Design of Genetic Algorithm Based Fuzzy Logic Power System Stabilizers in Multimachine Power System

Abstract

This paper presents the design of fuzzy logic power system stabilizers using genetic algorithms in multimachine power system. In the proposed fuzzy expert system, generator speed deviation and acceleration are chosen as input signals to fuzzy logic power system stabilizer. In this approach gains, centers of membership functions and the parameters of the fuzzy logic controllers have been tuned using genetic algorithm. Incorporation of GA in the design of fuzzy logic power system stabilizer will add an intelligent dimension to the stabilizer and significantly reduces computational time in the design process. The problem of selection of optimal parameters of fuzzy logic power system stabilizer is converted into an optimization problem and which is solved by genetic algorithm with the integral of squared time squared error (ISTSE) based objective function. To demonstrate the robustness of the proposed genetic based fuzzy logic power system stabilizer, simulation studies on multimachine system subjected to small perturbation and three-phase fault have been carried out. Simulation results show the superiority and robustness of GA based fuzzy logic power system stabilizer as compare to conventionally tuned controller.