Sample records for tiered demand charges

  1. Managing Increased Charging Demand

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't YourTransport(FactDepartment ofLetterEconomyDr.Energy University Managing Increased Charging

  2. Demand Charges | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOE Facility DatabaseMichigan: Energy Resources Jump to:Delta, Ohio:Charges Jump

  3. Property:OpenEI/UtilityRate/DemandRateStructure/Tier2Max | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformation Tier2Max Jump to: navigation,

  4. Property:OpenEI/UtilityRate/DemandRateStructure/Tier2Rate | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformation Tier2Max Jump to:

  5. Property:OpenEI/UtilityRate/DemandRateStructure/Tier3Adjustment | Open

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformation Tier2Max Jump to:Energy

  6. Property:OpenEI/UtilityRate/DemandRateStructure/Tier3Max | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformation Tier2Max Jump

  7. Property:OpenEI/UtilityRate/DemandRateStructure/Tier3Rate | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformation Tier2Max JumpInformation

  8. Property:OpenEI/UtilityRate/DemandRateStructure/Tier4Adjustment | Open

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformation Tier2Max

  9. Property:OpenEI/UtilityRate/DemandRateStructure/Tier4Max | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformation Tier2Max

  10. Property:OpenEI/UtilityRate/DemandRateStructure/Tier4Rate | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformation Tier2MaxInformation

  11. Property:OpenEI/UtilityRate/DemandRateStructure/Tier5Adjustment | Open

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformation Tier2MaxInformationEnergy

  12. Reducing Electricity Demand Charge for Data Centers with Partial Execution

    E-Print Network [OSTI]

    Li, Baochun

    . INTRODUCTION Data centers are the powerhouse behind many Internet services today. A modern data centerReducing Electricity Demand Charge for Data Centers with Partial Execution Hong Xu Department@eecg.toronto.edu ABSTRACT Data centers consume a large amount of energy and incur substantial electricity cost

  13. Brussels, Belgium, November 19-22, 2012 Energy Demand Prediction in a Charge Station: A

    E-Print Network [OSTI]

    Boyer, Edmond

    EEVC Brussels, Belgium, November 19-22, 2012 Energy Demand Prediction in a Charge Station over a real database which can be associated with the energy demand generated by electric vehicles simplifying assumptions about the EV drivers' energy demand. To improve the accuracy of the modelling

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

    Open Energy Info (EERE)

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

  15. Demand charge schedule data | OpenEI Community

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluating A Potential Microhydro SiteDayton Power & LightDemand ManagementDemand

  16. 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.

  17. Deployment of Behind-The-Meter Energy Storage for Demand Charge Reduction

    SciTech Connect (OSTI)

    Neubauer, J.; Simpson, M.

    2015-01-01T23:59:59.000Z

    This study investigates how economically motivated customers will use energy storage for demand charge reduction, as well as how this changes in the presence of on-site photovoltaic power generation, to investigate the possible effects of incentivizing increased quantities of behind-the-meter storage. It finds that small, short-duration batteries are most cost effective regardless of solar power levels, serving to reduce short load spikes on the order of 2.5% of peak demand. While profitable to the customer, such action is unlikely to adequately benefit the utility as may be desired, thus highlighting the need for modified utility rate structures or properly structured incentives.

  18. Tier identification (TID) for tiered memory characteristics

    DOE Patents [OSTI]

    Chang, Jichuan; Lim, Kevin T; Ranganathan, Parthasarathy

    2014-03-25T23:59:59.000Z

    A tier identification (TID) is to indicate a characteristic of a memory region associated with a virtual address in a tiered memory system. A thread may be serviced according to a first path based on the TID indicating a first characteristic. The thread may be serviced according to a second path based on the TID indicating a second characteristic.

  19. Design for implementation : fully integrated charging & docking infrastructure used in Mobility-on-Demand electric vehicle fleets

    E-Print Network [OSTI]

    Martin, Jean Mario Nations

    2012-01-01T23:59:59.000Z

    As the technology used in electric vehicles continues to advance, there is an increased demand for urban-appropriate electric charging stations emphasizing a modern user interface, robust design, and reliable functionality. ...

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

    E-Print Network [OSTI]

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

    rebate and maintenance programs for many years. The purpose of these programs was to improve the efficiency of the stock of air conditioning equipment and provide better demand-side management. This paper examines the effect of refrigerant charging... increases. The cooling load is assumed to be zero at an outdoor temperature of 70 F. This would assume an internal heat gain equal to approximately 8 F if the thermostat setting is at 78 F. The house load is also assumed to be equal to the test unit...

  1. Property:OpenEI/UtilityRate/DemandChargePeriod3 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump Jump to:DemandChargePeriod3 Jump to:

  2. Property:OpenEI/UtilityRate/DemandChargePeriod3FAdj | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump Jump to:DemandChargePeriod3 Jump

  3. Property:OpenEI/UtilityRate/DemandChargePeriod4 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump Jump to:DemandChargePeriod3

  4. Property:OpenEI/UtilityRate/DemandChargePeriod5 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump JumpDemandChargePeriod5 Jump to:

  5. Property:OpenEI/UtilityRate/DemandChargePeriod5FAdj | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump JumpDemandChargePeriod5 Jump

  6. Property:OpenEI/UtilityRate/DemandChargePeriod6 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump JumpDemandChargePeriod5

  7. Property:OpenEI/UtilityRate/DemandChargePeriod6FAdj | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump JumpDemandChargePeriod5Information

  8. Property:OpenEI/UtilityRate/DemandReactivePowerCharge | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to: navigation, search This is a

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to: navigation, search This

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerChargeInformation Rate Jump to:Information

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerChargeInformation Rate Jump

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerChargeInformation Rate JumpInformation 1

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerChargeInformation Rate JumpInformation

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerChargeInformation Rate

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerChargeInformation RateInformation

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerChargeInformation

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerChargeInformationInformation

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerChargeInformationInformationInformation

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8 Jump to: navigation, search

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8 Jump to: navigation,

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

    SciTech Connect (OSTI)

    Jeffrey Wishart

    2012-02-01T23:59:59.000Z

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

  2. Electricity Demand of PHEVs Operated by Private Households and Commercial Fleets: Effects of Driving and Charging Behavior

    SciTech Connect (OSTI)

    John Smart; Matthew Shirk; Ken Kurani; Casey Quinn; Jamie Davies

    2010-11-01T23:59:59.000Z

    Automotive and energy researchers have made considerable efforts to predict the impact of plug-in hybrid vehicle (PHEV) charging on the electrical grid. This work has been done primarily through computer modeling and simulation. The US Department of Energy’s (DOE) Advanced Vehicle Testing Activity (AVTA), in partnership with the University of California at Davis’s Institute for Transportation Stuides, have been collecting data from a diverse fleet of PHEVs. The AVTA is conducted by the Idaho National Laboratory for DOE’s Vehicle Technologies Program. This work provides the opportunity to quantify the petroleum displacement potential of early PHEV models, and also observe, rather than simulate, the charging behavior of vehicle users. This paper presents actual charging behavior and the resulting electricity demand from these PHEVs operating in undirected, real-world conditions. Charging patterns are examined for both commercial-use and personal-use vehicles. Underlying reasons for charging behavior in both groups are also presented.

  3. Property:OpenEI/UtilityRate/EnergyRateStructure/Tier4Adjustment | Open

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge JumpEnergy Information Tier4Adjustment

  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. Deep Burn Fuel Cycle Integration: Evaluation of Two-Tier Scenarios

    SciTech Connect (OSTI)

    S. Bays; H. Zhang; M. Pope

    2009-05-01T23:59:59.000Z

    The use of a deep burn strategy using VHTRs (or DB-MHR), as a means of burning transuranics produced by LWRs, was compared to performing this task with LWR MOX. The spent DB-MHR fuel was recycled for ultimate final recycle in fast reactors (ARRs). This report summarizes the preliminary findings of the support ratio (in terms of MWth installed) between LWRs, DB-MHRs and ARRs in an equilibrium “two-tier” fuel cycle scenario. Values from literature were used to represent the LWR and DB-MHR isotopic compositions. A reactor physics simulation of the ARR was analyzed to determine the effect that the DB-MHR spent fuel cooling time on the ARR transuranic consumption rate. These results suggest that the cooling time has some but not a significant impact on the ARRs conversion ratio and transuranic consumption rate. This is attributed to fissile worth being derived from non-fissile or “threshold-fissioning” isotopes in the ARR’s fast spectrum. The fraction of installed thermal capacity of each reactor in the DB-MHR 2-tier fuel cycle was compared with that of an equivalent MOX 2-tier fuel cycle, assuming fuel supply and demand are in equilibrium. The use of DB-MHRs in the 1st-tier allows for a 10% increase in the fraction of fleet installed capacity of UO2-fueled LWRs compared to using a MOX 1st-tier. Also, it was found that because the DB-MHR derives more power per unit mass of transuranics charged to the fresh fuel, the “front-end” reprocessing demand is less than MOX. Therefore, more fleet installed capacity of DB-MHR would be required to support a given fleet of UO2 LWRs than would be required of MOX plants. However, the transuranic deep burn achieved by DB-MHRs reduces the number of fast reactors in the 2nd-tier to support the DB-MHRs “back-end” transuranic output than if MOX plants were used. Further analysis of the relative costs of these various types of reactors is required before a comparative study of these options could be considered complete.

  6. Deployment of Behind-The-Meter Energy Storage for Demand Charge...

    Office of Scientific and Technical Information (OSTI)

    It finds that small, short-duration batteries are most cost effective regardless of solar power levels, serving to reduce short load spikes on the order of 2.5% of peak demand....

  7. Stackelberg Game based Demand Response for At-Home Electric Vehicle Charging

    E-Print Network [OSTI]

    Bahk, Saewoong

    Member, IEEE Abstract--Consumer electricity consumption can be controlled through electricity prices and customers respond accordingly with their electricity consumption levels. In particular, the demands as a game [7]. Note that in reality, electricity retailers are significantly regulated by governments

  8. AVTA: EVSE Charging Protocol for On and Off-Peak Demand | Department of

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny: The Future of1 A Strategic26-OPAMATTENDEEES:of Energy ChargePoint

  9. Data:E6aa536b-26f2-4af1-842e-2208eef78c6e | Open Energy Information

    Open Energy Info (EERE)

    of the cooperative. Demand Charge Distribution Delivery Service Demand Charge + Electricity Supply Service Demand Charge. Tiered Rates Distribution Delivery Service...

  10. Contract and Tiered Rate Methodology Overview

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

    2 Energy HLH 3,963,968 Tier 2 Energy HLH -655,344 Tier 1 Energy HLH 3,308,624 Tier 1 HLH SSL 5,304,441 3,543,617,448 Tier 1 HLH Load Shaping -1,995,817 kWh @ 0.04032 (80,471)...

  11. Pricing and bandwidth allocation problems in wireless multi-tier networks

    E-Print Network [OSTI]

    Boyer, Edmond

    Pricing and bandwidth allocation problems in wireless multi-tier networks Camila Maria Gabriel- tecture changes to cope with high throughput, energy and cost- efficiency demands. Emerging solutions. In these heterogeneous networks, we study the joint service pricing and bandwidth allocation problem at the operator

  12. 3TIER | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapersWindey Wind6:00-06:00 U.S. National SoftwareE Place:3TIER Jump

  13. Attaining Tier 2 Emissions Through Diesel Engine and Aftertreatment...

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

    Attaining Tier 2 Emissions Through Diesel Engine and Aftertreatment Integration - Strategy and Experimental Results Attaining Tier 2 Emissions Through Diesel Engine and...

  14. Towards Highly Available ThreeTier Monitoring Applications (Extended Abstract)

    E-Print Network [OSTI]

    Dolev, Danny

    dispatched at the middle tier. They monitor the target agents and other monitoring components accumulating

  15. 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...

