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Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves

dc.contributor.authorGil-González, Walter
dc.contributor.authorMontoya, Oscar Danilo
dc.contributor.authorGrisales-Noreña, Luis Fernando
dc.contributor.authorPerea-Moreno, Alberto-Jesus
dc.contributor.authorHernandez-Escobedo, Quetzalcoatl
dc.date.accessioned2020-10-30T18:43:19Z
dc.date.available2020-10-30T18:43:19Z
dc.date.issued2020-04-08
dc.date.submitted2020-10-28
dc.identifier.citationGil-González, W.; Montoya, O.D.; Grisales-Noreña, L.F.; Perea-Moreno, A.-J.; Hernandez-Escobedo, Q. Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves. Sustainability 2020, 12, 2983.spa
dc.identifier.urihttps://hdl.handle.net/20.500.12585/9521
dc.description.abstractThis paper presents an optimization model for the optimal placement and sizing of wind turbines, considering their reactive power capacity, wind speed, and demand curves. The optimization model is nonlinear and is focused on minimizing power losses in AC distribution networks. Also, paired wind turbine and power conversion systems are treated via chargeability factor η at the peak hour. This factor represents the percentage of usage of the power conversion system in the nominal wind speed conditions, and allows to support reactive power dynamically during all periods of the day as a function of the distribution system requirements. In addition, an artificial neural network is used for short-term forecasting to deal with uncertainties in wind power generation. We assume that the number of wind power distributed generators could be from zero to three generators integrated into the system, considering unit power factors and reactive power injections to follow up the effect of reactive power compensation in the daily operation. The General Algebraic Modeling System (GAMS) is employed to solve the proposed optimization model.spa
dc.format.extent20 páginas
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceSustainability 2020, 12(7), 2983spa
dc.titleOptimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curvesspa
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datacite.rightshttp://purl.org/coar/access_right/c_abf2spa
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.identifier.urlhttps://www.mdpi.com/2071-1050/12/7/2983
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.hasversioninfo:eu-repo/semantics/publishedVersionspa
dc.identifier.doi10.3390/su12072983
dc.subject.keywordsWind power generationspa
dc.subject.keywordsArtificial neural networksspa
dc.subject.keywordsChargeability factorspa
dc.subject.keywordsReactive power capacityspa
dc.subject.keywordsWind speed and demand curvesspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.identifier.instnameUniversidad Tecnológica de Bolívarspa
dc.identifier.reponameRepositorio Universidad Tecnológica de Bolívarspa
dc.publisher.placeCartagena de Indiasspa
dc.type.spaArtículospa
dc.audiencePúblico generalspa
oaire.resourcetypehttp://purl.org/coar/resource_type/c_2df8fbb1spa


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Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.