.2 117,277 76.5 133,765 ...

  5. Microsoft Word - table_17.doc

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

    4 Table 17. Natural gas delivered to residential consumers for the account of others by state, 2010-2014 (volumes in million cubic feet) Alabama 0 -- 0 -- 0 -- 0 -- 0 -- Alaska 0 ...

  6. ARM - Instrument - s-table

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

    govInstrumentss-table Documentation 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 Instrument : Stabilized Platform (S-TABLE) Instrument Categories Ocean Observations For ship-based deployments, some instruments require actively stabilized platforms to compensate for the ship's motion, especially rotations around the long axis of the ship (roll), short axis (pitch), and, for some instruments, vertical axis (yaw).

  7. 2012 NISE Awards Summary Table

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

    Awards » 2012 NISE Summary Table 2012 NISE Awards Summary Table Investigator NERSC repo Hours awarded DOE Office Project Title Gilbert Compo, University of Colorado at Boulder m958 10,000,000 BER Climate Research Ocean-Atmosphere Reanalysis for Climate Applications (OARCA) 1850-2013 Silvia Crivelli, Lawrence Berkeley National Laboratory m1532 1,550,000 BER Biological Systems Science WeFold: A collaborative effort for protein structure prediction Thomas Hamill, National Oceanic & Atmospheric

  8. 2013 NISE Awards Summary Table

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

    Awards » 2013 NISE Summary Table 2013 NISE Awards Summary Table Investigator NERSC repo Hours awarded DOE Office Project Title Katie Antypas, Lawrence Berkeley National Laboratory m1759 250,000 ASCR Applied Mathematical Sciences NERSC Application Readiness for Future Architectures Inez Fung, University of California Berkeley m189 750,000 BER Climate and Environmental Sciences Carbon Data Assimilation with a Coupled Ensemble Kalman Filter Thomas Hamill, National Oceanic & Atmospheric

  9. ARM - CARES - Tracer Forecast for CARES

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

    CampaignsCarbonaceous Aerosols and Radiative Effects Study (CARES)Tracer Forecast for CARES Related Links CARES Home AAF Home ARM Data Discovery Browse Data Post-Campaign Data Sets Field Updates CARES Wiki Campaign Images Experiment Planning Proposal Abstract and Related Campaigns Science Plan Operations Plan Measurements Forecasts News 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

  10. LED Lighting Forecast | Department of Energy

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

    Publications » Market Studies » LED Lighting Forecast LED Lighting Forecast 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. With declining costs and improving performance, LED products have been seeing increased adoption for general illumination applications. This is a positive development in terms of energy consumption, as LEDs use significantly

  11. NREL: Resource Assessment and Forecasting Home Page

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

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

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

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

  13. Forecast and Funding Arrangements - Hanford Site

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

  14. NREL: Resource Assessment and Forecasting - Webmaster

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

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

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

    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 ...

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

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

    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 ...

  17. Sandia National Labs: PCNSC: IBA Table

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

    Departments Radiation, Nano Materials, & Interface Sciences > Radiation & Solid Interactions > Nanomaterials Sciences > Surface & Interface Sciences Semiconductor & Optical Sciences Energy Sciences Small Science Cluster Business Office News Partnering Research Ion Beam Analysis (IBA) Periodic Table (HTML) IBA Table (HTML) | IBA Table (135KB GIF) | IBA Table (1.2MB PDF) | IBA Table (33MB TIF) | Heavy Ion Backscattering Spectrometry (HIBS) | Virtual Lab Tour (6MB) The

  18. 2011 NISE Awards Summary Table

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

    Awards » 2011 NISE Summary Table 2011 NISE Awards Summary Table Investigator NERSC Repo Hours Awarded DOE Office Project Title Dmitri Babikov, Marquette University m409 1,450,000 BES Chemistry New potential energy surface for ozone molecule Connor Balance, Auburn University m41 600,000 Fusion Energy Hybrid OpenMP/MPI approach to R-matrix scattering Amitava Bhattacharjee, University of New Hampshire m148 1,000,000 Fusion Energy Global Effects on the Dynamics of Plasmoids and Flux Ropes during

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

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

  20. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Broader source: All U.S. Department of Energy (DOE) Office 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, ...

  1. Study forecasts disappearance of conifers due to climate change

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

  2. Microsoft Word - table_07.doc

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

    8 Table 7. Supplemental gas supplies by state, 2014 (million cubic feet) Colorado 0 10 0 4,110 4,120 Delaware 0 6 0 0 6 Georgia 0 0 608 26 635 Hawaii 2,733 10 0 0 2,743 Illinois 0 ...

  3. Microsoft Word - table_18.doc

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

    5 Table 18. Natural gas delivered to commercial consumers for the account of others by state, 2010-2014 (volumes in million cubic feet) Alabama 5,494 20.3 5,313 21.1 5,126 23.8 ...

  4. Microsoft Word - table_04.doc

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

    2 Table 4. Offshore gross withdrawals of natural gas by state and the Gulf of Mexico, 2010-2014 (million cubic feet) 2010 Total 234,236 341,365 575,601 1,701,665 598,679 2,300,344 ...

  5. Microsoft Word - table_23.doc

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

    6 Table 23. Average citygate price of natural gas in the United States, 2010- 2014 (dollars per thousand cubic feet) Alabama 6.46 5.80 5.18 4.65 4.93 Alaska 6.67 6.53 6.14 6.02 ...

  6. Microsoft Word - table_13.doc

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

    3 Table 13. Additions to and withdrawals from gas storage by state, 2014 (million cubic feet) Alabama 34,286 28,683 5,603 1,664 1,869 -206 5,397 Alaska 11,675 6,523 5,152 0 0 0 ...

  7. Microsoft Word - table_14.doc

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

    44 Table 14. Underground natural gas storage capacity by state, December 31, 2014 (million cubic feet) Alabama 1 21,950 30,100 0 0 0 1 11,200 13,500 2 33,150 43,600 Alaska 0 0 0 0 ...

  8. Microsoft Word - table_27.doc

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

    8 Table 28. Percent distribution of natural gas delivered to consumers by state, 2014 Alabama 0.8 0.8 2.5 0.6 4.2 Alaska 0.3 0.5 0.1 < 0.4 Arizona 0.6 0.9 0.3 5.8 2.5 Arkansas 0.7 ...

  9. Table 2a. Electricity Consumption and Electricity Intensities...

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

    Administration Home Page Home > Commercial Buildings Home > Sq Ft Tables > Table 2a. Electricity Consumption per Sq Ft Table 2a. Electricity Consumption and Electricity...

  10. FY 2014 Budget Request Statistical Table | Department of Energy

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

    Statistical Table FY 2014 Budget Request Statistical Table PDF icon Stats Table FY2014.pdf More Documents & Publications FY 2009 Environmental Management Budget Request to Congress ...

  11. FY 2014 Budget Request Summary Table | Department of Energy

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

    PDF icon Summary Table by Appropriations PDF icon Summary Table by Organization More Documents & Publications FY 2014 Budget Request Statistical Table FY 2014 Budget Justification ...

  12. table3.4_02.xls

    Gasoline and Diesel Fuel Update (EIA)

    ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ... were Table 3.4 Number of Establishments by Fuel Consumption, 2002; Level: National Data; ...

  13. TableHC2.7.xls

    Gasoline and Diesel Fuel Update (EIA)

    ... Table HC7.7 Air-Conditioning Usage Indicators by Household Income, 2005 Below Poverty Line ... Table HC7.7 Air-Conditioning Usage Indicators by Household Income, 2005 Below Poverty Line ...

  14. TableHC2.10.xls

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

    ... Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line ... Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line ...

  15. CBECS 1992 - Building Characteristics, Detailed Tables

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

    major topics of each table. Directions for calculating an approximate relative standard error (RSE) for each estimate in the tables are presented in Figure A1, "Use of RSE Row...

  16. Code Tables | National Nuclear Security Administration | (NNSA)

    National Nuclear Security Administration (NNSA)

    Code Tables U.S. Department of Energy / U.S. Nuclear Regulatory Commission Nuclear Materials Management & Safeguards System Code Tables Action Code The action code identifies the type of activity being reported in a transaction. The Action Code table shows the valid action codes. Nature of Transaction (TI) Code The financial code signifies the nature of the financial or contractual activity that is involved in the transaction. The Nature of Transaction (TI) Code table shows the valid action

  17. SEP Program Transition Tables | Department of Energy

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

    Transition Tables SEP Program Transition Tables The Program Transition Tables provide information concerning the level of effort required to move from a traditional, industrial incentive program to Strategic Energy Management, ISO 50001, or SEP. Both the customers' and utility program administrators' perspectives are considered. Utilities and PAs can use these detailed tables to understand and develop estimates of scope, resources, and realistic implementation timelines. View Program Transition

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

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1994-02-01

    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.

  19. NREL: Resource Assessment and Forecasting - Facilities

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

    The Solar Radiation Research Laboratory gathers solar radiation and meteorological data on South Table Mountain. NREL's Solar Radiation Research Laboratory (SRRL) has been ...

  20. Coal Fired Power Generation Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  1. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  4. SECTION J - TABLE OF CONTENTS

    National Nuclear Security Administration (NNSA)

    Conformed to Mod 0108 DE-NA0000622 Section J Page i PART III - LIST OF DOCUMENTS, EXHIBITS, AND OTHER ATTACHMENTS SECTION J LIST OF APPENDICES TABLE OF CONTENTS Appendix A Statement of Work (Replaced by Mod 002; Modified Mod 016; Replaced Mod 029) Appendix B Performance Evaluation Plan (Replaced by Mods 002, 016, 020, 029, 0084) Appendix C Contractor's Transition Plan Appendix D Sensitive Foreign Nations Control Appendix E Performance Guarantee Agreement(s) Appendix F National Work Breakdown

  5. Flood Forecasting in River System Using ANFIS

    SciTech Connect (OSTI)

    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.

