National Library of Energy BETA

Sample records for monthly peak demand

  1. Optimization of Demand Response Through Peak Shaving

    E-Print Network [OSTI]

    Jul 5, 2013 ... Optimization of Demand Response Through Peak Shaving. G. Zakeri(g.zakeri *** at*** auckland.ac.nz) D. Craigie(David.Craigie ***at*** ...

  2. ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Council Region, "

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by9" ,"Released:3a. January Monthly Peak Hour

  3. A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

    E-Print Network [OSTI]

    Hong, Tianzhen

    2014-01-01

    reduction of peak electricity demand, and percentage savingsvariables and monthly electricity demand. Applied Energychanges of peak electricity demand. (a) large office, 90.1-

  4. ,"Table 3A.1. January Monthly Peak Hour Demand, by North American Electric Reliability Corporation Assesment Area,"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by9" ,"Released: December 2010"20052b.3A.1.

  5. ,"Table 3B.1. FRCC Monthly Peak Hour Demand, by North American Electric Reliability Corporation Assesment Area,"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by9" ,"Released: December

  6. ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by9" ,"Released: December6" ,"Released:

  7. ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by9" ,"Released: December6"

  8. ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Corporation Region, "

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by9" ,"Released: December6"January

  9. ,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected by North American Electric Reliability Council Region, "

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by9" ,"Released:

  10. Monitoring System Used to Identify, Track and Allocate Peak Demand Costs 

    E-Print Network [OSTI]

    Holmes, W. A.

    1998-01-01

    , it was clear that the percentage contribution by department or area to the plant's peak demand was not the same as that assigned based solely upon consumption. With a monthly peak exceeding 8 MW and peak demand charges accounting for more than 60...

  11. Optimization of Demand Response Through Peak Shaving

    E-Print Network [OSTI]

    2013-06-19

    Jun 19, 2013 ... efficient linear programming formulation for the demand response of such a consumer who could be a price taker, industrial or commercial user ...

  12. Optimization of Demand Response Through Peak Shaving , D. Craigie

    E-Print Network [OSTI]

    Todd, Michael J.

    Optimization of Demand Response Through Peak Shaving G. Zakeri , D. Craigie , A. Philpott , M. Todd for the demand response of such a consumer. We will establish a monotonicity result that indicates fuel supply

  13. How are flat demand charges based on the highest peak over the...

    Open Energy Info (EERE)

    How are flat demand charges based on the highest peak over the past 12 months designated in the database (LADWP does this) Home > Groups > Utility Rate Submitted by Marcroper on 11...

  14. Scalable Scheduling of Building Control Systems for Peak Demand Reduction

    E-Print Network [OSTI]

    Pappas, George J.

    price for their maximum demand to discourage their energy usage in peak load conditions. In buildings of Pennsylvania {nghiem, mbehl, rahulm, pappasg}@seas.upenn.edu Abstract-- In large energy systems, peak demand might cause severe issues such as service disruption and high cost of energy production and distribution

  15. Smoothing the Energy Consumption: Peak Demand Reduction in Smart Grid

    E-Print Network [OSTI]

    Li, Xiang-Yang

    % of the nation's total electricity consumption. Unfortunately, due to inefficient energy consumption patternSmoothing the Energy Consumption: Peak Demand Reduction in Smart Grid Shaojie Tang , Qiuyuan Huang of Software, TNLIST, Tsinghua University Department of Electrical & Computer Engineering, University

  16. Storing hydroelectricity to meet peak-hour demand

    SciTech Connect (OSTI)

    Valenti, M.

    1992-04-01

    This paper reports on pumped storage plants which have become an effective way for some utility companies that derive power from hydroelectric facilities to economically store baseload energy during off-peak hours for use during peak hourly demands. According to the Electric Power Research Institute (EPRI) in Palo Alto, Calif., 36 of these plants provide approximately 20 gigawatts, or about 3 percent of U.S. generating capacity. During peak-demand periods, utilities are often stretched beyond their capacity to provide power and must therefore purchase it from neighboring utilities. Building new baseload power plants, typically nuclear or coal-fired facilities that run 24 hours per day seven days a week, is expensive, about $1500 per kilowatt, according to Robert Schainker, program manager for energy storage at the EPRI. Schainker the that building peaking plants at $400 per kilowatt, which run a few hours a day on gas or oil fuel, is less costly than building baseload plants. Operating them, however, is more expensive because peaking plants are less efficient that baseload plants.

  17. The role of building technologies in reducing and controlling peak electricity demand

    E-Print Network [OSTI]

    Koomey, Jonathan; Brown, Richard E.

    2002-01-01

    AND CONTROLLING PEAK ELECTRICITY DEMAND Jonathan Koomey* andData to Improve Electricity Demand Forecasts–Final Report.further research. Electricity demand varies constantly. At

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

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

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

  19. Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike

    E-Print Network [OSTI]

    DeForest, Nicholas

    2014-01-01

    driver of summer peak electricity demand. In the developingin reducing peak electricity demand. Additionally, annualwill drive total electricity demand significantly above

  20. THE ROLE OF BUILDING TECHNOLOGIES IN REDUCING AND CONTROLLING PEAK ELECTRICITY DEMAND

    E-Print Network [OSTI]

    LBNL-49947 THE ROLE OF BUILDING TECHNOLOGIES IN REDUCING AND CONTROLLING PEAK ELECTRICITY DEMAND? ..................................... 8 What are the seasonal aspects of electric peak demand?............................ 9 What because of the California electricity crisis (Borenstein 2001). Uncertainties surrounding the reliability

  1. Exploring Power-Voltage Relationship for Distributed Peak Demand Flattening in Microgrids

    E-Print Network [OSTI]

    Adali, Tulay

    Exploring Power-Voltage Relationship for Distributed Peak Demand Flattening in Microgrids Zhichuan energy storage units in microgrids, how to regulate peak demand is one of the main challenges. Thus, it is possible that peak demand of the microgrid would not be flattened but only shifted to another period

  2. Data Center Demand Response: Avoiding the Coincident Peak via Workload Shifting and Local Generation

    E-Print Network [OSTI]

    Wierman, Adam

    Data Center Demand Response: Avoiding the Coincident Peak via Workload Shifting and Local facilities. In this extended abstract we briefly de- scribe recent work in [1] on two demand response schemes Keywords Demand response, coincident peak pricing, data center, work- load shifting, online algorithm 1

  3. Reducing Peak Demand to Defer Power Plant Construction in Oklahoma

    Office of Environmental Management (EM)

    in-home displays, programmable communicating thermostats, and access to a web portal (http:www.myOGEpower.com). The study measures demand reductions by customers during...

  4. A Fresh Look at Weather Impact on Peak Electricity Demand and

    E-Print Network [OSTI]

    LBNL-6280E A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data Road, Berkeley, CA 94720, USA 2 Green Energy and Environment Research Laboratories, Industrial

  5. Peak demand reduction from pre-cooling with zone temperature reset in an office building

    SciTech Connect (OSTI)

    Xu, Peng; Haves, Philip; Piette, Mary Ann; Braun, James

    2004-08-01

    The objective of this study was to demonstrate the potential for reducing peak-period electrical demand in moderate-weight commercial buildings by modifying the control of the HVAC system. An 80,000 ft{sup 2} office building with a medium-weight building structure and high window-to-wall ratio was used for a case study in which zone temperature set-points were adjusted prior to and during occupancy. HVAC performance data and zone temperatures were recorded using the building control system. Additional operative temperature sensors for selected zones and power meters for the chillers and the AHU fans were installed for the study. An energy performance baseline was constructed from data collected during normal operation. Two strategies for demand shifting using the building thermal mass were then programmed in the control system and implemented progressively over a period of one month. It was found that a simple demand limiting strategy performed well in this building. This strategy involved maintaining zone temperatures at the lower end of the comfort region during the occupied period up until 2 pm. Starting at 2 pm, the zone temperatures were allowed to float to the high end of the comfort region. With this strategy, the chiller power was reduced by 80-100% (1-2.3 W/ft{sup 2}) during normal peak hours from 2-5 pm, without causing any thermal comfort complaints. The effects on the demand from 2-5 pm of the inclusion of pre-cooling prior to occupancy are unclear.

  6. Peak Demand Reduction from Pre-Cooling with Zone Temperature Reset in an Office Building

    SciTech Connect (OSTI)

    Xu, Peng; Haves, Philip; Piette, Mary Ann; Braun, James

    2006-08-01

    The objective of this study was to demonstrate the potential for reducing peak-period electrical demand in moderate-weight commercial buildings by modifying the control of the HVAC system. An 80,000 ft{sup 2} office building with a medium-weight building structure and high window-to-wall ratio was used for a case study in which zone temperature set-points were adjusted prior to and during occupancy. HVAC performance data and zone temperatures were recorded using the building control system. Additional operative temperature sensors for selected zones and power meters for the chillers and the AHU fans were installed for the study. An energy performance baseline was constructed from data collected during normal operation. Two strategies for demand shifting using the building thermal mass were then programmed in the control system and implemented progressively over a period of one month. It was found that a simple demand limiting strategy performed well in this building. This strategy involved maintaining zone temperatures at the lower end of the comfort region during the occupied period up until 2 pm. Starting at 2 pm, the zone temperatures were allowed to float to the high end of the comfort region. With this strategy, the chiller power was reduced by 80-100% (1-2.3 W/ft{sup 2}) during normal peak hours from 2-5 pm, without causing any thermal comfort complaints. The effects on the demand from 2-5 pm of the inclusion of pre-cooling prior to occupancy are unclear.

  7. Demand Response and Peak Load Management; Programs, Products and Technology 

    E-Print Network [OSTI]

    Barth, A.

    2015-01-01

    Management: Programs, Products, and Technology IETC 2015 ESL-IE-15-06-13 Proceedings of the Thrity-Seventh Industrial Energy Technology Conference New Orleans, LA. June 2-4, 2015 2Supply & Demand Power Demand Grid Stability Reliability Risk Price Availability... ESL-IE-15-06-13 Proceedings of the Thrity-Seventh Industrial Energy Technology Conference New Orleans, LA. June 2-4, 2015 What Should We Expect? 0 1000 2000 3000 4000 5000 6000 2 0 1 1 2 0 1 2 2 0 1 3 2 0 1 4 2 0 1 5 2 0 1 6 2 0 1 7 2 0 1 8 2 0 1 9 2 0...

  8. Evidence is growing on demand side of an oil peak

    SciTech Connect (OSTI)

    2009-07-15

    After years of continued growth, the number of miles driven by Americans started falling in December 2007. Not only are the number of miles driven falling, but as cars become more fuel efficient, they go further on fewer gallons - further reducing demand for gasoline. This trend is expected to accelerate. Drivers include, along with higher-efficiency cars, mass transit, reversal in urban sprawl, biofuels, and plug-in hybrid vehicles.

  9. (2013) 128 Data Center Demand Response: Avoiding the Coincident Peak via

    E-Print Network [OSTI]

    Wierman, Adam

    2013-01-01

    (2013) 1­28 Data Center Demand Response: Avoiding the Coincident Peak via Workload Shifting.chen@hp.com Abstract Demand response is a crucial aspect of the future smart grid. It has the potential to provide centers' participation in demand response is becoming increasingly important given their high

  10. The role of building technologies in reducing and controlling peak electricity demand

    SciTech Connect (OSTI)

    Koomey, Jonathan; Brown, Richard E.

    2002-09-01

    Peak power demand issues have come to the fore recently because of the California electricity crisis. Uncertainties surrounding the reliability of electric power systems in restructured markets as well as security worries are the latest reasons for such concerns, but the issues surrounding peak demand are as old as the electric utility system itself. The long lead times associated with building new capacity, the lack of price response in the face of time-varying costs, the large difference between peak demand and average demand, and the necessity for real-time delivery of electricity all make the connection between system peak demand and system reliability an important driver of public policy in the electric utility sector. This exploratory option paper was written at the request of Jerry Dion at the U.S.Department of Energy (DOE). It is one of several white papers commissioned in 2002 exploring key issues of relevance to DOE. This paper explores policy-relevant issues surrounding peak demand, to help guide DOE's research efforts in this area. The findings of this paper are as follows. In the short run, DOE funding of deployment activities on peak demand can help society achieve a more economically efficient balance between investments in supply and demand-side technologies. DOE policies can promote implementation of key technologies to ameliorate peak demand, through government purchasing, technology demonstrations, and improvements in test procedures, efficiency standards, and labeling programs. In the long run, R&D is probably the most important single leverage point for DOE to influence the peak demand issue. Technologies for time-varying price response hold great potential for radically altering the way people use electricity in buildings, but are decades away from widespread use, so DOE R&D and expertise can make a real difference here.

  11. Building America Top Innovations 2012: High-Performance with Solar Electric Reduced Peak Demand

    SciTech Connect (OSTI)

    none,

    2013-01-01

    This Building America Top Innovations profile describes Building America solar home research that has demonstrated the ability to reduce peak demand by 75%. Numerous field studies have monitored power production and system effectiveness.

  12. Electrical Energy Conservation and Peak Demand Reduction Potential for Buildings in Texas: Preliminary Results 

    E-Print Network [OSTI]

    Hunn, B. D.; Baughman, M. L.; Silver, S. C.; Rosenfeld, A. H.; Akbari, H.

    1985-01-01

    This paper presents preliminary results of a study of electrical energy conservation and peak demand reduction potential for the building sector in Texas. Starting from 1980 building stocks and energy use characteristics, technical conservation...

  13. The Impact of Residential Air Conditioner Charging and Sizing on Peak Electrical Demand 

    E-Print Network [OSTI]

    Neal, L.; O'Neal, D. L.

    1992-01-01

    of Residential Air Conditioner Charging and Sizing on Peak Electrical Demand Leon Neal North Carolina Alternate Energy Corporation Research Triangle Park, N.C. ABSTRACT Electric utilities have had a number of air conditioner rebate and maintenance... of the equipment), system sizing, and efficiency on the steady-state, coincident peak utility demand of a residential central air conditioning system. The study is based on the results of laboratory tests of a three-ton, capillary tube expansion, split...

  14. Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike

    E-Print Network [OSTI]

    DeForest, Nicholas

    2014-01-01

    Effect of Heat and Electricity Storage and Reliability onThermal Energy Storage for Electricity Peak- demandemployer. Thermal Energy Storage for Electricity Peak-demand

  15. (2013) 128 Data Center Demand Response: Avoiding the Coincident Peak via

    E-Print Network [OSTI]

    Low, Steven H.

    2013-01-01

    significant peak demand reduction and to ease the incorporation of renewable energy into the grid. Data has the potential to significantly ease the adoption of renewable energy into the grid. Data centers.chen@hp.com Abstract Demand response is a crucial aspect of the future smart grid. It has the potential to provide

  16. Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California

    SciTech Connect (OSTI)

    Yin, Rongxin; Kiliccote, Sila; Piette, Mary Ann; Parrish, Kristen

    2010-05-14

    This paper reports on the potential impact of demand response (DR) strategies in commercial buildings in California based on the Demand Response Quick Assessment Tool (DRQAT), which uses EnergyPlus simulation prototypes for office and retail buildings. The study describes the potential impact of building size, thermal mass, climate, and DR strategies on demand savings in commercial buildings. Sensitivity analyses are performed to evaluate how these factors influence the demand shift and shed during the peak period. The whole-building peak demand of a commercial building with high thermal mass in a hot climate zone can be reduced by 30percent using an optimized demand response strategy. Results are summarized for various simulation scenarios designed to help owners and managers understand the potential savings for demand response deployment. Simulated demand savings under various scenarios were compared to field-measured data in numerous climate zones, allowing calibration of the prototype models. The simulation results are compared to the peak demand data from the Commercial End-Use Survey for commercial buildings in California. On the economic side, a set of electricity rates are used to evaluate the impact of the DR strategies on economic savings for different thermal mass and climate conditions. Our comparison of recent simulation to field test results provides an understanding of the DR potential in commercial buildings.

  17. Peak-Coincident Demand Savings from Behavior-Based Programs: Evidence from PPL Electric's Behavior and Education Program

    E-Print Network [OSTI]

    Stewart, James

    2013-01-01

    peak loads such as air conditioning. 1 The total peak loadand evenings when air conditioning loads are high. All ofelectric heat and air conditioning; (3) a complete monthly

  18. Duct Leakage Impacts on Airtightness, Infiltration, and Peak Electrical Demand in Florida Homes 

    E-Print Network [OSTI]

    Cummings, J. B.; Tooley, J. J.; Moyer, N.

    1990-01-01

    (ACHSO). When the duct registers were sealed, ACHSO decreased to 11.04, indicating that 12.2% of the house leaks were in the duct system. Duct leaks have a dramatic impact upon peak electrical demand. Based on theoretical analysis, a fifteen percent...

  19. Phase-Change Frame Walls (PCFWs) for Peak Demand Reduction, Load Shifting, Energy Conservation and Comfort 

    E-Print Network [OSTI]

    Medina, M.; Stewart, R.

    2008-01-01

    of the wall via the high latent heats of the PCMs. The main goal of this study was to determine the feasibility of using PCFWs for peak air conditioning demand reduction, thermal load shifting, energy conservation, and thermal comfort. The results showed...

  20. The Influence of Air-Conditioning Efficiency in the Peak Load Demand for Kuwait 

    E-Print Network [OSTI]

    Ali, A. A.; Maheshwari, G. P.

    2007-01-01

    A model co-relating the peak load demand of a utility with the allowable power rating (PR) of air-conditioning (AC) systems has been developed in this paper through a well defined methodology. The model is capable to predict the extent of allowable...

  1. Abstract--This paper formulates and develops a peak demand control tool for electric systems within the framework of direct

    E-Print Network [OSTI]

    Catholic University of Chile (Universidad Católica de Chile)

    techniques. Index Terms--Demand Side Management, direct load control, peak demand control, genetic algorithms in order to evaluate the suitability of the decision chosen. Demand Side Management (DSM) plans attempt of application has been developed in the field of demand management; however, the high energy consumption growth

  2. Modeling of GE Appliances in GridLAB-D: Peak Demand Reduction

    SciTech Connect (OSTI)

    Fuller, Jason C.; Vyakaranam, Bharat GNVSR; Prakash Kumar, Nirupama; Leistritz, Sean M.; Parker, Graham B.

    2012-04-29

    The widespread adoption of demand response enabled appliances and thermostats can result in significant reduction to peak electrical demand and provide potential grid stabilization benefits. GE has developed a line of appliances that will have the capability of offering several levels of demand reduction actions based on information from the utility grid, often in the form of price. However due to a number of factors, including the number of demand response enabled appliances available at any given time, the reduction of diversity factor due to the synchronizing control signal, and the percentage of consumers who may override the utility signal, it can be difficult to predict the aggregate response of a large number of residences. The effects of these behaviors can be modeled and simulated in open-source software, GridLAB-D, including evaluation of appliance controls, improvement to current algorithms, and development of aggregate control methodologies. This report is the first in a series of three reports describing the potential of GE's demand response enabled appliances to provide benefits to the utility grid. The first report will describe the modeling methodology used to represent the GE appliances in the GridLAB-D simulation environment and the estimated potential for peak demand reduction at various deployment levels. The second and third reports will explore the potential of aggregated group actions to positively impact grid stability, including frequency and voltage regulation and spinning reserves, and the impacts on distribution feeder voltage regulation, including mitigation of fluctuations caused by high penetration of photovoltaic distributed generation and the effects on volt-var control schemes.

  3. Reducing Residential Peak Electricity Demand with Mechanical Pre-Cooling of Building Thermal Mass

    SciTech Connect (OSTI)

    Turner, Will; Walker, Iain; Roux, Jordan

    2014-08-01

    This study uses an advanced airflow, energy and humidity modelling tool to evaluate the potential for residential mechanical pre-cooling of building thermal mass to shift electricity loads away from the peak electricity demand period. The focus of this study is residential buildings with low thermal mass, such as timber-frame houses typical to the US. Simulations were performed for homes in 12 US DOE climate zones. The results show that the effectiveness of mechanical pre-cooling is highly dependent on climate zone and the selected pre-cooling strategy. The expected energy trade-off between cooling peak energy savings and increased off-peak energy use is also shown.

  4. 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.

  5. 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.

  6. Testing of peak demand limiting using thermal mass at a small commercial building

    E-Print Network [OSTI]

    Lee, Kyoung-Ho; Braun, James E; Fredrickson, Steve; Konis, Kyle; Arens, Edward

    2007-01-01

    Submitted to the: Demand Response Research Center Preparedat Berkeley July 2007 Demand Response Research Center, Julywas coordinated by the Demand Response Research Center and

  7. Industrial-Load-Shaping: The Practice of and Prospects for Utility/Industry Cooperation to Manage Peak Electricity Demand 

    E-Print Network [OSTI]

    Bules, D. J.; Rubin, D. E.; Maniates, M. F.

    1986-01-01

    -LOAD-SHAPI1IG: TIlE PRACTICE OF AND PROSPECTS FOR UTILITY/INDUSTRY COOPERATION TO MAUGE PEAK ELECTRICITY DEMAND Donald J. BuIes and David E. Rubin Consultants, Pacific Gas and Electric Company San Francisco, California Michael F. Maniates Energy... and Resources Group, University of California Berkeley, California ABSTRACT Load-management programs designed to reduce demand for electricity during peak periods are becoming increasingly important to electric utilities. For a gf'owing number...

  8. Property:OpenEI/UtilityRate/FlatDemandMonth7 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2FlatDemandMonth3 Jump to: navigation, search This is aFlatDemandMonth7 Jump

  9. Property:OpenEI/UtilityRate/FlatDemandMonth8 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2FlatDemandMonth3 Jump to: navigation, search This is aFlatDemandMonth7

  10. Influence of Air Conditioner Operation on Electricity Use and Peak Demand 

    E-Print Network [OSTI]

    McGarity, A. E.; Feuermann, D.; Kempton, W.; Norford, L. K.