  16. Hybrid Access Control Mechanism in Two-Tier Femtocell Networks

    E-Print Network [OSTI]

    Mantravadi, Sirisha 1987-

    2012-08-21T23:59:59.000Z

    remains a challenge. Decentralized strategies such as femtocell access control have been identified as an effective means to mitigate cross-tier interference in two-tier networks. Femtocells can be configured to be either open access or closed access...

  17. 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

  18. An Economic Model for Pricing Tiered Network Services

    E-Print Network [OSTI]

    An Economic Model for Pricing Tiered Network Services Qian Lv, George N. Rouskas Department networks offering tiered services and corresponding price structures, a model that has become preva- lent-) optimal service tiers, we then employ game-theoretic techniques to find an optimal price for each service

  19. Tier II Canada Research Chair Migration and Ethnic Relations

    E-Print Network [OSTI]

    Sinnamon, Gordon J.

    Tier II Canada Research Chair in Migration and Ethnic Relations Faculty of Social Science Western University The Faculty of Social Science at Western University invites applications for a Tier II Canada for Tier II Canada Research Chairs, the candidate will hold a PhD (obtained within the last ten years

  20. Tier II Canada Research Chair Financial Econometrics

    E-Print Network [OSTI]

    Sinnamon, Gordon J.

    Tier II Canada Research Chair in Financial Econometrics The University of Western Ontario Research Chair in the area of Financial Econometrics, at the rank of probationary (tenure-track) Assistant: Labour Economics, Macroeconomics, Micro Theory and Econometrics. Quantitative Finance is an area

  1. 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.

  2. Automated Demand Response Technologies and Demonstration in New York City using OpenADR

    E-Print Network [OSTI]

    Kim, Joyce Jihyun

    2014-01-01T23:59:59.000Z

    customers need to reduce energy demand during expensiveadditive) $11.42 / kW-max demand Energy Delivery Charges Alltype, floor space, peak demand, energy supplier, DR program

  3. U-247: EMC Cloud Tiering Appliance Flaw Lets Remote Users Bypass...

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

    7: EMC Cloud Tiering Appliance Flaw Lets Remote Users Bypass Authentication and Gain Administrative Access U-247: EMC Cloud Tiering Appliance Flaw Lets Remote Users Bypass...

  4. Canada Research Chair, Tier II in Economics of Sustainable Development

    E-Print Network [OSTI]

    Martin, Jeff

    Canada Research Chair, Tier II in Economics of Sustainable Development The University of Winnipeg has designated a Tier II Canada Research Chair in the Economics of Sustainable Development within and enhanced research support. The Canada Research Chair program was established by the Government of Canada

  5. Tier I Canada Research Chair Human Capital and Productivity

    E-Print Network [OSTI]

    Lennard, William N.

    Tier I Canada Research Chair in Human Capital and Productivity The University of Western Ontario and international candidates for a Tier I Canada Research Chair in the area of Human Capital and Productivity renowned group of economists who work on research related to human capital and productivity. This includes

  6. Data:7261da4b-8aec-4bf4-8c81-e7599dcd5a17 | Open Energy Information

    Open Energy Info (EERE)

    demand delivered @ 9.00 per month Tiered Rates Distribution Energy Delivery Charges + Electricity Supply Service Charge. The amount of charges calculated at the above rate is...

  7. Demand Response and Open Automated Demand Response

    E-Print Network [OSTI]

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

  8. Serving database information using a flexible server in a three tier architecture

    SciTech Connect (OSTI)

    Lee Lueking et al.

    2003-08-11T23:59:59.000Z

    The D0 experiment at Fermilab relies on a central Oracle database for storing all detector calibration information. Access to this data is needed by hundreds of physics applications distributed worldwide. In order to meet the demands of these applications from scarce resources, we have created a distributed system that isolates the user applications from the database facilities. This system, known as the Database Application Network (DAN) operates as the middle tier in a three tier architecture. A DAN server employs a hierarchical caching scheme and database connection management facility that limits access to the database resource. The modular design allows for caching strategies and database access components to be determined by runtime configuration. To solve scalability problems, a proxy database component allows for DAN servers to be arranged in a hierarchy. Also included is an event based monitoring system that is currently being used to collect statistics for performance analysis and problem diagnosis. DAN servers are currently implemented as a Python multithreaded program using CORBA for network communications and interface specification. The requirement details, design, and implementation of DAN are discussed along with operational experience and future plans.

  9. Electric Demand Cost Versus Labor Cost: A Case Study

    E-Print Network [OSTI]

    Agrawal, S.; Jensen, R.

    Electric Utility companies charge industrial clients for two things: demand and usage. Depending on type of business and hours operation, demand cost could be very high. Most of the operations scheduling in a plant is achieved considering labor cost...

  10. 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

  11. Retrospective on the Seniors' Council Tier 1 LDRD portfolio.

    SciTech Connect (OSTI)

    Ballard, William Parker

    2012-04-01T23:59:59.000Z

    This report describes the Tier 1 LDRD portfolio, administered by the Seniors Council between 2003 and 2011. 73 projects were sponsored over the 9 years of the portfolio at a cost of $10.5 million which includes $1.9M of a special effort in directed innovation targeted at climate change and cyber security. Two of these Tier 1 efforts were the seeds for the Grand Challenge LDRDs in Quantum Computing and Next Generation Photovoltaic conversion. A few LDRDs were terminated early when it appeared clear that the research was not going to succeed. A great many more were successful and led to full Tier 2 LDRDs or direct customer sponsorship. Over a dozen patents are in various stages of prosecution from this work, and one project is being submitted for an R and D 100 award.

  12. Application of a Diesel Fuel Reformer for Tier 2 Bin 5 Emissions

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

    of a Diesel Fuel Reformer for Tier 2 Bin 5 Emissions APPROACH On-board diesel fuel reformation is being evaluated as an alternative to urea SCR to meet Tier 2 Bin 5 emissions...

  13. Cummins Next Generation Tier 2, Bin 2 Light Truck Diesel engine...

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

    Cummins Next Generation Tier 2, Bin 2 Light Truck Diesel engine Cummins Next Generation Tier 2, Bin 2 Light Truck Diesel engine Discusses plan, baselining, and modeling, for new...

  14. ATP-LD; Cummins Next Generation Tier 2 Bin 2 Diesel Engine |...

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

    & Publications Vehicle Technologies Office Merit Review 2014: ATP-LD; Cummins Next Generation Tier 2 Bin 2 Diesel Engine ATP-LD; Cummins Next Generation Tier 2 Bin 2 Diesel...

  15. Cummins' Next Generation Tier 2, Bin 2 Light Truck Diesel Engine...

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

    Cummins' Next Generation Tier 2, Bin 2 Light Truck Diesel Engine Cummins' Next Generation Tier 2, Bin 2 Light Truck Diesel Engine Development of a new light truck, in-line...

  16. ATP-LD; Cummins Next Generation Tier 2 Bin 2 Diesel Engine |...

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

    Peer Evaluation ace061ruth2011o.pdf More Documents & Publications ATP-LD; Cummins Next Generation Tier 2 Bin 2 Diesel Engine ATP-LD; Cummins Next Generation Tier 2 Bin 2 Diesel...

  17. Biodiesel Effects on the Operation of U.S. Light Duty Tier 2...

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

    Biodiesel Effects on the Operation of U.S. Light Duty Tier 2 Engine and Aftertreatment Systems Biodiesel Effects on the Operation of U.S. Light Duty Tier 2 Engine and...

  18. Biodiesel Effects on the Operation of U.S. Light-Duty Tier 2...

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

    Biodiesel Effects on the Operation of U.S. Light-Duty Tier 2 Engine and Aftertreatment Systems Biodiesel Effects on the Operation of U.S. Light-Duty Tier 2 Engine and...

  19. Property:OpenEI/UtilityRate/DemandRateStructure/Tier1Adjustment | Open

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations JumpInformationEnergy Information

  20. Property:OpenEI/UtilityRate/DemandRateStructure/Tier1Max | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations JumpInformationEnergy

  1. Property:OpenEI/UtilityRate/DemandRateStructure/Tier1Rate | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations JumpInformationEnergyInformation

  2. Property:OpenEI/UtilityRate/DemandRateStructure/Tier2Adjustment | Open

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations

  3. Property:OpenEI/UtilityRate/DemandRateStructure/Tier5Max | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformation

  4. Property:OpenEI/UtilityRate/DemandRateStructure/Tier5Rate | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformationInformation

  5. Property:OpenEI/UtilityRate/DemandRateStructure/Tier6Adjustment | Open

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizationsInformationInformationEnergy

  6. Property:OpenEI/UtilityRate/DemandRateStructure/Tier6Max | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins

  7. Property:OpenEI/UtilityRate/DemandRateStructure/Tier6Rate | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins

  8. PS'2006 -Photonics in Switching Conference An Intelligent Network Management System with Multi-Tier Distributed

    E-Print Network [OSTI]

    Kolner, Brian H.

    -Tier Distributed Intelligence for Optical Packet-Agile Transport Networks Jinqiang Yang and S.J. Ben Yoo Department introduces multi-tier distributed intelligence into the network management plane in order to address-line traffic engineering over optical packet-switching networks facilitated by the multi-tier distributed

  9. Dropwise condensation on superhydrophobic surfaces with two-tier roughness

    E-Print Network [OSTI]

    Chen, Chuan-Hua

    Dropwise condensation on superhydrophobic surfaces with two-tier roughness Chuan-Hua Chen,a Qingjun condensation. Superhydrophobicity appears ideal to promote continued dropwise condensation which requires rapid. This letter reports continuous dropwise condensation on a superhydrophobic surface with short carbon nanotubes

  10. Smart Frequency-Sensing Charge Controller for Electric Vehicles...

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

    for licensing:System uses frequency-sensing charge controllers that provide automatic demand response and regulation service to the grid by reducing or turning the charging...

  11. Intelligent Building Automation: A Demand Response Management Perspective

    E-Print Network [OSTI]

    Qazi, T.

    2010-01-01T23:59:59.000Z

    the energy consumption in response to energy price fluctuations, demand charges, or a direct request to reduce demand when the power grid reaches critical levels. However, in order for a demand response regime to be effective the building will need to have a...

  12. 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...

  13. 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

  14. 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

  15. 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

  16. Home energy rating system building energy simulation test (HERS BESTEST): Volume 1, Tier 1 and Tier 2 tests user's manual

    SciTech Connect (OSTI)

    Judkoff, R.; Neymark, J.

    1995-11-01T23:59:59.000Z

    The Home Energy Rating System (HERS) Building Energy Simulation Test (BESTEST) is a method for evaluating the credibility of software used by HERS to model energy use in buildings. The method provides the technical foundation for ''certification of the technical accuracy of building energy analysis tools used to determine energy efficiency ratings,'' as called for in the Energy Policy Act of 1992 (Title I, subtitle A,l Section 102, Title II, Part 6, Section 271). Certification is accomplished with a uniform set of test cases that facilitate the comparison of a software tool with several of the best public-domain, state-of-the-art building energy simulation programs available in the United States. This set of test cases represents the Tier 1 and Tier 2 Tests for Certification of Rating Tools as described in DOE 10 CFR Part 437 and the HERS Council Guidelines for Uniformity (HERS Council). A third Tier of tests not included in this document is also planned.

  17. Cummins Next Generation Tier 2, Bin 2 Light Truck Diesel Engine

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

    equivalent US Tier 2, Bin 2 emissions levels Commercially Viable Solutions - High quality, Great Performance, Low Total Cost of Ownership Program Targets 2010 Nissan Titan...

