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dc.contributor.authorMerizalde Zamora, Yury Humberto
dc.contributor.authorHernández Callejo, Luis 
dc.contributor.authorDuque Pérez, Óscar 
dc.contributor.authorAlonso Gómez, Víctor 
dc.date.accessioned2022-10-24T11:31:20Z
dc.date.available2022-10-24T11:31:20Z
dc.date.issued2019
dc.identifier.citationEnergies, 2019, vol. 12, n. 2, 225es
dc.identifier.issn1996-1073es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/56475
dc.descriptionProducción Científicaes
dc.description.abstractWind power generation has been the fastest-growing energy alternative in recent years, however, it still has to compete with cheaper fossil energy sources. This is one of the motivations to constantly improve the efficiency of wind turbines and develop new Operation and Maintenance (O&M) methodologies. The decisions regarding O&M are based on different types of models, which cover a wide range of scenarios and variables and share the same goal, which is to minimize the Cost of Energy (COE) and maximize the profitability of a wind farm (WF). In this context, this review aims to identify and classify, from a comprehensive perspective, the different types of models used at the strategic, tactical, and operational decision levels of wind turbine maintenance, emphasizing mathematical models (MatMs). The investigation allows the conclusion that even though the evolution of the models and methodologies is ongoing, decision making in all the areas of the wind industry is currently based on artificial intelligence and machine learning models.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherMDPIes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.classificationWind turbineses
dc.subject.classificationTurbinas eólicases
dc.subject.classificationMathematical modelses
dc.subject.classificationModelos matemáticoses
dc.titleMaintenance models applied to wind turbines. A comprehensive overviewes
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2019 The Authorses
dc.identifier.doi10.3390/en12020225es
dc.relation.publisherversionhttps://www.mdpi.com/1996-1073/12/2/225es
dc.peerreviewedSIes
dc.rightsAtribución 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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