Deep learning-based forecasting of aggregated CSP production
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Altres documents de l'autoria: Segarra-Tamarit, Jorge; Pérez, Emilio; Moya Bueno, Eric; Ayuso, Pablo; Beltrán San Segundo, Héctor
Metadades
Mostra el registre complet de l'elementcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7034
comunitat-uji-handle3:10234/8619
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INVESTIGACIONMetadades
Títol
Deep learning-based forecasting of aggregated CSP productionAutoria
Data de publicació
2020-02-25Editor
ElsevierISSN
0378-4754Cita bibliogràfica
J. Segarra-Tamarit, E. Pérez, E. Moya et al., Deep learning-based forecasting of aggregated CSP production, Mathematics and Computers in Simulation (2020), https://doi.org/10.1016/j.matcom.2020.02.007.Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://www.sciencedirect.com/science/article/pii/S037847542030046XVersió
info:eu-repo/semantics/acceptedVersionParaules clau / Matèries
Resum
This paper introduces deep learning-based forecasting models for the continuous prediction of the aggregated production generated by CSP plants in Spain. These models use as inputs the expected top of atmosphere ... [+]
This paper introduces deep learning-based forecasting models for the continuous prediction of the aggregated production generated by CSP plants in Spain. These models use as inputs the expected top of atmosphere irradiance
values and available weather conditions forecasts for the locations where the main CSP power plants are installed.
The performances of the forecast models are analysed and compared by means of the most extended metrics in the
literature for a whole year of CSP energy production. [-]
Publicat a
Mathematics and Computers in Simulation (2020).Proyecto de investigación
JI-B2017-26, ACIF/2019/106Drets d'accés
0378-4754/© 2020 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rightsreserved
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/openAccess
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/openAccess
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