National Library of Energy BETA

Sample records for forecast future demand

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

    Energy Savers [EERE]

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

  2. 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.

  3. 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.

  4. Drivers of Future Energy Demand

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

    Drivers of Future Energy Demand in China Asian Energy Demand Outlook 2014 EIA Energy Conference July 14, 2014 Valerie J. Karplus MIT Sloan School of Management 2 www.china.org.cn www.flickr.com www.wikimedia.org globalchange.mit.edu Global Climate Change Human Development Local Pollution Industrial Development & Resource Needs How to balance? 0 500 1000 1500 2000 2500 3000 3500 4000 1981 1991 2001 2011 Non-material Sectors/Other Construction Commercial consumption Residential consumption

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

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

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

  6. Forecast of transportation energy demand through the year 2010

    SciTech Connect (OSTI)

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

    1991-04-01

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

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

    SciTech Connect (OSTI)

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

    2013-03-01

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

  8. Demand Response: Lessons Learned with an Eye to the Future |...

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

    Demand Response: Lessons Learned with an Eye to the Future Demand Response: Lessons Learned with an Eye to the Future July 11, 2013 - 11:56am Addthis Patricia A. Hoffman Patricia...

  9. Global GPS Phones Market Size, Segmentation, Demand Forecast...

    Open Energy Info (EERE)

    we deeply analyzed the world's main region market conditions that including the product price, profit, capacity, production, capacity utilization, supply, demand and industry...

  10. Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future

    Broader source: Energy.gov [DOE]

    Freight transportation demand is projected to grow to 27.5 billion tons in 2040, and by extrapolation, to nearly 30.2 billion tons in 2050, requiring ever-greater amounts of energy. This report describes the current and future demand for freight transportation in terms of tons and ton-miles of commodities moved by truck, rail, water, pipeline, and air freight carriers. It outlines the economic, logistics, transportation, and policy and regulatory factors that shape freight demand; the possible trends and 2050 outlook for these factors, and their anticipated effect on freight demand and related energy use.After describing federal policy actions that could influence freight demand, the report then summarizes the available analytical models for forecasting freight demand, and identifies possible areas for future action.

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

    SciTech Connect (OSTI)

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

    2015-01-01

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

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

    Reports and Publications (EIA)

    1998-01-01

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

  13. Demand forecasting and revenue requirements, with implications for consideration in British Columbia

    SciTech Connect (OSTI)

    Acton, J.P.

    1983-05-01

    This paper was filed as an exhibit on behalf of The Consumers' Association of Canada (B.C. Branch), The Federated Anti-Poverty Groups of B.C., The Sierra Club of Western Canada, and the B.C. Old Age Pensioners' Organization. It was subjected to cross-examination on October 29, 1982, during Phase I of the hearings. The Utilities Commission had designated Phase I for consideration of (1) demand, (2) assets in service, (3) revenue requirements excluding return, and (4) financing and capital requirements. This paper presents a general discussion of the elements of a rate structure and their relationship to the demand for electricity, a systematic review of some 50 empirical studies of the demand for electricity as a function of price and other factors by the three principal classes of customers, and a discussion of the notion of revenue requirements. The paper should be of interest to utility regulators, rate specialists, and forecasters for its review of demand models and to academics concerned with the study of energy demand.

  14. The Future of U.S. Natural Gas: Supply, Demand & Infrastructure Developments

    Broader source: Energy.gov [DOE]

    This analysis forecasts natural gas supply, demand, and infrastructure developments through 2030 using an inventory and cell model. After introduction of methodology and market approach, the analysis describes expectations of production and supply and demand. This includes how production shifts in North America have shifted Midstream needs, trends in drilling that are leading to more wells with fewer rigs, and processing capacity considerations. Finally, the analysis describing the regionally driven infrastructure requirements and the impact on natural gas price forecasts and regional basis and volatility is presented.

  15. Enhanced Oil Recovery to Fuel Future Oil Demands | GE Global...

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

    of the fascinating things of my job is contemplating questions like: What will the future energy mix look like? This is difficult to predict but it is fair to argue that oil will...

  16. 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.

  17. Demand Response: Lessons Learned with an Eye to the Future | Department of

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

    Energy Demand Response: Lessons Learned with an Eye to the Future Demand Response: Lessons Learned with an Eye to the Future July 11, 2013 - 11:56am Addthis Patricia A. Hoffman Patricia A. Hoffman Assistant Secretary, Office of Electricity Delivery & Energy Reliability In today's world of limited resources and rising costs, everyone is looking for ways to use what they have more effectively while, at the same time, controlling - and ideally - reducing expenses. The electricity industry

  18. Renewable Electricity Futures Study. Volume 3. End-Use Electricity Demand

    SciTech Connect (OSTI)

    Hostick, Donna; Belzer, David B.; Hadley, Stanton W.; Markel, Tony; Marnay, Chris; Kintner-Meyer, Michael

    2012-06-15

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%–90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

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

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

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

  2. Coal supply/demand, 1980 to 2000. Task 3. Resource applications industrialization system data base. Final review draft. [USA; forecasting 1980 to 2000; sector and regional analysis

    SciTech Connect (OSTI)

    Fournier, W.M.; Hasson, V.

    1980-10-10

    This report is a compilation of data and forecasts resulting from an analysis of the coal market and the factors influencing supply and demand. The analyses performed for the forecasts were made on an end-use-sector basis. The sectors analyzed are electric utility, industry demand for steam coal, industry demand for metallurgical coal, residential/commercial, coal demand for synfuel production, and exports. The purpose is to provide coal production and consumption forecasts that can be used to perform detailed, railroad company-specific coal transportation analyses. To make the data applicable for the subsequent transportation analyses, the forecasts have been made for each end-use sector on a regional basis. The supply regions are: Appalachia, East Interior, West Interior and Gulf, Northern Great Plains, and Mountain. The demand regions are the same as the nine Census Bureau regions. Coal production and consumption in the United States are projected to increase dramatically in the next 20 years due to increasing requirements for energy and the unavailability of other sources of energy to supply a substantial portion of this increase. Coal comprises 85 percent of the US recoverable fossil energy reserves and could be mined to supply the increasing energy demands of the US. The NTPSC study found that the additional traffic demands by 1985 may be met by the railways by the way of improved signalization, shorter block sections, centralized traffic control, and other modernization methods without providing for heavy line capacity works. But by 2000 the incremental traffic on some of the major corridors was projected to increase very significantly and is likely to call for special line capacity works involving heavy investment.

  3. Renewable Electricity Futures Study. Volume 3: End-Use Electricity Demand

    SciTech Connect (OSTI)

    Hostick, D.; Belzer, D.B.; Hadley, S.W.; Markel, T.; Marnay, C.; Kintner-Meyer, M.

    2012-06-01

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).

  4. Renewable Electricity Futures Study Volume 3: End-Use Electricity Demand

    Broader source: Energy.gov [DOE]

    This volume details the end-use electricity demand and efficiency assumptions. The projection of electricity demand is an important consideration in determining the extent to which a predominantly renewable electricity future is feasible. Any scenario regarding future electricity use must consider many factors, including technological, sociological, demographic, political, and economic changes (e.g., the introduction of new energy-using devices; gains in energy efficiency and process improvements; changes in energy prices, income, and user behavior; population growth; and the potential for carbon mitigation).

  5. Future Opportunities and Challenges with Using Demand Response as a Resource in Distribution System Operation and Planning Activities

    Broader source: Energy.gov [DOE]

    This scoping study focuses on identifying the ability for current and future demand response opportunities to contribute to distribution system management. To do so, this scoping study will...

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

    SciTech Connect (OSTI)

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

    2005-06-30

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

  7. The Future of Food Demand: Understanding Differences in Global Economic Models

    SciTech Connect (OSTI)

    Valin, Hugo; Sands, Ronald; van der Mensbrugghe, Dominique; Nelson, Gerald; Ahammad, Helal; Blanc, Elodie; Bodirsky, Benjamin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Heyhoe, Edwina; Kyle, G. Page; Mason d'Croz, Daniel; Paltsev, S.; Rolinski, Susanne; Tabeau, Andrzej; van Meijl, Hans; von Lampe, Martin; Willenbockel, Dirk

    2014-01-01

    Understanding the capacity of agricultural systems to feed the world population under climate change requires a good prospective vision on the future development of food demand. This paper reviews modeling approaches from ten global economic models participating to the AgMIP project, in particular the demand function chosen and the set of parameters used. We compare food demand projections at the horizon 2050 for various regions and agricultural products under harmonized scenarios. Depending on models, we find for a business as usual scenario (SSP2) an increase in food demand of 59-98% by 2050, slightly higher than FAO projection (54%). The prospective for animal calories is particularly uncertain with a range of 61-144%, whereas FAO anticipates an increase by 76%. The projections reveal more sensitive to socio-economic assumptions than to climate change conditions or bioenergy development. When considering a higher population lower economic growth world (SSP3), consumption per capita drops by 9% for crops and 18% for livestock. Various assumptions on climate change in this exercise do not lead to world calorie losses greater than 6%. Divergences across models are however notable, due to differences in demand system, income elasticities specification, and response to price change in the baseline.

  8. Proceedings of the Chinese-American symposium on energy markets and the future of energy demand

    SciTech Connect (OSTI)

    Meyers, S.

    1988-11-01

    The Symposium was organized by the Energy Research Institute of the State Economic Commission of China, and the Lawrence Berkeley Laboratory and Johns Hopkins University from the United States. It was held at the Johns Hopkins University Nanjing Center in late June 1988. It was attended by about 15 Chinese and an equal number of US experts on various topics related to energy demand and supply. Each presenter is one of the best observers of the energy situation in their field. A Chinese and US speaker presented papers on each topic. In all, about 30 papers were presented over a period of two and one half days. Each paper was translated into English and Chinese. The Chinese papers provide an excellent overview of the emerging energy demand and supply situation in China and the obstacles the Chinese planners face in managing the expected increase in demand for energy. These are matched by papers that discuss the energy situation in the US and worldwide, and the implications of the changes in the world energy situation on both countries. The papers in Part 1 provide historical background and discuss future directions. The papers in Part 2 focus on the historical development of energy planning and policy in each country and the methodologies and tools used for projecting energy demand and supply. The papers in Part 3 examine the pattern of energy demand, the forces driving demand, and opportunities for energy conservation in each of the major sectors in China and the US. The papers in Part 4 deal with the outlook for global and Pacific region energy markets and the development of the oil and natural gas sector in China.

  9. EIA projections of coal supply and demand

    SciTech Connect (OSTI)

    Klein, D.E.

    1989-10-23

    Contents of this report include: EIA projections of coal supply and demand which covers forecasted coal supply and transportation, forecasted coal demand by consuming sector, and forecasted coal demand by the electric utility sector; and policy discussion.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28

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

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

    SciTech Connect (OSTI)

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

    2008-01-07

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

  12. Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs

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

    Pelletier, Jon D.; Murray, A. Brad; Pierce, Jennifer L.; Bierman, Paul R.; Breshears, David D.; Crosby, Benjamin T.; Ellis, Michael; Foufoula-Georgiou, Efi; Heimsath, Arjun M.; Houser, Chris; et al

    2015-07-14

    In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we havemore » the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.« less

  13. Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs

    SciTech Connect (OSTI)

    Pelletier, Jon D.; Murray, A. Brad; Pierce, Jennifer L.; Bierman, Paul R.; Breshears, David D.; Crosby, Benjamin T.; Ellis, Michael; Foufoula-Georgiou, Efi; Heimsath, Arjun M.; Houser, Chris; Lancaster, Nick; Marani, Marco; Merritts, Dorothy J.; Moore, Laura J.; Pederson, Joel L.; Poulos, Michael J.; Rittenour, Tammy M.; Rowland, Joel C.; Ruggiero, Peter; Ward, Dylan J.; Wickert, Andrew D.; Yager, Elowyn M.

    2015-07-14

    In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we have the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.

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

    SciTech Connect (OSTI)

    Not Available

    1992-09-01

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

  15. 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.

  16. Demand for oil and energy in developing countries

    SciTech Connect (OSTI)

    Wolf, C. Jr.; Relles, D.A.; Navarro, J.

    1980-05-01

    How much of the world's oil and energy supply will the non-OPEC less-developed countries (NOLDCs) demand in the next decade. Will their requirements be small and thus fairly insignificant compared with world demand, or large and relatively important. How will world demand be affected by the economic growth of the NOLDCs. In this report, we try to develop some reasonable forecasts of NOLDC energy demands in the next 10 years. Our focus is mainly on the demand for oil, but we also give some attention to the total commercial energy requirements of these countries. We have tried to be explicit about the uncertainties associated with our forecasts, and with the income and price elasticities on which they are based. Finally, we consider the forecasts in terms of their implications for US policies concerning the NOLDCs and suggest areas of future research on NOLDC energy issues.

  17. 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 ...

  18. International Oil Supplies and Demands

    SciTech Connect (OSTI)

    Not Available

    1992-04-01

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  19. International Oil Supplies and Demands

    SciTech Connect (OSTI)

    Not Available

    1991-09-01

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  20. 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.

  1. 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

  2. Hawaii demand-side management resource assessment. Final report, Reference Volume 5: The DOETRAN user`s manual; The DOE-2/DBEDT DSM forecasting model interface

    SciTech Connect (OSTI)

    1995-04-01

    The DOETRAN model is a DSM database manager, developed to act as an intermediary between the whole building energy simulation model, DOE-2, and the DBEDT DSM Forecasting Model. DOETRAN accepts output data from DOE-2 and TRANslates that into the format required by the forecasting model. DOETRAN operates in the Windows environment and was developed using the relational database management software, Paradox 5.0 for Windows. It is not necessary to have any knowledge of Paradox to use DOETRAN. DOETRAN utilizes the powerful database manager capabilities of Paradox through a series of customized user-friendly windows displaying buttons and menus with simple and clear functions. The DOETRAN model performs three basic functions, with an optional fourth. The first function is to configure the user`s computer for DOETRAN. The second function is to import DOE-2 files with energy and loadshape data for each building type. The third main function is to then process the data into the forecasting model format. As DOETRAN processes the DOE-2 data, graphs of the total electric monthly impacts for each DSM measure appear, providing the user with a visual means of inspecting DOE-2 data, as well as following program execution. DOETRAN provides three tables for each building type for the forecasting model, one for electric measures, gas measures, and basecases. The optional fourth function provided by DOETRAN is to view graphs of total electric annual impacts by measure. This last option allows a comparative view of how one measure rates against another. A section in this manual is devoted to each of the four functions mentioned above, as well as computer requirements and exiting DOETRAN.

  3. International Oil Supplies and Demands. Volume 2

    SciTech Connect (OSTI)

    Not Available

    1992-04-01

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  4. International Oil Supplies and Demands. Volume 1

    SciTech Connect (OSTI)

    Not Available

    1991-09-01

    The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

  5. Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Future of Renewable Energy in the West

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

    (This page intentionally left blank) National Renewable Energy Laboratory 15013 Denver West Parkway Golden, CO 80401 303-275-3000 * www.nrel.gov Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Future of Renewable Energy in the West David J. Hurlbut, Joyce McLaren, and Rachel Gelman National Renewable Energy Laboratory Prepared under Task No. AROE.2000 NREL is a national laboratory of the U.S. Department of Energy Office of Energy

  6. Future

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

    Future Future Print Information about the future expansion of research fields for synchrotrons and the growing number of light sources, including free electron lasers (FELs) will...

  7. Expectations models of electric utilities' forecasts: a case study of econometric estimation with influential data points

    SciTech Connect (OSTI)

    Vellutini, R. de A.S.; Mount, T.D.

    1983-01-01

    This study develops an econometric model for explaining how electric utilities revise their forecasts of future electricity demand each year. The model specification is developed from the adaptive expectations hypothesis and it relates forecasted growth rates to actual lagged growth rates of electricity demand. Unlike other studies of the expectation phenomenon, expectations of future demand levels constitute an observable variable and thus can be incorporated explicitly into the model. The data used for the analysis were derived from the published forecasts of the nine National Electric Reliability Councils in the US for the years 1974 to 1980. Three alternative statistical methods are used for estimation purposes: ordinary least-squares, robust regression and a diagnostic analysis to identify influential observations. The results obtained with the first two methods are very similar, but are both inconsistent with the underlying economic logic of the model. The estimated model obtained from the diagnostics approach after deleting two aberrant observations is consistent with economic logic, and supports the hypothesis that the low growth demand experienced immediately following the oil embargo in 1973 were disregarded by the industry for forecasting purposes. The model includes transitory effects associated with the oil embargo that gradually disappear over time, the estimated coefficients for the lagged values of actual growth approach a structure with declining positive weights. The general shape of this asymptotic structure is similar to the findings in many economic applications using distributed lag models.

  8. 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....

  9. Demand Reduction

    Broader source: Energy.gov [DOE]

    Grantees may use funds to coordinate with electricity supply companies and utilities to reduce energy demands on their power systems. These demand reduction programs are usually coordinated through...

  10. Heat wave contributes to higher summer electricity demand in...

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

    Heat wave contributes to higher summer electricity demand in the Northeast In its new energy forecast, the U.S. Energy Information Administration expects summer retail electricity ...

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

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

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

  12. 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 3,153 3,143 -0.3% Price (centskWh) 12.06 12.09 12.58 13.04 12.95 12.96 ...

  13. Commercial Demand Module - NEMS Documentation

    Reports and Publications (EIA)

    2014-01-01

    Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

  14. Irrigation and the demand for electricity. Progress report

    SciTech Connect (OSTI)

    Maddigan, R. J.; Chern, W. S.; Gallagher, C. A.

    1980-03-01

    In order to anticipate the need for generating capacity, utility planners must estimate the future growth in electricity demand. The need for demand forecasts is no less important for the nation's Rural Electric Cooperatives (RECs) than it is for the investor-owned utilities. The RECs serve an historically agrarian region; therefore, the irrigation sector accounts for a significant portion of the western RECs' total demand. A model is developed of the RECs' demand for electricity used in irrigation. The model is a simultaneous equation system which focuses on both the short-run utilization of electricity in irrigation and the long-run determination of the number of irrigators using electricity. Irrigation demand is described by a set of equations in which the quantity of electricity demanded, the average electricity price, the number of irrigation customers, and the ratio of electricity to total energy used for irrigation are endogenous. The structural equations are estimated using pooled state-level data for the period 1961-1977. In light of the model's results, the impact of changes in relative energy prices on irrigation can be examined.

  15. Taxonomy for Modeling Demand Response Resources

    SciTech Connect (OSTI)

    Olsen, Daniel; Kiliccote, Sila; Sohn, Michael; Dunn, Laura; Piette, Mary, A

    2014-08-01

    Demand response resources are an important component of modern grid management strategies. Accurate characterizations of DR resources are needed to develop systems of optimally managed grid operations and to plan future investments in generation, transmission, and distribution. The DOE Demand Response and Energy Storage Integration Study (DRESIS) project researched the degree to which demand response (DR) and energy storage can provide grid flexibility and stability in the Western Interconnection. In this work, DR resources were integrated with traditional generators in grid forecasting tools, specifically a production cost model of the Western Interconnection. As part of this study, LBNL developed a modeling framework for characterizing resource availability and response attributes of DR resources consistent with the governing architecture of the simulation modeling platform. In this report, we identify and describe the following response attributes required to accurately characterize DR resources: allowable response frequency, maximum response duration, minimum time needed to achieve load changes, necessary pre- or re-charging of integrated energy storage, costs of enablement, magnitude of controlled resources, and alignment of availability. We describe a framework for modeling these response attributes, and apply this framework to characterize 13 DR resources including residential, commercial, and industrial end-uses. We group these end-uses into three broad categories based on their response capabilities, and define a taxonomy for classifying DR resources within these categories. The three categories of resources exhibit different capabilities and differ in value to the grid. Results from the production cost model of the Western Interconnection illustrate that minor differences in resource attributes can have significant impact on grid utilization of DR resources. The implications of these findings will be explored in future DR valuation studies.

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

    SciTech Connect (OSTI)

    Cassel, T.A.V.; Shimamoto, G.T.; Amundsen, C.B.; Blair, P.D.; Finan, W.F.; Smith, M.R.; Edeistein, R.H.

    1982-03-31

    The backgrund, structure and use of modern forecasting methods for estimating the future development of geothermal energy in the United States are documented. The forecasting instrument may be divided into two sequential submodels. The first predicts the timing and quality of future geothermal resource discoveries from an underlying resource base. This resource base represents an expansion of the widely-publicized USGS Circular 790. The second submodel forecasts the rate and extent of utilization of geothermal resource discoveries. It is based on the joint investment behavior of resource developers and potential users as statistically determined from extensive industry interviews. It is concluded that geothermal resource development, especially for electric power development, will play an increasingly significant role in meeting US energy demands over the next 2 decades. Depending on the extent of R and D achievements in related areas of geosciences and technology, expected geothermal power development will reach between 7700 and 17300 Mwe by the year 2000. This represents between 8 and 18% of the expected electric energy demand (GWh) in western and northwestern states.

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

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

    Forecasting. | Department of Energy 0: The Smart Enterprise, its Objective and Forecasting. Future Power Systems 20: The Smart Enterprise, its Objective and Forecasting. Future Power Systems 20: The Smart Enterprise, its Objective and Forecasting. PDF icon Future Power Systems 20: The Smart Enterprise, its Objective and Forecasting. More Documents & Publications Future Power Systems 21 - The Smart Customer Smart Grid R&D Multi-Year Program Plan (2010-2014) - September 2011 Update

  18. Chinese Oil Demand: Steep Incline Ahead

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

    Chinese Oil Demand: Steep Incline Ahead Malcolm Shealy Alacritas, Inc. April 7, 2008 Oil Demand: China, India, Japan, South Korea 0 2 4 6 8 1995 2000 2005 2010 Million Barrels/Day China South Korea Japan India IEA China Oil Forecast 0 2 4 6 8 10 12 14 16 18 2000 2005 2010 2015 2020 2025 2030 Million Barrels/Day WEO 2007 16.3 mbd 12.7 mbd IEA China Oil Forecasts 0 2 4 6 8 10 12 14 16 18 2000 2005 2010 2015 2020 2025 2030 Million Barrels/Day WEO 2007 WEO 2006 WEO 2004 WEO 2002 Vehicle Sales in

  19. Demand Response

    Energy Savers [EERE]

    Demand Response Assessment for Eastern Interconnection Youngsun Baek, Stanton W. Hadley, Rocio Martinez, Gbadebo Oladosu, Alexander M. Smith, Fran Li, Paul Leiby and Russell Lee Prepared for FY12 DOE-CERTS Transmission Reliability R&D Internal Program Review September 20, 2012 2 Managed by UT-Battelle for the U.S. Department of Energy DOE National Laboratory Studies Funded to Support FOA 63 * DOE set aside $20 million from transmission funding for national laboratory studies. * DOE

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

    SciTech Connect (OSTI)

    1993-05-01

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

  1. travel-demand-modeling

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

    Demand Modeler, Cambridge Systematics, Tallahassee, FL Abstract ... Travel demand ... Ahmed Mohideen Travel Demand Modeler Cambridge Systematics, Tallahassee, FL Transportation ...

  2. Commercial & Industrial Demand Response

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

    & Events Skip navigation links Smart Grid Demand Response Agricultural Residential Demand Response Commercial & Industrial Demand Response Cross-sector Demand Response...

  3. Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Future of Renewable Energy in the West; Report and Executive Summary

    SciTech Connect (OSTI)

    Hurlbut, D. J.; McLaren, J.; Gelman, R.

    2013-08-01

    This study assesses the outlook for utility-scale renewable energy development in the West once states have met their renewable portfolio standard (RPS) requirements. In the West, the last state RPS culminates in 2025, so the analysis uses 2025 as a transition point on the timeline of RE development. Most western states appear to be on track to meet their final requirements, relying primarily on renewable resources located relatively close to the customers being served. What happens next depends on several factors including trends in the supply and price of natural gas, greenhouse gas and other environmental regulations, consumer preferences, technological breakthroughs, and future public policies and regulations. Changes in any one of these factors could make future renewable energy options more or less attractive.

  4. Demand Response Programs, 6. edition

    SciTech Connect (OSTI)

    2007-10-15

    The report provides a look at the past, present, and future state of the market for demand/load response based upon market price signals. It is intended to provide significant value to individuals and companies who are considering participating in demand response programs, energy providers and ISOs interested in offering demand response programs, and consultants and analysts looking for detailed information on demand response technology, applications, and participants. The report offers a look at the current Demand Response environment in the energy industry by: defining what demand response programs are; detailing the evolution of program types over the last 30 years; discussing the key drivers of current initiatives; identifying barriers and keys to success for the programs; discussing the argument against subsidization of demand response; describing the different types of programs that exist including:direct load control, interruptible load, curtailable load, time-of-use, real time pricing, and demand bidding/buyback; providing examples of the different types of programs; examining the enablers of demand response programs; and, providing a look at major demand response programs.

  5. 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...

  6. Forecasting Water Quality & Biodiversity

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

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

  7. 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...

  8. Using Wikipedia to forecast disease

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

    Using Wikipedia to forecast disease Using Wikipedia to forecast disease Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. December 22, 2014 Using Wikipedia to forecast disease Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. Contact Nancy Ambrosiano Communications Office (505) 667-0471 Email "A global disease-forecasting system will improve

  9. 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 ...

