Estimation of non-technical loss rates by regions

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorFederal University of ABC-
Autor(es): dc.creatorVentura, Lucas-
Autor(es): dc.creatorFelix, Gustavo Estevo-
Autor(es): dc.creatorVargas, Renzo-
Autor(es): dc.creatorFaria, Lucas Teles-
Autor(es): dc.creatorMelo, Joel David-
Data de aceite: dc.date.accessioned2025-08-21T16:22:32Z-
Data de disponibilização: dc.date.available2025-08-21T16:22:32Z-
Data de envio: dc.date.issued2023-11-06-
Data de envio: dc.date.issued2023-11-06-
Data de envio: dc.date.issued2023-07-18-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/251256-
Fonte completa do material: dc.identifierhttps://doi.org/10.1016/j.epsr.2023.109685-
Fonte completa do material: dc.identifierhttp://lattes.cnpq.br/0410725069211275-
Fonte completa do material: dc.identifierhttps://orcid.org/0000-0003-2287-1571-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/251256-
Descrição: dc.descriptionIdentifying vulnerable regions to non-technical losses allows more assertive combat against them. In this context, this paper presents a spatiotemporal methodology composed of two modules, spatial and temporal, to assist distribution companies in action planning to decrease the rates of non-technical losses by region. The spatial module contains a neighborhood structure based on the similarity among small regions named ‘‘neighborhood by the similarity of attributes’’, which improves the characterization of non-technical losses actions performed by end-consumers. That neighborhood structure is incorporated as an input parameter into a hierarchical spatial autoregressive regression model to represent the relationships between inhabitants. On the other hand, the temporal module uses a linear mixed-effects model to consider future values that are subject to the actions of consumers or distribution companies. The proposed methodology is applied to a medium-sized city with approximately 200,000 inhabitants, considering the inspections carried out by a Brazilian distribution utility. The proposal identified the future non-technical loss state in all the city’s regions with values greater than 69% of the success rate in identifying NTL to residential, commercial, and industrial consumer classes.-
Descrição: dc.descriptionPró-Reitoria de Pesquisa (PROPe UNESP)-
Descrição: dc.descriptionPró-Reitoria de Pós-Graduação (PROPG UNESP)-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionPreprint-
Descrição: dc.descriptionUNESP PROPG/PROPe N◦ 04/2022 Project Number 4289-
Descrição: dc.descriptionCNPq: 408898/2021-6-
Descrição: dc.descriptionFAPESP: 2021/08832-1-
Descrição: dc.descriptionFAPESP: 2019/04417-0-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Publicador: dc.publisherElsevier-
Relação: dc.relationElectric Power Systems Research-
Direitos: dc.rightsinfo:eu-repo/semantics/openAccess-
Palavras-chave: dc.subjectElectric power distribution-
Palavras-chave: dc.subjectNon-technical losses-
Palavras-chave: dc.subjectSpatial data analysis-
Título: dc.titleEstimation of non-technical loss rates by regions-
Título: dc.titleEstimação de perdas não-técnicas por regiões-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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