Estimation of photovoltaic potential on residential rooftops using empirical Bayesian estimator

Detalhes bibliográficos
Autor(a) principal: Villavicencio, J. [UNESP]
Data de Publicação: 2016
Outros Autores: Melo, J. D. [UNESP], Feltrin, A. Padilha [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/ISGT-LA.2015.7381161
http://hdl.handle.net/11449/168646
Resumo: Assessment of the photovoltaic generation potential on rooftops residential homes is performed by the calculation of the available areas for the installation of solar panels. However, socioeconomic factors could limit this installation for some people. Thus, this paper presents a methodology to estimate the photovoltaic potential using installation rates subject to the socioeconomic characteristics. The installation rates represent the preferences of the inhabitants to install this energy source and are calculated using global and local empirical Bayesian estimators. The result of the proposed methodology is a thematic map that allows the visualization of the spatial distribution of installation rates to identify regions with higher preference values, consequently, location of the greater photovoltaic electricity generation potential.
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spelling Estimation of photovoltaic potential on residential rooftops using empirical Bayesian estimatorelectrical distribution systemsEmpirical Bayesian estimatorsphotovoltaic systemsAssessment of the photovoltaic generation potential on rooftops residential homes is performed by the calculation of the available areas for the installation of solar panels. However, socioeconomic factors could limit this installation for some people. Thus, this paper presents a methodology to estimate the photovoltaic potential using installation rates subject to the socioeconomic characteristics. The installation rates represent the preferences of the inhabitants to install this energy source and are calculated using global and local empirical Bayesian estimators. The result of the proposed methodology is a thematic map that allows the visualization of the spatial distribution of installation rates to identify regions with higher preference values, consequently, location of the greater photovoltaic electricity generation potential.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Departamento de Engenharia Elétrica Universidade Estadual Paulista - UNESPDepartamento de Engenharia Elétrica Universidade Estadual Paulista - UNESPFAPESP: 2014/06629-0CNPq: 303817/2012-7CNPq: 444743/2014-6Universidade Estadual Paulista (Unesp)Villavicencio, J. [UNESP]Melo, J. D. [UNESP]Feltrin, A. Padilha [UNESP]2018-12-11T16:42:20Z2018-12-11T16:42:20Z2016-01-12info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject242-247http://dx.doi.org/10.1109/ISGT-LA.2015.73811612015 IEEE PES Innovative Smart Grid Technologies Latin America, ISGT LATAM 2015, p. 242-247.http://hdl.handle.net/11449/16864610.1109/ISGT-LA.2015.73811612-s2.0-84966649868Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2015 IEEE PES Innovative Smart Grid Technologies Latin America, ISGT LATAM 2015info:eu-repo/semantics/openAccess2021-10-23T21:47:02Zoai:repositorio.unesp.br:11449/168646Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:54:26.126462Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Estimation of photovoltaic potential on residential rooftops using empirical Bayesian estimator
title Estimation of photovoltaic potential on residential rooftops using empirical Bayesian estimator
spellingShingle Estimation of photovoltaic potential on residential rooftops using empirical Bayesian estimator
Villavicencio, J. [UNESP]
electrical distribution systems
Empirical Bayesian estimators
photovoltaic systems
title_short Estimation of photovoltaic potential on residential rooftops using empirical Bayesian estimator
title_full Estimation of photovoltaic potential on residential rooftops using empirical Bayesian estimator
title_fullStr Estimation of photovoltaic potential on residential rooftops using empirical Bayesian estimator
title_full_unstemmed Estimation of photovoltaic potential on residential rooftops using empirical Bayesian estimator
title_sort Estimation of photovoltaic potential on residential rooftops using empirical Bayesian estimator
author Villavicencio, J. [UNESP]
author_facet Villavicencio, J. [UNESP]
Melo, J. D. [UNESP]
Feltrin, A. Padilha [UNESP]
author_role author
author2 Melo, J. D. [UNESP]
Feltrin, A. Padilha [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Villavicencio, J. [UNESP]
Melo, J. D. [UNESP]
Feltrin, A. Padilha [UNESP]
dc.subject.por.fl_str_mv electrical distribution systems
Empirical Bayesian estimators
photovoltaic systems
topic electrical distribution systems
Empirical Bayesian estimators
photovoltaic systems
description Assessment of the photovoltaic generation potential on rooftops residential homes is performed by the calculation of the available areas for the installation of solar panels. However, socioeconomic factors could limit this installation for some people. Thus, this paper presents a methodology to estimate the photovoltaic potential using installation rates subject to the socioeconomic characteristics. The installation rates represent the preferences of the inhabitants to install this energy source and are calculated using global and local empirical Bayesian estimators. The result of the proposed methodology is a thematic map that allows the visualization of the spatial distribution of installation rates to identify regions with higher preference values, consequently, location of the greater photovoltaic electricity generation potential.
publishDate 2016
dc.date.none.fl_str_mv 2016-01-12
2018-12-11T16:42:20Z
2018-12-11T16:42:20Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/ISGT-LA.2015.7381161
2015 IEEE PES Innovative Smart Grid Technologies Latin America, ISGT LATAM 2015, p. 242-247.
http://hdl.handle.net/11449/168646
10.1109/ISGT-LA.2015.7381161
2-s2.0-84966649868
url http://dx.doi.org/10.1109/ISGT-LA.2015.7381161
http://hdl.handle.net/11449/168646
identifier_str_mv 2015 IEEE PES Innovative Smart Grid Technologies Latin America, ISGT LATAM 2015, p. 242-247.
10.1109/ISGT-LA.2015.7381161
2-s2.0-84966649868
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2015 IEEE PES Innovative Smart Grid Technologies Latin America, ISGT LATAM 2015
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 242-247
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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