IoT-ENABLED FAULT DETECTION IN DISTRIBUTION LINES

Abstract

The increasing complexity of modern electrical distribution networks demands intelligent, real-time fault detection and isolation systems. Traditional methods of manual inspection and fault identification in three-phase power distribution lines are time-consuming, labor-intensive, and prone to delays that can result in significant power outages and economic losses. This project proposes and implements an IoT-enabled automated fault detection and isolation system for three-phase distribution lines using cost-effective, commercially available hardware components. The system employs an Arduino Uno microcontroller as the central processing unit, interfaced with ACS712 Hall-effect current sensing modules on each of the three phases — R Phase, Y Phase, and B Phase. A 16x2 Liquid Crystal Display (LCD) with I2C communication protocol provides real-time on-site visual feedback of system status and detected fault type. An active buzzer provides immediate auditory alerts, and dedicated Red LEDs serve as phase-wise visual fault indicators. The ESP8266 Wi-Fi module enables seamless internet connectivity, facilitating real-time push notifications to registered mobile devices via the Blynk cloud platform whenever a fault is detected. The system successfully detects two primary categories of faults: Open Circuit Faults and Short Circuit Faults across all three phases, covering all six fault combinations (R-Open, YOpen, B-Open, R-Y Short, Y-B Short, R-B Short) with 100% detection accuracy and an average endto-end fault-to-notification latency of 1.8 seconds. The proposed system provides a low-cost, scalable, and reliable solution for smart grid distribution line monitoring, particularly suited for rural and semiurban electrical infrastructure.