A Comparative Study between Genetic Algorithms and Particle Swarm Optimization Applied to Power System Using Multi Objective Function

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).