Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
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Comparison of Particle Swarm Optimization and the Genetic Algorithm in the Improvement of Power System Stability by an SSSC-based Controller

  • Peyvandi, M. (Dept. of Electrical Engineering, Islamic Azad University) ;
  • Zafarani, M. (Dept. of Electrical and computer Engineering, Isfahan University of Technology) ;
  • Nasr, E. (Dept. of Electrical Engineering, Islamic Azad University)
  • Received : 2010.08.16
  • Accepted : 2010.12.07
  • Published : 2011.03.01
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Abstract

Genetic algorithms (GA) and particle swarm optimization (PSO) are the most famous optimization techniques among various modern heuristic optimization techniques. These two approaches identify the solution to a given objective function, but they employ different strategies and computational effort; therefore, a comparison of their performance is needed. This paper presents the application and performance comparison of the PSO and GA optimization techniques for a static synchronous series compensator-based controller design. The design objective is to enhance power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem, and both PSO and GA optimization techniques are employed to search for the optimal controller parameters.

Keywords

References

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