    1987-01-01

    Electricity demand due to occupant controlled room air conditioners in a large mater-metered apartment building is analyzed. Hourly data on the electric demand of the building and of individual air conditioners are used in analyses of annual...

  11. Dynamic Control of Electricity Cost with Power Demand Smoothing and Peak Shaving for Distributed Internet Data Centers

    E-Print Network [OSTI]

    Rahman, A.K.M. Ashikur

    Dynamic Control of Electricity Cost with Power Demand Smoothing and Peak Shaving for Distributed a major part of their running costs. Modern electric power grid provides a feasible way to dynamically and efficiently manage the electricity cost of distributed IDCs based on the Locational Marginal Pricing (LMP

  12. SmartCap: Flattening Peak Electricity Demand in Smart Homes Sean Barker, Aditya Mishra, David Irwin, Prashant Shenoy, and Jeannie Albrecht

    E-Print Network [OSTI]

    Massachusetts at Amherst, University of

    SmartCap: Flattening Peak Electricity Demand in Smart Homes Sean Barker, Aditya Mishra, David Irwin--Flattening household electricity demand reduces generation costs, since costs are disproportionately affected by peak demands. While the vast majority of household electrical loads are interactive and have little scheduling

  13. Testing of peak demand limiting using thermal mass at a small commercial building

    E-Print Network [OSTI]

    Lee, Kyoung-Ho; Braun, James E; Fredrickson, Steve; Konis, Kyle; Arens, Edward

    2007-01-01

    5 Air Conditioningresults showed a peak air conditioning power reduction ofuc/item/19p737k1 Air Conditioning Equipment The HVAC

  14. Factors Influencing Water Heating Energy Use and Peak Demand in a Large Scale Residential Monitoring Study 

    E-Print Network [OSTI]

    Bouchelle, M. P.; Parker, D. S.; Anello, M. T.

    2000-01-01

    , as well as obtain improved appliance energy consumption indexes and load profiles. A portion of the monitoring measures water heater energy use and demand in each home on a 15-minute basis....

  15. Potential For Energy, Peak Demand, and Water Savings in California Tomato Processing Facilities 

    E-Print Network [OSTI]

    Trueblood, A. J.; Wu, Y. Y.; Ganji, A. R.

    2013-01-01

    Tomato processing is a major component of California's food industry. Tomato processing is extremely energy intensive, with the processing season coinciding with the local electrical utility peak period. Significant savings are possible...

  16. The development of a charge protocol to take advantage of off- and on-peak demand economics at facilities

    SciTech Connect (OSTI)

    Jeffrey Wishart

    2012-02-01

    This document reports the work performed under Task 1.2.1.1: 'The development of a charge protocol to take advantage of off- and on-peak demand economics at facilities'. The work involved in this task included understanding the experimental results of the other tasks of SOW-5799 in order to take advantage of the economics of electricity pricing differences between on- and off-peak hours and the demonstrated charging and facility energy demand profiles. To undertake this task and to demonstrate the feasibility of plug-in hybrid electric vehicle (PHEV) and electric vehicle (EV) bi-directional electricity exchange potential, BEA has subcontracted Electric Transportation Applications (now known as ECOtality North America and hereafter ECOtality NA) to use the data from the demand and energy study to focus on reducing the electrical power demand of the charging facility. The use of delayed charging as well as vehicle-to-grid (V2G) and vehicle-to-building (V2B) operations were to be considered.

  17. Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike

    SciTech Connect (OSTI)

    DeForest, Nicholas; Mendes, Goncalo; Stadler, Michael; Feng, Wei; Lai, Judy; Marnay, Chris

    2013-06-02

    In much of the developed world, air-conditioning in buildings is the dominant driver of summer peak electricity demand. In the developing world a steadily increasing utilization of air-conditioning places additional strain on already-congested grids. This common thread represents a large and growing threat to the reliable delivery of electricity around the world, requiring capital-intensive expansion of capacity and draining available investment resources. Thermal energy storage (TES), in the form of ice or chilled water, may be one of the few technologies currently capable of mitigating this problem cost effectively and at scale. The installation of TES capacity allows a building to meet its on-peak air conditioning load without interruption using electricity purchased off-peak and operating with improved thermodynamic efficiency. In this way, TES has the potential to fundamentally alter consumption dynamics and reduce impacts of air conditioning. This investigation presents a simulation study of a large office building in four distinct geographical contexts: Miami, Lisbon, Shanghai, and Mumbai. The optimization tool DER-CAM (Distributed Energy Resources Customer Adoption Model) is applied to optimally size TES systems for each location. Summer load profiles are investigated to assess the effectiveness and consistency in reducing peak electricity demand. Additionally, annual energy requirements are used to determine system cost feasibility, payback periods and customer savings under local utility tariffs.

  18. Facility Scale Energy Storage for Peak Deman Management and Demand Response 

    E-Print Network [OSTI]

    Remillard, J.

    2015-01-01

    Technology Conference New Orleans, LA. June 2-4, 2015 1. Introduction 2. Definitions and key terminology 3. Facility scale value streams 4. Energy storage technologies 5. Technical and market barriers AGENDA ESL-IE-15-06-12a Proceedings of the Thrity...-Seventh Industrial Energy Technology Conference New Orleans, LA. June 2-4, 2015 ?To ensure power quality and level demand ? For integration of renewable generation Incentives ? NYSERDA and Con Edison ? $2,100/kW for batteries ? PG&E ? $1,620/kW for advanced energy...

  19. Property:OpenEI/UtilityRate/FixedDemandChargeMonth9 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformationInformation FixedDemandChargeMonth9

  20. Property:OpenEI/UtilityRate/FlatDemandMonth1 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformationInformationFlatDemandMonth1 Jump to:

  1. Property:OpenEI/UtilityRate/FlatDemandMonth10 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformationInformationFlatDemandMonth1 Jump

  2. Property:OpenEI/UtilityRate/FlatDemandMonth11 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformationInformationFlatDemandMonth1 JumpThis

  3. Property:OpenEI/UtilityRate/FlatDemandMonth12 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformationInformationFlatDemandMonth1

  4. Property:OpenEI/UtilityRate/FlatDemandMonth3 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2FlatDemandMonth3 Jump to: navigation, search This is a property of type

  5. Property:OpenEI/UtilityRate/FlatDemandMonth4 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2FlatDemandMonth3 Jump to: navigation, search This is a property of

  6. Property:OpenEI/UtilityRate/FlatDemandMonth5 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2FlatDemandMonth3 Jump to: navigation, search This is a property

  7. Property:OpenEI/UtilityRate/FlatDemandMonth6 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2FlatDemandMonth3 Jump to: navigation, search This is a

  8. Property:OpenEI/UtilityRate/FlatDemandMonth9 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2FlatDemandMonth3 Jump to: navigation, search This is

  9. Peak-Coincident Demand Savings from Behavior-Based Programs: Evidence from PPL Electric's Behavior and Education Program

    E-Print Network [OSTI]

    Stewart, James

    2013-01-01

    hours caused by residential demand for air conditioning. Airto those of other residential demand-response programs?11 Most residential demand response programs fall into one

  10. Program Design Analysis using BEopt Building Energy Optimization Software: Defining a Technology Pathway Leading to New Homes with Zero Peak Cooling Demand; Preprint

    SciTech Connect (OSTI)

    Anderson, R.; Christensen, C.; Horowitz, S.

    2006-08-01

    An optimization method based on the evaluation of a broad range of different combinations of specific energy efficiency and renewable-energy options is used to determine the least-cost pathway to the development of new homes with zero peak cooling demand. The optimization approach conducts a sequential search of a large number of possible option combinations and uses the most cost-effective alternatives to generate a least-cost curve to achieve home-performance levels ranging from a Title 24-compliant home to a home that uses zero net source energy on an annual basis. By evaluating peak cooling load reductions on the least-cost curve, it is then possible to determine the most cost-effective combination of energy efficiency and renewable-energy options that both maximize annual energy savings and minimize peak-cooling demand.

  11. Green Scheduling of Control Systems for Peak Demand Reduction Truong X. Nghiem, Madhur Behl, Rahul Mangharam and George J. Pappas

    E-Print Network [OSTI]

    Pappas, George J.

    Mangharam and George J. Pappas Abstract-- Building systems such as heating, air quality control approach for fine-grained scheduling of control systems within an aggregate peak power envelop while this by combining: (a) minimization of the feasible peak power constraint of the systems; and (b) coordination

  12. A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

    SciTech Connect (OSTI)

    Hong, Tianzhen; Chang, Wen-Kuei; Lin, Hung-Wen

    2013-05-01

    Buildings consume more than one third of the world?s total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energy management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980 to 2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: 1) annual weather variation has a greater impact on the peak electricity demand than it does on energy use in buildings; 2) the simulated energy use using the TMY3 weather data is not necessarily representative of the average energy use over a long period, and the TMY3 results can be significantly higher or lower than those from the AMY data; 3) the weather impact is greater for buildings in colder climates than warmer climates; 4) the weather impact on the medium-sized office building was the greatest, followed by the large office and then the small office; and 5) simulated energy savings and peak demand reduction by energy conservation measures using the TMY3 weather data can be significantly underestimated or overestimated. It is crucial to run multi-decade simulations with AMY weather data to fully assess the impact of weather on the long-term performance of buildings, and to evaluate the energy savings potential of energy conservation measures for new and existing buildings from a life cycle perspective.

  13. A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

    E-Print Network [OSTI]

    Hong, Tianzhen

    2014-01-01

    energy performance and demand response. Accurate estimationto assess accurately demand response strategies. 3.6 Weatherincluding HVAC design, demand response for smart grids, and

  14. Renewable energies such as solar photovoltaics "PV" have been widely used to minimize the use of grid power. Nevertheless, solar PV is hampered by the lack of solar radiation during peak energy demand hours

    E-Print Network [OSTI]

    Renewable energies such as solar photovoltaics "PV" have been widely used to minimize the use of grid power. Nevertheless, solar PV is hampered by the lack of solar radiation during peak energy demand curve and make the energy accessible during peak hours can be accomplished through pairing solar PV

  15. monthly_peak_2003.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural Gas Reserves AdjustmentsDecade Year-0 Year-1 Year-21440ZO

  16. monthly_peak_2004.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural Gas Reserves AdjustmentsDecade Year-0 Year-1 Year-21440ZO

  17. monthly_peak_2005.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural Gas Reserves AdjustmentsDecade Year-0 Year-1 Year-21440ZO3a

  18. monthly_peak_2006.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural Gas Reserves AdjustmentsDecade Year-0 Year-1 Year-21440ZO3a6

  19. Statewide Electrical Energy Cost Savings and Peak Demand Reduction from the IECC Code-Compliant, Single-Family Residences in Texas (2002-2009) 

    E-Print Network [OSTI]

    Kim, H; Baltazar, J.C.; Haberl, J.

    2011-01-01

    -02-01 STATEWIDE ELECTRICITY AND DEMAND CAPACITY SAVINGS FROM THE INTERNATIONAL ENERGY CONSERVATION CODE (IECC) ADOPTION FOR SINGLE-FAMILY RESIDENCES IN TEXAS (2002-2009) Hyojin Kim Juan-Carlos Baltazar, Ph.D. Jeff Haberl, Ph.D., P... SUMMARY Statewide electricity and electric demand savings achieved from the adoption of the different International Energy Conservation Code (IECC) versions for single-family residences in Texas and the corresponding construction cost increases over...

  20. Using Hydrated Salt Phase Change Materials for Residential Air Conditioning Peak Demand Reduction and Energy Conservation in Coastal and Transitional Climates in the State of California

    E-Print Network [OSTI]

    Lee, Kyoung Ok

    2013-05-31

    The recent rapid economic and population growth in the State of California have led to a significant increase in air conditioning use, especially in areas of the State with coastal and transitional climates. This fact makes that the electric peak...

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

    E-Print Network [OSTI]

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

    2008-01-01

    demands. Residential and commercial demand has a significantDemand by Sector Residential Peak Demand (MW) Commercialwe convert residential electricity demand based upon climate

  2. Effects of the drought on California electricity supply and demand

    E-Print Network [OSTI]

    Benenson, P.

    2010-01-01

    DEMAND . . . .Demand for Electricity and Power PeakDemand . . • . . ELECTRICITY REQUIREMENTS FOR AGRICULTUREResults . . Coriclusions ELECTRICITY SUPPLY Hydroelectric

  3. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Linkugel, Eric

    2006-01-01

    efficiency, daily peak load management and demand response.Loads Efficiency, Daily Load Management and Demand ResponseOperations Peak Load Management (Daily) - TOU Savings - Peak

  4. Demand Response: Load Management Programs 

    E-Print Network [OSTI]

    Simon, J.

    2012-01-01

    Management Programs CATEE Conference October, 2012 Agenda Outline I. General Demand Response Definition II. General Demand Response Program Rules III. CenterPoint Commercial Program IV. CenterPoint Residential Programs V. Residential Discussion... Points Demand Response Definition of load management per energy efficiency rule 25.181: ? Load control activities that result in a reduction in peak demand, or a shifting of energy usage from a peak to an off-peak period or from high-price periods...

  5. Monthly Generation System Peak (pbl/generation)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune 25,July 2003 E n e r

  6. monthly_peak_1996_2004.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural Gas Reserves AdjustmentsDecade Year-0 Year-1 Year-21440Z

  7. monthly_peak_byarea_2010.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural Gas Reserves AdjustmentsDecade Year-0 Year-1

  8. monthly_peak_bymonth_2010.xls

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural Gas Reserves AdjustmentsDecade Year-0 Year-1A.1. January

  9. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    Energy Efficiency, Demand Response, and Peak Load Managementdemand response, and load management programs in the Ebefore they undertake load management and demand response

  10. Electricity Monthly Update

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

    Wholesale Markets: February 2014 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale...

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

    E-Print Network [OSTI]

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

    2008-01-01

    Figure 16 Annual peak electricity demand by sector. Tableincludes an hourly electricity demand (i.e. power) profileof aggregating sectoral electricity demands into a statewide

  12. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. XX, NO. XX, MONTH 20XX 1 Efficient On-Demand Data Service Delivery to

    E-Print Network [OSTI]

    Zhuang, Weihua

    , resource allocation. I. INTRODUCTION Recently, the high-speed rail has been rapidly developing all over comforts by high-speed Internet services [3]. The cellular network deployed near the rail lines can provide-Demand Data Service Delivery to High-Speed Trains in Cellular/Infostation Integrated Networks Hao Liang

  13. Residential Customer Response to Real-time Pricing: The Anaheim Critical Peak Pricing Experiment

    E-Print Network [OSTI]

    Wolak, Frank A.

    2007-01-01

    load in California. Residential demand is approximately 30%12% reduction in statewide residential demand on a statewidefor residential customers with an aggregate peak demand that

  14. Electrical Demand Management 

    E-Print Network [OSTI]

    Fetters, J. L.; Teets, S. J.

    1983-01-01

    The Demand Management Plan set forth in this paper has proven to be a viable action to reduce a 3 million per year electric bill at the Columbus Works location of Western Electric. Measures are outlined which have reduced the peak demand 5% below...

  15. Estimating Demand Response Market Potential Among Large Commercial and Industrial Customers: A Scoping Study

    E-Print Network [OSTI]

    Goldman, Charles; Hopper, Nicole; Bharvirkar, Ranjit; Neenan, Bernie; Cappers, Peter

    2007-01-01

    3–6 percent of non-residential peak demand, can be viewed as3–6 percent of non-residential peak demand, can be viewed asto large, non-residential customers with peak demand greater

  16. Demand Reduction

    Office of Energy Efficiency and Renewable Energy (EERE)

    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...

  17. Preliminary Assumptions for Natural Gas Peaking

    E-Print Network [OSTI]

    plants and capital cost estimates for peaking technologies Frame, Aeroderivative, Intercooled, Reciprocating Engines Next steps 2 #12;Definitions Baseload Energy: power generated (or conserved) across a period of time to serve system demands for electricity Peaking Capacity: capability of power generating

  18. Assessment of Demand Response and Advanced Metering

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    #12;#12;2008 Assessment of Demand Response and Advanced Metering Staff Report Federal Energy metering penetration and potential peak load reduction from demand response have increased since 2006. Significant activity to promote demand response or to remove barriers to demand response occurred at the state

  19. Energy Demands and Efficiency Strategies in Data Center Buildings

    E-Print Network [OSTI]

    Shehabi, Arman

    2010-01-01

    DX Cooling Total Annual Energy Usage Peak Electric DemandDX Cooling Total Annual Energy Usage Scenario Supply/ ReturnDX Cooling Total Annual Energy Usage Peak Electric Demand

  20. Optimal Sizing of Energy Storage and Photovoltaic Power Systems for Demand Charge Mitigation (Poster)

    SciTech Connect (OSTI)

    Neubauer, J.; Simpson, M.

    2013-10-01

    Commercial facility utility bills are often a strong function of demand charges -- a fee proportional to peak power demand rather than total energy consumed. In some instances, demand charges can constitute more than 50% of a commercial customer's monthly electricity cost. While installation of behind-the-meter solar power generation decreases energy costs, its variability makes it likely to leave the peak load -- and thereby demand charges -- unaffected. This then makes demand charges an even larger fraction of remaining electricity costs. Adding controllable behind-the-meter energy storage can more predictably affect building peak demand, thus reducing electricity costs. Due to the high cost of energy storage technology, the size and operation of an energy storage system providing demand charge management (DCM) service must be optimized to yield a positive return on investment (ROI). The peak demand reduction achievable with an energy storage system depends heavily on a facility's load profile, so the optimal configuration will be specific to both the customer and the amount of installed solar power capacity. We explore the sensitivity of DCM value to the power and energy levels of installed solar power and energy storage systems. An optimal peak load reduction control algorithm for energy storage systems will be introduced and applied to historic solar power data and meter load data from multiple facilities for a broad range of energy storage system configurations. For each scenario, the peak load reduction and electricity cost savings will be computed. From this, we will identify a favorable energy storage system configuration that maximizes ROI.

  1. Dynamic Controls for Energy Efficiency and Demand Response: Framework Concepts and a New Construction Study Case in New York

    E-Print Network [OSTI]

    Kiliccote, Sila; Piette, Mary Ann; Watson, David S.; Hughes, Glenn

    2006-01-01

    energy efficiency, peak load management and demand response.minimization); peak load management (for daily operations);Energy Efficiency, Daily Load Management and DR Demand-Side

  2. Summary of the 2006 Automated Demand Response Pilot 

    E-Print Network [OSTI]

    Piette, M.; Kiliccote, S.

    2007-01-01

    This paper discusses the specific concept for, design of, and results from a pilot program to automate demand response with critical peak pricing. California utilities have been exploring the use of critical peak pricing (CPP) to help reduce peak...

  3. Price Responsive Demand in New York Wholesale Electricity Market using OpenADR

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2013-01-01

    months when buildings' electricity demand is also high dueoptimize buildings' electricity demand according to hourlymonths when buildings' electricity demand is also high due

  4. Risk Management for Video-on-Demand Servers leveraging Demand Forecast

    E-Print Network [OSTI]

    Li, Baochun

    Risk Management for Video-on-Demand Servers leveraging Demand Forecast Di Niu, Hong Xu, Baochun Li}@eecg.toronto.edu Shuqiao Zhao Multimedia Development Group UUSee, Inc. shuqiao.zhao@gmail.com ABSTRACT Video-on-demand (VoD) servers are usually over-provisioned for peak demands, incurring a low average resource effi- ciency

  5. APPLICATION-FORM DEMANDED'ADMISSION

    E-Print Network [OSTI]

    Opportunities and Challenges for Data Center Demand Response Adam Wierman Zhenhua Liu Iris Liu of renewable energy into the grid as well as electric power peak-load shaving: data center demand response. Data center demand response sits at the intersection of two growing fields: energy efficient data

  6. THE STATE OF DEMAND RESPONSE IN CALIFORNIA

    E-Print Network [OSTI]

    THE STATE OF DEMAND RESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demand response (DR) can.S. and internationally and lay out ideas that could help move California forward. KEY WORDS demand response, peak

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

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

    Photo of homes in Premier Gardens. As the housing market continues to evolve toward zero net-energy ready homes, Building America research has provided essential guidance for...

  8. Microgrid Dispatch for Macrogrid Peak-Demand Mitigation

    E-Print Network [OSTI]

    DeForest, Nicholas

    2013-01-01

    Building Energy System Selection and Operation,” Microgen’II: Second International Confer-ence of Microgeneration and

  9. Scenario Analysis of Peak Demand Savings for Commercial Buildings with

    E-Print Network [OSTI]

    side, a set of electricity rates are used to evaluate the impact of the DR strategies on economic response (DR) is a process of managing customer consumption of electricity in response to supply conditions to reduce electricity costs or improve electrical system reliability. Generally, DR refers to mechanisms

  10. Microgrid Dispatch for Macrogrid Peak-Demand Mitigation

    E-Print Network [OSTI]

    DeForest, Nicholas

    2013-01-01

    electricity. The benefits of microgrids are however a two-customer-operated microgrids can potentially reduce theIf the utility expects microgrids like SRJ to engage in this

  11. Microgrid Dispatch for Macrogrid Peak-Demand Mitigation

    E-Print Network [OSTI]

    DeForest, Nicholas

    2013-01-01

    The installed battery has an energy capacity of 4 MWh and aof 6.5%. It is the energy capacity of the electric storage (and Lost Savings by Energy Capacity The technical parameters

  12. Microgrid Dispatch for Macrogrid Peak-Demand Mitigation

    E-Print Network [OSTI]

    DeForest, Nicholas

    2013-01-01

    generation fuel cell with heat recovery (2006) - 1 MW electricityfuel cell (c) is meant to provide 1 MW of base-load electricity generation,

  13. Microgrid Dispatch for Macrogrid Peak-Demand Mitigation

    E-Print Network [OSTI]

    DeForest, Nicholas

    2013-01-01

    Effect of Heat and Electricity Storage and Reliability onTable 2 August Electricity Bill by Storage Schedule ChargeSRJ electricity purchases (a) for the original no-storage

  14. Reducing Peak Demand to Defer Power Plant Construction in Oklahoma

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious RankADVANCED MANUFACTURINGEnergy BillsNo. 195 - Oct. 7,DOERTI |Service ofConditioning Filter | Department

  15. What China Can Learn from International Experiences in Developing a Demand Response Program

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    of preferred resources, placing energy efficiency and demandPromoting Energy Efficiency as a Cost-Effective Resource infor energy efficiency and demand response resources. Peak

  16. February most likely month for flu season to peak

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformation Current HABFES OctoberEvan Racah861May 2011April David28 February 28our

  17. Off Peak Power - An Alternative to Interruptible Service 

    E-Print Network [OSTI]

    Nordyke, H. G., Jr.

