Power System Stabilizer Design using Genetic Algorithms and Particle Swarm Optimization

Ghouraf Djamel Eddine, Naceri Abdellatif, Sayeh Abdelkader

Abstract


in this paper, Meta-heuristic techniques using genetic algorithms GA and particle swarm optimization PSO to tuning optimal design of power system stabilizer PSS proposed. This latter have been used for many years to add damping to electromechanical oscillations of power system, Based on this idea we have proposed multiobjective function composed with tow function, first maximize stability margin by increasing the damping factors while minimizing the real parts of the eigenvalues. Simulation results to comparative study between genetic algorithms and particle swarm optimization obtained by our realized graphical user interface (GUI) proved the efficiency of PSS optimized by genetic algorithms in comparison with Particle Swarm Optimization, showing stable   system   responses   almost   insensitive   to   large parameter variations and under different operating regime (under-excited, nominal and over excited regime).

Keywords


Power System Stabilizer PSS; Genetic Algorithms GA; Particle Swarm Optimization PSO; Multiobjective Function; Graphical Interface GUI

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References


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DOI: https://doi.org/10.59247/csol.v1i1.15

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Copyright (c) 2023 Ghouraf Djamel Eddine, Naceri Abdellatif, Sayeh Abdelkader

 
Control Systems and Optimization Letters
ISSN: 2985-6116
Website: https://ejournal.csol.or.id/index.php/csol
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Publisher: Peneliti Teknologi Teknik Indonesia
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