  6. energy data + forecasting | OpenEI Community

    Open Energy Info (EERE)

    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...

  7. Text-Alternative Version LED Lighting Forecast

    Office of Energy Efficiency and Renewable Energy (EERE)

    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. 1999 Commercial Building Characteristics--Detailed Tables--Census...

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

    Census Region > Detailed Tables-Census Region Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Census Region Table B3. Census Region, Number of Buildings and Floorspace...

  9. FY 2014 Budget Request Laboratory Table | Department of Energy

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

    Laboratory Table FY 2014 Budget Request Laboratory Table Lab Table FY2014.pdf (235.54 KB) More Documents & Publications FY 2014 Budget Request State Table Fiscal Year 2013 President's Budget Request Fiscal Year 2013 President's

  10. FY 2014 Budget Request State Table | Department of Energy

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

    State Table FY 2014 Budget Request State Table State Table FY2014.pdf (279.32 KB) More Documents & Publications FY 2014 Budget Request Laboratory Table FY 2007 Congressional Budget Request FY 2007 Congressional

  11. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01

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

  12. TableBuster V1.0

    Energy Science and Technology Software Center (OSTI)

    2003-06-06

    Brief Description:TableBuster enables Telelogic DOORS users to export tables with split merged cells from Microsoft Word into DOORS. Practical Application: Users of Telelogic DOORS will be more easily able to track and manage requirements that are initally defined in Microsoft Word tables containing split or merged cells. Method of Solution: TableSplitter contains two procedures. The Setup subroutine unlinks all Word fields in the active Word document. It next counts all the tables in the documentmore » and then calls the SplitCells subroutine. SplitCells splits the appropriate cells for each table, so a n row by m column table actually has n by m cells that DOORS can import.« less

  13. Science on the Hill: The forecast calls for flu

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

    The forecast calls for flu The forecast calls for flu Using mathematics, computer programs, statistics and information about how disease develops and spreads, a research team at Los Alamos National Laboratory found a way to forecast the flu season and even next week's sickness trends. January 15, 2016 Forecasting flu A team from Los Alamos has developed a method to predict flu outbreaks based in part on influenza-related searches of Wikipedia. The forecast calls for flu Beyond the familiar flu,

  14. Table

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

    from (2012KE01): Energy Levels of 11 Li E x (MeV ± keV) J π ; T T 1 2 or Γ Decay Reactions g.s. 3 2 - ; 5 2 T 1 2 = 8.75 ± 0.14 ms β - 1, 2, 4, 5, 6, 8, 9 1.220 ± 40 Γ = 0.53 ± 0.15 MeV n 2, 6, 7, 9, 10 2.420 ± 50 Γ = 1.26 ± 0.30 MeV n 2, 4, 6, 7, 9, 10 3.700 ± 130 Γ < 200 keV n 7 4.860 ± 60 Γ < 100 keV n 2, 4, 9 6.230 ± 60 Γ < 100 keV n 2, 4, 9 11.300 n 2 1

  15. Table

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

    4 from (2012KE01): Energy levels of 11 Be E x (MeV ± keV) J π ; T T 1 2 or Γ c.m. (keV) Decay Reactions 0 1 2 + ; 3 2 T 1 2 = 13.76 ± 0.07 s β - 1, 3, 4, 5, 6, 8, 9, 10, 12, 14, 16, 17, 19, 23, 24, 25, 26, 27, 28, 30, 31, 32 0.32004 ± 0.1 1 2 - T 1 2 = 115 ± 10 fs γ 4, 5, 6, 8, 9, 10, 14, 15, 16, 17, 19, 21, 22, 23, 26, 28, 29, 30, 33 1.783 ± 4 5 2 + Γ = 100 ± 10 n 4, 5, 6, 9, 10, 14, 23, 26, 28 2.654 ± 10 3 2 - a 206 ± 8 n 5, 6, 9, 10, 15, 16, 21, 22, 23, 28, 29 3.40 ± 6 ( 3 2 - ,

  16. Table

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

    8 from (2012KE01): Energy levels of 11 B E x J π ; T Γ cm (keV) Decay Reactions (MeV ± keV) 0 3 2 - ; 1 2 stable 2, 3, 7, 8, 11, 15, 16, 17, 18, 19, 22, 26, 27, 28, 29, 30, 32, 33, 34, 35, 36, 37, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 51, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 67, 68, 69, 70, 71, 72, 73, 74 2.124693 ± 0.027 1 2 - 0.117 ± 0.004 eV γ 2, 7, 8, 11, 15, 16, 17, 18, 19, 26, 27, 28, 30, 32, 33, 35, 36, 37, 39, 40, 42, 44, 51, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 67, 68, 69,

  17. Table

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

    38 from (2012KE01): Energy levels of 11 C a E x in 11 C J π ; T T 1 2 or Γ cm Decay Reactions (MeV ± keV) 0 3 2 - ; 1 2 T 1 2 = 20.364 ± 0.014 min β + 1, 2, 6, 7, 10, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 43, 44 2.0000 ± 0.4 1 2 - T 1 2 = 7.1 ± 0.5 fs γ 2, 3, 6, 7, 10, 16, 17, 18, 19, 21, 22, 26, 28, 30, 31, 32, 33, 38, 39, 44 4.3188 ± 1.2 5 2 - < 8.3 fs γ 2, 3, 6, 7, 10, 16, 17, 19, 21, 22, 26, 28, 30, 31, 34, 38, 39, 44 4.8042

  18. Table

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

    5 from (2012KE01): Energy levels of 11 N E res (MeV ± keV) E x (MeV ± keV) J π ; T Γ (keV) Decay Reactions 1.49 ± 60 0 1 2 + ; 3 2 830 ± 30 p 1, 2, 3, 6 2.22 ± 30 0.73 ± 70 1 2 - 600 ± 100 p 1, 2, 3, 5, 6 3.06 ± 80 (1.57 ± 80) < 100 p 3 3.69 ± 30 2.20 ± 70 5 2 + 540 ± 40 p 1, 3, 5, 6 4.35 ± 30 2.86 ± 70 3 2 - 340 ± 40 p 1, 3, 5, 6 5.12 ± 80 (3.63 ± 100) ( 5 2 - ) < 220 p 5 5.91 ± 30 4.42 ± 70 ( 5 2 - ) p 3, 5, 6 6.57 ± 100 5.08 ± 120 ( 3 2 - ) 100 ± 60 p 3, 6 1

  19. Table

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

    6.13 from (1993TI07): Energy Levels of 16 O a E x (MeV ± keV) J π ; T K π Γ c.m. or τ m (keV) Decay Reactions 0 0 + ; 0 stable 5, 7, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 24, 30, 32, 33, 34, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82 6.0494 ± 1.0 0 + ; 0 0 + τ m = 96 ± 7 psec π 5, 7, 11, 12, 13, 15, 17, 19, 21, 23, 30, 32, 33, 34, 38, 39, 43, 44,

  20. Table

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

    transitions in A 18-19 nuclei a Nucleus E xi E xf J i J f b Mult. S (MeV) (eV) (W.u.) 18 O c 1.98 0 2 + 0 + (2.35 0.06) 10 -4 E2 3.32 ...

  1. Table

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

    - 17 a Nucleus E xi E xf J i (T i ) J f (T f ) (eV) Branching ratio Mult. S (W.u.) (MeV) (%) 16 N b 0.12 0 0 - (1) 2 - (1) (8.7 0.1) 10 -11 100 E2...

  2. Table

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

    transitions in A 5 - 10 a Nucleus E xi E xf (MeV) J i J f b (eV) Mult. S (W.u.) 5 He 16.75 0 3 2 + 3 2 - 2.1 0.4 E1 (2.3 0.4) 10 -3 5 Li...

  3. Table

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

    transitions in A 11 - 12 a Nucleus E xi E xf J i J f b Mult. S (MeV) (eV) (W.u.) 11 Be 0.32 0 1 2 - 1 2 + (3.97 0.36) 10 -3 E1 0.360...

  4. Table

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

    transitions in A 20 nuclei a Nucleus E xi E xf J i J f b Mult. S (MeV) (eV) (W.u.) 20 O c 1.67 0 2 + 0 + (6.28 0.24) 10 -5 E2 1.80 ...

  5. Table

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

    transitions in A 5 - 7 Nucleus E xi E xf J i J f a (eV) Mult. S (W.u.) b (MeV) 5 He 16.84 0 3 2 + 3 2 - 2.1 0.4 E1 (2.2 0.4) 10 -3...

  6. Table

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

    in A 13 - 15 a Nucleus E xi E xf J i (T i ) J i (T f ) Mult. S (MeV) (eV) (W.u.) 13 C b 3.09 0 1 2 + 1 2 - 0.43 0.04 E1 (3.9 0.4) ...

  7. Table

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

    transitions in A 18 - 20 a Nucleus E xi E xf J i J f b Mult. S (MeV) (eV) (W.u.) 18 O c 1.98 0 2 + 0 + (2.35 0.06) 10 -4 E2 3.32 ...

  8. Table

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

    electromagnetic transitions in A 11 Nucleus E xi E xf J i J f Mult. W (MeV) (eV) (W.u.) 11 Be 0.32 0 1 2 - 1 2 + (3.97 0.35) 10 -3...

  9. Table

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

    5.4 from (1991AJ01): Energy levels of 15 N a E x J ; T m or Decay Reactions (MeV keV) c.m. (keV) 0 1 2 - ; 1 2 - stable 3, 4, 5, 6, 13, 14, 16, 17, 18, 19, 20, 24, 25,...

