Estimation of Photovoltaic Potential on Residential Rooftops Using Empirical Bayesian Estimator
Autor(a) principal: | |
---|---|
Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/162667 |
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. |
id |
UNSP_3ea465651d0dc90065529a43b5fcb3ec |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/162667 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
Estimation of Photovoltaic Potential on Residential Rooftops Using Empirical Bayesian EstimatorEmpirical Bayesian estimatorsphotovoltaic systemselectrical distribution 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)Univ Estadual Paulista UNESP, Dept Engn Eletr, Ilha Solteira, BrazilUniv Estadual Paulista UNESP, Dept Engn Eletr, Ilha Solteira, BrazilFAPESP: 2014/06629-0CNPq: 303817/2012-7CNPq: 444743/2014-6IeeeUniversidade Estadual Paulista (Unesp)Villavicencio, J. [UNESP]Melo, J. D. [UNESP]Feltrin, A. Padilha [UNESP]IEEE2018-11-26T17:24:23Z2018-11-26T17:24:23Z2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject242-2472015 Ieee Pes Innovative Smart Grid Technologies Latin America (isgt Latam). New York: Ieee, p. 242-247, 2015.http://hdl.handle.net/11449/162667WOS:000398603600044Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2015 Ieee Pes Innovative Smart Grid Technologies Latin America (isgt Latam)info:eu-repo/semantics/openAccess2021-10-23T21:47:02Zoai:repositorio.unesp.br:11449/162667Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T21:47:02Repositório 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] Empirical Bayesian estimators photovoltaic systems electrical distribution 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] IEEE |
author_role |
author |
author2 |
Melo, J. D. [UNESP] Feltrin, A. Padilha [UNESP] IEEE |
author2_role |
author 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] IEEE |
dc.subject.por.fl_str_mv |
Empirical Bayesian estimators photovoltaic systems electrical distribution systems |
topic |
Empirical Bayesian estimators photovoltaic systems electrical distribution 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 |
2015 |
dc.date.none.fl_str_mv |
2015-01-01 2018-11-26T17:24:23Z 2018-11-26T17:24:23Z |
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 |
2015 Ieee Pes Innovative Smart Grid Technologies Latin America (isgt Latam). New York: Ieee, p. 242-247, 2015. http://hdl.handle.net/11449/162667 WOS:000398603600044 |
identifier_str_mv |
2015 Ieee Pes Innovative Smart Grid Technologies Latin America (isgt Latam). New York: Ieee, p. 242-247, 2015. WOS:000398603600044 |
url |
http://hdl.handle.net/11449/162667 |
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) |
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.publisher.none.fl_str_mv |
Ieee |
publisher.none.fl_str_mv |
Ieee |
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 |
|
_version_ |
1803047358132387840 |