Nowcasting System Based on Sky Camera Images to Predict the Solar Flux on the Receiver of a Concentrated Solar Plant
| dc.contributor.author | Alonso-Montesinos, Joaquín | |
| dc.contributor.author | Monterreal, Rafael | |
| dc.contributor.author | Fernández Reche, Jesús | |
| dc.contributor.author | Ballestrín, Jesús | |
| dc.contributor.author | López Rodríguez, Gabriel | |
| dc.contributor.author | Polo, Jesús | |
| dc.contributor.author | Barbero, Francisco Javier | |
| dc.contributor.author | Marzo, Aitor | |
| dc.contributor.author | Portillo, Carlos | |
| dc.contributor.author | Batlles, Francisco J. | |
| dc.date.accessioned | 2022-04-11T10:02:46Z | |
| dc.date.available | 2022-04-11T10:02:46Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | As part of the research for techniques to control the final energy reaching the receivers of central solar power plants, this work combines two contrasting methods in a novel way as a first step towards integrating such systems in solar plants. To determine the effective power reaching the receiver, the direct normal irradiance was predicted at ground level using a total sky camera, TSI-880 model. Subsequently, these DNI values were used as the inputs for a heliostat model (Fiat-Lux) to trace the sunlight’s path according to the mirror features. The predicted valuex of flux, obtained from these simulations, differ of less than 20% from the real values. This represents a significant advance in integrating different technologies to quantify the losses produced in the path from the heliostats to the central receiver, which are normally caused by the presence of atmospheric attenuation factors | es_ES |
| dc.description.department | Ingeniería Eléctrica y Térmica, de Diseño y Proyectos | |
| dc.description.sponsorship | This research was funded by the Ministerio de Economía, Industria y Competitividad grant numbers ENE2014-59454-C3-1, 2 and 3; and ENE2017-83790-C3-1, 2 and 3; and co-financed by the European Regional Development Fund. The author would like to thank the PRESOL Project (references ENE2014- 59454-C3-1, 2 and 3) and the PVCastSOIL Project (references ENE2017-83790-C3-1, 2 and 3), which were funded by the Ministerio de Economía, Industria y Competitividad, and the MAPVSpain Project (PID2020-118239RJ-I00), which was funded by the Ministerio de Ciencia e Innovación; all of them co-financed by the European Regional Development Fund. The authors also acknowledge ANID/FONDAP/15110019 SERC Chile | |
| dc.identifier.citation | Alonso-Montesinos, J., Monterreal, R., Fernandez-Reche, J., Ballestrín, J., López, G., Polo, J., Barbero, F. J., Marzo, A., Portillo, C., & Batlles, F. J. (2022). Nowcasting System Based on Sky Camera Images to Predict the Solar Flux on the Receiver of a Concentrated Solar Plant. In Remote Sensing (Vol. 14, Issue 7, p. 1602). MDPI AG. https://doi.org/10.3390/rs14071602 | es_ES |
| dc.identifier.doi | 10.3390/rs14071602 | |
| dc.identifier.issn | 2072-4292 (electrónico) | |
| dc.identifier.uri | http://hdl.handle.net/10272/20834 | |
| dc.language.iso | eng | es_ES |
| dc.publisher | MDPI | es_ES |
| dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | * |
| dc.rights.accessRights | open access | es_ES |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
| dc.subject.other | Image processing | es_ES |
| dc.subject.other | Solar energy | es_ES |
| dc.subject.other | Central solar power plant | es_ES |
| dc.subject.other | Sky cam images | es_ES |
| dc.subject.other | Flux simulation | es_ES |
| dc.subject.other | Solar plant control | es_ES |
| dc.subject.other | Remote sensing | es_ES |
| dc.subject.unesco | 33 Ciencias Tecnológicas | es_ES |
| dc.title | Nowcasting System Based on Sky Camera Images to Predict the Solar Flux on the Receiver of a Concentrated Solar Plant | es_ES |
| dc.type | journal article | es_ES |
| dc.type.hasVersion | VoR | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 703e8224-9057-431a-88c8-6a1720d615af | |
| relation.isAuthorOfPublication.latestForDiscovery | 703e8224-9057-431a-88c8-6a1720d615af |
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