Study and development of a solar radiation predicting algorithm based on ECMWF's forecasts and ANNs

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dc.contributor.authorPereira, Sara
dc.contributor.authorCanhoto, Paulo
dc.contributor.authorSalgado, Rui
dc.contributor.authorCosta, Maria João
dc.date.accessioned2019-01-18T17:38:46Z
dc.date.available2019-01-18T17:38:46Z
dc.date.issued2018-06-17
dc.description.abstractThis paper presents a study on the influence of Sun-Earth geometry and atmospheric variables on the predictions of solar global irradiation (GHI) obtained from the ECMWF model. It was found that the differences between predictions and measurements of GHI are correlated mainly with the clearness index, solar zenith angle, mean air temperature, relative humidity and total water column. An artificial neural network is developed to improve predictions of GHI for four locations being the base for a predicting algorithm that can be used in energy management models of solar systems thus allowing a better management of renewable energy conversion.por
dc.description.sponsorshipThis work was carried out under the contract with the company Warmhole, lda for the development of a solar radiation forecast algorithm. The authors wish to acknowledge ECMWF and IPMA for the provision of data and the funding provided by the European Regional Development Fund, included in the COMPETE 2020 (Operational Program Competitiveness and Internationalization) through the ICT project (UID/GEO/ 04683/2013) with the reference POCI-01-0145-FEDER -007690, DNI-A (ALT20-03-0145-FEDER-000011) and ALOP (ALT20-03-0145-FEDER-000004) projects.por
dc.identifier.authoremailspereira@uevora.pt
dc.identifier.authoremailcanhoto@uevora.pt
dc.identifier.authoremailrsal@uevora.pt
dc.identifier.authoremailmjcosta@uevora.pt
dc.identifier.citationSara Pereira, Paulo Canhoto, Rui Salgado, Maria João Costa, Study and development of a solar radiation predicting algorithm based on ECMWF's forecasts and ANNs. Grand Renewable Energy 2018 - International Conference and Exhibition, 17 - 22 June, 2018, Pacifico Yokohama, Japanpor
dc.identifier.doi10.13140/RG.2.2.22184.01288por
dc.identifier.scientificarea286por
dc.identifier.urihttp://hdl.handle.net/10174/24098
dc.identifier.withinvitedoralpresentationnaopor
dc.identifier.withoralpresentationsimpor
dc.identifier.withposternaopor
dc.language.isoengpor
dc.publisherGrand Renewable Energy 2018 - International Conference and Exhibitionpor
dc.rightsopenAccesspor
dc.subjectSolar radiationpor
dc.subjectSolar energypor
dc.subjectSolar radiation forecastpor
dc.subjectECMWF modelpor
dc.subjectArtificial neural networkpor
dc.titleStudy and development of a solar radiation predicting algorithm based on ECMWF's forecasts and ANNspor
dc.typelecturepor

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