Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/50522
Campo DC Valoridioma
dc.contributor.authorCarta, José A.
dc.contributor.authorRamírez, Penélope
dc.contributor.authorBueno, Celia
dc.date.accessioned2018-11-24T16:42:03Z-
dc.date.available2018-11-24T16:42:03Z-
dc.date.issued2008
dc.identifier.issn0196-8904
dc.identifier.urihttp://hdl.handle.net/10553/50522-
dc.description.abstractA very flexible joint probability density function of wind speed and direction is presented in this paper for use in wind energy analysis. A method that enables angular-linear distributions to be obtained with specified marginal distributions has been used for this purpose. For the marginal distribution of wind speed we use a singly truncated from below Normal-Weibull mixture distribution. The marginal distribution of wind direction comprises a finite mixture of von Mises distributions. The proposed model is applied in this paper to wind direction and wind speed hourly data recorded at several weather stations located in the Canary Islands (Spain). The suitability of the distributions is judged from the coefficient of determination R The conclusions reached are that the joint distribution proposed in this paper: (a) can represent unimodal, bimodal and bitangential wind speed frequency distributions, (b) takes into account the frequency Of null winds, (c) represents the wind direction regimes in zones with several modes or prevailing wind directions, (d) takes into account the correlation between wind speeds and its directions. It can therefore be used in several tasks involved in the evaluation process of the wind resources available at a potential site. We also conclude that, in the case of the Canary Islands, the proposed model provides better fits in all the cases analysed than those obtained with the models used in the specialised literature on wind energy. (C) 2008 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. 1309-1320
dc.subject.otherDistributions
dc.subject.otherModels
dc.titleA joint probability density function of wind speed and direction for wind energy analysis
dc.typeinfo:eu-repo/semantics/Articlees
dc.typeArticlees
dc.identifier.doi10.1016/j.enconman.2008.01.010
dc.identifier.scopus42749097896
dc.identifier.isi000256273400003
dc.contributor.authorscopusid7003652043
dc.contributor.authorscopusid8334207300
dc.contributor.authorscopusid7005223381
dc.description.lastpage1320
dc.description.firstpage1309
dc.relation.volume49
dc.type2Artículoes
dc.contributor.daisngid1198474
dc.contributor.daisngid32229306
dc.contributor.daisngid27849251
dc.contributor.wosstandardWOS:Carta, JA
dc.contributor.wosstandardWOS:Ramirez, P
dc.contributor.wosstandardWOS:Bueno, C
dc.date.coverdateJunio 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-
Colección:Artículos
Vista resumida

Citas SCOPUSTM   

158
actualizado el 17-nov-2024

Citas de WEB OF SCIENCETM
Citations

135
actualizado el 17-nov-2024

Visitas

59
actualizado el 02-dic-2023

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.