• DocumentCode
    2057997
  • Title

    A Dynamic Methodology Based in Hybrid Genetic and Fuzzy Logic Rules with Multi Shunt FACTS Devices to Enhance the Optimal Power Flow

  • Author

    Mahdad, Belkacem ; Bouktir, Tarek ; Srairi, Kamel

  • Author_Institution
    Department of Electrical Engineering, University of Biskra, BP 145, Biskra 07000, ALGERIA. bemahdad@yahoo.fr
  • fYear
    2007
  • fDate
    12-14 April 2007
  • Firstpage
    312
  • Lastpage
    317
  • Abstract
    In this paper an hybrid Genetic Algorithm and Fuzzy Logic rules is proposed to minimize the generator fuel cost with multi shunt Flexible AC Transmission Systems (FACTS). The problem is decomposed into, the optimal power generation subproblem that is searched by Genetic Algorithm and a simple practical reasoning fuzzy rules subproblem to control the reactive power exchanged with the network. The proposed method guarantees the near optimal solution and remarkably reduces the computation time. A global database generated based in reactive index sensitivity (RIS) as a flexible tool to choose economically the size of the shunt FACTS devices. This proposed approach is implemented with Matlab program with various case studies, and compared with conventional method and genetic algorithm (GA). The results show that the HGF can converge to optimum solution faster than other methods, and obtains the solution with high accuracy.
  • Keywords
    AC generators; Costs; Flexible AC transmission systems; Fuels; Fuzzy logic; Genetic algorithms; Hybrid power systems; Load flow; Power generation; Power generation economics; Economic dispatch(ED); FACTS; Fuzzy logic; Hybrid method; Optimal power flow; SVC; constrained optimization; genetic algorithm; heuristic optimization techniques;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering, Energy and Electrical Drives, 2007. POWERENG 2007. International Conference on
  • Conference_Location
    Setubal, Portugal
  • Print_ISBN
    978-1-4244-0895-5
  • Electronic_ISBN
    978-1-4244-0895-5
  • Type

    conf

  • DOI
    10.1109/POWERENG.2007.4380203
  • Filename
    4380203