• DocumentCode
    1795670
  • Title

    Efficient optimal scheduling of charging station with multiple electric vehicles via V2V

  • Author

    Pengcheng You ; Zaiyue Yang

  • Author_Institution
    State Key Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China
  • fYear
    2014
  • fDate
    3-6 Nov. 2014
  • Firstpage
    716
  • Lastpage
    721
  • Abstract
    This paper investigates the scheduling problem of an intermediary charging station with multiple electric vehicles (EV) in real-time electricity pricing environment. A charging aggregator (CA) is in charge to coordinate EVs´ charging so that all EVs´ requirements are met and meanwhile the total social cost is minimized. Besides, a new charging mechanism named Vehicle-to-Vehicle (V2V) is proposed to take full advantage of every EV´s battery energy. Due to the binary state of EVs, i.e., charging and discharging, scheduling of the charging station is formulated as a constrained mixed-integer linear program (MILP). A distributed algorithm is applied to solve the problem by means of dual decomposition and Benders decomposition. Therefore, scheduling is carried out on each EV and coordinated by the CA. Numerical results show efficiency of the proposed approach and validate our theoretical analysis.
  • Keywords
    battery powered vehicles; integer programming; linear programming; pricing; scheduling; Benders decomposition; V2V; charging aggregator; charging station; constrained mixed-integer linear program; distributed algorithm; dual decomposition; multiple electric vehicles; optimal scheduling; real-time electricity pricing environment; vehicle-to-vehicle charging mechanism; Batteries; Charging stations; Conferences; Electricity; Optimal scheduling; Real-time systems; Smart grids;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Smart Grid Communications (SmartGridComm), 2014 IEEE International Conference on
  • Conference_Location
    Venice
  • Type

    conf

  • DOI
    10.1109/SmartGridComm.2014.7007732
  • Filename
    7007732