Sample records for total demand includes

  1. Best Practices: Energy Savings Efficient energy use reduces Colorado State's total energy demand, decreases harmful

    E-Print Network [OSTI]

    Best Practices: Energy Savings Efficient energy use reduces Colorado State's total energy demand, decreases harmful emissions, and minimizes the cost of providing energy to the campus. As a result of energy conservation initiatives that have been implemented over the past 20 years, growth in the average demand per

  2. "Table A16. Components of Total Electricity Demand by Census Region, Industry"

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. AppliancesTotal" "(Data1.30. Total6. Components of

  3. Table A19. Components of Total Electricity Demand by Census Region and

    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 Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013,Iowa"Dakota" ,"FullWest Virginia"18. Quantity

  4. Table A26. Components of Total Electricity Demand by Census Region, Census Di

    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 Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013,Iowa"Dakota" ,"FullWest Virginia"18.1.

  5. #include #include

    E-Print Network [OSTI]

    Campbell, Andrew T.

    process #12;#include #include pid_t pid = fork(); if (pid () failed */ } else if (pid == 0) { /* parent process */ } else { /* child process */ } #12;thread #12

  6. #include #include

    E-Print Network [OSTI]

    Poinsot, Laurent

    #include #include //Rappels : "getpid()" permet d'obtenir son propre pid // "getppid()" renvoie le pid du père d'un processus int main (void) { pid_t pid_fils; pid_fils = fork(); if(pid_fils==-1) { printf("Erreur de création du processus fils\

  7. "Table A25. Components of Total Electricity Demand by Census Region, Census Division, Industry"

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocksa. AppliancesTotal" "(Data1.30. Total6.

  8. Demand Reduction

    Broader source: Energy.gov [DOE]

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

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

    E-Print Network [OSTI]

    Stadler, Michael

    2011-01-01T23:59:59.000Z

    Importance Total off- site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decrease

  10. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 2: Electricity Demand by Utility Planning Area Energy Policy Report. The forecast includes three full scenarios: a high energy demand case, a low

  11. How Can China Lighten Up? Urbanization, Industrialization and Energy Demand Scenarios

    E-Print Network [OSTI]

    Aden, Nathaniel T.

    2010-01-01T23:59:59.000Z

    on the forecast of total energy demand. Based on this, weIndustrialization and Energy Demand Scenarios Nathaniel T.adjustment spurred energy demand for construction of new

  12. Progress toward Producing Demand-Response-Ready Appliances

    SciTech Connect (OSTI)

    Hammerstrom, Donald J.; Sastry, Chellury

    2009-12-01T23:59:59.000Z

    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.

  13. 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

  14. 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

  15. Turkey's energy demand and supply

    SciTech Connect (OSTI)

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

    2009-07-01T23:59:59.000Z

    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.

  16. Demand Response Programs, 6. edition

    SciTech Connect (OSTI)

    NONE

    2007-10-15T23:59:59.000Z

    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. Overview of Demand Side Response

    Broader source: Energy.gov [DOE]

    Presentationgiven at the Federal Utility Partnership Working Group (FUPWG) Fall 2008 meetingdiscusses the utility PJM's demand side response (DSR) capabilities, including emergency and economic responses.

  18. Electrical Demand Control

    E-Print Network [OSTI]

    Eppelheimer, D. M.

    1984-01-01T23:59:59.000Z

    to the reservoir. Util i ties have iiting for a number of years. d a rebate for reducing their When the utility needs to shed is sent to turn off one or mnre mer's electric water heater or equipment. wges have enticed more and more same strategies... an increased need for demand 1 imiting. As building zone size is reduced, total instal led tonnage increases due to inversfty. Each compressor is cycled by a space thermostat. There is no control system to limit the number of compressors running at any...

  19. Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection

    E-Print Network [OSTI]

    Olsen, Daniel J.

    2014-01-01T23:59:59.000Z

    Demand (MW) 4000 Residential Hourly Average Load Profilesdaily profile showing average hourly demand. Residential:Total Demand (MW) 8 8 Residential Daily Averaqe Load Profile

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

    SciTech Connect (OSTI)

    Aden, Nathaniel; Fridley, David; Zheng, Nina

    2009-07-01T23:59:59.000Z

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

  1. PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022

    E-Print Network [OSTI]

    PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA for electric vehicles. #12;ii #12;iii ABSTRACT The Preliminary California Energy Demand Forecast 2012 includes three full scenarios: a high energy demand case, a low energy demand case, and a mid energy demand

  2. Demand Dispatch-Intelligent

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

    CA Control Areas CO 2 Carbon Dioxide CHP Combined Heat and Power CPP Critical Peak Pricing DG Distributed Generation DOE Department of Energy DR Demand Response DRCC Demand...

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    Addressing Energy Demand through Demand Response:both the avoided energy costs (and demand charges) as wellCoordination of Energy Efficiency and Demand Response,

  5. Using Utility Load Data to Estimate Demand for Space Cooling and Potential for Shiftable Loads

    SciTech Connect (OSTI)

    Denholm, P.; Ong, S.; Booten, C.

    2012-05-01T23:59:59.000Z

    This paper describes a simple method to estimate hourly cooling demand from historical utility load data. It compares total hourly demand to demand on cool days and compares these estimates of total cooling demand to previous regional and national estimates. Load profiles generated from this method may be used to estimate the potential for aggregated demand response or load shifting via cold storage.

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

    SciTech Connect (OSTI)

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

    2008-11-19T23:59:59.000Z

    The Department of Energys (DOEs) 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.

  7. 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

  8. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01T23:59:59.000Z

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

  9. 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

    2008-04-21T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Komiyama, Ryoichi

    2008-01-01T23:59:59.000Z

    Total Energy Source Demand Coal, Oil, Gas, Heat, ElectricityEnergy Source Demand per Household Coal, Oil, Gas, Heat,ton of oil equivalent Considerable increases in demand for

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    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

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    Data for Automated Demand Response in Commercial Buildings,Demand Response Infrastructure for Commercial Buildings",demand response and energy efficiency functions into the design of buildings,

  13. Demand response enabling technology development

    E-Print Network [OSTI]

    Arens, Edward; Auslander, David; Huizenga, Charlie

    2008-01-01T23:59:59.000Z

    behavior in developing a demand response future. Phase_II_Demand Response Enabling Technology Development Phase IIYi Yuan The goal of the Demand Response Enabling Technology

  14. Demand Response Spinning Reserve Demonstration

    E-Print Network [OSTI]

    2007-01-01T23:59:59.000Z

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

  15. Demand response enabling technology development

    E-Print Network [OSTI]

    2006-01-01T23:59:59.000Z

    Demand Response Enabling Technology Development Phase IEfficiency and Demand Response Programs for 2005/2006,Application to Demand Response Energy Pricing SenSys 2003,

  16. Automated Demand Response and Commissioning

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    and Demand Response in Commercial Buildings, Lawrencesystems. Demand Response using HVAC in Commercial BuildingsDemand Response Test in Large Facilities13 National Conference on Building

  17. 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

    2014-07-01T23:59:59.000Z

    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.

  18. Energy Demand Staff Scientist

    E-Print Network [OSTI]

    Eisen, Michael

    Energy Demand in China Lynn Price Staff Scientist February 2, 2010 #12;Founded in 1988 Focused,000 2,000 3,000 4,000 5,000 6,000 7,000 2007 USChina #12;Overview:Overview: Key Energy Demand DriversKey Energy Demand Drivers · 290 million new urban residents 1990-2007 · 375 million new urban residents 2007

  19. Industrial Demand Module

    Gasoline and Diesel Fuel Update (EIA)

    Boiler, Steam, and Cogeneration (BSC) Component. The BSC Component satisfies the steam demand from the PA and BLD Components. In some industries, the PA Component produces...

  20. Demand Response In California

    Broader source: Energy.gov [DOE]

    Presentation covers the demand response in California and is given at the FUPWG 2006 Fall meeting, held on November 1-2, 2006 in San Francisco, California.

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

    SciTech Connect (OSTI)

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

    2009-02-01T23:59:59.000Z

    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.

  2. Controlling electric power demand

    SciTech Connect (OSTI)

    Eikenberry, J.

    1984-11-15T23:59:59.000Z

    Traditionally, demand control has not been viewed as an energy conservation measure, its intent being to reduce the demand peak to lower the electric bill demand charge by deferring the use of a block of power to another demand interval. Any energy savings were essentially incidental and unintentional, resulting from curtailment of loads that could not be assumed at another time. This article considers a microprocessor-based multiplexed system linked to a minicomputer to control electric power demand in a winery. In addition to delivering an annual return on investment of 55 percent in electric bill savings, the system provides a bonus in the form of alarm and monitoring capability for critical processes.

  3. Issues in International Energy Consumption Analysis: Chinese Transportation Fuel Demand

    Reports and Publications (EIA)

    2014-01-01T23:59:59.000Z

    Since the 1990s, China has experienced tremendous growth in its transportation sector. By the end of 2010, China's road infrastructure had emerged as the second-largest transportation system in the world after the United States. Passenger vehicle sales are dramatically increasing from a little more than half a million in 2000, to 3.7 million in 2005, to 13.8 million in 2010. This represents a twenty-fold increase from 2000 to 2010. The unprecedented motorization development in China led to a significant increase in oil demand, which requires China to import progressively more petroleum from other countries, with its share of petroleum imports exceeding 50% of total petroleum demand since 2009. In response to growing oil import dependency, the Chinese government is adopting a broad range of policies, including promotion of fuel-efficient vehicles, fuel conservation, increasing investments in oil resources around the world, and many others.

  4. [Article 1 of 7: Motivates and Includes the Consumer

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

    and include the consumer exist. Some examples include advanced two-way metering (AMI), demand response (DR), and distributed energy resources (DER). A common misconception is...

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

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01T23:59:59.000Z

    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.

  7. Uranium 2009 resources, production and demand

    E-Print Network [OSTI]

    Organisation for Economic Cooperation and Development. Paris

    2010-01-01T23:59:59.000Z

    With several countries currently building nuclear power plants and planning the construction of more to meet long-term increases in electricity demand, uranium resources, production and demand remain topics of notable interest. In response to the projected growth in demand for uranium and declining inventories, the uranium industry the first critical link in the fuel supply chain for nuclear reactors is boosting production and developing plans for further increases in the near future. Strong market conditions will, however, be necessary to trigger the investments required to meet projected demand. The "Red Book", jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency, is a recognised world reference on uranium. It is based on information compiled in 40 countries, including those that are major producers and consumers of uranium. This 23rd edition provides a comprehensive review of world uranium supply and demand as of 1 January 2009, as well as data on global ur...

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

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01T23:59:59.000Z

    An Exploration of Australian Petrol Demand: Unobserv- ableRelative Prices: Simulating Petrol Con- sumption Behavior.habit stock variable in a petrol demand regression, they

  9. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01T23:59:59.000Z

    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

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

    E-Print Network [OSTI]

    Low, Steven H.

    Optimal Demand Response Based on Utility Maximization in Power Networks Na Li, Lijun Chen different appliances including PHEVs and batteries and propose a demand response approach based on utility. The utility company can thus use dynamic pricing to coordinate demand responses to the benefit of the overall

  11. Response to changes in demand/supply

    E-Print Network [OSTI]

    , distribution channels, differentiation of quality, price, specification, etc., of the products. Primary wood with the mill consuming 450 000 m3 , amounting to 30% of total plywood log demand in 1995. The composites board;112 distribution channels, differentiation of quality, price, specification, etc., of the products. Primary wood

  12. 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

  13. FERC sees huge potential for demand response

    SciTech Connect (OSTI)

    NONE

    2010-04-15T23:59:59.000Z

    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. Total Synthesis of (?)-Himandrine

    E-Print Network [OSTI]

    Movassaghi, Mohammad

    We describe the first total synthesis of (?)-himandrine, a member of the class II galbulimima alkaloids. Noteworthy features of this chemistry include a diastereoselective Diels?Alder reaction in the rapid synthesis of the ...

  15. Percentage of Total Natural Gas Commercial Deliveries included in Prices

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site. IfProved(MillionPrice (Percent) YearPricePrice

  16. Percentage of Total Natural Gas Industrial Deliveries included in Prices

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site. IfProved(MillionPrice (Percent) YearPricePricePipeline and

  17. Percentage of Total Natural Gas Industrial Deliveries included in Prices

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site. IfProved(MillionPrice (Percent) YearPricePricePipeline

  18. Percentage of Total Natural Gas Residential Deliveries included in Prices

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site. IfProved(MillionPrice (Percent) YearPricePricePipeline97.4

  19. Percentage of Total Natural Gas Residential Deliveries included in Prices

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site. IfProved(MillionPrice (Percent)

  20. Percentage of Total Natural Gas Commercial Deliveries included in Prices

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14 Jan-15LiquidBGOperablePERCENTthe PricethetheCity

  1. Stocks of Total Crude Oil and Petroleum Products (Including SPR)

    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 Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConference |6: "Regulating31,947,078

  2. Travel Demand Modeling

    SciTech Connect (OSTI)

    Southworth, Frank [ORNL; Garrow, Dr. Laurie [Georgia Institute of Technology

    2011-01-01T23:59:59.000Z

    This chapter describes the principal types of both passenger and freight demand models in use today, providing a brief history of model development supported by references to a number of popular texts on the subject, and directing the reader to papers covering some of the more recent technical developments in the area. Over the past half century a variety of methods have been used to estimate and forecast travel demands, drawing concepts from economic/utility maximization theory, transportation system optimization and spatial interaction theory, using and often combining solution techniques as varied as Box-Jenkins methods, non-linear multivariate regression, non-linear mathematical programming, and agent-based microsimulation.

  3. CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Manager Kae Lewis Acting Manager Demand Analysis Office Valerie T. Hall Deputy Director Energy Efficiency Demand Forecast report is the product of the efforts of many current and former California Energy

  4. Autonomous Demand Side Management Based on Game-Theoretic Energy Consumption

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    Autonomous Demand Side Management Based on Game-Theoretic Energy Consumption Scheduling distributed demand side energy management strategy requires each user to simply apply its best response-average ratio of the total energy demand, the total energy costs, as well as each user's individual daily

  5. Ethanol Demand in United States Gasoline Production

    SciTech Connect (OSTI)

    Hadder, G.R.

    1998-11-24T23:59:59.000Z

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

  6. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400. Hall Deputy Director Energy Efficiency and Demand Analysis Division Scott W. Matthews Acting Executive

  7. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    electricity demand forecast means that the region's electricity needs would grow by 5,343 average megawattsDemand 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

  8. Climate policy implications for agricultural water demand

    SciTech Connect (OSTI)

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

    2013-03-28T23:59:59.000Z

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

  9. 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power Administration wouldDECOMPOSITIONPortal DecisionRichlandDelegations,Demand

  10. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    SciTech Connect (OSTI)

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

    2008-11-19T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    BEST PRACTICES AND RESULTS OF DR IMPLEMENTATION . 31 Encouraging End-User Participation: The Role of Incentives 16 Demand Response

  12. TOTAL M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total Spring 2010

    E-Print Network [OSTI]

    Hayes, Jane E.

