Energy Theft and Fault Detection in Smart Energy Meter Using Fuzzy Logic

Abstract

Energy theft and fault is a significant global issue in the energy sector, which accounts for non-technical loss in power utilities. Specifically, in Nigerian context, energy theft arises from meter tampering to reduce energy consumption readings, unauthorized or illegal connections, and meter swapping. The nexus of Internet of Things and Fuzzy logic learning techniques applied in smart metering system could mitigate this endemic problem. While there are efforts in literature that address this problem. However, there is still need for an optimal and smart metering system with an increased intelligence and accuracy to address energy theft and fault detection problem in distribution network. Hence, this work presents a solution to energy theft and fault detection in the distribution network by designing a smart energy metering system that applies simple fuzzy logic rules to analyze data thereby detecting theft and fault in the system. The system compares the measurements from a pole-based smart meter and consumer unit meter for detection of fault and theft. The smart energy meter is designed with a microcontroller and uses Wi-Fi communication for data transmission from pole-based metering point and consumer unit metering point to the central server for analysis and processing. The result shows that Fuzzy logic is useful in solving energy theft and fault detection problems. The accuracy and precision are 95% and 95% respectively for theft detection as well as 91% and 95% for fault detection.