Fuzzy Inference Based Electricity Theft Prevention System to Restrict Direct Tapping Over Distribution Line

Abstract

Electricity theft is a major concern for power distribution utilities. The increase in non-technical losses give rise to imbalance between electricity supply and demand resulting into overloading of existing distribution network, reduction in reliability and stability of supply and additional tariff posed on genuine consumers. Although, the smart metering systems has resolved meter related power theft problems, however, direct tapping on distribution line remains perpetual issue which should be stringently annihilated. Thus, this paper presents real-time electricity theft detection using energy consumption data of all legal consumers and outgoing distribution transformer energy meter data. In order to prevent the hook-line activity, a fuzzy inference based scheme is implemented in LabVIEW to operate electricity theft prevention system (ETPS). The ETPS develops unsuitable voltage across illegal consumer and hinders normal operation of their appliances. The consumer care unit (CCU) interlocked with ETPS maintains normal supply voltage at legal consumers end. The suitability, flexibility in operation and effectiveness of the proposed ETPS and CCU based theft prevention scheme is experimentally and practically demonstrated as case study under various voltage regulation and energy loss scenarios.