Hybrid adaptive control for variable-speed variable-pitch wind energy systems using general regression neural network

Abstract. This paper presents a novel hybrid adaptive control approach for the VS-VP half-direct driven WECS by combining pitch control with variable generator torque regulation in different operating regions. A general regression neural network (GRNN) is employed to derive the reference commands of generator torque and pitch angle from the real-time signals of generator power and speed. Furthermore, a fast and effective nonlinear PID pitch controller is presented to track the reference command of pitch angle in the full load region. The proposed GRNN based hybrid adaptive control strategies have been developed and validated using simulations. This study shows that the proposed method is much faster, more accurate and effective than conventional linear control approach.