  10. Table

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

    1.0 fs 5, 7, 9, 14, 15, 19, 20, 23, 24, 25 5.2409 0.3 5 2 + 3.25 0.30 ps 4, 5, 6, 7, 9, 14, 15, 18, 19, 20, 23, 24, 25, 27 g +0.248 0.026 6.1763 1.7 3 2 -...

  11. 1999 Commercial Buildings Energy Consumption Survey Detailed Tables

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

    Consumption and Expenditures Tables Table C1. Total Energy Consumption by Major Fuel ............................................... 124 Table C2. Total Energy Expenditures by Major Fuel................................................ 130 Table C3. Consumption for Sum of Major Fuels ...................................................... 135 Table C4. Expenditures for Sum of Major Fuels....................................................... 140 Table C5. Consumption and Gross Energy Intensity by

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

    SciTech Connect (OSTI)

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

    2014-05-01

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

  13. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

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

    1994-09-01

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

  14. Table-top job analysis

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

    The purpose of this Handbook is to establish general training program guidelines for training personnel in developing training for operation, maintenance, and technical support personnel at Department of Energy (DOE) nuclear facilities. TTJA is not the only method of job analysis; however, when conducted properly TTJA can be cost effective, efficient, and self-validating, and represents an effective method of defining job requirements. The table-top job analysis is suggested in the DOE Training Accreditation Program manuals as an acceptable alternative to traditional methods of analyzing job requirements. DOE 5480-20A strongly endorses and recommends it as the preferred method for analyzing jobs for positions addressed by the Order.

  15. Microsoft Word - table_15.doc

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

    0 Table 15. Consumption of natural gas by state, 2010-2014 (million cubic feet) a Lease fuel quantities were estimated by assuming that the proportions of onsystem production used as lease fuel by respondents to the Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition," were the same as the proportions of gross withdrawals as reported on Form EIA-895, "Annual Quantity and Value of Natural Gas Production Report," used as lease by all operators.

  16. Microsoft Word - table_21.doc

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

    9 Table 21. Number of natural gas commercial consumers by type of service and state, 2013-2014 R Revised data. Note: Totals may not equal sum of components due to independent rounding. Source: Energy Information Administration (EIA), Form EIA-176, "Annual Report of Natural and Supplemental Gas Supply and Disposition." Please see the cautionary note regarding the number of residential and commercial customers located on the second page of Appendix A of this report. Alabama 67,006 130

  17. Comparison Table of Department of Energy Mentor-Protege Program...

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

    ... report to DOE HQ Semi-annually and final report to DOE HQ Semi-annually and final report ... Colleges and Universities and other minority institutions of higher learning and ...

  18. Environmental Regulatory Update Table, November 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-12-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  19. Environmental Regulatory Update Table, October 1990

    SciTech Connect (OSTI)

    Houlberg, L.M.; Noghrei-Nikbakht, P.A.; Salk, M.S.

    1990-11-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  20. Environmental Regulatory Update Table, December 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1992-01-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  1. Environmental Regulatory Update Table, October 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-11-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  2. Environmental Regulatory Update Table, September 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-10-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  3. Environmental Regulatory Update Table, August 1991

    SciTech Connect (OSTI)

    Houlberg, L.M., Hawkins, G.T.; Salk, M.S.

    1991-09-01

    This Environmental Regulatory Update Table (August 1991) provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  4. Environmental regulatory update table, July 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-08-01

    This Environmental Regulatory Update Table (July 1991) provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  5. Community Leaders Round Table | Argonne National Laboratory

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

    Community Leaders Round Table The Round Table consists of citizens with regional constituencies, including elected officials on the village, city, township, county and state levels; leaders of school districts, environmental boards and other agencies; and officers of labor unions and home owners associations. The Argonne National Laboratory/U.S. Department of Energy Community Leaders Round Table provides an informal and convenient forum for sharing information about Argonne plans and activities

  6. Environmental Regulatory Update Table, December 1989

    SciTech Connect (OSTI)

    Houlbert, L.M.; Langston, M.E. ); Nikbakht, A.; Salk, M.S. )

    1990-01-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  7. Environmental regulatory update table, March 1989

    SciTech Connect (OSTI)

    Houlberg, L.; Langston, M.E.; Nikbakht, A.; Salk, M.S.

    1989-04-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  8. Environmental Regulatory Update Table, April 1989

    SciTech Connect (OSTI)

    Houlberg, L.; Langston, M.E.; Nikbakht, A.; Salk, M.S.

    1989-05-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  9. 1995 CECS C&E Tables

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

    15. Season of Peak Electricity Demand, Number of Buildings and Floorspace, 1995 Table 16. Electricity Consumption and Conditional Energy Intensity by Season of Peak Demand, 1995...

  10. table7.9_02.xls

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

    ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ... example, LPG and residual and distillate fuel oil) purchased, and associated ...

  11. 1995 CECS C&E Tables

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

    reported for fewer than 20 buildings. Notes: * To obtain the RSE percentage for any table cell, multiply the corresponding RSE column and RSE row factors. * See Glossary for...

  12. TABLES1.CHP:Corel VENTURA

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

    Energy Information AdministrationPetroleum Supply Monthly, September 2004 2 Table S1. Crude Oil and Petroleum Products Overview, 1988 - Present (Continued) (Thousand Barrels...

  13. TABLE11.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    (Thousand Barrels) Table 11. PAD District II-Year-to-Date Supply, Disposition, and Ending Stocks of Crude Oil and Petroleum January-July 2004 Products, Crude Oil...

  14. TABLE15.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    Table 15. PAD District III-Year-to-Date Supply, Disposition, and Ending Stocks of Crude Oil and Petroleum (Thousand Barrels) January-July 2004 Products, Crude Oil...

  15. TABLE19.CHP:Corel VENTURA

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

    Table 19. PAD District IV-Year-to-Date Supply, Disposition, and Ending Stocks of Crude Oil and Petroleum (Thousand Barrels) January-July 2004 Products, Crude Oil...

  16. TableHC2.12.xls

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

    ... Table HC7.12 Home Electronics Usage Indicators by Household Income, 2005 Below Poverty ... Below Poverty Line Eligible for Federal Assistance 1 2005 Household Income Housing Units ...

  17. TableHC7.3.xls

    Gasoline and Diesel Fuel Update (EIA)

    Income Relative to Poverty Line Below 100 Percent...... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More Table HC7.3 Household ...

  18. TABLE53.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    Table 53. Movements of Crude Oil and Petroleum Products by Pipeline, Tanker, and Barge Between July 2004 Crude Oil ... 0 383 0...

  19. TABLE54.CHP:Corel VENTURA

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

    Administration (EIA) Forms EIA-812, "Monthly Product Pipeline Report," and EIA-813, Monthly Crude Oil Report." Table 54. Movements of Crude Oil and Petroleum Products by Pipeline...

  20. Health Care Buildings : Basic Characteristics Tables

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

    Basic Characteristics Tables Buildings and Size Data by Basic Characteristics for Health Care Buildings Number of Buildings (thousand) Percent of Buildings Floorspace (million...

  1. TABLE34.CHP:Corel VENTURA

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

    ... Total ...... 1,247 24,793 3,065 177 0 0 177 Table 34. Movements of Crude Oil and Petroleum Products by Tanker ...

  2. TABLE35.CHP:Corel VENTURA

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

    ... Table 35. Net Movements of Crude Oil and Petroleum Products by Pipeline, Tanker, and Barge Between PAD Districts, PAD District I PAD District II Commodity Receipts Shipments Net ...

  3. FY 2005 Control Table by Appropriation

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

    Appropriation (dollars in thousands - OMB Scoring) Table of Contents Summary...................................................................................................... 1 Mandatory Funding....................................................................................... 3 Energy Supply.............................................................................................. 4 Non-Defense site acceleration completion................................................... 5 Uranium

  4. FY 2005 Control Table by Organization

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

    Organization (dollars in thousands - OMB Scoring) Table of Contents Summary...................................................................................................... 1 Mandatory Funding....................................................................................... 2 National Nuclear Security Administration..................................................... 3 Energy Efficiency and Renewable Energy.................................................... 4 Electric Transmission

  5. 1995 CECS C&E Tables

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

    (3 pages, 20 kb) CONTENTS PAGES Table 19. Distribution of Peak Watts per Square Foot and Load Factors, 1995 These data are from the 1995 Commercial Buildings Energy...

  6. Continuous Learning Points Credit Assignment Table | Department...

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

    PDF icon Microsoft Word - CLPCreditAssignmentTable More Documents & Publications PMCDP Curriculum Learning Map Microsoft Word - AL2006-07.doc PMCDP Certification and Equivalency ...

  7. Public Notice Applicability Table | Open Energy Information

    Open Energy Info (EERE)

    http:crossref.org Citation Retrieved from "http:en.openei.orgwindex.php?titlePublicNoticeApplicabilityTable&oldid792160" Feedback Contact needs updating Image...

  8. Action Codes Table | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    Action Codes Table Action codes *U.S.: **IAEA: A - Shipper's original data A B - Receiver's data accepting shipper's weights without measurement W C - Shipper's adjustment or ...

  9. Summary Statistics Table 1. Crude Oil Prices

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

    from Table 24. Refiner acquisition costs -- Energy Information Administration, Form FEA-P110-M-1, "Refiners' Monthly Cost Allocation Report," January 1978 through June 1978;...

  10. TABLE15.CHP:Corel VENTURA

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

    5. Natural Gas Plant Net Production and Stocks of Petroleum Products by PAD and Refining ... Report." 170 Table 15. Natural Gas Plant Net Production and Stocks of Petroleum ...