    202 51 *total new freshmen 684: 636 Lexington campus, 48 Paducah campus MS Total 216 12 5 17 2 0 2 40 248 247 648 45 210 14 *total new freshmen 647: 595 Lexington campus, 52 Paducah campus MS Total 192 14

  13. CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY FORECAST Volume 1: Statewide Electricity Demand, End-User Natural Gas Demand, and Energy Efficiency The California Energy Demand 2014-2024 Preliminary Forecast, Volume 1: Statewide Electricity Demand

  14. Demand Side Bidding. Final Report

    SciTech Connect (OSTI)

    Spahn, Andrew

    2003-12-31T23:59:59.000Z

    This document sets forth the final report for a financial assistance award for the National Association of Regulatory Utility Commissioners (NARUC) to enhance coordination between the building operators and power system operators in terms of demand-side responses to Location Based Marginal Pricing (LBMP). Potential benefits of this project include improved power system reliability, enhanced environmental quality, mitigation of high locational prices within congested areas, and the reduction of market barriers for demand-side market participants. NARUC, led by its Committee on Energy Resources and the Environment (ERE), actively works to promote the development and use of energy efficiency and clean distributive energy policies within the framework of a dynamic regulatory environment. Electric industry restructuring, energy shortages in California, and energy market transformation intensifies the need for reliable information and strategies regarding electric reliability policy and practice. NARUC promotes clean distributive generation and increased energy efficiency in the context of the energy sector restructuring process. NARUC, through ERE's Subcommittee on Energy Efficiency, strives to improve energy efficiency by creating working markets. Market transformation seeks opportunities where small amounts of investment can create sustainable markets for more efficient products, services, and design practices.

  15. Demand Response Valuation Frameworks Paper

    SciTech Connect (OSTI)

    Heffner, Grayson

    2009-02-01T23:59:59.000Z

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

  16. Demand Response: Load Management Programs

    E-Print Network [OSTI]

    Simon, J.

    2012-01-01T23:59:59.000Z

    CenterPoint Load 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...

  17. Demand Response: Load Management Programs

    E-Print Network [OSTI]

    Simon, J.

    2012-01-01T23:59:59.000Z

    CenterPoint Load 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...

  18. 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

  19. DEMAND CONTROLLED VENTILATION AND CLASSROOM VENTILATION

    SciTech Connect (OSTI)

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

    2014-01-06T23:59:59.000Z

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

  20. Tracking Progress Last updated 5/7/2014 Statewide Energy Demand 1

    E-Print Network [OSTI]

    Tracking Progress Last updated 5/7/2014 Statewide Energy Demand 1 Statewide Energy Demand Energy Commission's energy demand forecast includes multiple scenarios, the Energy Commission worked together1 to agree upon a single managed demand forecast that incorporates all energy efficiency

  1. Open Automated Demand Response for Small Commerical Buildings

    SciTech Connect (OSTI)

    Dudley, June Han; Piette, Mary Ann; Koch, Ed; Hennage, Dan

    2009-05-01T23:59:59.000Z

    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.

  2. Electrical Demand Management

    E-Print Network [OSTI]

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

    1983-01-01T23:59:59.000Z

    bination of a 2200 ton, the 1200 ton and the 800 ton units or by two 2200 ton units. We sought to di sp 1ace the 1200 ton or part of a 2200 ton unit with two steam turbi ne chill ers duri ng peak hours at a total reduced cost for supplying all building...

  3. 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

    2011-04-29T23:59:59.000Z

    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.

  4. Uranium 2011 resources, production and demand

    E-Print Network [OSTI]

    Organisation for Economic Cooperation and Development. Paris

    2012-01-01T23:59:59.000Z

    In the wake of the Fukushima Daiichi nuclear power plant accident, questions are being raised about the future of the uranium market, including as regards the number of reactors expected to be built in the coming years, the amount of uranium required to meet forward demand, the adequacy of identified uranium resources to meet that demand and the ability of the sector to meet reactor requirements in a challenging investment climate. This 24th edition of the Red Book, a recognised world reference on uranium jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency, provides analyses and information from 42 producing and consuming countries in order to address these and other questions. It offers a comprehensive review of world uranium supply and demand as well as data on global uranium exploration, resources, production and reactor-related requirements. It also provides substantive new information on established uranium production centres around the world and in countri...

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

    E-Print Network [OSTI]

    Aden, Nathaniel

    2010-01-01T23:59:59.000Z

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

  6. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    gas demands are forecast for the four natural gas utilitythe 2006-2016 Forecast. Commercial natural gas demand isforecasts and demand scenarios. Electricity planning area Natural gas

  7. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

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

  8. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

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

  9. Strategies for Demand Response in Commercial Buildings

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

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

  10. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01T23:59:59.000Z

    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

  11. Home Network Technologies and Automating Demand Response

    E-Print Network [OSTI]

    McParland, Charles

    2010-01-01T23:59:59.000Z

    and Automating Demand Response Charles McParland, Lawrenceand Automating Demand Response Charles McParland, LBNLCommercial and Residential Demand Response Overview of the

  12. Barrier Immune Radio Communications for Demand Response

    E-Print Network [OSTI]

    Rubinstein, Francis

    2010-01-01T23:59:59.000Z

    of Fully Automated Demand Response in Large Facilities,Fully Automated Demand Response Tests in Large Facilities.for Automated Demand Response. Technical Document to

  13. Wireless Demand Response Controls for HVAC Systems

    E-Print Network [OSTI]

    Federspiel, Clifford

    2010-01-01T23:59:59.000Z

    Strategies Linking Demand Response and Energy Efficiency,Fully Automated Demand Response Tests in Large Facilities,technical support from the Demand Response Research Center (

  14. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    District Small Business Summer Solutions: Energy and DemandSummer Solutions: Energy and Demand Impacts Monthly Energy> B-2 Coordination of Energy Efficiency and Demand Response

  15. Coupling Renewable Energy Supply with Deferrable Demand

    E-Print Network [OSTI]

    Papavasiliou, Anthony

    2011-01-01T23:59:59.000Z

    World: Renewable Energy and Demand Response Proliferation intogether the renewable energy and demand response communityimpacts of renewable energy and demand response integration

  16. DEMAND CONTROLLED VENTILATION AND CLASSROOM VENTILATION

    E-Print Network [OSTI]

    Fisk, William J.

    2014-01-01T23:59:59.000Z

    of energy and environmental benefits of demand controlledindicate the energy and cost savings for demand controlled24) (California Energy Commission 2008), demand controlled

  17. Demand Controlled Ventilation and Classroom Ventilation

    E-Print Network [OSTI]

    Fisk, William J.

    2014-01-01T23:59:59.000Z

    ofenergyandenvironmentalbenefitsofdemandcontrolledindicatetheenergyandcostsavingsfor demandcontrolled24)(CaliforniaEnergy Commission2008),demandcontrolled

  18. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01T23:59:59.000Z

    integrating HECO and Hawaii Energy demand response relatedpotential. Energy efficiency and demand response efforts areBoth energy efficiency and demand response should

  19. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    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

    2007-01-01T23:59:59.000Z

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

  1. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01T23:59:59.000Z

    and best practices to guide HECO demand response developmentbest practices for DR renewable integration Technically demand responseof best practices. This is partially because demand response

  2. Strategies for Demand Response in Commercial Buildings

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    Strategies for Demand Response in Commercial Buildings DavidStrategies for Demand Response in Commercial Buildings Davidadjusted for demand response in commercial buildings. The

  3. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    Demand Response Systems National Conference on BuildingDemand Response Systems National Conference on BuildingDemand Response Systems National Conference on Building

  4. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    In terms of demand response capability, building operatorsautomated demand response and improve building energy andand demand response features directly into building design

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01T23:59:59.000Z

    DEMAND RESPONSE .7 Wholesale Marketuse at times of high wholesale market prices or when systemenergy expenditure. In wholesale markets, spot energy prices

  6. Demand Response and Energy Efficiency

    E-Print Network [OSTI]

    Demand Response & Energy Efficiency International Conference for Enhanced Building Operations ESL-IC-09-11-05 Proceedings of the Ninth International Conference for Enhanced Building Operations, Austin, Texas, November 17 - 19, 2009 2 ?Less than 5... for Enhanced Building Operations, Austin, Texas, November 17 - 19, 2009 5 What is Demand Response? ?The temporary reduction of electricity demanded from the grid by an end-user in response to capacity shortages, system reliability events, or high wholesale...

  7. Demand Response Technology Roadmap A

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

    workshop agendas, presentation materials, and transcripts. For the background to the Demand Response Technology Roadmap and to make use of individual roadmaps, the reader is...

  8. ELECTRICITY DEMAND FORECAST COMPARISON REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005.................................................................................................................................3 PACIFIC GAS & ELECTRIC PLANNING AREA ........................................................................................9 Commercial Sector

  9. Driving Demand | Department of Energy

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

    strategies, results achieved to date, and advice for other programs. Driving Demand for Home Energy Improvements. This guide, developed by the Lawrence Berkeley National...

  10. Demand Response Technology Roadmap M

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

    between May 2014 and February 2015. The Bonneville Power Administration (BPA) Demand Response Executive Sponsor Team decided upon the scope of the project in May. Two subsequent...

  11. LEED Demand Response Credit: A Plan for Research towards Implementation

    E-Print Network [OSTI]

    the need and methods for commercial building sector involvement in demand response (DR). We summarize, including architects, engineers, consultants, contractors, and building owners and managers. Finally, we in the US increased the focus on the need for flexible demand-side resources to address four major

  12. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    Energy Commission's final forecasts for 2012­2022 electricity consumption, peak, and natural gas demand Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand

  13. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    of 43% of total oil consumption. The residential sectorrepresenting 63% and oil consumption representing the rest.the diesel and fuel oil consumption are included, the total

  14. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01T23:59:59.000Z

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

  15. UBC STUDENT HOUSING DEMAND STUDY

    E-Print Network [OSTI]

    Ollivier-Gooch, Carl

    UBC STUDENT HOUSING DEMAND STUDY Presented by Nancy Knight and Andrew Parr FEBRUARY 5, 2010 #12;PURPOSE To determine the need/demand for future on- campus student housing To address requests from A survey of students, and analysis of housing markets, and preparation of a forecast The timeline

  16. Harnessing the power of demand

    SciTech Connect (OSTI)

    Sheffrin, Anjali; Yoshimura, Henry; LaPlante, David; Neenan, Bernard

    2008-03-15T23:59:59.000Z

    Demand response can provide a series of economic services to the market and also provide ''insurance value'' under low-likelihood, but high-impact circumstances in which grid reliablity is enhanced. Here is how ISOs and RTOs are fostering demand response within wholesale electricity markets. (author)

  17. ERCOT Demand Response Paul Wattles

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    changes or incentives.' (FERC) `Changes in electric use by demand-side resources from their normalERCOT Demand Response Paul Wattles Senior Analyst, Market Design & Development, ERCOT Whitacre thermostats -- Other DLC Possible triggers: Real-time prices, congestion management, 4CP response paid

  18. Automated Demand Response and Commissioning

    SciTech Connect (OSTI)

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

    2005-04-01T23:59:59.000Z

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

  19. Demand Response for Ancillary Services

    SciTech Connect (OSTI)

    Alkadi, Nasr E [ORNL; Starke, Michael R [ORNL

    2013-01-01T23:59:59.000Z

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

  20. Lead -- supply/demand outlook

    SciTech Connect (OSTI)

    Schnull, T. [Noranda, Inc., Toronto, Ontario (Canada)

    1999-03-01T23:59:59.000Z

    As Japan goes--so goes the world. That was the title of a recent lead article in The Economist that soberly discussed the potential of much more severe global economic problems occurring, if rapid and coordinated efforts were not made to stabilize the economic situation in Asia in general, and in Japan in particular. During the first 6 months of last year, commodity markets reacted violently to the spreading economic problems in Asia. More recent currency and financial problems in Russia have exacerbated an already unpleasant situation. One commodity after another--including oil, many of the agricultural commodities, and each of the base metals--have dropped sharply in price. Many are now trading at multiyear lows. Until there is an overall improvement in the outlook for these regions, sentiment will likely continue to be negative, and metals prices will remain under pressure. That being said, lead has maintained its value better than many other commodities during these difficult times, finding support in relatively strong fundamentals. The author takes a closer look at those supply and demand fundamentals, beginning with consumption.

  1. U.S. electric utility demand-side management 1993

    SciTech Connect (OSTI)

    NONE

    1995-07-01T23:59:59.000Z

    This report presents comprehensive information on electric power industry demand-side management activities in the United States at the national, regional, and utility levels. Data is included for energy savings, peakload reductions, and costs.

  2. Electricity Distribution Networks: Investment and Regulation, and Uncertain Demand

    E-Print Network [OSTI]

    Jamasb, Tooraj; Marantes, Cristiano

    2011-01-31T23:59:59.000Z

    " and describes a network investment assessment model developed as a tool to identify and assess the investment requirements of distribution networks. A broadening of the scope of network investments to include demand-related measures that can reduce the need...

  3. Emerging Technologies for Industrial Demand-Side Management

    E-Print Network [OSTI]

    Neely, J. E.; Kasprowicz, L. M.

    Demand-side management (DSM) is a set of actions taken by an electric utility to influence the electricity usage by a customer. Typical DSM activities include rebates for higher efficiency appliances and discounted electric rates for electric...

  4. Factors that will influence oil and gas supply and demand in the 21st century

    SciTech Connect (OSTI)

    Holditch, S.A.; Chianelli, R.R. [Texas A& amp; M University, College Station, TX (United States)

    2008-04-15T23:59:59.000Z

    A recent report published by the National Petroleum Council (NPC) in the United States predicted a 50-60% growth in total global demand for energy by 2030. Because oil, gas, and coal will continue to be the primary energy sources during this time, the energy industry will have to continue increasing the supply of these fuels to meet this increasing demand. Achieving this goal will require the exploitation of both conventional and unconventional reservoirs of oil and gas in (including coalbed methane) an environmentally acceptable manner. Such efforts will, in turn, require advancements in materials science, particularly in the development of materials that can withstand high-pressure, high-temperature, and high-stress conditions.

  5. Automated Demand Response and Commissioning

    E-Print Network [OSTI]

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

    2005-01-01T23:59:59.000Z

    Conference on Building Commissioning: May 4-6, 2005 Motegi,National Conference on Building Commissioning: May 4-6, 2005Demand Response and Commissioning Mary Ann Piette, David S.

  6. Marketing Demand-Side Management

    E-Print Network [OSTI]

    O'Neill, M. L.

    1988-01-01T23:59:59.000Z

    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...

  7. Community Water Demand in Texas

    E-Print Network [OSTI]

    Griffin, Ronald C.; Chang, Chan

    Solutions to Texas water policy and planning problems will be easier to identify once the impact of price upon community water demand is better understood. Several important questions cannot be addressed in the absence of such information...

  8. Demand response enabling technology development

    E-Print Network [OSTI]

    2006-01-01T23:59:59.000Z

    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.

  9. Internship Contract (Includes Practicum)

    E-Print Network [OSTI]

    Thaxton, Christopher S.

    Internship Contract (Includes Practicum) Student's name-mail: _________________________________________ Internship Agency Contact Agency Name: ____________________________________ Address-mail: __________________________________________ Location of Internship, if different from Agency: ________________________________________________ Copies

  10. 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.

    2007-05-01T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Mares, K.C.

    2010-01-01T23:59:59.000Z

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

  13. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand, EndUser Natural Gas Demand, and Energy Efficiency SEPTEMBER 2013 CEC2002013004SDV1REV CALIFORNIA The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 1: Statewide Electricity Demand and Methods

  14. Pump apparatus including deconsolidator

    DOE Patents [OSTI]

    Sonwane, Chandrashekhar; Saunders, Timothy; Fitzsimmons, Mark Andrew

    2014-10-07T23:59:59.000Z

    A pump apparatus includes a particulate pump that defines a passage that extends from an inlet to an outlet. A duct is in flow communication with the outlet. The duct includes a deconsolidator configured to fragment particle agglomerates received from the passage.

