Accurate aero-structural modelling of leading-edge inflatable kites is essential for scaling up airborne wind energy systems. Yet, existing approaches make simplifications on either the wing or the bridle line system. This paper presents a fast finite element modelling framework that integrates the wing structure and bridle lines into a single model. The finite element framework captures material and geometric non-linearities using the Newton–Raphson scheme with a co-rotational formulation. The bridle line system is represented using non-compressive springs, which are also used to represent pulleys. Inflatable leading edge and strut tubes are modelled as Timoshenko beam elements, with beam properties tuned iteratively to match experimentally fitted inflatable beam equations. The canopy is represented using non-compressive spring elements, allowing for the resolving of billowing effects. The framework is applied to the V3 kite, and validation is performed against stereoscopic photogrammetry measurements obtained from static load tests under varying internal pressures and external loads. The results demonstrate good agreement with measured kite shapes for most cases, confirming the model’s ability to capture the dominant structural behaviour of leading-edge inflatable kites. The proposed framework provides a basis for aero-structural analysis in kite design, and enables future coupling with aerodynamic models for steady and quasi-steady kite simulations. ... Read more

Airborne Wind Energy (AWE) generates renewable power by using tethered flying devices to access stronger winds at high altitudes. The Kitepower system uses a soft-wing kite that produces electricity during cyclic crosswind operation: energy is generated as the tether reels out under high tension, while the reel-in phase consumes less energy due to lower aerodynamic forces. However, the reel-in phase remains inefficient and susceptible to stall under low apparent wind conditions. This thesis develops control strategies to improve reel-in performance using active depower control, which adjusts the kite’s angle of attack. A non-linear four-point kite model was analysed to obtain trimmed parking states for linearisation. Quasi-steady reel-in trimming proved inconclusive, revealing methodological limitations. Controllers designed using H∞ synthesis improved stability under wind disturbances and reduced reliance on winch actuation. Results show active depower control enhances stability and efficiency, providing a foundation for future robust control development across broader operating conditions. ... Read more

The transition to sustainable energy sources is increasingly urgent, driving innovation in renewable energy technologies. Airborne wind energy (AWE) is a promising emerging alternative to conventional wind turbines, using tethered kites to harvest wind energy at higher altitudes where wind speeds are stronger and more consistent, while requiring significantly less material. Kitepower B.V. employs a leading-edge inflatable (LEI) kite flying in crosswind patterns to generate traction force on a tether that is reeled out from a ground-based drum connected to a generator. Energy is produced through repeated reel-out and energy-efficient reel-in cycles. As Kitepower is currently in active development, the kite design process requires many iterative design cycles and extensive testing, which are time-consuming, expensive, and heavily reliant on expert knowledge. This thesis investigates the application of multidisciplinary design analysis and optimisation (MDAO) to the geometric design of a LEI kite for ground-generation crosswind AWE systems, with specific focus on the system developed by Kitepower B.V. A computational framework is propose that integrates kite shape parametrisation, aerodynamic and structural analysis, and performance modelling within an MDAO toolchain. The kite geometry is described using a set of decoupled parameters that enable systematic reshaping while maintaining consistent reference properties. Two simulation frameworks are proposed to support this concept. The first is a conceptual high-fidelity toolchain that integrates aerodynamic, structural, and dynamic performance models, intended to guide future development of a fully coupled MDAO environment. The second is a simplified, computationally efficient toolchain that was implemented to enable quantitative optimisation under realistic time constraints. Using annual energy production as the optimisation objective, the implemented toolchain is employed to verify the optimisation methods and evaluate performance improvements relative to a reference kite design within a constrained design space. The results demonstrate that MDAO can effectively support early-stage geometric kite design for AWE applications, offering a fast, systematic alternative to traditional expert-driven design iteration.
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Quantitative in-flight deformation data are required to validate coupled aero-structural models of soft-wing kites. This work presents an end-to-end measurement framework that combines stereoscopic photogrammetry with ultra-wideband (UWB) ranging on an instrumented Gamma-shaped bar to reconstruct large-scale wing deformations under operational conditions. Stereo marker tracking yields a 3D point cloud that is corrected using UWB-derived span information, enabling robust shape comparison across manoeuvres. Deformation states are quantified for depowering and turning and are compared against a commonly used undeformed CAD reference employed in aerodynamic analyses. The resulting dataset improves the quantitative characterisation of soft-wing deformation and provides validation input for aero-structural models, supporting improved kite design and providing a pathway towards deformation-aware monitoring and (near) real-time control. ... Read more

