PERFORMANCE EVALUATION OF FAULT DETECTION AND ISOLATION METHODS IN POWER SYSTEMS USING SIMULATION

Abstract

Fault detection and isolation (FDI) play a critical role in ensuring the reliability, safety, and continuity of modern power systems. With increasing system complexity due to large-scale interconnections, renewable energy integration, and dynamic load variations, accurate and fast fault diagnosis has become essential. This paper presents a comprehensive performance evaluation of fault detection and isolation methods in power systems using simulation-based analysis. A detailed power system model is developed in MATLAB/Simulink to emulate transmission and distribution network behavior under normal and faulty operating conditions. Various fault scenarios, including single line-to-ground, line-toline, double line-to-ground, and three-phase faults, are simulated to assess the effectiveness of different FDI techniques. Key performance metrics such as detection accuracy, response time, fault classification capability, and isolation efficiency are analyzed and compared. The results demonstrate that simulation-based evaluation provides valuable insights into the strengths and limitations of fault detection and isolation methods, enabling improved protection strategies and enhanced power system reliability. The proposed framework serves as a practical and scalable approach for testing and validating FDI techniques before real-world deployment.