Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance

A simple yet accurate photovoltaic (PV) performance curve as a function of satellite-based solar irradiation is necessary to develop a PV power forecasting model that can cover all of South Korea, where more than 35,000 PV power plants are currently in operation. In order to express the nonlinear po...

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Autores: Vilanova, Alba, Kim, Bo-Young, Kim, Chang Ki, Kim, Hyun-Goo
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/69859
Acceso en línea:https://doi.org/10.3390/en13040781
http://hdl.handle.net/10459.1/69859
Access Level:acceso abierto
Palabra clave:Photovoltaic system performance
Power output prediction
Satellite-derived global horizontal irradiance
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spelling Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar IrradianceVilanova, AlbaKim, Bo-YoungKim, Chang KiKim, Hyun-GooPhotovoltaic system performancePower output predictionSatellite-derived global horizontal irradianceA simple yet accurate photovoltaic (PV) performance curve as a function of satellite-based solar irradiation is necessary to develop a PV power forecasting model that can cover all of South Korea, where more than 35,000 PV power plants are currently in operation. In order to express the nonlinear power output of the PV module with respect to the hourly global horizontal irradiance derived from satellite images, this study employed the Gompertz model, which is composed of three parameters and the sigmoid equation. The nonphysical behavior of the Gompertz model within the low solar irradiation range was corrected by combining a linear equation with the same gradient at the conjoint point. The overall fitness of Linear-Gompertz regression to the 242 PV power plants representing the country was R2 = 0.85 and nRMSE = 0.09. The Gompertz model coefficients showed normal distributions and equivariance of standard deviations of less than 15% by year and by season. Therefore, it can be conjectured that the Linear-Gompertz model represents the whole country’s PV system performance curve. In addition, the Gompertz coefficient C, which controls the growth rate of the curve, showed a strong correlation with the capacity factor, such that the regression equation for the capacity factor could be derived as a function of the three Gompertz model coefficients with a fitness of R2 = 0.88.This work was conducted under the framework of the Research and Development Program of the Korea Institute of Energy Research (C0-2407).MDPI2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://doi.org/10.3390/en13040781http://hdl.handle.net/10459.1/69859reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)InglésReproducció del document publicat a https://doi.org/10.3390/en13040781Energies, 2020, vol. 13, núm. 4, a781cc-by (c) Vilanova et al., 2020info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:repositori.udl.cat:10459.1/698592026-06-24T12:42:17Z
dc.title.none.fl_str_mv Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance
title Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance
spellingShingle Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance
Vilanova, Alba
Photovoltaic system performance
Power output prediction
Satellite-derived global horizontal irradiance
title_short Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance
title_full Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance
title_fullStr Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance
title_full_unstemmed Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance
title_sort Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance
dc.creator.none.fl_str_mv Vilanova, Alba
Kim, Bo-Young
Kim, Chang Ki
Kim, Hyun-Goo
author Vilanova, Alba
author_facet Vilanova, Alba
Kim, Bo-Young
Kim, Chang Ki
Kim, Hyun-Goo
author_role author
author2 Kim, Bo-Young
Kim, Chang Ki
Kim, Hyun-Goo
author2_role author
author
author
dc.subject.none.fl_str_mv Photovoltaic system performance
Power output prediction
Satellite-derived global horizontal irradiance
topic Photovoltaic system performance
Power output prediction
Satellite-derived global horizontal irradiance
description A simple yet accurate photovoltaic (PV) performance curve as a function of satellite-based solar irradiation is necessary to develop a PV power forecasting model that can cover all of South Korea, where more than 35,000 PV power plants are currently in operation. In order to express the nonlinear power output of the PV module with respect to the hourly global horizontal irradiance derived from satellite images, this study employed the Gompertz model, which is composed of three parameters and the sigmoid equation. The nonphysical behavior of the Gompertz model within the low solar irradiation range was corrected by combining a linear equation with the same gradient at the conjoint point. The overall fitness of Linear-Gompertz regression to the 242 PV power plants representing the country was R2 = 0.85 and nRMSE = 0.09. The Gompertz model coefficients showed normal distributions and equivariance of standard deviations of less than 15% by year and by season. Therefore, it can be conjectured that the Linear-Gompertz model represents the whole country’s PV system performance curve. In addition, the Gompertz coefficient C, which controls the growth rate of the curve, showed a strong correlation with the capacity factor, such that the regression equation for the capacity factor could be derived as a function of the three Gompertz model coefficients with a fitness of R2 = 0.88.
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.3390/en13040781
http://hdl.handle.net/10459.1/69859
url https://doi.org/10.3390/en13040781
http://hdl.handle.net/10459.1/69859
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a https://doi.org/10.3390/en13040781
Energies, 2020, vol. 13, núm. 4, a781
dc.rights.none.fl_str_mv cc-by (c) Vilanova et al., 2020
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv cc-by (c) Vilanova et al., 2020
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Repositori Obert UdL
instname:Universitat de Lleida (UdL)
instname_str Universitat de Lleida (UdL)
reponame_str Repositori Obert UdL
collection Repositori Obert UdL
repository.name.fl_str_mv
repository.mail.fl_str_mv
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