Abstract
Energy supplied by the power utility does not reach to the consumer end as a whole. A portion of energy is lost in the distribution system because of Technical and Nontechnical losses. The objective of this paper is to detect the Non-technical losses by monitoring customer irregular consumption profiles in power distribution system with the help of data-mining techniques. As a first step fuzzy C-Means clustering is performed to group customers of same consumption patterns. Then fuzzy based classification technique applied with help of fuzzy membership function and the distances of cluster centers are measured by Euclidean distance, and the distances are normalized and ordered with unitary index score, the highest score represents fraudsters. The approach was tested on a real data, showing good performance in tasks of fraud and measurement defect detection comparing with theft record of Power Distribution Company.
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