Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/50527
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dc.contributor.authorRamírez, Penélope
dc.contributor.authorCarta, José Antonio
dc.date.accessioned2018-11-24T16:44:20Z-
dc.date.available2018-11-24T16:44:20Z-
dc.date.issued2006
dc.identifier.issn0196-8904
dc.identifier.urihttp://hdl.handle.net/10553/50527-
dc.description.abstractThis paper analyses the use of a general probability distribution obtained through application of the maximum entropy principle (MEP), constrained by the low-order statistical moments of a given set of wind speed data, in the estimation of wind energy. For this purpose, a comparison is made between the two parameter Weibull distribution and the distributions obtained through the MER This comparison is based on an analysis of the level of fit to the cumulative frequencies of the hourly mean wind speeds recorded at weather stations located in the Canarian Archipelago. A comparison is also made of the ability to describe the experimental mean wind power density. The application of the probability plot correlation coefficient R 2, adjusted for degrees of freedom, shows that the Weibull distribution, whose parameters are estimated using the maximum likelihood principle, provide worse fits in all the cases analysed than those obtained through the maximum entropy distributions constrained by the low-order statistical moments. It is, thus, shown that maximum entropy distributions constrained by the three low-order statistical moments, in addition to representing the probabilities of observed periods of null wind speeds, offer less relative errors in determining the mean wind power density than the Weibull distribution. However, among other advantages of the Weibull distribution, is the greater simplicity of the calculations involved. (c) 2005 Elsevier Ltd. All rights reserved.
dc.publisher0196-8904
dc.relation.ispartofEnergy Conversion and Management
dc.sourceEnergy Conversion and Management[ISSN 0196-8904],v. 47, p. 2564-2577
dc.subject.otherSpeed Frequency-Distributions
dc.subject.otherStatistical Mechanics
dc.subject.otherWeibull Statistics
dc.subject.otherInformation Theory
dc.titleThe use of wind probability distributions derived from the maximum entropy principle in the analysis of wind energy. A case study
dc.typeinfo:eu-repo/semantics/Articlees
dc.typeArticlees
dc.identifier.doi10.1016/j.enconman.2005.10.027
dc.identifier.scopus33646754223
dc.identifier.isi000238277200049
dc.contributor.authorscopusid8334207300
dc.contributor.authorscopusid7003652043
dc.description.lastpage2577
dc.description.firstpage2564
dc.relation.volume47
dc.type2Artículoes
dc.contributor.daisngid4727747
dc.contributor.daisngid1198474
dc.contributor.wosstandardWOS:Ramirez, P
dc.contributor.wosstandardWOS:Carta, JA
dc.date.coverdateSeptiembre 2006
dc.identifier.ulpgces
dc.description.jcr1,325
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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