• Energy Research

For this specific test, the 25m² leading edge inflatable V3 kite was flown, which was also used by Oehler [1] in 2017 but with a different measurement configuration. The kite was equipped with a newly designed flow measurement setup to replace the less robust measurement setup of Oehler. Conservative operational settings were used as the test was focused on data acquisition rather than maximising energy production. Therefore, the power output during the test was lower than that for normal operation. Also, the system configuration was already dated at the time of the test and has gone through substantial development since then, e.g., Kitepower nowadays employs a much larger kite with an improved design.The measurements were performed with the 100 kW technology development platform of Kitepower B.V., which is a spin-off company from Delft University of Technology. For this particular test flight, the kite power system was equipped with a Leading Edge Inflatable (LEI) V3 kite. The traction force was transferred to the ground station by a tether made of Dyneema. A general description of the kite power system is given in the work of Van der Vlugt and Salma.

Life Cycle Inventory (LCI) and Life Cycle Impact Assessment (LCIA) models of two 50 MW wind farms consisting of 10 Airborne Wind Energy Systems (AWES) and 10 Horizontal Axis Wind Turbines (HAWT). The AWES data is determined by scaling the Ampyx Power AP3 (150 kW) up to 5 MW. The HAWT data is taken from the NREL 5 MW reference wind turbine. The dataset was generated during the graduation project of Luuk van Hagen "Life Cycle Assessment of Multi-Megawatt Airborne Wind Energy" at Delft University of Technology, completed on 8 July 2021. http://resolver.tudelft.nl/uuid:472a961d-1815-41f2-81b0-0c6245361efb

Airborne wind energy systems benefit from high-lift airfoils to increase power output. This paper proposes an optimisation approach for a multi-element airfoil of a fixed-wing system operated in pumping cycles to drive a drum-generator module on the ground. The approach accounts for the different design objectives of the tethered kite’s alternating production and return phases. The airfoil shape is first optimised for the production phase and then adapted for the requirements of the return phase by modifying the flap setting. The optimisation uses the multi-objective genetic algorithm NSGA-II in combination with the fast aerodynamic solver MSES. Once the optimal shape is determined, the aerodynamic performance is verified through CFD RANS simulations with OpenFOAM. The resulting airfoil achieves satisfactory performance for the production and return phases of the pumping cycles, and the CFD verification shows a fairly good agreement in terms of the lift coefficient. However, MSES significantly underpredicts the airfoil drag.

Similar to parafoils, ram-air kites are flexible membrane wings inflated by the apparent wind and supported by a bridle line system. A major challenge in estimating the performance of these wings using a computer model is the strong coupling between the airflow around the wing and the deformation of the membrane structure. In this paper, we introduce a staggered coupling scheme combining a structural finite element solver using a dynamic relaxation technique with a potential flow solver. The developed method proved numerically stable for determining the equilibrium shape of the wing under aerodynamic load and is thus suitable for performance measurement and load estimation. The method was validated with flight data provided by SkySails Power. Measured forces on the tether and steering belt of the robotic kite control pod showed good resemblance with the simulation results. As expected for a potential flow solver, the kite’s glide ratio was overestimated by 10–15%, and the measured tether elevation angle in a neutral flight scenario matched the simulations within 2 degrees. Based on the obtained results, it can be concluded that the proposed aero-structural model can be used for initial designs of ram-air kites with application to airborne wind energy.

AbstractWe present a computational fluid dynamic analysis of boundary layer transition on leading edge inflatable kite airfoils used for airborne wind energy generation. Because of the operation in pumping cycles, the airfoil is generally subject to a wide range of Reynolds numbers. The analysis is based on the combination of the shear stress transport turbulence model with thetransition model, which can handle the laminar boundary layer and its transition to turbulence. The implementation of both models in OpenFOAM is described. We show a validation of the method for a sailwing (ie, a wing with a membrane) airfoil and an application to a leading edge inflatable kite airfoil. For the sailwing airfoil, the results computed with transition model agree well with the existing low Reynolds number experiment over the whole range of angles of attack. For the leading edge inflatable kite airfoil, the transition modeling has both favorable and unfavorable effects on the aerodynamics. On the one hand, the aerodynamics suffer from the laminar separation. But, on the other hand, the laminar boundary layer thickens slower than the turbulent counterpart, which, in combination with transition, delays the separation. The results also indicate that the aerodynamics of the kite airfoil could be improved by delaying the boundary layer transition during the traction phase and tripping the transition in the retraction phase.

Abstract. Layout optimisation is essential for improving the overall performance of offshore wind farms. During the past 15 years, the use of yield optimisation algorithms has resulted in a transition from regular to more irregular farm layouts. However, since the layout affects many factors, yield optimisation alone may not maximise the overall performance. In this paper, a comparative case study is presented to quantify the effect of the wind farm layout on the overall performance of offshore wind farms. The case study was performed to investigate two performance indicators: power performance, using yield calculations with windPRO, and wake-induced tower fatigue, using the Frandsen model. It is observed that irregular wind farm layouts have a higher annual energy production compared to regular layouts. Their power production is also more persistent and less sensitive to wind direction, improving predictability and thus the market value of power output. However, one turbine location in the irregular layout has a 24 % higher effective turbulence level, leading to additional tower fatigue. As a result, fatigue-driven tower designs would require increased wall thicknesses, which would result in higher capital costs for all turbine locations. It is demonstrated in this study that layout optimisation using minimum inter-turbine spacing effectively resolves the induced wake issue while maintaining high-yield performance.

Airborne wind energy is an emerging technology that uses tethered unmanned aerial vehicles for harvesting wind energy at altitudes higher than conventional towered wind turbines. To make the technology competitive to other renewable energy technologies a reliable control system is required that allows autonomously operating the system throughout all phases of flight. In the present work a cascaded nonlinear control scheme for reliable pumping cycle control of a rigid wing airborne wind energy system is proposed. The high-level control strategy in the form of a state machine as well as the flight controller consisting of path-following guidance and control, attitude, and rate loop is presented along with a winch controller for tether force tracking. Amathematical model for an existing prototype will be derived, and results from a simulation study will be used to demonstrate the robustness of the proposed concept in the presence of turbulence and wind gusts.

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-ω 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.