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

    SciTech Connect (OSTI)

    McKane, Aimee; Rhyne, Ivin; Piette, Mary Ann; Thompson, Lisa; Lekov, Alex

    2008-08-01T23:59:59.000Z

    In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This 'electricity value chain' defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to 'demo' potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives. In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies of refrigerated warehouses and wastewater treatment facilities are used to illustrate OpenADR load reduction potential. Typical shed and shift strategies include: turning off or operating compressors, aerator blowers and pumps at reduced capacity, increasing temperature set-points or pre-cooling cold storage areas and over-oxygenating stored wastewater prior to a DR event. This study concludes that understanding industrial end-use processes and control capabilities is a key to support reduced service during DR events and these capabilities, if DR enabled, hold significant promise in reducing the electricity demand of the industrial sector during utility peak periods.

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

    SciTech Connect (OSTI)

    McKane, Aimee; Rhyne, Ivin; Lekov, Alex; Thompson, Lisa; Piette, MaryAnn

    2009-08-01T23:59:59.000Z

    In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This ?electricity value chain? defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to"demo" potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives.1 In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies of refrigerated warehouses and wastewater treatment facilities are used to illustrate OpenADR load reduction potential. Typical shed and shift strategies include: turning off or operating compressors, aerator blowers and pumps at reduced capacity, increasing temperature set-points or pre-cooling cold storage areas and over-oxygenating stored wastewater prior to a DR event. This study concludes that understanding industrial end-use processes and control capabilities is a key to support reduced service during DR events and these capabilities, if DR enabled, hold significant promise in reducing the electricity demand of the industrial sector during utility peak periods.

  17. Living Expenses (includes approximately

    E-Print Network [OSTI]

    Maroncelli, Mark

    & engineering programs All other programs Graduate: MBA/INFSY at Erie & Harrisburg (12 credits) Business Guarantee 3 (Does not include Dependents Costs4 ) Altoona, Berks, Erie, and Harrisburg 12-Month Estimated

  18. Demand response-enabled residential thermostat controls.

    E-Print Network [OSTI]

    Chen, Xue; Jang, Jaehwi; Auslander, David M.; Peffer, Therese; Arens, Edward A

    2008-01-01T23:59:59.000Z

    human dimension of demand response technology from a caseArens, E. , et al. 2008. Demand Response Enabling TechnologyArens, E. , et al. 2006. Demand Response Enabling Technology

  19. Demand Response as a System Reliability Resource

    E-Print Network [OSTI]

    Joseph, Eto

    2014-01-01T23:59:59.000Z

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

  20. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    the California Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand

  1. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak, and natural Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility

  2. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    California Energy Demand Scenario Projections to 2050 RyanCEC (2003a) California energy demand 2003-2013 forecast.CEC (2005a) California energy demand 2006-2016: Staff energy

  3. National Action Plan on Demand Response

    Broader source: Energy.gov [DOE]

    Presentationgiven at the Federal Utility Partnership Working Group (FUPWG) Fall 2008 meetingdiscusses the National Assessment of Demand Response study, the National Action Plan for Demand Response, and demand response as related to the energy outlook.

  4. Abstract --Due to the potentially large number of Distributed Energy Resources (DERs) demand response, distributed

    E-Print Network [OSTI]

    Zhang, Wei

    to accurately estimate the transients caused by demand response is especially important to analyze the stability of the system under different demand response strategies, where dynamics on time scales of seconds to minutes demand response. The aggregated model efficiently includes statistical information of the population

  5. ECEEE 2005 SUMMER STUDY WHAT WORKS & WHO DELIVERS? 183 Local energy efficiency and demand-side

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    ECEEE 2005 SUMMER STUDY ­ WHAT WORKS & WHO DELIVERS? 183 1,202 Local energy efficiency and demand be the basis for local energy policies and energy efficiency/demand-side management activities1, have been) activities in 1. DSM: Demand-Side Management; EE: energy efficiency (here, does not include renewable

  6. Supply Chain Networks, Electronic Commerce, and Supply Side and Demand Side Risk

    E-Print Network [OSTI]

    Nagurney, Anna

    Supply Chain Networks, Electronic Commerce, and Supply Side and Demand Side Risk Anna Nagurney as well as demand side risk are included in the formulation. The model consists of three tiers of decision chain network equilibrium model with electronic com- merce and with supply side and demand side risk

  7. Electricity Markets Meet the Home through Demand Response Lazaros Gkatzikis

    E-Print Network [OSTI]

    ) programs motivate home users through dynamic pricing to shift electricity consumption from peak demand incentives to the users, usually in the form of dynamic pricing, to reduce their electricity consumption. For example, the residential sector in UK accounts for 31% of the total electricity consumption

  8. Home Network Technologies and Automating Demand Response

    SciTech Connect (OSTI)

    McParland, Charles

    2009-12-01T23:59:59.000Z

    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.

  9. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    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

  10. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    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).

  11. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    al: Installation and Commissioning Automated Demand ResponseConference on Building Commissioning: April 22 24, 2008al: Installation and Commissioning Automated Demand Response

  12. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

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

  13. Demand Controlled Ventilation and Classroom Ventilation

    E-Print Network [OSTI]

    Fisk, William J.

    2014-01-01T23:59:59.000Z

    use of demand control ventilation systems in general officedemandcontrolled ventilationsystems,DennisDiBartolomeothedemandcontrolledventilationsystemincreasedtherate

  14. Supply chain planning decisions under demand uncertainty

    E-Print Network [OSTI]

    Huang, Yanfeng Anna

    2008-01-01T23:59:59.000Z

    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 ...

  15. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    sector, the demand response potential of California buildinga demand response event prohibit a buildings participationdemand response strategies in California buildings are

  16. Sandia National Laboratories: demand response inverter

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

    demand response inverter ECIS-Princeton Power Systems, Inc.: Demand Response Inverter On March 19, 2013, in DETL, Distribution Grid Integration, Energy, Energy Surety, Facilities,...

  17. The Demand Reduction Potential of Smart Appliances in U.S. Homes

    SciTech Connect (OSTI)

    Makhmalbaf, Atefe; Srivastava, Viraj; Parker, Graham B.

    2013-08-14T23:59:59.000Z

    The widespread deployment of demand respond (DR) enabled home appliances is expected to have significant reduction in the demand of electricity during peak hours. The work documented in this paper focuses on estimating the energy shift resulting from the installation of DR enabled smart appliances in the U.S. This estimation is based on analyzing the market for smart appliances and calculating the total energy demand that can potentially be shifted by DR control in appliances. Appliance operation is examined by considering their sub components individually to identify their energy consumptions and savings resulting from interrupting and shifting their load, e.g., by delaying the refrigerator defrost cycle. In addition to major residential appliances, residential pool pumps are also included in this study given their energy consumption profiles that make them favorable for DR applications. In the market analysis study documented in this paper, the U.S. Energy Information Administration's (EIA) Residential Energy Consumption Survey (RECS) and National Association of Home Builders (NAHB) databases are used to examine the expected life of an appliance, the number of appliances installed in homes constructed in 10 year intervals after 1940 and home owner income. Conclusions about the effectiveness of the smart appliances in reducing electrical demand have been drawn and a ranking of appliances in terms of their contribution to load shift is presented. E.g., it was concluded that DR enabled water heaters result in the maximum load shift; whereas, dishwashers have the highest user elasticity and hence the highest potential for load shifting through DR. This work is part of a larger effort to bring novel home energy management concepts and technologies to reduce energy consumption, reduce peak electricity demand, integrate renewables and storage technology, and change homeowner behavior to manage and consume less energy and potentially save consumer energy costs.

  18. International Oil Supplies and Demands

    SciTech Connect (OSTI)

    Not Available

    1992-04-01T23:59:59.000Z

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

  19. International Oil Supplies and Demands

    SciTech Connect (OSTI)

    Not Available

    1991-09-01T23:59:59.000Z

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

  20. US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier

    E-Print Network [OSTI]

    US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach Massimo www.cepe.ethz.ch #12;US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach Page 1 of 25 US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier

  1. Gasoline price volatility and the elasticity of demand for gasoline1 C.-Y. Cynthia Lina

    E-Print Network [OSTI]

    Lin, C.-Y. Cynthia

    externalities including local air pollution, global climate change, accidents, congestion, and dependence at reducing demand for gasoline or reducing pollution from automobiles. The latter could be addressed

  2. Demand Response Programs for Oregon

    E-Print Network [OSTI]

    wholesale prices and looming shortages in Western power markets in 2000-01, Portland General Electric programs for large customers remain, though they are not active at current wholesale prices. Other programs demand response for the wholesale market -- by passing through real-time prices for usage above a set

  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. Water demand management in Kuwait

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    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 ...

  5. obesity demands more than just

    E-Print Network [OSTI]

    Qian, Ning

    #12;The World That Makes Us Fat ***** ***** ***** Overcoming obesity demands more than just. By Melinda Wenner Moyer Illustrations by A. Richard Allen 27 #12;ON ONE LEVEL, of course, obesity has a sim to pollutants. Their research suggests that to solve the problem of obesity--and, ultimately, to prevent it from

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

    E-Print Network [OSTI]

    Benenson, P.

    2010-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01T23:59:59.000Z

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

  8. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    E-Print Network [OSTI]

    Thompson, Lisa

    2008-01-01T23:59:59.000Z

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

  9. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

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

  10. 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

  11. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand, EndUser Natural Gas Demand, and Energy Efficiency DECEMBER 2013 CEC2002013004SFV1 CALIFORNIA and expertise of numerous California Energy Commission staff members in the Demand Analysis Office. In addition

  12. Demand Side Management in Rangan Banerjee

    E-Print Network [OSTI]

    Banerjee, Rangan

    Demand Side Management in Industry Rangan Banerjee Talk at Baroda in Birla Corporate Seminar August 31,2007 #12;Demand Side Management Indian utilities energy shortage and peak power shortage. Supply for Options Demand Side Management (DSM) & Load Management #12;DSM Concept Demand Side Management (DSM) - co

  13. Falling MTBE demand bursts the methanol bubble

    SciTech Connect (OSTI)

    Wiesmann, G.; Cornitius, T.

    1995-03-01T23:59:59.000Z

    Methanol spot markets in Europe and the US have been hit hard by weakening demand from methyl tert-butyl ether (MTBE) producers. In Europe, spot prices for domestic T2 product have dropped to DM620-DM630/m.t. fob from early-January prices above DM800/m.t. and US spot prices have slipped to $1.05/gal fob from $1.35/gal. While chemical applications for methanol show sustained demand, sharp methanol hikes during 1994 have priced MTBE out of the gasoline-additive market. {open_quotes}We`ve learned an important lesson. We killed [MTBE] applications in the rest of the world,{close_quotes} says one European methanol producer. Even with methanol currently at DM620/m.t., another manufacturer points out, MTBE production costs still total $300/m.t., $30/m.t. more than MTBE spot prices. Since late 1994, Europe`s 3.3-million m.t./year MTBE production has been cut back 30%.

  14. Analysis of Open Automated Demand Response Deployments in California and Guidelines to Transition to Industry Standards

    SciTech Connect (OSTI)

    Ghatikar, Girish; Riess, David; Piette, Mary Ann

    2014-01-02T23:59:59.000Z

    This report reviews the Open Automated Demand Response (OpenADR) deployments within the territories serviced by California?s investor-owned utilities (IOUs) and the transition from the OpenADR 1.0 specification to the formal standard?OpenADR 2.0. As demand response service providers and customers start adopting OpenADR 2.0, it is necessary to ensure that the existing Automated Demand Response (AutoDR) infrastructure investment continues to be useful and takes advantage of the formal standard and its many benefits. This study focused on OpenADR deployments and systems used by the California IOUs and included a summary of the OpenADR deployment from the U.S. Department of Energy-funded demonstration conducted by the Sacramento Municipal Utility District (SMUD). Lawrence Berkeley National Laboratory collected and analyzed data about OpenADR 1.0 deployments, categorized architectures, developed a data model mapping to understand the technical compatibility of each version, and compared the capabilities and features of the two specifications. The findings, for the first time, provided evidence of the total enabled load shed and average first cost for system enablement in the IOU and SMUD service territories. The OpenADR 2.0a profile specification semantically supports AutoDR system architectures and data propagation with a testing and certification program that promotes interoperability, scaled deployments by multiple vendors, and provides additional features that support future services.

  15. FISHERY WASTE EFFLUENTS: A METHOD TO DETERMINE RELATIONSHIPS BETWEEN CHEMICAL OXYGEN DEMAND AND RESIDUE

    E-Print Network [OSTI]

    FISHERY WASTE EFFLUENTS: A METHOD TO DETERMINE RELATIONSHIPS BETWEEN CHEMICAL OXYGEN DEMAND effluents, especially for total suspended and settleable solids, and oil and grease. The relationship between chemical oxygen demand and residue was determined on a limited number of samples from four types

  16. MODELING THE DEMAND FOR E85 IN THE UNITED STATES

    SciTech Connect (OSTI)

    Liu, Changzheng [ORNL; Greene, David L [ORNL

    2013-10-01T23:59:59.000Z

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

  17. Detailed Modeling and Response of Demand Response Enabled Appliances

    SciTech Connect (OSTI)

    Vyakaranam, Bharat; Fuller, Jason C.

    2014-04-14T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Boutaba, Raouf

    Near Optimal Demand-Side Energy Management Under Real-time Demand-Response Pricing Jin Xiao, Jae--In this paper, we present demand-side energy manage- ment under real-time demand-response pricing as a task, demand-response, energy management I. INTRODUCTION The growing awareness of global climate change has

  19. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade EnergyTennesseeYear Jan Next MECS will be fielded in 2015 Table 8.4337

  20. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade EnergyTennesseeYear Jan Next MECS will be fielded in 2015 Table 8.4337

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

    SciTech Connect (OSTI)

    Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

    2014-01-01T23:59:59.000Z

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

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    in Demand Response for Wholesale Ancillary Services Silain Demand Response for Wholesale Ancillary Services Silasuccessfully in the wholesale non- spinning ancillary

  3. Physically-based demand modeling

    E-Print Network [OSTI]

    Calloway, Terry Marshall

    1980-01-01T23:59:59.000Z

    Transactions on Automatic Control, vol. AC-19, December 1974, pp. 887-893. L3] |4] LS] [6] [7] LB] C. W. Brice and S. K. Jones, MPhysically-Based Demand Modeling, d EC-77-5-01-5057, RF 3673, Electric Power Institute, Texas A&M University, October 1978.... C. W. Br ice and 5, K, Jones, MStochastically-Based Physical Load Models Topical Report, " EC-77-5-01-5057, RF 3673, Electric Power Institute, Texas A&M University, May 1979. S. K. Jones and C. W. Brice, "Point Process Models for Power System...

  4. Optimal Demand Response with Energy Storage Management

    E-Print Network [OSTI]

    Huang, Longbo; Ramchandran, Kannan

    2012-01-01T23:59:59.000Z

    In this paper, we consider the problem of optimal demand response and energy storage management for a power consuming entity. The entity's objective is to find an optimal control policy for deciding how much load to consume, how much power to purchase from/sell to the power grid, and how to use the finite capacity energy storage device and renewable energy, to minimize his average cost, being the disutility due to load- shedding and cost for purchasing power. Due to the coupling effect of the finite size energy storage, such problems are challenging and are typically tackled using dynamic programming, which is often complex in computation and requires substantial statistical information of the system dynamics. We instead develop a low-complexity algorithm called Demand Response with Energy Storage Management (DR-ESM). DR-ESM does not require any statistical knowledge of the system dynamics, including the renewable energy and the power prices. It only requires the entity to solve a small convex optimization pr...

