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

被引：215

作者：

dos Angelos, Eduardo Werley S. ^{[1
]}

Saavedra, Osvaldo R. ^{[1
]}

Carmona Cortes, Omar A. ^{[2
]}

de Souza, Andre Nunes ^{[3
]}

机构：

[1] Univ Fed Maranhao, Power Syst Grp, BR-65085580 Sao Luis, Maranhao, Brazil

[2] Tech Fed Inst, BR-65030005 Sao Luis, Maranhao, Brazil

[3] State Univ Sao Paulo, BR-17033360 Bauru, Brazil

来源：

IEEE TRANSACTIONS ON POWER DELIVERY | 2011年 / 26卷 / 04期

关键词：

Data mining; electricity theft; fuzzy clustering; nontechnical losses;

D O I：

10.1109/TPWRD.2011.2161621

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：2436 / 2442

页数：7

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