  18. Property:NEPA TieredDoc | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag Jump to: navigation,ProjectStartDateProperty Edit withTieredDoc Jump to:

  19. EPA Tier2 Submit Software Webpage | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOE FacilityDimondale,South, NewDyerTier2 Submit Software Webpage Jump to:

  20. Tiered time-of-use rates | OpenEI Community

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f <MaintainedInformationThePty Ltd Jump to: navigation,Tiered

  1. Achieving Tier 4 Emissions and Efficiency in Biomass Cookstoves

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny: The Future of1 AAccelerated aging of roofingDepartmentAchieve SteamHighTier 4

  2. Two-Tier Hierarchical Cyber-Physical Security Analysis Framework For Smart Grid

    E-Print Network [OSTI]

    Kundur, Deepa

    Two-Tier Hierarchical Cyber-Physical Security Analysis Framework For Smart Grid Jin Wei and Deepa consequence of cyber and/or physical disruption) using distributed control. In particular, we consider, USA Abstract--We propose a two-tier hierarchical cyber-physical framework for analyzing transient

  3. Toward a Two-Tier Clinical Warning System for Hospitalized Patients Gregory Hackmann1

    E-Print Network [OSTI]

    Lu, Chenyang

    at general hospital units. In this paper, we envision a two-tiered early warning system designed to identify significant limitations. Early warning systems based on existing medical records suffer from the sparseness two-tier system for clinical early warning and intervention. Our proposed system combines the two

  4. ERDC/ELTR-11-2 Methods for Tier 2 Modeling within the

    E-Print Network [OSTI]

    US Army Corps of Engineers

    and groundwater systems and to assess range management strategies to protect human and environmental health. Tier 2 will consist of time-varying contaminant fate/transport models for soil, vadose zone, groundwaterERDC/ELTR-11-2 Methods for Tier 2 Modeling within the Training Range Environmental Evaluation

  5. 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

  6. 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,

  7. Contract Demand Quantity (CDQ) Close-Out of Comments - June 17...

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

    customers that are exposed to excessive marginal demand costs resulting from a change in load profile. McMinnville will still be exposed to marginal demand charges that are double...

  8. Property:OpenEI/UtilityRate/EnergyRateStructure/Tier6Max | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge

  9. Retrofitting Existing Buildings for Demand Response & Energy Efficiency

    E-Print Network [OSTI]

    California at Los Angeles, University of

    Retrofitting Existing Buildings for Demand Response & Energy Efficiency www rate periods to avoid high charges. · Assembly Bill 1103 ­ Building Energy Efficiency Disclosure - Starting January 1, 2010, all commercial building lease transactions must disclose the energy efficiency

  10. 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

  11. 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

  12. 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,

  13. 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

  14. 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

  15. 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...

  16. 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.

  17. Development of Diesel Exhaust Aftertreatment System for Tier II Emissions

    SciTech Connect (OSTI)

    Yu, R. C.; Cole, A. S., Stroia, B. J.; Huang, S. C. (Cummins, Inc.); Howden, Kenneth C.; Chalk, Steven (U.S. Dept. of Energy)

    2002-06-01T23:59:59.000Z

    Due to their excellent fuel efficiency, reliability, and durability, compression ignition direct injection (CIDI) engines have been used extensively to power almost all highway trucks, urban buses, off-road vehicles, marine carriers, and industrial equipment. CIDI engines burn 35 to 50% less fuel than gasoline engines of comparable size, and they emit far less greenhouse gases (Carbon Dioxides), which have been implicated in global warming. Although the emissions of CIDI engines have been reduced significantly over the last decade, there remains concern with the Nitrogen Oxides (NOX) and Particulate Matter (PM) emission levels. In 2000, the US EPA proposed very stringent emissions standards to be introduced in 2007 along with low sulfur (< 15ppm) diesel fuel. The California Air Resource Board (CARB) has also established the principle that future diesel fueled vehicles should meet the same emissions standards as gasoline fueled vehicles and the EPA followed suit with its Tier II emissions regulations. Meeting the Tier II standards requires NOX and PM emissions to be reduced dramatically. Achieving such low emissions while minimizing fuel economy penalty cannot be done through engine development and fuel reformulation alone, and requires application of NOX and PM aftertreatment control devices. A joint effort was made between Cummins Inc. and the Department of Energy to develop the generic aftertreatment subsystem technologies applicable for Light-Duty Vehicle (LDV) and Light-Duty Truck (LDT) engines. This paper provides an update on the progress of this joint development program. Three NOX reduction technologies including plasmaassisted catalytic NOX reduction (PACR), active lean NOX catalyst (LNC), and adsorber catalyst (AC) technology using intermittent rich conditions for NOX reduction were investigated in parallel in an attempt to select the best NOX control approach for light-duty aftertreatment subsystem integration and development. Investigations included system design and analysis, critical lab/engine experiments, and ranking then selection of NOX control technologies against reliability, up-front cost, fuel economy, service interval/serviceability, and size/weight. The results of the investigations indicate that the best NOX control approach for LDV and LDT applications is a NOX adsorber system. A greater than 83% NOX reduction efficiency is required to achieve 0.07g/mile NOX Tier II vehicle-out emissions. Both active lean NOX and PACR technology are currently not capable of achieving the high conversion efficiency required for Tier II, Bin 5 emissions standards. In this paper, the NOX technology assessment and selection is first reviewed and discussed. Development of the selected NOX technology (NOX adsorber) and PM control are then discussed in more detail. Discussion includes exhaust sulfur management, further adsorber formulation development, reductant screening, diesel particulate filter development & active regeneration, and preliminary test results on the selected integrated SOX trap, NOX adsorber, and diesel particulate filter system over an FTP-75 emissions cycle, and its impact on fuel economy. Finally, the direction of future work for continued advanced aftertreatment technology development is discussed. (SAE Paper SAE-2002-01-1867 © 2002 SAE International. This paper is published on this website with permission from SAE International. As a user of this website, you are permitted to view this paper on-line, download this pdf file and print one copy of this paper at no cost for your use only. The downloaded pdf file and printout of this SAE paper may not be copied, distributed or forwarded to others or for the use of others.)

  18. Optimal Decentralized Protocols for Electric Vehicle Charging

    E-Print Network [OSTI]

    Low, Steven H.

    into the electric power grid. EV charging increases the electricity demand, and potentially amplifies the peak1 Optimal Decentralized Protocols for Electric Vehicle Charging Lingwen Gan Ufuk Topcu Steven Low Abstract--We propose decentralized algorithms for optimally scheduling electric vehicle (EV) charging

  19. Towards Multi-Service Traffic Shaping in Two-Tier Enterprise Data Centers

    E-Print Network [OSTI]

    Boyer, Edmond

    Centers (EDC), service providers are usually governed by Client Service Contracts (CSC) that specify and data clusters forming the second tier. Access to services is governed by Client Service Contracts (CSCs

  20. aaa program multi-tier: Topics by E-print Network

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

    their e-commerce systems in order to accommodate workflow Zou, Ying 13 Analysis of End-to-End Response Times of Multi-Tier Internet Services Engineering Websites Summary: , such as...

  1. Managing multi-tiered suppliers in the high-tech industry

    E-Print Network [OSTI]

    Frantz, Charles E. (Charles Evan)

    2009-01-01T23:59:59.000Z

    This thesis presents a roadmap for companies to follow as they manage multi-tiered suppliers in the high-tech industry. Our research covered a host of sources including interviews and publications from various companies, ...

  2. Multi-mode Energy Management for Multi-tier Server Tibor Horvath

    E-Print Network [OSTI]

    Skadron, Kevin

    Multi-mode Energy Management for Multi-tier Server Clusters Tibor Horvath tibor Charlottesville, VA 22904 ABSTRACT This paper presents an energy management policy for recon- figurable clusters General Terms Algorithms, Design, Experimentation, Management, Perfor- mance Keywords energy management

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. Property:OpenEI/UtilityRate/EnergyRateStructure/Tier1Adjustment | Open

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to: navigation, searchEnergy

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    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 I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to: navigation,

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    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 I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to: navigation,Information

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    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to:

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    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to:Energy Information

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    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to:Energy

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    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to:EnergyInformation Pages using

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    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 I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to:EnergyInformation Pages

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    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to:EnergyInformation PagesEnergy

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    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to:EnergyInformation

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    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to:EnergyInformationInformation

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    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump

  19. Property:OpenEI/UtilityRate/EnergyRateStructure/Tier4Max | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge JumpEnergy Information

  20. Property:OpenEI/UtilityRate/EnergyRateStructure/Tier4Rate | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge JumpEnergy InformationInformation

  1. Property:OpenEI/UtilityRate/EnergyRateStructure/Tier4Sell | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge JumpEnergy

  2. Property:OpenEI/UtilityRate/EnergyRateStructure/Tier5Adjustment | Open

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge JumpEnergyEnergy Information

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    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge JumpEnergyEnergy

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    Open Energy Info (EERE)

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  6. Property:OpenEI/UtilityRate/EnergyRateStructure/Tier6Adjustment | Open

    Open Energy Info (EERE)

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  9. 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

  10. Tier 1 ecological evaluation of proposed discharge of dredged material from Oakland Harbor into ocean waters

    SciTech Connect (OSTI)

    Shreffler, D.K.; Thorn, R.M.; Walls, B.E.; Word, J.Q. [Battelle/Marine Sciences Lab., Sequim, WA (United States)

    1994-01-01T23:59:59.000Z

    The Water Resources Development Act of 1986 (Public Law 99--662) authorized the U.S. Army Corps of Engineers (USACE) -- San Francisco District, to accommodate larger, deeper draft vessels in Oakland inner and Outer Harbors by deepening and widening the existing navigation channel, and providing turning basins and maneuvering areas in Oakland inner Harbor. The suitability of the resulting dredged material for disposal into ocean waters was subject to the procedures of the 1991 Testing Manual, Evaluation of Dredged Material Proposed for Ocean Disposal, known as the ``Green Book``. The Green Book provides a tiered approach for testing the suitability of dredged materials through chemical, physical, and biological evaluations. The first level of investigation, or Tier 1 evaluation, is used to determine whether a decision on LPC compliance can be made on the basis of readily available information. The Tier 1 report primarily summarizes existing information on sediment contamination and toxicity potential, identifies contaminants of concern, and determines the need for further testing. To assist the USACE in determining the suitability of dredged material from Oakland inner and Outer Harbors for ocean disposal, Battelle/Marine Sciences Laboratory prepared this Tier 1 report based upon information and data provided by USACE. Because this Tier 1 report originated well after an LPC determination was made to require testing of project sediments in Tier 3, the primary purpose of this report was to identify contaminants of concern (if any) in that particular dredged material. In addition, this Tier 1 report summarizes available information on chemical, physical, and biological characterization of the sediments in Oakland inner and Outer Harbors.

  11. A retrospective tiered environmental assessment of the Mount Storm Wind Energy Facility, West Virginia,USA

    SciTech Connect (OSTI)

    Efroymson, Rebecca Ann [ORNL; Day, Robin [No Affiliation; Strickland, M. Dale [Western EcoSystems Technology

    2012-11-01T23:59:59.000Z

    Bird and bat fatalities from wind energy projects are an environmental and public concern, with post-construction fatalities sometimes differing from predictions. Siting facilities in this context can be a challenge. In March 2012 the U.S. Fish and Wildlife Service (USFWS) released Land-based Wind Energy Guidelines to assess collision fatalities and other potential impacts to species of concern and their habitats to aid in siting and management. The Guidelines recommend a tiered approach for assessing risk to wildlife, including a preliminary site evaluation that may evaluate alternative sites, a site characterization, field studies to document wildlife and habitat and to predict project impacts, post construction studies to estimate impacts, and other post construction studies. We applied the tiered assessment framework to a case study site, the Mount Storm Wind Energy Facility in Grant County, West Virginia, USA, to demonstrate the use of the USFWS assessment approach, to indicate how the use of a tiered assessment framework might have altered outputs of wildlife assessments previously undertaken for the case study site, and to assess benefits of a tiered ecological assessment framework for siting wind energy facilities. The conclusions of this tiered assessment for birds are similar to those of previous environmental assessments for Mount Storm. This assessment found risk to individual migratory tree-roosting bats that was not emphasized in previous preconstruction assessments. Differences compared to previous environmental assessments are more related to knowledge accrued in the past 10 years rather than to the tiered structure of the Guidelines. Benefits of the tiered assessment framework include good communication among stakeholders, clear decision points, a standard assessment trajectory, narrowing the list of species of concern, improving study protocols, promoting consideration of population-level effects, promoting adaptive management through post-construction assessment and mitigation, and sharing information that can be used in other assessments.

