A THESIS SUBMITTED TO FACULTY OF ELECTRICAL AND COMPUTER ENGINEERING, INSTITUTE OF TECHNOLOGY, SCHOOL OF GRADUATE STUDIES, ARBA MINCH UNIVERSITY IN

Abstract

Faults are prevalent in electric generation, transmission, and distribution systems. These faults are due to environmental conditions (rain, lightning, wind, and storms), external factors (birds, trees), internal factors (aging), and others. Distribution systems experience higher fault rates than generation and transmission systems. Fault detection and location systems are crucial for maintaining reliable electric power, minimizing outage time, and reducing associated costs. In the Arba Minch District distribution department of Ethiopian Electric Utility (EEU), fault detection and location are performed manually through a trial-and-error approach. This approach is inefficient, time-consuming, and ineffective in resolving faults, leading to equipment damage, energy loss, reduced revenue, customer dissatisfaction, and increased labor requirements. In order to improve fault detection and location method of Arba Minch distribution system of shecha feeder, this thesis evaluates the current try-and-error approach of fault detection and location system and suggests an enhanced system utilizing GIS technology. The Arba Minch Shecha Feeder was selected due to its large customer base and frequent unplanned interruptions caused by faults. GIS-based fault detection and location was implemented in this thesis to address the limitations of the manual method and mitigate economic losses associated with feeder faults. By synchronization of ETAP circuit and ETAP GIS network, the location of the fault is visualized in ETAP-GIS system. The GIS system achieved a 99.11% reduction in fault detection and location time relative to the conventional method. By optimizing fault detection and location time, the System Average Interruption Duration Index (SAIDI) for the feeder was significantly reduced from 216.36 to 1.93 hours/customer per fault. Consequently, the GIS system eliminated economic losses associated with energy not supplied (24,784.58 KWh and 13,625.41 KVArh) and revenue not collected (42,000 ETB for 1 hour, 78,288 ETB for 1.864 hours, and 231,000 ETB for 5.5 hours).