    1984-01-01

    Georgia Power's Off-Peak Rider encourages load reductions up to 40% during on-peak periods over four summer months each year. Since summer on-peak time represents about 50% of available time, the customer's productive summer capacity may be reduced...

  18. Potential Peak Load Reductions From Residential Energy Efficient Upgrades 

    E-Print Network [OSTI]

    Meisegeier, D.; Howes, M.; King, D.; Hall, J.

    2002-01-01

    the potential peak load reductions from residential energy efficiency upgrades in hot and humid climates. First, a baseline scenario is established. Then, the demand and consumption impacts of individual upgrade measures are assessed. Several of these upgrades...

  19. An Innovative Approach Towards National Peak Load Management 

    E-Print Network [OSTI]

    Al-Mulla, A.; Maheshwari, G. P.; Al-Nakib, D.; ElSherbini, A.; Alghimlas, F.; Al-Taqi, H.; Al-Hadban, Y.

    2008-01-01

    An innovative approach was developed and implemented in eight governmental buildings to reduce their load during the peak demand hours in summer of 2007. The innovative approach implemented in these buildings included pre-closing treatment (PCT...

  20. LNG production for peak shaving operations

    SciTech Connect (OSTI)

    Price, B.C.

    1999-07-01

    LNG production facilities are being developed as an alternative or in addition to underground storage throughout the US to provide gas supply during peak gas demand periods. These facilities typically involved a small liquefaction unit with a large LNG storage tank and gas sendout facilities capable of responding to peak loads during the winter. Black and Veatch is active in the development of LNG peak shaving projects for clients using a patented mixed refrigerant technology for efficient production of LNG at a low installed cost. The mixed refrigerant technology has been applied in a range of project sizes both with gas turbine and electric motor driven compression systems. This paper will cover peak shaving concepts as well as specific designs and projects which have been completed to meet this market need.

  1. InDemandInDemandInDemand Energize Your Career

    E-Print Network [OSTI]

    Wolberg, George

    InDemandInDemandInDemand Energize Your Career You can join the next generation of workers who in Energy #12;#12;In Demand | 1 No, this isn't a quiz...but if you answered yes to any or all and Training Administration wants you to have this publication, In Demand: Careers in Energy. It will let you

  2. 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.

  3. VideoonDemandVideoonDemandVideoonDemand Video on Demand Testbed

    E-Print Network [OSTI]

    Eleftheriadis, Alexandros

    VideoonDemandVideoonDemandVideoonDemand Columbia's Video on Demand Testbed and Interoperability Experiment Columbia's Video on Demand Testbed and Interoperability Experiment S.-F. Chang and A Columbia UniversityColumbia University www.www.ctrctr..columbiacolumbia..eduedu/advent/advent #12;VideoonDemandVideoonDemandVideoonDemand

  4. VideoonDemandVideoonDemandVideoonDemand Video on Demand Testbed

    E-Print Network [OSTI]

    Eleftheriadis, Alexandros

    #12;VideoonDemandVideoonDemandVideoonDemand Columbia's Video on Demand Testbed and Interoperability Experiment Columbia's Video on Demand Testbed and Interoperability Experiment H.H. KalvaKalva, A.www.eeee..columbiacolumbia..eduedu/advent/advent #12;VideoonDemandVideoonDemandVideoonDemand VoD Testbed ArchitectureVoD Testbed Architecture Video

  5. 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)

  6. Semantic Information Integration and Processing for Demand Response Optimization Qunzhi Zhou, Sreedhar Natarajan, Yogesh Simmhan and Viktor Prasanna

    E-Print Network [OSTI]

    Hwang, Kai

    Semantic Information Integration and Processing for Demand Response Optimization Qunzhi Zhou Demand response optimization (DR) deals with curtailing power consumption when peak demand on the power for Dynamic Demand Response Optimization Existing DR programs are typically based on static planning

  7. Demand Response and Open Automated Demand Response

    E-Print Network [OSTI]

    LBNL-3047E Demand Response and Open Automated Demand Response Opportunities for Data Centers G described in this report was coordinated by the Demand Response Research Center and funded by the California. Demand Response and Open Automated Demand Response Opportunities for Data Centers. California Energy

  8. Automated Critical Peak Pricing Field Tests: 2006 Pilot Program Description and Results

    E-Print Network [OSTI]

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

    2007-01-01

    13.   Linking energy efficiency, load management, and Operations Peak Load Management (Daily) - TOU Savings - Peakof  energy  efficiency,  load  management,  and  demand 

  9. Smart (In-home) Power Scheduling for Demand Response on the Smart Grid

    E-Print Network [OSTI]

    Yener, Aylin

    1 Smart (In-home) Power Scheduling for Demand Response on the Smart Grid Gang Xiong, Chen Chen consumption are part of demand response, which relies on varying price of electricity to reduce peak demand

  10. Automated Demand Response: The Missing Link in the Electricity Value Chain

    E-Print Network [OSTI]

    McKane, Aimee

    2010-01-01

    promise in reducing the electricity demand of the industrialchanges the time of electricity demand to off-peak hours.Load shedding curtails electricity demand during a DR event.

  11. High Temperatures & Electricity Demand

    E-Print Network [OSTI]

    High Temperatures & Electricity Demand An Assessment of Supply Adequacy in California Trends.......................................................................................................1 HIGH TEMPERATURES AND ELECTRICITY DEMAND.....................................................................................................................7 SECTION I: HIGH TEMPERATURES AND ELECTRICITY DEMAND ..........................9 BACKGROUND

  12. Desert Peak EGS Project

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based| Department8, 20153Danielthrough theKDesert Peak EGS Project DOE Award:

  13. 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.

  14. Saving Power at Peak Hours (LBNL Science at the Theater)

    ScienceCinema (OSTI)

    Piette, Mary Ann

    2011-04-28

    California needs new, responsive, demand-side energy technologies to ensure that periods of tight electricity supply on the grid don't turn into power outages. Led by Berkeley Lab's Mary Ann Piette, the California Energy Commission (through its Public Interest Energy Research Program) has established a Demand Response Research Center that addresses two motivations for adopting demand responsiveness: reducing average electricity prices and preventing future electricity crises. The research seeks to understand factors that influence "what works" in Demand Response. Piette's team is investigating the two types of demand response, load response and price response, that may influence and reduce the use of peak electric power through automated controls, peak pricing, advanced communications, and other strategies.

  15. Advanced Demand Responsive Lighting

    E-Print Network [OSTI]

    Advanced Demand Responsive Lighting Host: Francis Rubinstein Demand Response Research Center demand responsive lighting systems ­ Importance of dimming ­ New wireless controls technologies · Advanced Demand Responsive Lighting (commenced March 2007) #12;Objectives · Provide up-to-date information

  16. Monthly Reports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9Report 2015

  17. Monthly Reports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9Report 2015

  18. Monthly Reports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9Report 2015

  19. Monthly Reports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9Report 2015

  20. Monthly Reports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9Report

  1. Peak Power Reduction Strategies for the Lighting Systems in Government Buildings 

    E-Print Network [OSTI]

    Al-Nakib, D.; Al-Mulla, A. A.; Maheshwari, G. P.

    2010-01-01

    Lighting systems are the second major contributor to the peak power demand and energy consumption in buildings after A/C systems. They account for nearly 20% of the peak power demand and 15% of the annual energy consumption. Thus energy efficient...

  2. Opportunities and Challenges for Data Center Demand Response

    E-Print Network [OSTI]

    Low, Steven H.

    Opportunities and Challenges for Data Center Demand Response Adam Wierman Zhenhua Liu Iris Liu of renewable energy into the grid as well as electric power peak-load shaving: data center demand response. Data center demand response sits at the intersection of two growing fields: energy efficient data

  3. Optimal Demand Response Based on Utility Maximization in Power Networks

    E-Print Network [OSTI]

    Low, Steven H.

    -- Demand side management will be a key component of future smart grid that can help reduce peak load interesting properties of the proposed scheme. I. INTRODUCTION Demand side management will be a key componentOptimal Demand Response Based on Utility Maximization in Power Networks Na Li, Lijun Chen

  4. 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.

  5. Electricity Demand and Energy Consumption Management System

    E-Print Network [OSTI]

    Sarmiento, Juan Ojeda

    2008-01-01

    This project describes the electricity demand and energy consumption management system and its application to the Smelter Plant of Southern Peru. It is composted of an hourly demand-forecasting module and of a simulation component for a plant electrical system. The first module was done using dynamic neural networks, with backpropagation training algorithm; it is used to predict the electric power demanded every hour, with an error percentage below of 1%. This information allows management the peak demand before this happen, distributing the raise of electric load to other hours or improving those equipments that increase the demand. The simulation module is based in advanced estimation techniques, such as: parametric estimation, neural network modeling, statistic regression and previously developed models, which simulates the electric behavior of the smelter plant. These modules allow the proper planning because it allows knowing the behavior of the hourly demand and the consumption patterns of the plant, in...

  6. NOAA ARL Monthly Activity Report February 2001

    E-Print Network [OSTI]

    of handling both volcanic ash and radiological #12;2 Figure 1. Salt Lake City, UT ­ showing peak SF6 locations SURFRAD facility. The site should be on line in less than a month. Software for real-time processing

  7. Peak mass and dynamical friction

    E-Print Network [OSTI]

    A. Del Popolo; M. Gambera

    1995-06-09

    We show how the results given by several authors relatively to the mass of a density peak are changed when small scale substructure induced by dynamical friction are taken into account. The peak mass obtained is compared to the result of Peacock \\& Heavens (1990) and to the peak mass when dynamical friction is absent to show how these effects conspire to reduce the mass accreted by the peak.

  8. Retail Demand Response in Southwest Power Pool

    SciTech Connect (OSTI)

    Bharvirkar, Ranjit; Heffner, Grayson; Goldman, Charles

    2009-01-30

    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 practices. This report describes the results of a comprehensive survey conducted by LBNL in support of the Customer Response Task Force and discusses policy implications for integrating legacy retail DR programs and dynamic pricing tariffs into wholesale markets in the SPP region. LBNL conducted a detailed survey of existing DR programs and dynamic pricing tariffs administered by SPP's member utilities. Survey respondents were asked to provide information on advance notice requirements to customers, operational triggers used to call events (e.g. system emergencies, market conditions, local emergencies), use of these DR resources to meet planning reserves requirements, DR resource availability (e.g. seasonal, annual), participant incentive structures, and monitoring and verification (M&V) protocols. Nearly all of the 30 load-serving entities in SPP responded to the survey. Of this group, fourteen SPP member utilities administer 36 DR programs, five dynamic pricing tariffs, and six voluntary customer response initiatives. These existing DR programs and dynamic pricing tariffs have a peak demand reduction potential of 1,552 MW. Other major findings of this study are: o About 81percent of available DR is from interruptible rate tariffs offered to large commercial and industrial customers, while direct load control (DLC) programs account for ~;;14percent. o Arkansas accounts for ~;;50percent of the DR resources in the SPP footprint; these DR resources are primarily managed by cooperatives. o Publicly-owned cooperatives accounted for 54percent of the existing DR resources among SPP members. For these entities, investment in DR is often driven by the need to reduce summer peak demand that is used to set demand charges for each distribution cooperative. o About 65-70percent of the interruptible/curtailable tariffs and DLC programs are routinely triggered based on market conditions, not just for system emergencies. Approximately, 53percent of the DR resources are available with less than two hours advance notice and 447 MW can be dispatched with less than thirty minutes notice. o Most legacy DR programs offered a reservation payment ($/kW) for participation; incentive payment levels ranged from $0.40 to $8.30/kW-month for interruptible rate tariffs and $0.30 to $4.60/kW-month for DLC programs. A few interruptible programs offered incentive payments which were explicitly linkedto actual load reductions during events; payments ranged from 2 to 40 cents/kWh for load curtailed.

  9. 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.

  10. Pacific Northwest Demand Response Project Lee Hall, BPA Smart Grid Program Manager

    E-Print Network [OSTI]

    Pacific Northwest Demand Response Project Lee Hall, BPA Smart Grid Program Manager February 14 utilities to invest in DR Regional situational analysis ­ issues to address #12;Nationally ­ Demand ResponseSource: FERC Demand Response & Advanced Metering Report, February 2011 Peak DR 65,000 MW 1,062 MW Peak DR

  11. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    of integrating demand response and energy efficiencyand D. Kathan (2009), Demand Response in U.S. ElectricityFRAMEWORKS THAT PROMOTE DEMAND RESPONSE 3.1. Demand Response

  12. Urban Water Demand with Periodic Error Correction David R. Bell

    E-Print Network [OSTI]

    Griffin, Ronald

    them. Econometric estimates of residential demand for water abound (Dalhuisen et al. 2003Urban Water Demand with Periodic Error Correction by David R. Bell and Ronald C. Griffin February, Department of Agricultural Economics, Texas A&M University. #12;Abstract Monthly demand for publicly supplied

  13. Automated Critical Peak Pricing Field Tests: Program Descriptionand Results

    SciTech Connect (OSTI)

    Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Xu, Peng

    2006-04-06

    California utilities have been exploring the use of critical peak prices (CPP) to help reduce needle peaks in customer end-use loads. CPP is a form of price-responsive demand response (DR). Recent experience has shown that customers have limited knowledge of how to operate their facilities in order to reduce their electricity costs under CPP (Quantum 2004). While the lack of knowledge about how to develop and implement DR control strategies is a barrier to participation in DR programs like CPP, another barrier is the lack of automation of DR systems. During 2003 and 2004, the PIER Demand Response Research Center (DRRC) conducted a series of tests of fully automated electric demand response (Auto-DR) at 18 facilities. Overall, the average of the site-specific average coincident demand reductions was 8% from a variety of building types and facilities. Many electricity customers have suggested that automation will help them institutionalize their electric demand savings and improve their overall response and DR repeatability. This report focuses on and discusses the specific results of the Automated Critical Peak Pricing (Auto-CPP, a specific type of Auto-DR) tests that took place during 2005, which build on the automated demand response (Auto-DR) research conducted through PIER and the DRRC in 2003 and 2004. The long-term goal of this project is to understand the technical opportunities of automating demand response and to remove technical and market impediments to large-scale implementation of automated demand response (Auto-DR) in buildings and industry. A second goal of this research is to understand and identify best practices for DR strategies and opportunities. The specific objectives of the Automated Critical Peak Pricing test were as follows: (1) Demonstrate how an automated notification system for critical peak pricing can be used in large commercial facilities for demand response (DR). (2) Evaluate effectiveness of such a system. (3) Determine how customers will respond to this form of automation for CPP. (4) Evaluate what type of DR shifting and shedding strategies can be automated. (5) Explore how automation of control strategies can increase participation rates and DR saving levels with CPP. (6) Identify optimal demand response control strategies. (7) Determine occupant and tenant response.

  14. The Economics of Energy (and Electricity) Demand

    E-Print Network [OSTI]

    Platchkov, Laura M.; Pollitt, Michael G.

    25 3.3.2 Electrification of personal transport New sources of electricity demand may emerge which substantially change the total demand for electricity and the way electricity is consumed by the household. The Tesla Roadster12 stores 53 k... substantial battery storage capacity to the electricity grid, both when stationary at home and when at work. They may thus be very useful in providing short term back-up at system demand peaks or for dumping electricity to the batteries when supply is at a...

  15. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01

    benefits of Demand Side Management (DSM) are insufficient toefficiency, demand side management (DSM) cost effectivenessResearch Center Demand Side Management Demand Side Resources

  16. Peak Oil, Peak Energy Mother Nature Bats Last

    E-Print Network [OSTI]

    Sereno, Martin

    Peak Oil, Peak Energy Mother Nature Bats Last Martin Sereno 1 Feb 2011 (orig. talk: Nov 2004) #12;Oil is the Lifeblood of Industrial Civilization · 80 million barrels/day, 1000 barrels/sec, 1 cubicPods to the roads themselves) · we're not "addicted to oil" -- that's like saying a person has an "addiction

  17. Texas Nuclear Profile - Comanche Peak

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

    Comanche Peak" "Unit","Summer capacity (mw)","Net generation (thousand mwh)","Summer capacity factor (percent)","Type","Commercial operation date","License expiration date"...

  18. Providing Regulation Services and Managing Data Center Peak Power Budgets

    E-Print Network [OSTI]

    Simunic, Tajana

    -based peak shaving. However, none of these publications consider the feasibility of using the energy storage AND RELATED WORK Substantial integration of electric vehicles and renewable energy sources into the electric utility companies use to ensure stability. It includes multiple mechanisms, such as demand-response (DR

  19. 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

  20. Climate control : smart thermostats, demand response, and energy efficiency in Austin, Texas

    E-Print Network [OSTI]

    Bowen, Brian (Brian Richard)

    2015-01-01

    Energy efficiency and demand response are critical resources for the transition to a cleaner electricity grid. Demand-side management programs can reduce electricity use during peak times when power is scarce and expensive, ...

  1. Modeling, Analysis, and Control of Demand Response Resources

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2013-01-01

    that pre-cool, rebound, or otherwise shift energy use to theexhibit almost no rebound and save some energy on DR days,min) Rebound (kW) Daily peak demand (%) Daily energy (%)

  2. Modeling, Analysis, and Control of Demand Response Resources

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01

    that pre-cool, rebound, or otherwise shift energy use to theexhibit almost no rebound and save some energy on DR days,min) Rebound (kW) Daily peak demand (%) Daily energy (%)

  3. Control and Optimization Meet the Smart Power Grid: Scheduling of Power Demands for Optimal Energy

    E-Print Network [OSTI]

    Koutsopoulos, Iordanis

    technologies to enforce sensible use of energy through effective demand load management. We envision a scenario of effective management of power supply and demand loads. Load management is primarily employed by the power by transferring non-emergency power demands at off-peak-load times. Demand load management does not significantly

  4. Peaking of world oil production: Impacts, mitigation, & risk management

    SciTech Connect (OSTI)

    Hirsch, R.L.; Bezdek, Roger; Wendling, Robert

    2005-02-01

    The peaking of world oil production presents the U.S. and the world with an unprecedented risk management problem. As peaking is approached, liquid fuel prices and price volatility will increase dramatically, and, without timely mitigation, the economic, social, and political costs will be unprecedented. Viable mitigation options exist on both the supply and demand sides, but to have substantial impact, they must be initiated more than a decade in advance of peaking.... The purpose of this analysis was to identify the critical issues surrounding the occurrence and mitigation of world oil production peaking. We simplified many of the complexities in an effort to provide a transparent analysis. Nevertheless, our study is neither simple nor brief. We recognize that when oil prices escalate dramatically, there will be demand and economic impacts that will alter our simplified assumptions. Consideration of those feedbacks will be a daunting task but one that should be undertaken. Our aim in this study is to-- • Summarize the difficulties of oil production forecasting; • Identify the fundamentals that show why world oil production peaking is such a unique challenge; • Show why mitigation will take a decade or more of intense effort; • Examine the potential economic effects of oil peaking; • Describe what might be accomplished under three example mitigation scenarios. • Stimulate serious discussion of the problem, suggest more definitive studies, and engender interest in timely action to mitigate its impacts.

  5. The Summer of 2006: A Milestone in the Ongoing Maturation of Demand Response

    E-Print Network [OSTI]

    Hopper, Nicole; Goldman, Charles; Bharvirkar, Ranjit; Engel, Dan

    2007-01-01

    presentation to Peak Load Management Alliance Fall Meeting,Midwest ISO 2006 Load Management Response Survey Summary,appeals, demand-side management, utility load conservation,

  6. The Effects of the Peak-Peak Correlation on the Peak Model of Hierarchical Clustering

    E-Print Network [OSTI]

    A. Manrique; A. Raig; J. M. Solanes; G. Gonzalez-Casado; P. Stein; E. Salvador-Sole

    1997-12-05

    In two previous papers a semi-analytical model was presented for the hierarchical clustering of halos via gravitational instability from peaks in a random Gaussian field of density fluctuations. This model is better founded than the extended Press-Schechter model, which is known to agree with numerical simulations and to make similar predictions. The specific merger rate, however, shows a significant departure at intermediate captured masses. The origin of this was suspected as being the rather crude approximation used for the density of nested peaks. Here, we seek to verify this suspicion by implementing a more accurate expression for the latter quantity which accounts for the correlation among peaks. We confirm that the inclusion of the peak-peak correlation improves the specific merger rate, while the good behavior of the remaining quantities is preserved.