  12. ATLAS off-Grid sites (Tier 3) monitoring. From local fabric monitoring to global overview of the VO computing activities

    E-Print Network [OSTI]

    PETROSYAN, A; The ATLAS collaboration; BELOV, S; ANDREEVA, J; KADOCHNIKOV, I

    2012-01-01T23:59:59.000Z

    The ATLAS Distributed Computing activities have so far concentrated in the "central" part of the experiment computing system, namely the first 3 tiers (the CERN Tier0, 10 Tier1 centers and over 60 Tier2 sites). Many ATLAS Institutes and National Communities have deployed (or intend to) deploy Tier-3 facilities. Tier-3 centers consist of non-pledged resources, which are usually dedicated to data analysis tasks by the geographically close or local scientific groups, and which usually comprise a range of architectures without Grid middleware. Therefore a substantial part of the ATLAS monitoring tools which make use of Grid middleware, cannot be used for a large fraction of Tier3 sites. The presentation will describe the T3mon project, which aims to develop a software suite for monitoring the Tier3 sites, both from the perspective of the local site administrator and that of the ATLAS VO, thereby enabling the global view of the contribution from Tier3 sites to the ATLAS computing activities. Special attention in p...

  13. 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.

  14. 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

  15. 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

  16. 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

  17. Accelerating the Adoption of Second-Tier Reach Standards for Applicable Appliance Products in China

    E-Print Network [OSTI]

    Lin, Jiang; Fridley, David

    2008-01-01T23:59:59.000Z

    of funding such as demand-side-management (DSM) programsutility-based demand-side management (DSM) program. Consumerdeveloped economies, demand-side-management (DSM) programs

  18. ATLAS Great Lakes Tier-2 Computing and Muon Calibration Center Commissioning

    E-Print Network [OSTI]

    Shawn McKee

    2009-10-15T23:59:59.000Z

    Large-scale computing in ATLAS is based on a grid-linked system of tiered computing centers. The ATLAS Great Lakes Tier-2 came online in September 2006 and now is commissioning with full capacity to provide significant computing power and services to the USATLAS community. Our Tier-2 Center also host the Michigan Muon Calibration Center which is responsible for daily calibrations of the ATLAS Monitored Drift Tubes for ATLAS endcap muon system. During the first LHC beam period in 2008 and following ATLAS global cosmic ray data taking period, the Calibration Center received a large data stream from the muon detector to derive the drift tube timing offsets and time-to-space functions with a turn-around time of 24 hours. We will present the Calibration Center commissioning status and our plan for the first LHC beam collisions in 2009.

  19. 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

  20. Power-Performance Study of Block-Level Monolithic 3D-ICs Considering Inter-Tier Performance Variations

    E-Print Network [OSTI]

    Lim, Sung Kyu

    interconnects are used on the bottom tier to withstand a high temperature process on the non- bottom tiers. We) the small size of MIVs enables ultra-high inte- gration density, considerably reducing silicon area and cost- formance envelope, and (3) the manufacturing process is entirely foundry-driven, and does not involve

  1. Posted on April 4, 2014 St. Francis Xavier University intends to nominate an exceptional individual for the Tier 2 Canada

    E-Print Network [OSTI]

    for the Tier 2 Canada Research Chair in Bioinformatics. The CRC in Bioinformatics will be located students and to mentor future researchers. The Canada Research Chair will be expected to contribute article of the Collective Agreement. The nomination will be at the Tier 2 level of Canada Research Chair

  2. Enhancing Energy Efficiency in Multi-tier Web Server Clusters via Prioritization Tibor Horvath and Kevin Skadron

    E-Print Network [OSTI]

    Skadron, Kevin

    Enhancing Energy Efficiency in Multi-tier Web Server Clusters via Prioritization Tibor Horvath that if the whole multi- tier system is effectively prioritized, additional power and energy savings are realizable-Champaign Urbana, IL 61801 zaher@cs.uiuc.edu Abstract This paper investigates the design issues and energy savings

  3. 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

  4. Supporting Strong Coherency for Active Caches in Multi-Tier Data-Centers over SUNDEEP NARRAVULA, PAVAN BALAJI, KARTHIKEYAN VAIDYANATHAN, SAVITHA KRISHNAMOORTHY, JIESHENG

    E-Print Network [OSTI]

    Panda, Dhabaleswar K.

    repositories. As mentioned in [23], a fourth tier emerges in today's data-center environ- ment: a communicationSupporting Strong Coherency for Active Caches in Multi-Tier Data-Centers over InfiniBand SUNDEEP-Tier Data-Centers over InfiniBand S. Narravula P. Balaji K. Vaidyanathan S. Krishnamoorthy J. Wu D. K

  5. 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

  6. 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...

  7. 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...

  8. 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...

  9. 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.

  10. 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

  11. ranking of utilities by demand charge? | OpenEI Community

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1 Wind Projectsource History ViewZAPZinccellranking of utilities

  12. The UNIVERSITY of WESTERN ONTARIO Tier I CANADA RESEARCH CHAIR in Data Analytics

    E-Print Network [OSTI]

    Denham, Graham

    data challenges in climate and ecosystems, seismic and wind hazards, smart and safe cities, and energy and experience. The starting date will be July 1, 2015. In accordance with the regulations set for Tier 1 Canada and water utilization; (ii) Financial Markets and Risk: with high- frequency time series and unstructured

  13. Tier-Based Underwater Acoustic Routing for Applications with Reliability and Delay Constraints

    E-Print Network [OSTI]

    Melodia, Tommaso

    Tier-Based Underwater Acoustic Routing for Applications with Reliability and Delay Constraints Li of New York at Buffalo Buffalo, New York 14260 Email: tmelodia@buffalo.edu Abstract--UnderWater Acoustic and military applications such as oceanographic data collection, pollution monitoring, offshore exploration

  14. A Two-Tier Approach to Grid Workflow Scheduling Dietmar Sommerfeld

    E-Print Network [OSTI]

    Zachmann, Gabriel

    in computational Grids is how to map and schedule workflow tasks onto multiple distributed resources, and how. It performs a just-in-time mapping of tasks to Grid resources and is equivalent to common metaA Two-Tier Approach to Grid Workflow Scheduling Dietmar Sommerfeld Gesellschaft f

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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.

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

  1. 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

  2. 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

  3. 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

  4. 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 (

  5. 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

  6. 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

  7. 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

  8. 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 controlled indicate the energy and cost savings for  demand controlled 24) (California Energy  Commission 2008), demand controlled 

  9. 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  

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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...

  18. 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...

  19. 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

  20. 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...

  1. 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...

  2. Vehicle Technologies Office Merit Review 2015: ATP-LD; Cummins Next Generation Tier 2 Bin 2 Diesel Engine

    Broader source: Energy.gov [DOE]

    Presentation given by Cummins at 2015 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Office Annual Merit Review and Peer Evaluation Meeting about ATP-LD; Cummins next generation tier...

  3. FlashTier: a Lightweight, Consistent and Durable Storage Cache Mohit Saxena, Michael M. Swift and Yiying Zhang

    E-Print Network [OSTI]

    Swift, Michael

    following a crash. Finally, FlashTier leverages cache behavior to silently evict data blocks during garbage the disk into SSD addresses for the cache. If the cache has to survive crashes, this map must be persistent

  4. 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

  5. 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

  6. The Use of Proxy Caches for File Access in a Multi-Tier Grid Environment

    SciTech Connect (OSTI)

    Brun, R.; Dullmann, D.; Ganis, G.; /CERN; Hanushevsky, A.; /SLAC; Janyst, L.; Peters, A.J.; Rademakers, F.; Sindrilaru, E.; /CERN

    2012-04-19T23:59:59.000Z

    The use of proxy caches has been extensively studied in the HEP environment for efficient access of database data and showed significant performance with only very moderate operational effort at higher grid tiers (T2, T3). In this contribution we propose to apply the same concept to the area of file access and analyze the possible performance gains, operational impact on site services and applicability to different HEP use cases. Base on a proof-of-concept studies with a modified XROOT proxy server we review the cache efficiency and overheads for access patterns of typical ROOT based analysis programs. We conclude with a discussion of the potential role of this new component at the different tiers of a distributed computing grid.

  7. VM-based infrastructure for simulating different cluster and storage solutions used on ATLAS tier3 sites

    E-Print Network [OSTI]

    KUTOUSKI, M; The ATLAS collaboration; PETROSYAN, A; KADOCHNIKOV, I; BELOV, S; KORENKOV, V

    2012-01-01T23:59:59.000Z

    ATLAS is a particle physics experiment on Large Hadron Collider at CERN. The experiment produces petabytes of data every year. The ATLAS Computing model embraces the Grid paradigm and originally included three levels of computing centres to be able to operate such large volume of data. With the formation of small computing centres, usually based at universities, the model was expanded to include them as Tier3 sites. The experiment supplies all necessary software to operate typical Grid-site, but Tier3 sites do not support Grid services of the experiment or support them partially. Tier3 centres comprise a range of architectures and many do not possess Grid middleware, thus, monitoring of storage and analysis software used on Tier2 sites becomes unavailable for Tier3 site system administrator and, also, Tier3 sites activity becomes unavailable for virtual organization of the experiment. In this paper we present ATLAS off-Grid sites monitoring software suite, which enables monitoring on sites, which are not unde...

  8. ATLAS off-Grid sites (Tier 3) monitoring. From local fabric monitoring to global overview of the VO computing activities

    E-Print Network [OSTI]

    PETROSYAN, A; The ATLAS collaboration; BELOV, S; ANDREEVA, J; KADOCHNIKOV, I

    2012-01-01T23:59:59.000Z

    ATLAS is a particle physics experiment on Large Hadron Collider at CERN. The experiment produces petabytes of data every year. The ATLAS Computing model embraces the Grid paradigm and originally included three levels of computing centres to be able to operate such large volume of data. With the formation of small computing centres, usually based at universities, the model was expanded to include them as Tier3 sites. The experiment supplies all necessary software to operate typical Grid-site, but Tier3 sites do not support Grid services of the experiment or support them partially. Tier3 centres comprise a range of architectures and many do not possess Grid middleware, thus, monitoring of storage and analysis software used on Tier2 sites becomes unavailable for Tier3 site system administrator and, also, Tier3 sites activity becomes unavailable for virtual organization of the experiment. In this paper we present ATLAS off-Grid sites monitoring software suite, which enables monitoring on sites, which are not unde...

  9. 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

  10. 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)

  11. 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

  12. Decentralized Charging Control for Large Populations of Plug-in Electric Vehicles: Application of the Nash Certainty Equivalence Principle

    E-Print Network [OSTI]

    Hiskens, Ian A.

    strategy results in valley filling, i.e. the total demand, consisting of aggregated PEV charging load PEVs, is responsive to the total demand of the grid, which is the summation of the inelastic non-PEV base demand together with the aggregated charging rates of the whole population of PEVs. Because

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. 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...

  18. 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.

  19. Overview of Demand Side Response

    Broader source: Energy.gov [DOE]

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

  20. 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.

