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Numerical optimisation of a small-scale wind turbine through the use of surrogate modelling

dc.contributor.authorErfort, Garethen_ZA
dc.contributor.authorVon Backstrom, Theodor Willemen_ZA
dc.contributor.authorVenter, Gerharden_ZA
dc.date.accessioned2018-10-19T12:59:03Z
dc.date.available2018-10-19T12:59:03Z
dc.date.issued2017
dc.identifier.citationErfort, G., Von Backstrom, T. W. & Venter, G. 2017. Numerical optimisation of a small-scale wind turbine through the use of surrogate modelling. Journal of Energy in Southern Africa, 28(3):79-91, doi:10.17159/2413-3051/2017/v28i3a2368
dc.identifier.issn2413-3051 (online)
dc.identifier.issn1021-447X (print)
dc.identifier.otherdoi:10.17159/2413-3051/2017/v28i3a2368
dc.identifier.urihttp://hdl.handle.net/10019.1/104580
dc.descriptionCITATION: Erfort, G., Von Backstrom, T. W. & Venter, G. 2017. Numerical optimisation of a small-scale wind turbine through the use of surrogate modelling. Journal of Energy in Southern Africa, 28(3):79-91, doi:10.17159/2413-3051/2017/v28i3a2368.
dc.descriptionThe original publication is available at https://journals.assaf.org.za/jesa
dc.description.abstractENGLISH ABSTRACT: Wind conditions in South Africa are suitable for small-scale wind turbines, with wind speeds below 7 m.s−1. This investigation is about a methodology to optimise a full wind turbine using a surrogate model. A previously optimised turbine was further optimised over a range of wind speeds in terms of a new parameterisation methodology for the aerodynamic profile of the turbine blades, using non-uniform rational B-splines to encompass a wide range of possible shapes. The optimisation process used a genetic algorithm to evaluate an input vector of 61 variables, which fully described the geometry, wind conditions and rotational speed of the turbine. The optimal performance was assessed according to a weighted coefficient of power, which rated the turbine blade’s ability to extract power from the available wind stream. This methodology was validated using XFOIL to assess the final solution. The results showed that the surrogate model was successful in providing an optimised solution and, with further refinement, could increase the coefficient of power obtained.en_ZA
dc.description.urihttps://journals.assaf.org.za/index.php/jesa/article/view/2368
dc.format.extent13 pages : illustrationsen_ZA
dc.language.isoen_ZAen_ZA
dc.publisherUniversity of Cape Town, Energy Research Centreen_ZA
dc.subjectOptimisation...en_ZA
dc.subjectWind turbinesen_ZA
dc.subjectTurbines -- Bladesen_ZA
dc.subjectAerodynamicsen_ZA
dc.titleNumerical optimisation of a small-scale wind turbine through the use of surrogate modellingen_ZA
dc.typeArticleen_ZA
dc.description.versionPublisher's version
dc.rights.holderAuthors retain copyrighten_ZA


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