Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/80682
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dc.titleLoad frequency control using genetic-algorithm based fuzzy gain scheduling of PI controllers
dc.contributor.authorChang, C.S.
dc.contributor.authorFu, W.
dc.contributor.authorWen, F.
dc.date.accessioned2014-10-07T03:00:10Z
dc.date.available2014-10-07T03:00:10Z
dc.date.issued1996-01-01
dc.identifier.citationChang, C.S.,Fu, W.,Wen, F. (1996-01-01). Load frequency control using genetic-algorithm based fuzzy gain scheduling of PI controllers. Electric Machines and Power Systems 26 (1) : 39-50. ScholarBank@NUS Repository.
dc.identifier.issn0731356X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/80682
dc.description.abstractThis paper describes the application of fuzzy gain scheduling on the proportionalintegral (PI) load frequency control for a multi-area interconnected power system. To improve the performance of the power system, an appropriate optimization method, namely a refined genetic algorithm (RGA), has been used to tune the membership functions and rule sets for the fuzzy control. The control methodology adopts a formulation for the area control error which always guarantees zero steady-state values for both the time error and inadvertent energy. The proposed control has been designed for a two-area interconnected power system with control deadbands and rate constraints. Simulation results confirm the designed control performance of the proposed control.
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.sourcetitleElectric Machines and Power Systems
dc.description.volume26
dc.description.issue1
dc.description.page39-50
dc.description.codenEMPSD
dc.identifier.isiutNOT_IN_WOS
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