• DocumentCode
    2823155
  • Title

    Novel Adaptive Genetic Algorithm for Reactive Power Optimization of Power System

  • Author

    Yang Guang ; Liu Xin-rong

  • Author_Institution
    Inst. of Opt-Electron. Inf. Technol., Yantai Univ., Yantai, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In order to avoid the premature convergence and improve convergence rate, a novel adaptive genetic algorithm for reactive power optimization is discussed in detail. In reproduction operator, the method of retaining optimal individual is used to ensure the convergence and at the same time, the competition method is also adopted to keep the better dispersal of all individuals. In Mutation operator, the mutation probability Pm is improved based on adaptive genetic algorithm. When fitness of individuals in the population tends to be identical, Pm can be adjusted to make bigger, and the local convergence can be avoided greatly. The algorithm has been applied to IEEE 30-bus testing system .The test shows that this algorithm is feasible and practical.
  • Keywords
    genetic algorithms; power systems; reactive power; IEEE 30-bus testing system; adaptive genetic algorithm; mutation operator; power system; reactive power optimization; Evolutionary computation; Genetic algorithms; Genetic mutations; Mathematical model; Power engineering and energy; Power generation; Power systems; Reactive power; System testing; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5363700
  • Filename
    5363700