A new predictive model for a photovoltaic module's surface temperature
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.egyr.2022.11.094 http://hdl.handle.net/11449/247908 |
Resumo: | The current study developed an analytical model to predict the PV module's operating temperature based on an experimental database, which considers cell temperature, local meteorological data (irradiance, ambient temperature, wind velocity, and humidity), voltage, and current generated by the photovoltaic system associated with the purely resistive load. Based on the analysis of the 172-day database, it was possible to compare the most used correlations in the literature with the analytical model developed in the current work. For all conditions, the model showed a better response to climate variation – with 100% of the data within an error band of ± 20% and an absolute mean percentage error of 3.1% – predicting well the PV module's operating temperature for both sky conditions (clear or cloudy) and demonstrated that the thermal capacity of the PV module to climatic variations should not be neglected. Moreover, the new model considered the PV module's thermal response capacity to include the variations in the incident solar irradiance caused by the presence of clouds (shading effect). By considering a global heat capacity as a mean value of the heat capacities of the layers of the PV module, the term transient – generally neglected in several works – is considered in the energy equation in the current work, which gives a better response to the variations in the incident radiation. |
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A new predictive model for a photovoltaic module's surface temperatureEnvironmental effectOperating temperaturePhotovoltaic solar energyPredictive modelsThermal capacityThe current study developed an analytical model to predict the PV module's operating temperature based on an experimental database, which considers cell temperature, local meteorological data (irradiance, ambient temperature, wind velocity, and humidity), voltage, and current generated by the photovoltaic system associated with the purely resistive load. Based on the analysis of the 172-day database, it was possible to compare the most used correlations in the literature with the analytical model developed in the current work. For all conditions, the model showed a better response to climate variation – with 100% of the data within an error band of ± 20% and an absolute mean percentage error of 3.1% – predicting well the PV module's operating temperature for both sky conditions (clear or cloudy) and demonstrated that the thermal capacity of the PV module to climatic variations should not be neglected. Moreover, the new model considered the PV module's thermal response capacity to include the variations in the incident solar irradiance caused by the presence of clouds (shading effect). By considering a global heat capacity as a mean value of the heat capacities of the layers of the PV module, the term transient – generally neglected in several works – is considered in the energy equation in the current work, which gives a better response to the variations in the incident radiation.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)UNESP - São Paulo State University School of Engineering Post-Graduation Program in Mechanical Engineering, Av. Brasil, 56, Ilha SolteiraMetrics Mechanical Engineering Department University of Minho, Campus de AzurémFSG - University Center Center of Innovation and Technology Department of Mechanical Engineering, Os Dezoito do Forte, 2366UNESP - São Paulo State University School of EngineeringUNESP - São Paulo State University School of Engineering Post-Graduation Program in Mechanical Engineering, Av. Brasil, 56, Ilha SolteiraUNESP - São Paulo State University School of EngineeringFAPESP: 2013/15431-7FAPESP: 2019/02566-8FAPESP: 2021/08818-9CNPq: 309848/2020-2CNPq: 458702/2014-5Universidade Estadual Paulista (UNESP)University of MinhoCenter of Innovation and TechnologySilva, Domisley Dutra [UNESP]Marson, Vinicius [UNESP]de Souza, Reinaldo Rodriguesde Oliveira, Jeferson DiehlSilva, João Batista Campos [UNESP]Cardoso, Elaine Maria [UNESP]2023-07-29T13:29:10Z2023-07-29T13:29:10Z2022-11-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article15206-15220http://dx.doi.org/10.1016/j.egyr.2022.11.094Energy Reports, v. 8, p. 15206-15220.2352-4847http://hdl.handle.net/11449/24790810.1016/j.egyr.2022.11.0942-s2.0-85142193141Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEnergy Reportsinfo:eu-repo/semantics/openAccess2024-07-04T20:06:24Zoai:repositorio.unesp.br:11449/247908Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:56:02.665036Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
A new predictive model for a photovoltaic module's surface temperature |
title |
A new predictive model for a photovoltaic module's surface temperature |
spellingShingle |
A new predictive model for a photovoltaic module's surface temperature Silva, Domisley Dutra [UNESP] Environmental effect Operating temperature Photovoltaic solar energy Predictive models Thermal capacity |
title_short |
A new predictive model for a photovoltaic module's surface temperature |
title_full |
A new predictive model for a photovoltaic module's surface temperature |
title_fullStr |
A new predictive model for a photovoltaic module's surface temperature |
title_full_unstemmed |
A new predictive model for a photovoltaic module's surface temperature |
title_sort |
A new predictive model for a photovoltaic module's surface temperature |
author |
Silva, Domisley Dutra [UNESP] |
author_facet |
Silva, Domisley Dutra [UNESP] Marson, Vinicius [UNESP] de Souza, Reinaldo Rodrigues de Oliveira, Jeferson Diehl Silva, João Batista Campos [UNESP] Cardoso, Elaine Maria [UNESP] |
author_role |
author |
author2 |
Marson, Vinicius [UNESP] de Souza, Reinaldo Rodrigues de Oliveira, Jeferson Diehl Silva, João Batista Campos [UNESP] Cardoso, Elaine Maria [UNESP] |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) University of Minho Center of Innovation and Technology |
dc.contributor.author.fl_str_mv |
Silva, Domisley Dutra [UNESP] Marson, Vinicius [UNESP] de Souza, Reinaldo Rodrigues de Oliveira, Jeferson Diehl Silva, João Batista Campos [UNESP] Cardoso, Elaine Maria [UNESP] |
dc.subject.por.fl_str_mv |
Environmental effect Operating temperature Photovoltaic solar energy Predictive models Thermal capacity |
topic |
Environmental effect Operating temperature Photovoltaic solar energy Predictive models Thermal capacity |
description |
The current study developed an analytical model to predict the PV module's operating temperature based on an experimental database, which considers cell temperature, local meteorological data (irradiance, ambient temperature, wind velocity, and humidity), voltage, and current generated by the photovoltaic system associated with the purely resistive load. Based on the analysis of the 172-day database, it was possible to compare the most used correlations in the literature with the analytical model developed in the current work. For all conditions, the model showed a better response to climate variation – with 100% of the data within an error band of ± 20% and an absolute mean percentage error of 3.1% – predicting well the PV module's operating temperature for both sky conditions (clear or cloudy) and demonstrated that the thermal capacity of the PV module to climatic variations should not be neglected. Moreover, the new model considered the PV module's thermal response capacity to include the variations in the incident solar irradiance caused by the presence of clouds (shading effect). By considering a global heat capacity as a mean value of the heat capacities of the layers of the PV module, the term transient – generally neglected in several works – is considered in the energy equation in the current work, which gives a better response to the variations in the incident radiation. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-11-01 2023-07-29T13:29:10Z 2023-07-29T13:29:10Z |
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://dx.doi.org/10.1016/j.egyr.2022.11.094 Energy Reports, v. 8, p. 15206-15220. 2352-4847 http://hdl.handle.net/11449/247908 10.1016/j.egyr.2022.11.094 2-s2.0-85142193141 |
url |
http://dx.doi.org/10.1016/j.egyr.2022.11.094 http://hdl.handle.net/11449/247908 |
identifier_str_mv |
Energy Reports, v. 8, p. 15206-15220. 2352-4847 10.1016/j.egyr.2022.11.094 2-s2.0-85142193141 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Energy Reports |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
15206-15220 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
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1808129374966251520 |