  7. A DISTRIBUTED INTELLIGENT AUTOMATED DEMAND RESPONSE BUILDING MANAGEMENT SYSTEM

    SciTech Connect (OSTI)

    Auslander, David; Culler, David; Wright, Paul; Lu, Yan; Piette, Mary

    2013-12-30

    The goal of the 2.5 year Distributed Intelligent Automated Demand Response (DIADR) project was to reduce peak electricity load of Sutardja Dai Hall at UC Berkeley by 30% while maintaining a healthy, comfortable, and productive environment for the occupants. We sought to bring together both central and distributed control to provide “deep” demand response1 at the appliance level of the building as well as typical lighting and HVAC applications. This project brought together Siemens Corporate Research and Siemens Building Technology (the building has a Siemens Apogee Building Automation System (BAS)), Lawrence Berkeley National Laboratory (leveraging their Open Automated Demand Response (openADR), Auto-­Demand Response, and building modeling expertise), and UC Berkeley (related demand response research including distributed wireless control, and grid-­to-­building gateway development). Sutardja Dai Hall houses the Center for Information Technology Research in the Interest of Society (CITRIS), which fosters collaboration among industry and faculty and students of four UC campuses (Berkeley, Davis, Merced, and Santa Cruz). The 141,000 square foot building, occupied in 2009, includes typical office spaces and a nanofabrication laboratory. Heating is provided by a district heating system (steam from campus as a byproduct of the campus cogeneration plant); cooling is provided by one of two chillers: a more typical electric centrifugal compressor chiller designed for the cool months (Nov-­ March) and a steam absorption chiller for use in the warm months (April-­October). Lighting in the open office areas is provided by direct-­indirect luminaries with Building Management System-­based scheduling for open areas, and occupancy sensors for private office areas. For the purposes of this project, we focused on the office portion of the building. Annual energy consumption is approximately 8053 MWh; the office portion is estimated as 1924 MWh. The maximum peak load during the study period was 1175 kW. Several new tools facilitated this work, such as the Smart Energy Box, the distributed load controller or Energy Information Gateway, the web-­based DR controller (dubbed the Central Load-­Shed Coordinator or CLSC), and the Demand Response Capacity Assessment & Operation Assistance Tool (DRCAOT). In addition, an innovative data aggregator called sMAP (simple Measurement and Actuation Profile) allowed data from different sources collected in a compact form and facilitated detailed analysis of the building systems operation. A smart phone application (RAP or Rapid Audit Protocol) facilitated an inventory of the building’s plug loads. Carbon dioxide sensors located in conference rooms and classrooms allowed demand controlled ventilation. The extensive submetering and nimble access to this data provided great insight into the details of the building operation as well as quick diagnostics and analyses of tests. For example, students discovered a short-­cycling chiller, a stuck damper, and a leaking cooling coil in the first field tests. For our final field tests, we were able to see how each zone was affected by the DR strategies (e.g., the offices on the 7th floor grew very warm quickly) and fine-­tune the strategies accordingly.

  8. 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).

  9. DEMAND INTERPROCEDURAL PROGRAM ANALYSIS

    E-Print Network [OSTI]

    Reps, Thomas W.

    1 DEMAND INTERPROCEDURAL PROGRAM ANALYSIS USING LOGIC DATABASES Thomas W. Reps Computer Sciences@cs.wisc.edu ABSTRACT This paper describes how algorithms for demand versions of inerprocedural program­ analysis for all elements of the program. This paper concerns the solution of demand versions of interprocedural

  10. Capacity Demand Power (GW)

    E-Print Network [OSTI]

    California at Davis, University of

    Capacity Demand Power (GW) Hour of the Day The "Dip" Electricity Demand in Electricity Demand Every weekday, Japan's electricity use dips about 6 GW at 12 but it also shows that: · Behavior affects naHonal electricity use in unexpected ways

  11. Demand Response Assessment INTRODUCTION

    E-Print Network [OSTI]

    Demand Response Assessment INTRODUCTION This appendix provides more detail on some of the topics raised in Chapter 4, "Demand Response" of the body of the Plan. These topics include 1. The features, advantages and disadvantages of the main options for stimulating demand response (price mechanisms

  12. A Demand-Side Management Experience in Existing Building Commissioning 

    E-Print Network [OSTI]

    Franconi, E.; Selch, M.; Bradford, J.; Gruen, B.

    2003-01-01

    As part of a suite of demand-side management (DSM) program offerings, Xcel Energy provides a recommissioning program to its Colorado commercial customers. The program has a summer peak-demand savings goal of 7.8 MW to be achieved by 2005. Commenced...

  13. 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.

  14. Management of Power Demand through Operations of Building Systems 

    E-Print Network [OSTI]

    ElSherbini, A. I.; Maheshwari, G.; Al-Naqib, D.; Al-Mulla, A.

    2009-01-01

    In hot summers, the demand for electrical power is dominated by the requirements of the air-conditioning and lighting systems. Such systems account for more than 80% of the peak electrical demand in Kuwait. A study was conducted to explore...

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    DECC aggregator managed portfolio automated demand responseaggregator designs their own programs, and offers demand responseaggregator is responsible for designing and implementing their own demand response

  16. U.S. Energy Demand, Offshore Oil Production and

    E-Print Network [OSTI]

    Patzek, Tadeusz W.

    U.S. Energy Demand, Offshore Oil Production and BP's Macondo Well Spill Tad Patzek, Petroleum that run the U.S. Complexity, models, risks Gulf of Mexico's oil and gas production Conclusions ­ p.3/4 #12;Summary of Conclusions. . . The global rate of production of oil is peaking now, coal will peak in 2

  17. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

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

  18. Automated Demand Response and Commissioning

    E-Print Network [OSTI]

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

    2005-01-01

    Fully-Automated Demand Response Test in Large Facilities14in DR systems. Demand Response using HVAC in Commercialof Fully Automated Demand Response in Large Facilities”

  19. Demand Response Spinning Reserve Demonstration

    E-Print Network [OSTI]

    2007-01-01

    F) Enhanced ACP Date RAA ACP Demand Response – SpinningReserve Demonstration Demand Response – Spinning Reservesupply spinning reserve. Demand Response – Spinning Reserve

  20. Demand Response Programs for Oregon

    E-Print Network [OSTI]

    Demand Response Programs for Oregon Utilities Public Utility Commission May 2003 Public Utility ....................................................................................................................... 1 Types of Demand Response Programs............................................................................ 3 Demand Response Programs in Oregon

  1. Peak finding using biorthogonal wavelets

    SciTech Connect (OSTI)

    Tan, C.Y.

    2000-02-01

    The authors show in this paper how they can find the peaks in the input data if the underlying signal is a sum of Lorentzians. In order to project the data into a space of Lorentzian like functions, they show explicitly the construction of scaling functions which look like Lorentzians. From this construction, they can calculate the biorthogonal filter coefficients for both the analysis and synthesis functions. They then compare their biorthogonal wavelets to the FBI (Federal Bureau of Investigations) wavelets when used for peak finding in noisy data. They will show that in this instance, their filters perform much better than the FBI wavelets.

  2. Near Optimal Demand-Side Energy Management Under Real-time Demand-Response Pricing

    E-Print Network [OSTI]

    Boutaba, Raouf

    1999 when abnormal hot weather combined with electricity generation shortage resulted in unheard management and is a major con- tributor of electric grid faults. Although peak demand happens very infrastructure (Figure 1): technology upgrade of the electric grid system, all-digital management infrastructure

  3. Exponential Demand Simulation Tool

    E-Print Network [OSTI]

    Reed, Derek D.

    2015-05-15

    Operant behavioral economics investigates the relation between environmental constraint and reinforcer consumption. The standard approach to quantifying this relation is through the use of behavioral economic demand curves. ...

  4. 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...

  5. National Women's History Month

    Office of Energy Efficiency and Renewable Energy (EERE)

    NATIONAL WOMEN’S HISTORY MONTH is an annual declared month that highlights the contributions of women to events in history and contemporary society.

  6. ORSSAB monthly board meeting

    Broader source: Energy.gov [DOE]

    The ORSSAB monthly board meeting is open to the public. This month, participants will receive an update on the U-233 Project.

  7. ORSSAB Monthly Board Meeting

    Broader source: Energy.gov [DOE]

    The ORSSAB Monthly Board meeting is open to the public. This month, participants will be briefed on the East Tennessee Technology Park Zone 1 Soils Proposed Plan.

  8. How USDA Forecasts Production and Supply/Demand 

    E-Print Network [OSTI]

    Anderson, David P.; O'Brien, Daniel; Welch, Mark

    2009-06-01

    USDA publishes crop supply and demand estimates for each month. Producers, merchandisers, processors, traders and other market participants rely on this information when making their buying and selling decisions. This leaflet explains how USDA makes...

  9. Silver Peak Innovative Exploration Project

    Broader source: Energy.gov [DOE]

    DOE Geothermal Peer Review 2010 - Presentation. Project objectives: Reduce the high level of risk during the early stages of geothermal project development by conducting a multi-faceted and innovative exploration and drilling program at Silver Peak. Determine the combination of techniques that are most useful and cost-effective in identifying the geothermal resource through a detailed, post-project evaluation of the exploration and drilling program.

  10. 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.

  11. Power Strip Packing of Malleable Demands in Mohammad M. Karbasioun, Gennady Shaikhet, Evangelos Kranakis, Ioannis Lambadaris

    E-Print Network [OSTI]

    Kranakis, Evangelos

    of the main goals of Demand Side Management (DSM) in smart grid is to reduce the peak to average ratio (PAR1 Power Strip Packing of Malleable Demands in Smart Grid Mohammad M. Karbasioun, Gennady Shaikhet of electrical energy which has to be supplied during the time interval [0, 1]. We assume that each demand has

  12. Distributed Load Demand Scheduling in Smart Grid to Minimize Electricity Generation Cost

    E-Print Network [OSTI]

    Pedram, Massoud

    Distributed Load Demand Scheduling in Smart Grid to Minimize Electricity Generation Cost Siyu Yue of electricity consumers is an effective way to alleviate the peak power demand on the elec- tricity grid- ple users cooperate to perform load demand scheduling in order to minimize the electricity generation

  13. Demand Dispatch-Intelligent

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

    such as wind, solar, and electric vehicles as well as dispatchable loads and microgrids. Many of these resources will be "behind-the-meter" (i.e., demand resources) and...

  14. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01

    World crude oil and natural gas: a demand and supply model.analysis of the demand for oil in the Middle East. EnergyEstimates elasticity of demand for crude oil, not gasoline.

  15. Demand and Price Volatility: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01

    World crude oil and natural gas: a demand and supply model.analysis of the demand for oil in the Middle East. EnergyEstimates elasticity of demand for crude oil, not gasoline.

  16. Demand and Price Volatility: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01

    H. , and James M. Gri¢ n. 1983. Gasoline demand in the OECDof dynamic demand for gasoline. Journal of Econometrics 77(An empirical analysis of gasoline demand in Denmark using

  17. Demand and Price Volatility: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01

    shift in the short-run price elasticity of gasoline demand.A meta-analysis of the price elasticity of gasoline demand.2007. Consumer demand un- der price uncertainty: Empirical

  18. 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.

  19. ORSSAB monthly board meeting

    Broader source: Energy.gov [DOE]

    The ORSSAB monthly meeting is open to the public. This month the board will hear a presentation and discuss the FY 2016 Oak Ridge Office of Environmental Management's budget and prioritization.

  20. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01

    Sterner. 1991. Analysing gasoline demand elasticities: A2011. Measuring global gasoline and diesel price and incomeMutairi. 1995. Demand for gasoline in Kuwait: An empirical

  1. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01

    No. ER06-615-000 CAISO Demand Response Resource User Guide -8 2.1. Demand Response Provides a Range of Benefits to8 2.2. Demand Response Benefits can be Quantified in Several

  2. Optimal Demand Response Libin Jiang

    E-Print Network [OSTI]

    Optimal Demand Response Libin Jiang Steven Low Computing + Math Sciences Electrical Engineering Caltech Oct 2011 #12;Outline Caltech smart grid research Optimal demand response #12;Global trends 1

  3. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

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

  4. Three Case Studues of the Application of Energy Systems Optimization Best Prectices for Automatic Demand Response 

    E-Print Network [OSTI]

    Shi, Y.; Guiberteau, K.; Yagua, C.; Watt, J.

    2013-01-01

    of the Application of Energy Systems Optimization Best Practices for Automatic Demand Response Yifu Shi Kelly Guiberteau Carlos Yagua, P.E. James Watt, P.E. Energy Systems Laboratory, Texas A&M University College Station, Texas Austin Energy... of the demand response program is to reduce facilities peak energy demand to reduce the cost of electricity for both Austin Energy and their customer. Reducing the demand mitigates the need to construct additional generation, transmission, and distribution...

  5. Estimating a Demand System with Nonnegativity Constraints: Mexican Meat Demand

    E-Print Network [OSTI]

    Carlini, David

    Estimating a Demand System with Nonnegativity Constraints: Mexican Meat Demand Amos Golan* Jeffrey an almost ideal demand system for five types of meat using cross-sectional data from Mexico, where most households did not buy at least one type of meat during the survey week. The system of demands is shown

  6. Peer-Assisted On-Demand Streaming: Characterizing Demands and

    E-Print Network [OSTI]

    Li, Baochun

    Peer-Assisted On-Demand Streaming: Characterizing Demands and Optimizing Supplies Fangming Liu Abstract--Nowadays, there has been significant deployment of peer-assisted on-demand streaming services over the Internet. Two of the most unique and salient features in a peer-assisted on-demand streaming

  7. Peak CO2? China's Emissions Trajectories to 2050

    E-Print Network [OSTI]

    Zhou, Nan

    2012-01-01

    demand, bunker fuel (heavy oil) demand will continue to risea gasoline exporter, as demand for other oil products is notof oil equivalent, but increase annual electricity demand by

  8. The Effect of CO2 Pricing on Conventional and Non- Conventional Oil Supply and Demand

    E-Print Network [OSTI]

    Méjean, Aurélie; Hope, Chris

    demand modelling Meling (StatoilHydro) 1.6%/year No detailed demand modelling Total 1.4%/year No detailed demand modelling Exxon Mobil 1.4%/year Detailed demand modelling Energyfiles 1.8%/year Demand not modelled, exogenous rate Adapted from (UKERC... of unconventional oil and gas) “By 2015, growth in the production of easily accessible oil and gas will not match the projected rate of demand growth.” UKERC (2009b p33) ExxonMobil 2008 101 in 2030 (excl. non-conventional oil) No peak before 2030 UKERC...

  9. Energy Demand Staff Scientist

    E-Print Network [OSTI]

    Eisen, Michael

    #12;Sources: China National Bureau of Statistics; U.S. Energy Information Administration, Annual Energy Outlook. Overview:Overview: Energy Use in China and the U.S.Energy Use in China and the U.S. 5 0Energy Demand in China Lynn Price Staff Scientist February 2, 2010 #12;Founded in 1988 Focused

  10. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01

    fraction of residential and commercial demands, leading16 Residential electricity demand endspecific residential electricity demands into electricity

  11. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

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

  12. Electric Power Monthly

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

    Electric Power Monthly Data for June 2015 | Release Date: August 26, 2015 | Next Release: September 24, 2015 | full report | Re-release date: August 28, 2015 | Revision Previous...

  13. Electricity Monthly Update

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

    as collected via the Form EIA-923. Nuclear Outages: Reflects the average daily outage amount for the month as reported by the Nuclear Regulatory Commission's Power Reactor...

  14. Electricity Monthly Update

    Gasoline and Diesel Fuel Update (EIA)

    Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains...

  15. ORSSAB Monthly Board Meeting

    Broader source: Energy.gov [DOE]

    The ORSSAB monthly board meeting is open to the public. The board will receive an update on the Transuranic Waste Processing Center.

  16. ORSSAB monthly meeting

    Broader source: Energy.gov [DOE]

    This month's ORSSAB board meeting will focus on the ETTP Zone 1 soils proposed plan. The meeting is open to the public.

  17. Electricity Monthly Update

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

    See all Electricity Reports Electricity Monthly Update With Data for November 2014 | Release Date: Jan. 26, 2015 | Next Release Date: Feb. 24, 2015 Previous Issues Issue:...

  18. Responder Technology Alert Monthly

    E-Print Network [OSTI]

    PNNL-24014 Responder Technology Alert Monthly (Oct-Nov 2014) January 2015 JF Upton SL Stein #12;#12;PNNL-24014 Responder Technology Alert Monthly (Oct-Nov 2014) JF Upton SL Stein January 2015 Prepared for the Department of Homeland Security Science and Technology Directorate under Contract HSHQPM-14-X-00058. Pacific

  19. Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California

    E-Print Network [OSTI]

    Yin, Rongxin

    2010-01-01

    2007). “Impact of Electricity Rate Structure on Energy Costside, a set of electricity rates are used to evaluate theto understand the impact of electricity rate structures on

  20. Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California

    E-Print Network [OSTI]

    Yin, Rongxin

    2010-01-01

    and Passive Building Thermal Storage Utilization. ” JournalControl of Passive Thermal Storage. ” ASHRAE Transactions,due to the high thermal storage during the pre-cooling

  1. Peak Demand Reduction from Pre-Cooling with Zone Temperature Reset in an Office Building

    E-Print Network [OSTI]

    Xu, Peng

    2010-01-01

    Control of Building Thermal Storage. ASHRAE Transactions 96(Control of Building Thermal Storage. ASHRAE Transactions1992. Heat Storage in Building Thermal Mass: A Parametric

  2. Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California

    E-Print Network [OSTI]

    Yin, Rongxin

    2010-01-01

    of HVAC Simulations Between EnergyPlus and DOE-2.2 for DataTool (DRQAT), which uses EnergyPlus simulation prototypesprototypical building using an EnergyPlus simulation model (

  3. Peak Demand Reduction with Dual-Source Heat Pumps Using Municipal Water 

    E-Print Network [OSTI]

    Morehouse, J. H.; Khan, J. A.; Connor, L. N.; Pal, D.

    1992-01-01

    The objective of this project was to examine a dual-source (air and/or water-coupled) heat pump concept which would reduce or eliminate the need for supplemental electrical resistance heating (strip heaters). The project examined two system options...

  4. Impact of Reflective Roofing on Cooling Electrical Use and Peak Demand in a Florida Retail Mall 

    E-Print Network [OSTI]

    Parker, D. S.; Sonne, J. K.; Sherwin, J. R.

    2002-01-01

    in California's climate (Akbari et al., 1991, 1992, 1997). In Florida, field research by the Florida Solar Energy Center (FSEC) since 1993 has quantified the impact of reflective roof coatings on sub-metered air conditioning (AC) consumption in tests in a dozen...

  5. A Power Scheduling Game for Reducing the Peak Demand of Residential Users

    E-Print Network [OSTI]

    users select the cheapest time slots (minimizing their daily bill) while satisfying their energy. INTRODUCTION The electricity generation, distribution and consumption are in the throes of change due challenges that have emerged in electric systems. One of the most relevant challenges associated

  6. OG&E Uses Time-Based Rate Program to Reduce Peak Demand

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergyTher i nAand DOEDepartmentNew2008Group, Inc. Order(National4,

  7. How are flat demand charges based on the highest peak over the past 12

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsource History View NewGuam: Energyarea,Magazine Jump to:II

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum12,ExecutiveFinancing ProgramsDepartmentHigh-EfficiencyPatrickMaterials forRancho

  9. Peak Travel, Peak Car and the Future of Mobility: Evidence, Unresolved...

    Open Energy Info (EERE)

    Peak Travel, Peak Car and the Future of Mobility: Evidence, Unresolved Issues, Policy Implications, and a Research Agenda Jump to: navigation, search Tool Summary LAUNCH TOOL Name:...

  10. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    retail regulatory authority prohibit such activity. Demand response integration into US wholesale power marketsretail or wholesale level. 17 While demand response began participating at scale in wholesale power markets

  11. 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 p

  12. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9 Monthly6 Monthly

  13. Demand Relief and Weather Sensitivity in Large California Commercial Office Buildings 

    E-Print Network [OSTI]

    Kinney, S.; Piette, M. A.; Gu, L.; Haves, P.

    2001-01-01

    A great deal of research has examined the weather sensitivity of energy consumption in commercial buildings; however, the recent power crisis in California has given greater importance to peak demand. Several new loadshedding programs have been...

  14. Enhanced Operation Strategies for Air-Conditioning and Lighting Systems Toward Peak Power Reduction for an Office Building in Kuwait 

    E-Print Network [OSTI]

    Alghimlas, F.; Al-Mulla, A.; Maheshwari, G.P.; Al-Nakib, D.

    2012-01-01

    t i o n ( M W h / y ) * 1 0 6 P e a k P o w e r D e m a n d ( M W ) Years Peak power Yearly Electricity Consumption Typical?Power?Demand?Profile?for?Summer?Day 5 2 0 0 5 5 8 0 5 9 6 0 6 3 4 0 6 7 2 0... w er The focus to reduce the power demand during the peak hours Options?to?Reduce?Fossil?Fuel?Consumption? 1. Implement?energy?efficiency?and? conservation?measures?in?buildings?to? reduce?their?demand?for?electricity. 2. Generate...

  15. Decentralized Control of Aggregated Loads for Demand Response Di Guo, Wei Zhang, Gangfeng Yan, Zhiyun Lin, and Minyue Fu

    E-Print Network [OSTI]

    Zhang, Wei

    Decentralized Control of Aggregated Loads for Demand Response Di Guo, Wei Zhang, Gangfeng Yan of residential responsive loads for vari- ous demand response applications. We propose a general hybrid system and effectively reduce the peak power consumption. I. INTRODUCTION Demand response has the potential to shift

  16. Deep Demand Response: The Case Study of the CITRIS Building at the University of California-Berkeley

    E-Print Network [OSTI]

    California at Berkeley, University of

    Deep Demand Response: The Case Study of the CITRIS Building at the University of California quality. We have made progress towards achieving deep demand response of 30% reduction of peak loads modeling expertise), and UC Berkeley (related demand response research including distributed wireless

  17. ORSSAB monthly board meeting

    Broader source: Energy.gov [DOE]

    The ORSSAB monthly board meeting is open to the public. The board will hear a presentation and discuss the development of a comprehensive mercury strategy for the Oak Ridge Reservation.

