Leading-edge inflatable (LEI) kites are morphing aerodynamic surfaces that are actuated by the bridle line system. Their design as tensile membrane structures has several implications for aerodynamic performance. Because of the pronounced C shape of the wings, a considerable part of the aerodynamic forces is redirected sideways and used for steering. The inflated tubular frame introduces flow recirculation zones on the pressure side of the wing. In this paper, we present wind tunnel measurements of a 1:6.5 rigid-scale model of the 25 ^m2 TU Delft V3 LEI kite developed specifically for airborne wind energy (AWE) harvesting. Aerodynamic forces and moments were recorded in an open-jet wind tunnel over wide ranges of flow conditions, including angles of attack from -11.6 to 24.5°, sideslip angles from -20 to 20°, and freestream velocities from 5 to 25 m^s-1. The wind tunnel measurements were performed with and without zigzag tape along the model's leading edge to investigate the possible boundary layer tripping effect of the stitching seam connecting the canopy to the inflated tube. At a Reynolds number of 5×¹⁰⁵, the addition of zigzag tape was found to reduce lift and increase drag, indicating a negative impact on aerodynamic performance. The rigid-scale model was manufactured to match the undeformed geometry employed in Reynolds-averaged Navier–Stokes (RANS) simulations from the literature, rather than the unknown in-flight deformed geometry. A representative subset of the measurements was used to benchmark both these RANS and new vortex-step method simulations. Both computational methods successfully reproduced the measured trends under nominal operating conditions. While the post-stall discrepancy persists, excellent agreement was observed for lift, drag, and side force coefficients, with lift deviations remaining within the 10% range.

Airborne wind energy (AWE) harnesses higher-altitude winds using kites to generate renewable electricity. As AWE technologies move closer to potential commercialization, understanding how local communities interact with and are affected by these technologies is crucial for socially responsible deployment. Identifying key predictors of community acceptance can help develop targeted measures to address potential impacts while the technology is still adaptable. This study tested the Integrated Acceptance Model (IAM) on survey data from two European AWE test sites. A linear regression analysis revealed that two of the five explanatory variables significantly predicted acceptance: perceived site impacts (e.g., sound emissions, landscape changes, and aviation lights), as well as developer transparency and fairness in site operations. In contrast, attitudes toward the energy transition, perceived economic impacts, and social norms did not predict acceptance. These findings suggest that while AWE developers prioritize technical challenges, attention must also be given to social factors, such as minimizing impacts and ensuring transparent and fair implementation. The results also have important policy implications, highlighting the need for AWE-specific regulations and socially responsible planning practices. Further research is required to investigate additional acceptance predictors, especially if AWE technologies continue to develop toward commercial applications.

Airborne wind energy (AWE) is an innovative technology that differs from the operating principles of horizontal axis wind turbines (HAWTs). It uses tethered flying devices, denoted as kites, to harvest higher-altitude wind resources. Kites eliminate the need for a tower but introduce a penalty in power generation since the kite has to spend part of its aerodynamic force to counter its weight. The differences between the two technologies lead to different scaling behaviours, and understanding these as well as the design drivers of AWE systems is essential for developing this technology further. To this end, we developed a multidisciplinary design, analysis, and optimisation (MDAO) framework which employs models evaluating the wind resource, power curve, energy production, overall component and operation costs, and various economic metrics. This framework was used to design fixed-wing ground-generation (GG) AWE systems based on the objective of minimising the levelised cost of energy (LCoE). The variables used to define the system were the wing area, aspect ratio, tether diameter, and rated power of the generator. The framework was employed to find optimal system designs for rated power ranging from 100 to 2000 kW. The results show that kite mass, energy storage, and tether replacements are the key LCoE driving factors. Moreover, in contradistinction to HAWTs, the total lifetime operational costs are equal to or higher than the initial investment costs. This distribution of costs over the project's lifetime, rather than as a large upfront investment, could make it easier to secure project financing. The scaling results show that the LCoE-driven optimum lies within the 100 to 1000 kW system size. The reason for this is that the kite mass penalty increases the cut-in and rated wind speeds, reducing the capacity factor of the larger systems. Sensitivity analyses with respect to extreme scenarios considering technological advancements, financial uncertainties, and environmental conditions show that this optimum is robust within our modelling assumptions.

Three unsteady aerodynamic tools at different levels of fidelity and computational cost were used to investigate the unsteady aerodynamic behavior of a delta kite applied to airborne wind energy. The first tool is an in-house unsteady panel method that is fast but delivers low to mid fidelity predictions. The second tool uses the open-source CFD code SU2 to solve the unsteady Reynolds-averaged Navier–Stokes equations with the (Formula presented.) SST turbulence model. At an intermediate level of fidelity, a semiempirical dynamic stall model that combines the panel method with a phenomenological dynamic stall module is proposed. The latter has free parameters that are fine-tuned with CFD results from the second tool. The research on the dynamic stall model has been inspired by two flight test campaigns suggesting dynamic stall phenomena possibly driven by the periodic variation of the angle of attack (aerodynamic pitching motion) during crosswind maneuvers. The recorded inflow along the flight path was prescribed in the three aerodynamic tools. As expected, the price to pay for the low computational cost of the panel method is its inability to capture the dynamic stall phenomenon. The results from unsteady CFD qualitatively matched the experimental data identifying a leading-edge vortex that forms and detaches cyclically during the pitching motion. Using RANS data, the semiempirical tool was fined-tuned to reproduce the dynamic stall behavior, becoming an accurate and fast aerodynamic tool for coupling with any kite flight simulator. Further discussions on the effects of kite aerostructural deflections are included.

This paper presents a quasi-steady simulation framework for soft-wing kites with suspended control unit employed for airborne wind energy. The kites are subject to actuation-induced and aero-elastic deformation and are described by a coupled aero-structural model in a virtual wind tunnel setup. Key contributions of the present work are a kinetic dynamic relaxation algorithm and a procedure to define a physically consistent initial state. For symmetric actuation, the kite is pitch-statically stable and the simulations converge to a static equilibrium state. Most soft-wing kites are not roll-statically stable and do not find a static equilibrium without a symmetry assumption, as this introduces non-zero roll- and yaw moments. Another important contribution is the introduction of a steady circular flight state that enables convergence without a symmetry assumption. By neglecting gravity, the kite can fly in a perfectly circular turning motion around the wind vector with a constant radius and constant rotational velocity without requiring active control input. In an idealized wind-aligned tether case, the difference in aerodynamic- and centrifugal force application centers makes it impossible to achieve both a force- and moment equilibrium. This was resolved by including an elevation angle that introduces a radial tether force component, which introduces a centrifugal and aerodynamic force difference. Therefore, an operating point with roll equilibrium can be found where the kite finds a static equilibrium, enabling the first quasi-steady simulations of turning flights. Simulated quantifications of soft-wing kite turning behavior, i.e., turning laws, contribute to better kite- and control design.

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.