Fast Fault Detection Using Optimal Intrinsic Modes and Energy Deviation Matrix in Distribution Systems

The detection, classification, and location of grid faults have always been challenging for power engineers. Among these, the detection of the grid fault is the most critical task because, without the detection, the remaining two processes will not start. In this study, a fast light-weight fault detection is proposed. This technique uses an empirical mode decomposition to decompose the fault signals into intrinsic mode functions (IMFs). Effective IMFs were selected using the earth mover’s distance-based selection algorithm. The selected IMFs are then passed through an energy calculator and then through a moving median absolute deviation stage to generate an energy deviation matrix (EDM). Based on the EDM, the occurrence of faults can be determined. The proposed technique was verified by evaluating various grid fault scenarios using the MATLAB/Simulink software platform. Furthermore, the proposed method shows a more precise and satisfactory performance than existing standard fault-detection methods.