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Design of fuzzy power system stabilizer using adaptive evolutionary algorithm

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4 Author(s)
Gi-Hyun Hwang ; Dept. of Electr. Eng., Pusan Nat. Univ., South Korea ; June-Ho Park ; Hyeon Tae Kang ; Sungshin Kim

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

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Industrial Electronics, 2000. ISIE 2000. Proceedings of the 2000 IEEE International Symposium on  (Volume:1 )

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