Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/73827
DC FieldValueLanguage
dc.contributor.authorFernández-Peruchena, Carlos M.en_US
dc.contributor.authorPolo, Jesúsen_US
dc.contributor.authorMartín, Luisen_US
dc.contributor.authorMazorra Aguiar, Luisen_US
dc.date.accessioned2020-07-27T12:13:38Z-
dc.date.available2020-07-27T12:13:38Z-
dc.date.issued2020en_US
dc.identifier.issn2072-4292en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/73827-
dc.description.abstractThe adaptation of modeled solar radiation data with coincident ground measurements has become a standard practice of the industry, typically requested by financial institutions in the detailed solar resource assessments of solar projects. This practice mitigates the risk of solar projects, enhancing the adequate solar plant design and reducing the uncertainty of its yield estimates. This work presents a procedure for improving the accuracy of modeled solar irradiance series through site-adaptation with coincident ground-based measurements relying on the use of a regression preprocessing followed by an empirical quantile mapping (eQM) correction. It was tested at nine sites in a wide range of latitudes and climates, resulting in significant improvements of statistical indicators of dispersion, distribution similarity and overall performance: relative bias is reduced on average from-1.8% and-2.3% to 0.1% and 0.3% for GHI and DNI, respectively; relative root mean square deviation is reduced on average from 17.9% and 34.9% to 14.6% and 29.8% for GHI and DNI, respectively; the distribution similarity is also improved after the site-adaptation (KSI is 3.5 and 3.9 times lower for GHI and DNI at hourly scale, respectively). The methodology is freely available as supplementary material and downloadable as R-package from SiteAdapt.en_US
dc.languageengen_US
dc.relation.ispartofRemote Sensingen_US
dc.sourceRemote Sensing [EISSN 2072-4292], v. 12 (13), 2127, (Julio 2020)en_US
dc.subject210601 Energía solaren_US
dc.subject250121 Simulación numéricaen_US
dc.subject.otherBankability of solar projectsen_US
dc.subject.otherBias removalen_US
dc.subject.otherData fusionen_US
dc.subject.otherSatellite-derived irradianceen_US
dc.subject.otherSite-adaptationen_US
dc.titleSite-adaptation of modeled solar radiation data: the SiteAdapt procedureen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/rs12132127en_US
dc.identifier.scopus85087545636-
dc.contributor.authorscopusid8551520700-
dc.contributor.authorscopusid35614161500-
dc.contributor.authorscopusid57214404888-
dc.contributor.authorscopusid6506386746-
dc.identifier.eissn2072-4292-
dc.identifier.issue13-
dc.relation.volume12en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
local.message.claim2022-05-03T15:29:14.483+0100|||rp00601|||submit_approve|||dc_contributor_author|||El autor es: Mazorra-Aguiar, Luis-
dc.description.notasThis article belongs to the Special Issue Remote Sensing of Energy Meteorologyen_US
dc.utils.revisionen_US
dc.date.coverdateJulio 2020en_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-INFen_US
dc.description.sjr1,285-
dc.description.jcr4,848-
dc.description.sjrqQ1-
dc.description.jcrqQ1-
dc.description.scieSCIE-
item.fulltextCon texto completo-
item.grantfulltextopen-
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.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameMazorra Aguiar, Luis-
Appears in Collections:Artículos
Thumbnail
PDF
Adobe PDF (2,98 MB)
Show simple item record

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.