Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/25751 https://doi.org/Lopes, F.M., Conceição, R., Silva, H.G., Salgado, R., Canhoto, P., Collares-Pereira, M., 2019. Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation. AIP Conference Proceedings 2126, 190010 (2019). https://doi.org/10.1063/1.5117707 https://doi.org/10.1063/1.5117707 |
Resumo: | Solar power forecasting plays a critical role in power-system management, scheduling, and dispatch operations. Accurate forecasts of direct normal irradiance (DNI) are essential for an optimized operation strategy of concentrating solar thermal (CST) systems, particularly during partly cloudy days, due to solar intermittency. In this work, short-term forecasts from the radiative scheme McRad (Cycle 41R2) included in the Integrated Forecasting System (IFS), the global numerical weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF), together with in-situ ground-based measurements, are used in a simulated linear focus parabolic-trough power system through the System Advisor Model (SAM). Results are part of a preliminary analysis concerning the value of DNI predictions from the IFS for operation improvement of a CST system with similar configurations as the Andasol 3 CST power plant. For a 365-day period, the present results show high correlations between predictions of energy to grid based on measurements and IFS forecasts mainly for daily values (≈0.94), while lower correlations are obtained for hourly values (≈0.88), due to cloud representation of the IFS during overcast periods, leading to small deviations with respect to those from measurements. Moreover, to measure the forecasting skill of the IFS, daily and hourly skill scores based on local measurements and a persistence model are obtained (≈0.66 and ≈0.51, respectively), demonstrating that the IFS has a good overall performance. These aspects show the value that forecasted DNI has in the operation management of CST power systems, and, consequently, in the electricity market. |
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Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems OperationSolar power forecasting plays a critical role in power-system management, scheduling, and dispatch operations. Accurate forecasts of direct normal irradiance (DNI) are essential for an optimized operation strategy of concentrating solar thermal (CST) systems, particularly during partly cloudy days, due to solar intermittency. In this work, short-term forecasts from the radiative scheme McRad (Cycle 41R2) included in the Integrated Forecasting System (IFS), the global numerical weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF), together with in-situ ground-based measurements, are used in a simulated linear focus parabolic-trough power system through the System Advisor Model (SAM). Results are part of a preliminary analysis concerning the value of DNI predictions from the IFS for operation improvement of a CST system with similar configurations as the Andasol 3 CST power plant. For a 365-day period, the present results show high correlations between predictions of energy to grid based on measurements and IFS forecasts mainly for daily values (≈0.94), while lower correlations are obtained for hourly values (≈0.88), due to cloud representation of the IFS during overcast periods, leading to small deviations with respect to those from measurements. Moreover, to measure the forecasting skill of the IFS, daily and hourly skill scores based on local measurements and a persistence model are obtained (≈0.66 and ≈0.51, respectively), demonstrating that the IFS has a good overall performance. These aspects show the value that forecasted DNI has in the operation management of CST power systems, and, consequently, in the electricity market.AIP Conference Proceedings 2126, 190010 (2019)2019-08-12T15:18:49Z2019-08-122019-07-26T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/25751https://doi.org/Lopes, F.M., Conceição, R., Silva, H.G., Salgado, R., Canhoto, P., Collares-Pereira, M., 2019. Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation. AIP Conference Proceedings 2126, 190010 (2019). https://doi.org/10.1063/1.5117707http://hdl.handle.net/10174/25751https://doi.org/10.1063/1.5117707engfmlopes@uevora.ptrfc@uevora.pthgsilva@uevora.ptrsal@uevora.ptcanhoto@uevora.ptcollarespereira@uevora.pt390Lopes, FranciscoConceição, RicardoSilva, HugoSalgado, RuiCanhoto, PauloCollares-Pereira, Manuelinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:19:52Zoai:dspace.uevora.pt:10174/25751Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:16:09.327846Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation |
title |
Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation |
spellingShingle |
Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation Lopes, Francisco |
title_short |
Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation |
title_full |
Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation |
title_fullStr |
Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation |
title_full_unstemmed |
Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation |
title_sort |
Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation |
author |
Lopes, Francisco |
author_facet |
Lopes, Francisco Conceição, Ricardo Silva, Hugo Salgado, Rui Canhoto, Paulo Collares-Pereira, Manuel |
author_role |
author |
author2 |
Conceição, Ricardo Silva, Hugo Salgado, Rui Canhoto, Paulo Collares-Pereira, Manuel |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Lopes, Francisco Conceição, Ricardo Silva, Hugo Salgado, Rui Canhoto, Paulo Collares-Pereira, Manuel |
description |
Solar power forecasting plays a critical role in power-system management, scheduling, and dispatch operations. Accurate forecasts of direct normal irradiance (DNI) are essential for an optimized operation strategy of concentrating solar thermal (CST) systems, particularly during partly cloudy days, due to solar intermittency. In this work, short-term forecasts from the radiative scheme McRad (Cycle 41R2) included in the Integrated Forecasting System (IFS), the global numerical weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF), together with in-situ ground-based measurements, are used in a simulated linear focus parabolic-trough power system through the System Advisor Model (SAM). Results are part of a preliminary analysis concerning the value of DNI predictions from the IFS for operation improvement of a CST system with similar configurations as the Andasol 3 CST power plant. For a 365-day period, the present results show high correlations between predictions of energy to grid based on measurements and IFS forecasts mainly for daily values (≈0.94), while lower correlations are obtained for hourly values (≈0.88), due to cloud representation of the IFS during overcast periods, leading to small deviations with respect to those from measurements. Moreover, to measure the forecasting skill of the IFS, daily and hourly skill scores based on local measurements and a persistence model are obtained (≈0.66 and ≈0.51, respectively), demonstrating that the IFS has a good overall performance. These aspects show the value that forecasted DNI has in the operation management of CST power systems, and, consequently, in the electricity market. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-08-12T15:18:49Z 2019-08-12 2019-07-26T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/25751 https://doi.org/Lopes, F.M., Conceição, R., Silva, H.G., Salgado, R., Canhoto, P., Collares-Pereira, M., 2019. Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation. AIP Conference Proceedings 2126, 190010 (2019). https://doi.org/10.1063/1.5117707 http://hdl.handle.net/10174/25751 https://doi.org/10.1063/1.5117707 |
url |
http://hdl.handle.net/10174/25751 https://doi.org/Lopes, F.M., Conceição, R., Silva, H.G., Salgado, R., Canhoto, P., Collares-Pereira, M., 2019. Predictive Value of Short-Term Forecasts of DNI for Solar Energy Systems Operation. AIP Conference Proceedings 2126, 190010 (2019). https://doi.org/10.1063/1.5117707 https://doi.org/10.1063/1.5117707 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
fmlopes@uevora.pt rfc@uevora.pt hgsilva@uevora.pt rsal@uevora.pt canhoto@uevora.pt collarespereira@uevora.pt 390 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
AIP Conference Proceedings 2126, 190010 (2019) |
publisher.none.fl_str_mv |
AIP Conference Proceedings 2126, 190010 (2019) |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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