• DocumentCode
    3021662
  • Title

    Reactive Power Optimization in Power System Based on Adaptive Focusing Particle Swarm Optimization

  • Author

    Liu, Shu-kui ; Tang, Jing ; Li, Qi ; Wu, Xia ; Luo, Yan

  • Author_Institution
    Chengdu Electr. Power Bur., Chengdu, China
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Firstpage
    4003
  • Lastpage
    4006
  • Abstract
    Adaptive focusing particle swarm optimization (AFPSO) based on the balance characteristic between global search and local search of particle swarm optimization was an adaptive swarm intelligence optimization algorithm with preferable ability of global search and search rate. AFPSO was proposed to optimize the reactive power optimization. Based on optimal control principle, AFPSO applied for optimal reactive power is evaluated on an IEEE 57-bus power system. The modeling of reactive power optimization is established taking the minimum network losses as the objective. The simulation results and the comparison results with various optimization algorithms demonstrated that the proposed approach converges to better solutions than and the algorithm can make effectively use in reactive power optimization. Simultaneously, the validity and superiority of AFPSO was proved.
  • Keywords
    adaptive control; optimal control; particle swarm optimisation; power system control; reactive power control; search problems; IEEE 57-bus power system; adaptive focusing particle swarm optimization; balance characteristic; global search; optimal control; power system; reactive power optimization; search rate; Algorithm design and analysis; Convergence; Generators; Optimization; Particle swarm optimization; Reactive power; Adaptive focusing particle swarm optimization; Power system; Reactive power optimization; Swarm intelligence;
  • 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.2010.975
  • Filename
    5631981