Real-Time Detection of Short Circuit Faults of Wind Turbine Permanent Magnet Synchronous Generator by Short-Time Analysis of the Signal Amplitude Ripple Intensity Based on Analytical Model

This paper introduces and analyzes the turn-to-turn short-circuit (TTSC) fault and phase-to-phase short-circuit (PPSC) fault in a permanent magnet synchronous generator (PMSG). The analytical equivalent magnetic network (EMN) method is used to model the PMSG under healthy and faulty conditions. This method provides a high modeling accuracy and has a shorter processing time compared to the finite element method (FEM). The faulty current signal in the dqo frame is evaluated, and mathematical relations are employed to demonstrate that the short circuit fault changes the 2nd harmonic amplitude of the current signal. The short-time analysis of the signal amplitude ripple intensity (ST-SARI) method is presented, and the fault index is obtained by extracting signal amplitude in real-time. In addition, this method separates TTSC and PPSC faults. Finally, the FEM and EMN modeling results are compared with the experimental test results of the prototyped PMSG. The results show that the combination of the proposed EMN and ST-SARI methods leads to high accuracy and speed in tracking and detecting faults at different stages of their occurrence.