Detection and Identification of Abnormalities in Customer Consumptions in Power Distribution Systems


Autoria(s): dos Angelos, Eduardo Werley S.; Saavedra, Osvaldo R.; Carmona Cortes, Omar A.; de Souza, Andre Nunes
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

20/05/2014

20/05/2014

01/10/2011

Resumo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

This paper proposes a computational technique for the classification of electricity consumption profiles. The methodology is comprised of two steps. In the first one, a C-means-based fuzzy clustering is performed in order to find consumers with similar consumption profiles. Afterwards, a fuzzy classification is performed using a fuzzy membership matrix and the Euclidean distance to the cluster centers. Then, the distance measures are normalized and ordered, yielding a unitary index score, where the potential fraudsters or users with irregular patterns of consumption have the highest scores. The approach was tested and validated on a real database, showing good performance in tasks of fraud and measurement defect detection.

Formato

2436-2442

Identificador

http://dx.doi.org/10.1109/TPWRD.2011.2161621

IEEE Transactions on Power Delivery. Piscataway: IEEE-Inst Electrical Electronics Engineers Inc, v. 26, n. 4, p. 2436-2442, 2011.

0885-8977

http://hdl.handle.net/11449/8928

10.1109/TPWRD.2011.2161621

WOS:000298981800041

Idioma(s)

eng

Publicador

Institute of Electrical and Electronics Engineers (IEEE)

Relação

IEEE Transactions on Power Delivery

Direitos

closedAccess

Palavras-Chave #Data mining #electricity theft #fuzzy clustering #nontechnical losses
Tipo

info:eu-repo/semantics/article