A Hybrid Single-Ended Fault Detection and Classification Scheme in a Double-Circuit Transmission Line

Abstract

A six-phase, double-circuit transmission system consists of two independent three-phase circuits powered by a common bus. The increase in the number of phases introduces a variety of faults, including both intra-circuit and inter-circuit faults, which can complicate fault detection and classification algorithms. Accurate identification and classification of these faults are essential for interrupting fault propagation and enabling rapid system restoration. This paper presents a hybrid algorithm that employs signal processing techniques based on mathematical transformations to detect faults, identify the faulty circuit, and classify the fault type. The algorithm operates by sampling the currents from a single terminal and includes zero-sequence current analysis to differentiate between ground and non-ground faults. Given that the threshold values for fault classification vary across different scenarios, a simple model is proposed to determine these thresholds dynamically. The proposed model is simulated on a standard double-circuit transmission system within the MATLAB/Simulink software environment, and its performance is evaluated under various fault scenarios. The simulation results demonstrate the model's capability to accurately detect and classify fault types in the test system. Notably, the objectives of fault detection and classification are achieved with 100% accuracy across all fault scenarios.