  5. Justice and the demands of realism

    E-Print Network [OSTI]

    Munro, Daniel K., 1972-

    2006-01-01T23:59:59.000Z

    The dissertation examines how concerns about the demands of realism should be addressed in political theories of justice. It asks whether the demands of realism should affect the construction of principles of justice and, ...

  6. Industrial Equipment Demand and Duty Factors

    E-Print Network [OSTI]

    Dooley, E. S.; Heffington, W. M.

    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 compressors were near 100...

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

    Energy Savers [EERE]

    drivingdemandsocialmedia010611.pdf More Documents & Publications Marketing & Driving Demand: Social Media Tools & Strategies - January 16, 2011 Social Media for Natural...

  8. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01T23:59:59.000Z

    renewable integration capability. Coordinating and integrating HECO and Hawaii Energy demand response related activities has the potential

  9. Wireless Demand Response Controls for HVAC Systems

    E-Print Network [OSTI]

    Federspiel, Clifford

    2010-01-01T23:59:59.000Z

    temperature-based demand response in buildings that havedemand response advantages of global zone temperature setup in buildings

  10. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    demand-side management (DSM) framework presented in Table x provides three major areas for changing electric loads in buildings:

  11. 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

  12. 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 can help reduce the threat of planned rotational outages. Demand response is also widely regarded as having

  13. Demand Response Resources in Pacific Northwest

    E-Print Network [OSTI]

    Demand Response Resources in Pacific Northwest Chuck Goldman Lawrence Berkeley National Laboratory cagoldman@lbl.gov Pacific Northwest Demand Response Project Portland OR May 2, 2007 #12;Overview · Typology Annual Reports ­ Journal articles/Technical reports #12;Demand Response Resources · Incentive

  14. Barrier Immune Radio Communications for Demand Response

    E-Print Network [OSTI]

    LBNL-2294E Barrier Immune Radio Communications for Demand Response F. Rubinstein, G. Ghatikar, J Ann Piette of Lawrence Berkeley National Laboratory's (LBNL) Demand Response Research Center (DRRC and Environment's (CIEE) Demand Response Emerging Technologies Development (DRETD) Program, under Work for Others

  15. Demand Response and Ancillary Services September 2008

    E-Print Network [OSTI]

    Demand Response and Ancillary Services September 2008 #12;© 2008 EnerNOC, Inc. All Rights Reserved programs The purpose of this presentation is to offer insight into the mechanics of demand response and industrial demand response resources across North America in both regulated and restructured markets As of 6

  16. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    LBNL-62226 Demand Responsive Lighting: A Scoping Study F. Rubinstein, S. Kiliccote Energy Environmental Technologies Division January 2007 #12;LBNL-62226 Demand Responsive Lighting: A Scoping Study in this report was coordinated by the Demand Response Research Center and funded by the California Energy

  17. Modeling Energy Demand Aggregators for Residential Consumers

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Modeling Energy Demand Aggregators for Residential Consumers G. Di Bella, L. Giarr`e, M. Ippolito, A. Jean-Marie, G. Neglia and I. Tinnirello § January 2, 2014 Abstract Energy demand aggregators are new actors in the energy scenario: they gather a group of energy consumers and implement a demand

  18. Transportation Energy: Supply, Demand and the Future

    E-Print Network [OSTI]

    Saldin, Dilano

    Transportation Energy: Supply, Demand and the Future http://www.uwm.edu/Dept/CUTS//2050/energy05 as a source of energy. Global supply and demand trends will have a profound impact on the ability to use our) Transportation energy demand in the U.S. has increased because of the greater use of less fuel efficient vehicles

  19. Industrial demand side management: A status report

    SciTech Connect (OSTI)

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

    1995-05-01T23:59:59.000Z

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

  20. Advances in total scattering analysis

    SciTech Connect (OSTI)

    Proffen, Thomas E [Los Alamos National Laboratory; Kim, Hyunjeong [Los Alamos National Laboratory

    2008-01-01T23:59:59.000Z

    In recent years the analysis of the total scattering pattern has become an invaluable tool to study disordered crystalline and nanocrystalline materials. Traditional crystallographic structure determination is based on Bragg intensities and yields the long range average atomic structure. By including diffuse scattering into the analysis, the local and medium range atomic structure can be unravelled. Here we give an overview of recent experimental advances, using X-rays as well as neutron scattering as well as current trends in modelling of total scattering data.

  1. Greater fuel diversity needed to meet growing US electricity demand

    SciTech Connect (OSTI)

    Burt, B.; Mullins, S. [Industrial Info Resources (United States)

    2008-01-15T23:59:59.000Z

    Electricity demand is growing in the USA. One way to manage the uncertainty is to diversity fuel sources. Fuel sources include coal, natural gas, nuclear and renewable energy sources. Tables show actual and planned generation projects by fuel types. 1 fig., 2 tabs.

  2. OPUC Flexibility Planning Guidelines Pacific Northwest Demand Response Project

    E-Print Network [OSTI]

    ) Demand management smart grid controllable "withdrawal" and "recharge" #12;Jim Hicks Energy Strategies Jim Hicks Energy Strategies West, LLC #12;OPUC's New IRP Guidelines* Integrated Resource Plans operational view of planning, including comprehensive multi-faceted VER integration strategy #12;Daily Wind

  3. Total Light Management

    Broader source: Energy.gov [DOE]

    Presentation covers total light management, and is given at the Spring 2010 Federal Utility Partnership Working Group (FUPWG) meeting in Providence, Rhode Island.

  4. Total Space Heat-

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration...

  5. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

  6. Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes

    E-Print Network [OSTI]

    Sastry, S. Shankar

    Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes. Developing novel schemes for demand response in smart electric gird is an increasingly active research area/SCADA for demand response in smart infrastructures face the following dilemma: On one hand, in order to increase

  7. Patterns of crude demand: Future patterns of demand for crude oil as a func-

    E-Print Network [OSTI]

    Langendoen, Koen

    #12;2 #12;Patterns of crude demand: Future patterns of demand for crude oil as a func- tion schemes, and/or change quality of the feedstock (crude). Demand for crude oil is growing, especially perspective. This thesis aims pre- cisely at understanding the quality of oil from a demand side perspective

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

    E-Print Network [OSTI]

    Culler, David E.

    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

  9. Water supply and demand in an energy supply model

    SciTech Connect (OSTI)

    Abbey, D; Loose, V

    1980-12-01T23:59:59.000Z

    This report describes a tool for water and energy-related policy analysis, the development of a water supply and demand sector in a linear programming model of energy supply in the United States. The model allows adjustments in the input mix and plant siting in response to water scarcity. Thus, on the demand side energy conversion facilities can substitute more costly dry cooling systems for conventional evaporative systems. On the supply side groundwater and water purchased from irrigators are available as more costly alternatives to unappropriated surface water. Water supply data is developed for 30 regions in 10 Western states. Preliminary results for a 1990 energy demand scenario suggest that, at this level of spatial analysis, water availability plays a minor role in plant siting. Future policy applications of the modeling system are discussed including the evaluation of alternative patterns of synthetic fuels development.

  10. Open Automated Demand Response Communications Specification (Version 1.0)

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    and Techniques for Demand Response. May 2007. LBNL-59975.tofacilitateautomating demandresponseactionsattheInteroperable Automated Demand Response Infrastructure,

  11. Role of Standard Demand Response Signals for Advanced Automated Aggregation

    E-Print Network [OSTI]

    Kiliccote, Sila

    2013-01-01T23:59:59.000Z

    for the Open Automated Demand Response (OpenADR) StandardsControl for Automated Demand Response, Grid Interop, 2009. [C. McParland, Open Automated Demand Response Communications

  12. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    reliability signals for demand response GTA HTTPS HVAC IT kWand Commissioning Automated Demand Response Systems. and Techniques for Demand Response. California Energy

  13. Scenarios for Consuming Standardized Automated Demand Response Signals

    E-Print Network [OSTI]

    Koch, Ed

    2009-01-01T23:59:59.000Z

    of Fully Automated Demand Response in Large Facilities.Fully Automated Demand Response Tests in Large Facilities.Interoperable Automated Demand Response Infrastructure.

  14. Demand Response in U.S. Electricity Markets: Empirical Evidence

    E-Print Network [OSTI]

    Cappers, Peter

    2009-01-01T23:59:59.000Z

    Reliability Corporation. Demand response data task force:Energy. Benefits of demand response in electricity marketsAssessment of demand response & advanced metering, staff

  15. Demand Response Opportunities in Industrial Refrigerated Warehouses in California

    E-Print Network [OSTI]

    Goli, Sasank

    2012-01-01T23:59:59.000Z

    and Open Automated Demand Response. In Grid Interop Forum.work was sponsored by the Demand Response Research Center (load-management.php. Demand Response Research Center (2009).

  16. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

    Goodin. 2009. Open Automated Demand Response Communicationsin Demand Response for Wholesale Ancillary Services. InOpen Automated Demand Response Demonstration Project. LBNL-

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

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01T23:59:59.000Z

    advanced metering and demand response in electricityGoldman, and D. Kathan. Demand response in U.S. electricity29] DOE. Benefits of demand response in electricity markets

  18. Coordination of Retail Demand Response with Midwest ISO Markets

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01T23:59:59.000Z

    Robinson, Michael, 2008, "Demand Response in Midwest ISOPresentation at MISO Demand Response Working Group Meeting,Coordination of Retail Demand Response with Midwest ISO

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2010-01-01T23:59:59.000Z

    Interoperable Automated Demand Response Infrastructure.and Techniques for Demand Response. LBNL Report 59975. Mayand Communications for Demand Response and Energy Efficiency

  20. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    A. Barat, D. Watson. Demand Response Spinning ReserveOpen Automated Demand Response Communication Standards:Dynamic Controls for Demand Response in a New Commercial

  1. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01T23:59:59.000Z

    ofFullyAutomatedDemand ResponseinLargeFacilities. FullyAutomatedDemandResponseTestsinLargeFacilities. OpenAutomated DemandResponseCommunicationStandards:

  2. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    description of six energy and demand management concepts.how quickly it can modify energy demand. This is not a newimprovements in both energy efficiency and demand response (

  3. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01T23:59:59.000Z

    Institute, Curbing Global Energy Demand Growth: The Energyup Assessment of Energy Demand in India Transportationa profound effect on energy demand. Policy analysts wishing

  4. Sandia National Laboratories: How a Grid Manager Meets Demand...

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

    Demand (Load) How a Grid Manager Meets Demand (Load) In the "historical" electric grid, power-generating plants fell into three categories: No daily electrical demand data plot...

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

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01T23:59:59.000Z

    13 Table 2. Demand Side Management Framework for IndustrialDR Strategies The demand-side management (DSM) frameworkpresented in Table 2. Demand Side Management Framework for

  6. SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY | Department of...

    Energy Savers [EERE]

    SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY As a city that experiences seasonal...

  7. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    Building Control Strategies and Techniques for Demand Response.Building Systems and DR Strategies 16 Demand ResponseDemand Response Systems. Proceedings, 16 th National Conference on Building

  8. LEED Demand Response Credit: A Plan for Research towards Implementation

    E-Print Network [OSTI]

    Kiliccote, Sila

    2014-01-01T23:59:59.000Z

    in California. DEMAND RESPONSE AND COMMERCIAL BUILDINGSload and demand response against other buildings and alsoDemand Response and Energy Efficiency in Commercial Buildings",

  9. Open Automated Demand Response Communications Specification (Version 1.0)

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    Keywords:demandresponse,buildings,electricityuse,Interface AutomatedDemandResponse BuildingAutomationofdemandresponsein commercialbuildings. Onekey

  10. Results and commissioning issues from an automated demand response pilot

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, Dave; Sezgen, Osman; Motegi, Naoya

    2004-01-01T23:59:59.000Z

    Management and Demand Response in Commercial Buildings", L BAutomated Demand Response National Conference on BuildingAutomated Demand Response National Conference on Building

  11. Scenarios for Consuming Standardized Automated Demand Response Signals

    E-Print Network [OSTI]

    Koch, Ed

    2009-01-01T23:59:59.000Z

    Keywords: Demand response, automation, commercial buildings,Demand Response and Energy Efficiency in Commercial Buildings,Building Control Strategies and Techniques for Demand Response.

  12. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01T23:59:59.000Z

    Demand ResponseforSmallCommercialBuildings. CEC?500?automateddemandresponse Forsmallcommercialbuildings,AUTOMATED DEMAND RESPONSE FOR SMALL COMMERCIAL BUILDINGS

  13. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    for Demand Response in New and Existing Commercial BuildingsDemand Response Strategies and National Conference on BuildingDemand Response Strategies and Commissioning Commercial Building

  14. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

    for Automated Demand Response in Commercial Buildings. Inbased demand response information to building controlDemand Response Standard for the Residential Sector. California Energy Commission, PIER Buildings

  15. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    is manual demand response where building staff receive acommercial buildings demand response technologies andBuilding Control Strategies and Techniques for Demand Response.

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2010-01-01T23:59:59.000Z

    Keywords: Demand response, automation, commercial buildings,Demand Response and Energy Efficiency in Commercial Buildings,Building Control Strategies and Techniques for Demand Response.

  17. Sensor-based demand controlled ventilation

    SciTech Connect (OSTI)

    De Almeida, A.T. [Universidade de Coimbra (Portugal). Dep. Eng. Electrotecnica; Fisk, W.J. [Lawrence Berkeley National Lab., CA (United States)

    1997-07-01T23:59:59.000Z

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

  18. Electricity Demand and Energy Consumption Management System

    E-Print Network [OSTI]

    Sarmiento, Juan Ojeda

    2008-01-01T23:59:59.000Z

    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...

  19. Industrial Demand-Side Management in Texas

    E-Print Network [OSTI]

    Jaussaud, D.

    of programs result in lower consumption and/or lower peak demand, and ultimately reduce the need to build new capacity. Hence demand-side management can be used as a resource option to be considered alongside more traditional supply-side resources in a...INDUSTRIAL DEMAND-SIDE MANAGEMENT IN TEXAS Danielle Jaussaud Economic Analysis Section Public Utility Commission of Texas Austin, Texas ABSTRACT The industrial sector in Texas is highly energy intensive and represents a large share...

  20. Demand Controlled Ventilation and Classroom Ventilation

    E-Print Network [OSTI]

    Fisk, William J.

    2014-01-01T23:59:59.000Z

    2 -based demand controlled ventilation using ASHRAE Standardoptimizing energy use and ventilation. ASHRAE TransactionsWJ, Grimsrud DT, et al. 2011. Ventilation rates and health:

  1. DEMAND CONTROLLED VENTILATION AND CLASSROOM VENTILATION

    E-Print Network [OSTI]

    Fisk, William J.

    2014-01-01T23:59:59.000Z

    for demand controlled ventilation in commercial buildings.The energy costs of classroom ventilation and some financialEstimating potential benefits of increased ventilation

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

    E-Print Network [OSTI]

    Aden, Nathaniel

    2010-01-01T23:59:59.000Z

    Drivers of demand: urbanization, heavy industry, and risingdemand: urbanization, heavy industry, and rising income Theprocesses of urbanization, heavy industry growth, and rising

  3. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01T23:59:59.000Z

    Commission (FERC) 2008a. Wholesale Competition in RegionsDemand Response into Wholesale Electricity Markets, (URL:1 2. Wholesale and Retails Electricity Markets in

  4. Demand Response - Policy | Department of Energy

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

    prices or when grid reliability is jeopardized. In regions with centrally organized wholesale electricity markets, demand response can help stabilize volatile electricity prices...

