Comparative Study of Population Based Techniques for Power System Stabilizer Design

Power system stabilizers (PSSs) are used in interconnected power systems in order to mitigate low frequency oscillations. The comparison of the performances of four advanced population based techniques in tuning the parameters of PSS in a three-machine-nine-bus test system is presented in this paper. The algorithms considered in this paper are: a) differential evolution based particle swarm optimization (DEPSO), b) modified clonal selection algorithm (MCSA), c) small population based particle swarm optimization (SPPSO) and d) population based incremental learning (PBIL). The comparative study is focused on the frequency domain performances. It is observed that MCSA is performing better than the other three algorithms. The performances of DEPSO and PBIL are quite similar whereas the SPPSO algorithm is not showing very good results compared to the other three.