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

    SciTech Connect (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 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.

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

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

    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

  13. Microsoft Word - table_03.doc

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

    9 Table 3. Gross withdrawals and marketed production of natural gas by state and the Gulf of Mexico, 2010-2014 (million cubic feet) 2010 Total 13,247,498 5,834,703 1,916,762 5,817,122 26,816,085 3,431,587 165,928 836,698 22,381,873 1,066,366 21,315,507 2011 Total 12,291,070 5,907,919 1,779,055 8,500,983 28,479,026 3,365,313 209,439 867,922 24,036,352 1,134,473 22,901,879 2012 Total 12,504,227 4,965,833 1,539,395 10,532,858 29,542,313 3,277,588 212,848 768,598 25,283,278 1,250,012 24,033,266 2013

  14. Microsoft Word - table_08.doc

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

    5 Table 8. Summary of U.S. natural gas imports, 2010-2014 Imports Volume (million cubic feet) Pipeline Canada a 3,279,752 3,117,081 2,962,827 2,785,427 2,634,375 Mexico 29,995 2,672 314 1,069 1,426 Total Pipeline Imports 3,309,747 3,119,753 2,963,140 2,786,496 2,635,801 LNG by Truck Canada 0 0 0 555 132 LNG by Vessel Egypt 72,990 35,120 2,811 0 0 Nigeria 41,733 2,362 0 2,590 0 Norway 26,014 15,175 6,212 5,627 5,616 Peru 16,045 16,620 0 0 0 Qatar 45,583 90,972 33,823 7,320 0 Trinidad/Tobago

  15. Microsoft Word - table_09.doc

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

    0 Table 10. Summary of U.S. natural gas exports, 2010-2014 Exports Volume (million cubic feet) Pipeline Canada 738,745 936,993 970,729 911,007 769,258 Mexico 333,251 498,657 619,802 658,368 728,513 Total Pipeline Exports 1,071,997 1,435,649 1,590,531 1,569,375 1,497,771 LNG Exports By Vessel China 0 1,127 0 0 0 Japan 30,100 15,271 9,342 0 13,310 By Truck Canada 0 0 2 71 99 Mexico 208 236 153 128 181 Re-Exports By Vessel Brazil 3,279 11,049 8,142 0 2,664 Chile 0 2,910 0 0 0 China 0 6,201 0 0 0

  16. Microsoft Word - table_20.doc

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

    8 Table 20. Number of natural gas residential consumers by type of service and state, 2013-2014 Alabama 765,957 0 765,957 769,418 0 769,418 Alaska 124,411 0 124,411 126,416 0 126,416 Arizona 1,171,997 6 1,172,003 1,186,788 6 1,186,794 Arkansas R 549,764 0 R 549,764 549,034 0 549,034 California 10,471,814 283,094 10,754,908 10,372,973 408,747 10,781,720 Colorado 1,672,307 5 1,672,312 1,690,576 5 1,690,581 Connecticut 512,110 1,382 513,492 521,460 1,198 522,658 Delaware 155,627 0 155,627 158,502 0

  17. Microsoft Word - table_22.doc

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

    0 Table 22. Number of natural gas industrial consumers by type of service and state, 2013-2014 Alabama 2,876 267 3,143 2,973 271 3,244 Alaska 2 1 3 1 0 1 Arizona 257 126 383 256 130 386 Arkansas 513 507 1,020 531 478 1,009 California 32,662 5,334 37,996 32,266 5,282 37,548 Colorado 946 6,347 7,293 986 6,837 7,823 Connecticut 3,360 1,094 4,454 3,340 877 4,217 Delaware 28 110 138 28 113 141 Florida 166 362 528 165 355 520 Georgia 984 1,258 2,242 887 1,594 2,481 Hawaii 22 0 22 23 0 23 Idaho 109 R

  18. Microsoft Word - table_25.doc

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

    72 Table 25. Average price of natural gas delivered to residential and commercial sector consumers by local distribution and marketers in selected states, 2013-2014 (dollars per thousand cubic feet) Georgia 11.86 15.04 14.60 13.9 12.38 14.79 14.45 14.0 New York 12.24 13.07 12.49 70.3 12.15 13.46 12.54 70.5 Ohio 9.20 9.52 9.46 19.8 10.15 10.16 10.16 20.0 Residential State 2013 2014 Local Distribution Company Average Price a Marketer Average Price b Combined Average Price c Percent Sold by Local

  19. Microsoft Word - table_26.doc

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

    7 Table 27. Percent distribution of natural gas supply and disposition by state, 2014 Alabama 0.7 1.6 Alaska 1.3 1.6 Arizona < 0.5 Arkansas 4.4 1.1 California 0.9 8.2 Colorado 6.0 2.1 Connecticut -- 0.7 Delaware -- 0.3 District of Columbia -- 0.2 Florida < 1.0 Georgia -- 2.0 Gulf of Mexico 4.6 0.5 Hawaii -- < Idaho -- 0.4 Illinois < 5.7 Indiana < 3.4 Iowa -- 1.7 Kansas 1.0 1.4 Kentucky 0.3 1.2 Louisiana 7.6 6.3 Maine -- 0.2 Maryland < 1.0 Massachusetts -- 1.5 Michigan 0.4 4.0

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

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

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

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

  2. 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 ...

  3. Supplemental Tables to the Annual Energy Outlook

    Reports and Publications (EIA)

    2015-01-01

    The Annual Energy Outlook (AEO) Supplemental tables were generated for the reference case of the AEO using the National Energy Modeling System, a computer-based model which produces annual projections of energy markets. Most of the tables were not published in the AEO, but contain regional and other more detailed projections underlying the AEO projections.

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

    SciTech Connect (OSTI)

    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.

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

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

    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 the National Oceanic and Atmospheric Administration (NOAA), AWS Truepower, and WindLogics in the Great Plains and Western Texas, demonstrated that wind power forecasts can be improved substantially using data collected from tall towers, remote sensors, and other devices, and incorporated into improved forecasting models

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

    Open Energy Info (EERE)

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

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

    SciTech Connect (OSTI)

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

    2010-04-01

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

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

    SciTech Connect (OSTI)

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

    2010-04-15

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

  9. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

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

  10. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    1996-08-01

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

  11. 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 QER - Comment of Edison Electric Institute (EEI) 2

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

    SciTech Connect (OSTI)

    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.

  13. Comparison of Clean Diesel Buses to CNG Buses

    Office of Scientific and Technical Information (OSTI)

    ... APPENDIX B - EMISSIONS TABLES APPENDIX C - DISCUSSION OF OUTLIER CNG TEST RESULTS APPENDIX ... Appendix A Figure 2 Emissions Test Cycles Comparison of Clean Diesel Buses to CNG Buses 1 ...

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

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

  15. Table 26. Natural gas home customer-weighted heating degree...

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

    6:14:01 PM Table 26. Natural gas home customer-weighted heating degree days MonthYear... Table 26 Created on: 4262016 6:14:07 PM Table 26. Natural gas home customer-weighted ...

  16. 1999 Commercial Building Characteristics--Detailed Tables--Size...

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

    Complete Set of 1999 CBECS Detailed Tables Detailed Tables- of Buildings Table B6. Building Size, Number of Buildings b6.pdf (PDF file), b6.xls (Excel spreadsheet file), b6.txt...

  17. 1999 Commercial Buildings Characteristics--Detailed Tables--Conservati...

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

    as rowstubs in most detailed tables. Total buildings, total floorspace, and average building size for these categories are shown in Table B1. The PDF and spreadsheet data tables...

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

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01

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

  19. Microsoft Word - table_05.doc

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

    3 Table 5. Number of producing gas wells by state and the Gulf of Mexico, December 31, 2010-2014 Alabama 7,026 7,063 6,327 R 6,165 6,118 Alaska 269 277 185 R 159 170 Arizona 5 5 5 5 5 Arkansas 7,397 8,388 8,538 R 9,843 10,150 California 1,580 1,308 1,423 R 1,335 1,118 Colorado 28,813 30,101 32,000 R 32,468 38,346 Gulf of Mexico 1,852 1,559 1,474 R 1,146 1,400 Illinois 50 40 40 R 34 36 Indiana 620 914 819 R 921 895 Kansas 22,145 25,758 24,697 R 23,792 24,354 Kentucky 17,670 14,632 17,936 R 19,494

  20. Microsoft Word - table_24.doc

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

    Table 24. Average price of natural gas delivered to consumers by state and sector, 2014 (dollars per thousand cubic feet) Alabama 14.59 100.0 11.92 78.4 5.49 23.3 4.74 Alaska 9.11 100.0 8.30 94.5 7.97 100.0 5.06 Arizona 17.20 100.0 10.34 84.4 7.52 12.8 5.30 Arkansas 10.39 100.0 7.88 45.5 6.99 1.8 W California 11.51 94.8 9.05 48.4 7.65 3.7 5.23 Colorado 8.89 100.0 8.15 94.5 6.84 7.7 5.49 Connecticut 14.13 95.9 10.24 67.2 8.07 39.4 6.82 Delaware 13.21 100.0 11.42 46.2 10.95 0.3 W District of

  1. Compiler Comparisons

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

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

  2. 1999 CBECS Summary Table for All Building Activities

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

    Tables 1999 Commercial Buildings Consumption Survey SUMMARY TABLES FOR ALL PRINCIPAL BUILDING ACTIVITIES Number of Buildings (thousand) Floorspace (million square feet) Square...

  3. Minimum Efficiency Requirements Tables for Heating and Cooling...

    Energy Savers [EERE]

    The Federal Energy Management Program (FEMP) created tables that mirror American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1-2013 tables, which ...

