• DocumentCode
    3117391
  • Title

    A genetic algorithm for the reactive power/voltage control problem

  • Author

    Malachi, Yair ; Singer, Sigmund

  • Author_Institution
    Planning, Dev. & Technol. Div., Israel Electr. Corp. Ltd., Haifa, Israel
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    218
  • Lastpage
    221
  • Abstract
    This paper presents an algorithm for the control of bus voltage and generator reactive power in an electricity supply system. Classic solution methods such as linear programming make use of linear approximations of system equations and as such have a limited precision. Genetic algorithms, connected to standard load flow calculations, do not need such approximations and are capable of finding numerous solutions for the emergency control of disturbed bus voltages. The disadvantage of GAs is the heavy computational burden. The paper presents a way of combining the benefits of linear approximation and a genetic algorithm into a solution method for the minimum number of control actions possible. The algorithm was demonstrated on a 300 bus model of the Israel Electric network
  • Keywords
    electric generators; genetic algorithms; linear programming; load flow; machine control; power system control; reactive power control; voltage control; 300 bus model; Israel Electric network; disturbed bus voltages; electricity supply system; emergency control; generator reactive power control; genetic algorithm; genetic algorithms; limited precision; linear approximation; linear approximations; linear programming; load flow calculations; reactive power control; system equations; voltage control; Control systems; Equations; Genetic algorithms; Linear approximation; Load flow; Optimal control; Power generation; Reactive power; Reactive power control; Voltage control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and electronic engineers in israel, 2000. the 21st ieee convention of the
  • Conference_Location
    Tel-Aviv
  • Print_ISBN
    0-7803-5842-2
  • Type

    conf

  • DOI
    10.1109/EEEI.2000.924374
  • Filename
    924374