Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants.
Resumen:
This work presents and validates an intra-day operational solar forecast for the southern cone of South America based on GOES16 satellite images. The forecast is evaluated over 12 photovoltaic (PV) generation sites in the northwest of Uruguay. The irradiance predictions are obtained from the combination of different satellite cloudiness forecasts and a standard satellite-to-irradiance conversion model, both specifically adapted to the region. The core of the system is a Cloud Motion Vector (CMV) satellite technique, considered in different spatial resolutions. The optimal linear combination of a single-pixel and space-averaged CMV forecast with the space-averaged persistence is proposed and analyzed. The performance assessment of the individual sub-forecasts and their combination is presented for each time horizon between 10 minutes and 4 hours, with a 10 minutes time step.
| 2021 | |
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Solar forecast CMV GOES16 satellite GHI |
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| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/43622 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| _version_ | 1875693099149164544 |
|---|---|
| author | Alonso-Suárez, Rodrigo |
| author2 | Marchesoni-Acland, Franco Dovat, Liber Laguarda, Agustín |
| author2_role | author author author |
| author_facet | Alonso-Suárez, Rodrigo Marchesoni-Acland, Franco Dovat, Liber Laguarda, Agustín |
| author_role | author |
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| collection | COLIBRI |
| dc.contributor.filiacion.none.fl_str_mv | Alonso-Suárez Rodrigo, Universidad de la República (Uruguay). Facultad de Ingeniería. Marchesoni-Acland Franco, Universidad de la República (Uruguay). Facultad de Ingeniería. Dovat Líber, Universidad de la República (Uruguay). Facultad de Ingeniería. Laguarda Agustín, Universidad de la República (Uruguay). Facultad de Ingeniería. |
| dc.creator.none.fl_str_mv | Alonso-Suárez, Rodrigo Marchesoni-Acland, Franco Dovat, Liber Laguarda, Agustín |
| dc.date.accessioned.none.fl_str_mv | 2024-04-24T14:04:11Z |
| dc.date.available.none.fl_str_mv | 2024-04-24T14:04:11Z |
| dc.date.issued.none.fl_str_mv | 2021 |
| dc.description.abstract.none.fl_txt_mv | This work presents and validates an intra-day operational solar forecast for the southern cone of South America based on GOES16 satellite images. The forecast is evaluated over 12 photovoltaic (PV) generation sites in the northwest of Uruguay. The irradiance predictions are obtained from the combination of different satellite cloudiness forecasts and a standard satellite-to-irradiance conversion model, both specifically adapted to the region. The core of the system is a Cloud Motion Vector (CMV) satellite technique, considered in different spatial resolutions. The optimal linear combination of a single-pixel and space-averaged CMV forecast with the space-averaged persistence is proposed and analyzed. The performance assessment of the individual sub-forecasts and their combination is presented for each time horizon between 10 minutes and 4 hours, with a 10 minutes time step. |
| dc.format.extent.es.fl_str_mv | 6 p. |
| dc.format.mimetype.es.fl_str_mv | application/pdf |
| dc.identifier.citation.es.fl_str_mv | Alonso-Suárez, R., Marchesoni-Acland, F., Dovat, L. y otros. Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants [en línea] EN: 2021 IEEE URUCON, Montevideo, Uruguay, 2021, pp. 182-187. DOI: 10.1109/URUCON53396.2021.9647087. |
| dc.identifier.doi.none.fl_str_mv | 10.1109/URUCON53396.2021.9647087 |
| dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12008/43622 |
| dc.language.iso.none.fl_str_mv | en eng |
| dc.publisher.es.fl_str_mv | IEEE |
| dc.relation.none.fl_str_mv | 2021 IEEE URUCON, Montevideo, Uruguay, 2021, pp. 182-187. |
| dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.es.fl_str_mv | Solar forecast CMV GOES16 satellite GHI |
| dc.title.none.fl_str_mv | Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants. |
| dc.type.es.fl_str_mv | Ponencia |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/conferenceObject |
| dc.type.version.none.fl_str_mv | info:eu-repo/semantics/publishedVersion |