  4. 2008 Annual Merit Review Results Summary - Cover and Table of...

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

    Cover and Table of Contents 2008 Annual Merit Review Results Summary - Cover and Table of Contents DOE Vehicle Technologies Annual Merit Review 2008meritreviewcontents.pdf ...

  5. ARM: RPH stabilized table control data (Dataset) | Data Explorer

    Office of Scientific and Technical Information (OSTI)

    RPH stabilized table control data Title: ARM: RPH stabilized table control data RPH ... Sponsoring Org: USDOE Office of Science (SC), Biological and Environmental Research (BER) ...

  6. Energy Information Administration - Energy Efficiency-Table 3...

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

    Energy Efficiency > Iron and Steel Manufacturing Energy, 1998 and 2002 > Table 3 Page Last Modified: June 2010 Table 3. Offsite-Produced Fuel Consumption, 1998, 2002, and 2006...

  7. Table I: Technical Targets for Catalyst Coated Membranes (CCMs...

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

    Table III: Technical Targets for Catalyst Coated Membranes (CCMs): Stationary R&D Plan for the High Temperature Membrane Working Group Table IV: Technical Targets for Membranes: ...

  8. Table III: Technical Targets for Catalyst Coated Membranes (CCMs...

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

    More Documents & Publications R&D Plan for the High Temperature Membrane Working Group Table I: Technical Targets for Catalyst Coated Membranes (CCMs): Automotive Table IV: ...

  9. EIA - Annual Energy Outlook (AEO) 2013 Data Tables

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

    Table 55.2. Electric Power Projections by Electricity Market Module Region - Florida Reliability Coordinating Council XLS Table 55.3. Electric Power Projections by Electricity...

  10. Energy.gov Data Tables in Content Management System | Department...

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

    Data Tables in Content Management System Energy.gov Data Tables in Content Management System For Office of Energy Efficiency and Renewable Energy (EERE) websites, follow these...

  11. Headquarters Facilities Master Security Plan- Table of Contents

    Office of Energy Efficiency and Renewable Energy (EERE)

    2016 Headquarters Facilities Master Security Plan - Table of Contents Table of Contents for the 2016 Headquarters Facilities Master Security Plan (HQFMSP).

  12. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    of table. 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State 262 Energy Information Administration Petroleum Marketing Annual 1997 Table 43....

  13. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    of table. 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State 262 Energy Information Administration Petroleum Marketing Annual 1996 Table 43....

  14. Petroleum Products Table 31. Motor Gasoline Prices by Grade...

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

    at end of table. 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 56 Energy Information Administration Petroleum Marketing Annual 1996 Table 31. Motor...

  15. Forecasting hotspots using predictive visual analytics approach

    SciTech Connect (OSTI)

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

    2014-12-30

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

  16. table2.4_02.xls

    Gasoline and Diesel Fuel Update (EIA)

    ... products (e.g., crude oil converted to residual and distillate fuel oils) are excluded. ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ...

  17. table8.2_02.xls

    Gasoline and Diesel Fuel Update (EIA)

    ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ... Oxy - Fuel Firing Waste Heat Recovery Adjustable - Speed Motors 389 3,468 309 1,507 2,200 ...

  18. table1.5_02.xls

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

    ... It is the total amount of first use of energy for all (fuel and nonfuel) purposes. NFNo ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ...

  19. TableHC7.8.xls

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

    ... Table HC7.8 Water Heating Characteristics by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 Million U.S. Housing Units 80,000 or ...

  20. TableHC2.8.xls

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

    ... Table HC7.8 Water Heating Characteristics by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 Million U.S. Housing Units 80,000 or ...

  1. TableHC2.13.xls

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

    ... Table HC7.13 Lighting Usage Indicators by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 Million U.S. Housing Units 2005 ...

  2. TableHC7.13.xls

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

    ... Table HC7.13 Lighting Usage Indicators by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 Million U.S. Housing Units 2005 ...

  3. Microsoft Word - table_A2.doc

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

    195 19 4 Figure A1. Natural gas processing plant capacity in the United States, 2014 2014 Table A2. Natural gas processing plant capacity, by state, 2014 (million cubic feet per ...

  4. Table of Contents for Desk Guide

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

    September, 2014 U. S. Department of Energy - Real Estate Desk Guide Revised 2014 Real Estate Desk Guide Table of Contents Chapter 1-- Purpose of Desk Guide............................................................................... 1 Chapter 2-- Introduction ................................................................................................. 3 Chapter 3-- Planning Policy ........................................................................................... 9 Chapter 4-- Real

  5. Table 3.3 Fuel Consumption, 2010;

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

    3 Fuel Consumption, 2010; Level: National and Regional Data; Row: Values of Shipments and ... Next MECS will be fielded in 2015 Table 3.3 Fuel Consumption, 2010; Level: National and ...

  6. Table 3.1 Fuel Consumption, 2010;

    Gasoline and Diesel Fuel Update (EIA)

    1 Fuel Consumption, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: ... Next MECS will be fielded in 2015 Table 3.1 Fuel Consumption, 2010; Level: National and ...

  7. Table 3.2 Fuel Consumption, 2010;

    Gasoline and Diesel Fuel Update (EIA)

    2 Fuel Consumption, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: ... Next MECS will be fielded in 2015 Table 3.2 Fuel Consumption, 2010; Level: National and ...

  8. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

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

    2011-02-23

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

  9. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

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

    2014-11-13

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

  10. Global disease monitoring and forecasting with Wikipedia

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

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

    2014-11-13

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

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

    SciTech Connect (OSTI)

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

    2015-08-05

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

  12. FY 2015 Statistical Table by Appropriation

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

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) Statistical Table by Appropriation Page 1 FY 2015 Congressional Request FY 2013 FY 2014 FY 2014 FY 2014 FY 2015 Current Enacted Adjustment Current Congressional Approp. Approp. Approp. Request Discretionary Summary By Appropriation Energy And Water Development And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy............................... 1,691,757 1,900,641 ---- 1,900,641

  13. FY 2015 Statistical Table by Organization

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

    of Energy FY 2015 Statistical Table by Organization (dollars in thousands - OMB Scoring) Statistical Table by Organization Page 1 FY 2015 Congressional Request FY 2013 FY 2014 FY 2014 FY 2014 FY 2015 Current Enacted Adjustments Current Congressional Approp. Approp. Approp. Request Discretionary Summary By Organization National Nuclear Security Administration Weapons Activities........................................................................... 6,966,855 7,781,000 ---- 7,781,000 8,314,902

  14. FY 2015 Summary Control Table by Appropriation

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

    Summary Control Table by Appropriation (dollars in thousands - OMB Scoring) Summary Control Table by Appropriation Page 1 FY 2015 Congressional Request FY 2013 FY 2014 FY 2014 FY 2014 FY 2015 Current Enacted Adjustment Current Congressional Approp. Approp. Approp. Request Discretionary Summary By Appropriation Energy And Water Development And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy................................... 1,691,757 1,900,641 ----

  15. Microsoft Word - Permit Table of Contents 2-2014 (2).docx

    Office of Environmental Management (EM)

    Table of Contents February 2014 WIPP Permit - Table of Contents PART 1 - GENERAL PERMIT CONDITIONS ... 1...

  16. Qualified Energy Conservation Bond State-by-State Summary Tables

    Broader source: Energy.gov [DOE]

    Provides a list of qualified energy conservation bond state summary tables. Author: Energy Programs Consortium

  17. Product Guide Product Guide Volumes Category Prices Table Crude...

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

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -- 49 Product Guide Volumes Category Prices Table Energy Information Administration Petroleum Marketing...

  18. Product Guide Product Guide Volumes Category Prices Table Crude...

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

    suppliers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -- 49 Product Guide Volumes Category Prices Table Energy Information Administration Petroleum...

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  20. 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

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

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

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

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

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

    Energy Savers [EERE]

    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 ...

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

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

  5. Roel Neggers European Centre for Medium-range Weather Forecasts

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

    transition from shallow to deep convection using a dual mass flux boundary layer scheme Roel Neggers European Centre for Medium-range Weather Forecasts Introduction " " % % &...

  6. 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. ...

  7. 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, ...

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

    SciTech Connect (OSTI)

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

    2015-12-08

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

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  10. New Forecasting Tools Enhance Wind Energy Integration In Idaho...

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

    ... RIT forecasting is saving costs and improving operational practices for IPC and helping integrate wind power more efficiently and cost effectively. Figure 3 shows how the ...

  11. A Review of Variable Generation Forecasting in the West: July...

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

    ... Cost Assignment - Only a few respondents partly or fully recover forecasting costs from variable generators. Many simply absorb the costs, possibly viewing them as relatively ...

  12. ANL Software Improves Wind Power Forecasting | Department of...

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

    ... The licensing arrangement helps to facilitate transfer of the statistical learning algorithms developed in the project to industry use. A leading forecast provider in the United ...

  13. Selected papers on fuel forecasting and analysis

    SciTech Connect (OSTI)

    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.

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

    SciTech Connect (OSTI)

    Woolsey, Lauren N.; Cranmer, Steven R.

    2014-06-01

    Forecasting models of the solar wind often rely on simple parameterizations of the magnetic field that ignore the effects of the full magnetic field geometry. In this paper, we present the results of two solar wind prediction models that consider the full magnetic field profile and include the effects of 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.