  18. ORSSAB monthly board meeting

    Broader source: Energy.gov [DOE]

    The ORSSAB monthly board meeting is open to the public. The board will receive an update on the Community Reuse Organization of East Tennessee efforts at the East Tennessee Technology Park.

  19. Geographic Area Month

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

    Fuels by PAD District and State (Cents per Gallon Excluding Taxes) - Continued Geographic Area Month No. 1 Distillate No. 2 Distillate a No. 4 Fuel b Sales to End Users Sales for...

  20. Monthly Financial Results

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

    FCRPS Summary Statement of Revenues and Expenses Run DateRun Time: August 14,2015 05:35 Requesting BL: CORPORATE BUSINESS UNIT Through the Month Ended July 31, 2015 Data...

  1. 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.

  2. BLACK HISTORY MONTH

    Broader source: Energy.gov [DOE]

    Black History Month is an annual celebration of achievements by black Americans and a time for recognizing the central role of African Americans in U.S. history. The event grew out of “Negro History Week,” created by historian Carter G. Woodson and other prominent African Americans. Other countries around the world, including Canada and the United Kingdom, also devote a month to celebrating black history.

  3. Demand Responsive and Energy Efficient Control Technologies andStrategies in Commercial Buildings

    SciTech Connect (OSTI)

    Piette, Mary Ann; Kiliccote, Sila

    2006-09-01

    Commercial buildings account for a large portion of summer peak electric demand. Research results show that there is significant potential to reduce peak demand in commercial buildings through advanced control technologies and strategies. However, a better understanding of commercial buildings contribution to peak demand and the use of energy management and control systems is required to develop this demand response resource to its full potential. The main objectives of the study were: (1) To evaluate the size of contributions of peak demand commercial buildings in the U.S.; (2) To understand how commercial building control systems support energy efficiency and DR; and (3) To disseminate the results to the building owners, facility managers and building controls industry. In order to estimate the commercial buildings contribution to peak demand, two sources of data are used: (1) Commercial Building Energy Consumption Survey (CBECS) and (2) National Energy Modeling System (NEMS). These two sources indicate that commercial buildings noncoincidental peak demand is about 330GW. The project then focused on technologies and strategies that deliver energy efficiency and also target 5-10% of this peak. Based on a building operations perspective, a demand-side management framework with three main features: (1) daily energy efficiency, (2) daily peak load management and (3) dynamic, event-driven DR are outlined. A general description of DR, its benefits, and nationwide DR potential in commercial buildings are presented. Case studies involving these technologies and strategies are described. The findings of this project are shared with building owners, building controls industry, researchers and government entities through a webcast and their input is requested. Their input is presented in the appendix section of this report.

  4. Demand Dispatch-Intelligent

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would like submit theCovalent Bonding Low-Cost2DepartmentDelta Dental Claim Form PDF iconDemand

  5. Revelation on Demand Nicolas Anciaux

    E-Print Network [OSTI]

    Revelation on Demand Nicolas Anciaux 1 · Mehdi Benzine1,2 · Luc Bouganim1 · Philippe Pucheral1 "revelation on demand". Keywords: Confidentiality and privacy, Secure device, Data warehousing, Indexing model

  6. by popular demand: Addiction II

    E-Print Network [OSTI]

    Niv, Yael

    by popular demand: Addiction II PSY/NEU338:Animal learning and decision making: Psychological, size of other non-drug rewards, and cost (but ultimately the demand is inelastic, or at least

  7. Load Reduction, Demand Response and Energy Efficient Technologies and Strategies

    SciTech Connect (OSTI)

    Boyd, Paul A.; Parker, Graham B.; Hatley, Darrel D.

    2008-11-19

    The Department of Energy’s (DOE’s) Pacific Northwest National Laboratory (PNNL) was tasked by the DOE Office of Electricity (OE) to recommend load reduction and grid integration strategies, and identify additional demand response (energy efficiency/conservation opportunities) and strategies at the Forest City Housing (FCH) redevelopment at Pearl Harbor and the Marine Corps Base Hawaii (MCBH) at Kaneohe Bay. The goal was to provide FCH staff a path forward to manage their electricity load and thus reduce costs at these FCH family housing developments. The initial focus of the work was at the MCBH given the MCBH has a demand-ratchet tariff, relatively high demand (~18 MW) and a commensurate high blended electricity rate (26 cents/kWh). The peak demand for MCBH occurs in July-August. And, on average, family housing at MCBH contributes ~36% to the MCBH total energy consumption. Thus, a significant load reduction in family housing can have a considerable impact on the overall site load. Based on a site visit to the MCBH and meetings with MCBH installation, FCH, and Hawaiian Electric Company (HECO) staff, recommended actions (including a "smart grid" recommendation) that can be undertaken by FCH to manage and reduce peak-demand in family housing are made. Recommendations are also made to reduce overall energy consumption, and thus reduce demand in FCH family housing.

  8. 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.

  9. Chord on Demand Alberto Montresor

    E-Print Network [OSTI]

    Jelasity, Márk

    Chord on Demand Alberto Montresor University of Bologna, Italy montresor@cs.unibo.it M´ark Jelasity to solve a specific task on demand. We introduce T- CHORD, that can build a Chord network efficiently to solve a specific task on demand. Existing join protocols are not designed to handle the massive

  10. Supply Chain Supernetworks Random Demands

    E-Print Network [OSTI]

    Nagurney, Anna

    Supply Chain Supernetworks with Random Demands June Dong and Ding Zhang Department of Marketing of three tiers of decision-makers: the manufacturers, the distributors, and the retailers, with the demands equilibrium model with electronic commerce and with random demands for which modeling, qualitative analysis

  11. Chord on Demand Alberto Montresor

    E-Print Network [OSTI]

    Chord on Demand Alberto Montresor University of Bologna, Italy montresor@cs.unibo.it Mark Jelasity to solve a specific task on demand. We introduce T- CHORD, that can build a Chord network efficiently on demand. Existing join protocols are not designed to handle the massive concurrency involved in a jump

  12. ERCOT Demand Response Paul Wattles

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    ERCOT Demand Response Paul Wattles Senior Analyst, Market Design & Development, ERCOT Whitacre;Definitions of Demand Response · `The short-term adjustment of energy use by consumers in response to price to market or reliability conditions.' (NAESB) #12;Definitions of Demand Response · The common threads

  13. Assessment of Demand Response Resource

    E-Print Network [OSTI]

    Assessment of Demand Response Resource Potentials for PGE and Pacific Power Prepared for: Portland January 15, 2004 K:\\Projects\\2003-53 (PGE,PC) Assess Demand Response\\Report\\Revised Report_011504.doc #12;#12;quantec Assessment of Demand Response Resource Potentials for I-1 PGE and Pacific Power I. Introduction

  14. Smart Operations of Air-Conditioning and Lighting Systems in Government Buildings for Peak Power Reduction 

    E-Print Network [OSTI]

    Al-Hadban, Y.; Maheshwari, G. P.; Al-Nakib, D.; Al-Mulla, A.; Alasseri, R.

    2008-01-01

    During the summer 2007 smart operation strategies for air-conditioning (A/C) and lighting systems were developed and tested in a number of governmental buildings in Kuwait as one of the solutions to reduce the national peak demand for electrical...

  15. Demand Shifting With Thermal Mass in Large Commercial Buildings:Field Tests, Simulation and Audits

    SciTech Connect (OSTI)

    Xu, Peng; Haves, Philip; Piette, Mary Ann; Zagreus, Leah

    2005-09-01

    The principle of pre-cooling and demand limiting is to pre-cool buildings at night or in the morning during off-peak hours, storing cooling in the building thermal mass and thereby reducing cooling loads and reducing or shedding related electrical demand during the peak periods. Cost savings are achieved by reducing on-peak energy and demand charges. The potential for utilizing building thermal mass for load shifting and peak demand reduction has been demonstrated in a number of simulation, laboratory, and field studies (Braun 1990, Ruud et al. 1990, Conniff 1991, Andresen and Brandemuehl 1992, Mahajan et al. 1993, Morris et al. 1994, Keeney and Braun 1997, Becker and Paciuk 2002, Xu et al. 2003). This technology appears to have significant potential for demand reduction if applied within an overall demand response program. The primary goal associated with this research is to develop information and tools necessary to assess the viability of and, where appropriate, implement demand response programs involving building thermal mass in buildings throughout California. The project involves evaluating the technology readiness, overall demand reduction potential, and customer acceptance for different classes of buildings. This information can be used along with estimates of the impact of the strategies on energy use to design appropriate incentives for customers.

  16. Detailed Modeling and Response of Demand Response Enabled Appliances

    SciTech Connect (OSTI)

    Vyakaranam, Bharat; Fuller, Jason C.

    2014-04-14

    Proper modeling of end use loads is very important in order to predict their behavior, and how they interact with the power system, including voltage and temperature dependencies, power system and load control functions, and the complex interactions that occur between devices in such an interconnected system. This paper develops multi-state time variant residential appliance models with demand response enabled capabilities in the GridLAB-DTM simulation environment. These models represent not only the baseline instantaneous power demand and energy consumption, but the control systems developed by GE Appliances to enable response to demand response signals and the change in behavior of the appliance in response to the signal. These DR enabled appliances are simulated to estimate their capability to reduce peak demand and energy consumption.

  17. Installation and Commissioning Automated Demand Response Systems

    SciTech Connect (OSTI)

    Global Energy Partners; Pacific Gas and Electric Company; Kiliccote, Sila; Kiliccote, Sila; Piette, Mary Ann; Wikler, Greg; Prijyanonda, Joe; Chiu, Albert

    2008-04-21

    Demand Response (DR) can be defined as actions taken to reduce electric loads when contingencies, such as emergencies and congestion, occur that threaten supply-demand balance, or market conditions raise supply costs. California utilities have offered price and reliability DR based programs to customers to help reduce electric peak demand. The lack of knowledge about the DR programs and how to develop and implement DR control strategies is a barrier to participation in DR programs, as is the lack of automation of DR systems. Most DR activities are manual and require people to first receive notifications, and then act on the information to execute DR strategies. Levels of automation in DR can be defined as follows. Manual Demand Response involves a labor-intensive approach such as manually turning off or changing comfort set points at each equipment switch or controller. Semi-Automated Demand Response involves a pre-programmed demand response strategy initiated by a person via centralized control system. 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. The receipt of the external signal initiates pre-programmed demand response strategies. We refer to this as Auto-DR (Piette et. al. 2005). Auto-DR for commercial and industrial facilities can be defined as fully automated DR initiated by a signal from a utility or other appropriate entity and that provides fully-automated connectivity to customer end-use control strategies. One important concept in Auto-DR is that a homeowner or facility manager should be able to 'opt out' or 'override' a DR event if the event comes at time when the reduction in end-use services is not desirable. Therefore, Auto-DR is not handing over total control of the equipment or the facility to the utility but simply allowing the utility to pass on grid related information which then triggers facility defined and programmed strategies if convenient to the facility. From 2003 through 2006 Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) developed and tested a series of demand response automation communications technologies known as Automated Demand Response (Auto-DR). In 2007, LBNL worked with three investor-owned utilities to commercialize and implement Auto-DR programs in their territories. This paper summarizes the history of technology development for Auto-DR, and describes the DR technologies and control strategies utilized at many of the facilities. It outlines early experience in commercializing Auto-DR systems within PG&E DR programs, including the steps to configure the automation technology. The paper also describes the DR sheds derived using three different baseline methodologies. Emphasis is given to the lessons learned from installation and commissioning of Auto-DR systems, with a detailed description of the technical coordination roles and responsibilities, and costs.

  18. Modeling and Forecasting Electric Daily Peak Loads

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

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

  19. Demand-Aware Price Policy Synthesis and Verification Services for Smart Grids

    E-Print Network [OSTI]

    Tronci, Enrico

    at the same time (peak hour), this may result in an economical damage (both for usage of peak power plants forcing residential end users to cut their power demand. On the other hand, if all users require energy interconnection. The first service, which we call EDN Virtual Tomography (EVT) service, considers the whole EDN

  20. Automated Critical Peak Pricing Field Tests: Program Description and Results

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Xu, Peng

    2006-01-01

    Development for Demand Response Calculation - Findings andStrategies Linking Demand Response and Energy Efficiency.and Communications for Demand Response and Energy Efficiency

  1. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9 Monthly

  2. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9 Monthly6

  3. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9 Monthly62

  4. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9 Monthly621

  5. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9 Monthly6212

  6. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9 Monthly62124

  7. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9 Monthly621243

  8. Monthly Reports 2014

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9ReportMonthly

  9. Residential Sector Demand Module

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYearby the(Dollars1.840 2.318 3.1195) Model8)3 November

  10. The Boson peak in supercooled water

    E-Print Network [OSTI]

    Pradeep Kumar; K. Thor Wikfeldt; Daniel Schlesinger; Lars G. M. Pettersson; H. E. Stanley

    2013-05-19

    We perform extensive molecular dynamics simulations of the TIP4P/2005 model of water to investigate the origin of the Boson peak reported in experiments on supercooled water in nanoconfined pores, and in hydration water around proteins. We find that the onset of the Boson peak in supercooled bulk water coincides with the crossover to a predominantly low-density-like liquid below the Widom line $T_W$. The frequency and onset temperature of the Boson peak in our simulations of bulk water agree well with the results from experiments on nanoconfined water. Our results suggest that the Boson peak in water is not an exclusive effect of confinement. We further find that, similar to other glass-forming liquids, the vibrational modes corresponding to the Boson peak are spatially extended and are related to transverse phonons found in the parent crystal, here ice Ih.

  11. Northwest Open Automated Demand Response Technology Demonstration Project

    SciTech Connect (OSTI)

    Kiliccote, Sila; Dudley, Junqiao Han; Piette, Mary Ann

    2009-08-01

    Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) performed a technology demonstration and evaluation for Bonneville Power Administration (BPA) in Seattle City Light's (SCL) service territory. This report summarizes the process and results of deploying open automated demand response (OpenADR) in Seattle area with winter morning peaking commercial buildings. The field tests were designed to evaluate the feasibility of deploying fully automated demand response (DR) in four to six sites in the winter and the savings from various building systems. The project started in November of 2008 and lasted 6 months. The methodology for the study included site recruitment, control strategy development, automation system deployment and enhancements, and evaluation of sites participation in DR test events. LBNL subcontracted McKinstry and Akuacom for this project. McKinstry assisted with recruitment, site survey collection, strategy development and overall participant and control vendor management. Akuacom established a new server and enhanced its operations to allow for scheduling winter morning day-of and day-ahead events. Each site signed a Memorandum of Agreement with SCL. SCL offered each site $3,000 for agreeing to participate in the study and an additional $1,000 for each event they participated. Each facility and their control vendor worked with LBNL and McKinstry to select and implement control strategies for DR and developed their automation based on the existing Internet connectivity and building control system. Once the DR strategies were programmed, McKinstry commissioned them before actual test events. McKinstry worked with LBNL to identify control points that can be archived at each facility. For each site LBNL collected meter data and trend logs from the energy management and control system. The communication system allowed the sites to receive day-ahead as well as day-of DR test event signals. Measurement of DR was conducted using three different baseline models for estimation peak load reductions. One was three-in-ten baseline, which is based on the site electricity consumption from 7 am to 10 am for the three days with the highest consumption of the previous ten business days. The second model, the LBNL outside air temperature (OAT) regression baseline model, is based on OAT data and site electricity consumption from the previous ten days, adjusted using weather regressions from the fifteen-minute electric load data during each DR test event for each site. A third baseline that simply averages the available load data was used for sites less with less than 10 days of historical meter data. The evaluation also included surveying sites regarding any problems or issues that arose during the DR test events. Question covered occupant comfort, control issues and other potential problems.

  12. PROGRESS REPORTS (every 6 months)

    E-Print Network [OSTI]

    Hickman, Mark

    ENROL REGISTER PROGRESS REPORTS (every 6 months) SUBMIT ORAL EXAMINATION Suspension of study Change of supervisor Study away from Christchurch Extension to submission date PROGRESS REPORTS (every 6 months) PROGRESS REPORTS (every 6 months) PROGRESS REPORTS (every 6 months)PROGRESS REPORTS (every 6 months

  13. Monthly energy review

    SciTech Connect (OSTI)

    1997-12-01

    This document presents an overview of the Energy Information Administration`s (EIA) recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors.

  14. November 2010 monthly report

    SciTech Connect (OSTI)

    Neff, Warren E [Los Alamos National Laboratory

    2010-12-07

    These viewgraphs are to be provided to NNSA to update the status of the B61 Life Extension Project work and activities. The viewgraphs cover such issues as budget, schedule, scope, and the like. They are part of the monthly reporting process.

  15. Monthly Energy Review

    SciTech Connect (OSTI)

    1996-05-28

    This publication presents an overview of the Energy information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. Two brief ``energy plugs`` (reviews of EIA publications) are included, as well.

  16. 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.

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

    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...

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

    E-Print Network [OSTI]

    Aden, Nathaniel

    2010-01-01

    raising transportation oil demand. Growing internationalcoal by wire could reduce oil demand by stemming coal roadEastern oil production. The rapid growth of coal demand

  19. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    of Energy demand-side management energy information systemdemand response. Demand-side management (DSM) program goalsa goal for demand-side management (DSM) coordination and

  20. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01

    3 2.1 Demand-Side Managementbuildings. The demand side management framework is discussedIssues 2.1 Demand-Side Management Framework Forecasting

  1. Home Network Technologies and Automating Demand Response

    E-Print Network [OSTI]

    McParland, Charles

    2010-01-01

    LBNL Commercial and Residential Demand Response Overview ofmarket [5]. Residential demand reduction programs have beenin the domain of residential demand response. There are a

  2. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

    Kiliccote, Sila; Global Energy Partners; Pacific Gas and Electric Company

    2008-01-01

    their partnership in demand response automation research andand Techniques for Demand Response. LBNL Report 59975. Mayof Fully Automated Demand Response in Large Facilities.

  3. Coupling Renewable Energy Supply with Deferrable Demand

    E-Print Network [OSTI]

    Papavasiliou, Anthony

    2011-01-01

    8.4 Demand Response Integration . . . . . . . . . . .for each day type for the demand response study - moderatefor each day type for the demand response study - deep

  4. Strategies for Demand Response in Commercial Buildings

    E-Print Network [OSTI]

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

    2006-01-01

    Fully Automated Demand Response Tests in Large Facilities”of Fully Automated Demand Response in Large Facilities”,was coordinated by the Demand Response Research Center and

  5. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01

    2 2.0 Demand ResponseFully Automated Demand Response Tests in Large Facilities,was coordinated by the Demand Response Research Center and

  6. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    and D. Kathan (2009). Demand Response in U.S. ElectricityEnergy Financial Group. Demand Response Research Center [2008). Assessment of Demand Response and Advanced Metering.

  7. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01

    Like HECO actual utility demand response implementations canindustry-wide utility demand response applications tend toobjective. Figure 4. Demand Response Objectives 17  

  8. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01

    23 ii Retail Demand Response in SPP List of Figures and10 Figure 3. Demand Response Resources by11 Figure 4. Existing Demand Response Resources by Type of

  9. Demand Response - Policy | Department of Energy

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

    Coordination of Energy Efficiency and Demand Response Demand Response in U.S. Electricity Markets: Empirical Evidence 2009 Retail Demand Response in Southwest Power Pool (January...

  10. Demand Response as a System Reliability Resource

    E-Print Network [OSTI]

    Joseph, Eto

    2014-01-01

    Barat, and D. Watson. 2007. Demand Response Spinning ReserveKueck, and B. Kirby. 2009. Demand Response Spinning Reserveand B. Kirby. 2012. The Demand Response Spinning Reserve

  11. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01

    duty fuel demand in alternate scenarios. ..for light-duty fuel demand in alternate scenarios. Minimum52 Heavy-duty vehicle fuel demand for each alternate

  12. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01

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

  13. Peak CO2? China's Emissions Trajectories to 2050

    E-Print Network [OSTI]

    Zhou, Nan

    2012-01-01

    technology and demand side management. This study uses twoGeneration Growth Demand Side Management EV mandates or

  14. US electric utility demand-side management, 1994

    SciTech Connect (OSTI)

    NONE

    1995-12-26

    The report presents comprehensive information on electric power industry demand-side management (DSM) activities in US at the national, regional, and utility levels. Objective is provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it relates to the US electric power industry. The first chapter, ``Profile: US Electric Utility Demand-Side Management,`` presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions, and costs attributable to DSM.

  15. Adaptive architectures for peak power management

    E-Print Network [OSTI]

    Kontorinis, Vasileios

    2013-01-01

    center (capital expenses, or capex) and monthly recurringexpenses (opex) [HB09]. Capex costs are proportional to thethe data center to reduce both capex and opex costs. Power

  16. 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...

