An Efficient Active and Reactive Power Control of DFIG for a Wind Power Generator

During the last decade, wind energy gained much importance as an energy source in power systems. DFIG energy is one of the most widely accepted types of renewable energy generation because of its several benefits. This paper presents a comparative study on the performance of different control strategies for DFIG wind turbines: proportional–integral (PI), Artificial Neural Networks (ANN), H_∞, and adaptive Fuzzy PI controller. Simulation results show that DFIG’s performance, dynamic response, and robustness against machine parameter variations are improved with H_∞ control technique.