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dc.contributor.authorCarmona Sanz, Mares-ES
dc.contributor.authorSanz Bobi, Miguel Ángeles-ES
dc.date.accessioned2016-12-16T04:07:47Z-
dc.date.available2016-12-16T04:07:47Z-
dc.date.issued20/11/2016es_ES
dc.identifier.urihttp://hdl.handle.net/11531/15737-
dc.descriptionCapítulos en libroses_ES
dc.description.abstractes-ES
dc.description.abstractThis paper presents a method for the possible detection of abnormal performance of a wind turbine based on real observed pairs of wind speed and generated power. Usually the power curve satisfies this objective but its use in real-time for the detection of abnormal performance is not easy because the pairs observed do not follow a single line, but rather cloud of points around an ideal definition of it. This is the reason why the concept of the power curve has been extended in this paper to a normal power generation area for a period of time taken as reference for later comparisons. This area has to cover the most part of the data observed in the period considered as reference of performance. Once a normal power generation area is defined, it can be used to detect possible deviations in future observations. The paper includes some examples of application to four wind turbines where some abnormal deviations of performance were detected. Also, an analysis is included of other measured variables that could feed a complementary view about the results observed in the study carried out.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.publisherInternational Journal of Renewable Energy Research; IEEE Power Electronics Society; IEEE Advancing T (Birmingham, Reino Unido)es_ES
dc.rightses_ES
dc.rights.uries_ES
dc.sourceLibro: 5th International Conference on Renewable Energy Research and Applications - ICRERA 2016, Página inicial: , Página final:es_ES
dc.subject.otherInstituto de Investigación Tecnológica (IIT)es_ES
dc.titleNormal power generation area of wind turbines for the detection of abnormal performancees_ES
dc.typeinfo:eu-repo/semantics/bookPartes_ES
dc.description.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.keywordses-ES
dc.keywordswind turbine performance; power curve model; anomaly detection; wind turbine health assessment.en-GB
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