  10. Projecting Electricity Demand in 2050

    SciTech Connect (OSTI)

    Hostick, Donna J.; Belzer, David B.; Hadley, Stanton W.; Markel, Tony; Marnay, Chris; Kintner-Meyer, Michael CW

    2014-07-01

    This paper describes the development of end-use electricity projections and load curves that were developed for the Renewable Electricity (RE) Futures Study (hereafter RE Futures), which explored the prospect of higher percentages (30% − 90%) of total electricity generation that could be supplied by renewable sources in the United States. As input to RE Futures, two projections of electricity demand were produced representing reasonable upper and lower bounds of electricity demand out to 2050. The electric sector models used in RE Futures required underlying load profiles, so RE Futures also produced load profile data in two formats: 8760 hourly data for the year 2050 for the GridView model, and in 2-year increments for 17 time slices as input to the Regional Energy Deployment System (ReEDS) model. The process for developing demand projections and load profiles involved three steps: discussion regarding the scenario approach and general assumptions, literature reviews to determine readily available data, and development of the demand curves and load profiles.

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

    SciTech Connect (OSTI)

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

    1995-12-01

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

  12. The forecast calls for flu

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

    The forecast calls for flu Science on the Hill: 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

  13. 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.

  14. 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.

  15. Global Energy: Supply, Demand, Consequences, Opportunities

    ScienceCinema (OSTI)

    Majumdar, Arun

    2010-01-08

    July 29, 2008 Berkeley Lab lecture: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

  16. Cross-sector Demand Response

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

    & Events Skip navigation links Smart Grid Demand Response Agricultural Residential Demand Response Commercial & Industrial Demand Response Cross-sector Demand Response...

  17. Residential Demand Sector Data, Commercial Demand Sector Data, Industrial Demand Sector Data - Annual Energy Outlook 2006

    SciTech Connect (OSTI)

    2009-01-18

    Tables describing consumption and prices by sector and census division for 2006 - includes residential demand, commercial demand, and industrial demand

  18. East Coast blizzard cuts into gasoline demand, but home electricity demand rises

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

    East Coast blizzard cuts into gasoline demand, but home electricity demand rises U.S. monthly gasoline consumption declined in January, as the big winter storm that shut down many East Coast cities kept people in their homes and off the road. In its new monthly forecast, the U.S. Energy Information Administration said monthly gasoline consumption dropped 230,000 barrels per day in January compared to year-ago levels and that marked the first year-over-year decline in monthly gasoline use since

  19. Behavioral Economics Applied to Energy Demand Analysis: A Foundation

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

    Behavioral Economics Applied to Energy Demand Analysis: A Foundation October 2014 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Behavioral Economics Applied to Energy Demand Analysis i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of

  20. The house of the future

    ScienceCinema (OSTI)

    None

    2010-09-01

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

  1. Demand Response Analysis Tool

    Energy Science and Technology Software Center (OSTI)

    2012-03-01

    Demand Response Analysis Tool is a software developed at the Lawrence Berkeley National Laboratory. It is initially funded by Southern California Edison. Our goal in developing this tool is to provide an online, useable, with standardized methods, an analysis tool to evaluate demand and demand response performance of commercial and industrial facilities. The tool provides load variability and weather sensitivity analysis capabilities as well as development of various types of baselines. It can be usedmore » by researchers, real estate management firms, utilities, or any individuals who are interested in analyzing their demand and demand response capabilities.« less

  2. Demand Response Analysis Tool

    SciTech Connect (OSTI)

    2012-03-01

    Demand Response Analysis Tool is a software developed at the Lawrence Berkeley National Laboratory. It is initially funded by Southern California Edison. Our goal in developing this tool is to provide an online, useable, with standardized methods, an analysis tool to evaluate demand and demand response performance of commercial and industrial facilities. The tool provides load variability and weather sensitivity analysis capabilities as well as development of various types of baselines. It can be used by researchers, real estate management firms, utilities, or any individuals who are interested in analyzing their demand and demand response capabilities.

  3. The motor gasoline industry: Past, present, and future. [Contains glossary

    SciTech Connect (OSTI)

    Not Available

    1991-01-01

    Motor gasoline constitutes the largest single component of US demand for petroleum products and is the Nation's most widely used transportation fuel. Because of its importance as a transportation fuel, motor gasoline has been the focus of several regulatory and tax policy initiatives in recent years. Much of the US refining capacity is specifically geared toward maximizing motor gasoline production, and future investments by the petroleum industry in refining infrastructure are likely to be made largely to produce larger volumes of clean motor gasoline. This report addresses major events and developments that have had an impact on motor gasoline supply, distribution, prices, and demand. The report provides historical perspective as well as analyses of important events from the 1970's and 1980's. Long-term forecasts are provided for the period from 1990 to 2010 in an effort to present and analyze possible future motor gasoline trends. Other forecasts examine the near-term impact of the invasion of Kuwait. 18 figs., 10 tabs.

  4. 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.

  5. Residential Demand Response

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

    in-home displays with controllable home area network capabilities and thermal storage devices for home heating. Goals and objectives: Reduce the City's NCP demand above...

  6. Managing Increased Charging Demand

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

    Managing Increased Charging Demand Carrie Giles ICF International, Supporting the Workplace Charging Challenge Workplace Charging Challenge Do you already own an EV? Are you...

  7. Managing Increased Charging Demand

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

    Managing Increased Charging Demand Carrie Giles ICF International, Supporting the Workplace Charging Challenge Workplace Charging Challenge Do you already own an EV? Are you ...

  8. 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)

  9. Supply Forecast and Analysis (SFA)

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

    Science Team Leader Oak Ridge National Laboratory DOE Bioenergy Technologies Office (BETO) 2015 Project Peer Review Supply Forecast and Analysis (SFA) 2 | Bioenergy Technologies ...

  10. 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.

  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. LNG Analysis Summary: A Different Way of Looking at the Future of World LNG Trade

    Broader source: Energy.gov [DOE]

    This report examines alternative future scenarios for global LNG trade. The analysis calibrates initial liquefied natural gas (LNG) demand projections to external forecasts. Alternative LNG demand and supply scenarios are then generated to assess a range of potential outcomes. Scenarios include variations in Chinese, European and Japanese market conditions, changes in natural gas pipeline supplies and alternative LNG export conditions from the Middle East. Overall, the report foresees a LNG market where supply growth is likely to outpace demand and lead to downward pressure on LNG prices. The analysis projects North American LNG exports to the Atlantic Basin to fall in a range between 8.8 billion cubic feet per day (Bcfd) and 12.2 Bcfd in 2030.

  13. Energy technologies and their impact on demand

    SciTech Connect (OSTI)

    Drucker, H.

    1995-06-01

    Despite the uncertainties, energy demand forecasts must be made to guide government policies and public and private-sector capital investment programs. Three principles can be identified in considering long-term energy prospects. First energy demand will continue to grow, driven by population growth, economic development, and the current low per capita energy consumption in developing countries. Second, energy technology advancements alone will not solve the problem. Energy-efficient technologies, renewable resource technologies, and advanced electric power technologies will all play a major role but will not be able to keep up with the growth in world energy demand. Third, environmental concerns will limit the energy technology choices. Increasing concern for environmental protection around the world will restrict primarily large, centralized energy supply facilities. The conclusion is that energy system diversity is the only solution. The energy system must be planned with consideration of both supply and demand technologies, must not rely on a single source of energy, must take advantage of all available technologies that are specially suited to unique local conditions, must be built with long-term perspectives, and must be able to adapt to change.

  14. Demand Response Dispatch Tool

    SciTech Connect (OSTI)

    2012-08-31

    The Demand Response (DR) Dispatch Tool uses price profiles to dispatch demand response resources and create load modifying profiles. These annual profiles are used as inputs to production cost models and regional planning tools (e.g., PROMOD). The tool has been effectively implemented in transmission planning studies conducted by the Western Electricity Coordinating Council via its Transmission Expansion Planning and Policy Committee. The DR Dispatch Tool can properly model the dispatch of DR resources for both reliability and economic conditions.

  15. Demand Dispatch-Intelligent

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

    Demand Dispatch-Intelligent Demand for a More Efficient Grid 10 August 2011 DOE/NETL- DE-FE0004001 U.S. Department of Energy Office of Electricity Delivery and Energy Reliability Prepared by: National Energy Technology Laboratory Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal

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

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

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

  17. 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:...

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

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

    6 - Metrics, Performance Measurements and Forecasting Module 6 - Metrics, Performance Measurements and Forecasting This module focuses on the metrics and performance measurement ...

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

    SciTech Connect (OSTI)

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

    2013-05-01

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

  20. Grid Integration of Aggregated Demand Response, Part 2: Modeling Demand Response in a Production Cost Model

    Broader source: Energy.gov [DOE]

    Renewable integration studies have evaluated many challenges associated with deploying large amounts of variable wind and solar generation technologies. These studies can evaluate operational impacts associated with variable generation, benefits of improved wind and solar resource forecasting, and trade-offs between institutional changes, including increasing balancing area cooperation and technical changes such as installing new flexible generation. Demand response (DR) resources present a potentially important source of grid flexibility and can aid in integrating variable generation; however, integration analyses have not yet incorporated these resources explicitly into grid simulation models as part of a standard toolkit for resource planners.

  1. 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

  2. Demand Response Dispatch Tool

    Energy Science and Technology Software Center (OSTI)

    2012-08-31

    The Demand Response (DR) Dispatch Tool uses price profiles to dispatch demand response resources and create load modifying profiles. These annual profiles are used as inputs to production cost models and regional planning tools (e.g., PROMOD). The tool has been effectively implemented in transmission planning studies conducted by the Western Electricity Coordinating Council via its Transmission Expansion Planning and Policy Committee. The DR Dispatch Tool can properly model the dispatch of DR resources for bothmore » reliability and economic conditions.« less

  3. 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.

  4. Residential Electricity Demand in China -- Can Efficiency Reverse the Growth?

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.; Zhou, Nan

    2009-05-18

    The time when energy-related carbon emissions come overwhelmingly from developed countries is coming to a close. China has already overtaken the United States as the world's leading emitter of greenhouse gas emissions. The economic growth that China has experienced is not expected to slow down significantly in the long term, which implies continued massive growth in energy demand. This paper draws on the extensive expertise from the China Energy Group at LBNL on forecasting energy consumption in China, but adds to it by exploring the dynamics of demand growth for electricity in the residential sector -- and the realistic potential for coping with it through efficiency. This paper forecasts ownership growth of each product using econometric modeling, in combination with historical trends in China. The products considered (refrigerators, air conditioners, fans, washing machines, lighting, standby power, space heaters, and water heating) account for 90percent of household electricity consumption in China. Using this method, we determine the trend and dynamics of demandgrowth and its dependence on macroeconomic drivers at a level of detail not accessible by models of a more aggregate nature. In addition, we present scenarios for reducing residential consumption through efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, thus allowing for a technologically realistic assessment of efficiency opportunities specifically in the Chinese context.

  5. 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. File Acquisition-Forecast-2016-05-06.xlsx More Documents & Publications Small Business Program Manager Directory EA-1900: Notice of Availability of a Draft Environmental Assessment Small Business Program Manager Directory

  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. Demand Response | Department of Energy

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

    Demand Response Demand Response Demand Response Demand response provides an opportunity for consumers to play a significant role in the operation of the electric grid by reducing or shifting their electricity usage during peak periods in response to time-based rates or other forms of financial incentives. Demand response programs are being used by electric system planners and operators as resource options for balancing supply and demand. Such programs can lower the cost of electricity in

  8. Model documentation report: Residential sector demand module of the national energy modeling system

    SciTech Connect (OSTI)

    1998-01-01

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This reference document provides a detailed description for energy analysts, other users, and the public. The NEMS Residential Sector Demand Module is currently used for mid-term forecasting purposes and energy policy analysis over the forecast horizon of 1993 through 2020. The model generates forecasts of energy demand for the residential sector by service, fuel, and Census Division. Policy impacts resulting from new technologies, market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.

  9. Demand Charges | Open Energy Information

    Open Energy Info (EERE)

    Demand Charges Jump to: navigation, search Retrieved from "http:en.openei.orgwindex.php?titleDemandCharges&oldid488967" Feedback Contact needs updating Image needs...

  10. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

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

    2011-11-29

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

  11. Report: Natural Gas Infrastructure Implications of Increased Demand from

    Energy Savers [EERE]

    the Electric Power Sector | Department of Energy Natural Gas Infrastructure Implications of Increased Demand from the Electric Power Sector Report: Natural Gas Infrastructure Implications of Increased Demand from the Electric Power Sector This report examines the potential infrastructure needs of the U.S. interstate natural gas pipeline transmission system across a range of future natural gas demand scenarios that drive increased electric power sector natural gas use. To perform this

  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 PDF icon Wind Forecast Improvement Project ...

  13. Uncertainty Reduction in Power Generation Forecast Using Coupled...

    Office of Scientific and Technical Information (OSTI)

    quantify the forecast uncertainty by reducing prediction intervals of forecasts. ... means, e.g., using weather-based models, and reduce forecast errors prediction intervals. ...

  14. Global Energy: Supply, Demand, Consequences, Opportunities (LBNL Summer Lecture Series)

    ScienceCinema (OSTI)

    Majumdar, Arun

    2011-04-28

    Summer Lecture Series 2009: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

  15. Global Energy: Supply, Demand, Consequences, Opportunities (LBNL Summer Lecture Series)

    SciTech Connect (OSTI)

    Majumdar, Arun

    2008-07-29

    Summer Lecture Series 2009: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

  16. 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

  17. Economic Rebalancing and Electricity Demand in China

    SciTech Connect (OSTI)

    He, Gang; Lin, Jiang; Yuan, Alexandria

    2015-11-01

    Understanding the relationship between economic growth and electricity use is essential for power systems planning. This need is particularly acute now in China, as the Chinese economy is going through a transition to a more consumption and service oriented economy. This study uses 20 years of provincial data on gross domestic product (GDP) and electricity consumption to examine the relationship between these two factors. We observe a plateauing effect of electricity consumption in the richest provinces, as the electricity demand saturates and the economy develops and moves to a more service-based economy. There is a wide range of forecasts for electricity use in 2030, ranging from 5,308 to 8,292 kWh per capita, using different estimating functions, as well as in existing studies. It is therefore critical to examine more carefully the relationship between electricity use and economic development, as China transitions to a new growth phase that is likely to be less energy and resource intensive. The results of this study suggest that policymakers and power system planners in China should seriously re-evaluate power demand projections and the need for new generation capacity to avoid over-investment that could lead to stranded generation assets.

  18. Residential Demand Module of the National Energy Modeling System: Model Documentation 2014

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

    Residential Demand Module of the National Energy Modeling System: Model Documentation 2014 August 2014 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | NEMS Residential Demand Module Documentation Report 2014 ii This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts

  19. 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. ...

  20. Demand Response Quick Assessment Tool

    Energy Science and Technology Software Center (OSTI)

    2008-12-01

    DRQAT (Demand Response Quick Assessment Tool) is the tool for assessing demand response saving potentials for large commercial buildings. This tool is based on EnergyPlus simulations of prototypical buildings and HVAC equipment. The opportunities for demand reduction and cost savings with building demand responsive controls vary tremendously with building type and location. The assessment tools will predict the energy and demand savings, the economic savings, and the thermal comfor impact for various demand responsive strategies.more » Users of the tools will be asked to enter the basic building information such as types, square footage, building envelope, orientation, utility schedule, etc. The assessment tools will then use the prototypical simulation models to calculate the energy and demand reduction potential under certain demand responsive strategies, such as precooling, zonal temperature set up, and chilled water loop and air loop set points adjustment.« less

  1. 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

  2. China's Coal: Demand, Constraints, and Externalities

    SciTech Connect (OSTI)

    Aden, Nathaniel; Fridley, David; Zheng, Nina

    2009-07-01

    This study analyzes China's coal industry by focusing on four related areas. First, data are reviewed to identify the major drivers of historical and future coal demand. Second, resource constraints and transport bottlenecks are analyzed to evaluate demand and growth scenarios. The third area assesses the physical requirements of substituting coal demand growth with other primary energy forms. Finally, the study examines the carbon- and environmental implications of China's past and future coal consumption. There are three sections that address these areas by identifying particular characteristics of China's coal industry, quantifying factors driving demand, and analyzing supply scenarios: (1) reviews the range of Chinese and international estimates of remaining coal reserves and resources as well as key characteristics of China's coal industry including historical production, resource requirements, and prices; (2) quantifies the largest drivers of coal usage to produce a bottom-up reference projection of 2025 coal demand; and (3) analyzes coal supply constraints, substitution options, and environmental externalities. Finally, the last section presents conclusions on the role of coal in China's ongoing energy and economic development. China has been, is, and will continue to be a coal-powered economy. In 2007 Chinese coal production contained more energy than total Middle Eastern oil production. The rapid growth of coal demand after 2001 created supply strains and bottlenecks that raise questions about sustainability. Urbanization, heavy industrial growth, and increasing per-capita income are the primary interrelated drivers of rising coal usage. In 2007, the power sector, iron and steel, and cement production accounted for 66% of coal consumption. Power generation is becoming more efficient, but even extensive roll-out of the highest efficiency units would save only 14% of projected 2025 coal demand for the power sector. A new wedge of future coal consumption is likely to come from the burgeoning coal-liquefaction and chemicals industries. If coal to chemicals capacity reaches 70 million tonnes and coal-to-liquids capacity reaches 60 million tonnes, coal feedstock requirements would add an additional 450 million tonnes by 2025. Even with more efficient growth among these drivers, China's annual coal demand is expected to reach 3.9 to 4.3 billion tonnes by 2025. Central government support for nuclear and renewable energy has not reversed China's growing dependence on coal for primary energy. Substitution is a matter of scale: offsetting one year of recent coal demand growth of 200 million tonnes would require 107 billion cubic meters of natural gas (compared to 2007 growth of 13 BCM), 48 GW of nuclear (compared to 2007 growth of 2 GW), or 86 GW of hydropower capacity (compared to 2007 growth of 16 GW). Ongoing dependence on coal reduces China's ability to mitigate carbon dioxide emissions growth. If coal demand remains on a high growth path, carbon dioxide emissions from coal combustion alone would exceed total US energy-related carbon emissions by 2010. Within China's coal-dominated energy system, domestic transportation has emerged as the largest bottleneck for coal industry growth and is likely to remain a constraint to further expansion. China has a low proportion of high-quality reserves, but is producing its best coal first. Declining quality will further strain production and transport capacity. Furthermore, transporting coal to users has overloaded the train system and dramatically increased truck use, raising transportation oil demand. Growing international imports have helped to offset domestic transport bottlenecks. In the long term, import demand is likely to exceed 200 million tonnes by 2025, significantly impacting regional markets.

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

    SciTech Connect (OSTI)

    Stoffel, T.

    2012-06-01

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

  4. NREL: Resource Assessment and Forecasting Home Page

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

    NREL's resource assessment and forecasting research supports industry, government, and academia by providing renewable energy resource measurements, models, maps, and support services. These resources are used to plan and develop renewable energy technologies and support climate change research. Learn more about NREL's resource assessment and forecasting research: Capabilities Facilities Research staff Data and resources. Resource assessment and forecasting research is primarily performed at

  5. Review/Verify Strategic Skills Needs/Forecasts/Future Mission...

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

    Sector program Execution Plans (1-3 yrs) HR Strategic Plan (1-3 yrs) Current hiring Lists (1-2 yrs) Succession Plans (1-x yrs) UpdateValidate Strategic Staff...

  6. Alternative future scenarios for the SPS comparative assessment

    SciTech Connect (OSTI)

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

    1980-08-01

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

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

    SciTech Connect (OSTI)

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

    2009-03-01

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

  8. LPG export growth will exceed demand by 2000

    SciTech Connect (OSTI)

    True, W.R.

    1994-08-08

    LPG supplies for international trade will increase sharply through 2000 and begin to outstrip demand by 1997 or 1998. This outlook depends on several production projects proceeding as planned. Leading the way to increased volumes are projects in Algeria, Nigeria, and Australia, among others. Purvin and Gertz, Dallas, projected this trend earlier this year at an international LPG seminar near Houston. Representatives from LPG-supplying countries also presented information to support this view and subsequently supplied more specifics to OGJ in response to questions. This paper discusses this information. Trends in Africa, Australia, North America, and South America are forecast.

  9. Opportunities for Automated Demand Response in California Agricultural Irrigation

    SciTech Connect (OSTI)

    Olsen, Daniel; Aghajanzadeh, Arian; McKane, Aimee

    2015-08-01

    Pumping water for agricultural irrigation represents a significant share of California’s annual electricity use and peak demand. It also represents a large source of potential flexibility, as farms possess a form of storage in their wetted soil. By carefully modifying their irrigation schedules, growers can participate in demand response without adverse effects on their crops. This report describes the potential for participation in demand response and automated demand response by agricultural irrigators in California, as well as barriers to widespread participation. The report first describes the magnitude, timing, location, purpose, and manner of energy use in California. Typical on-­farm controls are discussed, as well as common impediments to participation in demand response and automated demand response programs. Case studies of demand response programs in California and across the country are reviewed, and their results along with overall California demand estimates are used to estimate statewide demand response potential. Finally, recommendations are made for future research that can enhance the understanding of demand response potential in this industry.

  10. An Optimized Autoregressive Forecast Error Generator for Wind and Load Uncertainty Study

    SciTech Connect (OSTI)

    De Mello, Phillip; Lu, Ning; Makarov, Yuri V.

    2011-01-17

    This paper presents a first-order autoregressive algorithm to generate real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast errors. The methodology aims at producing random wind and load forecast time series reflecting the autocorrelation and cross-correlation of historical forecast data sets. Five statistical characteristics are considered: the means, standard deviations, autocorrelations, and cross-correlations. A stochastic optimization routine is developed to minimize the differences between the statistical characteristics of the generated time series and the targeted ones. An optimal set of parameters are obtained and used to produce the RT, HA, and DA forecasts in due order of succession. This method, although implemented as the first-order regressive random forecast error generator, can be extended to higher-order. Results show that the methodology produces random series with desired statistics derived from real data sets provided by the California Independent System Operator (CAISO). The wind and load forecast error generator is currently used in wind integration studies to generate wind and load inputs for stochastic planning processes. Our future studies will focus on reflecting the diurnal and seasonal differences of the wind and load statistics and implementing them in the random forecast generator.

  11. Demand Response Technology Roadmap A

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

    meetings and workshops convened to develop content for the Demand Response Technology Roadmap. The project team has developed this companion document in the interest of providing...

  12. Demand for superpremium needle cokes on upswing

    SciTech Connect (OSTI)

    Acciarri, J.A.; Stockman, G.H. )

    1989-12-01

    The authors discuss how recent supply shortages of super-premium quality needle cokes, plus the expectation of increased shortfalls in the future, indicate that refiners should consider upgrading their operations to fill these demands. Calcined, super-premium needle cokes are currently selling for as much as $550/metric ton, fob producer, and increasing demand will continue the upward push of the past year. Needle coke, in its calcined form, is the major raw material in the manufacture of graphite electrodes. Used in steelmaking, graphite electrodes are the electrical conductors that supply the heat source, through arcing electrode column tips, to electric arc steel furnaces. Needle coke is commercially available in three grades - super premium, premium, and intermediate. Super premium is used to produce electrodes for the most severe electric arc furnace steelmaking applications, premium for electrodes destined to less severe operations, and intermediate for even less critical needs.

  13. DemandDirect | Open Energy Information

    Open Energy Info (EERE)

    DemandDirect Place: Woodbury, Connecticut Zip: 6798 Sector: Efficiency, Renewable Energy, Services Product: DemandDirect provides demand response, energy efficiency, load...

  14. Market and energy demand analysis of a US maglev system

    SciTech Connect (OSTI)

    Vyas, A.D.; Rote, D.M.

    1993-06-01

    High-speed magnetically levitated (maglev) vehicles can provide an alternative mode of transportation for intercity travel, particularly for short- and medium-distance trips between 100 to 600 mi (160 and 960 km). The patterns of growth and the underlying factors affecting that growth In the year 2010 are evaluated to determine the magnitude of US Intercity travel that would become the basis for maglev demand. A methodology that is sensitive to the travelers` socioeconomic attributes was developed to Forecast intercity travel. Travel between 78 major metropolitan areas by air and highway modes is projected, and 12 high-density travel corridors are Identified and selected. The potential for a maglev system to substitute for part or that travel is calculated by using a model that estimates the extent of diversion from highway and air to maglev. Energy demand is estimated on the basis of energy usage during acceleration and cruise phases for each corridor and corridor connections.

  15. Market and energy demand analysis of a US maglev system

    SciTech Connect (OSTI)

    Vyas, A.D.; Rote, D.M.

    1993-01-01

    High-speed magnetically levitated (maglev) vehicles can provide an alternative mode of transportation for intercity travel, particularly for short- and medium-distance trips between 100 to 600 mi (160 and 960 km). The patterns of growth and the underlying factors affecting that growth In the year 2010 are evaluated to determine the magnitude of US Intercity travel that would become the basis for maglev demand. A methodology that is sensitive to the travelers' socioeconomic attributes was developed to Forecast intercity travel. Travel between 78 major metropolitan areas by air and highway modes is projected, and 12 high-density travel corridors are Identified and selected. The potential for a maglev system to substitute for part or that travel is calculated by using a model that estimates the extent of diversion from highway and air to maglev. Energy demand is estimated on the basis of energy usage during acceleration and cruise phases for each corridor and corridor connections.

