• DocumentCode
    2157432
  • Title

    The distribution network reconfiguration based on spanning tree

  • Author

    Chen, Jingrui ; Lv, Lin ; Xu, Xiaofeng

  • Author_Institution
    School of Electrical Engineering and Information, Key Laboratory of Smart Grid Sichuan University, Chengdu, China
  • fYear
    2010
  • fDate
    4-6 Dec. 2010
  • Firstpage
    7017
  • Lastpage
    7020
  • Abstract
    The genetic algorithm of intelligent optimization algorithm is important in the distribution system reconfiguration. Aiming at genetic algorithm, exact penalty function based fitness function is proposed in this paper. Introducing avoid cycle method decode chromosome produced by Grefenstette code and generate dendritic-shaped distribution network. The decoding process is as following: First, forming branch sets, one of sets is composed by the order of network branches, the other sets is composed by the order of cycle network branches. According to the rules that distribution network can´t be isolated operation and loop-net operation, at last generate dendritic-shaped distribution network. On this basis carrying on genetic evolution and then finding the minimum value of distribution network active loss. In order to evaluate algorithm performance, this paper propose optimization rate evaluation index which the probability of genetic algorithm find the global optimal solution. Three typical IEEE distribution systems are analyzed, and then we can obtain that the algorithm optimization ability has significantly improved, it is validity for different system.
  • Keywords
    Adaptive systems; Automation; Biological cells; Indexes; Optimization; Power systems; Traveling salesman problems; avoid cycle metho; branch set; distribution network; genetic algorithm; optimization rate evaluation index;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2010 2nd International Conference on
  • Conference_Location
    Hangzhou, China
  • Print_ISBN
    978-1-4244-7616-9
  • Type

    conf

  • DOI
    10.1109/ICISE.2010.5691620
  • Filename
    5691620