  5. Optimization of Demand Response Through Peak Shaving

    E-Print Network [OSTI]

    2013-06-19T23:59:59.000Z

    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...

  6. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    peak demand management. Photo sensors for daylight drivenare done by local photo-sensors and control hardwaresensing device in a photo sensor is typically a photodiode,

  7. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01T23:59:59.000Z

    in peak demand. This definition of energy efficiency makesthe following definitions are used: Energy efficiency refersThis definition implicitly distinguishes energy efficiency

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

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

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

  9. Geographically Based Hydrogen Demand and Infrastructure Analysis...

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

    Analysis Geographically Based Hydrogen Demand and Infrastructure Analysis Presentation by NREL's Margo Melendez at the 2010 - 2025 Scenario Analysis for Hydrogen Fuel Cell Vehicles...

  10. Natural Gas Demand Markets in the Northeast

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

    Providing a Significant Opportunity for New and Expanding Natural Gas Demand Markets in the Northeast Prepared for: America's Natural Gas Alliance (ANGA) Prepared by: Bentek...

  11. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    3 3.0 Previous Experience with Demand Responsive Lighting11 4.3. Prevalence of Lighting13 4.4. Impact of Title 24 on Lighting

  12. Wastewater plant takes plunge into demand response

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

    Commission and the Bonneville Power Administration, the Eugene-Springfield Water Pollution Control Facility in Eugene, Ore., was put through a series of demand response tests....

  13. Robust newsvendor problem with autoregressive demand

    E-Print Network [OSTI]

    2014-05-19T23:59:59.000Z

    May 19, 2014 ... business decision problems, in fields such as managing booking and ...... Q? having available the demand historical records for t = 1, ..., T. 2.

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

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

    Honeywell's Smart Grid Investment Grant (SGIG) project demonstrates utility-scale performance of a hardwaresoftware platform for automated demand response (ADR). This project...

  15. Wireless Demand Response Controls for HVAC Systems

    E-Print Network [OSTI]

    Federspiel, Clifford

    2010-01-01T23:59:59.000Z

    Response Controls for HVAC Systems Clifford Federspiel,tests. Figure 5: Specific HVAC electric power consumptioncontrol, demand response, HVAC, wireless Executive Summary

  16. Coupling Renewable Energy Supply with Deferrable Demand

    E-Print Network [OSTI]

    Papavasiliou, Anthony

    2011-01-01T23:59:59.000Z

    the dispatch of flexible loads and generation resources bothof controllable generation and flexible demand. In the casecontrollable generation resources and flexible loads in the

  17. FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007

    E-Print Network [OSTI]

    ......................................................................... 11 3. Demand Side Management (DSM) Program Impacts................................... 13 4. Demand Sylvia Bender Manager DEMAND ANALYSIS OFFICE Scott W. Matthews Chief Deputy Director B.B. Blevins Forecast Methods and Models ....................................................... 14 5. Demand-Side

  18. anorrectal total reporte: Topics by E-print Network

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

    markets including finance, energy, healthcare, telecommunications, unknown authors 5 Computer Integrated Revision Total Hip Replacement Surgery: Preliminary Report Computer...

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

    Energy Savers [EERE]

    Aligning Program Demand with Contractor's Seasonal Fluctuations Strategies for Aligning Program Demand with Contractor's Seasonal Fluctuations Better Buildings Neighborhood Program...

  20. Assessing Vehicle Electricity Demand Impacts on California Electricity Supply

    E-Print Network [OSTI]

    McCarthy, Ryan W.

    2009-01-01T23:59:59.000Z

    fuel electricity demands, and generation from these plantplants .. 47 Additional generation .. 48 Electricityelectricity demand increases generation from NGCC power plants.

  1. Drivers of Future Energy Demand

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline353/06) 2Yonthly Energy :and1. Total3.9Drivers

  2. 2013 Utility Bundled Retail Sales- Total

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001)gasoline prices4 Oil demand8)Commercial (DataTotal (Data

  3. Total Energy Monitor

    SciTech Connect (OSTI)

    Friedrich, S

    2008-08-11T23:59:59.000Z

    The total energy monitor (TE) is a thermal sensor that determines the total energy of each FEL pulse based on the temperature rise induced in a silicon wafer upon absorption of the FEL. The TE provides a destructive measurement of the FEL pulse energy in real-time on a pulse-by-pulse basis. As a thermal detector, the TE is expected to suffer least from ultra-fast non-linear effects and to be easy to calibrate. It will therefore primarily be used to cross-calibrate other detectors such as the Gas Detector or the Direct Imager during LCLS commissioning. This document describes the design of the TE and summarizes the considerations and calculations that have led to it. This document summarizes the physics behind the operation of the Total Energy Monitor at LCLS and derives associated engineering specifications.

  4. Demand Response and Electric Grid Reliability

    E-Print Network [OSTI]

    Wattles, P.

    2012-01-01T23:59:59.000Z

    Demand Response and Electric Grid Reliability Paul Wattles Senior Analyst, Market Design & Development, ERCOT CATEE Conference, Galveston October 10, 2012 2 North American Bulk Power Grids CATEE Conference October 10, 2012 ? The ERCOT... adequacy ? ?Achieving more DR participation would . . . displace some generation investments, but would achieve the same level of reliability... ? ?Achieving this ideal requires widespread demand response and market structures that enable loads...

  5. SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK DRAFTSTAFFREPORT May ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION B. B assessment of the capability of the physical electricity system to provide power to meet electricity demand

  6. Optimal Trading Strategy Supply/Demand Dynamics

    E-Print Network [OSTI]

    Gabrieli, John

    prices through the changes in their supply/demand.2 Thus, to study how market participants trade can have interesting implications on the observed behavior of intraday volume, volatility and prices: November 15, 2004. This Draft: April 8, 2006 Abstract The supply/demand of a security in the market

  7. INTEGRATION OF PV IN DEMAND RESPONSE

    E-Print Network [OSTI]

    Perez, Richard R.

    . It may also be implemented by means of customer-sited emergency power generation (e.g., diesel generators the case that distributed PV generation deserves a substantial portion of the credit allotted to demand response programs. This is because PV generation acts as a catalyst to demand response, markedly enhancing

  8. Demand Response Programs Oregon Public Utility Commission

    E-Print Network [OSTI]

    , Demand Side Management #12;Current Programs/Tariffs ­ Load Control Programs Cool Keeper, Utah (currentlyDemand Response Programs Oregon Public Utility Commission January 6, 2005 Mike Koszalka Director 33 MW, building to 90 MW) Irrigation load control, Idaho (35 MW summer, 2004) Lighting load control

  9. Total Energy Management in General Motors

    E-Print Network [OSTI]

    DeKoker, N.

    1979-01-01T23:59:59.000Z

    This paper presents an overview of General Motors' energy management program with special emphasis on energy conservation. Included is a description of the total program organization, plant guidelines, communication and motivation techniques...

  10. Coordination of Energy Efficiency and Demand Response

    SciTech Connect (OSTI)

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

    2010-01-29T23:59:59.000Z

    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.

  11. Demand Response This is the first of the Council's power plans to treat demand response as a resource.1

    E-Print Network [OSTI]

    Demand Response This is the first of the Council's power plans to treat demand response the resource and describes some of the potential advantages and problems of the development of demand response. WHAT IS DEMAND RESPONSE? Demand response is a change in customers' demand for electricity corresponding

  12. Total Precipitable Water

    SciTech Connect (OSTI)

    None

    2012-01-01T23:59:59.000Z

    The simulation was performed on 64K cores of Intrepid, running at 0.25 simulated-years-per-day and taking 25 million core-hours. This is the first simulation using both the CAM5 physics and the highly scalable spectral element dynamical core. The animation of Total Precipitable Water clearly shows hurricanes developing in the Atlantic and Pacific.

  13. Paying for demand-side response at the wholesale level

    SciTech Connect (OSTI)

    Falk, Jonathan

    2010-11-15T23:59:59.000Z

    The recent FERC Notice of Public Rulemaking regarding the payment to demand-side resources in wholesale markets has engendered a great deal of comments including FERC's obligation to ensure just and reasonable rates in the wholesale market and criteria for what FERC should do (on grounds of economic efficiency) without any real focus on what that commitment would really mean if FERC actually pursued it. (author)

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

    SciTech Connect (OSTI)

    NONE

    2009-07-15T23:59:59.000Z

    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.

  15. Subverting value hierarchies : essays on the causes and responses to shifts in demand for authenticity

    E-Print Network [OSTI]

    Hahl, Oliver (Oliver Douglas)

    2013-01-01T23:59:59.000Z

    This dissertation includes three essays on the causes and responses to shifts in demand for authenticity. In the first chapter, I answer the question: why do previously cast-off products, practices, or styles abruptly ...

  16. 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.

    2013-01-01T23:59:59.000Z

    This paper summarizes three case study buildings located in Austin, Texas that were selected for inclusion in a review of the demand reduction program of the utility company Austin Energy. The buildings studied include a city government office...

  17. The Role of Demand Resources In Regional Transmission Expansion Planning and Reliable Operations

    SciTech Connect (OSTI)

    Kirby, Brendan J [ORNL

    2006-07-01T23:59:59.000Z

    Investigating the role of demand resources in regional transmission planning has provided mixed results. On one hand there are only a few projects where demand response has been used as an explicit alternative to transmission enhancement. On the other hand there is a fair amount of demand response in the form of energy efficiency, peak reduction, emergency load shedding, and (recently) demand providing ancillary services. All of this demand response reduces the need for transmission enhancements. Demand response capability is typically (but not always) factored into transmission planning as a reduction in the load which must be served. In that sense demand response is utilized as an alternative to transmission expansion. Much more demand response is used (involuntarily) as load shedding under extreme conditions to prevent cascading blackouts. The amount of additional transmission and generation that would be required to provide the current level of reliability if load shedding were not available is difficult to imagine and would be impractical to build. In a very real sense demand response solutions are equitably treated in every region - when proposed, demand response projects are evaluated against existing reliability and economic criteria. The regional councils, RTOs, and ISOs identify needs. Others propose transmission, generation, or responsive load based solutions. Few demand response projects get included in transmission enhancement plans because few are proposed. But this is only part of the story. Several factors are responsible for the current very low use of demand response as a transmission enhancement alternative. First, while the generation, transmission, and load business sectors each deal with essentially the same amount of electric power, generation and transmission companies are explicitly in the electric power business but electricity is not the primary business focus of most loads. This changes the institutional focus of each sector. Second, market and reliability rules have, understandably, been written around the capabilities and limitations of generators, the historic reliability resources. Responsive load limitations and capabilities are often not accommodated in markets or reliability criteria. Third, because of the institutional structure, demand response alternatives are treated as temporary solutions that can delay but not replace transmission enhancement. Financing has to be based on a three to five year project life as opposed to the twenty to fifty year life of transmission facilities. More can be done to integrate demand response options into transmission expansion planning. Given the societal benefits it may be appropriate for independent transmission planning organizations to take a more proactive role in drawing demand response alternatives into the resource mix. Existing demand response programs provide a technical basis to build from. Regulatory and market obstacles will have to be overcome if demand response alternatives are to be routinely considered in transmission expansion planning.

  18. Autonomous Demand Response for Primary Frequency Regulation

    SciTech Connect (OSTI)

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

    2012-02-28T23:59:59.000Z

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

  19. Changes in worldwide demand for metals (final). Open File report

    SciTech Connect (OSTI)

    Faucett, J.G.; Chmelynski, H.J.

    1986-08-01T23:59:59.000Z

    Worldwide demand for metals was analyzed to identify the important factors that explain differences in the level of demand among world countries. The per capita demand for steel, aluminum, copper, and total nonferrous metals was investigated for 40 to 50 countries over a 22-year period. These countries have been further grouped into four world regions for purposes of making generalizations about the importance of these factors for countries in different stages of development and with dissimilar levels of per capita gross domestic product (GDP). Intercountry and intertemporal differences are explained largely by differences in per capita GDP and changes over time in per capita GDP, oil real prices, and to a lesser extent, metal real prices. The trend in world consumption is dramatically different in the last decade than the previous one. In 1962-73, per capita consumption increased in all areas and consumption intensity (consumption divided by (GDP) increased in most areas). In 1973-84, per capita consumption fell in most areas and intensity fell dramatically, except in developing nations.

  20. Students must complete a total of 22 units of graduate coursework, including

    E-Print Network [OSTI]

    Engineering is designed for graduate students in the Department of Statistics and Actuarial Science who would 830 - Statistical Theory I (4) > STAT 831 - Statistical Theory II (4) > STAT 832 - Applied Probability of Statistics and Actuarial Science: Gary Parker gparker@stat.sfu.ca #12;

  1. Capitalize on Existing Assets with Demand Response

    E-Print Network [OSTI]

    Collins, J.

    2008-01-01T23:59:59.000Z

    Industrial facilities universally struggle with escalating energy costs. EnerNOC will demonstrate how commercial, industrial, and institutional end-users can capitalize on their existing assetsat no cost and no risk. Demand response, the voluntary...

  2. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    account for the most natural gas usage (33% and 51% of totalseasonal dependence in natural gas usage, and consequently,Natural gas demand exhibits a strong winter peak in residential usage

  3. A residential energy demand system for Spain

    E-Print Network [OSTI]

    Labandeira Villot, Xavier

    2005-01-01T23:59:59.000Z

    Sharp price fluctuations and increasing environmental and distributional concerns, among other issues, have led to a renewed academic interest in energy demand. In this paper we estimate, for the first time in Spain, an ...

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

    ScienceCinema (OSTI)

    Arun Majumdar

    2010-01-08T23:59:59.000Z

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

  5. Micro economics for demand-side management

    E-Print Network [OSTI]

    Kibune, Hisao

    1991-01-01T23:59:59.000Z

    This paper aims to interpret Demand-Side Management (DSM) activity and to point out its problems, adopting microeconomics as an analytical tool. Two major findings follow. first, the cost-benefit analysis currently in use ...

  6. Response to changes in demand/supply

    E-Print Network [OSTI]

    Response to changes in demand/supply through improved marketing 21.2 #12;#12;111 Impacts of changes operating by some Korean paper companies for acquiring needed pulpwood as a first step for the construction

  7. Demand Controlled Ventilation for Improved Humidity Control

    E-Print Network [OSTI]

    Rogers, J. K.

    1996-01-01T23:59:59.000Z

    Demand Controlled Ventilation for Improved Humidity Control James K. Rogers, P.E. One Blacksmith Road Chelmsford, Massachusetts ABSTRACT Recently introduced technology makes it possible to continuously monitor for humidity in numerous... is brought in for ventilation. The high "latent load" inherent in this hot, humid outside air is often the reason for installing excess chiller capacity and the cause of peak power demands. Recent concerns over poor indoor air quality (IAQ) due...

  8. Measuring the capacity impacts of demand response

    SciTech Connect (OSTI)

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

    2009-07-15T23:59:59.000Z

    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)

  9. Real-Time Demand Side Energy Management

    E-Print Network [OSTI]

    Victor, A.; Brodkorb, M.