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

    SciTech Connect (OSTI)

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

    2013-11-01

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

  17. China, India demand cushions prices

    SciTech Connect (OSTI)

    Boyle, M.

    2006-11-15

    Despite the hopes of coal consumers, coal prices did not plummet in 2006 as demand stayed firm. China and India's growing economies, coupled with solid supply-demand fundamentals in North America and Europe, and highly volatile prices for alternatives are likely to keep physical coal prices from wide swings in the coming year.

  18. 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

  19. Demand Response for Ancillary Services

    SciTech Connect (OSTI)

    Alkadi, Nasr E; Starke, Michael R

    2013-01-01

    Many demand response resources are technically capable of providing ancillary services. In some cases, they can provide superior response to generators, as the curtailment of load is typically much faster than ramping thermal and hydropower plants. Analysis and quantification of demand response resources providing ancillary services is necessary to understand the resources economic value and impact on the power system. Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and illustrate a methodology to construct detailed temporal and spatial representations of the demand response resource and to examine how to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to translate the technical potential for demand response providing ancillary services into a realizable potential.

  20. Automated Demand Response and Commissioning

    SciTech Connect (OSTI)

    Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

    2005-04-01

    This paper describes the results from the second season of research to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve the electric grid reliability and manage electricity costs. Fully-Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. We refer to this as Auto-DR. The evaluation of the control and communications must be properly configured and pass through a set of test stages: Readiness, Approval, Price Client/Price Server Communication, Internet Gateway/Internet Relay Communication, Control of Equipment, and DR Shed Effectiveness. New commissioning tests are needed for such systems to improve connecting demand responsive building systems to the electric grid demand response systems.

  1. Demand-Side Response from Industrial Loads

    SciTech Connect (OSTI)

    Starke, Michael R; Alkadi, Nasr E; Letto, Daryl; Johnson, Brandon; Dowling, Kevin; George, Raoule; Khan, Saqib

    2013-01-01

    Through a research study funded by the Department of Energy, Smart Grid solutions company ENBALA Power Networks along with the Oak Ridge National Laboratory (ORNL) have geospatially quantified the potential flexibility within industrial loads to leverage their inherent process storage to help support the management of the electricity grid. The study found that there is an excess of 12 GW of demand-side load flexibility available in a select list of top industrial facilities in the United States. Future studies will expand on this quantity of flexibility as more in-depth analysis of different industries is conducted and demonstrations are completed.

  2. Solar Forecast Improvement Project | Department of Energy

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

    NOAA also will provide advanced satellite products. INNOVATIONS NOAA is providing numerical weather prediction (NWP) modeling with new information that will help solar forecasts. ...

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

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

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

  4. 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...

  5. 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...

  6. Honeywell Demonstrates Automated Demand Response Benefits for...

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

    Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers Honeywell Demonstrates Automated Demand Response Benefits for Utility, ...

  7. Demand Response for Ancillary Services

    Broader source: Energy.gov [DOE]

    Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and implement a methodology to construct detailed temporal and spatial representations of demand response resources and to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to assess economic value of the realizable potential of demand response for ancillary services.

  8. Industrial Demand Module - NEMS Documentation

    Reports and Publications (EIA)

    2014-01-01

    Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Module. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code.

  9. Residential Demand Module - NEMS Documentation

    Reports and Publications (EIA)

    2014-01-01

    Model Documentation - Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

  10. 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 ...

  11. 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 ...

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

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

    Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits ... Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits ...

  13. Modeling and forecasting the distribution of Vibrio vulnificus...

    Office of Scientific and Technical Information (OSTI)

    Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay Citation Details In-Document Search Title: Modeling and forecasting the distribution of Vibrio ...

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

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

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

  15. Tribal Facilities Retrofits: Freeing Up Resources through Reduced Demand

    Energy Savers [EERE]

    up resources through reduced demand" Elias Duran - Facilities Manager ¡ Day to day operations of facilities ¡ Budget control over facilities ¡ Project needs for future space requirements ¡ Maintenance ¡ Capital improvements ¡ Brief history of the Tlingit & Haida Tribes ¡ Tour of our existing facilities ¡ Historical utility cost data ¡ Summary of Project Objectives ¡ Expected cost and emission reductions ¡ Strategic planning for future implementation Two separate Tribes United

  16. MODELING THE DEMAND FOR E85 IN THE UNITED STATES

    SciTech Connect (OSTI)

    Liu, Changzheng; Greene, David L

    2013-10-01

    How demand for E85 might evolve in the future in response to changing economics and policies is an important subject to include in the National Energy Modeling System (NEMS). This report summarizes a study to develop an E85 choice model for NEMS. Using the most recent data from the states of Minnesota, North Dakota, and Iowa, this study estimates a logit model that represents E85 choice as a function of prices of E10 and E85, as well as fuel availability of E85 relative to gasoline. Using more recent data than previous studies allows a better estimation of non-fleet demand and indicates that the price elasticity of E85 choice appears to be higher than previously estimated. Based on the results of the econometric analysis, a model for projecting E85 demand at the regional level is specified. In testing, the model produced plausible predictions of US E85 demand to 2040.

  17. NREL: Energy Analysis - dGen: Distributed Generation Market Demand Model

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

    The Distributed Generation Market Demand (dGen) model is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The dGen model builds on and provides significant advances over NREL's deprecated Solar Deployment System (SolarDS) model. The dGen model can help develop deployment forecasts for distributed resources,

  18. Home Network Technologies and Automating Demand Response

    SciTech Connect (OSTI)

    McParland, Charles

    2009-12-01

    Over the past several years, interest in large-scale control of peak energy demand and total consumption has increased. While motivated by a number of factors, this interest has primarily been spurred on the demand side by the increasing cost of energy and, on the supply side by the limited ability of utilities to build sufficient electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in electricity use through the use of price incentives. DR systems are also be design to shift or curtail energy demand at critical times when the generation, transmission, and distribution systems (i.e. the 'grid') are threatened with instabilities. To be effectively deployed on a large-scale, these proposed DR systems need to be automated. Automation will require robust and efficient data communications infrastructures across geographically dispersed markets. The present availability of widespread Internet connectivity and inexpensive, reliable computing hardware combined with the growing confidence in the capabilities of distributed, application-level communications protocols suggests that now is the time for designing and deploying practical systems. Centralized computer systems that are capable of providing continuous signals to automate customers reduction of power demand, are known as Demand Response Automation Servers (DRAS). The deployment of prototype DRAS systems has already begun - with most initial deployments targeting large commercial and industrial (C & I) customers. An examination of the current overall energy consumption by economic sector shows that the C & I market is responsible for roughly half of all energy consumption in the US. On a per customer basis, large C & I customers clearly have the most to offer - and to gain - by participating in DR programs to reduce peak demand. And, by concentrating on a small number of relatively sophisticated energy consumers, it has been possible to improve the DR 'state of the art' with a manageable commitment of technical resources on both the utility and consumer side. Although numerous C & I DR applications of a DRAS infrastructure are still in either prototype or early production phases, these early attempts at automating DR have been notably successful for both utilities and C & I customers. Several factors have strongly contributed to this success and will be discussed below. These successes have motivated utilities and regulators to look closely at how DR programs can be expanded to encompass the remaining (roughly) half of the state's energy load - the light commercial and, in numerical terms, the more important residential customer market. This survey examines technical issues facing the implementation of automated DR in the residential environment. In particular, we will look at the potential role of home automation networks in implementing wide-scale DR systems that communicate directly to individual residences.

  19. U.S. Coal Supply and Demand

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

    Coal > U.S. Coal Supply and Demand > U.S. Coal Supply and Demand U.S. Coal Supply and Demand 2010 Review (entire report also available in printer-friendly format ) Previous ...

  20. Promising Technology: Demand Control Ventilation

    Broader source: Energy.gov [DOE]

    Demand control ventilation (DCV) measures carbon dioxide concentrations in return air or other strategies to measure occupancy, and accurately matches the ventilation requirement. This system reduces ventilation when spaces are vacant or at lower than peak occupancy. When ventilation is reduced, energy savings are accrued because it is not necessary to heat, cool, or dehumidify as much outside air.

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  2. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  4. 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...

  5. Demand Management Institute (DMI) | Open Energy Information

    Open Energy Info (EERE)

    Demand Management Institute (DMI) Jump to: navigation, search Name: Demand Management Institute (DMI) Address: 35 Walnut Street Place: Wellesley, Massachusetts Zip: 02481 Region:...

  6. Generating Demand for Multifamily Building Upgrades | Department...

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

    Generating Demand for Multifamily Building Upgrades Generating Demand for Multifamily Building Upgrades Better Buildings Residential Network Peer Exchange Call Series: Generating...

  7. Marketing & Driving Demand: Social Media Tools & Strategies ...

    Office of Environmental Management (EM)

    Marketing & Driving Demand: Social Media Tools & Strategies - January 16, 2011 (Text Version) Marketing & Driving Demand: Social Media Tools & Strategies - January 16, 2011 (Text...

  8. Demand Response - Policy | Department of Energy

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

    Demand Response - Policy Demand Response - Policy Since its inception, the Office of Electricity Delivery and Energy Reliability (OE) has been committed to modernizing the nation's ...

  9. 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....

  10. 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...

  11. Current Status and Future Scenarios of Residential Building Energy Consumption in China

    SciTech Connect (OSTI)

    Zhou, Nan; Nishida, Masaru; Gao, Weijun

    2008-12-01

    China's rapid economic expansion has propelled it into the ranks of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. Even though the rapid growth is largely attributable to heavy industry, this in turn is driven by rapid urbanization process, by construction materials and equipment produced for use in buildings. Residential energy is mostly used in urban areas, where rising incomes have allowed acquisition of home appliances, as well as increased use of heating in southern China. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modeling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities.

  12. NREL: Resource Assessment and Forecasting - Research Staff

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

    Research Staff NREL's resource assessment and forecasting research staff provides expertise in renewable energy measurement and instrumentation through NREL's Power Systems Engineering Center. Photo not available Linda Crow - Administrative Associate B.S. Environmental Studies, The Evergreen State College Linda currently works for the Resource Assessment and Forecasting group as their administrative support. She has worked with scientists at the Office of Science at the Air Force Academy and at

  13. The alchemy of demand response: turning demand into supply

    SciTech Connect (OSTI)

    Rochlin, Cliff

    2009-11-15

    Paying customers to refrain from purchasing products they want seems to run counter to the normal operation of markets. Demand response should be interpreted not as a supply-side resource but as a secondary market that attempts to correct the misallocation of electricity among electric users caused by regulated average rate tariffs. In a world with costless metering, the DR solution results in inefficiency as measured by deadweight losses. (author)

  14. Industrial demand side management: A status report

    SciTech Connect (OSTI)

    Hopkins, M.F.; Conger, R.L.; Foley, T.J.

    1995-05-01

    This report provides an overview of and rationale for industrial demand side management (DSM) programs. Benefits and barriers are described, and data from the Manufacturing Energy Consumption Survey are used to estimate potential energy savings in kilowatt hours. The report presents types and examples of programs and explores elements of successful programs. Two in-depth case studies (from Boise Cascade and Eli Lilly and Company) illustrate two types of effective DSM programs. Interviews with staff from state public utility commissions indicate the current thinking about the status and future of industrial DSM programs. A comprehensive bibliography is included, technical assistance programs are listed and described, and a methodology for evaluating potential or actual savings from projects is delineated.

  15. Addressing Energy Demand through Demand Response. International Experiences and Practices

    SciTech Connect (OSTI)

    Shen, Bo; Ghatikar, Girish; Ni, Chun Chun; Dudley, Junqiao; Martin, Phil; Wikler, Greg

    2012-06-01

    Demand response (DR) is a load management tool which provides a cost-effective alternative to traditional supply-side solutions to address the growing demand during times of peak electrical load. According to the US Department of Energy (DOE), demand response reflects “changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized.” 1 The California Energy Commission (CEC) defines DR as “a reduction in customers’ electricity consumption over a given time interval relative to what would otherwise occur in response to a price signal, other financial incentives, or a reliability signal.” 2 This latter definition is perhaps most reflective of how DR is understood and implemented today in countries such as the US, Canada, and Australia where DR is primarily a dispatchable resource responding to signals from utilities, grid operators, and/or load aggregators (or DR providers).

  16. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-01-01

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

  17. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-12-31

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

  18. Demand for petrochem feedstock to buoy world LPG industry

    SciTech Connect (OSTI)

    Not Available

    1992-05-18

    This paper reports that use of liquefied petroleum gas as petrochemical feedstock will increase worldwide, providing major growth opportunities for LPG producers. World exports of liquefied petroleum gas will increase more slowly than production as producers choose to use LPG locally as chemical feedstock and export in value added forms such as polyethylene. So predicts Poten and Partners Inc., New York. Poten forecasts LPG production in exporting countries will jump to 95 million tons in 2010 from 45 million tons in 1990. However, local and regional demand will climb to 60 million tons/year from 23 million tons/year during the same period. So supplies available for export will rise to 35 million tons in 2010 from 22 million tons in 1990.

  19. Opportunities for Automated Demand Response in California’s Dairy Processing Industry

    SciTech Connect (OSTI)

    Homan, Gregory K.; Aghajanzadeh, Arian; McKane, Aimee

    2015-08-30

    During periods of peak electrical demand on the energy grid or when there is a shortage of supply, the stability of the grid may be compromised or the cost of supplying electricity may rise dramatically, respectively. Demand response programs are designed to mitigate the severity of these problems and improve reliability by reducing the demand on the grid during such critical times. In 2010, the Demand Response Research Center convened a group of industry experts to suggest potential industries that would be good demand response program candidates for further review. The dairy industry was suggested due to the perception that the industry had suitable flexibility and automatic controls in place. The purpose of this report is to provide an initial description of the industry with regard to demand response potential, specifically automated demand response. This report qualitatively describes the potential for participation in demand response and automated demand response by dairy processing facilities in California, as well as barriers to widespread participation. The report first describes the magnitude, timing, location, purpose, and manner of energy use. Typical process equipment and controls are discussed, as well as common impediments to participation in demand response and automated demand response programs. Two case studies of demand response at dairy facilities in California and across the country are reviewed. Finally, recommendations are made for future research that can enhance the understanding of demand response potential in this industry.

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

    SciTech Connect (OSTI)

    Das, S.

    1991-12-01

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

  1. 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.

  2. 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.

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

    SciTech Connect (OSTI)

    Tutt, T.; Flory, J.

    1995-05-01

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

  4. Demand Response - Policy | Department of Energy

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

    Demand Response - Policy Demand Response - Policy Since its inception, the Office of Electricity Delivery and Energy Reliability (OE) has been committed to modernizing the nation's electricity delivery infrastructure to assure consumers a robust, reliable electric power system that meets their increasing demand for energy. OE's mission includes assisting states and regions in developing policies that decrease demand on existing energy infrastructure. Appropriate cost-effective demand response

  5. Energy for the Future

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

    Energy for the Future

  6. Tool Improves Electricity Demand Predictions to Make More Room for Renewables

    Broader source: Energy.gov [DOE]

    A new tool is available to help integrate wind and solar power into the electric grid by predicting the ranges in which power demand could increase or decrease in the immediate future.

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

    SciTech Connect (OSTI)

    Edwards, J.D.

    1997-08-01

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

  8. Demand Response Valuation Frameworks Paper

    SciTech Connect (OSTI)

    Heffner, Grayson

    2009-02-01

    While there is general agreement that demand response (DR) is a valued component in a utility resource plan, there is a lack of consensus regarding how to value DR. Establishing the value of DR is a prerequisite to determining how much and what types of DR should be implemented, to which customers DR should be targeted, and a key determinant that drives the development of economically viable DR consumer technology. Most approaches for quantifying the value of DR focus on changes in utility system revenue requirements based on resource plans with and without DR. This ''utility centric'' approach does not assign any value to DR impacts that lower energy and capacity prices, improve reliability, lower system and network operating costs, produce better air quality, and provide improved customer choice and control. Proper valuation of these benefits requires a different basis for monetization. The review concludes that no single methodology today adequately captures the wide range of benefits and value potentially attributed to DR. To provide a more comprehensive valuation approach, current methods such as the Standard Practice Method (SPM) will most likely have to be supplemented with one or more alternative benefit-valuation approaches. This report provides an updated perspective on the DR valuation framework. It includes an introduction and four chapters that address the key elements of demand response valuation, a comprehensive literature review, and specific research recommendations.

  9. ECIS-Princeton Power Systems, Inc.: Demand Response Inverter

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

    Princeton Power Systems, Inc.: Demand Response Inverter - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel Cycle Defense

  10. 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 ...

  11. 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...

  12. Energy demand and population changes

    SciTech Connect (OSTI)

    Allen, E.L.; Edmonds, J.A.

    1980-12-01

    Since World War II, US energy demand has grown more rapidly than population, so that per capita consumption of energy was about 60% higher in 1978 than in 1947. Population growth and the expansion of per capita real incomes have led to a greater use of energy. The aging of the US population is expected to increase per capita energy consumption, despite the increase in the proportion of persons over 65, who consume less energy than employed persons. The sharp decline in the population under 18 has led to an expansion in the relative proportion of population in the prime-labor-force age groups. Employed persons are heavy users of energy. The growth of the work force and GNP is largely attributable to the growing participation of females. Another important consequence of female employment is the growth in ownership of personal automobiles. A third factor pushing up labor-force growth is the steady influx of illegal aliens.

  13. Coordination of Energy Efficiency and Demand Response

    SciTech Connect (OSTI)

    none,

    2010-01-01

    Summarizes existing research and discusses current practices, opportunities, and barriers to coordinating energy efficiency and demand response programs.

  14. 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...

  15. 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

  16. 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.

  17. 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.

  18. 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)

  19. Uncertainty Reduction in Power Generation Forecast Using Coupled

    Office of Scientific and Technical Information (OSTI)

    Wavelet-ARIMA (Conference) | SciTech Connect Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA Citation Details In-Document Search Title: Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of

  20. 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.

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

    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 Preprint Jie Zhang 1 , Bri-Mathias Hodge 1 , Siyuan Lu 2 , Hendrik F. Hamann 2 , Brad Lehman 3 , Joseph Simmons 4 , Edwin Campos 5 , and Venkat Banunarayanan 6 1 National Renewable Energy Laboratory 2 IBM TJ Watson Research Center 3 Northeastern University 4 University of Arizona 5 Argonne National Laboratory 6 U.S. Department of Energy Presented at the IEEE Power and Energy Society General Meeting Denver,

  2. 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.

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

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

  4. 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.

  5. Hawaii demand-side management resource assessment. Final report: DSM opportunity report

    SciTech Connect (OSTI)

    1995-08-01

    The Hawaii Demand-Side Management Resource Assessment was the fourth of seven projects in the Hawaii Energy Strategy (HES) program. HES was designed by the Department of Business, Economic Development, and Tourism (DBEDT) to produce an integrated energy strategy for the State of Hawaii. The purpose of Project 4 was to develop a comprehensive assessment of Hawaii`s demand-side management (DSM) resources. To meet this objective, the project was divided into two phases. The first phase included development of a DSM technology database and the identification of Hawaii commercial building characteristics through on-site audits. These Phase 1 products were then used in Phase 2 to identify expected energy impacts from DSM measures in typical residential and commercial buildings in Hawaii. The building energy simulation model DOE-2.1E was utilized to identify the DSM energy impacts. More detailed information on the typical buildings and the DOE-2.1E modeling effort is available in Reference Volume 1, ``Building Prototype Analysis``. In addition to the DOE-2.1E analysis, estimates of residential and commercial sector gas and electric DSM potential for the four counties of Honolulu, Hawaii, Maui, and Kauai through 2014 were forecasted by the new DBEDT DSM Assessment Model. Results from DBEDTs energy forecasting model, ENERGY 2020, were linked with results from DOE-2.1E building energy simulation runs and estimates of DSM measure impacts, costs, lifetime, and anticipated market penetration rates in the DBEDT DSM Model. Through its algorithms, estimates of DSM potential for each forecast year were developed. Using the load shape information from the DOE-2.1E simulation runs, estimates of electric peak demand impacts were developed. 10 figs., 55 tabs.

  6. Providing Reliability Services through Demand Response: A Prelimnary Evaluation of the Demand Response Capabilities of Alcoa Inc.

    SciTech Connect (OSTI)

    Starke, Michael R; Kirby, Brendan J; Kueck, John D; Todd, Duane; Caulfield, Michael; Helms, Brian

    2009-02-01

    Demand response is the largest underutilized reliability resource in North America. Historic demand response programs have focused on reducing overall electricity consumption (increasing efficiency) and shaving peaks but have not typically been used for immediate reliability response. Many of these programs have been successful but demand response remains a limited resource. The Federal Energy Regulatory Commission (FERC) report, 'Assessment of Demand Response and Advanced Metering' (FERC 2006) found that only five percent of customers are on some form of demand response program. Collectively they represent an estimated 37,000 MW of response potential. These programs reduce overall energy consumption, lower green house gas emissions by allowing fossil fuel generators to operate at increased efficiency and reduce stress on the power system during periods of peak loading. As the country continues to restructure energy markets with sophisticated marginal cost models that attempt to minimize total energy costs, the ability of demand response to create meaningful shifts in the supply and demand equations is critical to creating a sustainable and balanced economic response to energy issues. Restructured energy market prices are set by the cost of the next incremental unit of energy, so that as additional generation is brought into the market, the cost for the entire market increases. The benefit of demand response is that it reduces overall demand and shifts the entire market to a lower pricing level. This can be very effective in mitigating price volatility or scarcity pricing as the power system responds to changing demand schedules, loss of large generators, or loss of transmission. As a global producer of alumina, primary aluminum, and fabricated aluminum products, Alcoa Inc., has the capability to provide demand response services through its manufacturing facilities and uniquely through its aluminum smelting facilities. For a typical aluminum smelter, electric power accounts for 30% to 40% of the factory cost of producing primary aluminum. In the continental United States, Alcoa Inc. currently owns and/or operates ten aluminum smelters and many associated fabricating facilities with a combined average load of over 2,600 MW. This presents Alcoa Inc. with a significant opportunity to respond in areas where economic opportunities exist to help mitigate rising energy costs by supplying demand response services into the energy system. This report is organized into seven chapters. The first chapter is the introduction and discusses the intention of this report. The second chapter contains the background. In this chapter, topics include: the motivation for Alcoa to provide demand response; ancillary service definitions; the basics behind aluminum smelting; and a discussion of suggested ancillary services that would be particularly useful for Alcoa to supply. Chapter 3 is concerned with the independent system operator, the Midwest ISO. Here the discussion examines the evolving Midwest ISO market structure including specific definitions, requirements, and necessary components to provide ancillary services. This section is followed by information concerning the Midwest ISO's classifications of demand response parties. Chapter 4 investigates the available opportunities at Alcoa's Warrick facility. Chapter 5 involves an in-depth discussion of the regulation service that Alcoa's Warrick facility can provide and the current interactions with Midwest ISO. Chapter 6 reviews future plans and expectations for Alcoa providing ancillary services into the market. Last, chapter 7, details the conclusion and recommendations of this paper.

  7. Outlook for Biomass Ethanol Production and Demand

    Reports and Publications (EIA)

    2000-01-01

    This paper presents a midterm forecast for biomass ethanol production under three different technology cases for the period 2000 to 2020, based on projections developed from the Energy Information Administration's National Energy Modeling System. An overview of cellulose conversion technology and various feedstock options and a brief history of ethanol usage in the United States are also presented.

  8. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

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

    2014-12-30

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

  9. 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

  10. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

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

    2014-11-13

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

  11. 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.

  12. NCEP_Demand_Response_Draft_111208.indd

    Energy Savers [EERE]

    National Council on Electricity Policy: Electric Transmission Series for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials Prepared by the U.S. Demand Response Coordinating Committee for The National Council on Electricity Policy Fall 2008 i National Council on Electricity Policy: Electric

  13. 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.

  14. Demand Response in the ERCOT Markets

    SciTech Connect (OSTI)

    Patterson, Mark

    2011-10-25

    ERCOT grid serves 85% of Texas load over 40K+ miles transmission line. Demand response: voluntary load response, load resources, controllable load resources, and emergency interruptible load service.

  15. Reducing Logistics Footprints and Replenishment Demands: Nano...

    Office of Scientific and Technical Information (OSTI)

    Water Treatment Citation Details In-Document Search Title: Reducing Logistics Footprints and Replenishment Demands: Nano-engineered Silica Aerogels a Proven Method for Water ...

  16. Geographically Based Hydrogen Demand and Infrastructure Rollout...

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

    Rollout Scenario Analysis Geographically Based Hydrogen Demand and Infrastructure Rollout Scenario Analysis Presentation by Margo Melendez at the 2010-2025 Scenario Analysis for ...

  17. Marketing & Driving Demand Collaborative - Social Media Tools...

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

    Marketing & Driving Demand Collaborative - Social Media Tools & Strategies Presentation slides from the Better Buildings webinar on January 6, 2011. PDF icon Marketing & Driving ...

  18. Fabricate-on-Demand Vacuum Insulating Glazings

    Broader source: Energy.gov [DOE]

    PPG is working to design a fabricate-on-demand process to overcome the cost and supply chain issues preventing widespread adoption of vacuum insulating glazings (VIGs).

