Predictive Value of Short-term Forecasts of DNI for Solar Energy Systems Operation
Autor(a) principal: | |
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Data de Publicação: | 2018 |
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/10174/24014 |
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 under clear-sky conditions during partly cloudy days. 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 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 the improvement of the operationalization 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 the lower correlations obtained for hourly values (~0.89) are due to cloud representation of the IFS during overcast periods, leading to small deviations with respect to those from measurements. Moreover, as means to measure the forecasting skill of the IFS, daily and hourly skill scores based on local measurements and a persistence model are obtained (0.67 and 0.53, 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 OperationShort-term ForecastsDirect Normal IrradianceCSPIntegrated Forecasting SystemSystem Advisor ModelNWPSolar 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 under clear-sky conditions during partly cloudy days. 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 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 the improvement of the operationalization 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 the lower correlations obtained for hourly values (~0.89) are due to cloud representation of the IFS during overcast periods, leading to small deviations with respect to those from measurements. Moreover, as means to measure the forecasting skill of the IFS, daily and hourly skill scores based on local measurements and a persistence model are obtained (0.67 and 0.53, 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.This work was co-funded by the European Union through the European Regional Development Fund, framed in COMPETE 2020 (Operational Program Competitiveness and Internationalization), through the Institute of Earth Sciences (UID/GEO/04683/2013) with reference POCI-01-0145-FEDER-007690, and through the projects DNI-A (ALT20-03-0145-FEDER-000011), ALOP (ALT20-03-0145-FEDER-000004) and INSHIP (H2020, grant agreement 731287). The initial recommendations of T. Fasquelle, P. Gilman (SAM Support) and R. Hogan, is recognized and appreciated. The authors are also thankful for the availability of the ECMWF and the Portuguese Meteorological Service (IPMA) in providing data. F. M. Lopes is thankful for the FCT scholarship (SFRH/BD/129580/2017), R. Conceição to the FCT scholarship (SFRH/BD/116344/2016), and H. G. Silva to DNI-A and INSHIP for his research contract.SolarPACES 2018 proceedings2019-01-14T13:14:36Z2019-01-142018-10-05T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/24014http://hdl.handle.net/10174/24014engLopes, FM, Conceição, R, Silva, HG, Salgado, R, Canhoto, P, Collares-Pereira, M. Predictive Value of Short-term Forecasts of DNI for Solar Energy Systems Operation. SolarPACES 2018 Conference Proceedings. 02-05 October 2018, Casablanca, Morocco.https://www.researchgate.net/publication/327646146_Predictive_value_of_short-term_forecasts_of_DNI_for_solar_energy_systems_operationfmlopes@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:RCAAP2024-01-03T19:16:39Zoai:dspace.uevora.pt:10174/24014Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:14:45.111787Repositório 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 Short-term Forecasts Direct Normal Irradiance CSP Integrated Forecasting System System Advisor Model NWP |
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 |
dc.subject.por.fl_str_mv |
Short-term Forecasts Direct Normal Irradiance CSP Integrated Forecasting System System Advisor Model NWP |
topic |
Short-term Forecasts Direct Normal Irradiance CSP Integrated Forecasting System System Advisor Model NWP |
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 under clear-sky conditions during partly cloudy days. 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 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 the improvement of the operationalization 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 the lower correlations obtained for hourly values (~0.89) are due to cloud representation of the IFS during overcast periods, leading to small deviations with respect to those from measurements. Moreover, as means to measure the forecasting skill of the IFS, daily and hourly skill scores based on local measurements and a persistence model are obtained (0.67 and 0.53, 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 |
2018 |
dc.date.none.fl_str_mv |
2018-10-05T00:00:00Z 2019-01-14T13:14:36Z 2019-01-14 |
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/10174/24014 http://hdl.handle.net/10174/24014 |
url |
http://hdl.handle.net/10174/24014 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Lopes, FM, Conceição, R, Silva, HG, Salgado, R, Canhoto, P, Collares-Pereira, M. Predictive Value of Short-term Forecasts of DNI for Solar Energy Systems Operation. SolarPACES 2018 Conference Proceedings. 02-05 October 2018, Casablanca, Morocco. https://www.researchgate.net/publication/327646146_Predictive_value_of_short-term_forecasts_of_DNI_for_solar_energy_systems_operation 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 |
SolarPACES 2018 proceedings |
publisher.none.fl_str_mv |
SolarPACES 2018 proceedings |
dc.source.none.fl_str_mv |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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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) |
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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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