    2006-01-01T23:59:59.000Z

    Real-Time Demand Side Energy Management Annelize Victor Michael Brodkorb Sr. Business Consultant Business Development Manager Aspen Technology, Inc. Aspen Technology Espaa, S.A. Houston, TX Barcelona, Spain ABSTRACT To remain... competitive, manufacturers must capture opportunities to increase bottom-line profitability. The goal of this paper is to present a new methodology for reducing energy costs Demand-Side Energy Management. Learn how process manufacturers assess energy...

  10. Seasonal demand and supply analysis of turkeys

    E-Print Network [OSTI]

    Blomo, Vito James

    1972-01-01T23:59:59.000Z

    SEASONAL DEMAND AND SUPPLY ANALYSIS OF TURKEYS A Thesis by VITO JAMES BLOMO Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE May 1972 Ma)or Sub...)ect: Agricultural Economics SEASONAL DEMAND AND SUPPLY ANALYSIS OF TURKEYS A Thesis by VITO JAMES BLOMO Approved as to style and content by: (Chairman of C mmittee) (Head of Department) (Member) (Member) ( ber) (Memb er) May 1972 ABSTRACT Seasonal...

  11. National Microalgae Biofuel Production Potential and Resource Demand

    SciTech Connect (OSTI)

    Wigmosta, Mark S.; Coleman, Andre M.; Skaggs, Richard; Huesemann, Michael H.; Lane, Leonard J.

    2011-04-14T23:59:59.000Z

    Microalgae continue to receive global attention as a potential sustainable "energy crop" for biofuel production. An important step to realizing the potential of algae is quantifying the demands commercial-scale algal biofuel production will place on water and land resources. We present a high-resolution national resource and oil production assessment that brings to bear fundamental research questions of where open pond microalgae production can occur, how much land and water resource is required, and how much energy is produced. Our study suggests under current technology microalgae have the potential to generate 220 billion liters/year of oil, equivalent to 48% of current U.S. petroleum imports for transportation fuels. However, this level of production would require 5.5% of the land area in the conterminous U.S., and nearly three times the volume of water currently used for irrigated agriculture, averaging 1,421 L water per L of oil. Optimizing the selection of locations for microalgae production based on water use efficiency can greatly reduce total water demand. For example, focusing on locations along the Gulf Coast, Southeastern Seaboard, and areas adjacent to the Great Lakes, shows a 75% reduction in water demand to 350 L per L of oil produced with a 67% reduction in land use. These optimized locations have the potential to generate an oil volume equivalent to 17% of imports for transportation fuels, equal to the Energy Independence and Security Act year 2022 "advanced biofuels" production target, and utilizing some 25% of the current irrigation consumptive water demand for the U. S. These results suggest that, with proper planning, adequate land and water are available to meet a significant portion of the U.S. renewable fuel goals.

  12. TotalView Training

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengthening a solidSynthesisAppliances » Top InnovativeTopoisomeraseTotalView

  13. Demand responsive programs - an emerging resource for competitive electricity markets?

    SciTech Connect (OSTI)

    Heffner, Grayson C. Dr.; Goldman, Charles A.

    2001-06-25T23:59:59.000Z

    The restructuring of regional electricity markets in the U.S. has been accompanied by numerous problems, including generation capacity shortages, transmission congestion, wholesale price volatility, and reduced system reliability. These problems have created significant new opportunities for technologies and business approaches that allow load serving entities and other aggregators, to control and manage the load patterns of their wholesale or retail end-users. These technologies and business approaches for manipulating end-user load shapes are known as Load Management or, more recently, Demand Responsive programs. Lawrence Berkeley National Laboratory (LBNL) is conducting case studies on innovative demand responsive programs and presents preliminary results for five case studies in this paper. These case studies illustrate the diversity of market participants and range of technologies and business approaches and focus on key program elements such as target markets, market segmentation and participation results; pricing scheme; dispatch and coordination; measurement, verification, and settlement; and operational results where available.

  14. Results and commissioning issues from an automated demand responsepilot

    SciTech Connect (OSTI)

    Piette, Mary Ann; Watson, Dave; Sezgen, Osman; Motegi, Naoya

    2004-08-05T23:59:59.000Z

    This paper describes a research project to develop and test Automated Demand Response hardware and software technology in large facilities. We describe the overall project and some of the commissioning and system design problems that took place. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve the electric grid reliability purposes, manage electricity costs, and ensure that customers receive signals that encourage load reduction during times when the electric grid is near its capacity. There were a number of specific commissioning challenges in conducting this test including software compatibility, incorrect time zones, IT and EMCS failures, and hardware issues. The knowledge needed for this type of system commissioning combines knowledge of building controls with network management and knowledge of emerging information technologies.

  15. New Demand for Old Food: the U.S. Demand for Olive Oil

    E-Print Network [OSTI]

    Bo Xiong; William Matthews; Daniel Sumner

    U.S. consumption of olive oil has tripled over the past twenty years, but nearly all olive oil continues to be imported. Estimation of demand parameters using monthly import data reveals that demand for non-virgin oil is income inelastic, but virgin oils have income elasticities above one. Moreover, demand for oils differentiated by origin and quality is price-elastic. These olive oils are highly substitutable with each other but not with other vegetable oils. News about the health and culinary benefits of olive oil and the spread of Mediterranean diet contribute significantly to the rising demand in the United States.

  16. Analysis of Open Automated Demand Response Deployments in California

    E-Print Network [OSTI]

    LBNL-6560E Analysis of Open Automated Demand Response Deployments in California and Guidelines The work described in this report was coordinated by the Demand Response Research. #12; #12;Abstract This report reviews the Open Automated Demand Response

  17. PIER: Demand Response Research Center Director, Mary Ann Piette

    E-Print Network [OSTI]

    1 PIER: Demand Response Research Center Director, Mary Ann Piette Program Development and Outreach Response Research Plan #12;2 Demand Response Research Center Objective Scope Stakeholders Develop, prioritize, conduct and disseminate multi- institutional research to facilitate Demand Response. Technologies

  18. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

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

    2006-01-01T23:59:59.000Z

    4 9 . Piette et at Automated Demand Response Strategies andDynamic Controls for Demand Response in New and ExistingFully Automated Demand Response Tests in Large Facilities"

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

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2013-01-01T23:59:59.000Z

    El-Saadany. A summary of demand response in electricityadvanced metering and demand response in electricityWolak. When it comes to demand response is FERC is own worst

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

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    ED2, September. CEC (2005b) Energy demand forecast methodsCalifornia Baseline Energy Demands to 2050 for Advancedof a baseline scenario for energy demand in California for a

  1. Demand Control Utilizing Energy Management Systems - Report of Field Tests

    E-Print Network [OSTI]

    Russell, B. D.; Heller, R. P.; Perry, L. W.

    1984-01-01T23:59:59.000Z

    Energy Management systems and particularly demand controllers are becoming more popular as commercial and light industrial operations attempt to reduce their electrical usage and demand. Numerous techniques are used to control energy use and demand...

  2. CALIFORNIA ENERGY CALIFORNIA ENERGY DEMAND 2010-2020

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2010-2020 ADOPTED FORECAST for this report: Kavalec, Chris and Tom Gorin, 2009. California Energy Demand 20102020, Adopted Forecast. California Energy Commission. CEC2002009012CMF #12; i Acknowledgments The demand forecast

  3. Learning Energy Demand Domain Knowledge via Feature Transformation

    E-Print Network [OSTI]

    Povinelli, Richard J.

    Learning Energy Demand Domain Knowledge via Feature Transformation Sanzad Siddique Department -- Domain knowledge is an essential factor for forecasting energy demand. This paper introduces a method knowledge substantially improves energy demand forecasting accuracy. However, domain knowledge may differ

  4. Energy Demands and Efficiency Strategies in Data Center Buildings

    E-Print Network [OSTI]

    Shehabi, Arman

    2010-01-01T23:59:59.000Z

    iv Chapter 5: National energy demand and potential energyEnergyDemandsandEfficiencyStrategies inDataCenterAC02?05CH11231. Energy Demands and Efficiency Strategies

  5. Coordination of Retail Demand Response with Midwest ISO Markets

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01T23:59:59.000Z

    Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the4. Status of Demand Side Management in Midwest ISO 5.

  6. Demand-Side Management and Energy Efficiency Revisited

    E-Print Network [OSTI]

    Auffhammer, Maximilian; Blumstein, Carl; Fowlie, Meredith

    2007-01-01T23:59:59.000Z

    EPRI). 1984. Demand Side Management. Vol. 1:Overview of Key1993. Industrial Demand-Side Management Programs: WhatsJ. Kulick. 2004. Demand side management and energy e?ciency

  7. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    for Demand Response in a New Commercial Building in NewDemand Response and Energy Efficiency in Commercial Buildings.Demand Response Mary Ann Piette, Sila Kiliccote, and Girish Ghatikar Lawrence Berkeley National Laboratory Building

  8. Smart Buildings Using Demand Response March 6, 2011

    E-Print Network [OSTI]

    Kammen, Daniel M.

    Smart Buildings Using Demand Response March 6, 2011 Sila Kiliccote Deputy, Demand Response Research Center Program Manager, Building Technologies Department Environmental Energy Technologies only as needed) · Energy Efficiency strategies are permanent (occur daily) 4 #12;Demand-Side

  9. Project Functions and Activities Definitions for Total Project...

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

    exactly is included in total estimated cost (TEC) and total project cost (TPC). g4301-1chp6.pdf -- PDF Document, 46 KB Writer: John Makepeace Subjects: Administration Management...

  10. Project Functions and Activities Definitions for Total Project Cost

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1997-03-28T23:59:59.000Z

    This chapter provides guidelines developed to define the obvious disparity of opinions and practices with regard to what exactly is included in total estimated cost (TEC) and total project cost (TPC).

  11. DSM Program Development. The demand-side resource options were developed using a combination of internal engineering estimates and external consulting services. The

    E-Print Network [OSTI]

    for the determination of the optimum program level to be included in the IRP. The demand-side management options wereDSM Program Development. The demand-side resource options were developed using a combination Practices Manual: Economic Analysis of Demand-side Programs and Projects.2 The proposed DSM programs

  12. Environmental and Resource Economics Household Energy Demand in Urban China: Accounting for regional prices and rapid

    E-Print Network [OSTI]

    Energy Demand in Urban China: Accounting for regional prices and rapid income change Article Type and changing demographics. We estimate income and price elasticities for these energy types using a two effects into account, we find that total energy is price-inelastic for all income groups. For individual

  13. Countries Gasoline Prices Including Taxes

    Gasoline and Diesel Fuel Update (EIA)

    Selected Countries (U.S. dollars per gallon, including taxes) Date Belgium France Germany Italy Netherlands UK US 51115 6.15 6.08 6.28 6.83 6.96 6.75 3.06 5415 6.14 6.06...

  14. Sponsorship includes: Agriculture in the

    E-Print Network [OSTI]

    Nebraska-Lincoln, University of

    Sponsorship includes: · Agriculture in the Classroom · Douglas County Farm Bureau · Gifford Farm · University of Nebraska Agricultural Research and Development Center · University of Nebraska- Lincoln Awareness Coalition is to help youth, primarily from urban communities, become aware of agriculture

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

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

    and the Department of Energy. Implementation Proposal for the National Action Plan on Demand Response - July 2011 More Documents & Publications National Action Plan on Demand...

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

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

    Federal Energy Regulatory Commission (FERC) presentation on demand response as power system resources before the Electicity Advisory Committee, October 29, 2010 Demand Response as...

  17. Robust Unit Commitment Problem with Demand Response and ...

    E-Print Network [OSTI]

    2010-10-31T23:59:59.000Z

    Oct 29, 2010 ... sion, both Demand Response (DR) strategy and intermittent renewable ... On the other hand, demand response, which enables customers to...

  18. ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES

    E-Print Network [OSTI]

    Gross, George

    ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES BY ANUPAMA SUNIL KOWLI B of consumers - called demand response resources (DRRs) - whose role has become increasingly important

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

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    gas demands are forecast for the four natural gas utility2013 Forecast, these trends lead to declining natural gasthe 2006-2016 Forecast. Commercial natural gas demand is

  20. CO2 MONITORING FOR DEMAND CONTROLLED VENTILATION IN COMMERCIAL BUILDINGS

    E-Print Network [OSTI]

    Fisk, William J.

    2010-01-01T23:59:59.000Z

    use of demand control ventilation systems in general officethe demand controlled ventilation system increased the ratedemand controlled ventilation systems will, because of poor

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

    E-Print Network [OSTI]

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

    2008-01-01T23:59:59.000Z

    seasonal dependence in natural gas usage. January typicallyindustrial fuels usage. Natural gas demand has been risingnatural gas demands regionally, to account for variability in energy usage

  2. Energy Upgrade California Drives Demand From Behind the Wheel...

    Energy Savers [EERE]

    Upgrade California Drives Demand From Behind the Wheel Energy Upgrade California Drives Demand From Behind the Wheel Photo of a trailer with the Energy Upgrade California logo and...

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

    Energy Savers [EERE]

    Reducing Energy Demand in Buildings Through State Energy Codes Reducing Energy Demand in Buildings Through State Energy Codes Building Codes Project for the 2013 Building...

  4. Response to several FOIA requests - Renewable Energy. Demand...

    Office of Environmental Management (EM)

    Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA...

  5. Assessing Vehicle Electricity Demand Impacts on California Electricity Supply

    E-Print Network [OSTI]

    McCarthy, Ryan W.

    2009-01-01T23:59:59.000Z

    and fuel-related electricity demands grow, so do the numberelectricity demands are unlikely to affect capacity additions and procurement decisions until they grow

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

    Energy Savers [EERE]

    Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters March 10, 2015 -...

  7. BUILDINGS SECTOR DEMAND-SIDE EFFICIENCY TECHNOLOGY SUMMARIES

    E-Print Network [OSTI]

    LBL-33887 UC-000 BUILDINGS SECTOR DEMAND-SIDE EFFICIENCY TECHNOLOGY SUMMARIES Jonathan G. Koomey ............................................................................................... 2 Demand-Side Efficiency Technologies I. Energy Management Systems (EMSs

  8. assessing workforce demand: Topics by E-print Network

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

    and Utilization Websites Summary: LBNL-5319E Assessing the Control Systems Capacity for Demand Response in California Industries in this report was coordinated by the Demand...

  9. air passenger demand: Topics by E-print Network

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

    Websites Summary: 1 Aggregated Modeling and Control of Air Conditioning Loads for Demand Response Wei Zhang, Member, IEEE Abstract--Demand response is playing an...

  10. air cargo demand: Topics by E-print Network

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

    Websites Summary: 1 Aggregated Modeling and Control of Air Conditioning Loads for Demand Response Wei Zhang, Member, IEEE Abstract--Demand response is playing an...

  11. Flexible Demand Management under Time-Varying Prices

    E-Print Network [OSTI]

    Liang, Yong

    2012-01-01T23:59:59.000Z

    Management System Flexible Appliances Distributed Flexible Demand Management under Time-Varying Prices by YongYing-Ju Chen Spring 2013 Flexible Demand Management under

  12. 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

    2009-06-28T23:59:59.000Z

    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.

  13. International Oil Supplies and Demands. Volume 2

    SciTech Connect (OSTI)

    Not Available

    1992-04-01T23:59:59.000Z

    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. Uranium 2014 resources, production and demand

    E-Print Network [OSTI]

    Organisation for Economic Cooperation and Development. Paris

    2014-01-01T23:59:59.000Z

    Published every other year, Uranium Resources, Production, and Demand, or the "Red Book" as it is commonly known, is jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency. It is the recognised world reference on uranium and is based on official information received from 43 countries. It presents the results of a thorough review of world uranium supplies and demand and provides a statistical profile of the world uranium industry in the areas of exploration, resource estimates, production and reactor-related requirements. It provides substantial new information from all major uranium production centres in Africa, Australia, Central Asia, Eastern Europe and North America. Long-term projections of nuclear generating capacity and reactor-related uranium requirements are provided as well as a discussion of long-term uranium supply and demand issues. This edition focuses on recent price and production increases that could signal major changes in the industry.

