• DocumentCode
    2541751
  • Title

    Optimal power flow of the algerian network using genetic algorithm/fuzzy rules

  • Author

    Mahdad, Belkacem ; Bouktir, Tarek ; Srairi, Kamel

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Biskra, Biskra
  • fYear
    2008
  • fDate
    20-24 July 2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper presents a combined genetic algorithm and fuzzy logic rules to enhance the optimal power flow (OPF) with consideration of multi shunt flexible AC transmission systems (FACTS). The OPF problem is formulated as a nonlinear constrained objective optimization problem with both equality and inequality constraints. The problem is decomposed into, the optimal power generation subproblem that is searched by a flexible genetic algorithm which crossover and mutation adjusted by fuzzy expert rules and a simple practical reasoning fuzzy rules designed as a second subproblem to control the reactive power exchanged with the network. The proposed method guarantees the near optimal solution and remarkably reduces the computation time. This proposed approach is implemented with Matlab program and applied to the medium 59 bus of the Algerian network. The optimization results are compared to the solution given by the standard GA and ant colony method (ACO). This comparison confirms the efficiency of the proposed approach which makes it promising to solve the OPF with consideration of FACTS devices.
  • Keywords
    flexible AC transmission systems; fuzzy set theory; genetic algorithms; load flow; Algerian network; FACTS; Matlab program; ant colony method; equality-inequality constraints; fuzzy expert rules; fuzzy rules; genetic algorithm; multishunt flexible AC transmission systems; optimal power flow; Algorithm design and analysis; Constraint optimization; Flexible AC transmission systems; Fuzzy control; Fuzzy logic; Fuzzy reasoning; Genetic algorithms; Genetic mutations; Load flow; Power generation; Ant Colony; Economic dispatch(ED); FACTS; Fuzzy logic; Optimal power flow; SVC; genetic algorithm; reactive sensitivity index;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE
  • Conference_Location
    Pittsburgh, PA
  • ISSN
    1932-5517
  • Print_ISBN
    978-1-4244-1905-0
  • Electronic_ISBN
    1932-5517
  • Type

    conf

  • DOI
    10.1109/PES.2008.4596656
  • Filename
    4596656