Dynamic wind farm flow control using free-vortex wake models

In the current state of model-based wind farm flow control, the implementation of yaw-based wake steering based on steady-state models has demonstrated potential for improving wind farm power production. However, for realistic, time-varying wind directions, the dynamics of wake propagation may impact the effectiveness of wake redirection. This dissertation presents the development of an economic model-predictive wind farm flow control strategy and assesses the potential for improved power production from wake steering in wind farms under time-varying conditions.

At the core of such a model-based control strategy is a control-oriented model of the wind farm flow. A free-vortex wake model is formulated based on an actuator-disc representation of the wind turbine rotor. A validation study is included for power predictions in the mid to far wake of turbines operating under yaw misalignment using data from wind tunnel experiments. Finally, a distributed strategy for control optimisation is constructed to provide a scalable solution for dynamic wind farm flow control which is tested in a large-eddy simulation environment under realistic conditions. This novel controller yields additional gains in power production during wind direction transients and reduces the increase in yaw actuator usage from wake steering.