Optimal blade pitch control for a vertical-axis wind turbine blade undergoing dynamic stall

Vertical-axis wind turbines feature many advantages to complement traditional wind turbines in power production including omni-directionality, low noise production, and scalability. The inherent aerodynamic complexity of vertical-axis wind turbines has challenged their development for large-scale power production. The blades of these turbines undergo periodic variations in effective angle of attack and incident flow velocity, leading to the occurrence of dynamic stall. This phenomenon causes large cycle-to-cycle load fluctuations, jeopardising the turbine’s structural integrity. We investigate the potential of individual blade pitching to control the occurrence of dynamic stall on a single-bladed wind turbine model. We optimise the blade’s pitching profile using a genetic algorithm with two objectives: 1) maximising the net power production and 2) minimising load fluctuations related to flow separation. We performed over 1500 experiments visiting a large envelope of pitching kinematics. We obtain time-resolved aerodynamic force measurements using a customised load cell built into the blade’s shaft and compute the wind turbine performance for each individual. The strongest individuals achieve a 300% increase in net power production compared to a non-actuated wind turbine blade.