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dc.creatorFerrero Bermejo, Jesúses
dc.creatorGómez Fernández, Juan Franciscoes
dc.creatorOlivencia Polo, Fernandoes
dc.creatorCrespo Márquez, Adolfoes
dc.date.accessioned2019-08-30T18:19:50Z
dc.date.available2019-08-30T18:19:50Z
dc.date.issued2019-05
dc.identifier.citationFerrero Bermejo, J., Gómez Fernández, J.F., Olivencia Polo, F. y Crespo Márquez, A. (2019). A Review of the Use of Artificial Neural Network Models for Energy and Reliability Prediction. A Study of the Solar PV, Hydraulic and Wind Energy Sources. Applied Sciences, 9 (9). Article number 1844.
dc.identifier.issn2076-3417es
dc.identifier.urihttps://hdl.handle.net/11441/88822
dc.description.abstractThe generation of energy from renewable sources is subjected to very dynamic changes in environmental parameters and asset operating conditions. This is a very relevant issue to be considered when developing reliability studies, modeling asset degradation and projecting renewable energy production. To that end, Artificial Neural Network (ANN) models have proven to be a very interesting tool, and there are many relevant and interesting contributions using ANN models, with different purposes, but somehow related to real-time estimation of asset reliability and energy generation. This document provides a precise review of the literature related to the use of ANN when predicting behaviors in energy production for the referred renewable energy sources. Special attention is paid to describe the scope of the different case studies, the specific approaches that were used over time, and the main variables that were considered. Among all contributions, this paper highlights those incorporating intelligence to anticipate reliability problems and to develop ad-hoc advanced maintenance policies. The purpose is to offer the readers an overall picture per energy source, estimating the significance that this tool has achieved over the last years, and identifying the potential of these techniques for future dependability analysis.es
dc.description.sponsorshipUnión Europea H2020-MSCA-RISE-2014es
dc.description.sponsorshipMinisterio de Economía y Competitividad DPI2015-70842-Res
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherMDPIes
dc.relation.ispartofApplied Sciences, 9 (9). Article number 1844.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectRenewable energyes
dc.subjectArtificial neural networkes
dc.subjectArtificial intelligencees
dc.subjectSurveyes
dc.titleA Review of the Use of Artificial Neural Network Models for Energy and Reliability Prediction. A Study of the Solar PV, Hydraulic and Wind Energy Sourceses
dc.typeinfo:eu-repo/semantics/articlees
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Organización Industrial y Gestión de Empresas Ies
dc.relation.projectIDH2020-MSCA-RISE-2014es
dc.relation.projectIDDPI2015-70842-Res
dc.relation.publisherversionhttps://doi.org/10.3390/app9091844es
idus.format.extent20 p.es
dc.journaltitleApplied Scienceses
dc.publication.volumen9es
dc.publication.issue9es
dc.publication.initialPageArticle number 1844es

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