Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/41931
DC FieldValueLanguage
dc.contributor.authorAguiar, L. Mazorraen_US
dc.contributor.authorPereira, Ben_US
dc.contributor.authorLauret, P.en_US
dc.contributor.authorDíaz, F.en_US
dc.contributor.authorDavid, M.en_US
dc.contributor.otherDiaz, Felipe
dc.contributor.otherMAZORRA AGUIAR, LUIS
dc.date.accessioned2018-09-13T17:28:10Z-
dc.date.available2018-09-13T17:28:10Z-
dc.date.issued2016en_US
dc.identifier.issn0960-1481en_US
dc.identifier.urihttp://hdl.handle.net/10553/41931-
dc.description.abstractIsolated power systems need to generate all the electricity demand with their own renewable resources. Among the latter, solar energy may account for a large share. However, solar energy is a fluctuating source and the island power grid could present an unstable behavior with a high solar penetration. Global Horizontal Solar Irradiance (GHI) forecasting is an important issue to increase solar energy production into electric power system. This study is focused in hourly GHI forecasting from 1 to 6 h ahead. Several statistical models have been successfully tested in GHI forecasting, such us autoregressive (AR), autoregressive moving average (ARMA) and Artificial Neural Networks (ANN). In this paper, ANN models are designed to produce intra-day solar forecasts using ground and exogenous data. Ground data were obtained from two measurement stations in Gran Canaria Island. In order to improve the results obtained with ground data, satellite GHI data (from Helioclim-3) as well as solar radiation and Total Cloud Cover forecasts provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) are used as additional inputs of the ANN model. It is shown that combining exogenous data (satellite and ECMWF forecasts) with ground data further improves the accuracy of the intra-day forecasts.en_US
dc.languageengen_US
dc.relation.ispartofRenewable Energyen_US
dc.sourceRenewable Energy[ISSN 0960-1481],v. 97, p. 599-610en_US
dc.subject210601 Energía solaren_US
dc.subject3322 Tecnología energéticaen_US
dc.subject250121 Simulación numéricaen_US
dc.subject.otherArtificial neural networksen_US
dc.subject.otherNumerical weather predictionen_US
dc.subject.otherSatellite imagesen_US
dc.subject.otherSolar forecastingen_US
dc.titleCombining solar irradiance measurements, satellite-derived data and a numerical weather prediction model to improve intra-day solar forecastingen_US
dc.typeinfo:eu-repo/semantics/Articlees
dc.typeArticlees
dc.identifier.doi10.1016/j.renene.2016.06.018
dc.identifier.scopus84974717477-
dc.identifier.isi000380600500054
dcterms.isPartOfRenewable Energy
dcterms.sourceRenewable Energy[ISSN 0960-1481],v. 97, p. 599-610
dc.contributor.authorscopusid56971482900
dc.contributor.authorscopusid56970705800
dc.contributor.authorscopusid7004327525
dc.contributor.authorscopusid26429057600
dc.contributor.authorscopusid35486904800
dc.description.lastpage610-
dc.description.firstpage599-
dc.relation.volume97-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.identifier.wosWOS:000380600500054-
dc.contributor.daisngid3785154
dc.contributor.daisngid6874850
dc.contributor.daisngid30889953
dc.contributor.daisngid1136985
dc.contributor.daisngid3919769
dc.contributor.daisngid1403275
dc.identifier.investigatorRIDL-1074-2014
dc.identifier.investigatorRIDK-4255-2017
dc.contributor.wosstandardWOS:Aguiar, LM
dc.contributor.wosstandardWOS:Pereira, B
dc.contributor.wosstandardWOS:Lauret, P
dc.contributor.wosstandardWOS:Diaz, F
dc.contributor.wosstandardWOS:David, M
dc.date.coverdateNoviembre 2016
dc.identifier.ulpgces
dc.description.sjr1,697
dc.description.jcr4,357
dc.description.sjrqQ1
dc.description.jcrqQ1
dc.description.scieSCIE
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptGIR SIANI: Modelización y Simulación Computacional-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Ingeniería Eléctrica-
crisitem.author.orcid0000-0002-9746-7461-
crisitem.author.orcid0000-0001-7874-6636-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameMazorra Aguiar, Luis-
crisitem.author.fullNameDíaz Reyes, Felipe-
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