  1. 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

  2. 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-

  3. 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

  4. 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

  5. Accelerating the Adoption of Second-Tier Reach Standards forApplicable Appliance Products in China

    SciTech Connect (OSTI)

    Lin, Jiang; Fridley, David

    2007-03-01T23:59:59.000Z

    The minimum energy efficiency standards program for household appliances in China was initiated in 1989. Since 1996, CLASP and its implementing partner, LBNL, have assisted China in developing 11 minimum energy performance standards (MEPS) for 9 products and endorsement labels for 11 products including: refrigerators; air conditioners; clothes washers; televisions; printers; computers; monitors; fax machines; copiers; DVD/VCD players; external power supplies; and set-top boxes (under development). Before 2003, China's traditional approach to standards development involved small increases in efficiency requirements for implementation within 6 months of a standard's approval. Since 2003, China has adopted a new approach in setting MEPS. This new approach involves the development of two tiers of standards--one for initial implementation and a second tier at a more aggressive level of energy efficiency for implementation three to five years later. The second-tier standard is also referred to as a 'reach standard'. Reach standards have now been developed in China for: color TVs; refrigerators; air conditioners; and external power supplies. This report is presented in five sections. After the introduction in Section 1, Section 2 analyzes the distribution of the efficiency of refrigerators and air-conditioners in China based on data collected by the China Energy Label Center for the mandatory energy information label program. The results provide an assessment of the adoption of reach standards for these two products. Section 3 summarizes on-going collaborations with Shanghai related to early local adoption of reach standards, and presents both the impact and an analysis of barriers to the local adoption of reach standard for air-conditioners. Section 4 offers suggestions for local governments on how to move forward in adopting reach standards in their localities and concludes with a summary of the results and a plan for developing local capacity in order to achieve success in adopting reach standards.

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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

  11. National Action Plan on Demand Response

    Broader source: Energy.gov [DOE]

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

  12. 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

  13. 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).

  14. 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

  15. 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

  16. 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 officedemand controlled  ventilation systems, Dennis DiBartolomeo the demand controlled ventilation system increased the rate 

  17. 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 ...

  18. 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 building’s participationdemand response strategies in California buildings are

  19. 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,...

  20. Workplace Charging Challenge: Sample Workplace Charging Policy...

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

    guidelines used by one Workplace Charging Challenge partner to keep their program running safe and successfully. Sample Workplace Charging Policy More Documents & Publications...

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Canada Research Chair, Tier I, Data Science The Canada Research Chair Program was established by the Government of Canada to enable

    E-Print Network [OSTI]

    Martin, Jeff

    Canada Research Chair, Tier I, Data Science The Canada Research Chair Program was established by the Government of Canada to enable Canadian universities to foster world-class research excellence for a Tier 1 Canada Research Chair (CRC) position in Data Science. This will be The University of Winnipeg

  6. College of Law, University of Saskatchewan, Canada Research Chair in Law (Tier 2) The College of Law at the University of Saskatchewan in Saskatoon, Saskatchewan, Canada seeks to

    E-Print Network [OSTI]

    Saskatchewan, University of

    College of Law, University of Saskatchewan, Canada Research Chair in Law (Tier 2) The College of Law at the University of Saskatchewan in Saskatoon, Saskatchewan, Canada seeks to recruit and nominate a Canada Research Chair in Law (Tier 2). The Canada Research Chair program (www

  7. Supporting Strong Coherency for Active Caches in Multi-Tier Data-Centers over S. Narravula P. Balaji K. Vaidyanathan S. Krishnamoorthy J. Wu D. K. Panda

    E-Print Network [OSTI]

    Panda, Dhabaleswar K.

    repositories. As mentioned in [16], a fourth tier emerges in today's data-center environment: a communicationSupporting Strong Coherency for Active Caches in Multi-Tier Data-Centers over InfiniBand S that in order to provide or design a data-center environ- ment which is efficient and offers high performance

  8. 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.

  9. 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

  10. 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

  11. 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 ...

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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:

  17. 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

  18. 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

  19. 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

  20. National Dioxin Study Tier 4 - combustion sources: final test report - Site 8, Black-liquor boiler BLB-C

    SciTech Connect (OSTI)

    Jamgochian, C.L.; Keller, L.E.

    1987-04-01T23:59:59.000Z

    This report summarizes the results of a dioxin/furan emissions test of a black-liquor recovery boiler equipped with a drybottom electrostatic precipitator for particulate emissions control. Black-liquor recovery boilers are used at kraft pulp mills to produce process steam and to reclaim inorganic chemicals from spent wood pulping liquors. The dioxin/furan emissions test was conducted under Tier 4 of the National Dioxin Study. The primary objective of Tier 4 is to determine if various combustion sources are sources of dioxin and/or furan emissions. If any of the combustion sources are found to emit dioxin or furan, the secondary objective of Tier 4 is to quantify these emissions. Black-liquor recovery boilers are one of 8 combustion-source categories that have been tested in the Tier 4 program. The tested black-liquor boiler, BLB-C, was selected for the test after an initial information screening and a one-day pretest survey visit. Boiler BLB-C is considered representative of black-liquor recovery boilers with dry-bottom electrostatic precipitators. The amount of chloride present in the black-liquor circuit at this site is considered intermediate to high relative to that found at other kraft pulp mills. Data presented in the report include dioxin (tetra through octa homologue +2378 TCDD) and furan (tetra through octa homologue +2378 TCDF) results for both stack samples and ash samples. In addition, process data collected during sampling are also presented.

  1. National Dioxin Study Tier 4 - combustion sources: final test report - Site 6, wire reclamation incinerator WRI-A

    SciTech Connect (OSTI)

    Keller, L.E.; McReynolds, J.R.; Benson, D.J.

    1987-04-01T23:59:59.000Z

    This report summarizes the results of a dioxin/furan emissions test of a wire-reclamation incinerator equipped with an afterburner for hydrocarbon emissions control. The wire reclamation incinerator is used for recovery of copper from coated copper wire and drained transformer cores. The test was the sixth in a series of several dioxin/furan emissions tests conducted under Tier 4 of the National Dioxin Study. The primary objective of Tier 4 is to determine if various combustion sources are sources of dioxin and/or furan emissions. If any of the combustion sources are found to emit dioxin or furan, the secondary objective of Tier 4 is to quantify these emissions. Wire reclamation incinerators are one of 8 combustion-source categories that have been tested in the Tier 4 program. The tested incinerator WRI-A was selected for the test after an initial information screening and a one-day pretest survey visit. Incinerator WRI-A is considered representative of the wire-reclamation incinerator population in the United States. Data presented in the report include dioxin (tetra through octa homologue + 2378 TCDD) and furan (tetra through octa homologue + 2378 TCDF) results for both stack samples and ash samples. In addition, process data collected during sampling are also presented.

  2. A First Look at the Impact of Electric Vehicle Charging on the Electric Grid in the EV Project

    SciTech Connect (OSTI)

    Stephen L. Schey; John G. Smart; Don R. Scoffield

    2012-05-01T23:59:59.000Z

    ECOtality was awarded a grant from the U.S. Department of Energy to lead a large-scale electric vehicle charging infrastructure demonstration, called The EV Project. ECOtality has partnered with Nissan North America, General Motors, the Idaho National Laboratory, and others to deploy and collect data from over 5,000 Nissan LEAFsTM and Chevrolet Volts and over 10,000 charging systems in 18 regions across the United States. This paper summarizes usage of residential charging units in The EV Project, based on data collected through the end of 2011. This information is provided to help analysts assess the impact on the electric grid of early adopter charging of grid-connected electric drive vehicles. A method of data aggregation was developed to summarize charging unit usage by the means of two metrics: charging availability and charging demand. Charging availability is plotted to show the percentage of charging units connected to a vehicle over time. Charging demand is plotted to show charging demand on the electric gird over time. Charging availability for residential charging units is similar in each EV Project region. It is low during the day, steadily increases in evening, and remains high at night. Charging demand, however, varies by region. Two EV Project regions were examined to identify regional differences. In Nashville, where EV Project participants do not have time-of-use electricity rates, demand increases each evening as charging availability increases, starting at about 16:00. Demand peaks in the 20:00 hour on weekdays. In San Francisco, where the majority of EV Project participants have the option of choosing a time-of-use rate plan from their electric utility, demand spikes at 00:00. This coincides with the beginning of the off-peak electricity rate period. Demand peaks at 01:00.

  3. 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

  4. Emergency Planning and Community Right-To-Know Act. Section 312 Tier Two report forms

    SciTech Connect (OSTI)

    Evans, R.A.

    1998-02-01T23:59:59.000Z

    As required by Right-to-Know Laws and Pollution Prevention Requirements, the Y-12 Plant staff is submitting an unclassified version of the Tier-Two Forms. This report contains data for CY 1997 for all hazardous chemicals stored at the Y-12 Plant in quantities equal to or greater than 10,000 pounds and all extremely hazardous substances stored in quantities equal to or greater than 500 pounds or the threshold planning quantity, whichever is lower. Also included with this submittal is a key to the inventory, temperature, pressure, and container codes used on the report forms. This information is included to aid in the interpretation of the data presented. It is not necessary that the code information be forwarded to the referenced state and local agencies. Classified information supporting this document will be maintained on file for review by Q-cleared personnel.

  5. Integrated systems approach to pollution prevention: A three-tier substitution strategy

    SciTech Connect (OSTI)

    Ahmed, I.; Cunniff, E.; Patch, J. [Booz-Allen & Hamilton Inc., Bethesda, MD (United States)

    1995-12-01T23:59:59.000Z

    Current pollution prevention initiatives are reactive, not proactive. Most federal and state regulations and industry participation in pollution prevention projects focus on post-production cleanup. However, an integrated systems approach to design pollution prevention strategies based on substitution of entire classes of chemicals with bio-based alternatives would significantly enhance the impact of pollution prevention efforts. Industry`s current attempts at pollution prevention efforts primarily rely on recycling, modifying processes to reduce the use of certain chemicals, or substituting a petrochemical not listed on the Toxic Release Inventory (TRI) for one currently listed. Such strategies may not constitute a long term solution to the pollution problem. A more durable and comprehensive strategy is to substitute renewable feedstock derived biochemicals for petrochemicals. The generation of pollution as driven by the consumer end-products industry occurs in three distinct levels; raw materials production (crude oil refining), commodity and intermediate chemicals production, a raw chemicals consumption. This paper suggests a three-tier substitution strategy based on the three levels of materials used in the chemical process industry with a goal of minimizing the pollution impact via substitutions. The substitution potential of each of the three tiers is determined based on the optimum impact criteria applicable to a given produce line or a process. The best existing pollution prevention initiatives should be incorporated in an integrated pollution management system. This system considers and includes long-term solutions to pollution problems faced both by the regulators and the chemical process industry. The role of existing production capacities that continue to produce toxic chemicals as a byproduct and their potential phase-out via biochemical substitution is also discussed.

  6. Congestion control in charging of electric vehicles

    E-Print Network [OSTI]

    Carvalho, Rui; Gibbens, Richard; Kelly, Frank

    2015-01-01T23:59:59.000Z

    The increasing penetration of electric vehicles over the coming decades, taken together with the high cost to upgrade local distribution networks, and consumer demand for home charging, suggest that managing congestion on low voltage networks will be a crucial component of the electric vehicle revolution and the move away from fossil fuels in transportation. Here, we model the max-flow and proportional fairness protocols for the control of congestion caused by a fleet of vehicles charging on distribution networks. We analyse the inequality in the charging times as the vehicle arrival rate increases, and show that charging times are considerably more uneven in max-flow than in proportional fairness. We also analyse the onset of instability, and find that the critical arrival rate is indistinguishable between the two protocols.

