• DocumentCode
    2996502
  • Title

    Combining Strategy of Genetic Algorithm and Particle Swarm Algorithm for Reactive Power Optimization

  • Author

    Lu, Jingui ; Zhang, Li ; Yang, Hong

  • Author_Institution
    CAD Center, Nanjing Univ. of Technol., Nanjing, China
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Firstpage
    3613
  • Lastpage
    3616
  • Abstract
    This paper is involved in reactive power optimization. The combining strategy of genetic algorithm and particle swarm algorithm is proposed for the optimization problem of reactive power in this paper. It is necessary that the initial individuals are feasible ones, and good individuals are chosen as the initial particles in the combining strategy. The numerical examples of IEEE-6 and IEEE-30 power systems for the combining strategy are performed for the reactive power optimization. The effectiveness of the combining strategy proposed in this paper has been demonstrated preliminarily from the examples.
  • Keywords
    genetic algorithms; particle swarm optimisation; reactive power; IEEE-30 power system; IEEE-6 power system; genetic algorithm; particle swarm algorithm; reactive power optimization; Gallium; Generators; Load flow; Optimization; Particle swarm optimization; Reactive power; garticle swarm optimization algorithm; genetic algorithm; reactive power optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Control Engineering (ICECE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6880-5
  • Type

    conf

  • DOI
    10.1109/iCECE.2010.882
  • Filename
    5630695