MegAWES is a reference design and simulation framework for ground-generation, fixed-wing airborne wind energy systems with a nominal power output of 3 MW. The winch size of MegAWES is based on a smaller system and needs to be scaled up because the current size leads to unrealistically fast dynamics, which require saturation. However, there is no available method to select an appropriate size for the winch. Additionally, while it has been hypothesized that the size of the winch has a significant effect on the dynamics of the overall system for ground-generation concepts, this effect has not been quantified. In this work, we first analyze the effects of the winch size on the system dynamics using a linearized model. Second, we present a method to find the upper bound for the size of the winch based on a selected maximum tether force overshoot during nominal operation. Third, we apply this method to find an upper bound for the winch size for the MegAWES reference design. Using the nonlinear MegAWES simulation framework, we validated this upper bound. At the upper bound, the system accurately tracked the reference tether force without overshoot and when exceeding our upper bound, the tether force response was oscillatory and overshot its ideal value.

High aerodynamic efficiency is a key design driver for airborne wind energy systems as it strongly affects the achievable energy output. Conventional fixed-wing systems generally use aerofoils with a high thickness-to-chord ratio to achieve high efficiency and wing loading. The box wing concept suits thinner aerofoils as the load distribution can be changed with a lower wing span and structural reinforcements between the upper and lower wings. This paper presents an open-source toolchain for reliable aerodynamic simulations of parameterized box wing configurations, automating the design, meshing, and simulation setup processes. The aerodynamic tools include the steady 3D panel method solver APAME and the CFD-solver OpenFOAM, which use a steady Reynolds-Averaged Navier–Stokes approach with k- (Formula presented.) SST turbulence model. The finite-volume mesh for the CFD-solver is generated automatically with Pointwise using eight physical design parameters, five aerofoil profiles and mesh refinement specifications. The panel method provided accurate and fast results in the linear lift region. For higher angles of attack, CFD simulations with high- to medium-quality meshes were required to obtain good agreement with measured lift and drag coefficients. The CFD simulations showed that the upper wing stall lagged behind the lower wing, increasing the stall angle of attack compared to conventional fixed-wing kites. In addition, the wing tip boundary layer separation was delayed compared to the wing root for the straight rectangular box wing. Choosing the design point and operational envelope wisely can enhance the aerodynamic performance of airborne wind energy kites, which are generally operated at a large angle of attack to maximise the wing loading and tether force, and through that, the power output of the system.

Currently developed airborne wind energy systems have reached sizes of up to several hundred kilowatts. This paper presents the high-level design and a six-degrees-of-freedom model of a future fixed-wing airborne wind energy system operated in pumping cycles. This framework is intended to be used as an open-source reference system. The fixed-wing aircraft has a span of 42.5 m and produces a nominal electrical power of 3 MW. The ground station is modelled as a winch with a rotational degree of freedom describing the reel-in and reel-out motion, constant drum diameter and drive train inertia. A quasi-static approach is used to model the relatively stiff tether. The tether is discretised by 16 segments with variable length to account for reeling. A tracking controller ensures the kite's flight path during the autonomous pumping cycle operation. The controller alternates between crosswind figure-of-eight manoeuvres while reeling out and gliding on an arc-shaped path towards the ground station during retraction. The operational and controller parameters are determined using a CMA-ES evolution algorithm to maximise the average cycle power of a specific kite design at different wind speeds and given operational constraints. The algorithm identifies optimised flight paths for a range of wind speeds up to 30 m s⁻¹ leading to a power curve with a cut-in wind speed of 10 m s⁻¹ at operating altitude.

In this paper, we present the design and computational model of a representative multi-megawatt airborne wind energy (AWE) system, together with a simulation framework that accounts for the flight dynamics of the fixed-wing aircraft and the sagging of the tether, combining this with flight control and optimisation strategies to derive the power curve of the system. The computational model is based on a point mass approximation of the aircraft, a discretisation of the tether by five elastic segments and a rotational degree of freedom of the winch. The aircraft has a wing surface area of 150 m² and is operated in pumping cycles, alternating between crosswind flight manoeuvres during reel out of the tether, and rapid decent towards the ground station during reel in. To maximise the net cycle power, we keep the design parameters of the aircraft constant, while tuning the operational and controller parameters for different wind speeds and given contraints. We find that the presented design can generate a net cycle power of up to 3.8 megawatts.