  15. Tree_Select_Probes, Build_Hybr_Index, and Build_Hybr_Table

    Energy Science and Technology Software Center (OSTI)

    2006-08-01

    Tree_Select_Probes: This program is part of a 3 program package that replaces the older probe selection software. The purpose of the package is to generate probes specific for the group of sequences that belong to a given phylogenetic node. This software employs modified proble selection algorithm that improves speed of calculations in comparison with older software. For each node of the input tree, this program selects probes that are positive for all sequences that belongmore » to this node and negative for all that doesn't. For speed it uses probe database created by build_hybr_index program and hybridization table database created by build_hyper_table program. As a result of calculation, the program prints lists for each node from the tree. Input file formats: FASTA for sequences database, internal INDEX for probe database, internal table for hybridization database. Output file format: text file. Build_Hybr_Index: This program is part of a 3 program package that replaces the older probe selection software. The purpose of the package is to generate probles specific for the group of sequences that belong to a given phylogenetic node. This software employs modified probe selection algorithm that improves speed of calculations in comparison with older software. This program creates database of potential probes based on given sequence database, reducing it in the way so it doesn't contain repeats or substrings with meta-nucleotides. Input file format: FASTA. Output file format: itnernal INDEX file. Build_Hybr_Table: This program is part of a 3-program package that replaces the older probe selection software. The purpose of the package is to generate probles specific for the group of sequences that belong to a given phylogenetic node. This software employes modified probe selection algorithm that improves speed of calculations in comparison with older software. For each node of he input tree, this program selects probles that are positive for all sequences that

  16. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01

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

  17. SimTable key tool for preparing, responding to wildfire

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

    SimTable key tool for preparing, responding to wildfire SimTable key tool for preparing, responding to wildfire Camera tracks movement and objects and project them onto a sand table. May 30, 2012 SimTable: Stephen Guerin (L) and Chip Garner (R) with SimTable, a Santa Fe company helping firefighters model and predict where a fire is most likely to spread, received support for their business through Lab economic development programs: VAF, NMSBA, Springboard. SimTable: Stephen Guerin (L) and Chip

  18. Technical analysis in short-term uranium price forecasting

    SciTech Connect (OSTI)

    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.

  19. FY 2007 Control Table by Appropriation

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

    Control Table by Appropriation (dollars in thousands - OMB Scoring) FY 2005 FY 2006 FY 2007 Current Current Congressional Approp. Approp. Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy supply and Conservation......................................... 1,801,815 1,812,627 1,923,361 +110,734 +6.1% Fossil energy programs Clean coal technology.......................................................

  20. FY 2008 Control Table by Appriopriation

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

    Control Table by Appropriation (dollars in thousands - OMB Scoring) FY 2006 FY 2007 FY 2008 Current Congressional Congressional Approp. Request Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy supply and Conservation..................................... 1,812,397 1,923,361 2,187,943 +264,582 +13.8% Fossil energy programs Clean coal technology...................................................

  1. FY 2011 Control Table by Organization

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

    1 Summary Control Table by Organization (dollars in thousands - OMB Scoring) FY 2009 FY 2009 FY 2010 FY 2011 Current Current Current Congressional Approp. Recovery Approp. Request $ % Discretionary Summary By Organization National Security Weapons................................................................................................. 6,410,000 0 6,384,431 7,008,835 +624,404 +9.8% Defense Nuclear Nonproliferation........................................................... 1,545,071 0

  2. FY 2013 Control Table by Organization

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

    3 Summary Control Table by Organization (dollars in thousands - OMB Scoring) FY 2011 FY 2012 FY 2013 Current Enacted Congressional Approp. Approp. * Request $ % Discretionary Summary By Organization Department Of Energy By Organization National Nuclear Security Administration Weapons Activities.............................................................................. 6,865,775 7,214,120 7,577,341 +363,221 +5.0% Defense Nuclear

  3. FY 2015 Summary Control Table by Organization

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

    5 Summary Control Table by Organization (dollars in thousands - OMB Scoring) Summary Control by Organization Page 1 FY 2015 Congressional Request FY 2013 FY 2014 FY 2014 FY 2014 FY 2015 Current Enacted Adjustments Current Congressional Approp. Approp. Approp. Request Discretionary Summary By Organization Department Of Energy By Organization National Nuclear Security Administration Weapons Activities............................................................................. 6,966,855 7,781,000

  4. Table of Contents for Desk Guide

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

    May, 2013 U. S. Department of Energy - Real Estate Desk Guide Revised 2013 Real Estate Desk Guide Table of Contents Chapter 1-- Purpose of Desk Guide ........................................................................ 1 Chapter 2-- Introduction ......................................................................................... 3 Chapter 3-- Planning Policy .................................................................................... 7 Chapter 4-- Real Estate Function

  5. Help:Tables | Open Energy Information

    Open Energy Info (EERE)

    on tables 3.2 Attributes on cells 3.3 Attributes on rows 3.4 HTML colspan and rowspan 3.5 With HTML attributes and CSS styles 4 Caveats 4.1 Negative numbers 4.2 CSS vs Attributes...

  6. 3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information

    Open Energy Info (EERE)

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

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

    Reports and Publications (EIA)

    2010-01-01

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

  8. EIA Energy Efficiency-Table 1a. Table 1a. Consumption of Site...

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

    a Page Last Modified: May 2010 Table 1a. Consumption of Energy (Site Energy) for All Purposes (First Use) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey...

  9. Incorporating Forecast Uncertainty in Utility Control Center

    SciTech Connect (OSTI)

    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)

  10. CBECS - Buildings and Energy in the 1980's, Table Titles

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

    for primary or site energy ("p" or "s"). For example, Table R8.90p, shows primary energy data for residential buildings for the 1990 survey year. The tables are arranged into...

  11. Appendix H biomonitoring data table H-1.xls

    Office of Legacy Management (LM)

    This page intentionally left blank Table H-1: Biomonitoring Sediment and Surface Water ... Surface Water P-S1 P-S2 P-S3 Table H-1: Biomonitoring Sediment and Surface Water Data a ...

  12. DOE ZERH Second Leading Builder Round Table Meeting Report |...

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

    DOE ZERH Second Leading Builder Round Table Meeting Report On October 23rd-24th, 2014, the ZERH program held its Second Leading Production Builder Round Table Meeting in Suwanee, ...

  13. Widget:UtilityRateEntryHelperTable | Open Energy Information

    Open Energy Info (EERE)

    UtilityRateEntryHelperTable Jump to: navigation, search This widget displays the utility rate database form. For example: Widget:UtilityRateEntryHelperTable Retrieved from...

  14. Radioactive decay data tables (Technical Report) | SciTech Connect

    Office of Scientific and Technical Information (OSTI)

    Radioactive decay data tables Citation Details In-Document Search Title: Radioactive decay data tables You are accessing a document from the Department of Energy's (DOE) SciTech ...

  15. Table IV: Technical Targets for Membranes: Stationary | Department of

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

    Energy IV: Technical Targets for Membranes: Stationary Table IV: Technical Targets for Membranes: Stationary "Technical targets for fuel cell membranes in stationary applications defined by the High Temperature Working Group (February 2003). " technical_targets_membr_stat.pdf (83.24 KB) More Documents & Publications Table II: Technical Targets for Membranes: Automotive Table III: Technical Targets for Catalyst Coated Membranes (CCMs): Stationary Table I: Technical Targets for

  16. Environmental Regulatory Update Table, January/February 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1992-03-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action. This table is for January/February 1992.

  17. TableHC1.1.1.xls

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

    ... Housing Unit Housing Unit Characteristics Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Household Member ...

  18. Minimum Efficiency Requirements Tables for Heating and Cooling Product

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

    Categories | Department of Energy Minimum Efficiency Requirements Tables for Heating and Cooling Product Categories Minimum Efficiency Requirements Tables for Heating and Cooling Product Categories The Federal Energy Management Program (FEMP) created tables that mirror American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1-2013 tables, which include minimum efficiency requirements for FEMP-designated and ENERGY STAR-qualified heating and cooling product

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

    SciTech Connect (OSTI)

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

    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

  20. Environmental Regulatory Update Table, January/February 1995

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Bock, R.E.; Mayer, S.J.; Salk, M.S.

    1995-03-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives impacting environmental, health, and safety management responsibilities. the table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  1. Torque/Moab vs. SLURM Comparisons

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

    Users » Torque/Moab vs. SLURM Comparisons Torque/Moab vs. SLURM Comparisons TORQUE vs. SLURM Comparison Tables Moab/Torque vs. Slurm Environment Variables Description Moab/Torque Slurm Job Id $PBS_JOBID $SLURM_JOB_ID Job Name $PBS_JOBNAME $SLURM_JOB_NAME Submit Directory $PBS_O_WORKDIR $SLURM_SUBMIT_DIR Node List $PBS_NODEFILE $SLURM_NODELIST Host submitted from $PBS_O_HOST $SLURM_SUBMIT_HOST Nodes allocated $PBS_NUM_NODES $SLURM_JOB_NUM_NODES Number cores/nodes $PBS_NUM_PPN $SLURM_CPUS_ON_NODE

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

    SciTech Connect (OSTI)

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

    2005-07-01

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

  3. AVLIS documentation overview and tables of contents

    SciTech Connect (OSTI)

    Not Available

    1984-11-15

    Three documents constitute the executive summary series in Data Package III: this document (Documentation Overview and Tables of Contents (E001)) plus the AVLIS Production Plant Executive Summary (E010) and the AVLIS Production Plant Overall Design Report (E020). They provide progressively greater detail on the key information and conclusions contained within the data package. The Executive Summary and Overall Design Report present summaries of each Data Package III document. They are intended to provide a global overview of AVLIS Production Plant deployment including program planning, project management, schedules, engineering design, production, operations, capital cost, and operating cost. The purpose of Overview and Tables of Contents is threefold: to briefly review AVLIS goals for Data Package III documentation, to present an overview of the contents of the data package, and to provide a useful guide to information contained in the numerous documents comprising the package.

