Biomimetic individual pitch control for wind turbines

Individual Pitch Control (IPC) has proved efficient in reducing fatigue loads on wind turbines. As 1P (once-per-revolution) blade loads are significant due to wind shear or tower shadow effect, their alleviation implies a rhythmic behavior in the changes of the blade pitch angles. This work relies on Large Eddy Simulations (LES) to demonstrate the effectiveness of a biomimetic architecture for IPC. The high-fidelity simulation of the flow physics is essential to assess the performances of the controller. It is performed by an in-house lifting-lines-enabled Vortex Particle-Mesh method, dealing with synthetic turbulence and wind shear at the inflow. The individual pitch controller is based on Central Pattern Generators (CPGs). CPGs produce, from very simple inputs, rhythmic outputs that drive repetitive motions like walking or breathing. The specificity of these networks is their ability to operate autonomously. They are here implemented as coupled non-linear oscillators, capable of producing coordinated rhythmic patterns and driven by a knowledge of the upstream flow conditions. The latter are reconstructed online by an Extended Kalman Filter processing the loads experienced by the individual blades.