  19. BPA, Energy Northwest launch demand response pilot

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

    BPA-Energy-Northwest-launch-demand-response-pilot Sign In About | Careers | Contact | Investors | bpa.gov Search News & Us Expand News & Us Projects & Initiatives Expand...

  20. Integration of Demand Side Management, Distributed Generation...

    Open Energy Info (EERE)

    various aspects of demand response, distributed generation, smart grid and energy storage. Annex 9 is a list of pilot programs and case studies, with links to those...

  1. Demand Response and Energy Storage Integration Study

    Broader source: Energy.gov [DOE]

    Demand response and energy storage resources present potentially important sources of bulk power system services that can aid in integrating variable renewable generation. While renewable...

  2. Demand Response (transactional control) - Energy Innovation Portal

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

    Energy Analysis Energy Analysis Electricity Transmission Electricity Transmission Find More Like This Return to Search Demand Response (transactional control) Pacific Northwest ...

  3. Distributed Automated Demand Response - Energy Innovation Portal

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

    Energy Analysis Energy Analysis Electricity Transmission Electricity Transmission Find More Like This Return to Search Distributed Automated Demand Response Lawrence Livermore ...

  4. Energy Efficiency, Demand Response, and Volttron

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

    ENERGY EFFICIENCY, DEMAND RESPONSE, AND VOLTTRON Presented by Justin Sipe SEEMINGLY SIMPLE STATEMENTS Utilities need more capacity to handle growth on the grid ...

  5. Geographically Based Hydrogen Consumer Demand and Infrastructure...

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

    Geographically Based Hydrogen Consumer Demand and Infrastructure Analysis Final Report M. Melendez and A. Milbrandt Technical Report NRELTP-540-40373 October 2006 NREL is operated...

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-01-20

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

  7. Integration of Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect (OSTI)

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

    2010-04-20

    In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (CAISO) real life data have shown the effectiveness and efficiency of the proposed approach.

  8. A Full Demand Response Model in Co-Optimized Energy and

    SciTech Connect (OSTI)

    Liu, Guodong; Tomsovic, Kevin

    2014-01-01

    It has been widely accepted that demand response will play an important role in reliable and economic operation of future power systems and electricity markets. Demand response can not only influence the prices in the energy market by demand shifting, but also participate in the reserve market. In this paper, we propose a full model of demand response in which demand flexibility is fully utilized by price responsive shiftable demand bids in energy market as well as spinning reserve bids in reserve market. A co-optimized day-ahead energy and spinning reserve market is proposed to minimize the expected net cost under all credible system states, i.e., expected total cost of operation minus total benefit of demand, and solved by mixed integer linear programming. Numerical simulation results on the IEEE Reliability Test System show effectiveness of this model. Compared to conventional demand shifting bids, the proposed full demand response model can further reduce committed capacity from generators, starting up and shutting down of units and the overall system operating costs.

  9. 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.

  10. Renewable Electricity Futures Study. Executive Summary

    SciTech Connect (OSTI)

    Mai, T.; Sandor, D.; Wiser, R.; Schneider, T.

    2012-12-01

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).

  11. Strategies for Demand Response in Commercial Buildings

    SciTech Connect (OSTI)

    Watson, David S.; Kiliccote, Sila; Motegi, Naoya; Piette, Mary Ann

    2006-06-20

    This paper describes strategies that can be used in commercial buildings to temporarily reduce electric load in response to electric grid emergencies in which supplies are limited or in response to high prices that would be incurred if these strategies were not employed. The demand response strategies discussed herein are based on the results of three years of automated demand response field tests in which 28 commercial facilities with an occupied area totaling over 11 million ft{sup 2} were tested. Although the demand response events in the field tests were initiated remotely and performed automatically, the strategies used could also be initiated by on-site building operators and performed manually, if desired. While energy efficiency measures can be used during normal building operations, demand response measures are transient; they are employed to produce a temporary reduction in demand. Demand response strategies achieve reductions in electric demand by temporarily reducing the level of service in facilities. Heating ventilating and air conditioning (HVAC) and lighting are the systems most commonly adjusted for demand response in commercial buildings. The goal of demand response strategies is to meet the electric shed savings targets while minimizing any negative impacts on the occupants of the buildings or the processes that they perform. Occupant complaints were minimal in the field tests. In some cases, ''reductions'' in service level actually improved occupant comfort or productivity. In other cases, permanent improvements in efficiency were discovered through the planning and implementation of ''temporary'' demand response strategies. The DR strategies that are available to a given facility are based on factors such as the type of HVAC, lighting and energy management and control systems (EMCS) installed at the site.

  12. Coordination of Energy Efficiency and Demand Response

    SciTech Connect (OSTI)

    Goldman, Charles; Reid, Michael; Levy, Roger; Silverstein, Alison

    2010-01-29

    This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025. Improving energy efficiency in our homes, businesses, schools, governments, and industries - which consume more than 70 percent of the nation's natural gas and electricity - is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that 'the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW' by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

  13. Effects of the Financial Crisis on Photovoltaics: An Analysis of Changes in Market Forecasts from 2008 to 2009

    SciTech Connect (OSTI)

    Bartlett, J. E.; Margolis, R. M.; Jennings, C. E.

    2009-09-01

    To examine how the financial crisis has impacted expectations of photovoltaic production, demand and pricing over the next several years, we surveyed the market forecasts of industry analysts that had issued projections in 2008 and 2009. We find that the financial crisis has had a significant impact on the PV industry, primarily through increasing the cost and reducing the availability of investment into the sector. These effects have been more immediately experienced by PV installations than by production facilities, due to the different types and duration of investments, and thus PV demand has been reduced by a greater proportion than PV production. By reducing demand more than production, the financial crisis has accelerated previously expected PV overcapacity and resulting price declines.

  14. Demand Response Resources for Energy and Ancillary Services (Presentation)

    SciTech Connect (OSTI)

    Hummon, M.

    2014-04-01

    Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind an solar power generation. However, DR in grid models is limited by data availability and modeling complexity. This presentation focuses on the co-optimization of DR resources to provide energy and ancillary services in a production cost model of the Colorado test system. We assume each DR resource can provide energy services by either shedding load or shifting its use between different times, as well as operating

  15. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

    Complex Terrain | Department of Energy for 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

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

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

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

  17. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical

    Office of Scientific and Technical Information (OSTI)

    Modelling Approach (Journal Article) | SciTech Connect Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach Citation Details In-Document Search Title: Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the

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

    Office of Scientific and Technical Information (OSTI)

    (BNL) Field Campaign Report (Technical Report) | SciTech Connect SciTech Connect Search Results Technical Report: Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report Citation Details In-Document Search Title: Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report The Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) [http://www.arm.gov/campaigns/osc2013rwpcf]

  19. Energy Conservation Program: Data Collection and Comparison with Forecasted

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

    Unit Sales for Five Lamp Types, Notice of Data Availability | Department of Energy Data Collection and Comparison with Forecasted 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 Data Availability This document is the notice of data availability for Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types. PDF icon

  20. Global Energy Futures Model

    Energy Science and Technology Software Center (OSTI)

    2004-01-01

    The Global Energy Futures Model (GEFM) is a demand-based, gross domestic product (GDP)-driven, dynamic simulation tool that provides an integrated framework to model key aspects of energy, nuclear-materials storage and disposition, environmental effluents from fossil and non fossil energy and global nuclear-materials management. Based entirely on public source data, it links oil, natural gas, coal, nuclear and renewable energy dynamically to greenhouse-gas emissions and 13 other measures of environmental impact. It includes historical data frommore » 1990 to 2000, is benchmarked to the DOE/EIA/IEO 2002 [5] Reference Case for 2000 to 2020, and extrapolates energy demand through the year 2050. The GEFM is globally integrated, and breaks out five regions of the world: United States of America (USA), the Peoples Republic of China (China), the former Soviet Union (FSU), the Organization for Economic Cooperation and Development (OECD) nations excluding the USA (other industrialized countries), and the rest of the world (ROW) (essentially the developing world). The GEFM allows the user to examine a very wide range of what ir scenarios through 2050 and to view the potential effects across widely dispersed, but interrelated areas. The authors believe that this high-level learning tool will help to stimulate public policy debate on energy, environment, economic and national security issues.« less

  1. The role of actinide burning and the Integral Fast Reactor in the future of nuclear power

    SciTech Connect (OSTI)

    Hollaway, W.R.; Lidsky, L.M.; Miller, M.M.

    1990-12-01

    A preliminary assessment is made of the potential role of actinide burning and the Integral Fast Reactor (IFR) in the future of nuclear power. The development of a usable actinide burning strategy could be an important factor in the acceptance and implementation of a next generation of nuclear power. First, the need for nuclear generating capacity is established through the analysis of energy and electricity demand forecasting models which cover the spectrum of bias from anti-nuclear to pro-nuclear. The analyses take into account the issues of global warming and the potential for technological advances in energy efficiency. We conclude, as do many others, that there will almost certainly be a need for substantial nuclear power capacity in the 2000--2030 time frame. We point out also that any reprocessing scheme will open up proliferation-related questions which can only be assessed in very specific contexts. The focus of this report is on the fuel cycle impacts of actinide burning. Scenarios are developed for the deployment of future nuclear generating capacity which exploit the advantages of actinide partitioning and actinide burning. Three alternative reactor designs are utilized in these future scenarios: The Light Water Reactor (LWR); the Modular Gas-Cooled Reactor (MGR); and the Integral Fast Reactor (FR). Each of these alternative reactor designs is described in some detail, with specific emphasis on their spent fuel streams and the back-end of the nuclear fuel cycle. Four separation and partitioning processes are utilized in building the future nuclear power scenarios: Thermal reactor spent fuel preprocessing to reduce the ceramic oxide spent fuel to metallic form, the conventional PUREX process, the TRUEX process, and pyrometallurgical reprocessing.

  2. 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.

  3. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    Title: 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory When considering the amount of shortwave radiation incident on a photovoltaic solar array and, ...

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

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

    These projects aim to improve the accuracy of solar forecasting that could increase penetration of solar power by enabling more certainty in power prediction from solar power ...

  5. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic...

    Office of Scientific and Technical Information (OSTI)

    Title: Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates ...

  6. 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.

  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. 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...

  9. 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...

  10. 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.

  11. Renewable Electricity Futures Study. Volume 1. Exploration of High-Penetration Renewable Electricity Futures

    SciTech Connect (OSTI)

    Hand, M. M.; Baldwin, S.; DeMeo, E.; Reilly, J. M.; Mai, T.; Arent, D.; Porro, G.; Meshek, M.; Sandor, D.

    2012-06-15

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%–90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/

  12. Electricity demand in a developing country. [Paraguay

    SciTech Connect (OSTI)

    Westley, G.D.

    1984-08-01

    This study analyzes the residential and commercial demand for electricity in ten regions in Paraguay for 1970-1977. Models that are both linear and nonlinear in the parameters are estimated. The nonlinear model takes advantage of prior information on the nature of the appliances being utilized and simultaneously deals with the demand discontinuities caused by appliance indivisibility. Three dynamic equations, including a novel cumulative adjustment model, all indicate rapid adjustment to desired appliance stock levels. Finally, the multiproduct surplus loss obtained from an estimated demand equation is used to measure the welfare cost of power outages. 15 references.

  13. Autonomous Demand Response for Primary Frequency Regulation

    SciTech Connect (OSTI)

    Donnelly, Matt; Trudnowski, Daniel J.; Mattix, S.; Dagle, Jeffery E.

    2012-02-28

    The research documented within this report examines the use of autonomous demand response to provide primary frequency response in an interconnected power grid. The work builds on previous studies in several key areas: it uses a large realistic model (i.e., the interconnection of the western United States and Canada); it establishes a set of metrics that can be used to assess the effectiveness of autonomous demand response; and it independently adjusts various parameters associated with using autonomous demand response to assess effectiveness and to examine possible threats or vulnerabilities associated with the technology.

  14. FERC sees huge potential for demand response

    SciTech Connect (OSTI)

    2010-04-15

    The FERC study concludes that U.S. peak demand can be reduced by as much as 188 GW -- roughly 20 percent -- under the most aggressive scenario. More moderate -- and realistic -- scenarios produce smaller but still significant reductions in peak demand. The FERC report is quick to point out that these are estimates of the potential, not projections of what could actually be achieved. The main varieties of demand response programs include interruptible tariffs, direct load control (DLC), and a number of pricing schemes.

  15. Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System

    SciTech Connect (OSTI)

    1998-01-01

    This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

  16. Electricity Demand Evolution Driven by Storm Motivated Population Movement

    SciTech Connect (OSTI)

    Allen, Melissa R; Fernandez, Steven J; Fu, Joshua S; Walker, Kimberly A

    2014-01-01

    Managing the risks posed by climate change to energy production and delivery is a challenge for communities worldwide. Sea Level rise and increased frequency and intensity of natural disasters due to sea surface temperature rise force populations to move locations, resulting in changing patterns of demand for infrastructure services. Thus, Infrastructures will evolve to accommodate new load centers while some parts of the network are underused, and these changes will create emerging vulnerabilities. Combining climate predictions and agent based population movement models shows promise for exploring the universe of these future population distributions and changes in coastal infrastructure configurations. In this work, we created a prototype agent based population distribution model and developed a methodology to establish utility functions that provide insight about new infrastructure vulnerabilities that might result from these patterns. Combining climate and weather data, engineering algorithms and social theory, we use the new Department of Energy (DOE) Connected Infrastructure Dynamics Models (CIDM) to examine electricity demand response to increased temperatures, population relocation in response to extreme cyclonic events, consequent net population changes and new regional patterns in electricity demand. This work suggests that the importance of established evacuation routes that move large populations repeatedly through convergence points as an indicator may be under recognized.

  17. Next Update: December 2011 Net Internal Demand

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

    Net Internal Demand (MW) Capacity Resources (MW) Capacity Margin (percent) Net Internal Demand (MW) Capacity Resources (MW) Capacity Margin (percent) Net Internal Demand (MW) Capacity Resources (MW) Capacity Margin (percent) Net Internal Demand (MW) Capacity Resources (MW) Capacity Margin (percent) 2005 746,470 882,125 15.4 45,950 50,200 8.5 38,266 46,792 18.2 57,402 72,258 20.6 2006 760,108 906,155 16.1 43,824 53,171 17.6 41,754 49,792 16.1 59,727 70,607 15.4 2007 768,061 946,631 18.9 46,434

  18. SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY

    Broader source: Energy.gov [DOE]

    As a city that experiences seasonal spikes in energy demand and accompanying energy bills, San Antonio, Texas, wanted to help homeowners and businesses reduce their energy use and save on energy...

  19. Solar in Demand | Department of Energy

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

    In case you missed it... This week, the Wall Street Journal published an article, "U.S. Solar-Panel Demand Expected to Double," highlighting the successes of the U.S. solar ...

  20. Demand Response and Energy Storage Integration Study

    Broader source: Energy.gov [DOE]

    This study is a multi-national laboratory effort to assess the potential value of demand response and energy storage to electricity systems with different penetration levels of variable renewable...

  1. Climate policy implications for agricultural water demand

    SciTech Connect (OSTI)

    Chaturvedi, Vaibhav; Hejazi, Mohamad I.; Edmonds, James A.; Clarke, Leon E.; Kyle, G. Page; Davies, Evan; Wise, Marshall A.; Calvin, Katherine V.

    2013-03-28

    Energy, water and land are scarce resources, critical to humans. Developments in each affect the availability and cost of the others, and consequently human prosperity. Measures to limit greenhouse gas concentrations will inevitably exact dramatic changes on energy and land systems and in turn alter the character, magnitude and geographic distribution of human claims on water resources. We employ the Global Change Assessment Model (GCAM), an integrated assessment model to explore the interactions of energy, land and water systems in the context of alternative policies to limit climate change to three alternative levels: 2.5 Wm-2 (445 ppm CO2-e), 3.5 Wm-2 (535 ppm CO2-e) and 4.5 Wm-2 (645 ppm CO2-e). We explore the effects of two alternative land-use emissions mitigation policy options—one which taxes terrestrial carbon emissions equally with fossil fuel and industrial emissions, and an alternative which only taxes fossil fuel and industrial emissions but places no penalty on land-use change emissions. We find that increasing populations and economic growth could be anticipated to almost triple demand for water for agricultural systems across the century even in the absence of climate policy. In general policies to mitigate climate change increase agricultural demands for water still further, though the largest changes occur in the second half of the century, under both policy regimes. The two policies examined profoundly affected both the sources and magnitudes of the increase in irrigation water demands. The largest increases in agricultural irrigation water demand occurred in scenarios where only fossil fuel emissions were priced (but not land-use change emission) and were primarily driven by rapid expansion in bioenergy production. In these scenarios water demands were large relative to present-day total available water, calling into question whether it would be physically possible to produce the associated biomass energy. We explored the potential of improved water delivery and irrigation system efficiencies. These could potentially reduce demands substantially. However, overall demands remained high under our fossil-fuel-only tax policy. In contrast, when all carbon was priced, increases in agricultural water demands were smaller than under the fossil-fuel-only policy and were driven primarily by increased demands for water by non-biomass crops such as rice. Finally we estimate the geospatial pattern of water demands and find that regions such as China, India and other countries in south and east Asia might be expected to experience greatest increases in water demands. 

  2. Measuring the capacity impacts of demand response

    SciTech Connect (OSTI)

    Earle, Robert; Kahn, Edward P.; Macan, Edo

    2009-07-15

    Critical peak pricing and peak time rebate programs offer benefits by increasing system reliability, and therefore, reducing capacity needs of the electric power system. These benefits, however, decrease substantially as the size of the programs grows relative to the system size. More flexible schemes for deployment of demand response can help address the decreasing returns to scale in capacity value, but more flexible demand response has decreasing returns to scale as well. (author)

  3. Expected international demand for woody and herbaceous feedstock

    SciTech Connect (OSTI)

    Lamers, Patrick; Jacobson, Jacob; Mohammad, Roni; Wright, Christopher

    2015-03-01

    The development of a U.S. bioenergy market and ultimately ‘bioeconomy’ has primarily been investigated with a national focus. Limited attention has been given to the potential impacts of international market developments. The goal of this project is to advance the current State of Technology of a single biorefinery to the global level providing quantitative estimates on how international markets may influence the domestic feedstock supply costs. The scope of the project is limited to feedstock that is currently available and new crops being developed to be used in a future U.S. bioeconomy including herbaceous residues (e.g., corn stover), woody biomass (e.g., pulpwood), and energy crops (e.g., switchgrass). The timeframe is set to the periods of 2022, 2030, and 2040 to align with current policy targets (e.g., the RFS2) and future updates of the Billion Ton data. This particular milestone delivers demand volumes for generic woody and herbaceous feedstocks for the main (net) importing regions along the above timeframes. The regional focus of the study is the European Union (EU), currently the largest demand region for U.S. pellets made from pulpwood and forest residues. The pellets are predominantly used in large-scale power plants (>5MWel) in the United Kingdom (UK), the Netherlands (NL), Belgium (BE), and Denmark (DK).

  4. Transportation Electrification Load Development For a Renewable Future Analysis

    SciTech Connect (OSTI)

    Markel, Tony; Mai, Trieu; Kintner-Meyer, Michael CW

    2010-09-30

    Electrification of the transportation sector offers the opportunity to significantly reduce petroleum consumption. The transportation sector accounts for 70% of US petroleum consumption. The transition to electricity as a transportation fuel will create a new load for electricity generation. In support of a recent US Department of Energy funded activity that analyzed a future generation scenario with high renewable energy technology contributions, a set of regional hourly load profiles for electrified vehicles were developed for the 2010 to 2050 timeframe. These load profiles with their underlying assumptions will be presented in this paper. The transportation electrical energy was determined using regional population forecast data, historical vehicle per capita data, and market penetration growth functions to determine the number of plug-in electric vehicles (PEVs) in each analysis region. Two market saturation scenarios of 30% of sales and 50% of sales of PEVs consuming on average {approx}6 kWh per day were considered. Results were generated for 3109 counties and were consolidated to 134 Power Control Areas (PCA) for the use NREL's's regional generation planning analysis tool ReEDS. PEV aggregate load profiles from previous work were combined with vehicle population data to generate hourly loads on a regional basis. A transition from consumer-controlled charging toward utility-controlled charging was assumed such that by 2050 approximately 45% of the transportation energy demands could be delivered across 4 daily time slices under optimal control from the utility perspective. No other literature has addressed the potential flexibility in energy delivery to electric vehicles in connection with a regional power generation study. This electrified transportation analysis resulted in an estimate for both the flexible load and fixed load shapes on a regional basis that may evolve under two PEV market penetration scenarios. EVS25 Copyright.

  5. Ethanol Demand in United States Gasoline Production

    SciTech Connect (OSTI)

    Hadder, G.R.

    1998-11-24

    The Oak Ridge National Laboratory (OWL) Refinery Yield Model (RYM) has been used to estimate the demand for ethanol in U.S. gasoline production in year 2010. Study cases examine ethanol demand with variations in world oil price, cost of competing oxygenate, ethanol value, and gasoline specifications. For combined-regions outside California summer ethanol demand is dominated by conventional gasoline (CG) because the premised share of reformulated gasoline (RFG) production is relatively low and because CG offers greater flexibility for blending high vapor pressure components like ethanol. Vapor pressure advantages disappear for winter CG, but total ethanol used in winter RFG remains low because of the low RFG production share. In California, relatively less ethanol is used in CG because the RFG production share is very high. During the winter in California, there is a significant increase in use of ethanol in RFG, as ethanol displaces lower-vapor-pressure ethers. Estimated U.S. ethanol demand is a function of the refiner value of ethanol. For example, ethanol demand for reference conditions in year 2010 is 2 billion gallons per year (BGY) at a refiner value of $1.00 per gallon (1996 dollars), and 9 BGY at a refiner value of $0.60 per gallon. Ethanol demand could be increased with higher oil prices, or by changes in gasoline specifications for oxygen content, sulfur content, emissions of volatile organic compounds (VOCS), and octane numbers.

  6. Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

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

    Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

    2015-02-14

    Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equationsmore » at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.« less

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

    SciTech Connect (OSTI)

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

    2014-11-01

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

  8. Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

    SciTech Connect (OSTI)

    Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

    2015-02-14

    Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equations at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.

  9. Climate, extreme heat, and electricity demand in California

    SciTech Connect (OSTI)

    Miller, N.L.; Hayhoe, K.; Jin, J.; Auffhammer, M.

    2008-04-01

    Climate projections from three atmosphere-ocean climate models with a range of low to mid-high temperature sensitivity forced by the Intergovernmental Panel for Climate Change SRES higher, middle, and lower emission scenarios indicate that, over the 21st century, extreme heat events for major cities in heavily air-conditioned California will increase rapidly. These increases in temperature extremes are projected to exceed the rate of increase in mean temperature, along with increased variance. Extreme heat is defined here as the 90 percent exceedance probability (T90) of the local warmest summer days under the current climate. The number of extreme heat days in Los Angeles, where T90 is currently 95 F (32 C), may increase from 12 days to as many as 96 days per year by 2100, implying current-day heat wave conditions may last for the entire summer, with earlier onset. Overall, projected increases in extreme heat under the higher A1fi emission scenario by 2070-2099 tend to be 20-30 percent higher than those projected under the lower B1 emission scenario, ranging from approximately double the historical number of days for inland California cities (e.g. Sacramento and Fresno), up to four times for previously temperate coastal cities (e.g. Los Angeles, San Diego). These findings, combined with observed relationships between high temperature and electricity demand for air-conditioned regions, suggest potential shortfalls in transmission and supply during T90 peak electricity demand periods. When the projected extreme heat and peak demand for electricity are mapped onto current availability, maintaining technology and population constant only for demand side calculations, we find the potential for electricity deficits as high as 17 percent. Similar increases in extreme heat days are suggested for other locations across the U.S. southwest, as well as for developing nations with rapidly increasing electricity demands. Electricity response to recent extreme heat events, such as the July 2006 heat wave in California, suggests that peak electricity demand will challenge current supply, as well as future planned supply capacities when population and income growth are taken into account.

  10. The Role of Demand Response in Default Service Pricing

    SciTech Connect (OSTI)

    Barbose, Galen; Goldman, Charles; Neenan, Bernie

    2005-11-09

    Dynamic retail pricing, especially real-time pricing (RTP), has been widely heralded as a panacea for providing much-needed demand response in electricity markets. However, in designing default service for competitive retail markets, demand response has been an afterthought, and in some cases not given any weight at all. But that may be changing, as states that initiated customer choice in the past 5-7 years reach an important juncture in retail market design. Most states with retail choice established an initial transitional period during which utilities were required to offer a default or standard offer generation service, often at a capped or otherwise administratively-determined rate. Many retail choice states have reached the end of their transitional period, and several have adopted or are actively considering an RTP-type default service for large commercial and industrial (C&I) customers. In most cases, the primary reason for adopting RTP as the default service has been to advance policy objectives related to the development of competitive retail markets. However, if attention is paid in its design and implementation, default RTP service can also provide a solid foundation for developing price responsive demand, creating an important link between wholesale and retail market transactions. This article, which draws from a lengthier report, describes experience to date with RTP as a default service, focusing on its role as an instrument for cultivating price responsive demand.1 As of summer 2005, default service RTP was in place or approved for future implementation in five U.S. states: New Jersey, Maryland, Pennsylvania, New York, and Illinois. For each of these states, we conducted a detailed review of the regulatory proceedings leading to adoption of default RTP and interviewed regulatory staff and utilities in these states, as well as eight competitive retail suppliers active in these markets.

