Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programs

Detalhes bibliográficos
Autor(a) principal: Mejia, Mario A. [UNESP]
Data de Publicação: 2020
Outros Autores: Melo, Joel D., Zambrano-Asanza, Sergio [UNESP], Padilha-Feltrin, Antonio [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.energy.2019.116531
http://hdl.handle.net/11449/201369
Resumo: Domestic energy policies destined to foster the use of end-use electric technologies could cause rapid penetration of new residential loads and, consequently, this could cause a significant increase in the demand for electricity in urban areas. This paper presents a spatial-temporal growth model for estimating the adoption of new end-use electric technologies encouraged by energy-efficiency policies. The proposed method consists of three modules: temporal, spatial and grouping. The temporal module calculates by districts or census tracts of a city, the percentage of homes in which residents are prospective buyers of a new end-use electric technology. Then, the spatial module adjusts the calculations made by the temporal module, considering the spatial interactions among the inhabitants of the districts. Finally, the grouping module discovers the low-voltage transformer where the prospective buyers are connected. The results of the proposed model are a spatial database with information related to the percentage of homes in which residents are prospective buyers of a new end-use electric technology, as well as the number of prospective buyers connected to each low-voltage transformer. The results can visualize through thematic maps to identify the districts where the new technology will have faster adoption. The proposed method was employed to estimate the adoption of induction heating cookers in a medium-sized Ecuadorian city. The Ecuadorian government has developed a program of economic subsidies to encourage its population to use this electrical appliance. The results from this application are an important tool to estimate the spatial increase in electricity demand, decide important issues related to the planning of distributed resources, and develop demand-side management programs. Furthermore, the results can be used to evaluate and manage energy policies formulated to achieve environmental and energy goals.
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spelling Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programsAnd spatial-temporal estimationGeographic information systemGeographically weighted regressionLogistic growth modelNew end-use electric technologies adoptionDomestic energy policies destined to foster the use of end-use electric technologies could cause rapid penetration of new residential loads and, consequently, this could cause a significant increase in the demand for electricity in urban areas. This paper presents a spatial-temporal growth model for estimating the adoption of new end-use electric technologies encouraged by energy-efficiency policies. The proposed method consists of three modules: temporal, spatial and grouping. The temporal module calculates by districts or census tracts of a city, the percentage of homes in which residents are prospective buyers of a new end-use electric technology. Then, the spatial module adjusts the calculations made by the temporal module, considering the spatial interactions among the inhabitants of the districts. Finally, the grouping module discovers the low-voltage transformer where the prospective buyers are connected. The results of the proposed model are a spatial database with information related to the percentage of homes in which residents are prospective buyers of a new end-use electric technology, as well as the number of prospective buyers connected to each low-voltage transformer. The results can visualize through thematic maps to identify the districts where the new technology will have faster adoption. The proposed method was employed to estimate the adoption of induction heating cookers in a medium-sized Ecuadorian city. The Ecuadorian government has developed a program of economic subsidies to encourage its population to use this electrical appliance. The results from this application are an important tool to estimate the spatial increase in electricity demand, decide important issues related to the planning of distributed resources, and develop demand-side management programs. Furthermore, the results can be used to evaluate and manage energy policies formulated to achieve environmental and energy goals.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)Department of Electrical Engineering São Paulo State University – UNESPThe Engineering Modeling and Applied Social Sciences Center the Federal University of ABC–UFABCElectric Power Distribution Utility - CENTROSURDepartment of Electrical Engineering São Paulo State University – UNESPFAPESP: 141985/2017-8FAPESP: 2015/21972-6FAPESP: 2017/22577-9FAPESP: 2019/00466-6;CNPq: 307281/2016-7FAPESP: 422044/2018-0Universidade Estadual Paulista (Unesp)Universidade Federal do ABC (UFABC)Electric Power Distribution Utility - CENTROSURMejia, Mario A. [UNESP]Melo, Joel D.Zambrano-Asanza, Sergio [UNESP]Padilha-Feltrin, Antonio [UNESP]2020-12-12T02:30:47Z2020-12-12T02:30:47Z2020-01-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.energy.2019.116531Energy, v. 191.0360-5442http://hdl.handle.net/11449/20136910.1016/j.energy.2019.1165312-s2.0-85075859497Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEnergyinfo:eu-repo/semantics/openAccess2024-07-04T19:06:36Zoai:repositorio.unesp.br:11449/201369Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:20:11.021397Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programs
title Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programs
spellingShingle Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programs
Mejia, Mario A. [UNESP]
And spatial-temporal estimation
Geographic information system
Geographically weighted regression
Logistic growth model
New end-use electric technologies adoption
title_short Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programs
title_full Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programs
title_fullStr Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programs
title_full_unstemmed Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programs
title_sort Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programs
author Mejia, Mario A. [UNESP]
author_facet Mejia, Mario A. [UNESP]
Melo, Joel D.
Zambrano-Asanza, Sergio [UNESP]
Padilha-Feltrin, Antonio [UNESP]
author_role author
author2 Melo, Joel D.
Zambrano-Asanza, Sergio [UNESP]
Padilha-Feltrin, Antonio [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Universidade Federal do ABC (UFABC)
Electric Power Distribution Utility - CENTROSUR
dc.contributor.author.fl_str_mv Mejia, Mario A. [UNESP]
Melo, Joel D.
Zambrano-Asanza, Sergio [UNESP]
Padilha-Feltrin, Antonio [UNESP]
dc.subject.por.fl_str_mv And spatial-temporal estimation
Geographic information system
Geographically weighted regression
Logistic growth model
New end-use electric technologies adoption
topic And spatial-temporal estimation
Geographic information system
Geographically weighted regression
Logistic growth model
New end-use electric technologies adoption
description Domestic energy policies destined to foster the use of end-use electric technologies could cause rapid penetration of new residential loads and, consequently, this could cause a significant increase in the demand for electricity in urban areas. This paper presents a spatial-temporal growth model for estimating the adoption of new end-use electric technologies encouraged by energy-efficiency policies. The proposed method consists of three modules: temporal, spatial and grouping. The temporal module calculates by districts or census tracts of a city, the percentage of homes in which residents are prospective buyers of a new end-use electric technology. Then, the spatial module adjusts the calculations made by the temporal module, considering the spatial interactions among the inhabitants of the districts. Finally, the grouping module discovers the low-voltage transformer where the prospective buyers are connected. The results of the proposed model are a spatial database with information related to the percentage of homes in which residents are prospective buyers of a new end-use electric technology, as well as the number of prospective buyers connected to each low-voltage transformer. The results can visualize through thematic maps to identify the districts where the new technology will have faster adoption. The proposed method was employed to estimate the adoption of induction heating cookers in a medium-sized Ecuadorian city. The Ecuadorian government has developed a program of economic subsidies to encourage its population to use this electrical appliance. The results from this application are an important tool to estimate the spatial increase in electricity demand, decide important issues related to the planning of distributed resources, and develop demand-side management programs. Furthermore, the results can be used to evaluate and manage energy policies formulated to achieve environmental and energy goals.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-12T02:30:47Z
2020-12-12T02:30:47Z
2020-01-15
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.energy.2019.116531
Energy, v. 191.
0360-5442
http://hdl.handle.net/11449/201369
10.1016/j.energy.2019.116531
2-s2.0-85075859497
url http://dx.doi.org/10.1016/j.energy.2019.116531
http://hdl.handle.net/11449/201369
identifier_str_mv Energy, v. 191.
0360-5442
10.1016/j.energy.2019.116531
2-s2.0-85075859497
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Energy
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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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