Spatial-temporal growth model to estimate the adoption of new end-use electric technologies encouraged by energy-efficiency programs
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , |
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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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 |
|
_version_ |
1808129310352998400 |