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Harmony search method for optimal wind turbine electrical generator design

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Gao, Xiaozhi
dc.contributor.author Wang, Xiaolei
dc.contributor.author Zenger, Kai
dc.date.accessioned 2017-01-19T10:40:42Z
dc.date.issued 2016-12-30
dc.identifier.citation Gao , X , Wang , X & Zenger , K 2016 , ' Harmony search method for optimal wind turbine electrical generator design ' , Rakenteiden Mekaniikka (Journal of Structural Mechanics) , vol. 49 , no. 3 , pp. 119-136 . < http://rmseura.tkk.fi/rmlehti/2016/nro3/RakMek_49_3_2016_2.pdf > en
dc.identifier.issn 0783-6104
dc.identifier.issn 1797-5301
dc.identifier.other PURE UUID: 11c469bd-0bae-4b14-8f6a-10c71a795f42
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/11c469bd-0bae-4b14-8f6a-10c71a795f42
dc.identifier.other PURE LINK: http://rmseura.tkk.fi/rmlehti/2016/nro3/RakMek_49_3_2016_2.pdf
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/10244380/Gao_Wang_Zenger_RakMek_49_3_2016_2.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/24163
dc.description.abstract The Harmony Search (HS) method is an emerging meta-heuristic optimization algorithm, which has been employed to cope with numerous challenging tasks during the past decade. In this paper, the essential theory of the HS algorithm is first described in details. Next, a few typical variations of the HS method are explained. The application of the HS in a practical wind turbine electrical generator optimal design case study is finally presented. Computer simulation results have clearly demonstrated its remarkable performances in dealing with demanding optimization problems. en
dc.format.extent 18
dc.format.extent 119-136
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries Rakenteiden mekaniikka (Journal of Structural Mechanics) en
dc.relation.ispartofseries Volume 49, issue 3 en
dc.rights openAccess en
dc.title Harmony search method for optimal wind turbine electrical generator design en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department LUT University
dc.contributor.department Department of Electrical Engineering and Automation
dc.subject.keyword nature-inspired computing methods, Harmony Search (HS) method, Popula-tion-Based Incremental Learning (PBIL), optimization, electrical machine design
dc.identifier.urn URN:NBN:fi:aalto-201701191108


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