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http://dx.doi.org/10.5370/JEET.2011.6.2.182

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)
Publication Information
Journal of Electrical Engineering and Technology / v.6, no.2, 2011 , pp. 182-191 More about this Journal
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
Genetic algorithm; FACTS; SSSC; Particle swarm optimization;
Citations & Related Records

Times Cited By Web Of Science : 3  (Related Records In Web of Science)
Times Cited By SCOPUS : 3
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