  15. Utility Sector Impacts of Reduced Electricity Demand

    SciTech Connect (OSTI)

    Coughlin, Katie

    2014-12-01T23:59:59.000Z

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

  16. Uranium 2007 resources, production and demand

    E-Print Network [OSTI]

    Organisation for Economic Cooperation and Development. Paris

    2008-01-01T23:59:59.000Z

    Based on official information received from 40 countries, Uranium 2007 provides a comprehensive review of world uranium supply and demand as of 1st January 2007, as well as data on global uranium exploration, resources, production and reactor-related requirements. It provides substantive new information from major uranium production centres in Africa, Australia, Central Asia, Eastern Europe and North America. Projections of nuclear generating capacity and reactor-related uranium requirements through 2030 are also featured, along with an analysis of long-term uranium supply and demand issues. It finds that with rising demand and declining inventories, uranium prices have increased dramatically in recent years. As a result, the uranium industry is undergoing a significant revival, bringing to an end a period of over 20 years of underinvestment.

  17. Uranium 2005 resources, production and demand

    E-Print Network [OSTI]

    Organisation for Economic Cooperation and Development. Paris

    2006-01-01T23:59:59.000Z

    Published every other year, Uranium Resources, Production, and Demand, or the "Red Book" as it is commonly known, is jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency. It is the recognised world reference on uranium and is based on official information received from 43 countries. This 21st edition presents the results of a thorough review of world uranium supplies and demand as of 1st January 2005 and provides a statistical profile of the world uranium industry in the areas of exploration, resource estimates, production and reactor-related requirements. It provides substantial new information from all major uranium production centres in Africa, Australia, Central Asia, Eastern Europe and North America. Projections of nuclear generating capacity and reactor-related uranium requirements through 2025 are provided as well as a discussion of long-term uranium supply and demand issues. This edition focuses on recent price and production increases that could signal major c...

  18. International Oil Supplies and Demands. Volume 1

    SciTech Connect (OSTI)

    Not Available

    1991-09-01T23:59:59.000Z

    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.

  19. Wireless Demand Response Controls for HVAC Systems

    SciTech Connect (OSTI)

    Federspiel, Clifford

    2009-06-30T23:59:59.000Z

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

  20. Electric Water Heater Modeling and Control Strategies for Demand Response

    SciTech Connect (OSTI)

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

    2012-07-22T23:59:59.000Z

    Abstract Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency support following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms Centralized control, decentralized control, demand response, electrical water heater, smart grid

  1. Enron sees major increases in U. S. gas supply, demand

    SciTech Connect (OSTI)

    Carson, M.M.; Stram, B. (Enron Corp., Houston, TX (US))

    1991-10-07T23:59:59.000Z

    Enron Corp., Houston, in an extensive study of U.S. natural-gas supply and demand through the year 2000, has found that the U.S. gas-resource base is 1,200 tcf. Despite current weaknesses in natural-gas prices, demand growth will be strong although affected by oil-price assumptions. This paper reports on highlights in the areas of reserves and production which include gains in both categories in the Rockies/Wyoming, San Juan basin, and Norphlet trends (offshore Alabama). The Midcontinent/Hugoton area exhibits reserve declines in a period of flat production. In the U.S. Gulf Coast (USGC) offshore, both production and reserves decline over the forecast period. These projections are derived from a base-case price of $4.07/MMBTU by 2000. U.S. gas production exhibits a production decline in a low oil-price case from 19 to 16.4 tcf by 2000, if prices are 30% below the base case, that is, $2.93/MMBTU. Gains in commercial gas use are strong under either scenario of a base oil price of $29.80 in 1990 dollars in the year 2000 or a low oil price of $20.50 in 1990 dollars in 2000. Demand for natural gas for power generation grows as much as 1.5 tcf by 2000 in the Enron base case and by 300 bcf by 2000 in the low crude-oil price case.

  2. Market Response ModelsMarket Response Models Demand CreationDemand Creation

    E-Print Network [OSTI]

    Brock, David

    Market Response ModelsMarket Response Models andand Demand CreationDemand Creation Dominique MImportance of Marketing Investments Need for a Market Response focusNeed for a Market Response focus Digital data enriched acquisition and retention costsasymmetry between acquisition and retention costs In both cases, longIn both

  3. Reviving'demand+pull'perspec2ves:' The'effect'of'demand'uncertainty'and'

    E-Print Network [OSTI]

    Sussex, University of

    / Daniele&Rotolo& D.Rotolo@sussex.ac.uk/ Associate(Editors& Area& Florian&Kern& Energy& F.Kern@sussex.ac.ukReviving'demand+pull'perspec2ves:' The'effect'of'demand'uncertainty'and' stagnancy'on'R&D'strategy'which'case'the'Associate'Editors'may'decide'to'skip'internal'review'process.' Website' SWPS:'www.sussex.ac.uk

  4. Demand Responsive Lighting: A Scoping Study

    SciTech Connect (OSTI)

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-03T23:59:59.000Z

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

  5. ERCOT's Weather Sensitive Demand Response Pilot

    E-Print Network [OSTI]

    Carter, T.

    2013-01-01T23:59:59.000Z

    ERCOTs Weather Sensitive Demand Response Pilot CATEE 12-17-13 ESL-KT-13-12-21 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 Disclaimer The information contained in this report has been obtained from... services along with other information about our business is available online at constellation.com. ESL-KT-13-12-21 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 Demand Response in ERCOT CATEE 121313 - Tim Carter...

  6. Demand Response Initiatives at CPS Energy

    E-Print Network [OSTI]

    Luna, R.

    2013-01-01T23:59:59.000Z

    Demand Response Initiatives at CPS Energy Clean Air Through Energy Efficiency (CATEE) Conference December 17, 2013 ESL-KT-13-12-53 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 CPSEs DR Program DR... than the military bases and Toyota combined. Schools & Universities contributed 6 MWs of Demand Response in 2013. 2013 DR Participants Trinity University - $5,654 Fort Sam ISD - $18,860 Judson ISD - $45,540 Alamo Colleges - $98,222 UTSA - $168...

  7. Quantification of latent travel demand on new urban facilities in the state of Texas

    E-Print Network [OSTI]

    Henk, Russell H

    1989-01-01T23:59:59.000Z

    transportation facility was opened for use. The comparison of the photographs allowed for any changes in land use to be easily recognized. 15 Preliminar Anal sis of Variables Identification of Latent Travel Oemand The first step in this analysis of latent... facilities (3). Therefore, this highway characteristic was also included as a possible latent demand indicator. Detailed Anal sis of Variables In order to examine their relationships with latent travel demand on new urban transportation facilities...

  8. Demand for Environmentally-Friendly Durables

    E-Print Network [OSTI]

    Martin, Leslie Aimee

    2012-01-01T23:59:59.000Z

    PFC reduction Total CO2 emission reductions Annual Total (10annual emissions reductions in thousands of tons of CO2Emission Reductions (ERS) by 2012 in millions of tons of CO2

  9. MTBE demand as a oxygenated fuel additive

    SciTech Connect (OSTI)

    NONE

    1996-10-01T23:59:59.000Z

    The MTBE markets are in the state of flux. In the U.S. the demand has reached a plateau while in other parts of the world, it is increasing. The various factors why MTBE is experiencing a global shift will be examined and future volumes projected.

  10. INVENTORY MANAGEMENT WITH PARTIALLY OBSERVED NONSTATIONARY DEMAND

    E-Print Network [OSTI]

    Ludkovski, Mike

    INVENTORY MANAGEMENT WITH PARTIALLY OBSERVED NONSTATIONARY DEMAND ERHAN BAYRAKTAR AND MICHAEL LUDKOVSKI Abstract. We consider a continuous-time model for inventory management with Markov mod- ulated non inventory level. We then solve this equivalent formulation and directly characterize an optimal inventory

  11. CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY

    E-Print Network [OSTI]

    Energy Commission's preliminary forecasts for 2014­2024 electricity consumption and peak: Electricity Demand by Utility Planning Area MAY 2013 CEC-200-2013-004-SD-V2 Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P. Oglesby Executive

  12. Global Climate Change and Demand for Energy

    E-Print Network [OSTI]

    Subramanian, Venkat

    -CARES) Washington University in St. Louis #12;9 Jun Jul Aug Temperature Anomaly Distribution Frequency of air and water temperatures Losses of ice from Greenland and Antarctica Sea-level rise Energy demands 169 390 327 90 16 H2O, CO2, O3 Earth receives visible light from hot Sun and Earth radiates to space

  13. Value of Demand Response -Introduction Klaus Skytte

    E-Print Network [OSTI]

    of wind power. #12;Perspectives The System Operator Keep the balance Demand reduction = increased as indicator. #12;Motivations We want more wind power in the system. This require more flexibility of the rest plants and better use of wind power. Public goods / Externalities not measured in the markets #12

  14. Energy Demand (released in AEO2010)

    Reports and Publications (EIA)

    2010-01-01T23:59:59.000Z

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

  15. Machine Learning for Demand Forecasting in Smart Grid Saima Aman, Wei Yin, Yogesh Simmhan, and Viktor Prasanna

    E-Print Network [OSTI]

    Prasanna, Viktor K.

    planning and conservation. These experiments are part of the Los Angeles Smart Grid Demonstration ProjectMachine Learning for Demand Forecasting in Smart Grid Saima Aman, Wei Yin, Yogesh Simmhan of AMIs and data collection in a Smart Grid environment means that all applications, including demand

  16. A Simulation Study of Demand Responsive Transit System Design

    E-Print Network [OSTI]

    Dessouky, Maged

    A Simulation Study of Demand Responsive Transit System Design Luca Quadrifoglio, Maged M. Dessouky changed the landscape for demand responsive transit systems. First, the demand for this type of transit experiencing increased usage for demand responsive transit systems. The National Transit Summaries and Trends

  17. The Role of Demand Response Policy Forum Series

    E-Print Network [OSTI]

    California at Davis, University of

    The Role of Demand Response Policy Forum Series Beyond 33 Percent: California's Renewable Future and Demand Response #12;Historic focus on Seasonal Grid Stress PG&E Demand Bid Test Day 0 2000 4000 6000 8000 Communication Latency #12;Bottom Up Review of End-Use Loads for Demand Response 5 Commercial Residential

  18. AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.

    E-Print Network [OSTI]

    Povinelli, Richard J.

    AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

  19. Flexible Demand Management under Time-Varying Prices

    E-Print Network [OSTI]

    Liang, Yong

    2012-01-01T23:59:59.000Z

    planning, multi-periods procurement, optimal stopping problem, the demand management for the Smart Grid

  20. Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California

    E-Print Network [OSTI]

    Lekov, Alex

    2009-01-01T23:59:59.000Z

    in significant energy and demand savings for refrigeratedbe modified to reduce energy demand during demand responsein refrigerated warehouse energy demand if they are not

  1. Environmentally related water trading, transfers and environmental flows: welfare, water demand and flows

    E-Print Network [OSTI]

    Han, Man Seung

    2008-10-10T23:59:59.000Z

    by source, and the other by sector. Demand by source is comprised of two sources: existing source basins (DIVERSIONQ) and new source basins (USER IBT). The variable DIVERTERUSE designates total water diverted by a river location for each sector in a given... development of a Texas surface water model. The developed model incorporates: (a) uncertain weather patterns and supply of iv water; (b) river flows in most of the Texas river basins - twenty-one basins excluding only the Rio Grande; (c) demand for water...

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

    SciTech Connect (OSTI)

    Komiyama, Ryoichi; Marnay, Chris; Stadler, Michael; Lai, Judy; Borgeson, Sam; Coffey, Brian; Azevedo, Ines Lima

    2009-09-01T23:59:59.000Z

    In this analysis, the authors projected Japan's energy demand/supply and energy-related CO{sub 2} emissions to 2050. Their analysis of various scenarios indicated that Japan's CO{sub 2} emissions in 2050 could be potentially reduced by 26-58% from the current level (FY 2005). These results suggest that Japan could set a CO{sub 2} emission reduction target for 2050 at between 30% and 60%. In order to reduce CO{sub 2} emissions by 60% in 2050 from the present level, Japan will have to strongly promote energy conservation at the same pace as an annual rate of 1.9% after the oil crises (to cut primary energy demand per GDP (TPES/GDP) in 2050 by 60% from 2005) and expand the share of non-fossil energy sources in total primary energy supply in 2050 to 50% (to reduce CO{sub 2} emissions per primary energy demand (CO{sub 2}/TPES) in 2050 by 40% from 2005). Concerning power generation mix in 2050, nuclear power will account for 60%, solar and other renewable energy sources for 20%, hydro power for 10% and fossil-fired generation for 10%, indicating substantial shift away from fossil fuel in electric power supply. Among the mitigation measures in the case of reducing CO{sub 2} emissions by 60% in 2050, energy conservation will make the greatest contribution to the emission reduction, being followed by solar power, nuclear power and other renewable energy sources. In order to realize this massive CO{sub 2} abatement, however, Japan will have to overcome technological and economic challenges including the large-scale deployment of nuclear power and renewable technologies.

  3. A DISTRIBUTED INTELLIGENT AUTOMATED DEMAND RESPONSE BUILDING MANAGEMENT SYSTEM

    SciTech Connect (OSTI)

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

    2013-12-30T23:59:59.000Z

    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 buildings 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.

  4. MUJERES TOTAL BIOLOGIA 16 27

    E-Print Network [OSTI]

    Autonoma de Madrid, Universidad

    , PLASTICA Y VISUAL 2 2 EDUCACION FISICA, DEPORTE Y MOTRICIDAD HUMANA 1 1 6 11 TOTAL CIENCIAS N DE TESIS

  5. MUJERES ( * ) TOTAL BIOLOGA 16 22

    E-Print Network [OSTI]

    Autonoma de Madrid, Universidad

    , DEPORTE Y MOTRICIDAD HUMANA 0 4 TOTAL FORMACIN DE PROFESORADO Y EDUCACIN 0 6 ANATOMA PATOLGICA 2 5

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

    SciTech Connect (OSTI)

    Neubauer, J.; Simpson, M.

    2013-10-01T23:59:59.000Z

    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.

  7. The Total RNA Story Introduction

    E-Print Network [OSTI]

    Goldman, Steven A.

    The Total RNA Story Introduction Assessing RNA sample quality as a routine part of the gene about RNA sample quality. Data from a high quality total RNA preparation Although a wide variety RNA data interpretation and identify features from total RNA electropherograms that reveal information

  8. New Demand for Old Food: the U.S. Demand for Olive Oil Bo Xiong, William Matthews, Daniel Sumner

    E-Print Network [OSTI]

    Schladow, S. Geoffrey

    New Demand for Old Food: the U.S. Demand for Olive Oil Bo Xiong, William Matthews, Daniel Sumner, demand for oils differentiated by origin and quality is price-elastic. These olive oils are highly of olive oil and the spread of Mediterranean diet contribute significantly to the rising demand

  9. Home Network Technologies and Automating Demand Response

    E-Print Network [OSTI]

    McParland, Charles

    2010-01-01T23:59:59.000Z

    Application / Profile API included in standard PresentationApplication API included in standard Part of standard PartApplication / Profile API included in standard Part of

  10. Demand management : a cross-industry analysis of supply-demand planning

    E-Print Network [OSTI]

    Tan, Peng Kuan

    2006-01-01T23:59:59.000Z

    Globalization increases product variety and shortens product life cycles. These lead to an increase in demand uncertainty and variability. Outsourcing to low-cost countries increases supply lead-time and supply uncertainty ...