This study aims to develop a regression model of the aerodynamic coefficients for leading edge inflatable (LEI) kite profiles. Aerodynamic data is obtained by 2D computational fluid dynamics (CFD) simulations for different Reynolds numbers, angle of attack and profile configuration, leading to the following: lift, drag and moment coefficients, as well as the surface distribution of pressure and skin friction coefficients. The machine learning regression model is trained on this multidimensional dataset to generate accurate 2D aerodynamic predictions, which serve as essential input for the vortex step method (VSM), a fast aerodynamic solver used in kite fluid-structure interaction (FSI) simulations.

The profile geometry parameterisation forms the backbone of the automated CFD toolchain. It provides an advanced and robust design framework for LEI kite profiles. The geometry is defined by its main components: a circular leading edge (LE) tube and a canopy, which is subdivided into two splines. The front spline connects the LE tube seam (i.e., the LE tube–canopy stitching connection) to the maximum camber point, while the rear spline extends from this point to the trailing edge (TE). Both splines are modelled as cubic Bézier curves with four control points, where the first and last points define the connection boundaries, enabling smooth and flexible surface shaping. The seam angle on the LE tube is dynamically calculated to ensure a smooth transition for any given configuration. The positions of the control points are governed by the following non-dimensionalised profile parameters, defined relative to the chord: LE diameter t, maximum camber chordwise position η, camber height κ, reflex angle δ, camber tension λ, and LE curvature φ. For meshing purposes, a finite thickness is assigned to the canopy to separate the upper and lower flow regions. Additionally, a LE fillet is added to the underside of the canopy to facilitate mesh smoothing at the sharp corner connection with the LE tube.

Aerodynamic data is collected from steady Reynolds-averaged Navier–Stokes (RANS) simulations, employing the k-omega shear stress transport (SST) turbulence model. The simulations are performed with the open-source CFD software OpenFOAM, using structured meshes generated in Pointwise. An extensive mesh sensitivity analysis was conducted, focusing on the effects of canopy thickness, the LE fillet, and the resolution of the fully structured grid in both normal and tangential directions. Transition modelling was omitted based on the assumption that the boundary layer undergoes forced transition at the LE tube seams. This includes the LE tube-canopy connection on the upper side and the LE closing seam on the lower side, where numerical results indicated that the flow transitions due to seam-induced roughness. Since the region upstream of the seams is small, its impact is considered negligible, justifying the simplification.

Due to the large number of simulations required, computational resources from the high-performance computing (HPC) cluster of the Faculty of Aerospace Engineering at TU Delft were utilised. To define the parameter configurations for data collection, a trade-off was made between parameter resolution and computational cost. Parameters were sampled across the following ranges for three Reynolds numbers (Re = 1 x 10^6, 5 x 10^6, and 2 x 10^7): α from -22° to -10° (13 values), t from 0.03 to 0.12 (5 values), η from 0.08 to 0.4 (8 values), κ from 0.04 to 0.16 (7 values), δ from -8° to 0° (4 values), and λ from 0.1 to 0.4 (4 values). The LE curvature φ was held constant at 0.65.

