• DocumentCode
    1574053
  • Title

    Optimum number, placement and capacity of DGs and reclosers using analysis hierarchical process and genetic algorithm

  • Author

    Jafari, Masoud ; Monsef, Hasan ; Moghadam, Saeed Zolfaghari

  • Author_Institution
    Univ. of Tehran, Tehran, Iran
  • fYear
    2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    One of the remarkable phenomena in power systems is the appearance of Distributed Generation (DGs). DGs may reduce the number and/or duration of interruptions for customer residing within their protection zones. DGs also can improve losses and voltage profile of system. In this paper a composition of Genetic algorithm (GA) and Analysis Hierarchical Process (AHP) are presented. The proposed algorithm uses GA algorithm for optimal placement and capacity of DGs and reclosers in the network. In the next stage, by using of AHP method, the optimal number of reclosers and DGs are determined based on economic and power quality considerations. This method was carried out on a modified 33 feeders IEEE distribution network. Simulation results validate the effectiveness of the proposed method.
  • Keywords
    decision making; distributed power generation; genetic algorithms; power distribution lines; power supply quality; AHP method; DG; GA; IEEE distribution network; analysis hierarchical process method; distributed generation; economic quality; genetic algorithm; optimum capacity; optimum number; optimum placement; power quality; recloser; Algorithm design and analysis; Genetic algorithms; Optimization; Power system reliability; Reactive power; Reliability; Resource management; analytical hierarchy process; distributed generation; genetic algorithm; optimum allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environment and Electrical Engineering (EEEIC), 2011 10th International Conference on
  • Conference_Location
    Rome
  • Print_ISBN
    978-1-4244-8779-0
  • Type

    conf

  • DOI
    10.1109/EEEIC.2011.5874832
  • Filename
    5874832