Show simple item record

dc.contributor.authorSimal Pérez, Noelia
dc.contributor.authorAlonso-Montesinos, Joaquín
dc.contributor.authorJavier Batlles, Francisco
dc.date.accessioned2021-02-15T11:50:08Z
dc.date.available2021-02-15T11:50:08Z
dc.date.issued2021-02-08
dc.identifier.issn2076-3417
dc.identifier.urihttp://hdl.handle.net/10835/9820
dc.description.abstractFossil fuels and their use to generate energy have multiple disadvantages, with renewable energies being presented as an alternative to this situation. Among them is photovoltaic solar energy, which requires solar installations that are capable of producing energy in an optimal way. These installations will have specific characteristics according to their location and meteorological variables of the place, one of these factors being soiling. Soiling generates energy losses, diminishing the plant’s performance, making it difficult to estimate the losses due to deposited soiling and to measure the amount of soiling if it is not done using very economically expensive devices, such as high-performance particle counters. In this work, these losses have been estimated with artificial intelligence techniques, using meteorological variables, commonly measured in a plant of these characteristics. The study consists of two tests, depending on whether or not the short circuit current (Isc) has been included, obtaining a maximum normalized root mean square error (nRMSE) lower than 7%, a correlation coefficient (R) higher than 0.9, as well as a practically zero normalized mean bias error (nMBE).es_ES
dc.language.isoenes_ES
dc.publisherMDPIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectsoilinges_ES
dc.subjectphotovoltaic plantes_ES
dc.subjectsolar energyes_ES
dc.subjectPV plant maintenancees_ES
dc.subjectANNes_ES
dc.subjectmachine learninges_ES
dc.titleEstimation of Soiling Losses from an Experimental Photovoltaic Plant Using Artificial Intelligence Techniqueses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://www.mdpi.com/2076-3417/11/4/1516es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


Files in this item

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional