Dynamic strategies for yaw and induction control of wind farms based on large-eddy simulation and optimization

In wind farms, wakes originating from upstream turbines cause reduced energy extraction and increased loading variability in downstream rows. The prospect of mitigating these detrimental effects through coordinated controllers at the wind-farm level has fueled a multitude of research efforts in wind-farm control. The main strategies in wind-farm control are to influence the velocity deficits in the wake by deviating from locally optimal axial induction setpoints on the one hand, and steering wakes away from downstream rows through yaw misalignment on the other hand. The current work investigates dynamic induction and yaw control of individual turbines for wind-farm power maximization in large-eddy simulations. To this end, receding-horizon optimal control techniques combined with continuous adjoint gradient evaluations are used. We study a 4 × 4 aligned wind farm, and find that for this farm layout yaw control is more effective than induction control, both for uniform and turbulent inflow conditions. Analysis of optimal yaw controls leads to the definition of two simplified yaw control strategies, in which wake meandering and wake redirection are exploited respectively. Furthermore it is found that dynamic yawing provides significant benefits over static yaw control in turbulent flow environments, whereas this is not the case for uniform inflow. Finally, the potential of combining overinductive axial induction control with yaw control is shown, with power gains that approximate the sum of those achieved by each control strategy separately