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Screening analysis and unconstrained optimization of a small-scale vertical axis wind turbine

dc.contributor.authorTrentin, Pedro Francisco Silva
dc.contributor.authorMartinez, Pedro Henrique Barsanaor de Barros
dc.contributor.authordos Santos, Gabriel Bertacco
dc.contributor.authorGasparin, Elóy Esteves
dc.contributor.authorSalviano, Leandro Oliveira
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2022-04-28T19:48:09Z
dc.date.available2022-04-28T19:48:09Z
dc.date.issued2022-02-01
dc.description.abstractThe demand for alternative and renewable energy sources has been substantially growing in recent years, mainly steered by economic and environmental inconveniences of conventional energy sources, such as oil and its derivatives. In this context, wind energy has emerged as an attractive renewable source, envisioning possibilities of developing more efficient equipment to meet the ever-growing energy demand. In this work, we coupled Computational Fluid Dynamics (CFD) with an optimization based on response surface (RS) methodologies to find an optimal design for a small-scale NACA 0021 Darrieus vertical axis wind turbine (VAWT) operating at a tip speed ratio of 2.63. For that, we investigated four geometric parameters: number of blades (N), rotor diameter (D), chord length (c), and pitch angle (β). For the numerical model, we considered a two-dimensional, incompressible, turbulent, and unsteady flow regime. A sensitivity analysis (SA) via Morris’ method was performed to identify the influence of the four geometric parameters on the turbine aerodynamic performance. Our results reveal that the pitch angle (β) contributes the most (58%) to the turbine performance. The resulting optimized turbine design increased the conversion efficiency by 40%. Additionally, we also present a detailed discussion on the flow phenomenology considering the impact of each one of the four geometric parameters on the power coefficient. Finally, the strategy adopted here, in which a qualitative sensitivity analysis combined to the response surface and unconstrained optimization, was shown to be robust and can be applied to high-dimensional and computational-expensive CFD models to reduce costs with adequate results regarding fluid flow phenomena.en
dc.description.affiliationSão Paulo State University (Unesp) School of Engineering
dc.description.affiliationUnespSão Paulo State University (Unesp) School of Engineering
dc.identifierhttp://dx.doi.org/10.1016/j.energy.2021.122782
dc.identifier.citationEnergy, v. 240.
dc.identifier.dimensionspub.1143543777
dc.identifier.doi10.1016/j.energy.2021.122782
dc.identifier.issn0360-5442
dc.identifier.issn1873-6785
dc.identifier.lattes8939437131313799
dc.identifier.lattes7035395910014595
dc.identifier.lattes0065309506501422
dc.identifier.orcid0000-0002-1880-6569
dc.identifier.orcid0000-0002-9029-6620
dc.identifier.orcid0000-0002-8163-419X
dc.identifier.orcid0000-0001-5005-9869
dc.identifier.scopus2-s2.0-85120827195
dc.identifier.urihttp://hdl.handle.net/11449/223008
dc.language.isoeng
dc.publisherElsevier
dc.relation.isnodouble219811*
dc.relation.ispartofEnergy
dc.rights.accessRightsAcesso abertopt
dc.rights.sourceRightsoa_all
dc.rights.sourceRightsgreen
dc.sourceScopus
dc.sourceDimensions
dc.subjectComputational fluid dynamics
dc.subjectOptimization
dc.subjectResponse surface methodology
dc.subjectVertical axis wind turbine
dc.titleScreening analysis and unconstrained optimization of a small-scale vertical axis wind turbineen
dc.typeArtigopt
dspace.entity.typePublication
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unesp.author.orcid0000-0002-1880-6569[2]

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