Design of fuzzy power system stabilizer using adaptive evolutionary algorithm

Authors:
Gi-Hyun Hwang;Dong-Wan Kim;Jae-Hyun Lee;Young-Joo An
Affiliations:
Department of Computer Information Engineering, Dongseo University, Busan 609-735, South Korea;Department of Electrical and Electronics Engineering, Tongmyong University, Busan 608-711, South Korea;College of Port and Logistics, Tongmyong University, Pusan 608-711, South Korea;Department of Electrical and Control and Measurement Engineering, Pukyong University, Busan 608-737, South Korea
Venue:
Engineering Applications of Artificial Intelligence
Year:
2008

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Abstract

This paper presents a design of fuzzy power system stabilizer (FPSS) using an adaptive evolutionary algorithm (AEA). AEA consists of genetic algorithm (GA) for a global search capability and evolution strategy (ES) for a local search in an adaptive manner when the present generation evolves into the next generation. AEA is used to optimize the membership functions and scaling factors of FPSS. The propose method is applied to single-machine infinite bus system (SIBS) and multi-machine power system (MPS). Results of numerical experiment show that the control performance of the FPSS is better than that of a conventional power system stabilizer (CPSS) for three-phase fault in heavy load. To show the robustness of FPSS, it is applied with disturbances such as change of mechanical torque and three-phase fault in nominal and heavy load, etc. FPSS shows better robustness than CPSS.