PhD Student - Wind Energy
Maxime Lejeune joined the iMMC/TFL in 2018 after obtaining a master degree in Mechanical Engineering at the Université catholique de Louvain. His work focuses on the development of smarter wind farm controllers accounting for wake interactions, aimed at decreasing the Levelized Cost of Energy of wind energy.
In the recent years, Model Predictive Control has gained an increasing amount of attention from the wind turbine control community. Today, it is even envisioned as one of the most promising approaches to alleviate wake effects within windfarms. Maxime Lejeune works toward the development of a physic-based surrogate wake model deployable in the wind turbine optimal control framework.
At this stage, the wake model developed is able to reconstruct the velocity profile downstream a wind turbine based on its load, operating settings and wind sensors. His current work therefore investigates joint state-parameter correction strategies in an attempt to achieve simultaneous correction and tuning of the model. Improving the accuracy of the model is indeed one of the pivotal challenge faced by the Model Predictive Control approach since excessive mismatch between the surrogate model predictions and the reality would lead to catastrophic performances of the controller synthetized.