The flow fields were analysed for the effects on the newly introduced parameters in the updated profile geometry model: δ, λ, and φ. Downward deflections of the profile TE due to negative δ resulted in reduced lift and increased drag performance, while enhancing longitudinal pitching moment stability. In contrast, variations in λ showed the opposite effect; increased camber tension resulted in higher lift and drag values but diminished longitudinal stability. The parameter φ, having minimal geometric influence, caused negligible changes in aerodynamic performance, only slightly altering the pressure distribution. Consequently, φ was fixed in the regression model. Among all tested algorithms, the extra trees (ET) model achieved the highest predictive accuracy, with R2 scores of 0.987 for Re = 1 x 10^6, 0.988 for 5 x 10^6, and 0.989 for 2 x 10^7.

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This thesis presents the development, implementation, and validation of a low-fidelity Aeroacoustic Prediction Framework designed for airborne wind energy systems (AWES), with the Kitepower system as a case study. As AWES technology moves toward commercial viability, understanding and predicting its acoustic emissions becomes critical for regulatory compliance, public acceptance, and design optimization.
The framework integrates established analytical and semi-empirical aeroacoustic models with aerodynamic data based on derived geometry and detailed flight information. It models all major noise sources from the airborne components, such as the Leading Edge Inflatable (LEI) kite, bridle lines, tether, and onboard ram-air turbine. The most significant contributions to the overall noise signature were found to be turbulent boundary layer trailing edge (TBL-TE) noise from airfoils, modeled using the Brooks–Pope–Marcolini (BPM) approach, vortex-shedding noise from cylindrical structures such as the tether and bridle lines, and tonal harmonics produced by the rotating turbine blades, captured through Hanson’s helicoidal surface theory.
To generate aerodynamic input, spanwise airfoil profiles were automatically extracted from 3D CAD models and analyzed through XFOIL. Real-time flight data was provided by an onboard sensor suite and processed through an Extended Kalman Filter (EKF), allowing dynamic simulation of flight conditions. Audio recordings were collected during test flights using GoPro cameras, enabling experimental validation of the acoustic predictions despite the absence of calibrated SPL measurements.
Validation showed strong agreement between predicted and measured spectra up to 5 kHz, particularly for turbine harmonics and general spectral shape. Deviations in the lower tonal harmonics were primarily attributed to acoustic shielding caused by the turbine’s duct structure. Additionally, the use of GoPro cameras introduced limitations due to their lack of calibration data and the presence of internal low-pass filtering above 5 kHz. Despite these constraints, the model successfully predicted tonal peaks, including the blade passing frequency and higher-order harmonics, aligning well with the experimental observations.
Additionally, the framework investigates the influence of the propagation effects, such as atmospheric absorption and geometric spreading, and integrates them to produce realistic observer-based predictions. Despite using non-professional audio hardware, the predictions captured key features including harmonic roll-off and broadband trends, affirming the framework's validity for early-stage design and evaluation.
This work demonstrates that low-order, physics-based models paired with aerodynamic inputs and synchronized flight data can yield meaningful acoustic predictions for AWES. The framework offers modularity, computational efficiency, and adaptability for future upgrades, such as the use of calibrated microphones or high-fidelity CFD data. It serves as a foundation for future extensions in auralization, psychoacoustic testing, and component-level noise reduction strategies.
Ultimately, the thesis bridges theoretical modeling with field-based validation, supporting the responsible integration of AWES technologies into noise-sensitive environments. ... Read more

This study investigates the aerodynamic behaviour of two-dimensional rigid leading-edge inflatable (LEI) airfoils through experiments in TU Delft’s Low Turbulence Tunnel and computational fluid dynamics (CFD) simulations. Lift and drag coefficients were measured for two steel scale models at Reynolds numbers of 5×10⁵ and 10⁶ and angles of attack between −10° and 25°. Corrections were applied for wall and wake-rake effects, and transition behaviour was analysed using infrared imaging and oil flow visualization. CFD simulations using OpenFOAM with the k–ω and 𝛾 − R̃e𝜃t models were compared to the experimental data. Fully turbulent CFD results showed the best agreement with measurements, while transition models performed inconsistently. Infrared and oil-flow data revealed fixed or moving transition zones, corner eddies, and a laminar separation bubble. This work provides the first dedicated experimental dataset for rigid LEI airfoils and validates CFD toolchains for future aerodynamic analysis of soft-wing kites. ... Read more

