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IMMC

Marion Coquelet
PhD student
Ir. at UMONS in 2018
Contact

Main project: WakeOpColl
Funding: ERC
Supervisor(s): Philippe Chatelain

Marion Coquelet is part of the ERC-granted project WakeOpColl, which focuses on learning and collective intelligence for optimized operations in wake flows. Her contribution is related to the control of wind turbines using artificial intelligence. One of the questions to be answered is how a wind turbine in a farm can learn and organize itself in order to maximize the global production of the farm, but also to limit the fatigue loads experienced by its blades.

She has focused on how wind turbine blades can be used as sensor of the flow. By measuring the blades loads, the wind profile upstream of the wind turbine can be reconstructed (local velocities, shear, turbulence intensity). She is now busy with making the wind turbine learn how to behave depending on this knowledge of the flow conditions. More precisely, individual pitch control is used te reduce the fatigue loads appearing on the blades and the control strategy is acquired by reinforcement learning.

IMMC main research direction(s):
Energy
Fluid mechanics

Keywords:
aerodynamics
wake flows
wind turbine

Research group(s): TFL
Collaborations: Collaboration with UMONS - Prof. Bricteux

  

Recent publications

See complete list of publications

Conference Papers


1. Lejeune, Maxime; Moens, Maud; Coquelet, Marion; Coudou, Nicolas; Chatelain, Philippe. Development of an online wind turbine wake model. http://hdl.handle.net/2078.1/228689

2. Lejeune, Maxime; Coquelet, Marion; Coudou, Nicolas; Moens, Maud; Chatelain, Philippe. Development and validation of a wake model fed by blade loads estimated wind conditions. http://hdl.handle.net/2078.1/225816

3. Lejeune, Maxime; Coquelet, Marion; Moens, Maud; Chatelain, Philippe. Characterisation and Online Update of a Vorticity-Based Wind Skeleton Wake Model. http://hdl.handle.net/2078.1/225804

4. Coquelet, Marion; Lejeune, Maxime; Moens, Maud; Bricteux, Laurent; Chatelain, Philippe. Local estimation of wind speed and turbulence using wind turbine blades as sensors. http://hdl.handle.net/2078.1/225970

5. Coquelet, Marion; Bricteux, Laurent; Lejeune, Maxime; Chatelain, Philippe. Biomimetic individual pitch control for wind turbines. http://hdl.handle.net/2078.1/225986

6. Lejeune, Maxime; Coquelet, Marion; Coudou, Nicolas; Moens, Maud; Chatelain, Philippe. Data assimilation for the prediction of wake trajectories within wind farms. http://hdl.handle.net/2078.1/225821