Wind energy is expected to play a key role in the future energy mix, but the increasing size of conventional wind turbines poses growing structural and material challenges. Airborne wind energy (AWE) offers a promising alternative; however, its large-scale deployment requires further studies of airborne wind energy system (AWES) operation under turbulent conditions and within wind farms. This work proposes a framework based on computational fluid dynamics for studying AWES in ambient turbulent wind and wakes, as will be encountered when arranged in farms. The present work focuses on ground-gen rigid-wing AWESs. The framework relies on a large-eddy simulation flow solver, in which the kites are represented using a model based on an actuator line for the main wing with its ailerons and complemented with models for the tail control surfaces (rudder and elevator). The flow solver is coupled, via a two-way coupling, to a control module based on model predictive control, to follow optimal trajectories. The framework is presented in some detail and is then used to investigate the MegAWES aircraft, a MW-scale AWES of 42.5 m wingspan, here flying four-loop trajectories. The first part of the investigation focuses on a single system. Its ability to fly in a turbulent wind is demonstrated and analyzed, and its wake is also characterized. It is demonstrated that the controlled kite can handle the turbulent wind. The deviation from its reference trajectory is less than 15 % of the wingspan. In the second part of the paper, a tandem configuration is considered, with the same four-loop trajectory for each kite. It is found that there is a configuration where the second kite, even fully aligned with the first one, can fly in unperturbed flow (other than the turbulence of the wind). A second case is investigated where the second kite is forced to fly in the wake from the first one. It is found that the wake produced by the first kite does not compromise the trajectory tracking of the second kite. However, the second kite feels the velocity deficit, and its power production is reduced by 6 %.
Crismer, J.-B., Haas, T., Duponcheel, M., & Winckelmans, G. (2026). Large-eddy simulation of airborne wind energy systems flying in turbulent wind using model predictive control. Wind Energy Science, 11(7), 2669-2694. https://doi.org/10.5194/wes-11-2669-2026 (Original work published 2026)