Airborne wind energy (AWE) is an emerging technology that differs in operating principles from horizontal axis wind turbines (HAWTs). It uses tethered flying devices to harness higher-altitude wind resources. The primary motivation for AWE development lies in its potential to deliver similar energy output at lower costs and reduced carbon emissions compared to wind turbines of equivalent power ratings. AWE is in its early development stage, with commercial prototypes reaching power outputs of up to several hundred kilowatts. At this early stage of technology development, the AWE industry can significantly benefit from a systems-level understanding of the technology. To this end, the work reported here developed a multi-disciplinary design, analysis and optimisation (MDAO) tool for the conceptual system design of an AWE device and applied it to identify key design drivers, trade-offs and the scaling potential of a chosen AWE concept.

The MDAO tool is a framework that integrates models, including wind resources, power production, energy production and costs. As part of this research, new models were developed to enable the framework’s functionality. This study focused on the fixed-wing ground-generation (GG) concept of AWE. Still, the proposed methodology can be applied to any AWE concept depending on the availability of individual models tailored to the particular concept. In most markets, performance is measured using a metric known as the levelised cost of energy (LCoE). This metric relates the system's total costs to the energy it can produce over its lifetime. This metric is used here as the objective for system design, evaluating trade-offs and scaling analysis.
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Airborne wind energy (AWE) is an emerging renewable technology that generates electricity using tethered flying devices, such as kites. It harvests wind energy at higher altitudes than conventional wind turbines. As the technology nears commercialization, its successful deployment will depend not only on technical and economic feasibility but also on social acceptance. Understanding how communities perceive and are affected by AWE can help ensure smoother deployment, protect community well-being, and enhance contribution to renewable energy goals.

This dissertation is among the first research to systematically investigate the social dimensions of AWE, focusing on community acceptance – residents’ approval of local energy projects – and its influencing factors. The research is based on surveys conducted with residents near AWE test sites in Europe and a laboratory listening experiment to assess reactions to AWE-related sound emissions. The findings demonstrate that community acceptance of AWE projects relates to a combination of technical characteristics, subjective perceptions, and the fairness and transparency of project implementation. In line with the applied Integrated Acceptance Model (IAM), stronger perceived impacts – such as sound emissions, landscape impacts, and aviation lights – were associated with lower levels of acceptance. At the same time, fair and transparent project implementation was linked to higher acceptance. Noise annoyance emerged as a critical factor, shaped by both psychoacoustic properties (i.e., sharpness, tonality, and loudness) and individual characteristics (i.e., noise sensitivity, familiarity with AWE, and age).

While most of the results align with research on wind turbine acceptance, some key differences emerge. Unlike for wind turbines, the remaining three IAM factors – perceived local economic benefits, expected community support for the project, and general attitudes toward the energy transition – did not significantly predict acceptance in the case of AWE. This may be due to the fact that the technology is still undergoing development and is not yet commercially available or contributing to renewable energy targets. As a result, economic and social considerations that are typically relevant for commercial energy projects may not yet be salient for communities living near AWE test sites.

The findings highlight the need to incorporate social science insights into AWE development from the outset. By investing in interdisciplinary research, developing targeted mitigation strategies, engaging with local communities meaningfully, and establishing robust regulatory frameworks, the AWE sector can avoid common pitfalls faced by established renewable energy technologies. The early stage of AWE presents an opportunity to learn from these experiences and take proactive steps to ensure that the technology is developed and deployed in a way that is both technically and socially viable. By anticipating and addressing potential social challenges early on, the sector can help ensure that AWE gains public trust and contributes to a just energy transition.

