Swarm Evaluated Threshold Elimination Approach for Symmetrical Fault Detection During Power Swing

This paper introduces the application of swarm intelligence in relaying to detect symmetrical faults during power swing. The swarm intelligence assistance reduces the computational burden and enhances the overall reliability of the fault detection scheme irrespective of the system conditions. For this purpose, a simple fault detector using instantaneous three-phase active power is implemented and particle swarm optimization (PSO) assistance is provided to identify the optimal value of threshold elimination factor (TEF) by considering fault and swing parameters as decision variables. In the optimal TEF search, the detailed coefficients of frequency components of the input signal are extracted using wavelet transform by generating the solutions using PSO. As a result, a direct trip command is activated with the help of the swarm-assisted wavelet TEF technique. The PSO-assisted proposed method is fast and secure in detecting faults during stressed conditions. Later, the performance of the proposed method is tested on numerous fault cases simulated on a two-bus test power system model using MATLAB/Simulink(R). Results clearly show that using the proposed method faults can be detected within a quarter cycle during the power swing. The comparative assessment with the existing methods confirms the effectiveness of the proposed scheme.