Please use this identifier to cite or link to this item: http://dspace.utpl.edu.ec/handle/123456789/18731
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dc.contributor.authorHernández Perdomo, W.es_ES
dc.date.accessioned2017-06-16T22:02:16Z-
dc.date.available2016-11-23es_ES
dc.date.available2017-06-16T22:02:16Z-
dc.date.submitted07/12/2016es_ES
dc.identifier10.3390/s16122080es_ES
dc.identifier.isbn14248220es_ES
dc.identifier.other10.3390/s16122080es_ES
dc.identifier.urihttp://dspace.utpl.edu.ec/handle/123456789/18731-
dc.description.abstractHaving an accurate model of the power curve of a wind turbine allows us to better monitor its operation and planning of storage capacity. Since wind speed and direction is of a highly stochastic nature, the forecasting of the power generated by the wind turbine is of the same nature as well. In this paper, a method for obtaining a robust confidence band containing the power curve of a wind turbine under test conditions is presented. Here, the confidence band is bound by two curves which are estimated using parametric statistical inference techniques. However, the observations that are used for carrying out the statistical analysis are obtained by using the binning method, and in each bin, the outliers are eliminated by using a censorship process based on robust statistical techniques. Then, the observations that are not outliers are divided into observation sets. Finally, both the power curve of the wind turbine and the two curves that define the robust confidence band are estimated using each of the previously mentioned observation sets.es_ES
dc.languageIngléses_ES
dc.subjectSCADA systemes_ES
dc.subjectpower curvees_ES
dc.subjectpower-curve confidence bandes_ES
dc.titleModeling of a robust confidence band for the power curve of a wind turbinees_ES
dc.typeArticlees_ES
dc.publisherSensorses_ES
Appears in Collections:Artículos de revistas Científicas



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