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dc.contributor.authorVillanueva Torres, Daniel 
dc.contributor.authorSixto, Adrián
dc.contributor.authorFeijoo Lorenzo, Andres Elias
dc.contributor.authorFernandez Otero, Antonio
dc.contributor.authorMiguez Garcia, Edelmiro
dc.date.accessioned2021-03-11T09:31:17Z
dc.date.available2021-03-11T09:31:17Z
dc.date.issued2020-05-10
dc.identifier.citationApplied Sciences, 10(9): 3317 (2020)spa
dc.identifier.issn20763417
dc.identifier.urihttp://hdl.handle.net/11093/1849
dc.description.abstractPower curves provided by wind turbine manufacturers are obtained under certain conditions that are different from those of real life operation and, therefore, they actually do not describe the behavior of these machines in wind farms. In those cases where one year of data is available, a logistic function may be fitted and used as an accurate model for such curves, with the advantage that it describes the power curve by means of a very simple mathematical expression. Building such a curve from data can be achieved by different methods, such as using mean values or, alternatively, all the possible values for given intervals. However, when using the mean values, some information is missing and when using all the values the model obtained can be wrong. In this paper, some methods are proposed and applied to real data for comparison purposes. Among them, the one that combines data clustering and simulation is recommended in order to avoid some errors made by the other methods. Besides, a data filtering recommendation and two different assessment procedures for the error provided by the model are proposed.spa
dc.language.isoengspa
dc.publisherApplied Sciencesspa
dc.rightsCreative Commons Attribution (CC BY) license
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleMethods to apply a 3-Parameter logistic model to wind turbine dataspa
dc.typearticlespa
dc.rights.accessRightsopenAccessspa
dc.identifier.doi10.3390/app10093317
dc.identifier.editorhttps://www.mdpi.com/2076-3417/10/9/3317spa
dc.publisher.departamentoEnxeñaría eléctricaspa
dc.publisher.grupoinvestigacionGrupo de Investigación en Redes Eléctricasspa
dc.subject.unesco2501 Ciencias de la Atmósferaspa
dc.subject.unesco3322.05 Fuentes no Convencionales de Energíaspa
dc.subject.unesco1209 Estadísticaspa
dc.date.updated2021-03-09T10:05:13Z


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