Spatio-Temporal Model to Estimate the Adoption of Rooftop Solar Photovoltaic Systems

Detalhes bibliográficos
Autor(a) principal: Morales, R. E.
Data de Publicação: 2022
Outros Autores: Zambrano-Asanza, S. [UNESP], Rios, Alberto, Gonzalez-Redrovan, J.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/245169
Resumo: The trend for renewable energies has motivated residential consumers around the world to have a rapid penetration in the installation of rooftop solar photovoltaic systems. For this reason, power utility companies must plan the inclusion of rooftop solar photovoltaic systems in their distribution grid. The proposed method projects the quantity and location of these systems. The method is divided into 3 modules: temporal, spatial, and potential modules. In the case of the temporal module, it uses census data by dividing the area into districts, and also, it calculates the number of residential customers, which can be converted into rooftop solar photovoltaic systems. On the other hand, the spatial module adjusts the temporal module based on the interaction and spatial influence of neighbours for each district. Finally, the potential module calculates their energy potential according to the geographical location of the districts and evaluates it with the forecast number of customers from the spatial module. The performance of the method is assessed in the service area of an Ecuadorian power utility. The results show that in Cuenca the greatest influence on adoption is given by two variables, the number of heads of households with permanent employment and the district's electrical power. The customers and energy results produced represent for each scenario only the 7% and 9% of the energy demanded, this concentration is shown through thematic maps that allow identifying the districts that have rapid adoption of solar panels. The results are important tools for the planning of the distribution company, the company will have the areas of highest rooftop solar photovoltaic systems penetration to evaluate its distribution system and maintain its reliability levels.
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spelling Spatio-Temporal Model to Estimate the Adoption of Rooftop Solar Photovoltaic Systemsspatial-temporallogistic growth modelgeographically weighted regressionsolar potentialsolar panelThe trend for renewable energies has motivated residential consumers around the world to have a rapid penetration in the installation of rooftop solar photovoltaic systems. For this reason, power utility companies must plan the inclusion of rooftop solar photovoltaic systems in their distribution grid. The proposed method projects the quantity and location of these systems. The method is divided into 3 modules: temporal, spatial, and potential modules. In the case of the temporal module, it uses census data by dividing the area into districts, and also, it calculates the number of residential customers, which can be converted into rooftop solar photovoltaic systems. On the other hand, the spatial module adjusts the temporal module based on the interaction and spatial influence of neighbours for each district. Finally, the potential module calculates their energy potential according to the geographical location of the districts and evaluates it with the forecast number of customers from the spatial module. The performance of the method is assessed in the service area of an Ecuadorian power utility. The results show that in Cuenca the greatest influence on adoption is given by two variables, the number of heads of households with permanent employment and the district's electrical power. The customers and energy results produced represent for each scenario only the 7% and 9% of the energy demanded, this concentration is shown through thematic maps that allow identifying the districts that have rapid adoption of solar panels. The results are important tools for the planning of the distribution company, the company will have the areas of highest rooftop solar photovoltaic systems penetration to evaluate its distribution system and maintain its reliability levels.Catholic Univ Cuenca, Acad Unit Posgrate Masters Program Renewable Ener, Cuenca 010101, EcuadorSao Paulo State Univ UNESP, Dept Elect Engn, BR-13506752 Sao Paulo, BrazilTech Univ Ambato, Fac Syst Elect & Ind Engn, Ambato 180104, EcuadorSao Paulo State Univ UNESP, Dept Elect Engn, BR-13506752 Sao Paulo, BrazilInt Journal Renewable Energy ResearchCatholic Univ CuencaUniversidade Estadual Paulista (UNESP)Tech Univ AmbatoMorales, R. E.Zambrano-Asanza, S. [UNESP]Rios, AlbertoGonzalez-Redrovan, J.2023-07-29T11:39:05Z2023-07-29T11:39:05Z2022-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1837-1845International Journal of Renewable Energy Research. Ankara: Int Journal Renewable Energy Research, v. 12, n. 4, p. 1837-1845, 2022.http://hdl.handle.net/11449/245169WOS:000904604700015Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Journal Of Renewable Energy Researchinfo:eu-repo/semantics/openAccess2023-07-29T11:39:05Zoai:repositorio.unesp.br:11449/245169Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-07-29T11:39:05Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Spatio-Temporal Model to Estimate the Adoption of Rooftop Solar Photovoltaic Systems
title Spatio-Temporal Model to Estimate the Adoption of Rooftop Solar Photovoltaic Systems
spellingShingle Spatio-Temporal Model to Estimate the Adoption of Rooftop Solar Photovoltaic Systems
Morales, R. E.
