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dc.contributor.authorPrieto Herráez, Diego 
dc.contributor.authorMartínez Lastras, Saray 
dc.contributor.authorFrías-Paredes, Laura
dc.contributor.authorAsensio Sevilla, María Isabel 
dc.contributor.authorGonzález Aguilera, Diego 
dc.date.accessioned2025-02-19T08:21:46Z
dc.date.available2025-02-19T08:21:46Z
dc.date.issued2024-03-23
dc.identifier.citationPrieto-Herráez, D. et al.(2024). EOLO, a wind energy forecaster based on public information and automatic learning for the Spanish Electricity Markets. Measurement, 231, 114557.es_ES
dc.identifier.issn0263-2241
dc.identifier.urihttp://hdl.handle.net/10366/163827
dc.description.abstract[EN]For the correct operation of the electricity system, producers must provide an estimate of the energy they are going to discharge into the system, and they must face financial penalties if their forecasts are wrong. This is especially difficult in the case of renewable energies, and in particular wind energy because of its variability and intermittency. The tool proposed allows, in a first step, to improve the prediction of wind energy to be produced and, in a second step, to optimize the offer to be presented to the electricity market, so that the overall economic performance can be improved. This tool is based on the use of public information and automatic learning and has been evaluated on a set of 30 wind farms in Spain, using their historical production data. The results indicate improvements in both the accuracy of the energy estimation and the profit obtained from the energy sold.es_ES
dc.description.sponsorshipMinisterio de Ciencia, Innovación y Universidades, Spain Fundación General de la Universidad de Salamanca, Spaines_ES
dc.format.mimetypeapplication/pdf
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAtribución 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectRenewable energyes_ES
dc.subjectWind power forecastinges_ES
dc.subjectElectricity marketses_ES
dc.subjectPublic informationes_ES
dc.subjectAutomatic learninges_ES
dc.subjectFeature selectiones_ES
dc.titleEOLO, a wind energy forecaster based on public information and automatic learning for the Spanish Electricity Marketses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publishversionhttps://doi.org/10.1016/j.measurement.2024.114557
dc.subject.unesco2510.91 Recursos Renovableses_ES
dc.subject.unesco3322.05 Fuentes no Convencionales de Energíaes_ES
dc.identifier.doi10.1016/j.measurement.2024.114557
dc.relation.projectIDRTC-2017-6635-3es_ES
dc.relation.projectIDPC_TCUE2-23_012es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/closedAccesses_ES


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Atribución 4.0 Internacional
Except where otherwise noted, this item's license is described as Atribución 4.0 Internacional