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dc.contributor.authorAndrade Vieira, Rodrigo Josées-ES
dc.contributor.authorSanz Bobi, Miguel Ángeles-ES
dc.date.accessioned2016-05-23T03:09:39Z
dc.date.available2016-05-23T03:09:39Z
dc.date.issued25/02/2016es_ES
dc.identifier.urihttp://hdl.handle.net/11531/7933
dc.descriptionCapítulos en libroses_ES
dc.description.abstractes-ES
dc.description.abstractThe power curve of a wind turbine plays an essential role from its design till the end of its life. The production of energy depends on the relation power/wind-speed defined by the power curve. Any deviation of the expected relation between these two variables has an important impact translated usually in money for the owner in different ways. If the power curve observed over a period of time is different from that available in a previous interval of time analysed, usually effects of faults or natural or induced degradations are present. This paper describes how to reduce the huge amount of information based on collecting in real-time pairs of values power/wind-speed to few essential pairs able to describe the whole power curve by a model. Using this model it is possible to define a power curve reference in order to compare with other future performances. Also, this will allow for the detection of anomalies. The methods used for those illustrated by examples are the main contribution included in this paper.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.publisherInternational Journal of Renewable Energy Research (Palermo, Italia)es_ES
dc.rightses_ES
dc.rights.uries_ES
dc.sourceLibro: 4th International Conference on Renewable Energy Research and Applications - ICRERA 2015, Página inicial: 1052-1057, Página final:es_ES
dc.subject.otherInstituto de Investigación Tecnológica (IIT)es_ES
dc.titlePower curve modelling of a wind turbine for monitoring its behavioures_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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