In addition to Dr. Roland Schmehl and Dr. Gerdien de Vries, this doctoral dissertation greatly benefited from the guidance of Dr. Reint Jan Renes (Amsterdam University of Applied Sciences). ... Read more

Airborne wind energy (AWE) systems harness wind power using devices flying in controlled patterns, with two main concepts: onboard power generation in the 'drag mode' and ground-based generation in the 'pumping cycle'. Quasi-steady state models (QSM) efficiently predict parameters like tether force and kite velocity for smaller AWE systems but the neglect of inertial forces leads to inaccuracies for bigger systems. Various formulations of quasi-steadiness exist in AWE literature, but their validity limits remain poorly understood. This research presents a theoretical framework specifically tailored to crosswind tethered flight dynamics, which is used to obtain a consistent definition of quasi-steadiness and to quantify the validity of this assumption, through extensive solution space analysis. The study finds that QSM provides reasonable accuracy for time-averaged quantities but fails to predict other aspects such as amplitude or phase. Limitations arise from the use of a steady aerodynamic model and assumptions of a rigid tether. ... Read more

The European Commission’s roadmap aims to install 60 GW of offshore wind energy by 2030 and 300 GW by 2050, requiring substantial raw materials. Airborne wind energy (AWE) offers a promising alternative with lower material demand and environmental impact. This thesis assesses the environmental impact of a 100 kW soft-kite AWE system using life cycle assessment (LCA). The target market for these AWE systems includes off-grid remote areas. Thus, a comparative LCA of hybrid power plant (HPP) configurations was conducted using site data from a military base in Marseille, France. Results show the Falcon AWE system has a GWP of 8.6 kg CO2 eq/MWh and CED of 144.1 MJ/MWh, with the ground station being the most impactful component. For the HPP, including diesel generators and batteries reduces the oversizing of renewable components, enhancing sustainability. Future recommendations include developing AWE-specific databases and evaluating more impact indicators. ... Read more

The WaveWings project seeks to harness the synergetic potential of Airborne Wind Energy Systems (AWES) and Wave Energy Converters (WEC) to create a 1 GW deep-offshore renewable energy farm, contributing to the European Union’s net-zero 2050 goals. This report details the design process and outcomes of integrating a Leading-Edge Inflatable (LEI) kite system with a point absorber wave energy converter (WEC). The LEI kite and point absorber generate 2.3 MW and 150 kW of power, respectively. Key trade-offs and design choices were made in selecting the kite, launch system, WEC, and anchoring mechanisms to optimize performance and sustainability. Sustainable design strategies are implemented to reduce the Levelised Cost Of Electricity (LCOE) and Global Warming Potential (GWP). The integration of the airborne and wave energy systems was optimized through simulations to maximize energy absorption and respect synergy requirements. Market and financial analyses indicated that WaveWings project can be competitive on the west coast of Ireland. ... Read more

This paper presents the design of a lab-scale silicon nitride photonic crystal lightsail, demonstrating the LightSailSim software package. LightSailSim, an open-source analysis pipeline, integrates a custom mechanical solver based on a particle system model with optical simulation results. The resulting design balances dynamic and structural stability with propulsive performance. It consists of an optimised photonic crystal that provides a suitable trade-off between stability and propulsive force. The sail is suspended at its edges by a circular ring made of silicon, providing sufficient boundary tension to prevent sail deformation-induced instability. The design is made such that it can be produced from a single silicon wafer and levitated using a single 400 W laser.
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Airborne wind energy (AWE) is a wind energy technology in the development phase consisting of tethered kites that reach high altitudes consisting of relatively stable wind speeds. While no company has yet reached the point of commercial viability, a variety of AWE technology concepts and designs have been under development and are currently at low- to intermediate technology readiness levels. When AWE systems are grid-connected a power smoothing element is needed to smooth the oscillating power output of the system for the grid. In this thesis, a framework for modeling a grid-connected hybrid power system (HPS) consisting of AWE and batteries participating in the day-ahead market (DAM) has been developed in the MATLAB environment. The framework incorporates an existing AWE performance and cost model with power smoothing performance, battery degradation, and DAM storage arbitrage. Multiple use case scenarios are evaluated to test the economic performance of multiple configurations of the HPS. These scenarios are; an AWE system with an ultracapacitor (UC); an AWE system with batteries; a battery system operating in DAM arbitrage and an AWE system with batteries operating in DAM arbitrage. The configurations were evaluated using multiple performance metrics, primarily the internal rate of return (IRR) as a metric for economic performance. A simulation of the HPS participating in storage arbitrage was then used to determine the economic viability of using the battery system for both power smoothing and arbitrage. The arbitrage behavior of the storage system was determined by a heuristic selling logic model developed to simulate the combined use of a storage system for power smoothing and arbitrage. The arbitrage logic is based on price volatility and power smoothing constraints.

