• DocumentCode
    108370
  • Title

    Adaptive Electric Vehicle Charging Coordination on Distribution Network

  • Author

    Lunci Hua ; Jia Wang ; Chi Zhou

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA
  • Volume
    5
  • Issue
    6
  • fYear
    2014
  • fDate
    Nov. 2014
  • Firstpage
    2666
  • Lastpage
    2675
  • Abstract
    Electric vehicles (EVs) with large battery charging demands may cause detrimental impact on distribution grid stability without EV charging coordination. This paper proposes an on-line adaptive EV charing scheduling (OACS) framework to optimize EV charging schedules and reduce flow limit, voltage magnitude limit, 3-phase voltage imbalance limit, and transformer capacity violations. EV user convenience is considered and EV charging cost is optimized. DC power flow based optimizations is proposed for EV charging scheduling approximation and parallel ac power flow verification is used to verify the scheduling results. Incremental feasibility improvement procedure is further proposed to correct the scheduling discrepancy between dc linear model and the ac model. Experiments are performed on a modified IEEE 34 14.7 kV distribution system with different EV penetration levels to demonstrate performance comparisons between different scheduling schemes. The result shows that our proposed OACS framework optimizes the EV charging coordination problem efficiently.
  • Keywords
    approximation theory; cost reduction; electric vehicles; load flow; optimisation; power distribution economics; power system stability; secondary cells; smart power grids; 3-phase voltage imbalance limit reduction; AC model; DC linear model; DC power flow based optimizations; EV charging cost optimization; EV charging schedule optimization; EV charging scheduling approximation; IEEE 34 distribution system; OACS framework; adaptive electric vehicle charging coordination; battery charging demands; detrimental impact; distribution grid stability; distribution network; flow limit reduction; online adaptive EV charing scheduling framework; parallel AC power flow verification; transformer capacity violation reduction; voltage 14.7 kV; voltage magnitude limit reduction; Approximation methods; Electric vehicles; Load modeling; Optimization; Real-time systems; Scheduling; Demand coordination; distribution grid; electric vehicle (EV); optimization model; smart grid;
  • fLanguage
    English
  • Journal_Title
    Smart Grid, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1949-3053
  • Type

    jour

  • DOI
    10.1109/TSG.2014.2336623
  • Filename
    6863680