  17. A New Market for an Old Food: the U.S. Demand for Olive Oil , Daniel Sumner

    E-Print Network [OSTI]

    Schladow, S. Geoffrey

    A New Market for an Old Food: the U.S. Demand for Olive Oil Bo Xiong , Daniel Sumner , William olive oil continues to be imported. Estimation of a demand system using monthly import data reveals that the income elasticity for virgin oils sourced from EU is above one, but demand for non-virgin oils is income

  18. Petroleum marketing monthly

    SciTech Connect (OSTI)

    NONE

    1996-07-01

    Petroleum Marketing Monthly (PPM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o. b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

  19. Petroleum marketing monthly

    SciTech Connect (OSTI)

    NONE

    1996-02-01

    The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

  20. Electric power monthly

    SciTech Connect (OSTI)

    Smith, Sandra R.; Johnson, Melvin; McClevey, Kenneth; Calopedis, Stephen; Bolden, Deborah

    1992-05-01

    The Electric Power Monthly is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the national, Census division, and State levels for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, cost of fuel, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fuel are also displayed for the North American Electric Reliability Council (NERC) regions. Additionally, statistics by company and plant are published in the EPM on capability of new plants, new generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fuel.

  1. Electric power monthly

    SciTech Connect (OSTI)

    1995-08-01

    The Energy Information Administration (EIA) prepares the Electric Power Monthly (EPM) for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. This publication provides monthly statistics for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source, consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead.

  2. A perspective on the CMB acoustic peak

    E-Print Network [OSTI]

    T. A. Marriage

    2002-03-11

    CMB angular spectrum measurements suggest a flat universe. This paper clarifies the relation between geometry and the spherical harmonic index of the first acoustic peak ($\\ell_{peak}$). Numerical and analytic calculations show that $\\ell_{peak}$ is approximately a function of $\\Omega_K/\\Omega_M$ where $\\Omega_K$ and $\\Omega_M$ are the curvature ($\\Omega_K > 0$ implies an open geometry) and mass density today in units of critical density. Assuming $\\Omega_K/\\Omega_M \\ll 1$, one obtains a simple formula for $\\ell_{peak}$, the derivation of which gives another perspective on the widely-recognized $\\Omega_M$-$\\Omega_\\Lambda$ degeneracy in flat models. This formula for near-flat cosmogonies together with current angular spectrum data yields familiar parameter constraints.

  3. QER- Comment of Cloud Peak Energy Inc

    Office of Energy Efficiency and Renewable Energy (EERE)

    Dear Ms Pickett Please find attached comments from Cloud Peak Energy as input to the Department of Energy’s Quadrennial Energy Review. If possible I would appreciate a confirmation that this email has been received Thank you.

  4. 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.

  5. Measured Peak Equipment Loads in Laboratories

    SciTech Connect (OSTI)

    Mathew, Paul A.

    2007-09-12

    This technical bulletin documents measured peak equipment load data from 39 laboratory spaces in nine buildings across five institutions. The purpose of these measurements was to obtain data on the actual peak loads in laboratories, which can be used to rightsize the design of HVAC systems in new laboratories. While any given laboratory may have unique loads and other design considerations, these results may be used as a 'sanity check' for design assumptions.

  6. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01

    Tables Table 1: Energy efficiency, daily load management andoptimization); peak load management (for daily operations);Operations Peak Load Management (Daily) - TOU Savings - Peak

  7. Supply Chain Supernetworks With Random Demands

    E-Print Network [OSTI]

    Nagurney, Anna

    Supply Chain Supernetworks With Random Demands June Dong Ding Zhang School of Business State Field Warehouses: stocking points Customers, demand centers sinks Production/ purchase costs Inventory Customer Demand Customer Demand Retailer OrdersRetailer Orders Distributor OrdersDistributor Orders

  8. Participation through Automation: Fully Automated Critical PeakPricing in Commercial Buildings

    SciTech Connect (OSTI)

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

    2006-06-20

    California electric utilities have been exploring the use of dynamic critical peak prices (CPP) and other demand response programs to help reduce peaks in customer electric loads. CPP is a tariff design to promote demand response. Levels of automation in DR can be defined as follows: Manual Demand Response involves a potentially labor-intensive approach such as manually turning off or changing comfort set points at each equipment switch or controller. Semi-Automated Demand Response involves a pre-programmed demand response strategy initiated by a person via centralized control system. 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. The receipt of the external signal initiates pre-programmed demand response strategies. They refer to this as Auto-DR. This paper describes the development, testing, and results from automated CPP (Auto-CPP) as part of a utility project in California. The paper presents the project description and test methodology. This is followed by a discussion of Auto-DR strategies used in the field test buildings. They present a sample Auto-CPP load shape case study, and a selection of the Auto-CPP response data from September 29, 2005. If all twelve sites reached their maximum saving simultaneously, a total of approximately 2 MW of DR is available from these twelve sites that represent about two million ft{sup 2}. The average DR was about half that value, at about 1 MW. These savings translate to about 0.5 to 1.0 W/ft{sup 2} of demand reduction. They are continuing field demonstrations and economic evaluations to pursue increasing penetrations of automated DR that has demonstrated ability to provide a valuable DR resource for California.

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

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

    & Driving Demand Collaborative - Social Media Tools & Strategies Marketing & Driving Demand Collaborative - Social Media Tools & Strategies Presentation slides from the Better...

  10. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01

    Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the

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

    Office of Environmental Management (EM)

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

  12. Effects of the drought on California electricity supply and demand

    E-Print Network [OSTI]

    Benenson, P.

    2010-01-01

    Acknowledgments SUMMARY Electricity Demand ElectricityAdverse Impacts ELECTRICITY DEMAND . . . .Demand forElectricity Sales Electricity Demand by Major Utility

  13. Chilled Water Thermal Storage System and Demand Response at the University of California at Merced

    SciTech Connect (OSTI)

    Granderson, Jessica; Dudley, Junqiao Han; Kiliccote, Sila; Piette, Mary Ann

    2009-10-08

    The University of California at Merced is a unique campus that has benefited from intensive efforts to maximize energy efficiency, and has participated in a demand response program for the past two years. Campus demand response evaluations are often difficult because of the complexities introduced by central heating and cooling, non-coincident and diverse building loads, and existence of a single electrical meter for the entire campus. At the University of California at Merced, a two million gallon chilled water storage system is charged daily during off-peak price periods and used to flatten the load profile during peak demand periods. This makes demand response more subtle and challenges typical evaluation protocols. The goal of this research is to study demand response savings in the presence of storage systems in a campus setting. First, University of California at Merced summer electric loads are characterized; second, its participation in two demand response events is detailed. In each event a set of strategies were pre-programmed into the campus control system to enable semi-automated response. Finally, demand savings results are applied to the utility's DR incentives structure to calculate the financial savings under various DR programs and tariffs. A key conclusion to this research is that there is significant demand reduction using a zone temperature set point change event with the full off peak storage cooling in use.

  14. 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.

  15. Petroleum marketing monthly

    SciTech Connect (OSTI)

    1995-11-01

    The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data.

  16. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune 25,July 2003 E n eMonthly6

  17. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune 25,July 2003 E n0 Monthly

  18. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune 25,July 2003 E n0 Monthly1

  19. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune 25,JulyOctober39 Monthly

  20. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune 25,JulyOctober39 Monthly1

  1. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune 25,JulyOctober392 Monthly

  2. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune 25,JulyOctober392 Monthly4

  3. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune 25,JulyOctober3927 Monthly

  4. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly Performance

  5. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly Performance9

  6. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly Performance960

  7. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly Performance9607

  8. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly Performance96073

  9. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly Performance960735

  10. Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly

  11. Monthly Report 2015

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines light on77 PAGEMissionStress New WebpageJune0 Monthly9Report 2015

  12. NUG Monthly Telecon Agenda

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines lightGeospatialDevelopment of09 AugustPlasma Physics 6, 2015 NUG Monthly

  13. NUG Monthly Telecon Welcome!

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration wouldMass map shines lightGeospatialDevelopment of09 AugustPlasma Physics 6, 2015 NUG Monthly

  14. Electric Power Monthly

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963 1.969Central RegionReporting GuidelinesFeet)Table 1.Monthly >

  15. Monthly NUG Webinars

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete7ModificationsMonitoring JobsBiodieselWebinars Monthly

  16. MSC Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport) | SciTechAdministration | DepartmentMSA2 Monthly

  17. MSC Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport) | SciTechAdministration | DepartmentMSA2 Monthly1

  18. MSC Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport) | SciTechAdministration | DepartmentMSA2 Monthly18

  19. MSC Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport) | SciTechAdministration | DepartmentMSA2 Monthly180

  20. MSC Monthly Performance Report

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverseIMPACTThousandReport) | SciTechAdministration | DepartmentMSA2 Monthly1806

  1. First Tracer Test After Circulation in Desert Peak 27-15

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

    Rose, Peter

    2013-11-16

    Following the successful stimulation of Desert Peak target EGS well 27-15, a circulation test was initiated by injecting a conservative tracer (1,5-nds) in combination with a reactive tracer (7-amino-1,3-naphthalene disulfonate). The closest production well 74-21 was monitored over the subsequent several months.

  2. First Tracer Test After Circulation in Desert Peak 27-15

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

    Rose, Peter

    Following the successful stimulation of Desert Peak target EGS well 27-15, a circulation test was initiated by injecting a conservative tracer (1,5-nds) in combination with a reactive tracer (7-amino-1,3-naphthalene disulfonate). The closest production well 74-21 was monitored over the subsequent several months.

  3. The PEAK experience in South Carolina

    SciTech Connect (OSTI)

    1998-11-01

    The PEAK Institute was developed to provide a linkage for formal (schoolteachers) and nonformal educators (extension agents) with agricultural scientists of Clemson University`s South Carolina Agricultural Experiment Station System. The goal of the Institute was to enable teams of educators and researchers to develop and provide PEAK science and math learning experiences related to relevant agricultural and environmental issues of local communities for both classroom and 4-H Club experiences. The Peak Institute was conducted through a twenty day residential Institute held in June for middle school and high school teachers who were teamed with an Extension agent from their community. These educators participated in hands-on, minds-on sessions conducted by agricultural researchers and Clemson University Cooperative Extension specialists. Participants were given the opportunity to see frontier science being conducted by scientists from a variety of agricultural laboratories.

  4. Demand and Price Volatility: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01

    A Joint Model of the Global Crude Oil Market and the U.S.Noureddine. 2002. World crude oil and natural gas: a demandelasticity of demand for crude oil, not gasoline. Results

  5. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01

    A Joint Model of the Global Crude Oil Market and the U.S.Noureddine. 2002. World crude oil and natural gas: a demandelasticity of demand for crude oil, not gasoline. Results

  6. Addressing Energy Demand through Demand Response: International Experiences and Practices

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    electricity. In this manner, demand side management is directly integrated into the wholesale capacity marketcapacity market U.S. Federal Energy Regulatory Commission Florida Reliability Coordinating Council incremental auctions independent electricity

  7. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01

    global gasoline and diesel price and income elasticities.shift in the short-run price elasticity of gasoline demand.Habits and Uncertain Relative Prices: Simulating Petrol Con-

  8. U.S. electric utility demand-side management 1995

    SciTech Connect (OSTI)

    NONE

    1997-01-01

    The US Electric Utility Demand-Side Management report is prepared by the Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternative Fuels; Energy Information Administration (EIA); US Department of Energy. The report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it relates to the US electric power industry. The first chapter, ``Profile: US Electric Utility Demand-Side Management``, presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs.

  9. U.S. electric utility demand-side management 1996

    SciTech Connect (OSTI)

    1997-12-01

    The US Electric Utility Demand-Side Management report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it related to the US electric power industry. The first chapter, ``Profile: U.S. Electric Utility Demand-Side Management,`` presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs.

  10. AMI Communication Requirements to Implement Demand-Response: Applicability of Hybrid Spread Spectrum Wireless

    SciTech Connect (OSTI)

    Hadley, Mark D.; Clements, Samuel L.; Carroll, Thomas E.

    2011-09-30

    While holistically defining the smart grid is a challenge, one area of interest is demand-response. In 2009, the Department of Energy announced over $4 billion in grant and project funding for the Smart Grid. A significant amount of this funding was allotted to utilities for cost sharing projects to deploy Smart Grid technologies, many of whom have deployed and are deploying advanced metering infrastructure (AMI). AMI is an enabler to increase the efficiency of utilities and the bulk power grid. The bulk electrical system is unique in that it produces electricity as it is consumed. Most other industries have a delay between generation and consumption. This aspect of the power grid means that there must be enough generation capacity to meet the highest demand whereas other industries could over produce during off-peak times. This requires significant investment in generation capacity to cover the few days a year of peak consumption. Since bulk electrical storage doesn't yet exist at scale another way to curb the need for new peak period generation is through demand-response; that is to incentivize consumers (demand) to curtail (respond) electrical usage during peak periods. Of the various methods proposed for enabling demand-response, this paper will focus on the communication requirements for creating an energy market using transactional controls. More specifically, the paper will focus on the communication requirements needed to send the peak period notices and receive the response back from the consumers.

  11. Optimization of Occupancy Based Demand Controlled Ventilation in Residences

    SciTech Connect (OSTI)

    Mortensen, Dorthe K.; Walker, Iain S.; Sherman, Max H.

    2011-05-01

    Although it has been used for many years in commercial buildings, the application of demand controlled ventilation in residences is limited. In this study we used occupant exposure to pollutants integrated over time (referred to as 'dose') as the metric to evaluate the effectiveness and air quality implications of demand controlled ventilation in residences. We looked at air quality for two situations. The first is that typically used in ventilation standards: the exposure over a long term. The second is to look at peak exposures that are associated with time variations in ventilation rates and pollutant generation. The pollutant generation had two components: a background rate associated with the building materials and furnishings and a second component related to occupants. The demand controlled ventilation system operated at a low airflow rate when the residence was unoccupied and at a high airflow rate when occupied. We used analytical solutions to the continuity equation to determine the ventilation effectiveness and the long-term chronic dose and peak acute exposure for a representative range of occupancy periods, pollutant generation rates and airflow rates. The results of the study showed that we can optimize the demand controlled airflow rates to reduce the quantity of air used for ventilation without introducing problematic acute conditions.

  12. 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.

  13. Physically-based demand modeling 

    E-Print Network [OSTI]

    Calloway, Terry Marshall

    1980-01-01

    nts on the demand. Of course the demand of a real a1r cond1t1oner has lower and upper bounds equal to 0 and 0 , respec- u tively. A constra1ned system can be simulated numerically, but there 1s no explicit system response formula s1m11ar... sect1on. It may now be instruct1ve to relate this model to that of Jones and Bri ce [5] . The average demand pred1 cted by their model is the expected value of the product of a load response factor 0 and a U sw1tching process H(t), which depends...

  14. Journal of Artificial Intelligence Research 50 (2014) 885-922 Submitted 4/14; published 8/14 Demand Side Energy Management via Multiagent Coordination in

    E-Print Network [OSTI]

    Sadeh, Norman M.

    2014-01-01

    Side Energy Management via Multiagent Coordination in Consumer Cooperatives Andreas Veit ANDREAS are to increase the penetration of renewable sources, and to manage supply and demand so as to reduce demand peaks demand supply balance by adjusting only the supply side leads to the use of flexible (usually diesel

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    Pacific Gas and Electric power purchase agreement peak timein structure to a power purchase agreement (PPA) that athe need to purchase high-priced power, all customers in a

  16. Hawaii demand-side management resource assessment. Final report, Reference Volume 4: The DBEDT DSM assessment model user`s manual

    SciTech Connect (OSTI)

    1995-04-01

    The DBEDT DSM Assessment Model (DSAM) is a spreadsheet model developed in Quattro Pro for Windows that is based on the integration of the DBEDT energy forecasting model, ENERGY 2020, with the output from the building energy use simulation model, DOE-2. DOE-2 provides DSM impact estimates for both energy and peak demand. The ``User`s Guide`` is designed to assist DBEDT staff in the operation of DSAM. Supporting information on model structure and data inputs are provided in Volumes 2 and 3 of the Final Report. DSAM is designed to provide DBEDT estimates of the potential DSM resource for each county in Hawaii by measure, program, sector, year, and levelized cost category. The results are provided for gas and electric and for both energy and peak demand. There are two main portions of DSAM, the residential sector and the commercial sector. The basic underlying logic for both sectors are the same. However, there are some modeling differences between the two sectors. The differences are primarily the result of (1) the more complex nature of the commercial sector, (2) memory limitations within Quattro Pro, and (3) the fact that the commercial sector portion of the model was written four months after the residential sector portion. The structure for both sectors essentially consists of a series of input spreadsheets, the portion of the model where the calculations are performed, and a series of output spreadsheets. The output spreadsheets contain both detailed and summary tables and graphs.

  17. Coordination of Retail Demand Response with Midwest ISO Markets

    SciTech Connect (OSTI)

    Bharvirkar, Ranjit; Bharvirkar, Ranjit; Goldman, Charles; Heffner, Grayson; Sedano, Richard

    2008-05-27

    The Organization of Midwest ISO States (OMS) launched the Midwest Demand Resource Initiative (MWDRI) in 2007 to identify barriers to deploying demand response (DR) resources in the Midwest Independent System Operator (MISO) region and develop policies to overcome them. The MWDRI stakeholders decided that a useful initial activity would be to develop more detailed information on existing retail DR programs and dynamic pricing tariffs, program rules, and utility operating practices. This additional detail could then be used to assess any"seams issues" affecting coordination and integration of retail DR resources with MISO's wholesale markets. Working with state regulatory agencies, we conducted a detailed survey of existing DR programs, dynamic pricing tariffs, and their features in MISO states. Utilities were asked to provide information on advance notice requirements to customers, operational triggers used to call events (e.g. system emergencies, market conditions, local emergencies), use of these DR resources to meet planning reserves requirements, DR resource availability (e.g., seasonal, annual), participant incentive structures, and monitoring and verification (M&V) protocols. This report describes the results of this comprehensive survey and discusses policy implications for integrating legacy retail DR programs and dynamic pricing tariffs into organized wholesale markets. Survey responses from 37 MISO members and 4 non-members provided information on 141 DR programs and dynamic pricing tariffs with a peak load reduction potential of 4,727 MW of retail DR resource. Major findings of this study area:- About 72percent of available DR is from interruptible rate tariffs offered to large commercial and industrial customers, while direct load control (DLC) programs account for ~;;18percent. Almost 90percent of the DR resources included in this survey are provided by investor-owned utilities. - Approximately, 90percent of the DR resources are available with less than two hours advance notice and over 1,900 MW can be dispatched on less than thirty minutes notice. These legacy DR programs are increasingly used by utilities for economic in addition to reliability purposes, with over two-thirds (68percent) of these programs callable based on market conditions. - Approximately 60percent of DLC programs and 30percent of interruptible rate programs called ten or more DR events in 2006. Despite the high frequency of DR events, customer complaints remained low. The use of economic criteria to trigger DR events and the flexibility to trigger a large number of events suggests that DR resources can help improve the efficiency of MISO wholesale markets. - Most legacy DR programs offered a reservation payment ($/kW) for participation; incentive payment levels averaged about $5/kW-month for interruptible rate tariffs and $6/kW-month for DLC programs. Few programs offered incentive payments that were explicitly linked to actual load reductions during events and at least 27 DR programs do not have penalties for non-performance. - Measurement and verification (M&V) protocols to estimate load impacts vary significantly across MISO states. Almost half of the DR programs have not been evaluated in recent times and thus performance data for DR events is not available. For many DLC programs, M&V protocols may need to be enhancedin order to allow participation in MISO's proposed EDR schedule. System operators and planners will need to develop more accurate estimates of the load reduced capability and actual performance.

  18. Seasonality in air transportation demand

    E-Print Network [OSTI]

    Reichard Megwinoff, H?tor Nicolas

    1988-01-01

    This thesis investigates the seasonality of demand in air transportation. It presents three methods for computing seasonal indices. One of these methods, the Periodic Average Method, is selected as the most appropriate for ...

  19. Demand response enabling technology development

    E-Print Network [OSTI]

    2006-01-01

    Monitoring in an Agent-Based Smart Home, Proceedings of theConference on Smart Homes and Health Telematics, September,Smart Meter Motion sensors Figure 1: Schematic of the Demand Response Electrical Appliance Manager in a Home.

  20. Full Rank Rational Demand Systems

    E-Print Network [OSTI]

    LaFrance, Jeffrey T; Pope, Rulon D.

    2006-01-01

    Dover Publications 1972. Barnett, W.A. and Y.W. Lee. “TheEconometrica 53 (1985): 1421- Barnett, W.A. , Lee, Y.W. ,Laurent demand systems (Barnett and Lee 1985; Barnett, Lee,

  1. 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.

  2. Marketing Demand-Side Management 

    E-Print Network [OSTI]

    O'Neill, M. L.

    1988-01-01

    Demand-Side Management is an organizational tool that has proven successful in various realms of the ever changing business world in the past few years. It combines the multi-faceted desires of the customers with the increasingly important...

  3. Preliminary Assumptions for Natural Gas Peaking

    E-Print Network [OSTI]

    ; adjusted to 2012$, state construction cost index, vintage of cost estimate, scope of estimate to extent's Discussion Aeroderivative Gas Turbine Technology Proposed reference plant and assumptions Preliminary cost Robbins 2 #12;Peaking Power Plant Characteristics 6th Power Plan ($2006) Unit Size (MW) Capital Cost ($/k

  4. Demand Response Spinning Reserve Demonstration

    SciTech Connect (OSTI)

    Eto, Joseph H.; Nelson-Hoffman, Janine; Torres, Carlos; Hirth,Scott; Yinger, Bob; Kueck, John; Kirby, Brendan; Bernier, Clark; Wright,Roger; Barat, A.; Watson, David S.

    2007-05-01

    The Demand Response Spinning Reserve project is a pioneeringdemonstration of how existing utility load-management assets can providean important electricity system reliability resource known as spinningreserve. Using aggregated demand-side resources to provide spinningreserve will give grid operators at the California Independent SystemOperator (CAISO) and Southern California Edison (SCE) a powerful, newtool to improve system reliability, prevent rolling blackouts, and lowersystem operating costs.