| description | This work presents and validates an intra-day operational solar forecast for the southern cone of South America based on GOES16 satellite images. The forecast is evaluated over 12 photovoltaic (PV) generation sites in the northwest of Uruguay. The irradiance predictions are obtained from the combination of different satellite cloudiness forecasts and a standard satellite-to-irradiance conversion model, both specifically adapted to the region. The core of the system is a Cloud Motion Vector (CMV) satellite technique, considered in different spatial resolutions. The optimal linear combination of a single-pixel and space-averaged CMV forecast with the space-averaged persistence is proposed and analyzed. The performance assessment of the individual sub-forecasts and their combination is presented for each time horizon between 10 minutes and 4 hours, with a 10 minutes time step. |
| eu_rights_str_mv | openAccess |
| format | conferenceObject |
| id | COLIBRI_667ef2deaccc857b5f9c6cf3a387d9e2 |
| identifier_str_mv | Alonso-Suárez, R., Marchesoni-Acland, F., Dovat, L. y otros. Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants [en línea] EN: 2021 IEEE URUCON, Montevideo, Uruguay, 2021, pp. 182-187. DOI: 10.1109/URUCON53396.2021.9647087. 10.1109/URUCON53396.2021.9647087 |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | COLIBRI |
| network_name_str | COLIBRI |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/43622 |
| publishDate | 2021 |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | karina.camps@seciu.edu.uy |
| repository.name.fl_str_mv | COLIBRI - Universidad de la República |
| repository_id_str | 4771 |
| rights_invalid_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| spelling | Alonso-Suárez Rodrigo, Universidad de la República (Uruguay). Facultad de Ingeniería.Marchesoni-Acland Franco, Universidad de la República (Uruguay). Facultad de Ingeniería.Dovat Líber, Universidad de la República (Uruguay). Facultad de Ingeniería.Laguarda Agustín, Universidad de la República (Uruguay). Facultad de Ingeniería.2024-04-24T14:04:11Z2024-04-24T14:04:11Z2021Alonso-Suárez, R., Marchesoni-Acland, F., Dovat, L. y otros. Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants [en línea] EN: 2021 IEEE URUCON, Montevideo, Uruguay, 2021, pp. 182-187. DOI: 10.1109/URUCON53396.2021.9647087.https://hdl.handle.net/20.500.12008/4362210.1109/URUCON53396.2021.9647087This work presents and validates an intra-day operational solar forecast for the southern cone of South America based on GOES16 satellite images. The forecast is evaluated over 12 photovoltaic (PV) generation sites in the northwest of Uruguay. The irradiance predictions are obtained from the combination of different satellite cloudiness forecasts and a standard satellite-to-irradiance conversion model, both specifically adapted to the region. The core of the system is a Cloud Motion Vector (CMV) satellite technique, considered in different spatial resolutions. The optimal linear combination of a single-pixel and space-averaged CMV forecast with the space-averaged persistence is proposed and analyzed. The performance assessment of the individual sub-forecasts and their combination is presented for each time horizon between 10 minutes and 4 hours, with a 10 minutes time step.Submitted by Berón Cecilia (cberon@fing.edu.uy) on 2024-04-19T17:39:22Z No. of bitstreams: 2 license_rdf: 25790 bytes, checksum: 489f03e71d39068f329bdec8798bce58 (MD5) AMDL21.pdf: 879234 bytes, checksum: 29dec2697776d77bd7ed63e9e304a7b0 (MD5)Approved for entry into archive by Machado Jimena (jmachado@fing.edu.uy) on 2024-04-24T13:54:47Z (GMT) No. of bitstreams: 2 license_rdf: 25790 bytes, checksum: 489f03e71d39068f329bdec8798bce58 (MD5) AMDL21.pdf: 879234 bytes, checksum: 29dec2697776d77bd7ed63e9e304a7b0 (MD5)Made available in DSpace by Luna Fabiana (fabiana.luna@seciu.edu.uy) on 2024-04-24T14:04:11Z (GMT). No. of bitstreams: 2 license_rdf: 25790 bytes, checksum: 489f03e71d39068f329bdec8798bce58 (MD5) AMDL21.pdf: 879234 bytes, checksum: 29dec2697776d77bd7ed63e9e304a7b0 (MD5) Previous issue date: 20216 p.application/pdfenengIEEE2021 IEEE URUCON, Montevideo, Uruguay, 2021, pp. 182-187.Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. 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- Universidad de la Repúblicafalse |
| spellingShingle | Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants. Alonso-Suárez, Rodrigo Solar forecast CMV GOES16 satellite GHI |
| status_str | publishedVersion |
| title | Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants. |
| title_full | Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants. |
| title_fullStr | Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants. |
| title_full_unstemmed | Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants. |
| title_short | Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants. |
| title_sort | Satellite-based operational solar irradiance forecast for Uruguay’s solar power plants. |
| topic | Solar forecast CMV GOES16 satellite GHI |
| url | https://hdl.handle.net/20.500.12008/43622 |