  11. Model Documentation Report: Residential Demand Module of the...

    Gasoline and Diesel Fuel Update (EIA)

    (conditioned square footage) based on current Census Bureau data. * Revision of the benchmarking process that incorporates historical and near-term forecasted values. December 2012...

  12. Residential Demand Module of the National Energy Modeling System...

    Gasoline and Diesel Fuel Update (EIA)

    (conditioned square footage) based on current Census Bureau data. * Revision of the benchmarking process that incorporates historical and near-term forecasted values. * Revision of...

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

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

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

  14. Refrigerated Warehouse Demand Response Strategy Guide

    SciTech Connect (OSTI)

    Scott, Doug; Castillo, Rafael; Larson, Kyle; Dobbs, Brian; Olsen, Daniel

    2015-11-01

    This guide summarizes demand response measures that can be implemented in refrigerated warehouses. In an appendix, it also addresses related energy efficiency opportunities. Reducing overall grid demand during peak periods and energy consumption has benefits for facility operators, grid operators, utility companies, and society. State wide demand response potential for the refrigerated warehouse sector in California is estimated to be over 22.1 Megawatts. Two categories of demand response strategies are described in this guide: load shifting and load shedding. Load shifting can be accomplished via pre-cooling, capacity limiting, and battery charger load management. Load shedding can be achieved by lighting reduction, demand defrost and defrost termination, infiltration reduction, and shutting down miscellaneous equipment. Estimation of the costs and benefits of demand response participation yields simple payback periods of 2-4 years. To improve demand response performance, it’s suggested to install air curtains and another form of infiltration barrier, such as a rollup door, for the passageways. Further modifications to increase efficiency of the refrigeration unit are also analyzed. A larger condenser can maintain the minimum saturated condensing temperature (SCT) for more hours of the day. Lowering the SCT reduces the compressor lift, which results in an overall increase in refrigeration system capacity and energy efficiency. Another way of saving energy in refrigerated warehouses is eliminating the use of under-floor resistance heaters. A more energy efficient alternative to resistance heaters is to utilize the heat that is being rejected from the condenser through a heat exchanger. These energy efficiency measures improve efficiency either by reducing the required electric energy input for the refrigeration system, by helping to curtail the refrigeration load on the system, or by reducing both the load and required energy input.

  15. 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.

  16. 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...

  17. Material World: Forecasting Household Appliance Ownership in a Growing Global Economy

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

    Over the past years the Lawrence Berkeley National Laboratory (LBNL) has developed an econometric model that predicts appliance ownership at the household level based on macroeconomic variables such as household income (corrected for purchase power parity), electrification, urbanization and climate variables. Hundreds of data points from around the world were collected in order to understand trends in acquisition of new appliances by households, especially in developing countries. The appliances covered by this model are refrigerators, lighting fixtures, air conditioners, washing machines and televisions. The approach followed allows the modeler to construct a bottom-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residential sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time. This serves two important functions with regard to evaluation of the impact of energy efficiency policies. First, it provides insight into which end uses will be responsible for the largest share of demand growth, and therefore should be policy priorities. Second, it provides a characterization of the rate at which policies affecting new equipment penetrate the appliance stock. Over the past 3 years, this method has been used to support the development of energy demand forecasts at the country, region or global level.

  18. Electricity pricing as a demand-side management strategy: Western lessons for developing countries

    SciTech Connect (OSTI)

    Hill, L.J.

    1990-12-01

    Electric utilities in the Western world have increasingly realized that load commitments can be met not only by constructing new generating plants but also by influencing electricity demand. This demand-side management (DSM) process requires that electric utilities promote measures on the customer's side of the meter to directly or indirectly influence electricity consumption to meet desired load objectives. An important demand-side option to achieve these load objectives is innovative electricity pricing, both by itself and as a financial incentive for other demand-site measures. This study explores electricity pricing as a DSM strategy, addressing four questions in the process: What is the Western experience with DSM in general and electricity pricing in particular Do innovative pricing strategies alter the amount and pattern of electricity consumption Do the benefits of these pricing strategies outweigh the costs of implementation What are future directions in electricity pricing Although DSM can be used to promote increases in electricity consumption for electric utilities with excess capacity as well as to slow demand growth for capacity-short utilities, emphasis here is placed on the latter. The discussion should be especially useful for electric utilities in developing countries that are exploring alternatives to capacity expansion to meet current and future electric power demand.

  19. Renewable Electricity Futures Study. Volume 1: Exploration of High-Penetration Renewable Electricity Futures

    SciTech Connect (OSTI)

    Mai, T.; Wiser, R.; Sandor, D.; Brinkman, G.; Heath, G.; Denholm, P.; Hostick, D.J.; Darghouth, N.; Schlosser, A.; Strzepek, K.

    2012-06-01

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).

  20. Wireless Demand Response Controls for HVAC Systems

    SciTech Connect (OSTI)

    Federspiel, Clifford

    2009-06-30

    The objectives of this scoping study were to develop and test control software and wireless hardware that could enable closed-loop, zone-temperature-based demand response in buildings that have either pneumatic controls or legacy digital controls that cannot be used as part of a demand response automation system. We designed a SOAP client that is compatible with the Demand Response Automation Server (DRAS) being used by the IOUs in California for their CPP program, design the DR control software, investigated the use of cellular routers for connecting to the DRAS, and tested the wireless DR system with an emulator running a calibrated model of a working building. The results show that the wireless DR system can shed approximately 1.5 Watts per design CFM on the design day in a hot, inland climate in California while keeping temperatures within the limits of ASHRAE Standard 55: Thermal Environmental Conditions for Human Occupancy.

  1. Centralized and Decentralized Control for Demand Response

    SciTech Connect (OSTI)

    Lu, Shuai; Samaan, Nader A.; Diao, Ruisheng; Elizondo, Marcelo A.; Jin, Chunlian; Mayhorn, Ebony T.; Zhang, Yu; Kirkham, Harold

    2011-04-29

    Demand response has been recognized as an essential element of the smart grid. Frequency response, regulation and contingency reserve functions performed traditionally by generation resources are now starting to involve demand side resources. Additional benefits from demand response include peak reduction and load shifting, which will defer new infrastructure investment and improve generator operation efficiency. Technical approaches designed to realize these functionalities can be categorized into centralized control and decentralized control, depending on where the response decision is made. This paper discusses these two control philosophies and compares their relative advantages and disadvantages in terms of delay time, predictability, complexity, and reliability. A distribution system model with detailed household loads and controls is built to demonstrate the characteristics of the two approaches. The conclusion is that the promptness and reliability of decentralized control should be combined with the predictability and simplicity of centralized control to achieve the best performance of the smart grid.

  2. Utility Sector Impacts of Reduced Electricity Demand

    SciTech Connect (OSTI)

    Coughlin, Katie

    2014-12-01

    This report presents a new approach to estimating the marginal utility sector impacts associated with electricity demand reductions. The method uses publicly available data and provides results in the form of time series of impact factors. The input data are taken from the Energy Information Agency's Annual Energy Outlook (AEO) projections of how the electric system might evolve in the reference case, and in a number of side cases that incorporate different effciency and other policy assumptions. The data published with the AEO are used to define quantitative relationships between demand-side electricity reductions by end use and supply-side changes to capacity by plant type, generation by fuel type and emissions of CO2, Hg, NOx and SO2. The impact factors define the change in each of these quantities per unit reduction in site electricity demand. We find that the relative variation in these impacts by end use is small, but the time variation can be significant.

  3. 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 (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

  4. DEMAND CONTROLLED VENTILATION AND CLASSROOM VENTILATION

    SciTech Connect (OSTI)

    Fisk, William J.; Mendell, Mark J.; Davies, Molly; Eliseeva, Ekaterina; Faulkner, David; Hong, Tienzen; Sullivan, Douglas P.

    2014-01-06

    This document summarizes a research effort on demand controlled ventilation and classroom ventilation. The research on demand controlled ventilation included field studies and building energy modeling. Major findings included: ? The single-location carbon dioxide sensors widely used for demand controlled ventilation frequently have large errors and will fail to effectively control ventilation rates (VRs).? Multi-location carbon dioxide measurement systems with more expensive sensors connected to multi-location sampling systems may measure carbon dioxide more accurately.? Currently-available optical people counting systems work well much of the time but have large counting errors in some situations. ? In meeting rooms, measurements of carbon dioxide at return-air grilles appear to be a better choice than wall-mounted sensors.? In California, demand controlled ventilation in general office spaces is projected to save significant energy and be cost effective only if typical VRs without demand controlled ventilation are very high relative to VRs in codes. Based on the research, several recommendations were developed for demand controlled ventilation specifications in the California Title 24 Building Energy Efficiency Standards.The research on classroom ventilation collected data over two years on California elementary school classrooms to investigate associations between VRs and student illness absence (IA). Major findings included: ? Median classroom VRs in all studied climate zones were below the California guideline, and 40percent lower in portable than permanent buildings.? Overall, one additional L/s per person of VR was associated with 1.6percent less IA. ? Increasing average VRs in California K-12 classrooms from the current average to the required level is estimated to decrease IA by 3.4percent, increasing State attendance-based funding to school districts by $33M, with $6.2 M in increased energy costs. Further VR increases would provide additional benefits.? Confirming these findings in intervention studies is recommended. ? Energy costs of heating/cooling unoccupied classrooms statewide are modest, but a large portion occurs in relatively few classrooms.

  5. Demand Responsive Lighting: A Scoping Study

    SciTech Connect (OSTI)

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-03

    The objective of this scoping study is: (1) to identify current market drivers and technology trends that can improve the demand responsiveness of commercial building lighting systems and (2) to quantify the energy, demand and environmental benefits of implementing lighting demand response and energy-saving controls strategies Statewide. Lighting systems in California commercial buildings consume 30 GWh. Lighting systems in commercial buildings often waste energy and unnecessarily stress the electrical grid because lighting controls, especially dimming, are not widely used. But dimmable lighting equipment, especially the dimming ballast, costs more than non-dimming lighting and is expensive to retrofit into existing buildings because of the cost of adding control wiring. Advances in lighting industry capabilities coupled with the pervasiveness of the Internet and wireless technologies have led to new opportunities to realize significant energy saving and reliable demand reduction using intelligent lighting controls. Manufacturers are starting to produce electronic equipment--lighting-application specific controllers (LAS controllers)--that are wirelessly accessible and can control dimmable or multilevel lighting systems obeying different industry-accepted protocols. Some companies make controllers that are inexpensive to install in existing buildings and allow the power consumed by bi-level lighting circuits to be selectively reduced during demand response curtailments. By intelligently limiting the demand from bi-level lighting in California commercial buildings, the utilities would now have an enormous 1 GW demand shed capability at hand. By adding occupancy and light sensors to the remotely controllable lighting circuits, automatic controls could harvest an additional 1 BkWh/yr savings above and beyond the savings that have already been achieved. The lighting industry's adoption of DALI as the principal wired digital control protocol for dimming ballasts and increased awareness of the need to standardize on emerging wireless technologies are evidence of this transformation. In addition to increased standardization of digital control protocols controller capabilities, the lighting industry has improved the performance of dimming lighting systems over the last two years. The system efficacy of today's current dimming ballasts is approaching that of non-dimming program start ballasts. The study finds that the benefits of applying digital controls technologies to California's unique commercial buildings market are enormous. If California were to embark on an concerted 20 year program to improve the demand responsiveness and energy efficiency of commercial building lighting systems, the State could avoid adding generation capacity, improve the elasticity of the grid, save Californians billion of dollars in avoided energy charges and significantly reduce greenhouse gas emissions.

  6. Climatic Forecasting of Net Infiltration at Yucca Montain Using Analogue Meteororological Data

    SciTech Connect (OSTI)

    B. Faybishenko

    2006-09-11

    At Yucca Mountain, Nevada, future changes in climatic conditions will most likely alter net infiltration, or the drainage below the bottom of the evapotranspiration zone within the soil profile or flow across the interface between soil and the densely welded part of the Tiva Canyon Tuff. The objectives of this paper are to: (a) develop a semi-empirical model and forecast average net infiltration rates, using the limited meteorological data from analogue meteorological stations, for interglacial (present day), and future monsoon, glacial transition, and glacial climates over the Yucca Mountain region, and (b) corroborate the computed net-infiltration rates by comparing them with the empirically and numerically determined groundwater recharge and percolation rates through the unsaturated zone from published data. In this paper, the author presents an approach for calculations of net infiltration, aridity, and precipitation-effectiveness indices, using a modified Budyko's water-balance model, with reference-surface potential evapotranspiration determined from the radiation-based Penman (1948) formula. Results of calculations show that net infiltration rates are expected to generally increase from the present-day climate to monsoon climate, to glacial transition climate, and then to the glacial climate. The forecasting results indicate the overlap between the ranges of net infiltration for different climates. For example, the mean glacial net-infiltration rate corresponds to the upper-bound glacial transition net infiltration, and the lower-bound glacial net infiltration corresponds to the glacial transition mean net infiltration. Forecasting of net infiltration for different climate states is subject to numerous uncertainties-associated with selecting climate analogue sites, using relatively short analogue meteorological records, neglecting the effects of vegetation and surface runoff and runon on a local scale, as well as possible anthropogenic climate changes.

  7. 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.

  8. Tankless Demand Water Heater Basics | Department of Energy

    Energy Savers [EERE]

    Water Heating Tankless Demand Water Heater Basics Tankless Demand Water Heater Basics August 19, 2013 - 2:57pm Addthis Illustration of an electric demand water heater. At the ...

  9. Washington: Sustainability Training for Realtors in High Demand...

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

    Sustainability Training for Realtors in High Demand Washington: Sustainability Training for Realtors in High Demand March 6, 2014 - 5:50pm Addthis Demand has been high for a free ...

  10. Final Scientific Technical Report: INTEGRATED PREDICTIVE DEMAND RESPONSE CONTROLLER FOR COMMERCIAL BUILDINGS

    SciTech Connect (OSTI)

    Wenzel, Mike

    2013-10-14

    This project provides algorithms to perform demand response using the thermal mass of a building. Using the thermal mass of the building is an attractive method for performing demand response because there is no need for capital expenditure. The algorithms rely on the thermal capacitance inherent in the building?s construction materials. A near-optimal ?day ahead? predictive approach is developed that is meant to keep the building?s electrical demand constant during the high cost periods. This type of approach is appropriate for both time-of-use and critical peak pricing utility rate structures. The approach uses the past days data in order to determine the best temperature setpoints for the building during the high price periods on the next day. A second ?model predictive approach? (MPC) uses a thermal model of the building to determine the best temperature for the next sample period. The approach uses constant feedback from the building and is capable of appropriately handling real time pricing. Both approaches are capable of using weather forecasts to improve performance.

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

    SciTech Connect (OSTI)

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

    2009-11-20

    Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and uncertainty in wind power and to more efficiently operate power systems with large wind power penetrations. Moreover, in a market environment, the wind power contribution to the generation portofolio becomes important in determining the daily and hourly prices, as variations in the estimated wind power will influence the clearing prices for both energy and operating reserves. With the increasing penetration of wind power, WPF is quickly becoming an important topic for the electric power industry. System operators (SOs), generating companies (GENCOs), and regulators all support efforts to develop better, more reliable and accurate forecasting models. Wind farm owners and operators also benefit from better wind power prediction to support competitive participation in electricity markets against more stable and dispatchable energy sources. In general, WPF can be used for a number of purposes, such as: generation and transmission maintenance planning, determination of operating reserve requirements, unit commitment, economic dispatch, energy storage optimization (e.g., pumped hydro storage), and energy trading. The objective of this report is to review and analyze state-of-the-art WPF models and their application to power systems operations. We first give a detailed description of the methodologies underlying state-of-the-art WPF models. We then look at how WPF can be integrated into power system operations, with specific focus on the unit commitment problem.

  12. Indianapolis Offers a Lesson on Driving Demand

    Broader source: Energy.gov [DOE]

    Successful program managers know that understanding the factors that drive homeowners to make upgrades is critical to the widespread adoption of energy efficiency. What better place to learn about driving demand for upgrades than in Indianapolis, America's most famous driving city?

  13. Energy Demand (released in AEO2010)

    Reports and Publications (EIA)

    2010-01-01

    Growth in U.S. energy use is linked to population growth through increases in demand for housing, commercial floorspace, transportation, manufacturing, and services. This affects not only the level of energy use, but also the mix of fuels and consumption by sector.

  14. Multi-Path Transportation Futures Study: Results from Phase 1

    SciTech Connect (OSTI)

    Phil Patterson, P.; Singh, M.; Plotkin, S.; Moore, J.

    2007-03-09

    Presentation reporting Phase 1 results, 3/9/2007. Projecting the future role of advanced drivetrains and fuels in the light vehicle market is inherently difficult, given the uncertainty (and likely volatility) of future oil prices, inadequate understanding of likely consumer response to new technologies, the relative infancy of several important new technologies with inevitable future changes in their performance and costs, and the importance and uncertainty of future government marketplace interventions (e.g., new regulatory standards or vehicle purchase incentives). The Multi-Path Transportation Futures (MP) Study has attempted to improve our understanding of this future role by examining several scenarios of vehicle costs, fuel prices, government subsidies, and other key factors. These are projections, not forecasts, in that they try to answer a series of what if questions without assigning probabilities to most of the basic assumptions.

  15. Structuring Rebate and Incentive Programs for Sustainable Demand...

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

    Structuring Rebate and Incentive Programs for Sustainable Demand Structuring Rebate and ... Loan Rates and Demand Peer Exchange Call on Financing and Revenue: Bond Funding Marketing ...

  16. Structuring Rebate and Incentive Programs for Sustainable Demand...

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

    Structuring Rebate and Incentive Programs for Sustainable Demand Structuring Rebate and Incentive Programs for Sustainable Demand Better Buildings Neighborhood Program Peer...

  17. Using Mobile Applications to Generate Customer Demand | Department...

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

    Using Mobile Applications to Generate Customer Demand Using Mobile Applications to Generate Customer Demand Better Buildings Residential Network Peer Exchange Call Series: Using...

  18. Strategies for Marketing and Driving Demand for Commercial Financing...

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

    Marketing and Driving Demand for Commercial Financing Products Strategies for Marketing and Driving Demand for Commercial Financing Products Better Buildings Neighborhood Program ...

  19. Demand Response and Energy Storage Integration Study - Past Workshops...

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

    Demand Response and Energy Storage Integration Study - Past Workshops Demand Response and Energy Storage Integration Study - Past Workshops The project was initiated and informed...

  20. Draft Chapter 3: Demand-Side Resources | Department of Energy

    Office of Environmental Management (EM)

    Demand-Side Resources Draft Chapter 3: Demand-Side Resources Utilities in many states have been implementing energy efficiency and load management programs (collectively called ...

  1. Agreement Template for Energy Conservation and Demand Side Management...

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

    Agreement Template for Energy Conservation and Demand Side Management Services Agreement Template for Energy Conservation and Demand Side Management Services Template agreement ...

  2. Estimating Costs and Efficiency of Storage, Demand, and Heat...

    Energy Savers [EERE]

    Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters A water heater's energy ...

  3. Estimating Costs and Efficiency of Storage, Demand, and Heat...

    Energy Savers [EERE]

    Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters A water heater's ...

  4. Tool Improves Electricity Demand Predictions to Make More Room...

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

    Tool Improves Electricity Demand Predictions to Make More Room for Renewables Tool Improves Electricity Demand Predictions to Make More Room for Renewables October 3, 2011 - ...

  5. Reducing Energy Demand in Buildings Through State Energy Codes...

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

    Reducing Energy Demand in Buildings Through State Energy Codes Reducing Energy Demand in ... More Documents & Publications Technology Performance Exchange - 2013 BTO Peer Review ...

  6. Estimating Costs and Efficiency of Storage, Demand, and Heat...

    Office of Environmental Management (EM)

    Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters A water heater's...

  7. Can Automotive Battery Recycling Help Meet Lithium Demand? |...

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

    Can Automotive Battery Recycling Help Meet Lithium Demand? Title Can Automotive Battery Recycling Help Meet Lithium Demand? Publication Type Presentation Year of Publication 2013...

  8. SGDP Report Now Available: Interoperability of Demand Response...

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

    SGDP Report Now Available: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report Now Available: Interoperability of Demand Response ...

  9. SGDP Report: Interoperability of Demand Response Resources Demonstrati...

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

    SGDP Report: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report: Interoperability of Demand Response Resources Demonstration in NY ...

  10. FERC Presendation: Demand Response as Power System Resources...

    Office of Environmental Management (EM)

    FERC Presendation: Demand Response as Power System Resources, October 29, 2010 FERC Presendation: Demand Response as Power System Resources, October 29, 2010 Federal Energy ...

  11. Implementation Proposal for the National Action Plan on Demand...

    Energy Savers [EERE]

    Implementation Proposal for the National Action Plan on DemandResponse - July 2011 Implementation Proposal for the National Action Plan on Demand Response - July 2011 Report to ...

  12. Sustainable Energy Resources for Consumers (SERC) - On-Demand...

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

    On-Demand Tankless Water Heaters Sustainable Energy Resources for Consumers (SERC) - On-Demand Tankless Water Heaters This presentation, aimed at Sustainable Energy Resources for ...

  13. High-Performance with Solar Electric Reduced Peak Demand: Premier...

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

    with Solar Electric Reduced Peak Demand: Premier Homes Rancho Cordoba, CA - Building America Top Innovation High-Performance with Solar Electric Reduced Peak Demand: Premier Homes ...

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

    Broader source: Energy.gov [DOE]

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

  15. Value of Demand Response: Quantities from Production Cost Modeling (Presentation)

    SciTech Connect (OSTI)

    Hummon, M.

    2014-04-01

    Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind and solar power generation. However, managed loads in grid models are limited by data availability and modeling complexity. This presentation focuses on the value of co-optimized DR resources to provide energy and ancillary services in a production cost model. There are significant variations in the availabilities of different types of DR resources, which affect both the operational savings as well as the revenue for each DR resource. The results presented include the system-wide avoided fuel and generator start-up costs as well as the composite revenue for each DR resource by energy and operating reserves. In addition, the revenue is characterized by the capacity, energy, and units of DR enabled.

  16. 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,...

  17. 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....

  18. 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.

  19. ARM - PI Product - CCPP-ARM Parameterization Testbed Model Forecast...

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

    love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : CCPP-ARM Parameterization Testbed Model Forecast Data Dataset contains the NCAR...

  20. 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.

  1. 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.

  2. Summer gasoline price forecast slightly higher, but drivers still...

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

    In its new monthly forecast, the U.S. Energy Information Administration said the retail price for regular grade gasoline will average 2.21 per gallon this summer. While that's 17 ...

  3. 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.

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

    Office of Scientific and Technical Information (OSTI)

    1) To provide profiles of the horizontal wind to be used to test and validate short-term cloud advection forecasts for solar-energy applications and 2) to provide vertical ...

  5. 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...

  6. Forecasting the oil-gasoline price relationship: should we care...

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

    (2007, EE) obtain similar results on a panel of 15 OECD countries, with annual data ... Results Point forecasts of the N.Y. gasoline price 26 Panel (a): daily data Model MSFE ...

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

    Office of Environmental Management (EM)

    New Forecasting Tools Enhance Wind Energy Integration in Idaho and Oregon Page 1 Under the ... (RIT) that enables grid operators to use wind energy more cost-effectively to serve ...

  8. The Impact of Uncertain Physical Parameters on HVAC Demand Response

    SciTech Connect (OSTI)

    Sun, Yannan; Elizondo, Marcelo A.; Lu, Shuai; Fuller, Jason C.

    2014-03-01

    HVAC units are currently one of the major resources providing demand response (DR) in residential buildings. Models of HVAC with DR function can improve understanding of its impact on power system operations and facilitate the deployment of DR technologies. This paper investigates the importance of various physical parameters and their distributions to the HVAC response to DR signals, which is a key step to the construction of HVAC models for a population of units with insufficient data. These parameters include the size of floors, insulation efficiency, the amount of solid mass in the house, and efficiency of the HVAC units. These parameters are usually assumed to follow Gaussian or Uniform distributions. We study the effect of uncertainty in the chosen parameter distributions on the aggregate HVAC response to DR signals, during transient phase and in steady state. We use a quasi-Monte Carlo sampling method with linear regression and Prony analysis to evaluate sensitivity of DR output to the uncertainty in the distribution parameters. The significance ranking on the uncertainty sources is given for future guidance in the modeling of HVAC demand response.

  9. Modeling and forecasting the distribution of Vibrio vulnificus in

    Office of Scientific and Technical Information (OSTI)

    Chesapeake Bay (Journal Article) | SciTech Connect Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay Citation Details In-Document Search Title: Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters

  10. Forecasting neutrino masses from combining KATRIN and the CMB observations:

    Office of Scientific and Technical Information (OSTI)

    Frequentist and Bayesian analyses (Journal Article) | SciTech Connect SciTech Connect Search Results Journal Article: Forecasting neutrino masses from combining KATRIN and the CMB observations: Frequentist and Bayesian analyses Citation Details In-Document Search Title: Forecasting neutrino masses from combining KATRIN and the CMB observations: Frequentist and Bayesian analyses We present a showcase for deriving bounds on the neutrino masses from laboratory experiments and cosmological

  11. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National

    Office of Scientific and Technical Information (OSTI)

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

  12. 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

  13. Model documentation report: Residential sector demand module of the National Energy Modeling System

    SciTech Connect (OSTI)

    1997-01-01

    This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document that provides a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

  14. Demand Side Management in the Smart Grid: Information Processing for the Power Switch

    SciTech Connect (OSTI)

    Alizadeh, Mahnoosh; LI, Xiao; Wang, Zhifang; Scagilone, Anna; Melton, Ronald B.

