• DocumentCode
    1583484
  • Title

    Coordination of multiple PSSs using multi-objective genetic algorithm

  • Author

    Zhang, P.X. ; Cao, Y.J. ; Cheng, S.J.

  • Author_Institution
    Huazhong Univ. of Sci. & Technol., Wuhan, China
  • Volume
    6
  • fYear
    2004
  • Firstpage
    5040
  • Abstract
    A multi-objective genetic algorithm (MOCA) used for the coordination of power system stabilizers to deal with the damping of multi-mode oscillations in large-scale power systems is presented in this paper. The selection of the PSS parameters for large power system is formulated as a multiobjective optimization problem, in which the system response is optimized by minimizing several system-behavior measure criterions. Design of the multi-objective optimization aims to find out the Pareto optimal solution, which is a set of possible optimal solutions for parameters of the PSSs. The simulation results show that the proposed MOGA method is effective. It enables the PSSs to provide effective damping for power system multi-mode oscillations and satisfactory control performance can be obtained.
  • Keywords
    Pareto optimisation; damping; genetic algorithms; oscillations; power system dynamic stability; Pareto optimal solution; coordinative control; large-scale power systems; multimode oscillations; multiobjective genetic algorithm; power system stabilizers; Damping; Design optimization; Genetic algorithms; Large-scale systems; Pareto optimization; Power measurement; Power system control; Power system measurements; Power system simulation; Power systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
  • Print_ISBN
    0-7803-8273-0
  • Type

    conf

  • DOI
    10.1109/WCICA.2004.1343677
  • Filename
    1343677