Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/62386
DC Field | Value | |
---|---|---|
dc.title | Load frequency control using genetic-algorithm based fuzzy gain scheduling of PI controllers | |
dc.contributor.author | Chang, C.S. | |
dc.contributor.author | Fu, W. | |
dc.contributor.author | Wen, F. | |
dc.date.accessioned | 2014-06-17T06:50:29Z | |
dc.date.available | 2014-06-17T06:50:29Z | |
dc.date.issued | 1996-01-01 | |
dc.identifier.citation | Chang, 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.issn | 0731356X | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/62386 | |
dc.description.abstract | This 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.source | Scopus | |
dc.type | Article | |
dc.contributor.department | ELECTRICAL ENGINEERING | |
dc.description.sourcetitle | Electric Machines and Power Systems | |
dc.description.volume | 26 | |
dc.description.issue | 1 | |
dc.description.page | 39-50 | |
dc.description.coden | EMPSD | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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