• DocumentCode
    1675627
  • Title

    An adaptive particle swarm optimization algorithm for reactive power optimization in power system

  • Author

    Wu, Enqi ; Huang, Yue ; Li, Dan

  • Author_Institution
    Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Baoding, China
  • fYear
    2010
  • Firstpage
    3132
  • Lastpage
    3137
  • Abstract
    An adaptive particle swarm optimization(APSO) algorithm is presented to solve the problem that the standard particle swarm optimization(PSO) algorithm is easy to fall into a locally optimized point, where inertia weight is nonlinearly adjusted by using population diversity information. Velocity mutation factor and position interchange factor are both introduced. The APSO algorithm thus improves its solvability for global optimization to avoid effectively the precocious convergence. The new algorithm is applied to reactive power optimization of the standard IEEE-30-bus power system as instances, and the simulation results show the effectiveness and feasibility of APSO algorithm for the reactive power optimization. It is proved to be efficient and practical during the reactive power optimization.
  • Keywords
    particle swarm optimisation; power systems; reactive power; adaptive particle swarm optimization algorithm; inertia weight; population diversity information; position interchange factor; reactive power optimization; standard IEEE-30-bus power system; velocity mutation factor; Convergence; Equations; Mathematical model; Optimization; Particle swarm optimization; Reactive power; adaptive mutation; particle swarm optimization; reactive power optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2010 8th World Congress on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-6712-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2010.5553988
  • Filename
    5553988