  11. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal StocksProved Reserves (Billion Cubic Feet)Wellhead0 Capability to.5

  12. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal StocksProved Reserves (Billion Cubic Feet)Wellhead0 Capability to.54 End

  13. Opportunities for Demand Response in California Agricultural Irrigation: A Scoping Study

    SciTech Connect (OSTI)

    Marks, Gary; Wilcox, Edmund; Olsen, Daniel; Goli, Sasank

    2013-01-02T23:59:59.000Z

    California agricultural irrigation consumes more than ten billion kilowatt hours of electricity annually and has significant potential for contributing to a reduction of stress on the grid through demand response, permanent load shifting, and energy efficiency measures. To understand this potential, a scoping study was initiated for the purpose of determining the associated opportunities, potential, and adoption challenges in California agricultural irrigation. The primary research for this study was conducted in two ways. First, data was gathered and parsed from published sources that shed light on where the best opportunities for load shifting and demand response lie within the agricultural irrigation sector. Secondly, a small limited survey was conducted as informal face-to-face interviews with several different California growers to get an idea of their ability and willingness to participate in permanent load shifting and/or demand response programs. Analysis of the data obtained from published sources and the survey reveal demand response and permanent load shifting opportunities by growing region, irrigation source, irrigation method, grower size, and utility coverage. The study examines some solutions for demand response and permanent load shifting in agricultural irrigation, which include adequate irrigation system capacity, automatic controls, variable frequency drives, and the contribution from energy efficiency measures. The study further examines the potential and challenges for grower acceptance of demand response and permanent load shifting in California agricultural irrigation. As part of the examination, the study considers to what extent permanent load shifting, which is already somewhat accepted within the agricultural sector, mitigates the need or benefit of demand response for agricultural irrigation. Recommendations for further study include studies on how to gain grower acceptance of demand response as well as other related studies such as conducting a more comprehensive survey of California growers.

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

    SciTech Connect (OSTI)

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

    2014-06-01T23:59:59.000Z

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

  15. Only tough choices in Meeting growing demand

    SciTech Connect (OSTI)

    NONE

    2007-12-15T23:59:59.000Z

    U.S. electricity demand is not growing very fast by international or historical standards. Yet meeting this relatively modest growth is proving difficult because investment in new capacity is expected to grow at an even slower pace. What is more worrisome is that a confluence of factors has added considerable uncertainties, making the investment community less willing to make the long-term commitments that will be needed during the coming decade.

  16. What is a High Electric Demand Day?

    Broader source: Energy.gov [DOE]

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

  17. Flexible system development strategies for the Chuo Shinkansen Maglev Project : dealing with uncertain demand and R&D outcomes

    E-Print Network [OSTI]

    Ishii, Masaki, S.M. Massachusetts Institute of Technology

    2007-01-01T23:59:59.000Z

    As a large-scale, long-term transportation project, the Chuo Shinkansen Maglev Project in Japan includes various uncertainties. Among them, two major uncertainties are identified in this thesis: the uncertainty of demand ...

  18. Statewide Electricity and Demand Capacity Savings from the Implementation of IECC Code in Texas: Analysis for Single-Family Residences

    E-Print Network [OSTI]

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

    2011-01-01T23:59:59.000Z

    This paper presents estimates of the statewide electricity and electric demand savings achieved from the adoption of the International Energy Conservation Code (IECC) for single-family residences in Texas and includes the corresponding increase...

  19. Use of Statistical Approach to Design an Optimal Duct System for On-demand Industrial Exhaust Ventilation

    E-Print Network [OSTI]

    Litomisky, A.

    2010-01-01T23:59:59.000Z

    This paper elaborates on how to use statistics to calculate optimal parameters (including duct diameters) of energy-efficient industrial ventilation systems. Based on the fan-law, on-demand ventilation can save up to 80% ...

  20. Use of Statistical Approach to Design an Optimal Duct System for On-demand Industrial Exhaust Ventilation

    E-Print Network [OSTI]

    Litomisky, A.

    2010-01-01T23:59:59.000Z

    This paper elaborates on how to use statistics to calculate optimal parameters (including duct diameters) of energy-efficient industrial ventilation systems. Based on the fan-law, on-demand ventilation can save up to 80% of electricity compared...

  1. Architecture Concepts and Technical Issues for an Open,Interoperable Automated Demand Response Infrastructure

    SciTech Connect (OSTI)

    Koch, Ed; Piette, Mary Ann

    2007-10-01T23:59:59.000Z

    This paper presents the technical and architectural issues associated with automating Demand Response (DR) programs. The paper focuses on a description of the Demand Response Automation Server (DRAS), which is the main component used to automate the interactions between the Utilities and their customers for DR programs. Use cases are presented that show the role of the DRAS in automating various aspects of DR programs. This paper also describes the various technical aspects of the DRAS including its interfaces and major modes of operation. This includes how the DRAS supports automating such Utility/Customer interactions as automated DR bidding, automated DR event handling, and finally real-time pricing.

  2. Positron interactions with watertotal elastic, total inelastic, and elastic differential cross section measurements

    SciTech Connect (OSTI)

    Tattersall, Wade [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia) [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia); Centre for Antimatter-Matter Studies, School of Engineering and Physical Sciences, James Cook University, Townsville, 4810 Queensland (Australia); Chiari, Luca [Centre for Antimatter-Matter Studies, School of Chemical and Physical Sciences, Flinders University, GPO Box 2100, Adelaide 5001, South Australia (Australia)] [Centre for Antimatter-Matter Studies, School of Chemical and Physical Sciences, Flinders University, GPO Box 2100, Adelaide 5001, South Australia (Australia); Machacek, J. R.; Anderson, Emma; Sullivan, James P. [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia)] [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia); White, Ron D. [Centre for Antimatter-Matter Studies, School of Engineering and Physical Sciences, James Cook University, Townsville, 4810 Queensland (Australia)] [Centre for Antimatter-Matter Studies, School of Engineering and Physical Sciences, James Cook University, Townsville, 4810 Queensland (Australia); Brunger, M. J. [Centre for Antimatter-Matter Studies, School of Chemical and Physical Sciences, Flinders University, GPO Box 2100, Adelaide 5001, South Australia (Australia) [Centre for Antimatter-Matter Studies, School of Chemical and Physical Sciences, Flinders University, GPO Box 2100, Adelaide 5001, South Australia (Australia); Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur (Malaysia); Buckman, Stephen J. [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia) [Centre for Antimatter-Matter Studies, Research School of Physics and Engineering, The Australian National University, Canberra, ACT 0200 (Australia); Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur (Malaysia); Garcia, Gustavo [Instituto de F?sica Fundamental, Consejo Superior de Investigationes Cient?ficas (CSIC), Serrano 113-bis, E-28006 Madrid (Spain)] [Instituto de F?sica Fundamental, Consejo Superior de Investigationes Cient?ficas (CSIC), Serrano 113-bis, E-28006 Madrid (Spain); Blanco, Francisco [Departamento de F?sica Atomica, Molecular y Nuclear, Universidad Complutense de Madrid, E-28040 Madrid (Spain)] [Departamento de F?sica Atomica, Molecular y Nuclear, Universidad Complutense de Madrid, E-28040 Madrid (Spain)

    2014-01-28T23:59:59.000Z

    Utilising a high-resolution, trap-based positron beam, we have measured both elastic and inelastic scattering of positrons from water vapour. The measurements comprise differential elastic, total elastic, and total inelastic (not including positronium formation) absolute cross sections. The energy range investigated is from 1 eV to 60 eV. Comparison with theory is made with both R-Matrix and distorted wave calculations, and with our own application of the Independent Atom Model for positron interactions.

  3. Demand Response Opportunities in Industrial Refrigerated Warehouses in California

    SciTech Connect (OSTI)

    Goli, Sasank; McKane, Aimee; Olsen, Daniel

    2011-06-14T23:59:59.000Z

    Industrial refrigerated warehouses that implemented energy efficiency measures and have centralized control systems can be excellent candidates for Automated Demand Response (Auto-DR) due to equipment synergies, and receptivity of facility managers to strategies that control energy costs without disrupting facility operations. Auto-DR utilizes OpenADR protocol for continuous and open communication signals over internet, allowing facilities to automate their Demand Response (DR). Refrigerated warehouses were selected for research because: They have significant power demand especially during utility peak periods; most processes are not sensitive to short-term (2-4 hours) lower power and DR activities are often not disruptive to facility operations; the number of processes is limited and well understood; and past experience with some DR strategies successful in commercial buildings may apply to refrigerated warehouses. This paper presents an overview of the potential for load sheds and shifts from baseline electricity use in response to DR events, along with physical configurations and operating characteristics of refrigerated warehouses. Analysis of data from two case studies and nine facilities in Pacific Gas and Electric territory, confirmed the DR abilities inherent to refrigerated warehouses but showed significant variation across facilities. Further, while load from California's refrigerated warehouses in 2008 was 360 MW with estimated DR potential of 45-90 MW, actual achieved was much less due to low participation. Efforts to overcome barriers to increased participation may include, improved marketing and recruitment of potential DR sites, better alignment and emphasis on financial benefits of participation, and use of Auto-DR to increase consistency of participation.

  4. Total..........................................................

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

    Q 0.4 3 or More Units... 5.4 0.3 Q Q Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  5. Total..........................................................

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

    ... 1.9 1.1 Q Q 0.3 Q Do Not Use Central Air-Conditioning... 45.2 24.6 3.6 5.0 8.8 3.2 Use a Programmable...

  6. Total..........................................................

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

    Q 0.6 3 or More Units... 5.4 3.8 2.9 0.4 Q N 0.2 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  7. Total..........................................................

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

    1.3 Q 3 or More Units... 5.4 1.6 0.8 Q 0.3 0.3 Q Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  8. Total..........................................................

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

    3 or More Units... 5.4 2.4 1.4 0.7 0.9 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  9. Total..........................................................

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

    3 or More Units... 5.4 2.3 1.7 0.6 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  10. Total..........................................................

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

    8.6 Have Equipment But Do Not Use it... 1.9 Q Q Q Q 0.6 0.4 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System......

  11. Total..........................................................

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

    3 or More Units... 5.4 2.1 0.9 0.2 1.0 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  12. Total..........................................................

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

    30.3 Have Equipment But Do Not Use it... 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Type of Air-Conditioning Equipment 1, 2 Central System......

  13. Total..........................................................

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

    0.3 3 or More Units... 5.4 0.7 0.5 Q Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  14. Total..........................................................

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

    3 or More Units... 5.4 2.3 0.7 2.1 0.3 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  15. Total..........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    111.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer... 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer......

  16. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer......

  17. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    Personal Computers Do Not Use a Personal Computer... 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer... 75.6...

  18. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer... 35.5 8.1 5.6 2.5 Use a Personal Computer......

  19. Total..........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer... 35.5 6.4 2.2 4.2 Use a Personal Computer......

  20. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    ..... 111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer......

  1. Total..........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer... 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer......

  2. Total..........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    1.3 0.8 0.5 Once a Day... 19.2 4.6 3.0 1.6 Between Once a Day and Once a Week... 32.0 8.9 6.3 2.6 Once a...

  3. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    AppliancesTools.... 56.2 11.6 3.3 8.2 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 0.2 Q 0.1 Hot Tub or Spa......

  4. Total..........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    Tools... 56.2 20.5 10.8 3.6 6.1 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 N N N N Hot Tub or Spa......

  5. Total..........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    Tools... 56.2 27.2 10.6 9.3 9.2 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 Q Q Q 0.4 Hot Tub or Spa......

  6. Total..........................................................

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

    AppliancesTools.... 56.2 12.2 9.4 2.8 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 Q Q Q Hot Tub or Spa......

  7. Total..........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

    1.3 3.8 Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line Eligible for Federal Assistance 1 40,000 to 59,999 60,000 to 79,999 80,000...

  8. Total..............................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6 2,720

  9. Total................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6 2,720..

  10. Total........................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6 2,720..

  11. Total..........................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6

  12. Total...........................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q Table

  13. Total...........................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q TableQ

  14. Total...........................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q

  15. Total...........................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q26.7

  16. Total............................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1

  17. Total............................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1

  18. Total.............................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7 28.8 20.6

  19. Total..............................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7 28.8

  20. Total..............................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7 28.8,171

  1. Total...............................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7

  2. Total...............................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.7 21.7

  3. Total...............................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.7

  4. Total...............................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.747.1

  5. Total...............................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.747.1Do

  6. Total................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.747.1Do

  7. Total.................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.

  8. Total.................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4 12.5 12.5

  9. Total.................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4 12.5

  10. Total..................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4 12.578.1

  11. Total..................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4

  12. Total..................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4. 111.1 14.7

  13. Total...................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4. 111.1

  14. Total...................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4. 111.115.2

  15. Total...................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4.

  16. Total...................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7

  17. Total...................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,033 1,618

  18. Total....................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,033 1,61814.7

  19. Total.......................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,033

  20. Total.......................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.6 17.7

  1. Total.......................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.6 17.74.2

  2. Total........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.6

  3. Total........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.615.1 5.5

  4. Total........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.615.1

  5. Total........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.615.10.7

  6. Total........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:

  7. Total........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not Have

  8. Total........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not Have7.1

  9. Total.........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not

  10. Total..........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not25.6 40.7

  11. Total..........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not25.6

  12. Total..........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not25.65.6

  13. Total..........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do

  14. Total..........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.6 16.6

  15. Total..........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.6

  16. Total..........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.67.1

  17. Total...........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.67.10.6

  18. Total...........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2

  19. Total...........................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.24.2 7.6

  20. Total.............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.24.2

  1. Total.............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.24.2Cooking

  2. Total.............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1

  3. Total.............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not Have

  4. Total.............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not HaveDo

  5. Total.............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not HaveDoDo

  6. Total.............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not

  7. Total.............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo Not

  8. Total..............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo Not

  9. Total..............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo Not20.6

  10. Total..............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo

  11. Total..............................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1 19.0

  12. Total.................................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1

  13. Total.................................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1...

  14. Total....................................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do

  15. Total....................................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1DoCooking

  16. Total....................................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1DoCooking25.6

  17. Total....................................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1DoCooking25.65.6

  18. Total....................................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0

  19. Total....................................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6 Personal

  20. Total....................................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6 Personal

  1. Total.........................................................................................

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6

  2. Total

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear JanYear Jan Feb Mar Apr May(MillionFeet)July 23,

  3. Total

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear JanYear Jan Feb Mar Apr May(MillionFeet)July 23,Product:

  4. Total..............................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720 1,970

  5. Total................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720

  6. Total........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720 111.1

  7. Total..........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720

  8. Total...........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q Table

  9. Total...........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q

  10. Total...........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q14.7

  11. Total...........................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6

  12. Total............................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1

  13. Total............................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1

  14. Total.............................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8 20.6

  15. Total..............................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8 20.6,171

  16. Total..............................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8

  17. Total...............................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.6 25.6

  18. Total...............................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.6

  19. Total...............................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.626.7

  20. Total...............................................................

    Annual Energy Outlook 2013 [U.S. Energy Information Administration (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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7