• DocumentCode
    3329314
  • Title

    Application of Evolution Algorithm in Power System Control Design

  • Author

    Folly, KA

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Cape Town, Cape Town
  • fYear
    2007
  • fDate
    16-20 July 2007
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Power system controller design based on an evolutionary algorithm called population based incremental learning (PBIL) is proposed in this paper. The problem of controller design is transformed into an optimization problem and the parameters of the controller are determined via PBIL. The proposed method has the advantage that it is simpler, faster and more efficient than both the classical trial and error approach of designing PSS and the genetic algorithms (GAs). The PBIL-PSS is compared with the GA-PSS. Simulation results show that PBIL-PSS is more effective than GA-PSS in damping the system´s oscillations.
  • Keywords
    control system synthesis; genetic algorithms; oscillations; power system control; power system stability; controller design; error approach; evolutionary algorithm; genetic algorithms; population based incremental learning; power system control design; system oscillations; Africa; Algorithm design and analysis; Cities and towns; Control systems; Damping; Evolution (biology); Genetic algorithms; Power system control; Power system stability; Power systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society Conference and Exposition in Africa, 2007. PowerAfrica '07. IEEE
  • Conference_Location
    Johannesburg
  • Print_ISBN
    978-1-4244-1477-2
  • Electronic_ISBN
    978-1-4244-1478-9
  • Type

    conf

  • DOI
    10.1109/PESAFR.2007.4498046
  • Filename
    4498046