• DocumentCode
    558379
  • Title

    An improved genetic algorithm and graph theory based method for optimal sectionalizer switch placement in distribution networks with DG

  • Author

    Vahidnia, Arash ; Ledwich, Gerard ; Ghosh, Arindam ; Palmer, Edward

  • Author_Institution
    Sch. of Eng. Syst., Queensland Univ. of Technol., Brisbane, QLD, Australia
  • fYear
    2011
  • fDate
    25-28 Sept. 2011
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    In this paper a new graph-theory and improved genetic algorithm based practical method is employed to solve the optimal sectionalizer switch placement problem. The proposed method determines the best locations of sectionalizer switching devices in distribution networks considering the effects of presence of distributed generation (DG) in fitness functions and other optimization constraints, providing the maximum number of costumers to be supplied by distributed generation sources in islanded distribution systems after possible faults. The proposed method is simulated and tested on several distribution test systems in both cases of with DG and non DG situations. The results of the simulations validate the proposed method for switch placement of the distribution network in the presence of distributed generation.
  • Keywords
    distributed power generation; distribution networks; genetic algorithms; graph theory; DG; distributed generation; distribution networks; distribution test systems; genetic algorithm; graph theory; graph-theory; optimal sectionalizer switch placement; optimization constraints; Biological cells; Distributed power generation; Genetic algorithms; Optimization; Power system reliability; Reliability; Switches; Distributed Generation (DG); Distribution Networks; Genetic Algorithm (GA); Reliability; Spanning Tree;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Universities Power Engineering Conference (AUPEC), 2011 21st Australasian
  • Conference_Location
    Brisbane, QLD
  • Print_ISBN
    978-1-4577-1793-2
  • Type

    conf

  • Filename
    6102509