  4. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

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

  5. FY 2007 Control Table by Organization

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

    Control Table by Organization (dollars in thousands - OMB Scoring) FY 2005 FY 2006 FY 2007 Current Current Congressional Approp. Approp. Request $ % Discretionary Summary By Organization National Security Weapons................................................................................. 6,625,542 6,369,597 6,407,889 +38,292 +0.6% Defense Nuclear Nonproliferation.......................................... 1,507,966 1,614,839 1,726,213 +111,374 +6.9% Naval

  6. FY 2008 Control Table by Organization

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

    Control Table by Organization (dollars in thousands - OMB Scoring) FY 2006 FY 2007 FY 2008 Current Congressional Congressional Approp. Request Request $ % Discretionary Summary By Organization National Security Weapons.............................................................................. 6,355,297 6,407,889 6,511,312 +103,423 +1.6% Defense Nuclear Nonproliferation....................................... 1,619,179 1,726,213 1,672,646 -53,567 -3.1% Naval

  7. FY 2009 Control Table by Appropriation

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

    Control Table by Appropriation (dollars in thousands - OMB Scoring) FY 2007 FY 2008 FY 2009 Current Current Congressional Op. Plan Approp. Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy.......................... -- 1,722,407 1,255,393 -467,014 -27.1% Electricity delivery and energy reliability........................... -- 138,556 134,000 -4,556 -3.3% Nuclear

  8. FY 2009 Control Table by Organization

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

    9 Control Table by Organization (dollars in thousands - OMB Scoring) FY 2007 FY 2008 FY 2009 Current Current Congressional Op. Plan Approp. Request $ % Discretionary Summary By Organization National Security Weapons................................................................................. 6,258,583 6,297,466 6,618,079 +320,613 +5.1% Defense Nuclear Nonproliferation........................................... 1,824,202 1,335,996 1,247,048 -88,948 -6.7% Naval

  9. FY 2010 Control Table by Appropriation

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

    Control Table by Appropriation (dollars in thousands - OMB Scoring) FY 2008 FY 2009 FY 2009 FY 2010 Current Current Current Congressional Approp. Approp. Recovery Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy.......................................... 1,704,112 2,178,540 16,800,000 2,318,602 +140,062 +6.4% Electricity delivery and energy

  10. FY 2010 Control Table by Organization

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

    0 Control Table by Organization (dollars in thousands - OMB Scoring) FY 2008 FY 2009 FY 2009 FY 2010 Current Current Current Congressional Approp. Approp. Recovery Request $ % Discretionary Summary By Organization National Security Weapons........................................................................................... 6,302,366 6,380,000 -- 6,384,431 +4,431 +0.1% Defense Nuclear Nonproliferation....................................................... 1,334,922 1,482,350 -- 2,136,709

  11. FY 2011 Control Table by Appropriation

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

    Summary Control Table by Appropriation (dollars in thousands - OMB Scoring) FY 2009 FY 2009 FY 2010 FY 2011 Current Current Current Congressional Approp. Recovery Approp. Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy........................................... 2,156,865 16,771,907 2,242,500 2,355,473 +112,973 +5.0% Electricity delivery and energy

  12. FY 2012 Control Table by Appropriation

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

    FY 2012 Summary Control Table by Appropriation (dollars in thousands - OMB Scoring) FY 2010 FY 2011 FY 2011 FY 2012 Current Congressional Annualized Congressional Approp. Request CR Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy....................................... 2,216,392 2,355,473 2,242,500 3,200,053 +983,661 +44.4% Electricity delivery and energy

  13. FY 2012 Control Table by Organization

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

    2 Summary Control Table by Organization (dollars in thousands - OMB Scoring) FY 2010 FY 2011 FY 2011 FY 2012 Current Congressional Annualized Congressional Approp. Request CR Request $ % Discretionary Summary By Organization Department Of Energy By Organization National Nuclear Security Administration Weapons Activities * ............................................................................. 6,386,371 7,008,835 7,008,835 7,629,716 +620,881 +8.9% Defense Nuclear Nonproliferation *

  14. FY 2013 Control Table by Appropriation

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

    Summary Control Table by Appropriation (dollars in thousands - OMB Scoring) FY 2011 FY 2012 FY 2013 Current Enacted Congressional Approp. Approp. * Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy......................................... 1,771,721 1,809,638 2,337,000 +527,362 +29.1% Electricity delivery and energy reliability..........................................

  15. FY 2017 Statistical Table by Organization

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

    Organization (dollars in thousands - OMB Scoring) Statistical Table by Organization Page 1 FY 2017 Congressional Budget Justification FY 2015 FY 2015 FY 2016 FY 2017 Enacted Current Enacted Congressional Approp. Approp. Approp. Request $ % Discretionary Summary By Organization National Nuclear Security Administration Weapons Activities................................................................................. 8,180,359 8,180,609 8,846,948 9,243,147 +396,199 +4.5% Defense Nuclear

  16. SimTable helps firefighters model and predict fire direction

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

    SimTable models and predicts fire path SimTable helps firefighters model and predict fire direction In 2009, SimTable received $100,000 from the LANS Venture Acceleration Fund to improve the user interface and seed firefighting academies with customized set ups. April 3, 2012 Stephen Guerin (L) and Chip Garner (R) with SimTable Stephen Guerin (L), and Chip Garner (R), with SimTable, a Santa Fe company helping firefighters model and predict where a fire is most likely to spread, received support

  17. Argonne Table Tennis Club Meets | Argonne National Laboratory

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

    Table Tennis Club Meets September 6, 2016 5:30PM to 8:00PM Location Building 362, Room E148 Type Social Event The Argonne Table Tennis Club meets every Tuesday and Thursday, from 5:30 to 8 p.m., in Bldg. 362, Rm. E-148. If you enjoy playing table tennis, stop by and bring your racket. Players of all skill levels, beginner, intermediate and advanced, are welcome. About Table Tennis Table tennis, also known as ping pong, is an exciting game that can be played by two or four players. It is a game

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

    Office of Energy Efficiency and Renewable Energy (EERE)

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

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

    SciTech Connect (OSTI)

    Lantz, E.; Hand, M.

    2010-05-01

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

  20. World oil inventories forecast to grow significantly in 2016...

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

    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 ...

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

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

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

    Reports and Publications (EIA)

    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.

  3. 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 ...

  4. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

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

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

    Broader source: Energy.gov [DOE]

    The U.S. Department of Energy has just published the latest edition of its biannual report, Energy Savings Forecast of Solid-State Lighting in General Illumination Applications, which models the...

  6. Value of Improved Short-Term Wind Power Forecasting

    SciTech Connect (OSTI)

    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.

  7. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

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

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

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

    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 ...

  9. Solar Trackers Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

    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....

  11. Recently released EIA report presents international forecasting data

    SciTech Connect (OSTI)

    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.

  12. New Climate Research Centers Forecast Changes and Challenges | Department

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

    of Energy Climate Research Centers Forecast Changes and Challenges New Climate Research Centers Forecast Changes and Challenges October 25, 2013 - 12:24pm Addthis This artist's rendering illustrates the full site installation, including a new aerosol observing system (far left) and a precipitation radar (far right, with 20-ft tower). The site is located near the Graciosa Island aiport terminal, hidden by the image inset. | Image courtesy of ARM Climate Research Facility. This artist's

  13. 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,

  14. Study forecasts disappearance of conifers due to climate change

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

  15. LCLS CDR Appendix A - Parameter Tables

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

    A Parameter Tables A.1 FEL-Physics A.1.1 Performance A.1.1.1 Electron Beam Parameter Name Low Energy High Energy All Energies Unit Electron energy 4.54 14.35 GeV Electron Lorentz factor 8880 28082 Normalized slice emittance 1.2 1.2 µm rad Charge at undulator entrance 1 1 nC Peak current 3400 3400 A Longitudinal pulse form Flat-Top Transverse pulse form Gaussian RMS bunch length 23 23 µm RMS bunch duration 77 77 fs FWHM bunch length 69 69 µm FWHM bunch duration 230 230 fs Slice rms gamma

  16. AVLIS: a technical and economic forecast

    SciTech Connect (OSTI)

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

    1986-01-01

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

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

    SciTech Connect (OSTI)

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

    1997-01-07

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

  18. Forecasting the 2013–2014 influenza season using Wikipedia

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

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

    2015-05-14

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

  19. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect (OSTI)

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

    2015-05-14

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

  20. International energy indicators. [Statistical tables and graphs

    SciTech Connect (OSTI)

    Bauer, E.K.

    1980-05-01

    International statistical tables and graphs are given for the following: (1) Iran - Crude Oil Capacity, Production and Shut-in, June 1974-April 1980; (2) Saudi Arabia - Crude Oil Capacity, Production, and Shut-in, March 1974-Apr 1980; (3) OPEC (Ex-Iran and Saudi Arabia) - Capacity, Production and Shut-in, June 1974-March 1980; (4) Non-OPEC Free World and US Production of Crude Oil, January 1973-February 1980; (5) Oil Stocks - Free World, US, Japan, and Europe (Landed, 1973-1st Quarter, 1980); (6) Petroleum Consumption by Industrial Countries, January 1973-December 1979; (7) USSR Crude Oil Production and Exports, January 1974-April 1980; and (8) Free World and US Nuclear Generation Capacity, January 1973-March 1980. Similar statistical tables and graphs included for the United States include: (1) Imports of Crude Oil and Products, January 1973-April 1980; (2) Landed Cost of Saudi Oil in Current and 1974 Dollars, April 1974-January 1980; (3) US Trade in Coal, January 1973-March 1980; (4) Summary of US Merchandise Trade, 1976-March 1980; and (5) US Energy/GNP Ratio, 1947 to 1979.