The battery power smoothing system resulted in significantly lower system cost overall and consequently an increase in profitability (IRR of 12.37%) compared to the more expensive UC power smoothing configuration (IRR of 10.20%). The HPS configuration with batteries used for power smoothing combined with arbitrage showed a marginal increase in economic performance with an IRR of 12.43%. This showed a potential value increase of the system when using excess capacity arbitrage but not at a significant rate.
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Computational Fluid Dynamics (CFD) simulations of objects like the Kitepower V3A Leading Edge Inflatable (LEI) kite require accurate experimental data for validation. However, for these kites, particularly in steady-state simulations, such data is scarce. LEI kites are soft and deform continuously during flight, making validation complex. To address this, a unique experiment in the Open Jet Facility (OJF) at TU Delft, testing a rigidized subscale model of the V3A kite, marking the first wind tunnel test on a rigid kite.

The rigid model was made of carbon fiber reinforced polymer and mounted on a custom support structure that allowed adjustments to the kite’s angle of attack and sideslip. Aerodynamic forces and moments were measured at different wind speeds and orientations, with and without zigzag tape to study its effects on low Reynolds number flow.

The results were compared to existing CFD simulations, including Reynolds-Averaged Navier-Stokes (RANS) and vortex step methods. The experimental data aligned well with these simulations at low Reynolds numbers, validating the setup. However, some discrepancies highlighted areas for improvement, such as reducing interference from the support structure and better matching Reynolds numbers between simulations and experiments. ... Read more

Airborne wind energy (AWE) is a novel concept aiming to substantially reduce the material demand and environmental impact of wind energy generation. AWE systems can also access steadier and stronger wind at higher altitudes, which is inaccessible to conventional wind turbines. The lower material effort, the increased capacity factor, and the access to so-far unused wind resources render AWE a potential cornerstone in a future low-carbon energy economy. The new conversion concept is currently being demonstrated by several start-up companies using different technical implementations at different maturity levels. The unifying challenge for commercialization is the operational robustness of the technology. For a successful market acceptance, the introduced aviation and ground-related safety risks need to be mitigated.

The present work aims to bring AWE closer to commercial success through two main contributions. As a first contribution, well-established practices of reliability engineering are used to measure and then systematically improve the safety and reliability of AWES systems. Experience from other safety-critical domains such as aviation, space, automotive, and medical are used to achieve this objective. A fault tree analysis (FTA) and failure mode and effects analysis (FMEA) are applied to an existing demonstrator system. A common practice in the safety-critical domain is automatically monitoring the system's health and taking action in case of faults. In this regard, a systematic fault detection isolation and recovery (FDIR) model is proposed for AWES. This architecture is generally applicable and flexible and can be applied to different AWE systems.

