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dc.contributor.authorMayo, Michaelen_NZ
dc.contributor.authorDaoud, Maisaen_NZ
dc.date.accessioned2016-04-12T03:33:29Z
dc.date.available2016en_NZ
dc.date.available2016-04-12T03:33:29Z
dc.date.issued2016en_NZ
dc.identifier.citationMayo, M., & Daoud, M. (2016). Informed mutation of wind farm layouts to maximise energy harvest. Renewable Energy, 89, 437–448. http://doi.org/10.1016/j.renene.2015.12.006en
dc.identifier.issn0960-1481en_NZ
dc.identifier.urihttps://hdl.handle.net/10289/10078
dc.description.abstractCorrect placement of turbines in a wind farm is a critical issue in wind farm design optimisation. While traditional "trial and error"-based approaches suffice for small layouts, automated approaches are required for larger wind farms with turbines numbering in the hundreds. In this paper we propose an evolutionary strategy with a novel mutation operator for identifying wind farm layouts that minimise expected velocity deficit due to wake effects. The mutation operator is based on constructing a predictive model of velocity deficits across a layout so that mutations are inherently biased towards better layouts. This makes the operator informed rather than randomised. We perform a comprehensive evaluation of our approach on five challenging simulated scenarios using a simulation approach acceptable to industry [1]. We then compare our algorithm against two baseline approaches including the Turbine Displacement Algorithm [2]. Our results indicate that our informed mutation approach works effectively, with our approach identifying layouts with the lowest aggregate velocity deficits on all five test scenarios.en_NZ
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherElsevieren_NZ
dc.rightsThis is an authors submitted version of an article published in the journal: Renewable Energy © 2015 Elsevier Ltd.
dc.subjectMachine learning
dc.titleInformed mutation of wind farm layouts to maximise energy harvesten_NZ
dc.typeJournal Article
dc.identifier.doi10.1016/j.renene.2015.12.006en_NZ
dc.relation.isPartOfRenewable Energyen_NZ
pubs.begin-page437
pubs.elements-id136067
pubs.end-page448
pubs.volume89en_NZ
dc.identifier.eissn1879-0682en_NZ
uow.identifier.article-noCen_NZ


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