Numerical investigation of wind turbine control schemes for load alleviation and wake effects mitigation by Marion COQUELET


December 14, 2022



Place Sainte Barbe, auditorium BARB93

For the degree of Doctor of Engineering Sciences and Technology (join PhD with UMONS)

For more than 3000 years, windmills have been used to harvest energy from the wind. Over the past 30 years, electrical generators and advanced aerodynamics have turned them into the wind turbines we know. From here on, how can the coming 30 years see them transition from outsider to key player of the energy system to help reach carbon neutrality? Increasing rotor diameters is a possible answer, clustering turbines into wind farms is another. Yet with both options come new challenges, as the sensitivity of components to fatigue increases with the size of rotors and the wake phenomenon is responsible for power losses in wind farms. This thesis falls in the context of using control strategies to tackle these challenges. More specifically, this work relies on high fidelity simulations to investigate control approaches numerically.

When it comes to reducing fatigue loads, individually controlling the pitch of each blade has proven to be efficient. This thesis introduces a novel controller architecture that relies on a neural network trained with reinforcement learning. This work demonstrates that a neural network can learn how to alleviate loads in simple wind conditions and that it is also capable of transferring that knowledge to realistic ones, such as turbulence and wakes.

On the question of wake mitigation, dynamically controlling wind turbines is gaining interest. While some strategies enhance the lateral displacement of the wake, others periodically modify its intensity. This work provides elements of answers regarding the mechanisms relating dynamic actuation of the blades to power gains in the wake. To do so, the effects of dynamic flow control on the wake destabilization and recovery processes are investigated. Attention is also paid to quantifying the impacts of such strategies on both power production and loads at the scale of a pair of turbines.


Jury members :

  • Prof. Philippe Chatelain (UCLouvain, Belgium), supervisor
  • Prof. Laurent Bricteux (UMONS, Belgium), supervisor
  • Prof.  Sandra Soares-Frazao (UCLouvain, Belgium), chairperson
  • Dr. Matthieu Duponcheel (UCLouvain, Belgium)
  • Dr. Stéphanie Zeoli (UMONS, Belgium)
  • Prof. Jan-Willem van Wingerden (TU Delft, Netherlands)
  • Prof. Matilde Santos Peñas (Universidad Complutense de Madrid, Spain)


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