Control of Doubly Fed Induction Generator with Maximum Power Point Tracking for Variable Speed Wind Energy Conversion Systems

In this paper, a Direct Power Control (DPC) based on the switching table and Artificial Neural Network-based Maximum Power Point Tracking control for variable speed Wind Energy Conversion Systems (WECS) is proposed. In the context of wind energy exploitation, we are interested in this work to improve the performance of the wind generator by controlling the continuation of the Maximum Power Point Tracking (MPPT) using the Artificial Neural Network (ANN). The results obtained show the interest of such control in this system. The proposed Direct Power Control strategy produces a fast and robust power response, also the grid side is controlled by Direct Power Control based a grid voltage position to ensure a constant DC- link voltage. The THD of the current injected into the electric grid for the Wind Energy Conversion Systems with Direct Power Control is shown in this paper, the THD is lower than the 5 % limit imposed by IEEE STANDARDS ASSOCIATION. This approach Direct Power Control is validated using the Matlab/Simulink software and simulation results can prove the excellent performance of this control as improving power quality and stability of wind turbine.