POWER SYSTEM STABILIZATION USING SWARM TUNED FUZZY CONTROLLER

This paper proposes a swarm optimized fuzzy logic based power system stabilizer (SFLPSS). The fuzzy logic stabilizer membership functions parameters, inputs and outputs gains and fuzzy rules are tuned and optimized using particle swarm optimization (PSO) technique. Optimization parameters were subje...

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Bibliographic Details
Published inIFAC Proceedings Volumes Vol. 41; no. 2; pp. 11106 - 11111
Main Author El-Metwally, Khaled A.
Format Journal Article
LanguageEnglish
Published 2008
Subjects
Artificial intelligence
Intelligent control of power systems
Neural fuzzy modeling and control
Intelligent control of power systems
Artificial intelligence
Neural fuzzy modeling and control
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Summary:This paper proposes a swarm optimized fuzzy logic based power system stabilizer (SFLPSS). The fuzzy logic stabilizer membership functions parameters, inputs and outputs gains and fuzzy rules are tuned and optimized using particle swarm optimization (PSO) technique. Optimization parameters were subject to realistic constraint. The optimization is done using a seventh order nonlinear model of a single synchronous machine connected to infinite bus bar. A Guided simulation technique using stability limits check is used to accelerate the PSO algorithm search for optimized parameters. Optimization results in reduction of fuzzy rules. Transient tests of the optimized controller performance showed better performance over conventional controllers.
ISSN:1474-6670
DOI:10.3182/20080706-5-KR-1001.01882