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

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4 Author(s)
Angelos, E.W.S. ; Power Syst. Group, Fed. Univ. of Maranhao, Maranhão, Brazil ; Saavedra, O.R. ; Cortés, O.A.C. ; de Souza, A.N.

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.

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Power Delivery, IEEE Transactions on  (Volume:26 ,  Issue: 4 )