Design of fuzzy power system stabilizer using adaptive evolutionary algorithm

This paper presents a design methodology of fuzzy system stabilizer (FPSS) using an adaptive evolution algorithm (AEA). The AEA consists of a genetic algorithm for a global search and evolution strategy for a local search in an adaptive manner when the present generation evolves into the next generation. The AEA is used to optimize the membership functions and scaling factors of FPSS. A single machine infinite system is applied to evaluate the usefulness of the FPSS. The results show that the proposed FPSS has a better control performance than the conventional power system stabilizer (CPSS) in the case of a three-phase fault under heavy load. To show the robustness of FPSS, it is applied to the system with disturbances such as change of mechanical torque and three-phase fault under the normal and light load. The results of the FPSS show a better robustness than that of the CPSS.