Enhancing Fault Detection and Location Identification using GIS-based Techniques: A Case Study of Arba Minch Distribution System

ABSTRACT Fault detection and location in distribution systems are critical for maintaining reliable electric power supply and minimizing outage time. The Arba Minch District distribution department of Ethiopian Electric Utility (EEU) currently employs a manual trial-and-error approach for fault detection and location, which is inefficient, time-consuming, and ineffective in resolving faults. This study evaluates the current approach and proposes an enhanced system utilizing Geographic Information System (GIS) technology to improve fault detection and location in the Arba Minch distribution system, specifically the Shecha feeder. The implementation of GIS-based fault detection and location aims to address the limitations of the manual method and mitigate economic losses associated with feeder faults. ETAP GIS simulations successfully detected and located faults, achieving effective reduction in fault detection and location time compared to the conventional method. By optimizing fault detection and location time, the System Average Interruption Duration Index (SAIDI) for the feeder was significantly reduced. Consequently, the GIS system highly minimizes the economic losses associated with energy not supplied. The results demonstrate the potential of GIS technology in enhancing fault detection and location, ultimately improving the reliability and efficiency of the distribution system.