A novel algorithm for asymmetrical fault detection in DFIG based wind-farm using wavelet singular entropy function

This paper proposes a novel technique for asymmetrical fault detection (LLL-G) in DFIG based wind farm using wavelet singular entropy function. In this study, there are six wind turbine driven DFIG are grouping together to make wind farm and 9 MW power is feeding to the grid. Further, the rotor is supplied by a bidirectional PWM converter for the control of active and reactive power flows from DFIG to the grid. In the case study, the three-phase fault is created in the grid and proposed algorithm detects the fault with in one and half cycles for 60 Hz system. A new diagnostic method based on the grid modulating signals pre-processing by Discrete Wavelet Transform (DWT) to derive singular values, used to find out Shannon entropy, called Wavelet Singular Entropy (WSE) is here proposed to detect grid faults dynamically over time. Simulation results demonstrate the effectiveness of the proposed approach under time-varying conditions.