    2012-09-01

    In this article we discuss the most recent developments in the area of load management, and consider possible interaction schemes of novel architectures with distributed energy resources (DER). In order to handle the challenges faced by tomorrow’s smart grid, which are caused by volatile load and generation profiles (from the large number of plug-in EVs and from renewable integration), the conventional grid operating principle of load-following needs to be changed into load-shaping or generation-following. Demand Side Management will be a most promising and powerful solution to the above challenges. However, many other issues such as load forecasting, pricing structure, market policy, renewable integration interface, and even the AC/DC implementation at the distribution side, need to be taken into the design in order to search for the most effective and applicable solution.

  15. Scenarios of Global Municipal Water-Use Demand Projections over the 21st Century

    SciTech Connect (OSTI)

    Hejazi, Mohamad I.; Edmonds, James A.; Chaturvedi, Vaibhav; Davies, Evan; Eom, Jiyong

    2013-03-06

    This paper establishes three future projections of global municipal water use to the end of the 21st century: A reference business-as usual (BAU) scenario, a High Technological Improvement (High Tech) scenario and a Low Technological Improvement (Low Tech) scenario. A global municipal water demand model is constructed using global water use statistics at the country-scale, calibrated to the base year of 2005, and simulated to the end of the 21st century. Since the constructed water demand model hinges on socioeconomic variables (population, income), water price, and end-use technology and efficiency improvement rates, projections of those input variables are adopted to characterize the uncertainty in future water demand estimates. The water demand model is linked to the Global Change Assessment Model (GCAM), a global change integrated assessment model. Under the reference scenario, the global total water withdrawal increases from 466 km3/year in 2005 to 941 km3/year in 2100,while withdrawals in the high and low tech scenarios are 321 km3/ year and 2000 km3/ year, respectively. This wide range (321-2000 km3/ year) indicates the level of uncertainty associated with such projections. The simulated global municipal demand projections are most sensitive to population and income projections, then to end-use technology and efficiency projections, and finally to water price. Thus, using water price alone as a policy measure to reduce municipal water use may substantiate the share of municipal water price of peoples annual incomes.

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

    SciTech Connect (OSTI)

    Lacommare, Kristina S H; Komiyama, Ryoichi; Marnay, Chris

    2008-05-15

    As one of the measures to achieve the reduction in greenhouse gas emissions agreed to in the"Kyoto Protocol," an institutional scheme for determining energy efficiency standards for energy-consuming appliances, called the"Top-Runner Approach," was developed by the Japanese government. Its goal is to strengthen the legal underpinnings of various energy conservation measures. Particularly in Japan's residential sector, where energy demand has grown vigorously so far, this efficiency standard is expected to play a key role in mitigating both energy demand growth and the associated CO2 emissions. This paper presents an outlook of Japan's residential energy demand, developed by a stochastic econometric model for the purpose of analyzing the impacts of the Japan's energy efficiency standards, as well as the future stochastic behavior of income growth, demography, energy prices, and climate on the future energy demand growth to 2030. In this analysis, we attempt to explicitly take into consideration more than 30 kinds of electricity uses, heating, cooling and hot water appliances in order to comprehensively capture the progress of energy efficiency in residential energy end-use equipment. Since electricity demand, is projected to exhibit astonishing growth in Japan's residential sector due to universal increasing ownership of electric and other appliances, it is important to implement an elaborate efficiency standards policy for these appliances.

  17. National Oceanic and Atmospheric Administration Provides Forecasting Support for CLASIC and CHAPS 2007

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

    NOAA Provides Forecasting Support for CLASIC and CHAPS 2007 Forecasting Challenge While weather experiments in the heart of Tornado Alley typically focus on severe weather, the CLASIC and CHAPS programs will have different emphases. Forecasters from the National Oceanic and Atmospheric Administration in Norman, Okla. will provide weather forecasting support to these two Department of Energy experiments based in the state. Forecasting support for meteorological research field programs usually

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

    ScienceCinema (OSTI)

    Collins, Bill

    2011-04-28

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

  19. What is a High Electric Demand Day?

    Broader source: Energy.gov [DOE]

    This presentation by T. McNevin of the New Jersey Bureau of Air Quality Planning was part of the July 2008 Webcast sponsored by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Weatherization and Intergovernmental Program Clean Energy and Air Quality Integration Initiative that was titled Role of Energy Efficiency and Renewable Energy in Improving Air Quality and Addressing Greenhouse Gas Reduction Goals on High Electric Demand Days.

  20. Retail Demand Response in Southwest Power Pool

    Energy Savers [EERE]

    LBNL-1470E Retail Demand Response in Southwest Power Pool Ranjit Bharvirkar, Grayson Heffner and Charles Goldman Lawrence Berkeley National Laboratory Environmental Energy Technologies Division January 2009 The work described in this report was funded by the Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Disclaimer This document was

  1. Price-responsive demand management for a smart grid world

    SciTech Connect (OSTI)

    Chao, Hung-po

    2010-01-15

    Price-responsive demand is essential for the success of a smart grid. However, existing demand-response programs run the risk of causing inefficient price formation. This problem can be solved if each retail customer could establish a contract-based baseline through demand subscription before joining a demand-response program. (author)

  2. 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.

  3. A hybrid inventory management system respondingto regular demand and surge demand

    SciTech Connect (OSTI)

    Mohammad S. Roni; Mingzhou Jin; Sandra D. Eksioglu

    2014-06-01

    This paper proposes a hybrid policy for a stochastic inventory system facing regular demand and surge demand. The combination of two different demand patterns can be observed in many areas, such as healthcare inventory and humanitarian supply chain management. The surge demand has a lower arrival rate but higher demand volume per arrival. The solution approach proposed in this paper incorporates the level crossing method and mixed integer programming technique to optimize the hybrid inventory policy with both regular orders and emergency orders. The level crossing method is applied to obtain the equilibrium distributions of inventory levels under a given policy. The model is further transformed into a mixed integer program to identify an optimal hybrid policy. A sensitivity analysis is conducted to investigate the impact of parameters on the optimal inventory policy and minimum cost. Numerical results clearly show the benefit of using the proposed hybrid inventory model. The model and solution approach could help healthcare providers or humanitarian logistics providers in managing their emergency supplies in responding to surge demands.

  4. Dramatic Demand Reduction In The Desert Southwest

    SciTech Connect (OSTI)

    Boehm, Robert; Hsieh, Sean; Lee, Joon; Baghzouz, Yahia; Cross, Andrew; Chatterjee, Sarah

    2015-07-06

    This report summarizes a project that was funded to the University of Nevada Las Vegas (UNLV), with subcontractors Pulte Homes and NV Energy. The project was motivated by the fact that locations in the Desert Southwest portion of the US demonstrate very high peak electrical demands, typically in the late afternoons in the summer. These high demands often require high priced power to supply the needs, and the large loads can cause grid supply problems. An approach was proposed through this contact that would reduce the peak electrical demands to an anticipated 65% of what code-built houses of the similar size would have. It was proposed to achieve energy reduction through four approaches applied to a development of 185 homes in northwest part of Las Vegas named Villa Trieste. First, the homes would all be highly energy efficient. Secondly, each house would have a PV array installed on it. Third, an advanced demand response technique would be developed to allow the resident to have some control over the energy used. Finally, some type of battery storage would be used in the project. Pulte Homes designed the houses. The company considered initial cost vs. long-term savings and chose options that had relatively short paybacks. HERS (Home Energy Rating Service) ratings for the homes are approximately 43 on this scale. On this scale, code-built homes rate at 100, zero energy homes rate a 0, and Energy Star homes are 85. In addition a 1.764 Wp (peak Watt) rated PV array was used on each house. This was made up of solar shakes that were in visual harmony with the roofing material used. A demand response tool was developed to control the amount of electricity used during times of peak demand. While demand response techniques have been used in the utility industry for some time, this particular approach is designed to allow the customer to decide the degree of participation in the response activity. The temperature change in the residence can be decided by the residents by adjusting settings. In a sense the customer can choose between greater comfort and greater money savings during demand response circumstances. Finally a battery application was to be considered. Initially it was thought that a large battery (probably a sodium-sulfur type) would be installed. However, after the contract was awarded, it was determined that a single, centrally-located battery system would not be appropriate for many reasons, including that with the build out plan there would not be any location to put it. The price had risen substantially since the budget for the project was put together. Also, that type of battery has to be kept hot all the time, but its use was only sought for summer operation. Hence, individual house batteries would be used, and these are discussed at the end of this report. Many aspects of the energy use for climate control in selected houses were monitored before residents moved in. This was done both to understand the magnitude of the energy flows but also to have data that could be compared to the computer simulations. The latter would be used to evaluate various aspects of our plan. It was found that good agreement existed between actual energy use and computed energy use. Hence, various studies were performed via simulations. Performance simulations showed the impact on peak energy usage between a code built house of same size and shape compared to the Villa Trieste homes with and without the PV arrays on the latter. Computations were also used to understand the effect of varying orientations of the houses in this typical housing development, including the effect of PV electrical generation. Energy conservation features of the Villa Trieste homes decreased the energy use during peak times (as well as all others), but the resulting decreased peak occurred at about the same time as the code-built houses. Consideration of the PV generation decreases the grid energy use further during daylight hours, but did not extend long enough many days to decrease the peak. Hence, a demand response approach, as planned, was needed. With participation of the residents in the demand response program developed does enable the houses to reduce the peak demand between 66% and 72%, depending on the built years. This was addressed fully in the latter part the study and is described in the latter part of this report.

  5. Demand Response - Policy: More Information | Department of Energy

    Energy Savers [EERE]

    Demand Response - Policy: More Information Demand Response - Policy: More Information OE's commitment to ensuring non-wires options to modernize the nation's electricity delivery system includes ongoing support of a number of national and regional activities in support of demand response. The New England Demand Response Initiative (NEDRI), OE's initial endeavor to assist states with non-wire solutions, was created to develop a comprehensive, coordinated set of demand response programs for the

  6. 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

  7. 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.

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

    SciTech Connect (OSTI)

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

    2010-01-01

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

  9. Transportation Energy Futures Snapshot

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

    modes, manage the demand for transportation, and shift the fuel mix to more sustainable sources necessary to reach these significant outcomes. Coordinating a...

  10. LNG demand, shipping will expand through 2010

    SciTech Connect (OSTI)

    True, W.R.

    1998-02-09

    The 1990s, especially the middle years, have witnessed a dramatic turnaround in the growth of liquefied-natural-gas demand which has tracked equally strong natural-gas demand growth. This trend was underscored late last year by several annual studies of world LNG demand and shipping. As 1998 began, however, economic turmoil in Asian financial markets has clouded near-term prospects for LNG in particular and all energy in general. But the extent of damage to energy markets is so far unclear. A study by US-based Institute of Gas Technology, Des Plaines, IL, reveals that LNG imports worldwide have climbed nearly 8%/year since 1980 and account for 25% of all natural gas traded internationally. In the mid-1970s, the share was only 5%. In 1996, the most recent year for which complete data are available, world LNG trade rose 7.7% to a record 92 billion cu m, outpacing the overall consumption for natural gas which increased 4.7% in 1996. By 2015, says the IGT study, natural-gas use would surpass coal as the world`s second most widely used fuel, after petroleum. Much of this growth will occur in the developing countries of Asia where gas use, before the current economic crisis began, was projected to grow 8%/year through 2015. Similar trends are reflected in another study of LNG trade released at year end 1997, this from Ocean Shipping Consultants Ltd., Surrey, U.K. The study was done too early, however, to consider the effects of the financial problems roiling Asia.

  11. Quantifying Changes in Building Electricity Use, with Application to Demand Response

    SciTech Connect (OSTI)

    Mathieu, Johanna L.; Price, Phillip N.; Kiliccote, Sila; Piette, Mary Ann

    2010-11-17

    We present methods for analyzing commercial and industrial facility 15-minute-interval electric load data. These methods allow building managers to better understand their facility's electricity consumption over time and to compare it to other buildings, helping them to ask the right questions to discover opportunities for demand response, energy efficiency, electricity waste elimination, and peak load management. We primarily focus on demand response. Methods discussed include graphical representations of electric load data, a regression-based electricity load model that uses a time-of-week indicator variable and a piecewise linear and continuous outdoor air temperature dependence, and the definition of various parameters that characterize facility electricity loads and demand response behavior. In the future, these methods could be translated into easy-to-use tools for building managers.

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

    SciTech Connect (OSTI)

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

    1997-01-07

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01

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

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

    SciTech Connect (OSTI)

    Not Available

    1981-05-27

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

  15. FutureGen.ppt

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

    Erik Turner Summer 2004 Technical Career Intern Program The Pennsylvania State University FutureGen And the importance of project management Outline * FutureGen technologies * ...

  16. Living a Sustainable Future

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

    Living a Sustainable Future Living a Sustainable Future August 1, 2013 Biomass to fuel project The Laboratory's biomass team is working to solve the energy crisis through...

  17. OSCARS-Future-Tech

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

    OSCARS and Future Tech Engineering Services The Network OSCARS How It Works Who's Using OSCARS? OSCARS and Future Tech OSCARS Standard and Open Grid Forum OSCARS Developers...

  18. Nuclear and Particle Futures

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

    Nuclear and Particle Futures Nuclear and Particle Futures The Lab's four Science Pillars harness our scientific capabilities for national security solutions. Contacts Pillar ...

  19. Probabilities of Possible Future Prices (Released in the STEO April 2010)

    Reports and Publications (EIA)

    2010-01-01

    The Energy Information Administration introduced a monthly analysis of energy price volatility and forecast uncertainty in the October 2009 Short-Term Energy Outlook (STEO). Included in the analysis were charts portraying confidence intervals around the New York Mercantile Exchange (NYMEX) futures prices of West Texas Intermediate (equivalent to light sweet crude oil) and Henry Hub natural gas contracts.

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

    Energy Savers [EERE]

    0 The Smart Enterprise, its Objective and Forecasting.    Steve Browning Page 1 of 6 May 2010 Overview Each AC Power System is always in perfect balance (Kirchoff's law). The wires have no storage and the product moves through them at the speed of light from every electrical alternator and other generation mechanism through every socket to every demand. What the System Operators have to do is continuously match (NOT just balance) Generation to Demand within close limits or the

  1. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

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

  2. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    2008-01-15

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

  3. California: Geothermal Plant to Help Meet High Lithium Demand...

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

    Geothermal Plant to Help Meet High Lithium Demand California: Geothermal Plant to Help Meet High Lithium Demand May 21, 2013 - 5:54pm Addthis Through funding provided by the...

  4. Tankless or Demand-Type Water Heaters | Department of Energy

    Energy Savers [EERE]

    or Demand-Type Water Heaters Tankless or Demand-Type Water Heaters Diagram of a tankless water heater. Diagram of a tankless water heater. Tankless water heaters, also known as ...

  5. A National Forum on Demand Response: Results on What Remains...

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

    Part of the July 2011 Implementation Proposal called for a "National Forum" on demand response to be conducted by DOE and FERC. Given the rapid development of the demand response ...

  6. California Geothermal Power Plant to Help Meet High Lithium Demand...

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

    California Geothermal Power Plant to Help Meet High Lithium Demand California Geothermal Power Plant to Help Meet High Lithium Demand September 20, 2012 - 1:15pm Addthis Ever ...

  7. Tankless or Demand-Type Water Heaters | Department of Energy

    Office of Environmental Management (EM)

    Tankless or Demand-Type Water Heaters Tankless or Demand-Type Water Heaters Diagram of a tankless water heater. Diagram of a tankless water heater. Tankless water heaters, also...

  8. A Hierarchical Framework for Demand-Side Frequency Control (Conference...

    Office of Scientific and Technical Information (OSTI)

    A Hierarchical Framework for Demand-Side Frequency Control Citation Details In-Document Search Title: A Hierarchical Framework for Demand-Side Frequency Control With large-scale ...

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

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2000-08-31

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

  10. Sensor-based demand controlled ventilation

    SciTech Connect (OSTI)

    De Almeida, A.T.; Fisk, W.J.

    1997-07-01

    In most buildings, occupancy and indoor pollutant emission rates vary with time. With sensor-based demand-controlled ventilation (SBDCV), the rate of ventilation (i.e., rate of outside air supply) also varies with time to compensate for the changes in pollutant generation. In other words, SBDCV involves the application of sensing, feedback and control to modulate ventilation. Compared to ventilation without feedback, SBDCV offers two potential advantages: (1) better control of indoor pollutant concentrations; and (2) lower energy use and peak energy demand. SBDCV has the potential to improve indoor air quality by increasing the rate of ventilation when indoor pollutant generation rates are high and occupants are present. SBDCV can also save energy by decreasing the rate of ventilation when indoor pollutant generation rates are low or occupants are absent. After providing background information on indoor air quality and ventilation, this report provides a relatively comprehensive discussion of SBDCV. Topics covered in the report include basic principles of SBDCV, sensor technologies, technologies for controlling air flow rates, case studies of SBDCV, application of SBDCV to laboratory buildings, and research needs. SBDCV appears to be an increasingly attractive technology option. Based on the review of literature and theoretical considerations, the application of SBDCV has the potential to be cost-effective in applications with the following characteristics: (a) a single or small number of dominant pollutants, so that ventilation sufficient to control the concentration of the dominant pollutants provides effective control of all other pollutants; (b) large buildings or rooms with unpredictable temporally variable occupancy or pollutant emission; and (c) climates with high heating or cooling loads or locations with expensive energy.

  11. Marketing & Driving Demand Collaborative - Social Media Tools & Strategies

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

    | Department of Energy & Driving Demand Collaborative - Social Media Tools & Strategies Marketing & Driving Demand Collaborative - Social Media Tools & Strategies Presentation slides from the Better Buildings webinar on January 6, 2011. PDF icon Marketing & Driving Demand Collaborative More Documents & Publications Using Social Media for Long-Term Branding Marketing & Driving Demand: Social Media Tools & Strategies - January 16, 2011 (Text Version) Generating

  12. Using Partnerships to Drive Demand and Provide Services in Communities |

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

    Department of Energy Partnerships to Drive Demand and Provide Services in Communities Using Partnerships to Drive Demand and Provide Services in Communities Better Buildings Neighborhood Program Multifamily and Low-Income Peer Exchange Call: Using Partnerships to Drive Demand and Provide Services in Communities, February 2, 2012. PDF icon Call Slides and Discussion Summary More Documents & Publications Strategies for Marketing and Driving Demand for Commercial Financing Products

  13. 2010 Assessment of Demand Response and Advanced Metering - Staff Report |

    Energy Savers [EERE]

    Department of Energy Assessment of Demand Response and Advanced Metering - Staff Report 2010 Assessment of Demand Response and Advanced Metering - Staff Report 2010 Assessment of Demand Response and Advanced Metering - Staff Report. The Federal Energy Regulatory Commission's 2010 Demand Response and Advanced Metering Survey (2010 FERC Survey, covering calendar year 2009) indicates that advanced metering penetration (i.e., the fraction of all installed meters that are advanced meters) reached

  14. International Transportation Energy Demand Determinants (ITEDD): Prototype Results for China

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

    Jim Turnure, Director Office of Energy Consumption & Efficiency Analysis, EIA EIA Conference: Asian Energy Demand July 14, 2014 | Washington, DC International Transportation Energy Demand Determinants (ITEDD): Prototype Results for China Dawn of new global oil market paradigm? 2 Jim Turnure, EIA Conference July 14, 2014 * Conventional wisdom has centered around $100-120/barrel oil and 110-115 million b/d global liquid fuel demand in the long term (2030-2040) * Demand in non-OECD may push

  15. FERC Presendation: Demand Response as Power System Resources, October 29,

    Energy Savers [EERE]

    2010 | Department of Energy FERC Presendation: Demand Response as Power System Resources, October 29, 2010 FERC Presendation: Demand Response as Power System Resources, October 29, 2010 Federal Energy Regulatory Commission (FERC) presentation on demand response as power system resources before the Electicity Advisory Committee, October 29, 2010 PDF icon Demand Response as Power System Resources More Documents & Publications Ancillary Service Revenue Potential for Geothermal Generators in

  16. Hawaii demand-side management resource assessment. Final report, Reference Volume 1: Building prototype analysis

    SciTech Connect (OSTI)

    1995-04-01

    This report provides a detailed description of, and the baseline assumptions and simulation results for, the building prototype simulations conducted for the building types designated in the Work Plan for Demand-side Management Assessment of Hawaii`s Demand-Side Resources (HES-4, Phase 2). This report represents the second revision to the initial building prototype description report provided to DBEDT early in the project. Modifications and revisions to the prototypes, based on further calibration efforts and on comments received from DBEDT Staff have been incorporated into this final version. These baseline prototypes form the basis upon which the DSM measure impact estimates and the DSM measure data base were developed for this project. This report presents detailed information for each of the 17 different building prototypes developed for use with the DOE-21E program (23 buildings in total, including resorts and hotels defined separately for each island) to estimate the impact of the building technologies and measures included in this project. The remainder of this section presents some nomenclature and terminology utilized in the reports, tables, and data bases developed from this project to denote building type and vintage. Section 2 contains a more detailed discussion of the data sources, the definition of the residential sector building prototypes, and results of the DOE-2 analysis. Section 3 provides a similar discussion for the commercial sector. The prototype and baseline simulation results are presented in a separate section for each building type. Where possible, comparison of the baseline simulation results with benchmark data from the ENERGY 2020 model or other demand forecasting models specific to Hawaii is included for each building. Appendix A contains a detailed listing of the commercial sector baseline indoor lighting technologies included in the existing and new prototypes by building type.

  17. Lessons learned in implementing a demand side management contract at the Presidio of San Francisco

    SciTech Connect (OSTI)

    Sartor, D.; Munn, M.

    1998-06-01

    The National Park Service (NSP) recently completed the implementation phase of its Power Saving Partners (PSP) Demand Side Management (DSM) contract with the local utility, Pacific Gas and Electric (PG&E). Through the DSM contract, NPS will receive approximately $4.1 million over eight years in payment for saving 61 kW of electrical demand, 179,000 km of electricity per year, and 1.1 million therms of natural gas per year. These payments are for two projects: the installation of high-efficiency lighting systems at the Thoreau Center for Sustainability and the replacement of an old central boiler plant with new, distributed boilers. Although these savings and payments are substantial, the electrical savings and contract payments fall well short of the projected 1,700 kW of electrical demand, 8 million kwh of annual electricity savings, and $11 million in payments, anticipated at the project's onset. Natural gas savings exceeded the initial forecast of 800,000 therms per year. The DSM contract payments did not meet expectations for a variety of reasons which fall into two broad categories: first, many anticipated projects were not constructed, and second, some of the projects that were constructed were not included in the program because the cost of implementing the DSM program's measurement and verification (M&V) requirements outweighed anticipated payments. This paper discusses the projects implemented, and examines the decisions made to withdraw some of them from the DSM contract. It also presents the savings that were realized and documented through M&V efforts. Finally, it makes suggestions relative to M&V protocols to encourage all efficiency measures, not just those that are easy to measure.

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

    Broader source: Energy.gov [DOE]

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

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

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01

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

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

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

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

  2. A Public-Private-Academic Partnership to Advance Solar Power Forecasting |

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

    Department of Energy A Public-Private-Academic Partnership to Advance Solar Power Forecasting A Public-Private-Academic Partnership to Advance Solar Power Forecasting UCAR logo2.jpg The University Corporation for Atmospheric Research (UCAR) will develop a solar power forecasting system that advances the state of the science through cutting-edge research. APPROACH UCAR value chain.png The team will develop a solar power forecasting system that advances the state of the science through

  3. Data Collection and Comparison with Forecasted Unit Sales of Five Lamp

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

    Types | Department of Energy 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 and Comparison with Forecasted Unit Sales of Five Lamp Types More Documents & Publications Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability CX-100584 Categorical Exclusion Determination ISSUANCE

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01

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

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

    SciTech Connect (OSTI)

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

    2011-03-28

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

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

    Energy Science and Technology Software Center (OSTI)

    2012-05-01

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

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

    Broader source: Energy.gov [DOE]

    Four major research objectives were completed over the course of this study. Three of the objectives were to evaluate three, new, state-of-the-art solar irradiance forecasting models. The fourth objective was to improve the California independent system operator’s load forecasts by integrating behind-the-meter photovoltaic forecasts.

  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. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    SciTech Connect (OSTI)

    Ghatikar, Girish; Mathieu, Johanna L.; Piette, Mary Ann; Koch, Ed; Hennage, Dan

    2010-08-02

    This study examines the use of OpenADR communications specification, related data models, technologies, and strategies to send dynamic prices (e.g., real time prices and peak prices) and Time of Use (TOU) rates to commercial and industrial electricity customers. OpenADR v1.0 is a Web services-based flexible, open information model that has been used in California utilities' commercial automated demand response programs since 2007. We find that data models can be used to send real time prices. These same data models can also be used to support peak pricing and TOU rates. We present a data model that can accommodate all three types of rates. For demonstration purposes, the data models were generated from California Independent System Operator's real-time wholesale market prices, and a California utility's dynamic prices and TOU rates. Customers can respond to dynamic prices by either using the actual prices, or prices can be mapped into"operation modes," which can act as inputs to control systems. We present several different methods for mapping actual prices. Some of these methods were implemented in demonstration projects. The study results demonstrate show that OpenADR allows interoperability with existing/future systems/technologies and can be used within related dynamic pricing activities within Smart Grid.

