Design of fuzzy power system stabilizer using adaptive evolutionary algorithm

被引：33

作者：

Hwang, Gi-Hyun ^{[2
]}

Kim, Dong-Wan ^{[1
]}

Lee, Jae-Hyun ^{[3
]}

An, Young-Joo ^{[4
]}

机构：

[1] Tongmyong Univ, Dept Elect & Elect Engn, Pusan 608711, South Korea

[2] Dongseo Univ, Dept Comp Informat Engn, Pusan 609735, South Korea

[3] Tongmyong Univ, Coll Port & Logist, Pusan 608711, South Korea

[4] Pukyong Univ, Dept Elect & Control & Measurement Engn, Pusan 608737, South Korea

来源：

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2008年 / 21卷 / 01期

关键词：

adaptive evolutionary algorithm-; fuzzy power system stabilizer; genetic algorithm; evolution strategy;

D O I：

10.1016/j.engappai.2006.11.008

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 [计算机科学与技术];

摘要：

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 (NIPS). 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. (c) 2006 Elsevier Ltd. All rights reserved.

引用

页码：86 / 96

页数：11

共 24 条

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Hybridizing rule-based power system stabilizers with genetic algorithms [J].