Performance improvement of Doubly Fed Induction Generator using Grey Wolf Optimization

Gray Wolf Optimization (GWO) algorithm is one of the most recently studied bio-inspired algorithms proposed for tuning a fractional order proportional - integral-derivative (FOPID) controller’s parameters for satisfactory DFIG control. Using numerical differentiation of the model subsequently used for FOPID controller design, the lower order nominal representation of DFIG is obtained. By optimising an aggregated cost function based totally at the time-weighted absolute error integral, subjected to robustness constraints. To achieve correct set-point tracking and disturbance rejection overall performance, the control system is designed. The robustness analysis has been conducted using Convex hull approach. To show the efficacy of the controller, it is compared with the recent approaches published in the literature. Comparative investigation exhibits that proposed FOPID controllers enhance the settling time and decreases overshoot viably towards small step load disturbances.