• DocumentCode
    2183215
  • Title

    Direct load management of electric vehicles

  • Author

    Alizadeh, Mahnoosh ; Scaglione, Anna ; Thomas, Robert J.

  • Author_Institution
    Univ. of California, Davis, CA, USA
  • fYear
    2011
  • fDate
    22-27 May 2011
  • Firstpage
    5964
  • Lastpage
    5967
  • Abstract
    Electrical Vehicles are gaining increasing attention, due to the opportunities and challenges they present for the energy market. On the one hand, they will allow to drastically reduce the need for oil; on the other hand they may require a significant shift in the day to day management of the electricity generation. This paper is concerned with finding appropriate models for residential load in light of a widespread penetration of electric vehicles. The analysis is aimed at finding a SmartGrid solution that would enable us to optimize the generation dispatch in real time and allow to plug cars in any SmartGrid enabled plug. The key idea is to discriminate between regular load and the load due to the EVs, gathering in real time aggregate information about the sensed EV arrivals and their associated charging times in a demand matrix, that can be readily used to optimize the dispatch, while updating without real time constraints the billing record for the EV.
  • Keywords
    electric vehicles; load management; power generation dispatch; power markets; smart power grids; billing record; demand matrix; direct load management; electric vehicle; electricity generation management; energy market; generation dispatch; real time aggregate information; residential load; smart grid; widespread penetration; Electric vehicles; Load forecasting; Load modeling; Mobile communication; Predictive models; Real time systems; Communication; Direct Load Control; Electric Vehicles; Load Forecast; Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
  • Conference_Location
    Prague
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4577-0538-0
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2011.5947720
  • Filename
    5947720