A New TSA-Fuzzy Logic Based Diagnosis of Rotor Winding Inter-turn Short Circuit Fault in Wind Turbine Based on DFIG Under Different Operating Wind Speeds

Abstract

Doubly-fed induction generators (DFIGs) are the most utilized generator types of wind turbine systems, thanks to their important efficiency, elevated power factor, quicker response and robust construction. However, they may be subject of many kinds of defect. Condition monitoring methods and early failure diagnosis algorithms for wind turbine installation have become a fundamental practice as they serve to enhance wind farm dependability, performance and overall productivity. In this context, an advanced diagnostic technique for the detection of rotor inter-turn short circuit residual faults, based on the combination of the Time Synchronous Averaging (TSA) technique and Fuzzy Logic (FL) is established. In fact, rotor residual failure cannot be detected directly by analyzing the stator current, especially in the low wind speed (WS) case. The RMS of residual current and the value of wind speed will be used as inputs for the fuzzy logic bloc in order to give the decision about the state of the rotor. The proposed strategy has been implemented and verified using simulations built in MatLab SIMULINK environment. The simulation results prove the efficiency and the reliability of the proposed approach.