• DocumentCode
    2963936
  • Title

    Clustering power demand for feasibility study on transition to plugin hybrid electric vehicles

  • Author

    Jahromi, M. Hossein Moayyed ; Asaei, Behzad ; Haghdadi, Navid

  • Author_Institution
    ECE Dept., Univ. of Tehran, Tehran, Iran
  • fYear
    2011
  • fDate
    15-17 Nov. 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In order to make comprehensive investigation on feasibility of replacing conventional vehicle with plugin electric vehicle, the electricity grid limitation should be considered. Pdemand is one of the essential limitations. Moreover, historical data of demand profile could be used in simulation. Instead of considering whole data, some representatives could be utilized. Hard (K-means and K-medoid) and fuzzy (Fuzzy C-means and Gustafson Kessel) methods are used so as to find a few representatives for Pdemand, which describe their own clusters perfectly. Using validity measurement indices, optimal number of clusters and the best clustering technique are found out and finally relaying on Separation Invariant index, a comparison with a conventional technique is made.
  • Keywords
    demand side management; fuzzy set theory; hybrid electric vehicles; pattern clustering; power grids; Gustafson Kessel method; K-means method; K-medoid method; demand profile; electricity grid limitation; fuzzy C-means method; plugin hybrid electric vehicles; power demand clustering; separation invariant index; validity measurement indices; Clustering methods; Data models; Electricity; Indexes; Power demand; Power grids; Vehicles; Data clustering; Fuzzy clustering; Plugin Hybrid Electric Vehicle; Validity indices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Power and Energy Conversion Systems (EPECS), 2011 2nd International Conference on
  • Conference_Location
    Sharjah
  • Print_ISBN
    978-1-4577-0804-6
  • Type

    conf

  • DOI
    10.1109/EPECS.2011.6126824
  • Filename
    6126824