• DocumentCode
    1712679
  • Title

    An Efficient Multi-objective Meta-heuristic Method for Distribution Network Expansion Planning

  • Author

    Mori, Hiroyuki ; Yamada, Yoshinori

  • Author_Institution
    Dept. of Electron. & Bioinf., Meiji Univ., Kawasaki
  • fYear
    2007
  • Firstpage
    374
  • Lastpage
    379
  • Abstract
    This paper proposes a new method for distribution network expansion planning. The proposed method is based on SPEA2 (strength Pareto evolutionary algorithm 2) of multi-objective meta-heuristics. As power systems are deregulated, the power market becomes more competitive. Hence, the cost minimization has been recognized as one of the most important factors in distribution systems. Apart from the cost minimization, the network loss minimization and the power quality are also important. This paper focuses on distribution network expansion planning under new environment with distribution generations (DG). It needs to deal with multi-objective optimization. In this paper, SPEA2 that is effective for evaluating the Pareto solution set is used to solve the multi-objective network expansion planning problem. It has advantage in finding out a set of Pareto solutions with the strategies of using both the archives and the evaluated solution set. The proposed method is successfully applied to the 69-node distribution system with DG units.
  • Keywords
    Pareto analysis; cost reduction; evolutionary computation; power distribution economics; power distribution planning; power markets; power supply quality; cost minimization; distribution generations; distribution network expansion planning; multiobjective metaheuristic method; network loss minimization; power market; power quality; strength Pareto evolutionary algorithm 2; Constraint optimization; Costs; Evolutionary computation; Optimization methods; Pareto optimization; Power markets; Power quality; Power system planning; Power system security; Substations; Distribution network expansion planning; Multi-objective optimization; Strength Pareto Evolutionary Algorithm 2;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Tech, 2007 IEEE Lausanne
  • Conference_Location
    Lausanne
  • Print_ISBN
    978-1-4244-2189-3
  • Electronic_ISBN
    978-1-4244-2190-9
  • Type

    conf

  • DOI
    10.1109/PCT.2007.4538346
  • Filename
    4538346