Novel fully sensorless synergetic control of brushless doubly fed induction machine integrated in wind energy conversion system driven by fuzzy-based HCS MPPT algorithm

This paper proposes a novel fully sensorless synergetic algorithm that adopts concerns from both power, torque, and speed of brushless doubly fed induction machine (BDFIM) for application in wind energy conversion system (WECS). A sensorless fuzzy-based hills climb search algorithm (HCS-MPPT) is introduced to the control system along with a comparison study with the conventional tip speed ratio algorithm (TSR-MPPT). For studying the feasibility of the suggested control, a robust control of the BDFIM based on synergetic control theory is build up for the first time ever on this machine type with different scenarios where the active and reactive power, the torque, and speed of the machine are controlled. In the second step, the aim is maximizing the wind’s energy extraction by replacing the wind speed sensors with a fuzzy-based HCS-MPPT approach. Lastly, to increase the robustness of the suggested scheme control, an extended Kalman filter EKF is employed for the estimation of rotor speed in presence of considerable noise values in order to make it closer to reality as possible. Computational simulation results confirm that the proposed method, consistently outperforms other techniques and proves effectiveness under several conditions.