An Efficient Fault Detection and Localization System for Three-Phase Transmission Line using Arduino and Artificial Neural Networks

Abstract

This paper presents an efficient fault detection and localization system for a three-phase transmission line using Arduino and artificial neural networks. The
proposed system is designed to detect and localize faults in real-time, reducing the downtime and improving the reliability of the power system. The system consists of three main components: the fault detection unit, the fault classification unit, and the fault localization unit. The fault detection unit uses Arduino microcontroller and current transformers to collect and process the current signals from the transmission line. The fault classification unit uses an artificial neural network algorithm to classify the fault type based on the current signals. The fault localization unit uses the fault type and the time delays of the current signals to determine the fault location. The proposed system is evaluated on a simulated three-phase transmission line, and the results show that it can detect and localize faults with high accuracy and efficiency.