Numerous dynamic stall models exist to improve aerodynamic modelling. As such, they play an integral part in aeroelastic analyses. In numerous publications, their qualitative damping effect on stall-induced instabilities of wind turbine blades compared to using quasi-steady aerodynamics has been proven. However, often different dynamic stall models are used without consideration of quantitative differences between aeroelastic predictions. Thus, the goal of this thesis is to quantify the damping effect of dynamic stall models on stall-induced instabilities. A model used in HAWC2, openFAST, one developed by IAG, and one unpublished model are compared amongst each other and in comparison to predictions with quasi-steady aerodynamics. A typical blade section at 75 % span of the DTU 10 MW reference wind turbine is modelled. The blade the section belongs to is facing vertically up at a pitch angle of 90° in parked conditions. The inflow ranges from 5 m/s to 50 m/s with yaw-misalignment angles from -25° to 25°. In comparison to using quasi-steady aerodynamics, the dynamic stall model from openFAST reduces the amplitude of edgewise limit cycle oscillations from maxima of 22.5 m to 7.2 m. The model from HAWC2 further reduces the maxima to 5.4 m. No edgewise limit cycle oscillations occur using the IAG or unpublished model. Instabilities other than limit cycle oscillations are not predicted. Analyses of the time series of dynamic stall parameters, dynamic lift, drag, and moment power, as well as the unsteady force and moment coefficient loops and aeroelastic damping ratios, did not trivially explain the models' different predictions.

When designing an airborne wind energy system, it is necessary to be able to estimate the traction force that the kite produces as a function of its flight trajectory. Being a flexible structure, the geometry of a soft kite depends on its aerodynamic loading and vice versa, which forms a complex fluid-structure interaction (FSI) problem.
Currently, kite design is usually done on an experimental basis since no model meets the requirements of being both accurate and fast.

In this project, an FSI methodology is developed to study the steady-state aerodynamic performance of leading-edge inflatable (LEI) kites by coupling two fast and simple models.

On the structural part, the deformations are calculated with a particle system model, based on the assumption that the shape of the kite can be modelled using a wireframe wing model represented by the bridle line attachment points, whose coordinate changes are modelled using a bridle
line system model and canopy billowing relations.

On the aerodynamic side, the load distribution is calculated with a 3D nonlinear vortex step method, coupled with 2D polars obtained with a correlation model derived from Reynolds averaged Navier-Stokes (RANS) analysis, to account for viscous effects and flow separation. Furthermore, with the 2D correlation model it is possible to consider changes in the thickness and the camber of each section. Based on 2D thin airfoil theory, the three-quarter chord point is used to determine the magnitude of the forces, and the one-quarter chord point is used to determine the direction of these forces.
Moreover, the model developed for LEI kites can consider canopy billowing and variations in kite and airfoil geometry while proving robust and inexpensive.
This model has been validated with several geometries and a RANS analysis of the LEI kite, showing great accuracy for pre-stall angles of attack.

The coupling of these two models results in a fast aeroelastic model of LEI kites capable of predicting the steady-state deformations and aerodynamic forces on the kite for the range of actuation settings and inflow conditions expected during a normal pumping cycle. Furthermore, the results show that the deformations follow the same trends as the results from the photogrammetry analysis and that, by taking into account the deformations that the kite undergoes, the aerodynamic forces more closely resemble experimental data.

In order to reduce the levelised cost of energy, the rotors of wind turbines are increasing in size. To increase the energy yield, wind turbine rotors need to have an innovative tip design; such as winglets. Winglets are used widely in aircraft design; however, they remain mostly absent in state-of-the-art wind turbine design. The low-fidelity wind turbine design models used by industry, such as BEM, are insufficient to capture the full 3D flow physics in such an innovative design. Therefore, high-fidelity methods, such as vortex methods, are becoming more and more important in such a design phase in wind energy research. Single-objective optimisation has been applied in earlier works to maximise power production. Winglets have shown the potential of increasing power production while simultaneously increasing the design-driving loads (DDLs), for example, the thrust or flapwise bending moment. This work focuses on optimisation using machine learning of a winglet that increases power production without increasing DDLs.

A parameterised design for a winglet on a wind turbine is created. Different design constraints, such as DDLs or a diameter constraint, are explored to determine under which constraints and conditions a winglet can have an added value to the wind turbine blade design. Multi-objective Bayesian optimisation is used to maximise the rotor's power production and minimise DDLs. Surrogate models, created using machine learning techniques such as Gaussian Processes and Bayesian Neural Networks, are used in combination with an acquisition function, to determine what designs should be evaluated by the lifting line model AWSM. This has the goal to obtain designs that lie on the Pareto front of two or more objectives. The recent Bayesian Neural Networks were able to find the Pareto front most effectively in this work. Furthermore, the results show that different DDL constraints led to different winglet designs, with noticeable differences between upwind and downwind winglet designs obtained by the optimiser. Both a downwind and upwind winglet were found to be able to increase power without increasing the thrust, root flapwise bending moment and flapwise bending moment at 80% of the rotor radius.

In the present world of conventional wind energy, the National Renewable Energy Laboratory (NREL) 5MW reference wind turbine for offshore system development has become an important piece of the puzzle towards a renewable future based on wind energy. DTU showed the benefit of such a reference model with their 10 MW reference wind turbine and continued the evolution in multi-megawatt wind power systems. Even though these two systems exist in the conventional wind turbine industry, a publicly available reference system does not exist in airborne wind energy. Currently, Airborne Wind Energy Systems (AWES) are still in the prototype testing phase as no commercial utility-scale product has been released to the market yet. A reference model like the NREL 5MW turbine can therefore significantly increase the speed of AWES development and open a door towards more publicly available research. This thesis solves the following main research question: "How does a multi-megawatt utility scale airborne wind energy reference system look like, focusing on the main wing parameters?". This is done by setting up a relatively computationally efficient optimisation framework based on a Fluid Structure Interaction (FSI) model combined with a flight dynamics simulation model which can be used in early design optimisations, for example. The FSI model consists of a 3D linear structural Finite Element model coupled with a potential-flow based 3D panel method. The aircraft structure is parametrised and parameters are found for an aircraft with a wing area of approximately 150 m2. The wing mesh and other structural components are created in Matlab while Nastran is exploited to obtain the stiffness, mass and inertia matrices. A model order reduction technique is applied to the structural model, relying on the mode superposition method to decrease the computation effort by several orders. The wing's aerodynamic behaviour is calculated by the 3D panel method. A model order reduction technique is also applied here, based on a Taylor expansion of the aerodynamic influence coefficient matrices. A modified fixed wing aircraft flight controller is used to fly a circular flight path where the ground station periodically allows the tether to be reeled out and in. The navigation of the aircraft is split up in two components, namely the lateral controller (based on a modification to the L1-control logic) and radial dynamics controller (depending on the elevator and tether reel-out behaviour). A Covariance Matrix Adaptation Evolution Strategy (CMAES) optimisation method is applied with a specific objective function to find the system design parameters. This work then presents a detailed representation of the aircraft design, consisting of the planform parameters, material choices and composite layup. It demonstrates the ability of the framework to obtain a wing that can sustain high wing loadings. Also the system performance in a full power cycle illustrates the full potential of a 150 m2 wing which is able to generate multiple megawatts of power. This thesis serves as a foundation of reference systems in airborne wind energy, which other researchers can use and adapt to contribute further to a benchmark network in Airborne Wind Energy.