A novel active wake control strategy based on LiDAR for wind farms

The increasing size and clustering of wind turbines have amplified wake effects, reducing wind farm power generation. For this reason, a multi-priority control strategy based on axial induction control was proposed to enhance the total power output of the wind farm in this paper. Firstly, a wind speed time-delay prediction model based on LiDAR for tandem turbines was constructed, by employing a time-delay processing algorithm to refine the wind speed engineering model and integrating a neural network model for the axial induction factor at the rotor. After that, a multi-priority control strategy, defining turbine priorities based on wake effects and adjusting power distribution via the axial induction factor, was proposed to maximize power capture for wind farms. Simulink and FAST co-simulations shown that, under steady-state wind input conditions, the multi-priority control strategy increased power output of the wind farm by 6.62 %, compared to the maximum power point tracking strategy. Finally, preliminary hardware-in-the-loop experiments demonstrated that the control strategy did not have a negative impact in a semi-physical environment, providing theoretical support for subsequent ground-based wind turbine experiments.