spatial-temporal
logistic growth model
geographically weighted regression
solar potential
solar panel
title_short Spatio-Temporal Model to Estimate the Adoption of Rooftop Solar Photovoltaic Systems
title_full Spatio-Temporal Model to Estimate the Adoption of Rooftop Solar Photovoltaic Systems
title_fullStr Spatio-Temporal Model to Estimate the Adoption of Rooftop Solar Photovoltaic Systems
title_full_unstemmed Spatio-Temporal Model to Estimate the Adoption of Rooftop Solar Photovoltaic Systems
title_sort Spatio-Temporal Model to Estimate the Adoption of Rooftop Solar Photovoltaic Systems
author Morales, R. E.
author_facet Morales, R. E.
Zambrano-Asanza, S. [UNESP]
Rios, Alberto
Gonzalez-Redrovan, J.
author_role author
author2 Zambrano-Asanza, S. [UNESP]
Rios, Alberto
Gonzalez-Redrovan, J.
author2_role author
author
author
dc.contributor.none.fl_str_mv Catholic Univ Cuenca
Universidade Estadual Paulista (UNESP)
Tech Univ Ambato
dc.contributor.author.fl_str_mv Morales, R. E.
Zambrano-Asanza, S. [UNESP]
Rios, Alberto
Gonzalez-Redrovan, J.
dc.subject.por.fl_str_mv spatial-temporal
logistic growth model
geographically weighted regression
solar potential
solar panel
topic spatial-temporal
logistic growth model
geographically weighted regression
solar potential
solar panel
description The trend for renewable energies has motivated residential consumers around the world to have a rapid penetration in the installation of rooftop solar photovoltaic systems. For this reason, power utility companies must plan the inclusion of rooftop solar photovoltaic systems in their distribution grid. The proposed method projects the quantity and location of these systems. The method is divided into 3 modules: temporal, spatial, and potential modules. In the case of the temporal module, it uses census data by dividing the area into districts, and also, it calculates the number of residential customers, which can be converted into rooftop solar photovoltaic systems. On the other hand, the spatial module adjusts the temporal module based on the interaction and spatial influence of neighbours for each district. Finally, the potential module calculates their energy potential according to the geographical location of the districts and evaluates it with the forecast number of customers from the spatial module. The performance of the method is assessed in the service area of an Ecuadorian power utility. The results show that in Cuenca the greatest influence on adoption is given by two variables, the number of heads of households with permanent employment and the district's electrical power. The customers and energy results produced represent for each scenario only the 7% and 9% of the energy demanded, this concentration is shown through thematic maps that allow identifying the districts that have rapid adoption of solar panels. The results are important tools for the planning of the distribution company, the company will have the areas of highest rooftop solar photovoltaic systems penetration to evaluate its distribution system and maintain its reliability levels.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-01
2023-07-29T11:39:05Z
2023-07-29T11:39:05Z
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 International Journal of Renewable Energy Research. Ankara: Int Journal Renewable Energy Research, v. 12, n. 4, p. 1837-1845, 2022.
http://hdl.handle.net/11449/245169
WOS:000904604700015
identifier_str_mv International Journal of Renewable Energy Research. Ankara: Int Journal Renewable Energy Research, v. 12, n. 4, p. 1837-1845, 2022.
WOS:000904604700015
url http://hdl.handle.net/11449/245169
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv International Journal Of Renewable Energy Research
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1837-1845
dc.publisher.none.fl_str_mv Int Journal Renewable Energy Research
publisher.none.fl_str_mv Int Journal Renewable Energy Research
dc.source.none.fl_str_mv Web of Science
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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