A Novel Technique for Asymmetrical Fault Detection in DFIG based Wind-Farm

This paper proposes a novel technique for asymmetrical fault detection (LLL-G) in DFIG based wind form using wavelet based energy 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) is here proposed to detect grid faults dynamically over time. Simulation results demonstrate the effectiveness of the proposed approach under time varying conditions