After reaching the required reliability and safety levels, formalization by the certification authorities is required. As a second contribution, the current regulatory framework is reviewed, the relevant authorities identified and a roadmap for aviation certification is presented. The ``Specific Operations Risk Assessment'' (SORA) by the Joint Authorities for Rulemaking on Unmanned Systems (JARUS) is a comprehensive and well-structured framework. Therefore, following the SORA is considered the best way forward to get the flying permit for AWES, claiming the ``specific'' category from the European Union Aviation Safety Agency (EASA) regulation. This permit is applicable for commercial operations in Europe. Other civil aviation authorities may also recognize the EASA's flying permit. In this respect, the SORA is applied to a hypothetical commercial operation scenario, and requirements for the flying permit are discussed. ... Read more

The potential of utility-scale airborne wind energy (AWE) systems to contribute significantly to the energy transition hinges on their large-scale deployment, which depends on the cost-competitiveness and complementarity with conventional wind turbines. Central to the assessment of these metrics is understanding long-term energy production, which is influenced by the variability of wind profiles. This thesis investigates the significance of wind profile variability on annual energy production estimation for AWE systems. The study establishes the climatology of vertical wind profiles and expands flight operation models of AWE systems. By synthesising these aspects, a new energy production estimation framework is developed to incorporate variations in the wind profile shape. This framework is utilised to assess the impact of different wind profile shapes on the energy production estimation. The research underlines the need to move away from conventional wind energy calculation methods and offers a more suitable alternative for AWE systems. The framework offers a valuable tool for increasing the understanding of the viability of large-scale deployment of AWE systems. ... Read more

Power output during flight operation of multi-megawatt airborne wind energy systems is substantially affected by the mass of the airborne subsystem, resulting in power fluctuations. In this paper, an approach to control the tether force using the airborne subsystem is presented that improves the quality of the power output. This kite tether force control concept is implemented on the 3DOF dynamic simulation of the MegAWES reference model. First, the winch of MegAWES is resized because an analysis of winch inertia and radius shows its effect on power output and tether force overshoot. Second, the power consuming sections during the traction phase are eliminated by using a feedforward winch controller. Finally, the peak power is substantially reduced by implementing the kite tether force controller which uses a measurement of the tether force, angle of attack, and airspeed to keep the tether force constant when the system is at its power limit. This reduces the range between minimum and maximum power output by 75%. ... Read more

The aim of this executive overview is to summarise the content of this extensive report regarding the design of an Landing, Launching and Storage (LLS) system for a soft kite Airborne Wind Energy (AWE) system.
An innovative idea does not translate automatically to financial gain. With new technologies, such as AWEs it is crucial to assess the potential market for a product and the associated economic performance. Four market segments exist for energy generation: on-shore on-grid, on-shore off-grid, off-shore on-grid and off-shore off-grid. AWE performs best in on-shore offgrid applications due to its high mobility, higher capacity factor compared to wind and relatively lower land usage. AWE soft kites are currently targeting 100 kW to 500 kW range, which is currently dominated by medium-power diesel generators. ... Read more

Airborne wind energy systems offer a promising approach for renewable energy generation. However, the noise emissions associated with these systems should be understood and minimized as well to promote their integration and (social) acceptance. This research aims to identify the noise sources of airborne wind energy systems, systems with leading-edge inflatable (LEI) kites and fixed-wing kites in particular, and establish a foundation for future research in this field. Analytical simulations using the Brooks, Pope, and Marcolini model and the Amiet model were combined with experimental measurements for this research.

The analysis of the fixed-wing kite revealed prominent peaks around 1500 Hz and 2000 Hz in the noise spectra, with the higher frequency peak observed at higher kite velocities. Analytical predictions indicated laminar boundary layer vortex shedding and tether vortex shedding as the main noise sources. The study also investigated the directivity of the turbulent boundary layer trailing edge noise, which revealed dipoles that exhibited slight deformations at higher frequencies.

For the LEI kite, noise analysis identified peaks in the sound pressure level around 300-400 Hz and 1000-2000 Hz. Analytical predictions highlighted turbulent boundary layer trailing edge noise and vortex shedding from the tether and bridle lines as the dominant noise sources.

By considering the implications of these findings, the noise impact of airborne wind energy systems can be minimized, fostering their sustainable deployment and acceptance. ... Read more