  1. Compiler Comparisons

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

  2. Environmental Regulatory Update Table, January--February 1994

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.; Danford, G.S.; Lewis, E.B.

    1994-03-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations ad contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  3. Table II: Technical Targets for Membranes: Automotive | Department of

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

    Energy II: Technical Targets for Membranes: Automotive Table II: Technical Targets for Membranes: Automotive Technical targets for fuel cell membranes in automotive applications defined by the High Temperature Working Group (February 2003). technical_targets_membr_auto.pdf (99.62 KB) More Documents & Publications Table IV: Technical Targets for Membranes: Stationary Table I: Technical Targets for Catalyst Coated Membranes (CCMs): Automotive R&D Plan for the High Temperature Membrane

  4. Environmental regulatory update table, September--October 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Lewis, E.B.; Salk, M.S.

    1992-11-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  5. Environmental Regulatory Update Table, July--August 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Lewis, E.B.; Salk, M.S.

    1992-09-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  6. Environmental Regulatory Update Table, March/April 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1992-05-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  7. Environmental regulatory update table, July/August 1994

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Bock, R.E.; Salk, M.S.

    1994-09-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  8. Environmental regulatory update table November--December 1994

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Bock, R.E.; Mayer, S.J.; Salk, M.S.

    1995-01-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  9. Environmental Regulatory Update Table, November--December 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Lewis, E.B.; Salk, M.S.

    1993-01-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly wit information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  10. Composite slip table of dissimilar materials for damping longitudinal modes

    DOE Patents [OSTI]

    Gregory, Danny L. (Albuquerque, NM); Priddy, Tommy G. (Albuquerque, NM); Smallwood, David O. (Albuquerque, NM); Woodall, Tommy D. (Albuquerque, NM)

    1991-01-01

    A vibration slip table for use in a vibration testing apparatus. The table s comprised of at least three composite layers of material; a first metal layer, a second damping layer, and a third layer having a high acoustic velocity relative to the first layer. The different acoustic velocities between the first and third layers cause relative shear displacements between the layers with the second layer damping the displacements between the first and third layers to reduce the table longitudinal vibration modes.

  11. Environmental Regulatory Update Table, May--June 1994

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Bock, R.E.; Salk, M.S.

    1994-07-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bimonthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  12. Environmental Regulatory Update Table, November--December 1993

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.; Danford, G.S.; Lewis, E.B.

    1994-01-01

    The Environmental Regulatory Update Table provides information on regulatory of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  13. Environmental regulatory update table, March--April 1994

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Bock, R.E.; Salk, M.S.

    1994-03-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  14. Environmental Regulatory Update Table July/August 1993

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.; Danford, G.S.; Lewis, E.B.

    1993-09-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  15. Environmental Regulatory Update Table, January--February 1993

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.; Danford, G.S.; Lewis, E.B.

    1993-03-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  16. Environmental regulatory update table: September/October 1994

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Bock, R.E.; Salk, M.S.

    1994-11-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  17. Environmental Regulatory Update Table, September/October 1993

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.; Danford, G.S.; Lewis, E.B.

    1993-11-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operation and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  18. Environmental sciences division: Environmental regulatory update table July 1988

    SciTech Connect (OSTI)

    Langston, M.E.; Nikbakht, A.; Salk, M.S.

    1988-08-01

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  19. Residential Transportation Historical Data Tables for 1983-2001

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

    per household and per vehicle; fuel consumption; fuel expenditures; and fuel economy. Excel PDF Trends in Households & Vehicles Table 1. Number of Households with Vehicles excel...

  20. Energy.gov Content Management System Data Tables

    Broader source: Energy.gov [DOE]

    For Office of Energy Efficiency and Renewable Energy (EERE) websites, follow these guidelines for creating Section 508-compliant data tables in the Energy.gov content management system.

  1. Trends in Commercial Buildings--Energy Sources Consumption Tables

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

    ** estimates adjusted to match the 1995 CBECS definition of target population Energy Information Administration Commercial Buildings Energy Consumption Survey Table 2....

  2. Table 1b. Relative Standard Errors for Effective, Occupied, and...

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

    b.Relative Standard Errors Table 1b. Relative Standard Errors for Effective Occupied, and Vacant Square Footage, 1992 Building Characteristics All Buildings (thousand) Total...

  3. Buildings and Energy in the 1980's (TABLES)

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

    than 10 households were sampled. Notes: * To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. * Because of rounding, data may...

  4. Microsoft Word - Updated Air Dispersion Modeling Table _sulfur...

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

    DIVINE STRAKE AIR DISPERSION MODELING RESULTS for SULFUR DIOXIDE The attached table is ... within the Nevada Ambient Air Quality Standards at the boundary of the Nevada Test Site. ...

  5. Table 2b. Relative Standard Errors for Electricity Consumption...

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

    2b. Relative Standard Errors for Electricity Table 2b. Relative Standard Errors for Electricity Consumption and Electricity Intensities, per Square Foot, Specific to Occupied and...

  6. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

    Gasoline and Diesel Fuel Update (EIA)

    See footnotes at end of table. 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State 386 Energy Information...

  7. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

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

    Marketing Annual 1998 Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State (Thousand Gallons per Day) -...

  8. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

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

    Marketing Annual 1995 Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State (Thousand Gallons per Day) -...

  9. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

    Gasoline and Diesel Fuel Update (EIA)

    Marketing Annual 1999 Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State (Thousand Gallons per Day) -...

  10. Table 21. Domestic Crude Oil First Purchase Prices

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

    Administration Petroleum Marketing Annual 1996 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

  11. Table 21. Domestic Crude Oil First Purchase Prices

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

    AdministrationPetroleum Marketing Annual 1998 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

  12. Table 21. Domestic Crude Oil First Purchase Prices

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

    Administration Petroleum Marketing Annual 1995 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

  13. Crude Oil Prices Table 21. Domestic Crude Oil First Purchase...

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

    Information Administration Petroleum Marketing Annual 1995 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

  14. Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils...

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

    Marketing Annual 1999 359 Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils and Kerosene by PAD District and State (Thousand Gallons per Day) - Continued...

  15. "Table 7a. Natural Gas Price, Electric Power Sector, Actual...

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

    ... September 2014 Monthly Energy Review, DOEEIA-0035(201308) (Washington, DC, September 25, 2014), Table 9.10. Bureau of Economic Analysis, US Dept. of Commerce, September 2014

  16. Commercial Buildings Energy Consumption Survey 2003 - Detailed Tables

    Reports and Publications (EIA)

    2008-01-01

    The tables contain information about energy consumption and expenditures in U.S. commercial buildings and information about energy-related characteristics of these buildings.

  17. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    1995 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per Day) - Continued Geographic Area Month Premium All Grades Sales...

  18. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    2000 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per Day) - Continued Geographic Area Month Premium All Grades Sales...

  19. Petroleum Products Table 31. Motor Gasoline Prices by Grade...

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

    Annual 1995 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) - Continued Geographic Area Month Premium All...

  20. Petroleum Products Table 31. Motor Gasoline Prices by Grade...

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

    Annual 2000 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) - Continued Geographic Area Month Premium All...

  1. Table 3a. Total Natural Gas Consumption per Effective Occupied...

    Gasoline and Diesel Fuel Update (EIA)

    3a. Natural Gas Consumption per Sq Ft Table 3a. Total Natural Gas Consumption per Effective Occupied Square Foot, 1992 Building Characteristics All Buildings Using Natural Gas...

  2. First-principles opacity table of warm dense deuterium forinertial...

    Office of Scientific and Technical Information (OSTI)

    ...ial-confinement-fusion applications Citation Details In-Document Search Title: First-principles opacity table of warm dense deuterium for inertial-confinement-fusion applications ...

  3. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

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

    Information AdministrationPetroleum Marketing Annual 1999 Table 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and Selected States (Cents per...

  4. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

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

    Energy Information Administration Petroleum Marketing Annual 1995 Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  5. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

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

    250 Energy Information AdministrationPetroleum Marketing Annual 1999 Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State (Thousand Gallons...

  6. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

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

    Information Administration Petroleum Marketing Annual 1995 Table 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  7. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

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

    Energy Information Administration Petroleum Marketing Annual 1995 Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State (Thousand Gallons...

  8. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    Petroleum Marketing Annual 1998 Table 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State (Thousand Gallons per Day) -...

  9. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

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

    134 Energy Information AdministrationPetroleum Marketing Annual 1998 Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  10. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

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

    134 Energy Information AdministrationPetroleum Marketing Annual 1999 Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  11. Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type...

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

    220 Energy Information AdministrationPetroleum Marketing Annual 1998 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per...

  12. Table 33. Oxygenated Motor Gasoline Prices by Grade, Sales Type...

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

    - - - - - - - - - - - - See footnotes at end of table. 33. Oxygenated Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 116 Energy Information...

  13. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

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

    - - - - W W - - - - - - See footnotes at end of table. 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State 292 Energy...

  14. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    Petroleum Marketing Annual 1999 Table 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State (Thousand Gallons per Day) -...

  15. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

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

    Information AdministrationPetroleum Marketing Annual 1998 Table 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and Selected States (Cents per...

  16. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

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

    - - - - W W - - - - - - See footnotes at end of table. 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 86 Energy Information...

  17. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    Petroleum Marketing Annual 1995 Table 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State (Thousand Gallons per Day) -...

  18. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

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

    - - - - 64.7 64.7 - - - - - - See footnotes at end of table. 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 86 Energy Information...

  19. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

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

    250 Energy Information AdministrationPetroleum Marketing Annual 1998 Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State (Thousand Gallons...

  20. Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type...

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

    220 Energy Information AdministrationPetroleum Marketing Annual 1999 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per...