  7. Retail Demand Response in Southwest Power Pool

    SciTech Connect (OSTI)

    Bharvirkar, Ranjit; Heffner, Grayson; Goldman, Charles

    2009-01-30T23:59:59.000Z

    In 2007, the Southwest Power Pool (SPP) formed the Customer Response Task Force (CRTF) to identify barriers to deploying demand response (DR) resources in wholesale markets and develop policies to overcome these barriers. One of the initiatives of this Task Force was to develop more detailed information on existing retail DR programs and dynamic pricing tariffs, program rules, and utility operating practices. This report describes the results of a comprehensive survey conducted by LBNL in support of the Customer Response Task Force and discusses policy implications for integrating legacy retail DR programs and dynamic pricing tariffs into wholesale markets in the SPP region. LBNL conducted a detailed survey of existing DR programs and dynamic pricing tariffs administered by SPP's member utilities. Survey respondents were asked to provide information on advance notice requirements to customers, operational triggers used to call events (e.g. system emergencies, market conditions, local emergencies), use of these DR resources to meet planning reserves requirements, DR resource availability (e.g. seasonal, annual), participant incentive structures, and monitoring and verification (M&V) protocols. Nearly all of the 30 load-serving entities in SPP responded to the survey. Of this group, fourteen SPP member utilities administer 36 DR programs, five dynamic pricing tariffs, and six voluntary customer response initiatives. These existing DR programs and dynamic pricing tariffs have a peak demand reduction potential of 1,552 MW. Other major findings of this study are: o About 81percent of available DR is from interruptible rate tariffs offered to large commercial and industrial customers, while direct load control (DLC) programs account for ~;;14percent. o Arkansas accounts for ~;;50percent of the DR resources in the SPP footprint; these DR resources are primarily managed by cooperatives. o Publicly-owned cooperatives accounted for 54percent of the existing DR resources among SPP members. For these entities, investment in DR is often driven by the need to reduce summer peak demand that is used to set demand charges for each distribution cooperative. o About 65-70percent of the interruptible/curtailable tariffs and DLC programs are routinely triggered based on market conditions, not just for system emergencies. Approximately, 53percent of the DR resources are available with less than two hours advance notice and 447 MW can be dispatched with less than thirty minutes notice. o Most legacy DR programs offered a reservation payment ($/kW) for participation; incentive payment levels ranged from $0.40 to $8.30/kW-month for interruptible rate tariffs and $0.30 to $4.60/kW-month for DLC programs. A few interruptible programs offered incentive payments which were explicitly linkedto actual load reductions during events; payments ranged from 2 to 40 cents/kWh for load curtailed.

  8. 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

  9. 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...

  10. 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, ...

  11. 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...

  12. 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...

  13. 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

  14. 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

  15. 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:

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. TANK 18 AND 19-F TIER 1A EQUIPMENT FILL MOCK UP TEST SUMMARY

    SciTech Connect (OSTI)

    Stefanko, D.; Langton, C.

    2011-11-04T23:59:59.000Z

    The United States Department of Energy (US DOE) has determined that Tanks 18-F and 19-F have met the F-Tank Farm (FTF) General Closure Plan Requirements and are ready to be permanently closed. The high-level waste (HLW) tanks have been isolated from FTF facilities. To complete operational closure they will be filled with grout for the purpose of: (1) physically stabilizing the tanks, (2) limiting/eliminating vertical pathways to residual waste, (3) discouraging future intrusion, and (4) providing an alkaline, chemical reducing environment within the closure boundary to control speciation and solubility of select radionuclides. Bulk waste removal and heel removal equipment remain in Tanks 18-F and 19-F. This equipment includes the Advance Design Mixer Pump (ADMP), transfer pumps, transfer jets, standard slurry mixer pumps, equipment-support masts, sampling masts, dip tube assemblies and robotic crawlers. The present Tank 18 and 19-F closure strategy is to grout the equipment in place and eliminate vertical pathways by filling voids in the equipment to vertical fast pathways and water infiltration. The mock-up tests described in this report were intended to address placement issues identified for grouting the equipment that will be left in Tank 18-F and Tank 19-F. The Tank 18-F and 19-F closure strategy document states that one of the Performance Assessment (PA) requirements for a closed tank is that equipment remaining in the tank be filled to the extent practical and that vertical flow paths 1 inch and larger be grouted. The specific objectives of the Tier 1A equipment grout mock-up testing include: (1) Identifying the most limiting equipment configurations with respect to internal void space filling; (2) Specifying and constructing initial test geometries and forms that represent scaled boundary conditions; (3) Identifying a target grout rheology for evaluation in the scaled mock-up configurations; (4) Scaling-up production of a grout mix with the target rheology (16 second flow cone value) from 0.25 cubic feet to 4.3 cubic feet. (Ten 0.43 cubic batches were produced because full-scale equipment was not available for the Tier 1A test.); (5) Demonstrating continuous gravity filling of the ADMP mock up test form; (6) Demonstrating continuous gravity filling of 1 inch and 2 inch schedule 40 pipe; and (7) Demonstrating filling of 1 inch and 2 inch schedule 40 pipe from the bottom up by discharging through a tube inserted into the pipes. The Tier 1A mock-up test focused on the ADMP and pipes at least one inch in diameter. The ADMP which is located in center riser of Tank 18-F is a concern because the column for this long-shaft (55 ft) pump is unique and modification to the pump prior to placing it in service limited the flow path options for filling by creating a single flow path for filling and venting the ADMP support column. The large size, vertical orientation, and complicated flow path in the ADMP warrants a detailed description of this piece of ancillary equipment.

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

    SciTech Connect (OSTI)

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

    2009-10-08T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

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

    2005-09-01T23:59:59.000Z

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

  9. 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

  10. 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

  11. 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.to facilitate automating  demand response actions at the Interoperable Automated Demand Response Infrastructure,

  12. 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

  13. 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

  14. 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.

  15. 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

  16. 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).

  17. 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-

  18. 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

  19. 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

  20. 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

  1. 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

  2. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01T23:59:59.000Z

    of Fully Automated Demand  Response in Large Facilities.  Fully Automated Demand Response Tests in Large Facilities.  Open Automated  Demand Response Communication Standards: 

  3. 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 (

  4. 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

  5. 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...

  6. 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

  7. 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...

  8. 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

  9. 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",

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

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    Keywords: demand response, buildings, electricity use, Interface  Automated Demand Response  Building Automation of demand response in  commercial buildings.   One key 

  11. 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

  12. 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.

  13. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01T23:59:59.000Z

    Demand  Response for Small Commercial Buildings.   CEC?500?automated demand response  For small commercial buildings, AUTOMATED DEMAND RESPONSE FOR SMALL COMMERCIAL BUILDINGS

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. Provisioning a Multi-Tiered Data Staging Area for Extreme-Scale Machines

    SciTech Connect (OSTI)

    Prabhakar, Ramya A [ORNL; Vazhkudai, Sudharshan S [ORNL; Kim, Youngjae [ORNL; Butt, Ali R [Virginia Polytechnic Institute and State University (Virginia Tech); Li, Min [Virginia Polytechnic Institute and State University (Virginia Tech); Kandemir, Mahmut [Pennsylvania State University

    2011-01-01T23:59:59.000Z

    Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic data staging area for extreme-scale machines. Such a staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the checkpointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.

  19. After dumping agreement: A two-tiered market. [Uranium market transactions October 1992

    SciTech Connect (OSTI)

    Not Available

    1992-11-01T23:59:59.000Z

    In its largest increase since July 1990, the NUKEM price range for this month ended up at $9.50-$10.50. On October 16th, destined to become a landmark date in uranium industry history, the republics of Uzbekistan, Kazakhstan, Tajikistan, Kyrgyzstan, Ukraine and the Russian Federation signed quantitative restraint agreements with the US Department of Commerce. Predictably, prices jumped significantly as sellers withdrew from the market. With Commerce's initial calculation of a $7.95 market price for determining the level of CIS imports over the next six months, it appears quite certain that prices for non-CIS origins will continue to rise. (CIS imports can only begin when Commerce determines that the market price has hit $13). There is the possibility that a two-tiered market could emerge in the future with lower prices being paid for CIS origins by those utilities not affected by Euratom or Commerce restrictions. However, at this point, most potential buyers falling into this category have opted to maintain a wait-and-see approach.

  20. 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...

  1. 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.

  2. 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...

  3. 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:

  4. 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

  5. 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

  6. 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

  7. 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...

  8. 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 ...

  9. 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,

  10. 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

  11. 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...

  12. 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...

  13. 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...

  14. 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

  15. 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....

  16. 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.

  17. 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...

  18. 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

  19. 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

  20. 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

  1. 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...

  2. 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.

  3. Charge regulation circuit

    DOE Patents [OSTI]

    Ball, Don G. (Livermore, CA)

    1992-01-01T23:59:59.000Z

    A charge regulation circuit provides regulation of an unregulated voltage supply in the range of 0.01%. The charge regulation circuit is utilized in a preferred embodiment in providing regulated voltage for controlling the operation of a laser.

  4. Multi-tiered sensing and data processing for monitoring ship structures

    SciTech Connect (OSTI)

    Farrar, Charles [Los Alamos National Laboratory; Salvino, Liming [NSWCCD; Lynch, Jerome [UNIV. OF MICHIGAN; Brady, Thomas [NSWCCD

    2009-01-01T23:59:59.000Z

    A comprehensive structural health monitoring (SHM) system is a critical mechanism to ensure hull integrity and evaluate structural performance over the life of a ship, especially for lightweight high-speed ships. One of the most important functions of a SHM system is to provide real-time performance guidance and reduce the risk of structural damage during operations at sea. This is done by continuous feedback from onboard sensors providing measurements of seaway loads and structural responses. Applications of SHM should also include diagnostic capabilities such as identifying the presence of damage, assessing the location and extent of damage when it does occur in order to plan for future inspection and maintenance. The development of such SHM systems is extremely challenging because of the physical size of these structures, the widely varying and often extreme operational and environmental conditions associated with the missions of high performance ships, the lack of data from known damage conditions, the limited sensing that was not designed specifically for SHM, the management of the vast amounts of data, and the need for continued, real-time data processing. This paper will discuss some of these challenges and several outstanding issues that need to be addressed in the context of applying various SHM approaches to sea trials data measured on an aluminum high-speed catamaran, the HSV-2 Swift. A multi-tiered approach for sensing and data processing will be discussed as potential SHM architecture for future shipboard application. This approach will involve application of low cost and dense sensor arrays such as wireless communications in selected areas of the ship hull in addition to conventional sensors measuring global structural response of the ship. A recent wireless hull monitoring demo on FSF-I SeaFighter will be discussed as an example to show how this proposed architecture is a viable approach for long-term and real-time hull monitoring.

  5. 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...

  6. 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

  7. 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

  8. 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

  9. 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

  10. Electrically charged pulsars

    E-Print Network [OSTI]

    M. D. Alloy; D. P. Menezes

    2007-04-24T23:59:59.000Z

    n the present work we investigate one possible variation on the usual electrically neutral pulsars: the inclusion of electric charge. We study the effect of electric charge in pulsars assuming that the charge distribution is proportional to the energy density. All calculations were performed for zero temperature and fixed entropy equations of state.

  11. 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...

  12. Electric Vehicle Smart Charging Infrastructure

    E-Print Network [OSTI]

    Chung, Ching-Yen

    2014-01-01T23:59:59.000Z

    for Multiplexed Electric Vehicle Charging”, US20130154561A1,Chynoweth, ”Intelligent Electric Vehicle Charging System”,of RFID Mesh Network for Electric Vehicle Smart Charging

  13. Potentially Self-defeating: Group Buying in a Two-tier Supply Chain

    E-Print Network [OSTI]

    Xie, Jinxing

    's response to GB. In this paper, we take the supplier's response into consideration, and present a game model; quantity discount; economies of scale; price-dependent demand; supply chain management; game theory. 1 when buyer groups are aggregating orders across countries for Europe-wide discounts [1]. Many empirical

  14. Ultra Low Power 2-tier 3D Stacked Sub-threshold H.264 Intra Frame Encoder

    E-Print Network [OSTI]

    Lim, Sung Kyu

    longer battery life and do not demand a fast frequency of operation. Sub-threshold cir- cuits beneficial to such unattended sensor networks by extending their battery life. Sub- threshold design helps us in-house tools to handle TSVs and 3D stacking. The standard cells were sized with Cadence Virtuoso

  15. 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.