  10. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    SciTech Connect (OSTI)

    Thompson, Lisa; Song, Katherine; Lekov, Alex; McKane, Aimee

    2008-11-19

    Wastewater treatment is an energy intensive process which, together with water treatment, comprises about three percent of U.S. annual energy use. Yet, since wastewater treatment facilities are often peripheral to major electricity-using industries, they are frequently an overlooked area for automated demand response opportunities. Demand response is a set of actions taken to reduce electric loads when contingencies, such as emergencies or congestion, occur that threaten supply-demand balance, and/or market conditions occur that raise electric supply costs. Demand response programs are designed to improve the reliability of the electric grid and to lower the use of electricity during peak times to reduce the total system costs. Open automated demand response is a set of continuous, open communication signals and systems provided over the Internet to allow facilities to automate their demand response activities without the need for manual actions. Automated demand response strategies can be implemented as an enhanced use of upgraded equipment and facility control strategies installed as energy efficiency measures. Conversely, installation of controls to support automated demand response may result in improved energy efficiency through real-time access to operational data. This paper argues that the implementation of energy efficiency opportunities in wastewater treatment facilities creates a base for achieving successful demand reductions. This paper characterizes energy use and the state of demand response readiness in wastewater treatment facilities and outlines automated demand response opportunities.

  11. Measurement and evaluation techniques for automated demand response demonstration

    SciTech Connect (OSTI)

    Motegi, Naoya; Piette, Mary Ann; Watson, David S.; Sezgen, Osman; ten Hope, Laurie

    2004-08-01

    The recent electricity crisis in California and elsewhere has prompted new research to evaluate demand response strategies in large facilities. This paper describes an evaluation of fully automated demand response technologies (Auto-DR) in five large facilities. Auto-DR does not involve human intervention, but is initiated at a facility through receipt of an external communications signal. This paper summarizes the measurement and evaluation of the performance of demand response technologies and strategies in five large facilities. All the sites have data trending systems such as energy management and control systems (EMCS) and/or energy information systems (EIS). Additional sub-metering was applied where necessary to evaluate the facility's demand response performance. This paper reviews the control responses during the test period, and analyzes demand savings achieved at each site. Occupant comfort issues are investigated where data are available. This paper discusses methods to estimate demand savings and results from demand response strategies at five large facilities.

  12. Research Study - Global Enterprise VoIP Equipment Market Forecasts...

    Open Energy Info (EERE)

    we deeply analyzed the world's main region market conditions that including the product price, profit, capacity, production, capacity utilization, supply, demand and industry...

  13. Incentives for demand-side management

    SciTech Connect (OSTI)

    Reid, M.W.; Brown, J.B.

    1992-01-01

    This report is the first product of an ongoing project to monitor the efforts of states to remove regulatory barriers to, and provide financial incentives for, utility investment in demand-side management (DSM) resources. The project was commissioned by the National Association of Regulatory Utility Commissioners (NARUC) in response to growing interest among regulators for a comprehensive survey of developments in this area. Each state report beings with an overview of the state`s progress toward removing regulatory barriers and providing incentives for DSM. Information is organized under five headings: status; IRP regulations and practice; current treatment of DSM, directions and trends; commission contact person. Where applicable, each overview is followed by one or more sections that report on specific incentive proposals or mechanisms within the state. Information on each proposal or mechanism is organized under eight headings. A notation on each page identifies the utility or other group associated with the proposal or mechanism. The eight headings are as follows: status; background; treatment of cost recovery; treatment of lost revenues/decoupling; treatment of profitability; other features; issues, and additional observations.

  14. Incentives for demand-side management

    SciTech Connect (OSTI)

    Reid, M.W.; Brown, J.B. )

    1992-01-01

    This report is the first product of an ongoing project to monitor the efforts of states to remove regulatory barriers to, and provide financial incentives for, utility investment in demand-side management (DSM) resources. The project was commissioned by the National Association of Regulatory Utility Commissioners (NARUC) in response to growing interest among regulators for a comprehensive survey of developments in this area. Each state report beings with an overview of the state's progress toward removing regulatory barriers and providing incentives for DSM. Information is organized under five headings: status; IRP regulations and practice; current treatment of DSM, directions and trends; commission contact person. Where applicable, each overview is followed by one or more sections that report on specific incentive proposals or mechanisms within the state. Information on each proposal or mechanism is organized under eight headings. A notation on each page identifies the utility or other group associated with the proposal or mechanism. The eight headings are as follows: status; background; treatment of cost recovery; treatment of lost revenues/decoupling; treatment of profitability; other features; issues, and additional observations.

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

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

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

  16. Isotope Related Reports | U.S. DOE Office of Science (SC)

    Office of Science (SC) Website

    of the Biological and Environmental Research Advisory Committee, April 2004. Expert Panel: Forecast Future Demand for Medical Isotopes, .pdf file (109KB)March 1999. Medical ...

  17. Coal: Energy for the future

    SciTech Connect (OSTI)

    1995-05-01

    This report was prepared in response to a request by the US Department of energy (DOE). The principal objectives of the study were to assess the current DOE coal program vis-a-vis the provisions of the Energy Policy Act of 1992 (EPACT), and to recommend the emphasis and priorities that DOE should consider in updating its strategic plan for coal. A strategic plan for research, development, demonstration, and commercialization (RDD and C) activities for coal should be based on assumptions regarding the future supply and price of competing energy sources, the demand for products manufactured from these sources, technological opportunities, and the need to control the environmental impact of waste streams. These factors change with time. Accordingly, the committee generated strategic planning scenarios for three time periods: near-term, 1995--2005; mid-term, 2006--2020; and, long-term, 2021--2040. The report is divided into the following chapters: executive summary; introduction and scope of the study; overview of US DOE programs and planning; trends and issues for future coal use; the strategic planning framework; coal preparation, coal liquid mixtures, and coal bed methane recovery; clean fuels and specialty products from coal; electric power generation; technology demonstration and commercialization; advanced research programs; conclusions and recommendations; appendices; and glossary. 174 refs.

  18. Planning for the future

    SciTech Connect (OSTI)

    Lesh, Pamela

    2009-06-15

    Four changes to integrated resource planning could significantly improve alignment between future utility spending and the forces and changes that are upending past preconceptions of how to predict future load. (author)

  19. Keck Futures Initiative

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

    National Academies Keck Futures Initiative Complex Systems Conference, November 12 - 15, 2008 Challa Kumar(second from left) was invited to attend 1st National Academies Keck Futures Initiative Complex Systems Conference

  20. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-10-01

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

  1. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-11-01

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

  2. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2013-04-01

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

  3. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M. M.

    2012-09-01

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

  4. Create a Sustainable Future

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

    Create a Sustainable Future Image of river edge with text overlay of 'How does LANL accomplish future stewardship of the natural and historical resources?' We sample to detect any...

  5. Future high energy colliders symposium. Summary report

    SciTech Connect (OSTI)

    Parsa, Z. |

    1996-12-31

    A `Future High Energy Colliders` Symposium was held October 21-25, 1996 at the Institute for Theoretical Physics (ITP) in Santa Barbara. This was one of the 3 symposia hosted by the ITP and supported by its sponsor, the National Science Foundation, as part of a 5 month program on `New Ideas for Particle Accelerators`. The long term program and symposia were organized and coordinated by Dr. Zohreh Parsa of Brookhaven National Laboratory/ITP. The purpose of the symposium was to discuss the future direction of high energy physics by bringing together leaders from the theoretical, experimental and accelerator physics communities. Their talks provided personal perspectives on the physics objectives and the technology demands of future high energy colliders. Collectively, they formed a vision for where the field should be heading and how it might best reach its objectives.

  6. Investigation of structural changes in residential electricity demand

    SciTech Connect (OSTI)

    Chern, W.S.; Bouis, H.E.

    1982-09-23

    The purpose of this study was to investigate the stability of aggregate national residential electricity demand coefficients over time. The hypothesis is maintained that the aggregate residential demand is the sum of various end-use demand components. Since the end-use composition changes over time, the demand relationship may change as well. Since the end-use composition differs among regions, the results obtained from this study can be used for making inferences about regional differences in electricity demand relationships. There are two additional sources for a possible structural change. One is that consumers may react differently to declining and rising prices, secondly, the impact of the 1973 oil embargo may have shifted demand preferences. The electricity demand model used for this study is presented. A moving regression method was employed to investigate changes in residential electricity demand over time. The statistical results show a strikingly consistent pattern of change for most of the structural variables. The most important finding of this study is that the estimated structure of residential electricity demand changes systematically over time as a result of changes in the characteristics (both durability and saturation level) of the stock of appliances. Furthermore, there is not strong evidence that the structural changes in demand occurred due to either the reversal of the declining trend of electricity prices or the impact of the 1973 oil embarge. (LCL)

  7. Renewable Electricity Futures Study Volume 1: Exploration of High-Penetration Renewable Electrcity Futures

    Broader source: Energy.gov [DOE]

    The Renewable Electricity Futures Study (RE Futures) is an initial investigation of the extent to which renewable energy supply can meet the electricity demands of the contiguous United States1 over the next several decades. This study includes geographic and electric system operation resolution that is unprecedented for long-term studies of the U.S. electric sector. The analysis examines the implications and challenges of renewable electricity generation levels—from 30% up to 90%, with a focus on 80%, of all U.S. electricity generation from renewable technologies—in 2050. The study focuses on some key technical implications of this environment, exploring whether the U.S. power system can supply electricity to meet customer demand with high levels of renewable electricity, including variable wind and solar generation. The study also begins to address the potential economic, environmental, and social implications of deploying and integrating high levels of renewable electricity in the United States.

  8. Create a Sustainable Future

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

    Create a Sustainable Future Image of river edge with text overlay of 'How does LANL accomplish future stewardship of the natural and historical resources?' We sample to detect any release of materials to the environment. We manage environmental concerns by eco region. We evaluate our impact on the environment. We consult with experts and stakeholders. We fund projects that reduce environmental effects. Create a Sustainable Future Home Planning for Years to Come Living a Sustainable Future

  9. Active stewardship: sustainable future

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

    Active hurricane season expected to shut-in higher amount of oil and natural gas production An above-normal 2013 hurricane season is expected to cause a median production loss of about 19 million barrels of U.S. crude oil and 46 billion cubic feet of natural gas production in the Gulf of Mexico, according to the new forecast from the U.S. Energy Information Administration. That's about one-third more than the amount of oil and gas production knocked offline during last year's hurricane season.

  10. Direct versus Facility Centric Load Control for Automated Demand Response

    SciTech Connect (OSTI)

    Koch, Ed; Piette, Mary Ann

    2009-11-06

    Direct load control (DLC) refers to the scenario where third party entities outside the home or facility are responsible for deciding how and when specific customer loads will be controlled in response to Demand Response (DR) events on the electric grid. Examples of third parties responsible for performing DLC may be Utilities, Independent System Operators (ISO), Aggregators, or third party control companies. DLC can be contrasted with facility centric load control (FCLC) where the decisions for how loads are controlled are made entirely within the facility or enterprise control systems. In FCLC the facility owner has more freedom of choice in how to respond to DR events on the grid. Both approaches are in use today in automation of DR and both will continue to be used in future market segments including industrial, commercial and residential facilities. This paper will present a framework which can be used to differentiate between DLC and FCLC based upon where decisions are made on how specific loads are controlled in response to DR events. This differentiation is then used to compare and contrast the differences between DLC and FCLC to identify the impact each has on:(1)Utility/ISO and third party systems for managing demand response, (2)Facility systems for implementing load control, (3)Communications networks for interacting with the facility and (4)Facility operators and managers. Finally a survey of some of the existing DR related specifications and communications standards is given and their applicability to DLC or FCLC. In general FCLC adds more cost and responsibilities to the facilities whereas DLC represents higher costs and complexity for the Utility/ISO. This difference is primarily due to where the DR Logic is implemented and the consequences that creates. DLC may be more certain than FCLC because it is more predictable - however as more loads have the capability to respond to DR signals, people may prefer to have their own control of end-use loads and FCLC systems. Research is needed to understand the predictability of FCLC which is related to the perceived value of the DR from the facility manager or home owner's perspective.

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

    SciTech Connect (OSTI)

    Darghouth, Naim; Barbose, Galen; Wiser, Ryan

    2013-01-09

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

  12. Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration

    SciTech Connect (OSTI)

    Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.; Chassin, David P.; Djilali, Ned

    2014-01-31

    Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generator and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.

  13. Future challenges for nuclear data research in fission (u) (Journal

    Office of Scientific and Technical Information (OSTI)

    Article) | SciTech Connect Journal Article: Future challenges for nuclear data research in fission (u) Citation Details In-Document Search Title: Future challenges for nuclear data research in fission (u) I describe some high priority research areas in nuclear fission, where applications in nuclear reactor technologies and in modeling criticality in general are demanding higher accuracies in our databases. We focus on fission cross sections, fission neutron spectra, and fission product data.

  14. NREL Launches Interactive Tool for Developing a Cleaner Energy Future -

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

    News Releases | NREL Launches Interactive Tool for Developing a Cleaner Energy Future January 9, 2013 The U.S. Department of Energy's (DOE) National Renewable Energy Laboratory (NREL) has created an energy analysis tool to help individuals and educators experiment with future energy use scenarios. The interactive Buildings, Industry, Transportation, Electricity, and Transportation Scenarios (BITES) allows users to explore how changes in energy demand and supply can impact carbon dioxide

  15. Historical impacts and future trends in industrial cogeneration

    SciTech Connect (OSTI)

    Bluestein, J.; Lihn, M.

    1999-07-01

    Cogeneration, also known as combined heat and power (CHP), is the combined sequential generation of electricity and thermal or electric energy. The technology has been known essentially since the first commercial generation of electricity as a high efficiency technology option. After a period of decline, its use increased significantly during the 1980s and it is receiving renewed interest lately as a means of increasing efficiency and reducing emissions of air pollutants including carbon emissions. New and developing technology options have added to this potential. Forecasts of future growth and efforts to stimulate cogeneration need to take into account the history of the technology, the factors that have driven it in the past, and factors which could stimulate or retard future growth. This paper reviews and analyzes these factors and looks toward the future potential for cogeneration.

  16. Using Mobile Applications to Generate Customer Demand | Department of

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

    Energy Mobile Applications to Generate Customer Demand Using Mobile Applications to Generate Customer Demand Better Buildings Residential Network Peer Exchange Call Series: Using Mobile Applications to Generate Customer Demand, Call Slides and Discussion Summary, March 12, 2015. PDF icon Call Slides and Discussion Summary More Documents & Publications Better Buildings Network View | October 2014 Incorporating Behavior Change Efforts Into Energy Efficiency Programs Outreach to Multifamily

  17. Executive Order 13693 Training Now Available On Demand | Department of

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

    Energy Executive Order 13693 Training Now Available On Demand Executive Order 13693 Training Now Available On Demand January 4, 2016 - 8:00am Addthis Executive Order (E.O.) 13693: Recent Developments, Implementation Updates, and Opportunities Training is now available on-demand. The seminar covers the major goals of E. O. 13693 and offers examples of technologies and concepts the U.S. Department of Energy and other federal agencies are using to meet these goals. Addthis Related Articles

  18. Monitoring SERC Technologies: On-Demand Tankless Water Heaters | Department

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

    of Energy Weatherization Assistance Program » Pilot Projects » Monitoring SERC Technologies: On-Demand Tankless Water Heaters Monitoring SERC Technologies: On-Demand Tankless Water Heaters On Oct. 4, 2011, Ethan MacCormick, VP for Services to Energy Businesses at Performance Systems Development, presented a Webinar about On-Demand Tankless Water Heaters and how to properly monitor their installation. View the webinar presentation. More Information Some resources and tools mentioned in the

  19. Sustainable Energy Resources for Consumers (SERC) - On-Demand Tankless

    Energy Savers [EERE]

    Water Heaters | Department of Energy On-Demand Tankless Water Heaters Sustainable Energy Resources for Consumers (SERC) - On-Demand Tankless Water Heaters This presentation, aimed at Sustainable Energy Resources for Consumers (SERC) grantees, provides information on Monitoring Checklists for the installation of On-Demand Tankless Water Heaters. PDF icon serc_webinar_presentation_20111004.pdf More Documents & Publications Sustainable Energy Resources for Consumers (SERC) - Solar Hot

  20. Retail Demand Response in Southwest Power Pool | Department of Energy

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

    Retail Demand Response in Southwest Power Pool Retail Demand Response in Southwest Power Pool In 2007, the Southwest Power Pool (SPP) formed the Customer Response Task Force (CRTF) to identify barriers to deploying demand response (DR) resources in wholesale markets and develop policies to overcome these barriers. One of the initiatives of this Task Force was to develop more detailed information on existing retail DR programs and dynamic pricing tariffs, program rules, and utility operating

  1. SGDP Report Now Available: Interoperability of Demand Response Resources

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

    Demonstration in NY (February 2015) | Department of Energy SGDP Report Now Available: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report Now Available: Interoperability of Demand Response Resources Demonstration in NY (February 2015) March 20, 2015 - 4:42pm Addthis The Interoperability of Demand Response Resources Demonstration in NY was awarded to Con Edison in 2009 as part of DOE's Smart Grid Demonstration Project (SGDP) grants funded by the

  2. SGDP Report: Interoperability of Demand Response Resources Demonstration in

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

    NY (February 2015) | Department of Energy SGDP Report: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report: Interoperability of Demand Response Resources Demonstration in NY (February 2015) The Interoperability of Demand Response Resources Demonstration in NY was awarded to Con Edison in 2009 as part of DOE's Smart Grid Demonstration Project (SGDP) grants funded by the Recovery Act. The objective of the project was to develop and demonstrate

  3. Generating Demand for Multifamily Building Upgrades | Department of Energy

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

    Demand for Multifamily Building Upgrades Generating Demand for Multifamily Building Upgrades Better Buildings Residential Network Peer Exchange Call Series: Generating Demand for Multifamily Building Upgrades, call slides and discussion summary, May 14, 2015. PDF icon Call Slides and Discussion Summary More Documents & Publications Strategies to Address Split Incentives in Multifamily Buildings Outreach to Multifamily Landlords and Tenants Trends in Multifamily Programs: What's Working and

  4. Honeywell Demonstrates Automated Demand Response Benefits for Utility,

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

    Commercial, and Industrial Customers | Department of Energy Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers September 22, 2014 - 5:59pm Addthis Honeywell's Smart Grid Investment Grant (SGIG) project demonstrates utility-scale performance of a hardware/software platform for automated demand response (ADR). This project stands

  5. Regulation Services with Demand Response - Energy Innovation Portal

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

    Regulation Services with Demand Response Pacific Northwest National Laboratory Contact PNNL About This Technology Using grid frequency information, researchers have created algorithms that intelligently control power demand while meeting consumer objectives (i.e. target pricing). Using grid frequency information, researchers have created algorithms that intelligently control power demand while meeting consumer objectives (i.e. target pricing). Technology Marketing Summary Grid Friendly(tm)

  6. Demand Response National Trends: Implications for the West? | Department of

    Energy Savers [EERE]

    Energy National Trends: Implications for the West? Demand Response National Trends: Implications for the West? Committee on Regional Electric Power Cooperation. San Francisco, CA. March 25, 2004 PDF icon Demand Response National Trends: Implications for the West? More Documents & Publications Demand Response in U.S. Electricity Markets: Empirical Evidence Technical Assistance to ISO's and Grid Operators For Loads Providing Ancillary Services To Enhance Grid Reliability Transmission

  7. Demand and Price Outlook for Phase 2 Reformulated Gasoline, 2000

    Gasoline and Diesel Fuel Update (EIA)

    Demand and Price Outlook for Phase 2 Reformulated Gasoline, 2000 Tancred Lidderdale and Aileen Bohn (1) Contents * Summary * Introduction * Reformulated Gasoline Demand * Oxygenate Demand * Logistics o Interstate Movements and Storage o Local Distribution o Phase 2 RFG Logistics o Possible Opt-Ins to the RFG Program o State Low Sulfur, Low RVP Gasoline Initiatives o NAAQS o Tier 2 Gasoline * RFG Production Options o Toxic Air Pollutants (TAP) Reduction o Nitrogen Oxides (NOx) Reduction o

  8. Agreement Template for Energy Conservation and Demand Side Management

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

    Services | Department of Energy Agreement Template for Energy Conservation and Demand Side Management Services Agreement Template for Energy Conservation and Demand Side Management Services Template agreement between a federal agency and a utility company for the implementation of energy conservation measures and demand side management services. A detailed description of the template is also available below. PDF icon Download the template agreement. PDF icon Download the model agreement

  9. 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 ! " #" $ % % & # % " " " ' % ' ( ) * + " % ( , - . / 0 / " 0 . * 0 . * . . " 0 References A short model description Sensitivity tests Results Tropospheric humidity # " humidity 1 % 2 % ' 3 " % + 1 % 2 % % 3 % Updraft entrainment ' + % " 3 % 4 # " + %' 5 6)( . % ' 1 % .7

  10. 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 Center (RReDC) Provides information about biomass, geothermal, solar, and wind energy resources. Measurement and Instrumentation Data Center Provides irradiance and meteorological data from stations throughout the United States. Baseline Measurement System (BMS) Provides live solar radiation data from approximately 70

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

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

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

  12. Hydrogen Demand and Resource Analysis (HyDRA) Model

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

    users to view, download, and analyze hydrogen demand, resource, and infrastructure ... HyDRA contains more than 100 datasets, including resource cost and availability, hydrogen ...

  13. Oil, gas tanker industry responding to demand, contract changes

    SciTech Connect (OSTI)

    True, W.R.

    1998-03-02

    Steady if slower growth in demand for crude oil and natural gas, low levels of scrapping, and a moderate newbuilding pace bode well for the world`s petroleum and natural-gas shipping industries. At year-end 1997, several studies of worldwide demand patterns and shipping fleets expressed short and medium-term optimism for seaborne oil and gas trade and fleet growth. The paper discusses steady demand and shifting patterns, the aging fleet, the slowing products traffic, the world`s fleet, gas carriers, LPG demand, and LPG vessels.

  14. Strategies for Aligning Program Demand with Contractor's Seasonal...

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

    Strategies for Aligning Program Demand with Contractor's Seasonal Fluctuations Better Buildings Neighborhood Program Workforce Peer Exchange Call: Strategies for Aligning Program ...

  15. Strategies for Marketing and Driving Demand for Commercial Financing Products

    Broader source: Energy.gov [DOE]

    Better Buildings Neighborhood Program Financing and Commercial Peer Exchange Call: Strategies for Marketing and Driving Demand for Commercial Financing Products, Call Slides and Discussion Summary, February 2, 2012.

  16. Assessment of Energy Savings Potential from the Use of Demand...

    Office of Scientific and Technical Information (OSTI)

    Energy Savings Potential from the Use of Demand Controlled Ventilation in General Office Spaces in California Citation Details In-Document Search Title: Assessment of Energy ...

  17. Calculating impacts of energy standards on energy demand in U...

    Office of Scientific and Technical Information (OSTI)

    Calculating impacts of energy standards on energy demand in U.S. buildings with uncertainty in an integrated assessment model Citation Details In-Document Search Title: Calculating ...

  18. Table A19. Components of Total Electricity Demand by Census...

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

    Components of Total Electricity Demand by Census Region and" " Economic Characteristics of ...ansfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)",...

  19. Strategies for Aligning Program Demand with Contractor's Seasonal Fluctuations

    Broader source: Energy.gov [DOE]

    Better Buildings Neighborhood Program Workforce Peer Exchange Call: Strategies for Aligning Program Demand with Contractor’s Seasonal Fluctuations, Call Slides and Discussion Summary, June 7, 2012.

  20. Using Partnerships to Drive Demand and Provide Services in Communities...

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

    Using Partnerships to Drive Demand and Provide Services in Communities Better Buildings Neighborhood Program Multifamily and Low-Income Peer Exchange Call: Using Partnerships to ...

  1. Optical People Counting for Demand Controlled Ventilation: A...

    Office of Scientific and Technical Information (OSTI)

    of Counter Performance Citation Details In-Document Search Title: Optical People Counting for Demand Controlled Ventilation: A Pilot Study of Counter Performance This pilot ...

  2. Optical People Counting for Demand Controlled Ventilation: A...

    Office of Scientific and Technical Information (OSTI)

    of Counter Performance Citation Details In-Document Search Title: Optical People Counting for Demand Controlled Ventilation: A Pilot Study of Counter Performance You are ...

  3. China-Transportation Demand Management in Beijing: Mitigation...

    Open Energy Info (EERE)

    demand management (TDM) in Beijing in order to manage the steadily increasing traffic density. The project provides capacity building for decision-makers and transport planners in...

  4. South Korea-ANL Distributed Energy Resources and Demand Side...

    Open Energy Info (EERE)

    is part of a team that assists the Korean government in analyzing the economic and environmental benefits of distributed resources and demand side management (DSM). DSM has...

