Adaptive inverse control of variable speed wind turbine

The efficiency and reliability of wind power has been shown to be depending on the applied control strategy of the wind turbine. In this paper, an adaptive control strategy is proposed for variable speed wind turbine (VSWT), producing energy limitation above rated wind speed. In the proposed control strategy, the process is modeled using a neural networks based identifier, providing the sensitivity information of the process to the control input. Another neural networks is employed as an inverse model controller established via inverse system method. These two neural networks are off-line learned firstly and are on-line updated using the back propagation algorithm. Simulation results have shown the effectiveness of the proposed adaptive control strategy.