Show simple item record

dc.contributor.authorHasanien, H.
dc.contributor.authorMuyeen, S.M.
dc.date.accessioned2017-01-30T12:58:52Z
dc.date.available2017-01-30T12:58:52Z
dc.date.created2016-10-05T19:30:22Z
dc.date.issued2012
dc.identifier.citationHasanien, H. and Muyeen, S.M. 2012. Design optimization of controller parameters used in variable speed wind energy conversion system by genetic algorithms. IEEE Transactions on Sustainable Energy. 3 (2): pp. 200-208.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/27427
dc.identifier.doi10.1109/TSTE.2012.2182784
dc.description.abstract

This paper presents an optimum design procedure for the controller used in the frequency converter of a variable speed wind turbine (VSWT) driven permanent magnet synchronous generator (PMSG) by using genetic algorithms (GAs) and response surface methodology (RSM). The cascaded control is frequently used in the control of the frequency converter using the proportional plus integral (PI) controllers. The setting of the parameters of the PI controller used in a large system is cumbersome, especially in an electrical power system, which is difficult to be expressed by a mathematical model or transfer function. This study attempts to optimally design the parameters of the PI controllers used in the frequency converter of a variable speed wind energy conversion system (WECS). The effectiveness of the designed parameters using GAs-RSM is then compared with that obtained using a generalized reduced gradient (GRG) algorithm considering both symmetrical and unsymmetrical faults. The permanent fault condition due to unsuccessful reclosing of circuit breakers is considered as well. It represents another salient feature of this study. It is found that fault-ride-through of VSWT-PMSG can be improved considerably using the parameters of its frequency converter obtained from GAs-RSM.

dc.publisherThe Institute of Electrical and Electronic Engineers (IEEE)
dc.titleDesign optimization of controller parameters used in variable speed wind energy conversion system by genetic algorithms
dc.typeJournal Article
dcterms.source.volume3
dcterms.source.number2
dcterms.source.startPage200
dcterms.source.endPage208
dcterms.source.issn1949-3029
dcterms.source.titleIEEE Transactions on Sustainable Energy
curtin.note

© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusOpen access


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record