  5. Amplified Demand for Solar Trackers to Boost Market Growth in...

    Open Energy Info (EERE)

    Amplified Demand for Solar Trackers to Boost Market Growth in Middle East and Africa Home > Groups > Solar Permitting Roadmap Development Wayne31jan's picture Submitted by...

  6. Network-Driven Demand Side Management Website | Open Energy Informatio...

    Open Energy Info (EERE)

    URI: cleanenergysolutions.orgcontentnetwork-driven-demand-side-management Language: English Policies: "Deployment Programs,Regulations" is not in the list of possible...

  7. Estimating Demand Response Market Potential | Open Energy Information

    Open Energy Info (EERE)

    URI: cleanenergysolutions.orgcontentestimating-demand-response-market-pot Language: English Policies: "Deployment Programs,Regulations" is not in the list of possible...

  8. Demand Response Energy Consulting LLC | Open Energy Information

    Open Energy Info (EERE)

    Response Energy Consulting LLC Jump to: navigation, search Name: Demand Response & Energy Consulting LLC Place: Delanson, New York Zip: NY 12053 Sector: Efficiency Product:...

  9. Coordination of Energy Efficiency and Demand Response: A Resource...

    Open Energy Info (EERE)

    Coordination of Energy Efficiency and Demand Response: A Resource of the National Action Plan for Energy Efficiency Jump to: navigation, search Tool Summary LAUNCH TOOL Name:...

  10. Benefits of Demand Response in Electricity Markets and Recommendations...

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

    Demand Response in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005 ...

  11. Chapter 3 Demand-Side Resources | Department of Energy

    Energy Savers [EERE]

    Typically, these resources result from one of two methods of reducing load: energy efficiency or demand response load management. The energy efficiency method designs and deploys ...

  12. Reducing Peak Demand to Defer Power Plant Construction in Oklahoma

    Office of Environmental Management (EM)

    To better control costs and manage electric reliability under these conditions, OG&E is pursuing demand response strategies made possible by implementation of smart grid ...

  13. Electricity demand as frequency controlled reserves, ForskEL...

    Open Energy Info (EERE)

    ForskEL (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ForskEL Country Denmark Coordinates 56.26392,...

  14. Electricity demand as frequency controlled reserves, ENS (Smart...

    Open Energy Info (EERE)

    ENS (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ENS Country Denmark Coordinates 56.26392, 9.501785...

  15. U.S. Electric Utility Demand-Side Management

    Reports and Publications (EIA)

    2002-01-01

    Final issue of this report. - Presents comprehensive information on electric power industry demand side management (DSM) activities in the United States at the national, regional, and utility levels.

  16. Opportunities for Mass Market Demand Response to Provide Ancillary Services

    SciTech Connect (OSTI)

    Pratt, Rob; Najewicz, Dave

    2011-10-01

    Discusses what is meant by mass market demand response to provide ancillary services and outlines opportunities for adoption, and barriers to adoption.

  17. Structuring Rebate and Incentive Programs for Sustainable Demand

    Broader source: Energy.gov [DOE]

    Better Buildings Neighborhood Program Peer Exchange Call: Structuring Rebate and Incentive Programs for Sustainable Demand, call slides and discussion summary, August 18, 2011.

  18. Hydrogen Demand and Resource Assessment Tool | Open Energy Information

    Open Energy Info (EERE)

    Resource Assessment Tool Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Hydrogen Demand and Resource Assessment Tool AgencyCompany Organization: National Renewable...

  19. EnergySolve Demand Response | Open Energy Information

    Open Energy Info (EERE)

    Demand Response Place: Somerset, New Jersey Product: Somerset-based utility bill outsourcing company that provides electronic utility bill auditing, tariff analysis, late fee...

  20. Table 11.2 Electricity: Components of Net Demand, 2010;

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

    Electricity: Components of Net Demand, 2010; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Electricity Components; Unit: Million ...

  1. Assumption to the Annual Energy Outlook 2014 - Commercial Demand...

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

    chosen to meet the projected service demands for the seven major end uses. Once technologies are chosen, the energy consumed by the equipment stock (both existing and purchased...

  2. Towards a Science of Tumor Forecast for Clinical Oncology

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

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

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

  3. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

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

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

    SciTech Connect (OSTI)

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

    1991-09-01

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

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

    SciTech Connect (OSTI)

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

    1991-09-01

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

  6. Natural Gas Infrastructure Implications of Increased Demand from the Electric Sector

    Broader source: Energy.gov [DOE]

    This report examines the potential infrastructure needs of the U.S. interstate natural gas pipeline transmission system across a range of future natural gas demand scenarios that drive increased electric power sector natural gas use. To perform this analysis, the U.S. Department of Energy commissioned Deloitte MarketPoint to examine scenarios in its North American Integrated Model (NAIM), which simultaneously models the electric power and the natural gas sectors. This study concludes that, under scenarios in which natural gas demand from the electric power sector increases, the incremental increase in interstate natural gas pipeline expansion is modest, relative to historical capacity additions. Similarly, capital expenditures on new interstate pipelines in the scenarios considered here are projected to be significantly less than the capital expenditures associated with infrastructure expansion over the last 15 years.

  7. Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid

    SciTech Connect (OSTI)

    Ghatikar, Girish; Mathieu, Johanna L.; Piette, Mary Ann; Kiliccote, Sila

    2010-06-02

    We present an Open Automated Demand Response Communications Specifications (OpenADR) data model capable of communicating real-time prices to electricity customers. We also show how the same data model could be used to for other types of dynamic pricing tariffs (including peak pricing tariffs, which are common throughout the United States). Customers participating in automated demand response programs with building control systems can respond to dynamic prices by using the actual prices as inputs to their control systems. Alternatively, prices can be mapped into"building operation modes," which can act as inputs to control systems. We present several different strategies customers could use to map prices to operation modes. Our results show that OpenADR can be used to communicate dynamic pricing within the Smart Grid and that OpenADR allows for interoperability with existing and future systems, technologies, and electricity markets.

  8. Barrier Immune Radio Communications for Demand Response

    SciTech Connect (OSTI)

    Rubinstein, Francis; Ghatikar, Girish; Granderson, Jessica; Haugen, Paul; Romero, Carlos; Watson, David

    2009-02-01

    Various wireless technologies were field-tested in a six-story laboratory building to identify wireless technologies that can scale for future DR applications through very low node density power consumption, and unit cost. Data analysis included analysis of the signal-to-noise ratio (SNR), packet loss, and link quality at varying power levels and node densities. The narrowband technologies performed well, penetrating the floors of the building with little loss and exhibiting better range than the wideband technology. 900 MHz provided full coverage at 1 watt and substantially complete coverage at 500 mW at the test site. 900 MHz was able to provide full coverage at 100 mW with only one additional relay transmitter, and was the highest-performing technology in the study. 2.4 GHz could not provide full coverage with only a single transmitter at the highest power level tested (63 mW). However, substantially complete coverage was provided at 2.4 GHz at 63 mW with the addition of one repeater node.

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

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

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

  10. Current and future industrial energy service characterizations

    SciTech Connect (OSTI)

    Krawiec, F.; Thomas, T.; Jackson, F.; Limaye, D.R.; Isser, S.; Karnofsky, K.; Davis, T.D.

    1980-10-01

    Current and future energy demands, end uses, and cost used to characterize typical applications and resultant services in the industrial sector of the United States and 15 selected states are examined. A review and evaluation of existing industrial energy data bases was undertaken to assess their potential for supporting SERI research on: (1) market suitability analysis, (2) market development, (3) end-use matching, (3) industrial applications case studies, and (4) identification of cost and performance goals for solar systems and typical information requirements for industrial energy end use. In reviewing existing industrial energy data bases, the level of detail, disaggregation, and primary sources of information were examined. The focus was on fuels and electric energy used for heat and power purchased by the manufacturing subsector and listed by 2-, 3-, and 4-digit SIC, primary fuel, and end use. Projections of state level energy prices to 1990 are developed using the energy intensity approach. The effects of federal and state industrial energy conservation programs on future industrial sector demands were assessed. Future end-use energy requirements were developed for each 4-digit SIC industry and were grouped as follows: (1) hot water, (2) steam (212 to 300/sup 0/F, each 100/sup 0/F interval from 300 to 1000/sup 0/F, and greater than 1000/sup 0/F), and (3) hot air (100/sup 0/F intervals). Volume I details the activities performed in this effort.

  11. Opportunities for Automated Demand Response in California Wastewater Treatment Facilities

    SciTech Connect (OSTI)

    Aghajanzadeh, Arian; Wray, Craig; McKane, Aimee

    2015-08-30

    Previous research over a period of six years has identified wastewater treatment facilities as good candidates for demand response (DR), automated demand response (Auto-­DR), and Energy Efficiency (EE) measures. This report summarizes that work, including the characteristics of wastewater treatment facilities, the nature of the wastewater stream, energy used and demand, as well as details of the wastewater treatment process. It also discusses control systems and automated demand response opportunities. Furthermore, this report summarizes the DR potential of three wastewater treatment facilities. In particular, Lawrence Berkeley National Laboratory (LBNL) has collected data at these facilities from control systems, submetered process equipment, utility electricity demand records, and governmental weather stations. The collected data were then used to generate a summary of wastewater power demand, factors affecting that demand, and demand response capabilities. These case studies show that facilities that have implemented energy efficiency measures and that have centralized control systems are well suited to shed or shift electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. In summary, municipal wastewater treatment energy demand in California is large, and energy-­intensive equipment offers significant potential for automated demand response. In particular, large load reductions were achieved by targeting effluent pumps and centrifuges. One of the limiting factors to implementing demand response is the reaction of effluent turbidity to reduced aeration at an earlier stage of the process. Another limiting factor is that cogeneration capabilities of municipal facilities, including existing power purchase agreements and utility receptiveness to purchasing electricity from cogeneration facilities, limit a facility’s potential to participate in other DR activities.

  12. The Boom of Electricity Demand in the Residential Sector in the Developing World and the Potential for Energy Efficiency

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2008-05-13

    With the emergence of China as the world's largest energy consumer, the awareness of developing country energy consumption has risen. According to common economic scenarios, the rest of the developing world will probably see an economic expansion as well. With this growth will surely come continued rapid growth in energy demand. This paper explores the dynamics of that demand growth for electricity in the residential sector and the realistic potential for coping with it through efficiency. In 2000, only 66% of developing world households had access to electricity. Appliance ownership rates remain low, but with better access to electricity and a higher income one can expect that households will see their electricity consumption rise significantly. This paper forecasts developing country appliance growth using econometric modeling. Products considered explicitly - refrigerators, air conditioners, lighting, washing machines, fans, televisions, stand-by power, water heating and space heating - represent the bulk of household electricity consumption in developing countries. The resulting diffusion model determines the trend and dynamics of demand growth at a level of detail not accessible by models of a more aggregate nature. In addition, the paper presents scenarios for reducing residential consumption through cost-effective and/or best practice efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, which allows for a realistic assessment of efficiency opportunities at the national or regional level. The past decades have seen some of the developing world moving towards a standard of living previously reserved for industrialized countries. Rapid economic development, combined with large populations has led to first China and now India to emerging as 'energy giants', a phenomenon that is expected to continue, accelerate and spread to other countries. This paper explores the potential for slowing energy consumption and greenhouse gas emissions in the residential sector in developing countries and evaluates the potential of energy savings and emissions mitigation through market transformation programs such as, but not limited to Energy Efficiency Standards and Labeling (EES&L). The bottom-up methodology used allows one to identify which end uses and regions have the greatest potential for savings.

  13. Impacts of increased bioenergy demand on global food markets: an AgMIP economic model intercomparison

    SciTech Connect (OSTI)

    Lotze-Campen, Hermann; von Lampe, Martin; Kyle, G. Page; Fujimori, Shinichiro; Havlik, Petr; van Meijl, Hans; Hasegawa, Tomoko; Popp, Alexander; Schmitz, Christoph; Tabeau, Andrzej; Valin, Hugo; Willenbockel, Dirk; Wise, Marshall A.

    2014-01-01

    Integrated Assessment studies have shown that meeting ambitious greenhouse gas mitigation targets will require substantial amounts of bioenergy as part of the future energy mix. In the course of the Agricultural Model Comparison and Improvement Project (AgMIP), five global agro-economic models were used to analyze a future scenario with global demand for ligno-cellulosic bioenergy rising to about 100 ExaJoule in 2050. From this exercise a tentative conclusion can be drawn that ambitious climate change mitigation need not drive up global food prices much, if the extra land required for bioenergy production is accessible or if the feedstock, e.g. from forests, does not directly compete for agricultural land. Agricultural price effects across models by the year 2050 from high bioenergy demand in an RCP2.6-type scenario appear to be much smaller (+5% average across models) than from direct climate impacts on crop yields in an RCP8.5-type scenario (+25% average across models). However, potential future scarcities of water and nutrients, policy-induced restrictions on agricultural land expansion, as well as potential welfare losses have not been specifically looked at in this exercise.

  14. Availability of Canadian imports to meet U.S. demand for ethane, propane and butane

    SciTech Connect (OSTI)

    Hawkins, D.J.

    1996-12-31

    Historically, Canada has had a surplus of ethane, propane and butane. Almost all of the available propane and butane in Canadian natural gas streams is recovered. While there is significant ethane recovery in Canada, ethane that cannot be economically sold is left in the gas streams. All of the surplus Canadian ethane and most of the Canadian surplus propane and butane is exported to the US. Some volumes of Canadian propane and butane have been moved offshore by marine exports to the Asia-Pacific region or South America, or directly to Mexico by rail. Essentially all of the Canadian ethane, 86% of the propane and 74% of the butane are recovered by gas processing. Canadian natural gas production has increased significantly over the last 10 years. Canadian gas resources in the Western Canadian Sedimentary Basin should permit further expansion of gas exports, and several gas pipeline projects are pending to expand the markets for Canadian gas in the US. The prospective increase in Canadian gas production will yield higher volumes of ethane, propane and butane. While there is a potential to expand domestic markets for ethane, propane and butane, a significant part of the incremental production will move to export markets. This paper provides a forecast of the expected level of ethane, propane and butane exports from Canada and discusses the supply, demand and logistical developments which may affect export availability from Canada.

  15. Role of Storage and Demand Response, Greening the Grid

    SciTech Connect (OSTI)

    Author: Denholm, Paul

    2015-09-01

    Greening the Grid provides technical assistance to energy system planners, regulators, and grid operators to overcome challenges associated with integrating variable renewable energy into the grid. This document, part of a Greening the Grid toolkit, examines storage and demand response as means to match renewable energy supply with demand.

  16. Open Automated Demand Response for Small Commerical Buildings

    SciTech Connect (OSTI)

    Dudley, June Han; Piette, Mary Ann; Koch, Ed; Hennage, Dan

    2009-05-01

    This report characterizes small commercial buildings by market segments, systems and end-uses; develops a framework for identifying demand response (DR) enabling technologies and communication means; and reports on the design and development of a low-cost OpenADR enabling technology that delivers demand reductions as a percentage of the total predicted building peak electric demand. The results show that small offices, restaurants and retail buildings are the major contributors making up over one third of the small commercial peak demand. The majority of the small commercial buildings in California are located in southern inland areas and the central valley. Single-zone packaged units with manual and programmable thermostat controls make up the majority of heating ventilation and air conditioning (HVAC) systems for small commercial buildings with less than 200 kW peak electric demand. Fluorescent tubes with magnetic ballast and manual controls dominate this customer group's lighting systems. There are various ways, each with its pros and cons for a particular application, to communicate with these systems and three methods to enable automated DR in small commercial buildings using the Open Automated Demand Response (or OpenADR) communications infrastructure. Development of DR strategies must consider building characteristics, such as weather sensitivity and load variability, as well as system design (i.e. under-sizing, under-lighting, over-sizing, etc). Finally, field tests show that requesting demand reductions as a percentage of the total building predicted peak electric demand is feasible using the OpenADR infrastructure.

  17. Progress toward Producing Demand-Response-Ready Appliances

    SciTech Connect (OSTI)

    Hammerstrom, Donald J.; Sastry, Chellury

    2009-12-01

    This report summarizes several historical and ongoing efforts to make small electrical demand-side devices like home appliances more responsive to the dynamic needs of electric power grids. Whereas the utility community often reserves the word demand response for infrequent 2 to 6 hour curtailments that reduce total electrical system peak load, other beneficial responses and ancillary services that may be provided by responsive electrical demand are of interest. Historically, demand responses from the demand side have been obtained by applying external, retrofitted, controlled switches to existing electrical demand. This report is directed instead toward those manufactured products, including appliances, that are able to provide demand responses as soon as they are purchased and that require few, or no, after-market modifications to make them responsive to needs of power grids. Efforts to be summarized include Open Automated Demand Response, the Association of Home Appliance Manufacturer standard CHA 1, a simple interface being developed by the U-SNAP Alliance, various emerging autonomous responses, and the recent PinBus interface that was developed at Pacific Northwest National Laboratory.

  18. Reducing Energy Demand in Buildings Through State Energy Codes | Department

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

    of Energy Reducing Energy Demand in Buildings Through State Energy Codes Reducing Energy Demand in Buildings Through State Energy Codes Building Codes Project for the 2013 Building Technologies Office's Program Peer Review PDF icon bldgcodes03_guttman_040213.pdf More Documents & Publications Technology Performance Exchange - 2013 BTO Peer Review Atmospheric Pressure Deposition for Electrochromic Windows Building America System Research

  19. Interoperability of Demand Response Resources Demonstration in NY

    SciTech Connect (OSTI)

    Wellington, Andre

    2014-03-31

    The Interoperability of Demand Response Resources Demonstration in NY (Interoperability Project) was awarded to Con Edison in 2009. The objective of the project was to develop and demonstrate methodologies to enhance the ability of customer sited Demand Response resources to integrate more effectively with electric delivery companies and regional transmission organizations.

  20. Impacts of Climate Change on Energy Consumption and Peak Demand in Buildings: A Detailed Regional Approach

    SciTech Connect (OSTI)

    Dirks, James A.; Gorrissen, Willy J.; Hathaway, John E.; Skorski, Daniel C.; Scott, Michael J.; Pulsipher, Trenton C.; Huang, Maoyi; Liu, Ying; Rice, Jennie S.

    2015-01-01

    This paper presents the results of numerous commercial and residential building simulations, with the purpose of examining the impact of climate change on peak and annual building energy consumption over the portion of the Eastern Interconnection (EIC) located in the United States. The climate change scenario considered (IPCC A2 scenario as downscaled from the CASCaDE data set) has changes in mean climate characteristics as well as changes in the frequency and duration of intense weather events. This investigation examines building energy demand for three annual periods representative of climate trends in the CASCaDE data set at the beginning, middle, and end of the century--2004, 2052, and 2089. Simulations were performed using the Building ENergy Demand (BEND) model which is a detailed simulation platform built around EnergyPlus. BEND was developed in collaboration with the Platform for Regional Integrated Modeling and Analysis (PRIMA), a modeling framework designed to simulate the complex interactions among climate, energy, water, and land at decision-relevant spatial scales. Over 26,000 building configurations of different types, sizes, vintages, and, characteristics which represent the population of buildings within the EIC, are modeled across the 3 EIC time zones using the future climate from 100 locations within the target region, resulting in nearly 180,000 spatially relevant simulated demand profiles for each of the 3 years. In this study, the building stock characteristics are held constant based on the 2005 building stock in order to isolate and present results that highlight the impact of the climate signal on commercial and residential energy demand. Results of this analysis compare well with other analyses at their finest level of specificity. This approach, however, provides a heretofore unprecedented level of specificity across multiple spectrums including spatial, temporal, and building characteristics. This capability enables the ability to perform detailed hourly impact studies of building adaptation and mitigation strategies on energy use and electricity peak demand within the context of the entire grid and economy.

  1. Future City Competition

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

    Future City Competition The New Mexico Regional Competition is an unique opportunity for middle school children to combine skills in engineering, environmental science, and art to...

  2. Energy for our Future

    Energy Savers [EERE]

    ... gallons of diesel per year "Stronger Together for the Next 100 Years" Looking into The Future... (Traditional Athabascan Solar Array?) "Stronger Together for the Next 100 Years"

  3. My Amazing Future 2012

    ScienceCinema (OSTI)

    None

    2013-05-28

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

  4. Transportation Energy Futures Snapshot

    Broader source: Energy.gov [DOE]

    This snapshot is a summary of the EERE reports that provide a detailed analysis of opportunities and challenges along the path to a more sustainable transportation energy future.

  5. Growing the Future Bioeconomy

    Broader source: Energy.gov [DOE]

    Breakout Session IA—Conversion Technologies I: Industrial Perspectives on Pathways to Advanced Biofuels Growing the Future Bioeconomy Joel Velasco, Senior Vice President, Amyris, Inc

  6. AVTA: EVSE Charging Protocol for On and Off-Peak Demand

    Broader source: Energy.gov [DOE]

    The Vehicle Technologies Office's Advanced Vehicle Testing Activity carries out testing on a wide range of advanced vehicles and technologies on dynamometers, closed test tracks, and on-the-road. These results provide benchmark data that researchers can use to develop technology models and guide future research and development. The following report is a description of development of a charge protocol to take advantage of off and on-peak demand economics at facilities, as informed by the AVTA's testing on plug-in electric vehicle charging equipment. This research was conducted by Idaho National Laboratory.

  7. Utility rebates for efficient motors -- The outlook for demand-side management

    SciTech Connect (OSTI)

    Nailen, R.L.

    1997-01-01

    Since 1987, many electric utilities throughout North America have been actively promoting demand-side management (DSM), the attempt to conserve fuels and postpone costly generating capacity increases by encouraging customers to use more efficient electrical equipment, including motors. One popular DSM program has been utility payment of cash rebates to purchasers of more efficient motors. Today, such payments face extinction in a rapidly changing utility economic climate based on deregulation. How rebates originated, the basis for such payments, how successful rebate programs have been, and what the future holds for them are the subjects of this paper.

  8. Utility rebates for efficient motors -- The outlook for demand-side management

    SciTech Connect (OSTI)

    Nailen, R.L.

    1995-12-31

    Since 1987, many electric utilities throughout North America have been actively promoting DSM--demand-side management, the attempt to conserve fuels and postpone costly generating capacity increases by encouraging customers to use more efficient electrical equipment, including motors. One popular DSM program has been utility payment of cash rebates to purchasers of more efficient motors. Today, such payments face extinction in a rapidly changing utility economic climate based on deregulation. How rebates originated, the basis for such payments, how successful rebate programs have been, and what the future holds for them--these are the subjects of this paper.

  9. Local government involvement in long term resource planning for community energy systems. Demand side management

    SciTech Connect (OSTI)

    Not Available

    1992-03-01

    A program was developed to coordinate governmental, research, utility, and business energy savings efforts, and to evaluate future potential actions, based on actual field data obtained during the implementation of Phase I of the State Resource Plan. This has lead to the establishment of a state conservation and energy efficiency fund for the purpose of establishing a DSM Program. By taking a state wide perspective on resource planning, additional savings, including environmental benefits, can be achieved through further conservation and demand management. This effort has already blossomed into a state directive for DSM programs for the natural gas industry.

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

    SciTech Connect (OSTI)

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

    2009-12-03

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

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

  12. Development and evaluation of fully automated demand response in large facilities

    SciTech Connect (OSTI)

    Piette, Mary Ann; Sezgen, Osman; Watson, David S.; Motegi, Naoya; Shockman, Christine; ten Hope, Laurie

    2004-03-30

    This report describes the results of a research project to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve electric grid reliability, manage electricity costs, and ensure that customers receive signals that encourage load reduction during times when the electric grid is near its capacity. The two main drivers for widespread demand responsiveness are the prevention of future electricity crises and the reduction of electricity prices. Additional goals for price responsiveness include equity through cost of service pricing, and customer control of electricity usage and bills. The technology developed and evaluated in this report could be used to support numerous forms of DR programs and tariffs. For the purpose of this report, we have defined three levels of Demand Response automation. Manual Demand Response involves manually turning off lights or equipment; this can be a labor-intensive approach. Semi-Automated Response involves the use of building energy management control systems for load shedding, where a preprogrammed load shedding strategy is initiated by facilities staff. Fully-Automated Demand Response is initiated at a building or facility through receipt of an external communications signal--facility staff set up a pre-programmed load shedding strategy which is automatically initiated by the system without the need for human intervention. We have defined this approach to be Auto-DR. An important concept in Auto-DR is that a facility manager is able to ''opt out'' or ''override'' an individual DR event if it occurs at a time when the reduction in end-use services is not desirable. This project sought to improve the feasibility and nature of Auto-DR strategies in large facilities. The research focused on technology development, testing, characterization, and evaluation relating to Auto-DR. This evaluation also included the related decisionmaking perspectives of the facility owners and managers. Another goal of this project was to develop and test a real-time signal for automated demand response that provided a common communication infrastructure for diverse facilities. The six facilities recruited for this project were selected from the facilities that received CEC funds for new DR technology during California's 2000-2001 electricity crises (AB970 and SB-5X).

  13. The Hanford Story: Future

    Broader source: Energy.gov [DOE]

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

  14. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M.

    2012-10-01

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

  15. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M.; Mai, T.

    2012-08-01

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

  16. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-08-01

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

  17. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-08-01

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

  18. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M. M.

    2012-08-01

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

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

    SciTech Connect (OSTI)

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

    1994-05-01

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

  20. 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.