  5. Open Automated Demand Response Communications in Demand Response for Wholesale Ancillary Services

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01

    A. Barat, D. Watson. 2006 Demand Response Spinning ReserveKueck, and B. Kirby 2008. Demand Response Spinning ReserveReport 2009. Open Automated Demand Response Communications

  6. Demand Response and Open Automated Demand Response Opportunities for Data Centers

    E-Print Network [OSTI]

    Mares, K.C.

    2010-01-01

    Standardized Automated Demand Response Signals. Presented atand Automated Demand Response in Industrial RefrigeratedActions for Industrial Demand Response in California. LBNL-

  7. Optimal Demand Response and Power Flow

    E-Print Network [OSTI]

    Willett, Rebecca

    Optimal Demand Response and Power Flow Steven Low Computing + Math Sciences Electrical Engineering #12;Outline Optimal demand response n With L. Chen, L. Jiang, N. Li Optimal power flow n With S. Bose;Optimal demand response Model Results n Uncorrelated demand: distributed alg n Correlated demand

  8. Peak CO2? China's Emissions Trajectories to 2050

    E-Print Network [OSTI]

    Zhou, Nan

    2012-01-01

    vis- à-vis lowering electricity demand), as efficiencygce/kWh) in 2050 Total electricity demand reaches 9100 TWhin 2050 Total electricity demand reaches 7,764 TWh in 2050

  9. Monthly energy review, August 1997

    SciTech Connect (OSTI)

    1997-08-01

    The Monthly Energy Review for the month of August 1997, presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors.

  10. Petroleum supply monthly

    SciTech Connect (OSTI)

    1995-10-01

    The Petroleum Supply Monthly (PSM) is one of a family of four publications produced by the Petroleum Supply Division within the Energy Information Administration (EIA) reflecting different levels of data timeliness and completeness. The other publications are the Weekly Petroleum Status Report (WPSR), the Winter Fuels Report, and the Petroleum Supply Annual (PSA). Data presented in the PSM describe the supply and disposition of petroleum products in the United States and major US geographic regions. The data series describe production, imports and exports, inter-Petroleum Administration for Defense (PAD) District movements, and inventories by the primary suppliers of petroleum products in the United States (50 States and the District of Columbia). The reporting universe includes those petroleum sectors in primary supply. Included are: petroleum refiners, motor gasoline blends, operators of natural gas processing plants and fractionators, inter-PAD transporters, importers, and major inventory holders of petroleum products and crude oil. When aggregated, the data reported by these sectors approximately represent the consumption of petroleum products in the United States.

  11. Petroleum Supply Monthly

    SciTech Connect (OSTI)

    1996-02-01

    The Petroleum Supply Monthly (PSM) is one of a family of four publications produced by the Petroleum Supply Division within the Energy Information Administration (EIA) reflecting different levels of data timeliness and completeness. The other publications are the Weekly Petroleum Status Report (WPSR), the Winter Fuels Report, and the Petroleum Supply Annual (PSA). Data presented in the PSM describe the supply and disposition of petroleum products in the United States and major U.S. geographic regions. The data series describe production, imports and exports, inter-Petroleum Administration for Defense (PAD) District movements, and inventories by the primary suppliers of petroleum products in the United States (50 States and the District of Columbia). The reporting universe includes those petroleum sectors in primary supply. Included are: petroleum refiners, motor gasoline blenders, operators of natural gas processing plants and fractionators, inter-PAD transporters, importers, and major inventory holders of petroleum products and crude oil. When aggregated, the data reported by these sectors approximately represent the consumption of petroleum products in the United States. Data presented in the PSM are divided into two sections: Summary Statistics and Detailed Statistics.

  12. Monitoring peak power and cooling energy savings of shade trees and white surfaces in the Sacramento Municipal Utility District (SMUD) service area: Project design and preliminary results

    SciTech Connect (OSTI)

    Akbari, H.; Bretz, S.; Hanford, J.; Rosenfeld, A.; Sailor, D.; Taha, H. [Lawrence Berkeley Lab., CA (United States); Bos, W. [Sacramento Municipal Utility District, CA (United States)

    1992-12-01

    Urban areas in warm climates create summer heat islands of daily average intensity of 3--5{degrees}C, adding to discomfort and increasing air-conditioning loads. Two important factors contributing to urban heat islands are reductions in albedo (lower overall city reflectance) and loss of vegetation (less evapotranspiration). Reducing summer heat islands by planting vegetation (shade trees) and increasing surface albedos, saves cooling energy, allows down-sizing of air conditioners, lowers air-conditioning peak demand, and reduces the emission of CO{sub 2} and other pollutants from electric power plants. The focus of this multi-year project, jointly sponsored by SMUD and the California Institute for Energy Efficiency (CIEE), was to measure the direct cooling effects of trees and white surfaces (mainly roofs) in a few buildings in Sacramento. The first-year project was to design the experiment and obtain base case data. We also obtained limited post retrofit data for some sites. This report provides an overview of the project activities during the first year at six sites. The measurement period for some of the sites was limited to September and October, which are transitional cooling months in Sacramento and hence the interpretation of results only apply to this period. In one house, recoating the dark roof with a high-albedo coating rendered air conditioning unnecessary for the month of September (possible savings of up to 10 kWh per day and 2 kW of non-coincidental peak power). Savings of 50% relative to an identical base case bungalow were achieved when a school bungalow`s roof and southeast wall were coated with a high-albedo coating during the same period. Our measured data for the vegetation sites do not indicate conclusive results because shade trees were small and the cooling period was almost over. We need to collect more data over a longer cooling season in order to demonstrate savings conclusively.

  13. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

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

  14. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

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

  15. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

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

  16. Demand Response as a System Reliability Resource

    E-Print Network [OSTI]

    Joseph, Eto

    2014-01-01

    Barat, and D. Watson. 2007. Demand Response Spinning ReserveKueck, and B. Kirby. 2009. Demand Response Spinning ReserveFormat of 2009-2011 Demand Response Activity Applications.

  17. Central peaking of magnetized gas discharges

    SciTech Connect (OSTI)

    Chen, Francis F. [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States)] [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Curreli, Davide [Department of Nuclear, Plasma and Radiological Engineering, University of Illinois at Urbana Champaign, Urbana, Illinois 61801 (United States)] [Department of Nuclear, Plasma and Radiological Engineering, University of Illinois at Urbana Champaign, Urbana, Illinois 61801 (United States)

    2013-05-15

    Partially ionized gas discharges used in industry are often driven by radiofrequency (rf) power applied at the periphery of a cylinder. It is found that the plasma density n is usually flat or peaked on axis even if the skin depth of the rf field is thin compared with the chamber radius a. Previous attempts at explaining this did not account for the finite length of the discharge and the boundary conditions at the endplates. A simple 1D model is used to focus on the basic mechanism: the short-circuit effect. It is found that a strong electric field (E-field) scaled to electron temperature T{sub e}, drives the ions inward. The resulting density profile is peaked on axis and has a shape independent of pressure or discharge radius. This “universal” profile is not affected by a dc magnetic field (B-field) as long as the ion Larmor radius is larger than a.

  18. Desert Peak EGS Project | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:FinancingPetroleum Based| Department8, 20153Danielthrough theKDesert Peak EGS Project DOE

  19. Peak power tracking for a solar buck charger

    E-Print Network [OSTI]

    Cohen, Jeremy Michael, M. Eng. Massachusetts Institute of Technology

    2010-01-01

    This thesis discusses the design, implementation, and testing of a buck converter with peak power tracking. The peak power tracker uses a perturb and observe algorithm to actively track the solar panel's peak power point ...

  20. An alternative interpretation for cosmic ray peaks

    E-Print Network [OSTI]

    Kim, Doojin

    2015-01-01

    We propose an alternative mechanism based upon dark matter (DM) interpretation for anomalous peak signatures in cosmic ray measurements, assuming an extended dark sector with two DM species. This is contrasted with previous effort to explain various line-like cosmic-ray excesses in the context of DM models where the relevant DM candidate directly annihilates into Standard Model (SM) particles. The heavier DM is assumed to annihilate to an on-shell intermediate state. As the simplest choice, it decays directly into the lighter DM along with an unstable particle which in turn decays to a pair of SM states corresponding to the interesting cosmic anomaly. We show that a sharp continuum energy peak can be readily generated under the proposed DM scenario, depending on dark sector particle mass spectra. Remarkably, such a peak is robustly identified as half the mass of the unstable particle. Furthermore, other underlying mass parameters are analytically related to the shape of energy spectrum. We apply this idea to ...

  1. OFF-SHORE WIND AND GRID-CONNECTED PV: HIGH PENETRATION PEAK SHAVING FOR NEW YORK CITY

    E-Print Network [OSTI]

    Perez, Richard R.

    OFF-SHORE WIND AND GRID-CONNECTED PV: HIGH PENETRATION PEAK SHAVING FOR NEW YORK CITY Richard Perez-shore wind and PV generation using the city of New York as a test case. While wind generation is not known one year's worth of hourly site & time-specific data including electrical demand PV and off-shore wind

  2. Exponential Communication Ine ciency of Demand Queries

    E-Print Network [OSTI]

    Sandholm, Tuomas W.

    FORECAST COMBINATION IN REVENUE MANAGEMENT DEMAND FORECASTING SILVIA RIEDEL A thesissubmitted Combination in RevenueManagement Demand Forecasting Abstract The domain of multi level forecastcombination

  3. 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...

  4. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    demand response: ? Distribution utility ? ISO ? Aggregator (demand response less obstructive and inconvenient for the customer (particularly if DR resources are aggregated by a load aggregator).

  5. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01

    annual per-capita electricity consumption by demand15 California electricity consumption projections by demandannual per-capita electricity consumption by demand

  6. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    California Long-term Energy Efficiency Strategic Plan. B-2 Coordination of Energy Efficiency and Demand Response> B-4 Coordination of Energy Efficiency and Demand Response

  7. Supply chain planning decisions under demand uncertainty

    E-Print Network [OSTI]

    Huang, Yanfeng Anna

    2008-01-01

    Sales and operational planning that incorporates unconstrained demand forecasts has been expected to improve long term corporate profitability. Companies are considering such unconstrained demand forecasts in their decisions ...

  8. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    > B-2 Coordination of Energy Efficiency and Demand Response> B-4 Coordination of Energy Efficiency and Demand Responseand integration is: Energy efficiency, energy conservation,

  9. 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 May 14, 2015 12:30PM to 2:00PM EDT Learn more...

  10. Demand Response Programs Oregon Public Utility Commission

    E-Print Network [OSTI]

    Demand Response Programs Oregon Public Utility Commission January 6, 2005 Mike Koszalka Director;Demand Response Results, 2004 Load Control ­ Cool Keeper ­ ID Irrigation Load Control Price Responsive

  11. 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.

  12. Turkey's energy demand and supply

    SciTech Connect (OSTI)

    Balat, M. [Sila Science, Trabzon (Turkey)

    2009-07-01

    The aim of the present article is to investigate Turkey's energy demand and the contribution of domestic energy sources to energy consumption. Turkey, the 17th largest economy in the world, is an emerging country with a buoyant economy challenged by a growing demand for energy. Turkey's energy consumption has grown and will continue to grow along with its economy. Turkey's energy consumption is high, but its domestic primary energy sources are oil and natural gas reserves and their production is low. Total primary energy production met about 27% of the total primary energy demand in 2005. Oil has the biggest share in total primary energy consumption. Lignite has the biggest share in Turkey's primary energy production at 45%. Domestic production should be to be nearly doubled by 2010, mainly in coal (lignite), which, at present, accounts for almost half of the total energy production. The hydropower should also increase two-fold over the same period.

  13. 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.

  14. 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.

  15. Findings from Seven Years of Field Performance Data for Automated Demand Response in Commercial Buildings

    SciTech Connect (OSTI)

    Kiliccote, Sila; Piette, Mary Ann; Mathieu, Johanna; Parrish, Kristen

    2010-05-14

    California is a leader in automating demand response (DR) to promote low-cost, consistent, and predictable electric grid management tools. Over 250 commercial and industrial facilities in California participate in fully-automated programs providing over 60 MW of peak DR savings. This paper presents a summary of Open Automated DR (OpenADR) implementation by each of the investor-owned utilities in California. It provides a summary of participation, DR strategies and incentives. Commercial buildings can reduce peak demand from 5 to 15percent with an average of 13percent. Industrial facilities shed much higher loads. For buildings with multi-year savings we evaluate their load variability and shed variability. We provide a summary of control strategies deployed, along with costs to install automation. We report on how the electric DR control strategies perform over many years of events. We benchmark the peak demand of this sample of buildings against their past baselines to understand the differences in building performance over the years. This is done with peak demand intensities and load factors. The paper also describes the importance of these data in helping to understand possible techniques to reach net zero energy using peak day dynamic control capabilities in commercial buildings. We present an example in which the electric load shape changed as a result of a lighting retrofit.

  16. Peak CO2? China's Emissions Trajectories to 2050

    SciTech Connect (OSTI)

    Zhou, Nan; Fridley, David G.; McNeil, Michael; Zheng, Nina; Ke, Jing; Levine, Mark

    2011-05-01

    As a result of soaring energy demand from a staggering pace of economic growth and the related growth of energy-intensive industry, China overtook the United States to become the world's largest contributor to CO{sub 2} emissions in 2007. At the same time, China has taken serious actions to reduce its energy and carbon intensity by setting both short-term energy intensity reduction goal for 2006 to 2010 as well as long-term carbon intensity reduction goal for 2020. This study focuses on a China Energy Outlook through 2050 that assesses the role of energy efficiency policies in transitioning China to a lower emission trajectory and meeting its intensity reduction goals. In the past years, LBNL has established and significantly enhanced the China End-Use Energy Model based on the diffusion of end-use technologies and other physical drivers of energy demand. This model presents an important new approach for helping understand China's complex and dynamic drivers of energy consumption and implications of energy efficiency policies through scenario analysis. A baseline ('Continued Improvement Scenario') and an alternative energy efficiency scenario ('Accelerated Improvement Scenario') have been developed to assess the impact of actions already taken by the Chinese government as well as planned and potential actions, and to evaluate the potential for China to control energy demand growth and mitigate emissions. It is a common belief that China's CO{sub 2} emissions will continue to grow throughout this century and will dominate global emissions. The findings from this research suggest that this will not likely be the case because of saturation effects in appliances, residential and commercial floor area, roadways, railways, fertilizer use, and urbanization will peak around 2030 with slowing population growth. The baseline and alternative scenarios also demonstrate that the 2020 goals can be met and underscore the significant role that policy-driven energy efficiency improvements will play in carbon mitigation along with a decarbonized power supply through greater renewable and non-fossil fuel generation.

  17. Demand Response and Energy Efficiency 

    E-Print Network [OSTI]

    2009-01-01

    stream_source_info ESL-IC-09-11-05.pdf.txt stream_content_type text/plain stream_size 14615 Content-Encoding ISO-8859-1 stream_name ESL-IC-09-11-05.pdf.txt Content-Type text/plain; charset=ISO-8859-1 Demand Response... 4 An Innovative Solution to Get the Ball Rolling ? Demand Response (DR) ? Monitoring Based Commissioning (MBCx) EnerNOC has a solution involving two complementary offerings. ESL-IC-09-11-05 Proceedings of the Ninth International Conference...

  18. Strategies for Demand Response in Commercial Buildings

    E-Print Network [OSTI]

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

    2006-01-01

    when called to do so. Daily Peak Load Management: Dailypeak load management is done in many buildings to minimizeimplement daily peak load management. Decisions about when

  19. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01

    Operations Peak Load Management (Daily) - TOU Savings - Peakefficiency, daily load management and DR Energy Efficiency:methods Daily Peak Load Management: Advances in metering

  20. First symposium on safety and standardisation of ultrasound in obstetrics 0 G. KOSSOFFand S. B. BARNETT 101 peak positive and peak negative acoustic pressure

    E-Print Network [OSTI]

    Illinois at Urbana-Champaign, University of

    . BARNETT 101 peak positive and peak negative acoustic pressure (P' and a-) location of both of the peak

  1. Pilot Peak Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo, Maryland:NPIProtectio1975) | Open EnergyPhoenicia,Creek,Pilgrim Hot SpringsPillow,Peak

  2. Mt Peak Utility | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIXsourceII Jump to: navigation, searchsource HistoryCharleston,Peak Utility Jump to:

  3. Revelation on Demand Nicolas Anciaux

    E-Print Network [OSTI]

    is willing to reveal the aggregate response (according to his company's policy) to the customer dataRevelation on Demand Nicolas Anciaux 1 · Mehdi Benzine1,2 · Luc Bouganim1 · Philippe Pucheral1 time to support epidemiological studies. In these and many other situations, aggregate data or partial

  4. Demand Response Providing Ancillary Services

    E-Print Network [OSTI]

    1 Demand Response Providing Ancillary Services: A Comparison of Opportunities and Challenges in US to operate (likely price takers) ­ Statistical reliability (property of large aggregations of small resources size based on Mid-Atlantic Reserve Zone #12;Market Rules: Resource Size Min. Size (MW) Aggregation

  5. 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.

  6. Water demand management in Kuwait

    E-Print Network [OSTI]

    Milutinovic, Milan, M. Eng. Massachusetts Institute of Technology

    2006-01-01

    Kuwait is an arid country located in the Middle East, with limited access to water resources. Yet water demand per capita is much higher than in other countries in the world, estimated to be around 450 L/capita/day. There ...

  7. On-demand data broadcasting 

    E-Print Network [OSTI]

    Kothandaraman, Kannan

    1998-01-01

    related to on-demand data broadcasting. We look at the problem of data broadcasting in an environment where clients make explicit requests to the server. The server broadcasts requested data items to all the clients, including those who have not requested...

  8. Natural Gas Monthly, October 1993

    SciTech Connect (OSTI)

    Not Available

    1993-11-10

    The (NGM) Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. This month`s feature articles are: US Production of Natural Gas from Tight Reservoirs: and Expanding Rule of Underground Storage.

  9. September is Scientific Supercomputing Month

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

    research. How has this investment benefitted you? Let us count the ways This month, DOE is celebrating scientific supercomputing. So over the next four Mondays, we will...

  10. Monthly energy review, January 1998

    SciTech Connect (OSTI)

    1998-01-01

    This report presents an overview of recent monthly energy statistics. Major activities covered include production, consumption, trade, stocks, and prices for fossil fuels, electricity, and nuclear energy.

  11. Natural gas monthly, August 1995

    SciTech Connect (OSTI)

    NONE

    1995-08-24

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. This month`s feature article is on US Natural Gas Imports and Exports 1994.

  12. Monthly energy review. May 1998

    SciTech Connect (OSTI)

    1998-05-01

    This report presents recent energy monthly statistics on the production, consumption, trade, stocks, and prices of petroleum, natural gas, coal, electricity, and nuclear energy.

  13. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    E-Print Network [OSTI]

    Thompson, Lisa

    2008-01-01

    Interoperable Automated Demand Response Infrastructure,study of automated demand response in wastewater treatmentopportunities for demand response control strategies in

  14. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01

    Report 2009. Open Automated Demand Response Communicationsand Techniques for Demand Response. California Energyand S. Kiliccote. Estimating Demand Response Load Impacts:

  15. Opportunities, Barriers and Actions for Industrial Demand Response in California

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01

    and Techniques for Demand Response, report for theand Reliability Demand Response Programs: Final Report.Demand Response

  16. Incorporating Demand Response into Western Interconnection Transmission Planning

    E-Print Network [OSTI]

    Satchwell, Andrew

    2014-01-01

    Aggregator Programs. Demand Response Measurement andIncorporating Demand Response into Western Interconnection13 Demand Response Dispatch

  17. Upply Chain Supernetworks with Random Demands

    E-Print Network [OSTI]

    Nagurney, Anna

    Upply Chain Supernetworks with Random Demands June Dong & Ding Zhang School of Business State Warehouses: stocking points Field Warehouses: stocking points Customers, demand centers sinks Production Commerce and Value Chain Management, 1998 Customer Demand Customer Demand Retailer OrdersRetailer Orders

  18. Design and Implementation of an Open, Interoperable AutomatedDemand Response Infrastructure

    SciTech Connect (OSTI)

    Piette, Mary Ann; Kiliccote, Sila; Ghatikar, Girish

    2007-10-01

    This paper describes the concept for and lessons from the development and field-testing of an open, interoperable communications infrastructure to support automating demand response (DR). Automating DR allows greater levels of participation and improved reliability and repeatability of the demand response and customer facilities. Automated DR systems have been deployed for critical peak pricing and demand bidding and are being designed for real time pricing. The system is designed to generate, manage, and track DR signals between utilities and Independent System Operators (ISOs) to aggregators and end-use customers and their control systems.

  19. Regression Models for Demand Reduction based on Cluster Analysis of Load Profiles

    SciTech Connect (OSTI)

    Yamaguchi, Nobuyuki; Han, Junqiao; Ghatikar, Girish; Piette, Mary Ann; Asano, Hiroshi; Kiliccote, Sila

    2009-06-28

    This paper provides new regression models for demand reduction of Demand Response programs for the purpose of ex ante evaluation of the programs and screening for recruiting customer enrollment into the programs. The proposed regression models employ load sensitivity to outside air temperature and representative load pattern derived from cluster analysis of customer baseline load as explanatory variables. The proposed models examined their performances from the viewpoint of validity of explanatory variables and fitness of regressions, using actual load profile data of Pacific Gas and Electric Company's commercial and industrial customers who participated in the 2008 Critical Peak Pricing program including Manual and Automated Demand Response.

