Modeling of a robust confidence band for the power curve of a wind turbine

Having 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...

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1. autor: Hernández Perdomo, W. (author)
Format: article
Wydane: 2016
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Dostęp online:http://dspace.utpl.edu.ec/handle/123456789/18731
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author Hernández Perdomo, W.
author_facet Hernández Perdomo, W.
author_role author
collection Repositorio Universidad Técnica Particular de Loja
dc.creator.none.fl_str_mv Hernández Perdomo, W.
dc.date.none.fl_str_mv 07/12/2016
2016-11-23
2017-06-16T22:02:16Z
2017-06-16T22:02:16Z
dc.identifier.none.fl_str_mv 10.3390/s16122080
14248220
10.3390/s16122080
http://dspace.utpl.edu.ec/handle/123456789/18731
dc.language.none.fl_str_mv Inglés
dc.publisher.none.fl_str_mv Sensors
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:Repositorio Universidad Técnica Particular de Loja
instname:Universidad Técnica Particular de Loja
instacron:UTPL
dc.subject.none.fl_str_mv SCADA system
power curve
power-curve confidence band
dc.title.none.fl_str_mv Modeling of a robust confidence band for the power curve of a wind turbine
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Having 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.
eu_rights_str_mv openAccess
format article
id UTPL_f00df5f2718891ca3369a5ba9397d2a3
identifier_str_mv 10.3390/s16122080
14248220
instacron_str UTPL
institution UTPL
instname_str Universidad Técnica Particular de Loja
language_invalid_str_mv Inglés
network_acronym_str UTPL
network_name_str Repositorio Universidad Técnica Particular de Loja
oai_identifier_str oai:dspace.utpl.edu.ec:123456789/18731
publishDate 2016
publisher.none.fl_str_mv Sensors
reponame_str Repositorio Universidad Técnica Particular de Loja
repository.mail.fl_str_mv .
repository.name.fl_str_mv Repositorio Universidad Técnica Particular de Loja - Universidad Técnica Particular de Loja
repository_id_str 1227
spelling Modeling of a robust confidence band for the power curve of a wind turbineHernández Perdomo, W.SCADA systempower curvepower-curve confidence bandHaving 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.Sensors2017-06-16T22:02:16Z2016-11-232017-06-16T22:02:16Z07/12/2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article10.3390/s161220801424822010.3390/s16122080http://dspace.utpl.edu.ec/handle/123456789/18731Inglésinfo:eu-repo/semantics/openAccessreponame:Repositorio Universidad Técnica Particular de Lojainstname:Universidad Técnica Particular de Lojainstacron:UTPL2017-06-16T22:02:16Zoai:dspace.utpl.edu.ec:123456789/18731Institucionalhttps://dspace.utpl.edu.ec/Institución privadahttps://www.utpl.edu.ec/https://dspace.utpl.edu.ec/oai.Ecuador...opendoar:12272017-06-16T22:02:16Repositorio Universidad Técnica Particular de Loja - Universidad Técnica Particular de Lojafalse
spellingShingle Modeling of a robust confidence band for the power curve of a wind turbine
Hernández Perdomo, W.
SCADA system
power curve
power-curve confidence band
status_str publishedVersion
title Modeling of a robust confidence band for the power curve of a wind turbine
title_full Modeling of a robust confidence band for the power curve of a wind turbine
title_fullStr Modeling of a robust confidence band for the power curve of a wind turbine
title_full_unstemmed Modeling of a robust confidence band for the power curve of a wind turbine
title_short Modeling of a robust confidence band for the power curve of a wind turbine
title_sort Modeling of a robust confidence band for the power curve of a wind turbine
topic SCADA system
power curve
power-curve confidence band
url http://dspace.utpl.edu.ec/handle/123456789/18731