Efficient Multi-objective Optimizers by Meta-heuristics for Power System Control

This paper proposes the Meta-heuristics approaches using genetic algorithms (GA) and particle swarm optimization (PSO) for tuning power system stabilizer PSS parameters. In this work we have proposed a multi-objective function based on two objectives: first maximize the stability margin by increasing the damping factors and second minimize the eigenvalues real parts. For the effectiveness function proposed check, we compared it with mono-objective function. The simulation results, by comparative study between genetic algorithms and particle swarm optimizations techniques via multi objective and mono objective functions proved the efficiency of the PSS adapted by multi-objective function based genetic algorithms in comparison with particle swarm optimization, it’s enhanced stability of power system works under different operating modes and different network configurations. The simulation results obtained under developed graphical user interface (GUI).