  20. 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)

  1. The Pacific Northwest Demand Response Market Demonstration

    SciTech Connect (OSTI)

    Chassin, David P.; Hammerstrom, Donald J.; DeSteese, John G.

    2008-07-20

    This paper describes the implementation and results of a field demonstration wherein residential electric water heaters and thermostats, commercial building space conditioning, municipal water pump loads, and several distributed generators were coordinated to manage constrained feeder electrical distribution through the two-way communication of load status and electric price signals. The field demonstration took place in Washington and Oregon and was paid for by the U.S. Department of Energy and several northwest utilities. Price is found to be an effective control signal for managing transmission or distribution congestion. Real-time signals at 5-minute intervals are shown to shift controlled load in time. The behaviors of customers and their responses under fixed, time-ofuse, and real-time price contracts are compared. Peak loads are effectively reduced on the experimental feeder. A novel application of portfolio theory is applied to the selection of an optimal mix of customer contract types. Index Terms—demand response, power markets, retail markets, distribution automation, distributed resources, load control.

  2. Monthly energy review, November 1997

    SciTech Connect (OSTI)

    1997-11-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 91 tabs.

  3. Monthly energy review, July 1998

    SciTech Connect (OSTI)

    1998-07-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs. 73 tabs.

  4. Monthly energy review, November 1998

    SciTech Connect (OSTI)

    1998-11-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 61 tabs.

  5. Monthly energy review, March 1999

    SciTech Connect (OSTI)

    1999-03-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 74 tabs.

  6. Monthly energy review, October 1998

    SciTech Connect (OSTI)

    1998-10-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 61 tabs.

  7. Monthly energy review, January 1999

    SciTech Connect (OSTI)

    1999-01-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 61 tabs.

  8. Monthly energy review, February 1999

    SciTech Connect (OSTI)

    1999-02-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 73 tabs.

  9. Natural gas monthly, November 1998

    SciTech Connect (OSTI)

    NONE

    1998-11-01

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. 6 figs., 27 tabs.

  10. Natural gas monthly, February 1999

    SciTech Connect (OSTI)

    NONE

    1999-02-01

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. 6 figs., 28 tabs.

  11. Monthly energy review: April 1996

    SciTech Connect (OSTI)

    1996-04-01

    This monthly report presents an overview of energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. A section is also included on international energy. The feature paper which is included each month is entitled ``Energy equipment choices: Fuel costs and other determinants.`` 37 figs., 59 tabs.

  12. Monthly energy review, November 1996

    SciTech Connect (OSTI)

    1996-11-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 75 tabs.

  13. Monthly Energy Review, February 1996

    SciTech Connect (OSTI)

    1996-02-26

    This monthly publication presents an overview of EIA`s recent monthly energy statistics, covering the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. Two brief descriptions (`energy plugs`) on two EIA publications are presented at the start.

  14. Natural gas monthly, January 1999

    SciTech Connect (OSTI)

    NONE

    1999-02-01

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. 6 figs., 28 tabs.

  15. Monthly energy review, May 1999

    SciTech Connect (OSTI)

    1999-05-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 61 tabs.

  16. Monthly energy review, June 1998

    SciTech Connect (OSTI)

    1998-06-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 36 figs., 61 tabs.

  17. Property:OpenEI/UtilityRate/FixedDemandChargeMonth1 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformation Max Jump to:Information

  18. Property:OpenEI/UtilityRate/FixedDemandChargeMonth10 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformation Max Jump

  19. Property:OpenEI/UtilityRate/FixedDemandChargeMonth11 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformation Max JumpInformation 1 Jump to:

  20. Property:OpenEI/UtilityRate/FixedDemandChargeMonth12 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformation Max JumpInformation 1 Jump

  1. Property:OpenEI/UtilityRate/FixedDemandChargeMonth2 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformation Max JumpInformation 1

  2. Property:OpenEI/UtilityRate/FixedDemandChargeMonth3 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformation Max JumpInformation

  3. Property:OpenEI/UtilityRate/FixedDemandChargeMonth4 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformation Max JumpInformationInformation

  4. Property:OpenEI/UtilityRate/FixedDemandChargeMonth5 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformation Max

  5. Property:OpenEI/UtilityRate/FixedDemandChargeMonth6 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformation MaxInformation

  6. Property:OpenEI/UtilityRate/FixedDemandChargeMonth7 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformation MaxInformationInformation

  7. Property:OpenEI/UtilityRate/FixedDemandChargeMonth8 | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2 JumpPublicationDateInformation

  8. Property:OpenEI/UtilityRate/FlatDemandMonth2 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo,AltFuelVehicle2

  9. Nuclear Science & Engineering Monthly Reports | ORNL

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

    Science | Publications and Reports | NSED Monthly Reports SHARE Nuclear Science and Engineering Monthly Reports The Nuclear Science and Engineering Monthly Report includes a...

  10. Use of Residential Smart Appliances for Peak-Load Shifting and Spinning Reserves Cost/Benefit Analysis

    SciTech Connect (OSTI)

    Sastry, Chellury; Pratt, Robert G.; Srivastava, Viraj; Li, Shun

    2010-12-01

    In this report, we present the results of an analytical cost/benefit study of residential smart appliances from a utility/grid perspective in support of a joint stakeholder petition to the ENERGY STAR program within the Environmental Protection Agency (EPA) and Department of Energy (DOE). The goal of the petition is in part to provide appliance manufacturers incentives to hasten the production of smart appliances. The underlying hypothesis is that smart appliances can play a critical role in addressing some of the societal challenges, such as anthropogenic global warming, associated with increased electricity demand, and facilitate increased penetration of renewable sources of power. The appliances we consider include refrigerator/freezers, clothes washers, clothes dryers, room air-conditioners, and dishwashers. The petition requests the recognition that providing an appliance with smart grid capability, i.e., products that meet the definition of a smart appliance, is at least equivalent to a corresponding five percent in operational machine efficiencies. It is then expected that given sufficient incentives and value propositions, and suitable automation capabilities built into smart appliances, residential consumers will be adopting these smart appliances and will be willing participants in addressing the aforementioned societal challenges by more effectively managing their home electricity consumption. The analytical model we utilize in our cost/benefit analysis consists of a set of user-definable assumptions such as the definition of on-peak (hours of day, days of week, months of year), the expected percentage of normal consumer electricity consumption (also referred to as appliance loads) that can shifted from peak hours to off-peak hours, the average power rating of each appliance, etc. Based on these assumptions, we then formulate what the wholesale grid operating-cost savings, or benefits, would be if the smart capabilities of appliances were invoked, and some percentage of appliance loads were shifted away from peak hours to run during off-peak hours, and appliance loads served power-system balancing needs such as spinning reserves that would otherwise have to be provided by generators. The rationale is that appliance loads can be curtailed for about ten minutes or less in response to a grid contingency without any diminution in the quality of service to the consumer. We then estimate the wholesale grid operating-cost savings based on historical wholesale-market clearing prices (location marginal and spinning reserve) from major wholesale power markets in the United States. The savings derived from the smart grid capabilities of an appliance are then compared to the savings derived from a five percent increase in traditional operational machine efficiencies, referred to as cost in this report, to determine whether the savings in grid operating costs (benefits) are at least as high as or higher than the operational machine efficiency credit (cost).

  11. Gamow peak approximation near strong resonances

    E-Print Network [OSTI]

    Sachie Kimura; Aldo Bonasera

    2013-05-09

    We discuss the most effective energy range for charged particle induced reactions in a plasma environment at a given plasma temperature. The correspondence between the plasma temperature and the most effective energy should be modified from the one given by the Gamow peak energy, in the presence of a significant incident-energy dependence in the astrophysical S-factor as in the case of resonant reactions. The suggested modification of the effective energy range is important not only in thermonuclear reactions at high temperature in the stellar environment, e.g., in advanced burning stages of massive stars and in explosive stellar environment, as it has been already claimed, but also in the application of the nuclear reactions driven by ultra-intense laser pulse irradiations.

  12. Northwest Open Automated Demand Response Technology Demonstration Project

    SciTech Connect (OSTI)

    Kiliccote, Sila; Piette, Mary Ann; Dudley, Junqiao

    2010-03-17

    The Lawrence Berkeley National Laboratory (LBNL) Demand Response Research Center (DRRC) demonstrated and evaluated open automated demand response (OpenADR) communication infrastructure to reduce winter morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA) in the Seattle City Light (SCL) service territory at five sites: Seattle Municipal Tower, Seattle University, McKinstry, and two Target stores. This report describes the process and results of the demonstration. OpenADR is an information exchange model that uses a client-server architecture to automate demand-response (DR) programs. These field tests evaluated the feasibility of deploying fully automated DR during both winter and summer peak periods. DR savings were evaluated for several building systems and control strategies. This project studied DR during hot summer afternoons and cold winter mornings, both periods when electricity demand is typically high. This is the DRRC project team's first experience using automation for year-round DR resources and evaluating the flexibility of commercial buildings end-use loads to participate in DR in dual-peaking climates. The lessons learned contribute to understanding end-use loads that are suitable for dispatch at different times of the year. The project was funded by BPA and SCL. BPA is a U.S. Department of Energy agency headquartered in Portland, Oregon and serving the Pacific Northwest. BPA operates an electricity transmission system and markets wholesale electrical power at cost from federal dams, one non-federal nuclear plant, and other non-federal hydroelectric and wind energy generation facilities. Created by the citizens of Seattle in 1902, SCL is the second-largest municipal utility in America. SCL purchases approximately 40% of its electricity and the majority of its transmission from BPA through a preference contract. SCL also provides ancillary services within its own balancing authority. The relationship between BPA and SCL creates a unique opportunity to create DR programs that address both BPA's and SCL's markets simultaneously. Although simultaneously addressing both market could significantly increase the value of DR programs for BPA, SCL, and the end user, establishing program parameters that maximize this value is challenging because of complex contractual arrangements and the absence of a central Independent System Operator or Regional Transmission Organization in the northwest.

  13. Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01

    that pre-cool, rebound, or otherwise shift energy use to theexhibit almost no rebound and save some energy on DR days,kW) Rebound (kW) Daily Peak Demand (kW) Daily Energy (kWh) a

  14. Bottom-Up Self-Organization of Unpredictable Demand and Supply under Decentralized Power Management

    E-Print Network [OSTI]

    Wedde, Horst F.

    level of granularity, with short-term power balance fluctuation, in terms of a peak demand and supply, distributed power production at lower voltage levels (through wind turbines or solar panels) is considered, as this depends on external environmental conditions (e.g. solar and wind power). In Electrical Engineering

  15. Natural gas monthly, June 1996

    SciTech Connect (OSTI)

    NONE

    1996-06-24

    The natural gas monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The feature article for this month is Natural Gas Industry Restructuring and EIA Data Collection.

  16. Natural gas monthly, January 1994

    SciTech Connect (OSTI)

    Not Available

    1994-02-01

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The featured article for this month is on US coalbed methane production.

  17. Natural gas monthly, June 1994

    SciTech Connect (OSTI)

    Not Available

    1994-06-01

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The feature article this month is the executive summary from Natural Gas 1994: Issues and Trends. 6 figs., 31 tabs.

  18. Natural gas monthly, May 1997

    SciTech Connect (OSTI)

    1997-05-01

    The Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The feature article this month is ``Restructuring energy industries: Lessons from natural gas.`` 6 figs., 26 tabs.

  19. Natural gas monthly, December 1997

    SciTech Connect (OSTI)

    1997-12-01

    The Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The article this month is entitled ``Recent Trends in Natural Gas Spot Prices.`` 6 figs., 27 tabs.

  20. Peak Population: Timing and Influences of Peak Energy on the World and the United States 

    E-Print Network [OSTI]

    Warner, Kevin 1987-

    2012-11-28

    Peak energy is the notion that the world’s total production of usable energy will reach a maximum value and then begin an inexorable decline. Ninety-two percent of the world’s energy is currently derived from the non-renewable sources (oil, coal...

  1. Off-peak cooling using phase change material

    E-Print Network [OSTI]

    Benton, Charles Crisp

    1979-01-01

    The electric utilities in the United States are faced with continued rapid growth in electrical demand. The traditional response to growth in demand has been the expansion of generating capacity. However, economic, ...

  2. Monthly Energy Review, July 1992

    SciTech Connect (OSTI)

    1992-07-27

    The Monthly Energy Review is prepared by the Energy Information Administration. Topics discussed include: Energy Overview, Energy Consumption, Petroleum, Natural Gas, Oil and Gas Resource Development, Coal, Electricity, Nuclear Energy, Energy Prices, International Energy. (VC)

  3. Monthly energy review, August 1993

    SciTech Connect (OSTI)

    Not Available

    1993-08-26

    This publication presents information for the month of August, 1993 on the following: Energy overview; energy consumption; petroleum; natural gas; oil and gas resource development; coal; electricity; nuclear energy; energy prices, and international energy.

  4. EIA-914 monthly production report

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

    Monthly Crude Oil and Natural Gas Production Release date: August 31, 2015 | Next release date: September 30, 2015 Beginning with the June 2015 data, EIA is providing estimates for...

  5. Monthly energy review, July 1997

    SciTech Connect (OSTI)

    1997-07-01

    This document presents an overview of recent monthly energy statistics. Activities covered include: U.S. production, consumption, trade, stock, and prices for petroleum, coal, natural gas, electricity, and nuclear energy.

  6. Monthly energy review, August 1996

    SciTech Connect (OSTI)

    1996-08-01

    This report presents an overview of recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, coal, natural gas, electricity, and nuclear energy.

  7. Monthly energy review, April 1998

    SciTech Connect (OSTI)

    1998-04-01

    This report presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy data. A brief summary of the monthly and historical comparison data is provided in Section 1 of the report. A highlight section of the report provides an assessment of summer 1997 motor gasoline price increases.

  8. Monthly energy review, April 1999

    SciTech Connect (OSTI)

    1999-04-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public.

  9. Natural gas monthly, August 1994

    SciTech Connect (OSTI)

    Not Available

    1994-08-24

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  10. Natural gas monthly, November 1993

    SciTech Connect (OSTI)

    Not Available

    1993-11-29

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground state data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  11. Natural gas monthly, May 1999

    SciTech Connect (OSTI)

    NONE

    1999-05-01

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 27 tabs.

  12. Natural gas monthly, June 1993

    SciTech Connect (OSTI)

    Not Available

    1993-06-22

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  13. Natural gas monthly, April 1994

    SciTech Connect (OSTI)

    Not Available

    1994-04-26

    The National Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  14. Natural gas monthly: September 1996

    SciTech Connect (OSTI)

    NONE

    1996-09-01

    The Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 24 tabs.

  15. Natural gas monthly: December 1993

    SciTech Connect (OSTI)

    Not Available

    1993-12-01

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. Articles are included which are designed to assist readers in using and interpreting natural gas information.

  16. Natural gas monthly, September 1995

    SciTech Connect (OSTI)

    1995-09-27

    The (NGM) Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  17. Natural gas monthly, October 1995

    SciTech Connect (OSTI)

    1995-10-23

    The Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. A glossary of the terms used in this report is provided to assist readers in understanding the data presented in this publication. 6 figs., 30 tabs.

  18. Natural Gas Monthly, March 1996

    SciTech Connect (OSTI)

    NONE

    1996-03-25

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  19. Natural gas monthly, June 1998

    SciTech Connect (OSTI)

    NONE

    1998-06-01

    The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 27 tabs.

  20. Natural gas monthly, July 1993

    SciTech Connect (OSTI)

    Not Available

    1993-07-27

    The Natural Gas Monthly NGM highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

  1. Monthly energy review, August 1998

    SciTech Connect (OSTI)

    1998-08-01

    The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. 37 figs., 73 tabs.

  2. Monthly

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry NaturalPrices1Markets See(STEO), 19992, 19999,33.0ModelingDOL/

  3. Peak-Coincident Demand Savings from Behavior-Based Programs: Evidence from PPL Electric's Behavior and Education Program

    E-Print Network [OSTI]

    Stewart, James

    2013-01-01

    such as cooling degree hours as explanatory variables on thethe equation . A cooling degree hour (CDH) is the maximum of

  4. Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike

    E-Print Network [OSTI]

    DeForest, Nicholas

    2014-01-01

    N ATIONAL L ABORATORY Thermal Energy Storage for Electricity20, 2012. I. Dincer, On thermal energy storage systems andin research on cold thermal energy storage, International

  5. Abstract--This paper formulates and develops a peak demand control tool for electric systems within the framework of direct

    E-Print Network [OSTI]

    Catholic University of Chile (Universidad Católica de Chile)

    . The generic model presented herein is evaluated in an actual urban substation, characterized by a predominant commercial consumption, by the contribution of the air conditioning systems in the substation loads expansions. Currently, the high investment costs in new capacity have taken distribution firms to search

  6. Peak-Coincident Demand Savings from Behavior-Based Programs: Evidence from PPL Electric's Behavior and Education Program

    E-Print Network [OSTI]

    Stewart, James

    2013-01-01

    kW from residential load management programs (EIA, 2012).States are employing load-management strategies to reducefrom residential load management programs. Thus, from a

  7. Peak-Coincident Demand Savings from Behavior-Based Programs: Evidence from PPL Electric's Behavior and Education Program

    E-Print Network [OSTI]

    Stewart, James

    2013-01-01

    savings derived from air-conditioning efficiency measures.measures that increased air-conditioning efficiency, their electricity use and savings

  8. Managing the Night Off-Peak Power Demand in the Central Region UPS with Newly Commissioned NPP Capacities

    SciTech Connect (OSTI)

    Aminov, R. Z. [Saratov Research Center of the Russian Academy of Sciences (Russian Federation); Pron’, D. M. [Yu. A. Gagarin Saratov State Technical University (Russian Federation)

    2014-01-15

    The use of hydrogen technologies as a controlled-load consumer based on the newly commissioned base-load nuclear power plants to level out the daily load profile is justified for the Unified Power System (UPS) of the Central Region of Russia, as an example, for the period till 2020.

  9. STEO December 2012 - coal demand

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservation of Fe(II) byMultidayAlumni > The2/01/12 Page 1NEWSSupportcoal demand seen below

  10. Exploiting User Generated Content for Mountain Peak Detection

    E-Print Network [OSTI]

    Tagliasacchi, Marco

    Exploiting User Generated Content for Mountain Peak Detection Roman Fedorov Politecnico di Milano.g. snow water availability maps based on mountain peaks states extracted from photographs hosting services). User Generated Content(UGC); collective intelligence; passive crowdsourcing; environmental models

  11. Scaling Microblogging Services with Divergent Traffic Demands

    E-Print Network [OSTI]

    Fu, Xiaoming

    Scaling Microblogging Services with Divergent Traffic Demands Tianyin Xu, Yang Chen, Lei Jiao, Ben-server architecture has not scaled with user demands, lead- ing to server overload and significant impairment

  12. Michel Meulpolder Managing Supply and Demand of

    E-Print Network [OSTI]

    Michel Meulpolder Managing Supply and Demand of Bandwidth in Peer-to-Peer Communities #12;#12;Managing Supply and Demand of Bandwidth in Peer-to-Peer Communities Proefschrift ter verkrijging van de

  13. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

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

  14. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

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

  15. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

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

  16. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

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

  17. Solar in Demand | Department of Energy

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

    Solar in Demand Solar in Demand June 15, 2012 - 10:23am Addthis Kyle Travis, left and Jon Jackson, with Lighthouse Solar, install microcrystalline PV modules on top of Kevin...

  18. Demand Effects in Productivity and Efficiency Analysis 

    E-Print Network [OSTI]

    Lee, Chia-Yen

    2012-07-16

    Demand fluctuations will bias the measurement of productivity and efficiency. This dissertation described three ways to characterize the effect of demand fluctuations. First, a two-dimensional efficiency decomposition (2DED) of profitability...

  19. Industrial Equipment Demand and Duty Factors 

    E-Print Network [OSTI]

    Dooley, E. S.; Heffington, W. M.

    1998-01-01

    Demand and duty factors have been measured for selected equipment (air compressors, electric furnaces, injection molding machines, centrifugal loads, and others) in industrial plants. Demand factors for heavily loaded air ...

  20. Assessing the Control Systems Capacity for Demand Response in California Industries

    SciTech Connect (OSTI)

    Ghatikar, Girish; McKane, Aimee; Goli, Sasank; Therkelsen, Peter; Olsen, Daniel

    2012-01-18

    California's electricity markets are moving toward dynamic pricing models, such as real-time pricing, within the next few years, which could have a significant impact on an industrial facility's cost of energy use during the times of peak use. Adequate controls and automated systems that provide industrial facility managers real-time energy use and cost information are necessary for successful implementation of a comprehensive electricity strategy; however, little is known about the current control capacity of California industries. To address this gap, Lawrence Berkeley National Laboratory, in close collaboration with California industrial trade associations, conducted a survey to determine the current state of controls technologies in California industries. This,study identifies sectors that have the technical capability to implement Demand Response (DR) and Automated Demand Response (Auto-DR). In an effort to assist policy makers and industry in meeting the challenges of real-time pricing, facility operational and organizational factors were taken into consideration to generate recommendations on which sectors Demand Response efforts should be focused. Analysis of the survey responses showed that while the vast majority of industrial facilities have semi- or fully automated control systems, participation in Demand Response programs is still low due to perceived barriers. The results also showed that the facilities that use continuous processes are good Demand Response candidates. When comparing facilities participating in Demand Response to those not participating, several similarities and differences emerged. Demand Response-participating facilities and non-participating facilities had similar timings of peak energy use, production processes, and participation in energy audits. Though the survey sample was smaller than anticipated, the results seemed to support our preliminary assumptions. Demonstrations of Auto-Demand Response in industrial facilities with good control capabilities are needed to dispel perceived barriers to participation and to investigate industrial subsectors suggested of having inherent Demand Response potential.