Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/50523
Campo DC Valoridioma
dc.contributor.authorCarta, José A.
dc.contributor.authorBueno, Celia
dc.contributor.authorRamírez, Penélope
dc.date.accessioned2018-11-24T16:42:30Z-
dc.date.available2018-11-24T16:42:30Z-
dc.date.issued2008
dc.identifier.issn0196-8904
dc.identifier.urihttp://hdl.handle.net/10553/50523-
dc.description.abstractA finite mixture model of continuous variable probability is used in this paper to represent the distribution of directional wind speed. The model is comprised of a finite mixture of von Mises (vM-pdf) distributions.The parameters of the model are estimated using the least squares method. The range of integration to compute the mean angle and the standard deviation of wind direction is adjusted to minimum variance requirements. The suitability of the distributions is judged from the coefficient of determination R-2. The model is applied in this paper to wind direction data recorded at several weather stations located in the Canary Islands (Spain). The conclusion reached is that the mixture distribution used in this paper provides a very flexible model for wind direction studies and can be applied in a widespread manner to represent the wind direction regimes in zones with several modes or prevailing wind directions. In the case of the Canary Islands, mixtures of two vM-pdfs provide better fits in all the cases analysed than those obtained with the models proposed in the specialised literature oil wind energy. The conclusion is also drawn that when the number of components N of the mixture distribution increases, tile value of R-2 increases. However, the variations in R-2 are not significant for values of N greater than six. (C) 2007 Elsevier Ltd. All rights reserved.
dc.publisher0196-8904
dc.relation.ispartofEnergy Conversion and Management
dc.sourceEnergy Conversion and Management[ISSN 0196-8904],v. 49, p. 897-907
dc.subject.otherEnergy
dc.titleStatistical modelling of directional wind speeds using mixtures of von Mises distributions: Case study
dc.typeinfo:eu-repo/semantics/Articlees
dc.typeArticlees
dc.identifier.doi10.1016/j.enconman.2007.10.017
dc.identifier.scopus40849141085
dc.identifier.isi000255318600001
dc.contributor.authorscopusid7003652043
dc.contributor.authorscopusid7005223381
dc.contributor.authorscopusid8334207300
dc.description.lastpage907
dc.description.firstpage897
dc.relation.volume49
dc.type2Artículoes
dc.contributor.daisngid1198474
dc.contributor.daisngid27849251
dc.contributor.daisngid32229306
dc.contributor.wosstandardWOS:Carta, JA
dc.contributor.wosstandardWOS:Bueno, C
dc.contributor.wosstandardWOS:Ramirez, P
dc.date.coverdateMayo 2008
dc.identifier.ulpgces
dc.description.jcr1,813
dc.description.jcrqQ1
dc.description.scieSCIE
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR Group for the Research on Renewable Energy Systems-
crisitem.author.deptDepartamento de Ingeniería Mecánica-
crisitem.author.orcid0000-0003-1379-0075-
crisitem.author.parentorgDepartamento de Ingeniería Mecánica-
crisitem.author.fullNameCarta González, José Antonio-
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