• DocumentCode
    188507
  • Title

    Anticipative charging of Plug-in Electric Vehicles and its impact on the grid

  • Author

    Kefayati, Mahdi ; Baldick, Ross

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Texas at Austin, Austin, TX, USA
  • fYear
    2014
  • fDate
    15-18 June 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Transportation electrification is deemed to have profound impacts on both transportation and electricity networks as well as our dependence on fossil fuels. Therefore, it is imperative to understand the impacts of this transition and prepare for it. Most of the literature on Plug-in Electric Vehicle (PEV) charging models treat charging sessions independently and ignore their interdependence. In this work, we argue the importance of understanding this interdependence, propose the anticipative charging model, and investigate its effect on PEV demand flexibility, PEV charging demand and the grid. We demonstrate that the anticipative behavior of the drivers, i.e. their (partial) knowledge of their transportation plan in near future, results in less overall flexibility in the PEV load. However, under certain conditions, it positively impacts the overall PEV load by moving it toward off peak hours.
  • Keywords
    electric vehicles; power grids; transportation; PEV anticipative charging demand; driver anticipative behavior; electricity network; plug-in electric vehicle grid; transportation electrification; Biological system modeling; Electric vehicles; Electricity; Load modeling; Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transportation Electrification Conference and Expo (ITEC), 2014 IEEE
  • Conference_Location
    Dearborn, MI
  • Type

    conf

  • DOI
    10.1109/ITEC.2014.6861805
  • Filename
    6861805