• DocumentCode
    3012973
  • Title

    Multi-objective Optimal Design for Hybrid Active Power Filter Based on Composite Method of Genetic Algorithm and Particle Swarm Optimization

  • Author

    Jiang You-hua ; Liao Dai-fa

  • Author_Institution
    Sch. of Comput. & Inf. Technol., Shanghai Univ. of Electr. Power, Shanghai, China
  • Volume
    2
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    549
  • Lastpage
    553
  • Abstract
    A new mixed algorithm of genetic theory and particle swarm optimization (GA-PSO) have been proposed in this paper to tackle the optimal design problem of hybrid active power filter (HAPF) in its parameter design and investment optimization, considering the better convergence of genetic theory and fast convergence of particle swarm optimization. It takes the original investment, the capacity of reactive power compensation and harmonic distortion as three objectives, and penalty function theory have been used to convert multi-objective design problems into single-objective design problems. Finally a HAPF simulation under the background of PSCAD/EMTDC has been analyzed, the results show that the proposed optimal design method of HAPF can save cost, enhance performance-price ratio and filtering performance.
  • Keywords
    active filters; genetic algorithms; harmonic distortion; hybrid power systems; particle swarm optimisation; power harmonic filters; power system harmonics; reactive power; HAPF simulation; composite method; genetic algorithm; genetic theory; harmonic distortion; hybrid active power filter; investment optimization; multiobjective optimal design; parameter design; particle swarm optimization; penalty function; performance-price ratio; reactive power compensation; Active filters; Algorithm design and analysis; Analytical models; Convergence; Design optimization; Genetic algorithms; Harmonic distortion; Investments; Particle swarm optimization; Reactive power; hybrid active power filters; multi-objective; particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.295
  • Filename
    5375919