Multimachine Power System Stabilizer Design Based on Evolutionary Algorithm

This paper discusses the design of multimachine power system stabilizers based on three evolutionary algorithm techniques, namely: Genetic Algorithm (GA), Population Based Incremental Learning (PBIL) and the Breeder Genetic Algorithm (BGA) with adaptive mutation. The three PSSs are designed using eigenvalues analysis, whereby the lowest damped ratio is maximized. A comparison is done to determine which type of algorithm gives better results. Theoretically the BGA and the PBIL designed based power system stabilizer performs better than the GA based power system stabilizer. The three PSSs (BGA, PBIL and GA design based) are tested against the conventional power system stabilizer (CPSS), to verify that the PSS design with multiple operating conditions performs better than the single operating condition designed PSS. A four machine theoretical system is used in the simulations. Time domain simulation is presented to prove the above. The PBIL and BGA designed PSS performs better than the GA while all the evolutionary algorithm designed PSS performs better than the CPSS as expected.