Numerical optimal control methods for robustness optimization of multi-wing airborne wind energy systems

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Airborne Wind Energy (AWE) is a renewable energy technology that aims at harvesting high-altitude winds that cannot be reached by conventional wind turbines, at a fraction of the resources of the latter. It does so by discarding the foundation, tower and inner rotor parts of a conventional wind turbine, and by replacing the rotor tips by tethered autonomous wings that fly fast crosswind maneuvers. Electricity is most commonly generated via small turbines on board of the wing, or by the periodic reeling-out and -in of the tether to drive a winch on the ground. One of the main challenges to establish AWE as a viable renewable energy technology will be the cost-effectiveness at utility-scale, which is closely related to the power density that can be achieved by AWE systems in farm configurations. Currently, state-of-the-art AWE systems are almost exclusively based on single-wing configurations, characterized by a large trajectory footprint and a limited operating height. For reasons of safety and efficiency, these systems hence require a similar farm spacing as conventional wind turbines. By contrast, in multi-wing AWE systems (MW-AWES), multiple tethered wings fly circular crosswind trajectories around a shared main tether enabling more compact trajectories at almost arbitrary operating heights. Hence, they can be packed more closely together on the ground, while being stacked vertically to avoid wake interaction. Therefore, MW-AWES potentially offer higher power densities with respect to the farm's ground area. Moreover, MW-AWES designs typically double the system efficiency compared to single-wing designs, and they have beneficial, modular, up-scaling properties. However, multi-wing configurations come with a considerably increased level of complexity, and so far, MW-AWES were only investigated in computer simulations, to a significant part by the applicant’s research group. The overall aim of this proposed research project is to lay the groundwork for the robust and autonomous operation of MW-AWES. To achieve this, we formulate three objectives. The first objective is to develop efficient problem formulations for robustness optimization of MW-AWES. This should allow to plan coordinated multi-wing flight paths that satisfy interdependent constraints robustly. The second objective is to develop numerical algorithms for state estimation and model predictive control of MW-AWES. The outcome of this work should allow for online planning of disturbance rejection maneuvers for the overall multi-wing system over a long time horizon. The third objective is to develop algorithms for the optimization of MW-AWES trajectories based on high-fidelity models, in particular in order to account for induction effects in the wind field. This will close an important gap to be able to obtain accurate flight paths and performance predictions for yearly average power output or attainable power densities.