Spatial-Temporal Model for Demand Estimation Due to Appliances with High Energy Consumption
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/185112 |
Resumo: | The residential load of existing consumers can be increased significantly due to large-scale purchase of household appliances with high-energy consumption; consequently, changing the expansion plans of electrical distribution networks. In this paper, a spatial-temporal model is proposed to estimate the load growth of distribution transformers owed for this kind of electrical appliances. In order to determine the location of inhabitants interested in buying these appliances, the proposed approach includes the socioeconomic characteristics of the consumers in a spatial form. After that, the number of appliances added each year is computed using a logistic regression. The results are the residential load curves of distribution transformers, including the additional yearly demand of the new appliances. These curves provide valuable information regarding the distribution network expansion planning. |
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Spatial-Temporal Model for Demand Estimation Due to Appliances with High Energy Consumptiondistribution network expansion planninggeographic information systemspatial-temporal estimationThe residential load of existing consumers can be increased significantly due to large-scale purchase of household appliances with high-energy consumption; consequently, changing the expansion plans of electrical distribution networks. In this paper, a spatial-temporal model is proposed to estimate the load growth of distribution transformers owed for this kind of electrical appliances. In order to determine the location of inhabitants interested in buying these appliances, the proposed approach includes the socioeconomic characteristics of the consumers in a spatial form. After that, the number of appliances added each year is computed using a logistic regression. The results are the residential load curves of distribution transformers, including the additional yearly demand of the new appliances. These curves provide valuable information regarding the distribution network expansion planning.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Sao Paulo State Univ, UNESP, Dept Elect Engn, Ilha Solteira, BrazilUniv Fed Abc, Fed Univ ABC, Engn Modeling & Appl Social Sci Ctr, CECS, Santo Andre, BrazilCtr Distribut Util, Dept Planning, Cuenca, EcuadorSao Paulo State Univ, UNESP, Dept Elect Engn, Ilha Solteira, BrazilCNPq: 444743/2014-6CNPq: 307281/2016-7FAPESP: 2015/21972-6FAPESP: 2017/01909-3IeeeUniversidade Estadual Paulista (Unesp)Universidade Federal do ABC (UFABC)Ctr Distribut UtilMejia, M. A. [UNESP]Padilha-Feltrin, A. [UNESP]Melo, J. D.Zambrano-Asanza, S.IEEE2019-10-04T12:32:44Z2019-10-04T12:32:44Z2017-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject62017 Ieee Pes Innovative Smart Grid Technologies Conference - Latin America (isgt Latin America). New York: Ieee, 6 p., 2017.http://hdl.handle.net/11449/185112WOS:000451380200039Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2017 Ieee Pes Innovative Smart Grid Technologies Conference - Latin America (isgt Latin America)info:eu-repo/semantics/openAccess2024-07-04T19:11:39Zoai:repositorio.unesp.br:11449/185112Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:10:45.181248Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Spatial-Temporal Model for Demand Estimation Due to Appliances with High Energy Consumption |
title |
Spatial-Temporal Model for Demand Estimation Due to Appliances with High Energy Consumption |
spellingShingle |
Spatial-Temporal Model for Demand Estimation Due to Appliances with High Energy Consumption Mejia, M. A. [UNESP] distribution network expansion planning geographic information system spatial-temporal estimation |
title_short |
Spatial-Temporal Model for Demand Estimation Due to Appliances with High Energy Consumption |
title_full |
Spatial-Temporal Model for Demand Estimation Due to Appliances with High Energy Consumption |
title_fullStr |
Spatial-Temporal Model for Demand Estimation Due to Appliances with High Energy Consumption |
title_full_unstemmed |
Spatial-Temporal Model for Demand Estimation Due to Appliances with High Energy Consumption |
title_sort |
Spatial-Temporal Model for Demand Estimation Due to Appliances with High Energy Consumption |
author |
Mejia, M. A. [UNESP] |
author_facet |
Mejia, M. A. [UNESP] Padilha-Feltrin, A. [UNESP] Melo, J. D. Zambrano-Asanza, S. IEEE |
author_role |
author |
author2 |
Padilha-Feltrin, A. [UNESP] Melo, J. D. Zambrano-Asanza, S. IEEE |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Universidade Federal do ABC (UFABC) Ctr Distribut Util |
dc.contributor.author.fl_str_mv |
Mejia, M. A. [UNESP] Padilha-Feltrin, A. [UNESP] Melo, J. D. Zambrano-Asanza, S. IEEE |
dc.subject.por.fl_str_mv |
distribution network expansion planning geographic information system spatial-temporal estimation |
topic |
distribution network expansion planning geographic information system spatial-temporal estimation |
description |
The residential load of existing consumers can be increased significantly due to large-scale purchase of household appliances with high-energy consumption; consequently, changing the expansion plans of electrical distribution networks. In this paper, a spatial-temporal model is proposed to estimate the load growth of distribution transformers owed for this kind of electrical appliances. In order to determine the location of inhabitants interested in buying these appliances, the proposed approach includes the socioeconomic characteristics of the consumers in a spatial form. After that, the number of appliances added each year is computed using a logistic regression. The results are the residential load curves of distribution transformers, including the additional yearly demand of the new appliances. These curves provide valuable information regarding the distribution network expansion planning. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01-01 2019-10-04T12:32:44Z 2019-10-04T12:32:44Z |
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 |
2017 Ieee Pes Innovative Smart Grid Technologies Conference - Latin America (isgt Latin America). New York: Ieee, 6 p., 2017. http://hdl.handle.net/11449/185112 WOS:000451380200039 |
identifier_str_mv |
2017 Ieee Pes Innovative Smart Grid Technologies Conference - Latin America (isgt Latin America). New York: Ieee, 6 p., 2017. WOS:000451380200039 |
url |
http://hdl.handle.net/11449/185112 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2017 Ieee Pes Innovative Smart Grid Technologies Conference - Latin America (isgt Latin America) |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
6 |
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_ |
1808129029205655552 |