21 Sep 2023
 | 21 Sep 2023
Status: a revised version of this preprint is currently under review for the journal WES.

Dynamic wind farm flow control using free-vortex wake models

Maarten J. van den Broek, Marcus Becker, Benjamin Sanderse, and Jan-Willem van Wingerden

Abstract. A novel dynamic economic model-predictive control strategy is presented that improves wind farm power production and reduces the additional demands of wake steering on yaw actuation when compared to an industry state-of-the-art reference controller. The novel controller takes a distributed approach to yaw control optimisation using a free-vortex wake model. An actuator-disc representation of the wind turbine is employed and adapted to the wind-farm scale by modelling secondary effects of wake steering and connecting individual turbines through a directed graph network. The economic model-predictive control problem is solved on a receding horizon using gradient-based optimisation, demonstrating sufficient performance for realising real-time control. The novel controller is tested in a large-eddy simulation environment and compared against a state-of-the-art look-up table approach based on steady-state model optimisation. Under realistic variations in wind direction and wind speed, the novel controller yields additional gains in power production during transients as well as a reduction in yaw actuator usage.

Maarten J. van den Broek et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2023-119', Jaime Liew, 11 Oct 2023
  • RC2: 'Comment on wes-2023-119', Anonymous Referee #2, 12 Oct 2023
  • RC3: 'Comment on wes-2023-119', Michael Sinner, 19 Oct 2023
  • AC1: 'Comment on wes-2023-119', Maarten van den Broek, 21 Nov 2023

Maarten J. van den Broek et al.

Data sets

Simulation data and code accompanying the publication: Dynamic wind farm flow control using free-vortex wake models Maarten J. van den Broek

Maarten J. van den Broek et al.


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Short summary
Wind turbines wakes negatively affect wind farm performance as they impinge on downstream rotors. Wake steering reduces these losses by redirecting wakes using yaw misalignment of the upstream rotor. We develop a novel control strategy based on model predictions to implement wake steering under time-varying conditions. The controller is tested in a high-fidelity simulation environment and improves wind farm power output compared to a state-of-the-art reference controller.