• DocumentCode
    3600422
  • Title

    Model order reduction using PSO algorithm and it´s application to power systems

  • Author

    Gallehdari, Z. ; Karrari, M. ; Malik, O.P.

  • Author_Institution
    Dept. of Electr. Eng., Amirkabir Univ. of Technol., Tehran, Iran
  • fYear
    2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Power systems are high order nonlinear large-scale systems with randomly changing operating conditions. Due to that an appropriate model order reduction technique is a must in power system analysis. Most of the existing methods are suitable only for linear systems. The main problem is that linearized models of power systems could be non-minimum phase, unstable or improper. Therefore, not all model order reduction techniques could be used for power systems. In this paper, Particle Swarm Optimization (PSO) method is used for model reduction of power systems. The main advantage of the developed method in this paper is that it is applicable for all systems and not restricted to only stable or strictly proper systems. Therefore, it is most suitable for power systems. Simulation results show the effectiveness of the proposed method.
  • Keywords
    large-scale systems; nonlinear systems; particle swarm optimisation; power system simulation; PSO algorithm; high order nonlinear large-scale systems; linear systems; model order reduction; particle swarm optimization; power system analysis; power systems linearized models; Genetic algorithms; Linear systems; Particle swarm optimization; Power system analysis computing; Power system control; Power system dynamics; Power system modeling; Power system simulation; Power systems; Reduced order systems; Hankel norm; PSOoptimization; model reduction; power system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Power and Energy Conversion Systems, 2009. EPECS '09. International Conference on
  • Print_ISBN
    978-1-4244-5477-8
  • Type

    conf

  • Filename
    5415727