• DocumentCode
    131753
  • Title

    A hybrid algorithm for planning public charging stations

  • Author

    Bendiabdellah, Zoulikha ; Senouci, Sidi Mohammed ; Feham, Mohamed

  • Author_Institution
    STIC Lab., Abou Bekr Belkaid Univ., Tlemcen, Algeria
  • fYear
    2014
  • fDate
    15-19 Sept. 2014
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Green mobility solutions are receiving currently an enormous attention. Indeed, during last years, electric vehicles, being part of the field of the smart-grid, entered the automobile market of the whole world. This technology requires an effective deployment of charging stations of electric refill since the main problem in this system remains over the duration of refill of the batteries. In this work, we propose an optimized algorithm to locate electric charging stations. The main task of the algorithm is to find the best site of charging stations locations so as to minimize loss on the way to the charging station, as well as minimize investment cost, we take into account several constraints to find the optimal number and placement of charging station. Our hybrid algorithm with improved K-means clustering and genetic algorithm can be used to find optimal number and place of charging stations.
  • Keywords
    electric vehicles; genetic algorithms; pattern clustering; K-means clustering; electric charging stations locations; genetic algorithm; hybrid algorithm; investment cost minimization; optimized algorithm; public charging stations planning; Charging stations; Clustering algorithms; Genetic algorithms; Genetics; Investment; Mathematical model; Optimization; Smart-Grid; charging stations; electric vehicles; genetic optimization; k-means clustring;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Information Infrastructure and Networking Symposium (GIIS), 2014
  • Conference_Location
    Montreal, QC
  • Type

    conf

  • DOI
    10.1109/GIIS.2014.6934262
  • Filename
    6934262