  16. 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

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8 Jump to:FlatDemandMonth1 Jump

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8 Jump to:FlatDemandMonth1

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8 Jump to:FlatDemandMonth1This is

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8 Jump to:FlatDemandMonth1This

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8 JumpFlatDemandMonth3 Jump to:

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8 JumpFlatDemandMonth3 Jump

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8 JumpFlatDemandMonth3

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8FlatDemandMonth7 Jump to:

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8FlatDemandMonth7 Jump

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8FlatDemandMonth7

  7. 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.

  8. 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.

  9. Distributed Solar Photovoltaics for Electric Vehicle Charging: Regulatory and Policy Considerations (Brochure)

    SciTech Connect (OSTI)

    Not Available

    2014-09-01T23:59:59.000Z

    Increasing demand for electric vehicle (EV) charging provides an opportunity for market expansion of distributed solar technology. A major barrier to the current deployment of solar technology for EV charging is a lack of clear information for policy makers, utilities and potential adopters. This paper introduces the pros and cons of EV charging during the day versus at night, summarizes the benefits and grid implications of combining solar and EV charging technologies, and offers some regulatory and policy options available to policy makers and regulators wanting to incentivize solar EV charging.

  10. Photovoltaics for demand-side management: Opportunities for early commercialization

    SciTech Connect (OSTI)

    Byrne, J.; Letendre, S.; Govindarajalu, C.; Wang, Y.D. [Univ. of Delaware, Newark, DE (United States). Center for Energy and Environmental Policy; Nigro, R. [Delmarva Power, Newark, DE (United States); Wallace, W. [National Renewable Energy Lab., Golden, CO (United States)

    1995-10-01T23:59:59.000Z

    Recently, interest in utilizing photovoltaics (PV) in a demand-side management (DSM) role has been increasing. Research has shown that many utilities across the US have a good match between peak loads and the availability of the solar resource. Maximum value for PV in DSM applications can be achieved by incorporating a dispatching capability to PV systems (through the addition of storage). This enables utilities to evaluate PV systems as a peak-shaving technology. To date, peak-shaving has been a high-value DSM application for US utilities. The authors analysis of the value of dispatchable PV-DSM systems indicates that small-scale, customer-sited systems are approaching competitive cost levels in several regions of the US that have favorable load matching and high demand charges. This paper presents the results of an economic analysis for high-value PV-DSM systems located in the service territories of five case study utilities. The results suggest that PV is closer to commercialization when viewed as a DSM technology relative to analyses that focus on the technology as a supply-side option.

  11. 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 assets—at no cost and no risk. Demand response, the voluntary...

  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

    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

  13. 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 ...

  14. 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.

  15. 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 ...

  16. 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

  17. 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 options—one which taxes terrestrial carbon emissions equally with fossil fuel and industrial emissions, and an alternative which only taxes fossil fuel and industrial emissions but places no penalty on land-use change emissions. We find that increasing populations and economic growth could be anticipated to almost triple demand for water for agricultural systems across the century even in the absence of climate policy. In general policies to mitigate climate change increase agricultural demands for water still further, though the largest changes occur in the second half of the century, under both policy regimes. The two policies examined profoundly affected both the sources and magnitudes of the increase in irrigation water demands. The largest increases in agricultural irrigation water demand occurred in scenarios where only fossil fuel emissions were priced (but not land-use change emission) and were primarily driven by rapid expansion in bioenergy production. In these scenarios water demands were large relative to present-day total available water, calling into question whether it would be physically possible to produce the associated biomass energy. We explored the potential of improved water delivery and irrigation system efficiencies. These could potentially reduce demands substantially. However, overall demands remained high under our fossil-fuel-only tax policy. In contrast, when all carbon was priced, increases in agricultural water demands were smaller than under the fossil-fuel-only policy and were driven primarily by increased demands for water by non-biomass crops such as rice. Finally we estimate the geospatial pattern of water demands and find that regions such as China, India and other countries in south and east Asia might be expected to experience greatest increases in water demands.?

  18. 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...

  19. 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)

  20. 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 España, 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...

  1. 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...

  2. 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.

  3. 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

  4. General Groves takes charge

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

    takes charge Colonel James C. Marshall, head of the DSM project (Development of Substitute Materials), did not make much headway, yet he did accomplish some things that lasted....

  5. 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.

  6. 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

  7. 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

  8. 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"

  9. 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

  10. 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

  11. 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...

  12. 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

  13. 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

  14. 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

  15. 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 energyEnergy Demands and Efficiency Strategies   in Data Center AC02?05CH11231.   Energy Demands and Efficiency Strategies

  16. 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.

  17. 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: What’sJ. Kulick. 2004. ”Demand side management and energy e?ciency

  18. 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

  19. 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

  20. New Diesel Emissions Control Strategy for U.S. Tier 2 | Department of

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn'tOrigin of Contamination in Many DevilsForum |EnergyNew CatalyticDemands on HeavyEnergy

  1. Electrically charged compact stars

    E-Print Network [OSTI]

    Subharthi Ray; Manuel Malheiro; Jose' P. S. Lemos; Vilson T. Zanchin

    2006-04-17T23:59:59.000Z

    We review here the classical argument used to justify the electrical neutrality of stars and show that if the pressure and density of the matter and gravitational field inside the star are large, then a charge and a strong electric field can be present. For a neutron star with high pressure (~ 10^{33} to 10^{35} dynes /cm^2) and strong gravitational field (~ 10^{14} cm/s^2), these conditions are satisfied. The hydrostatic equation which arises from general relativity, is modified considerably to meet the requirements of the inclusion of the charge. In order to see any appreciable effect on the phenomenology of the neutron stars, the charge and the electrical fields have to be huge (~ 10^{21} Volts/cm). These stars are not however stable from the viewpoint that each charged particle is unbound to the uncharged particles, and thus the system collapses one step further to a charged black hole

  2. Charging Black Saturn?

    E-Print Network [OSTI]

    Brenda Chng; Robert Mann; Eugen Radu; Cristian Stelea

    2008-10-28T23:59:59.000Z

    We construct new charged static solutions of the Einstein-Maxwell field equations in five dimensions via a solution generation technique utilizing the symmetries of the reduced Lagrangian. By applying our method on the multi-Reissner-Nordstrom solution in four dimensions, we generate the multi-Reissner-Nordstrom solution in five dimensions. We focus on the five-dimensional solution describing a pair of charged black objects with general masses and electric charges. This solution includes the double Reissner-Nordstrom solution as well as the charged version of the five-dimensional static black Saturn. However, all the black Saturn configurations that we could find present either a conical singularity or a naked singularity. We also obtain a non-extremal configuration of charged black strings that reduces in the extremal limit to a Majumdar-Papapetrou like solution in five dimensions.

  3. National Dioxin Study Tier 4 - combustion sources: final test report - Site 10, secondary-copper-recovery cupola furnace MET-A

    SciTech Connect (OSTI)

    Keller, L.E.; McReynolds, J.R.; Benson, D.J.

    1987-04-01T23:59:59.000Z

    This report summarizes the results of a dioxin/furan emissions test of a secondary-copper-recovery cupola furnace equipped with an afterburner for hydrocarbon emissions control and two baghouses for particulate-emissions control. The cupola furnace is used for recovery of copper from telephone scrap and other copper-bearing materials. The test was No. 10 in a series of dioxin/furan emissions tests conducted under Tier 4 of the National Dioxin Study. The primary objective of Tier 4 is to determine if various combustion sources are sources of dioxin/or furan emissions. If any of the combustion sources are found to emit dioxin or furan, the secondary objective of Tier 4 is to quantify these emissions. Secondary-copper-recovery cupola furnaces are one of 8 combustion-source categories that have been tested in the Tier 4 program. The tested cupola furnace, MET-A, was selected for the test after an initial information screening and a one-day pretest survey visit. Cupola furnace MET-A is a large secondary-copper-recovery cupola furnace relative to others in the United States. The furnace feed includes plastic-bearing materials of various types, some of which may contain chlorinated organic compounds. Data presented in the report include dioxin (tera through octa homologue +2378 TCDD) and furan (tetra through octa homologue +2378 TCDF) results for both stack samples and ash samples. In addition, process data collected during sampling are also presented.

  4. 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...

  5. 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...

  6. 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 ...

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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...

  12. 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...

  13. 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...

  14. 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

  15. 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 -...

  16. 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

  17. 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...

  18. 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...

  19. 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...

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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...

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. A Dynamic Algorithm for Facilitated Charging of Plug-In Electric Vehicles

    E-Print Network [OSTI]

    Taheri, Nicole; Ye, Yinyu

    2011-01-01T23:59:59.000Z

    Plug-in Electric Vehicles (PEVs) are a rapidly developing technology that can reduce greenhouse gas emissions and change the way vehicles obtain power. PEV charging stations will most likely be available at home and at work, and occasionally be publicly available, offering flexible charging options. Ideally, each vehicle will charge during periods when electricity prices are relatively low, to minimize the cost to the consumer and maximize societal benefits. A Demand Response (DR) service for a fleet of PEVs could yield such charging schedules by regulating consumer electricity use during certain time periods, in order to meet an obligation to the market. We construct an automated DR mechanism for a fleet of PEVs that facilitates vehicle charging to ensure the demands of the vehicles and the market are met. Our dynamic algorithm depends only on the knowledge of a few hundred driving behaviors from a previous similar day, and uses a simple adjusted pricing scheme to instantly assign feasible and satisfactory c...

  13. 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

  14. 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

  15. ERCOT's Weather Sensitive Demand Response Pilot

    E-Print Network [OSTI]

    Carter, T.

    2013-01-01T23:59:59.000Z

    ERCOT’s 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...

  16. 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 CPSE’s DR Program • DR... than the military bases and Toyota combined. • Schools & Universities contributed 6 MW’s 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...

  17. taking charge : optimizing urban charging infrastructure for shared electric vehicles

    E-Print Network [OSTI]

    Subramani, Praveen

    2012-01-01T23:59:59.000Z

    This thesis analyses the opportunities and constraints of deploying charging infrastructure for shared electric vehicles in urban environments. Existing electric vehicle charging infrastructure for privately owned vehicles ...

  18. 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.

  19. Empirical analysis of the spot market implications ofprice-elastic demand

    SciTech Connect (OSTI)

    Siddiqui, Afzal S.; Bartholomew, Emily S.; Marnay, Chris

    2004-07-08T23:59:59.000Z

    Regardless of the form of restructuring, deregulated electricity industries share one common feature: the absence of any significant, rapid demand-side response to the wholesale (or, spotmarket) price. For a variety of reasons, electricity industries continue to charge most consumers an average cost based on regulated retail tariff from the era of vertical integration, even as the retailers themselves are forced to purchase electricity at volatile wholesale prices set in open markets. This results in considerable price risk for retailers, who are sometimes forbidden by regulators from signing hedging contracts. More importantly, because end-users do not perceive real-time (or even hourly or daily) fluctuations in the wholesale price of electricity, they have no incentive to adjust their consumption in response to price signals. Consequently, demand for electricity is highly inelastic, and electricity generation resources can be stretched to the point where system stability is threatened. This, then, facilitates many other problems associated with electricity markets, such as market power and price volatility. Indeed, economic theory suggests that even modestly price-responsive demand can remove the stress on generation resources and decrease spot prices. To test this theory, we use actual generator bid data from the New York control area to construct supply stacks, and intersect them with demand curves of various slopes to approximate different levels of demand elasticity. We then estimate the potential impact of real-time pricing on the equilibrium spot price and quantity. These results indicate the immediate benefits that could be derived from a more price-elastic demand. Such analysis can provide policymakers with a measure of how effective price-elastic demand can potentially reduce prices and maintain consumption within the capability of generation resources.

  20. 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

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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.

