Spatial-Temporal Estimation for Nontechnical Losses

Detalhes bibliográficos
Autor(a) principal: Faria, Lucas Teles [UNESP]
Data de Publicação: 2016
Outros Autores: Melo, Joel David [UNESP], Padilha-Feltrin, Antonio [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/TPWRD.2015.2469135
http://hdl.handle.net/11449/172766
Resumo: This paper presents a novel method for estimating the spatial distribution in geographical space of the nontechnical losses over time. The method progresses in two stages: in the first stage, a generalized additive model is used to generate a map of current loss probabilities. The second stage employs the Markov chain to generate a map that indicates possible future changes in loss probabilities. The method yields an assessment of the location of the nontechnical losses now and in the future at the city subarea level, even indicating the variables that have greater statistical correlation with the nontechnical losses. We apply the method to a city with approximately 81 000 consumers, and the results are compared with those obtained through inspections carried out by a Brazilian power utility. The detection rate surpasses 78% in inspected subareas. The method we propose offers improved estimation of distribution of the nontechnical losses in urban regions.
id UNSP_53cbbf985d4fcea8157f09b8033c0cea
oai_identifier_str oai:repositorio.unesp.br:11449/172766
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Spatial-Temporal Estimation for Nontechnical LossesElectricity theftgeneralized additive modelsnontechnical lossesspatial-point pattern analysisThis paper presents a novel method for estimating the spatial distribution in geographical space of the nontechnical losses over time. The method progresses in two stages: in the first stage, a generalized additive model is used to generate a map of current loss probabilities. The second stage employs the Markov chain to generate a map that indicates possible future changes in loss probabilities. The method yields an assessment of the location of the nontechnical losses now and in the future at the city subarea level, even indicating the variables that have greater statistical correlation with the nontechnical losses. We apply the method to a city with approximately 81 000 consumers, and the results are compared with those obtained through inspections carried out by a Brazilian power utility. The detection rate surpasses 78% in inspected subareas. The method we propose offers improved estimation of distribution of the nontechnical losses in urban regions.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Department of Electrical Enginnering São Paulo State University (UNESP) Ilha Solteira Campus Ilha SolteiraDepartment of Electrical Enginnering São Paulo State University (UNESP) Ilha Solteira Campus Ilha SolteiraCAPES: 2014/06629-0CNPq: 2014/06629-0Universidade Estadual Paulista (Unesp)Faria, Lucas Teles [UNESP]Melo, Joel David [UNESP]Padilha-Feltrin, Antonio [UNESP]2018-12-11T17:02:05Z2018-12-11T17:02:05Z2016-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article362-369application/pdfhttp://dx.doi.org/10.1109/TPWRD.2015.2469135IEEE Transactions on Power Delivery, v. 31, n. 1, p. 362-369, 2016.0885-8977http://hdl.handle.net/11449/17276610.1109/TPWRD.2015.24691352-s2.0-849623769152-s2.0-84962376915.pdf0437995235427473Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIEEE Transactions on Power Delivery1,814info:eu-repo/semantics/openAccess2024-07-04T19:06:36Zoai:repositorio.unesp.br:11449/172766Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:06:42.274963Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Spatial-Temporal Estimation for Nontechnical Losses
title Spatial-Temporal Estimation for Nontechnical Losses
spellingShingle Spatial-Temporal Estimation for Nontechnical Losses
Faria, Lucas Teles [UNESP]
Electricity theft
generalized additive models
nontechnical losses
spatial-point pattern analysis
title_short Spatial-Temporal Estimation for Nontechnical Losses
title_full Spatial-Temporal Estimation for Nontechnical Losses
title_fullStr Spatial-Temporal Estimation for Nontechnical Losses
title_full_unstemmed Spatial-Temporal Estimation for Nontechnical Losses
title_sort Spatial-Temporal Estimation for Nontechnical Losses
author Faria, Lucas Teles [UNESP]
author_facet Faria, Lucas Teles [UNESP]
Melo, Joel David [UNESP]
Padilha-Feltrin, Antonio [UNESP]
author_role author
author2 Melo, Joel David [UNESP]
Padilha-Feltrin, Antonio [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Faria, Lucas Teles [UNESP]
Melo, Joel David [UNESP]
Padilha-Feltrin, Antonio [UNESP]
dc.subject.por.fl_str_mv Electricity theft
generalized additive models
nontechnical losses
spatial-point pattern analysis
topic Electricity theft
generalized additive models
nontechnical losses
spatial-point pattern analysis
description This paper presents a novel method for estimating the spatial distribution in geographical space of the nontechnical losses over time. The method progresses in two stages: in the first stage, a generalized additive model is used to generate a map of current loss probabilities. The second stage employs the Markov chain to generate a map that indicates possible future changes in loss probabilities. The method yields an assessment of the location of the nontechnical losses now and in the future at the city subarea level, even indicating the variables that have greater statistical correlation with the nontechnical losses. We apply the method to a city with approximately 81 000 consumers, and the results are compared with those obtained through inspections carried out by a Brazilian power utility. The detection rate surpasses 78% in inspected subareas. The method we propose offers improved estimation of distribution of the nontechnical losses in urban regions.
publishDate 2016
dc.date.none.fl_str_mv 2016-02-01
2018-12-11T17:02:05Z
2018-12-11T17:02:05Z
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/10.1109/TPWRD.2015.2469135
IEEE Transactions on Power Delivery, v. 31, n. 1, p. 362-369, 2016.
0885-8977
http://hdl.handle.net/11449/172766
10.1109/TPWRD.2015.2469135
2-s2.0-84962376915
2-s2.0-84962376915.pdf
0437995235427473
url http://dx.doi.org/10.1109/TPWRD.2015.2469135
http://hdl.handle.net/11449/172766
identifier_str_mv IEEE Transactions on Power Delivery, v. 31, n. 1, p. 362-369, 2016.
0885-8977
10.1109/TPWRD.2015.2469135
2-s2.0-84962376915
2-s2.0-84962376915.pdf
0437995235427473
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv IEEE Transactions on Power Delivery
1,814
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 362-369
application/pdf
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_ 1808129285471338496