Using baseline methods to identify non-technical losses in the context of smart grids

Detalhes bibliográficos
Autor(a) principal: Faria, Pedro
Data de Publicação: 2013
Outros Autores: Vale, Zita, Antunes, Pedro, Souza, André [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/ISGT-LA.2013.6554495
http://hdl.handle.net/11449/76330
Resumo: Demand response has gained increasing importance in the context of competitive electricity markets and smart grid environments. In addition to the importance that has been given to the development of business models for integrating demand response, several methods have been developed to evaluate the consumers' performance after the participation in a demand response event. The present paper uses those performance evaluation methods, namely customer baseline load calculation methods, to determine the expected consumption in each period of the consumer historic data. In the cases in which there is a certain difference between the actual consumption and the estimated consumption, the consumer is identified as a potential cause of non-technical losses. A case study demonstrates the application of the proposed method to real consumption data. © 2013 IEEE.
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spelling Using baseline methods to identify non-technical losses in the context of smart gridsCustomer baseline loaddemand responsenontechnical lossesperformance evaluation methodssmart gridCustomer baseline loadsDemand responseEvaluation methodsNon-technical lossSmart gridSmart power gridsDemand response has gained increasing importance in the context of competitive electricity markets and smart grid environments. In addition to the importance that has been given to the development of business models for integrating demand response, several methods have been developed to evaluate the consumers' performance after the participation in a demand response event. The present paper uses those performance evaluation methods, namely customer baseline load calculation methods, to determine the expected consumption in each period of the consumer historic data. In the cases in which there is a certain difference between the actual consumption and the estimated consumption, the consumer is identified as a potential cause of non-technical losses. A case study demonstrates the application of the proposed method to real consumption data. © 2013 IEEE.GECAD Knowledge Engineering and Decision Support Research Center IPP Polytechnic Institute of Porto, PortoDepartment of Electrical Engineering UNESP Univ Estadual Paulista, BauruDepartment of Electrical Engineering UNESP Univ Estadual Paulista, BauruPolytechnic Institute of PortoUniversidade Estadual Paulista (Unesp)Faria, PedroVale, ZitaAntunes, PedroSouza, André [UNESP]2014-05-27T11:30:15Z2014-05-27T11:30:15Z2013-08-26info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/ISGT-LA.2013.65544952013 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT LA 2013.http://hdl.handle.net/11449/7633010.1109/ISGT-LA.2013.65544952-s2.0-848823909638212775960494686Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2013 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT LA 2013info:eu-repo/semantics/openAccess2024-06-28T13:34:42Zoai:repositorio.unesp.br:11449/76330Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:06:48.451847Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Using baseline methods to identify non-technical losses in the context of smart grids
title Using baseline methods to identify non-technical losses in the context of smart grids
spellingShingle Using baseline methods to identify non-technical losses in the context of smart grids
Faria, Pedro
Customer baseline load
demand response
nontechnical losses
performance evaluation methods
smart grid
Customer baseline loads
Demand response
Evaluation methods
Non-technical loss
Smart grid
Smart power grids
title_short Using baseline methods to identify non-technical losses in the context of smart grids
title_full Using baseline methods to identify non-technical losses in the context of smart grids
title_fullStr Using baseline methods to identify non-technical losses in the context of smart grids
title_full_unstemmed Using baseline methods to identify non-technical losses in the context of smart grids
title_sort Using baseline methods to identify non-technical losses in the context of smart grids
author Faria, Pedro
author_facet Faria, Pedro
Vale, Zita
Antunes, Pedro
Souza, André [UNESP]
author_role author
author2 Vale, Zita
Antunes, Pedro
Souza, André [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Polytechnic Institute of Porto
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Faria, Pedro
Vale, Zita
Antunes, Pedro
Souza, André [UNESP]
dc.subject.por.fl_str_mv Customer baseline load
demand response
nontechnical losses
performance evaluation methods
smart grid
Customer baseline loads
Demand response
Evaluation methods
Non-technical loss
Smart grid
Smart power grids
topic Customer baseline load
demand response
nontechnical losses
performance evaluation methods
smart grid
Customer baseline loads
Demand response
Evaluation methods
Non-technical loss
Smart grid
Smart power grids
description Demand response has gained increasing importance in the context of competitive electricity markets and smart grid environments. In addition to the importance that has been given to the development of business models for integrating demand response, several methods have been developed to evaluate the consumers' performance after the participation in a demand response event. The present paper uses those performance evaluation methods, namely customer baseline load calculation methods, to determine the expected consumption in each period of the consumer historic data. In the cases in which there is a certain difference between the actual consumption and the estimated consumption, the consumer is identified as a potential cause of non-technical losses. A case study demonstrates the application of the proposed method to real consumption data. © 2013 IEEE.
publishDate 2013
dc.date.none.fl_str_mv 2013-08-26
2014-05-27T11:30:15Z
2014-05-27T11:30:15Z
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 http://dx.doi.org/10.1109/ISGT-LA.2013.6554495
2013 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT LA 2013.
http://hdl.handle.net/11449/76330
10.1109/ISGT-LA.2013.6554495
2-s2.0-84882390963
8212775960494686
url http://dx.doi.org/10.1109/ISGT-LA.2013.6554495
http://hdl.handle.net/11449/76330
identifier_str_mv 2013 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT LA 2013.
10.1109/ISGT-LA.2013.6554495
2-s2.0-84882390963
8212775960494686
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2013 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT LA 2013
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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