  7. Abstract adiabatic charge pumping

    E-Print Network [OSTI]

    A. Joye; V. Brosco; F. Hekking

    2010-02-05T23:59:59.000Z

    This paper is devoted to the analysis of an abstract formula describing quantum adiabatic charge pumping in a general context. We consider closed systems characterized by a slowly varying time-dependent Hamiltonian depending on an external parameter $\\alpha$. The current operator, defined as the derivative of the Hamiltonian with respect to $\\alpha$, once integrated over some time interval, gives rise to a charge pumped through the system over that time span. We determine the first two leading terms in the adiabatic parameter of this pumped charge under the usual gap hypothesis. In particular, in case the Hamiltonian is time periodic and has discrete non-degenerate spectrum, the charge pumped over a period is given to leading order by the derivative with respect to $\\alpha$ of the corresponding dynamical and geometric phases.

  8. International aeronautical user charges

    E-Print Network [OSTI]

    Odoni, Amedeo R.

    1985-01-01T23:59:59.000Z

    Introduction: 1.1 BACKGROUND AND MOTIVATION Very few issues relating to the international air transportation industry are today as divisive as those pertaining to user charges imposed at international airports and enroute ...

  9. 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

  10. 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

  11. 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

  12. 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

  13. Electrically charged targets

    DOE Patents [OSTI]

    Goodman, Ronald K. (Livermore, CA); Hunt, Angus L. (Alamo, CA)

    1984-01-01T23:59:59.000Z

    Electrically chargeable laser targets and method for forming such charged targets in order to improve their guidance along a predetermined desired trajectory. This is accomplished by the incorporation of a small amount of an additive to the target material which will increase the electrical conductivity thereof, and thereby enhance the charge placed upon the target material for guidance thereof by electrostatic or magnetic steering mechanisms, without adversely affecting the target when illuminated by laser energy.

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

    E-Print Network [OSTI]

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

    1992-01-01T23:59:59.000Z

    . Dennis L. O'Neal Department of Mechanical Engineering Texas A & M University College Station, TX Federal and state governments can also impact the choice of central air conditioners/heat pumps through requirements mandated by legislation.... The National Energy Efficient Appliances Act requires an SEER of JO for all split-system central air conditioners or heat pumps manufactured after January 1, 1992, and an SEER of 9.7 for all package systems manufactured after January 1, 1993 [I]. Electric...

  15. ASSESSING THE POTENTIAL FOR ROAD AND PARKING CHARGES TO REDUCE DEMAND FOR

    E-Print Network [OSTI]

    Vancouver region. Examining Committee: Senior Supervisor: Mark Jaccard Associate Professor School problems on the local, regional and global scale. The external nature of many automobile use costs

  16. California PG&E E-19 Rate Structure -- demand charge structure...

    Open Energy Info (EERE)

    correctly? Do the upcoming schema changes address these issues? Thanks for your help. -Allan Groups: Utility Rate Login to post comments Allandaly's blog Comments Allandaly...

  17. how can I sort utilities by demand charge? | OpenEI Community

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapersWindey Wind Home Rmckeel's Homeguidance document

  18. California PG&E E-19 Rate Structure -- demand charge structure doesn't seem

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:Power LP Biomass Facilityin ChartsQuality Act Jumpto fit current schema

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag Jump to: navigation,ProjectStartDateProperty EditResults Jump to:

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, search OpenEIHesperia, California:Project Jump to:Would You Rebuild a Town

  1. Property:OpenEI/UtilityRate/DemandChargePeriod1 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump Jump to: navigation,

  2. Property:OpenEI/UtilityRate/DemandChargePeriod1FAdj | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump Jump to: navigation,Information

  3. Property:OpenEI/UtilityRate/DemandChargePeriod2 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump Jump to: navigation,Information

  4. Property:OpenEI/UtilityRate/DemandChargePeriod2FAdj | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump Jump to:

  5. Property:OpenEI/UtilityRate/DemandChargePeriod4FAdj | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump Jump

  6. Property:OpenEI/UtilityRate/DemandChargePeriod7 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump

  7. Property:OpenEI/UtilityRate/DemandChargePeriod7FAdj | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump

  8. Property:OpenEI/UtilityRate/DemandChargePeriod8 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump

  9. Property:OpenEI/UtilityRate/DemandChargePeriod8FAdj | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump

  10. Property:OpenEI/UtilityRate/DemandChargePeriod9 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump

  11. Property:OpenEI/UtilityRate/DemandChargePeriod9FAdj | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County,NumberOfNonCorporateOrganizations Jump

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation

  13. Deployment of Behind-The-Meter Energy Storage for Demand Charge Reduction

    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 wouldDECOMPOSITIONPortalTo helpUniversitiesofDepartmental

  14. 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

  15. Improving Grid Performance with Electric Vehicle Charging 2011San Diego Gas & Electric Company. All copyright and trademark rights reserved.

    E-Print Network [OSTI]

    California at Davis, University of

    Improving Grid Performance with Electric Vehicle Charging © 2011San Diego Gas & Electric Company · Education SDG&E Goal ­ Grid Integrated Charging · More plug-in electric vehicles · More electric grid to a hairdryer) per PEV in the population · Instantaneous demand, 40 all-electric vehicles for one day (8

  16. 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

  17. Models and Solution Approaches for Emergency Response Network Design Integrating Supply and Demand Sides

    E-Print Network [OSTI]

    Dalal, Jyotirmoy

    2014-12-02T23:59:59.000Z

    We present three models for emergency response network design. First, in a deterministic setting, we focus on two critical aspects of emergency logistics: evacuation and relief distribution. We consider a three-tier system comprising evacuation...

  18. 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 ...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Quick charge battery

    SciTech Connect (OSTI)

    Parise, R.J.

    1998-07-01T23:59:59.000Z

    Electric and hybrid electric vehicles (EVs and HEVs) will become a significant reality in the near future of the automotive industry. Both types of vehicles will need a means to store energy on board. For the present, the method of choice would be lead-acid batteries, with the HEV having auxiliary power supplied by a small internal combustion engine. One of the main drawbacks to lead-acid batteries is internal heat generation as a natural consequence of the charging process as well as resistance losses. This limits the re-charging rate to the battery pack for an EV which has a range of about 80 miles. A quick turnaround on recharge is needed but not yet possible. One of the limiting factors is the heat buildup. For the HEV the auxiliary power unit provides a continuous charge to the battery pack. Therefore heat generation in the lead-acid battery is a constant problem that must be addressed. Presented here is a battery that is capable of quick charging, the Quick Charge Battery with Thermal Management. This is an electrochemical battery, typically a lead-acid battery, without the inherent thermal management problems that have been present in the past. The battery can be used in an all-electric vehicle, a hybrid-electric vehicle or an internal combustion engine vehicle, as well as in other applications that utilize secondary batteries. This is not restricted to only lead-acid batteries. The concept and technology are flexible enough to use in any secondary battery application where thermal management of the battery must be addressed, especially during charging. Any battery with temperature constraints can benefit from this advancement in the state of the art of battery manufacturing. This can also include nickel-cadmium, metal-air, nickel hydroxide, zinc-chloride or any other type of battery whose performance is affected by the temperature control of the interior as well as the exterior of the battery.

  4. Holographic Charge Oscillations

    E-Print Network [OSTI]

    Mike Blake; Aristomenis Donos; David Tong

    2014-12-05T23:59:59.000Z

    The Reissner-Nordstrom black hole provides the prototypical description of a holographic system at finite density. We study the response of this system to the presence of a local, charged impurity. Below a critical temperature, the induced charge density, which screens the impurity, exhibits oscillations. These oscillations can be traced to the singularities in the density-density correlation function moving in the complex momentum plane. At finite temperature, the oscillations are very similar to the Friedel oscillations seen in Fermi liquids. However, at zero temperature the oscillations in the black hole background remain exponentially damped, while Friedel oscillations relax to a power-law

  5. Overview of charge symmetry

    SciTech Connect (OSTI)

    Miller, G.A. [Department of Physics, FM-15, University of Washington, Seattle, Washington 98195 (United States)

    1995-07-15T23:59:59.000Z

    Charge independence and symmetry are approximate symmetries of nature. The observations of the small charge symmetry breaking effects and the consequences of those effects are reviewed. The effects of the mass difference between up and down quarks and the off shell dependence {ital q}{sup 2} of {rho}{sup 0}-{omega} mixing are stressed. We find that models which predict a strong {ital q}{sup 2} dependence of {rho}{sup 0}-{omega} mixing seem also to predict a strong {ital q}{sup 2} variation for the {rho}{sup 0}-{gamma}* matrix element, in contradiction with experiment.

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

    E-Print Network [OSTI]

    Ghatikar, Girish

    2014-01-01T23:59:59.000Z

    Automated  Demand  Response  in  Commercial  Buildings.  Demand  Response  Infrastructure  for   Commercial  Buildings.  

  7. LNG demand, shipping will expand through 2010

    SciTech Connect (OSTI)

    True, W.R.

    1998-02-09T23:59:59.000Z

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

  8. Reducing the demand forecast error due to the bullwhip effect in the computer processor industry

    E-Print Network [OSTI]

    Smith, Emily (Emily C.)

    2010-01-01T23:59:59.000Z

    Intel's current demand-forecasting processes rely on customers' demand forecasts. Customers do not revise demand forecasts as demand decreases until the last minute. Intel's current demand models provide little guidance ...

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformation DemandReactivePowerCharge Jump to: navigation, search This is

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8 Jump

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkinsInformationInformation FixedDemandChargeMonth8

  12. Demand Controlled Filtration in an Industrial Cleanroom

    SciTech Connect (OSTI)

    Faulkner, David; DiBartolomeo, Dennis; Wang, Duo

    2007-09-01T23:59:59.000Z

    In an industrial cleanroom, significant energy savings were realized by implementing two types of demand controlled filtration (DCF) strategies, one based on particle counts and one on occupancy. With each strategy the speed of the recirculation fan filter units was reduced to save energy. When the control was based on particle counts, the energy use was 60% of the baseline configuration of continuous fan operation. With simple occupancy sensors, the energy usage was 63% of the baseline configuration. During the testing of DCF, no complaints were registered by the operator of the cleanroom concerning processes and products being affected by the DCF implementation.

  13. Demand-Side Response from Industrial Loads

    SciTech Connect (OSTI)

    Starke, Michael R [ORNL; Alkadi, Nasr E [ORNL; Letto, Daryl [Enbala Power Networks; Johnson, Brandon [University of Tennessee, Knoxville (UTK); Dowling, Kevin [University of Tennessee, Knoxville (UTK); George, Raoule [Enbala Power Networks; Khan, Saqib [University of Texas, Austin

    2013-01-01T23:59:59.000Z

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

  14. The Economics of Energy (and Electricity) Demand

    E-Print Network [OSTI]

    Platchkov, Laura M.; Pollitt, Michael G.

    13 taxation on the use of energy.6 This is in addition to taxation of the profits of energy companies and taxes on the production of oil and gas in the North Sea. Any migration of energy demand from heavily taxed liquid fuels to currently lightly... also be substituted for energy expenditure in the future (e.g. solar panels as part of a new roof). The figure shows that substantial amount of expenditure on transport where expenditure on vehicles and on their repair exceeds expenditure on fuel...

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

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluating A Potential Microhydro SiteDayton Power & LightDemand Management

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

    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,DemandEnergy

  17. Demand Response and Smart Metering Policy Actions Since the Energy...

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

    This report represents a review of policy developments on demand response and other related areas such as smart meters and smart grid. It has been prepared by the Demand Response...

  18. Quantifying the Variable Effects of Systems with Demand Response Resources

    E-Print Network [OSTI]

    Gross, George

    Quantifying the Variable Effects of Systems with Demand Response Resources Anupama Kowli and George in the electricity industry. In particular, there is a new class of consumers, called demand response resources (DRRs

  19. Grid Integration of Aggregated Demand Response, Part I: Load Availability

    E-Print Network [OSTI]

    LBNL-6417E Grid Integration of Aggregated Demand Response, Part I: Load Availability Profiles Resources 4 #12;#12;#12;CHAPTER 3: Results: DR Profiles 3.1 Projected Demand Response Availability in 2020

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

    E-Print Network [OSTI]

    Todd, Michael J.

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