• DocumentCode
    3395823
  • Title

    Development of an Improved Particle Swarm Optimization Algorithm and Its Application in the Optimal Design of Nuclear Power System

  • Author

    Liu, Chengyang ; Yan, Changqi

  • Author_Institution
    Nat. Defense Key Discipline Lab. of Nucl. Safety & Simulation Technol., Harbin, China
  • fYear
    2012
  • fDate
    27-29 March 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This article focuses on the development of an improved particle swarm optimization algorithm and its application in the optimal design of the nuclear power system, whose goal is to find a combination of system parameter values that minimize the weight of the system given the power capacity requirement and safety criteria. An improved particle swarm optimization (IPSO) algorithm was developed using the feasibility rule constraints handling method, crossover and mutation operator. Using the improved compound shape algorithm to do the local search after the particle swarm reaches a satisfactory point. The algorithm gave satisfactory optimization results from both search efficiency and accuracy perspectives. This IPSO successfully solved the design optimization problem of nuclear power system. It is an advanced and efficient methodology that can be applied to the similar optimization problems in other areas.
  • Keywords
    constraint handling; electrical safety; nuclear power stations; particle swarm optimisation; IPSO algorithm; crossover operator; feasibility rule constraint handling method; improved compound shape algorithm; improved particle swarm optimization algorithm; mutation operator; nuclear power system; optimal design; power capacity requirement; safety criteria; Algorithm design and analysis; Generators; Inductors; Optimization; Particle swarm optimization; Power systems; Safety;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
  • Conference_Location
    Shanghai
  • ISSN
    2157-4839
  • Print_ISBN
    978-1-4577-0545-8
  • Type

    conf

  • DOI
    10.1109/APPEEC.2012.6307492
  • Filename
    6307492