Paper Details

Distribution of electricity involves significant Technical as well as Non-Technical Losses (NTL). Illegalconsumption of electricity or electricity theft constitutes a major share of NTL. This project discusses several methodsimplemented by illegal consumers for stealing. With the advent of advanced metering technologies, real-time energyconsumption data will be available at the utilities end, which can be used to detect illegal consumers. This project presentsan encoding technique that simplifies the received customer energy consumption readings (patterns) and maps them intocorresponding irregularities in consumption. Then, this project elucidates operation of intelligent classification techniqueson customer energy consumption data to classify genuine and illegal consumers. These classification models are applied onregular energy consumption data as well as the encoded data to compare corresponding classification accuracies andcomputational overhead. Depending on abnormal consumtion behaviour suspected consumers are onspected .Using datamining techniques suspected customers profiles are loaded .The approach of this project is to deal with power loss activitylike detecting the illegal power consumers

Pranali Sable, Priyanka Ohol, Pallavi Murhe, Sneha Vidhate, “ELECTRICAL POWER THEFT DETECTION”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 12, pp. -, December 2017.