To achieve a high conversion efficiency and at the same time robust control of a pumping kite power system it is crucial to optimize the three-dimensional flight path of the tethered wing. This chapter extends a dynamic system model to account for a realistic, turbulent wind environment and adds a flight path planner using a sequence of attractor points and turn actions. Path coordinates are calculated with explicit geometric formulas. To optimize the power output the path is adapted to the average wind speed and the vertical wind profile, using a small set of parameters. The planner employs a finite state machine with switch conditions that are highly robust towards sensor errors. The results indicate, that the decline of the average power output of pumping kite power systems at high wind speeds can be mitigated. In addition it is shown, that reeling out towards the zenith after flying figure eight flight maneuvers significantly reduces the traction forces during reel-in and thus increases the total efficiency.

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In wind energy research, airborne wind energy systems are one of the promising energy sources in the near future. They can extract more energy from high altitude wind currents compared to conventional wind turbines. This can be achieved with the aid of aerodynamic lift generated by a wing tethered to the ground. Significant savings in investment costs and overall system mass would be obtained since no tower is required. To solve the problems of wind speed uncertainty and kite deflections throughout the flight, system identification is required. Consequently, the kite governing equations can be accurately described. In this work, a simple model was presented for a tether with a fixed length and compared to another model for parameter estimation. In addition, for the purpose of stabilizing the system, fuzzy control was also applied. The design of the controller was based on the concept of Mamdani. Due to its robustness, fuzzy control can cover a wider range of different wind conditions compared to the classical controller. Finally, system identification was compared to the simple model at various wind speeds, which helps to tune the fuzzy control parameters.

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In 2016 Uwe Fechner presented the paper "Downscaling of Airborne Wind Energy Systems" [1] at the Torque conference in Munich. Here, we report on our efforts in the development of small-scale Airborne Wind Energy (AWE) systems with vertical launch and landing. We are trying to accelerate development of small-scale Airborne Wind Energy systemsby providing the key components that are always needed but not yet available off-the-shelf. We aim at reducing development costs for any AWE startup, but also to provide components and systems for educational purposes. The first part our presentation we explain how cooperation with other startups is shaping the structure of our R&D programs. We have been supplying control systems and simulation models to the Dutch startup ekite and the Swiss startup SkyPull. A case study discusses how component-suppliers help AWE system integrators achieve leaner development cycles. The role of scale economies, specialization and institutional arrangements is assessed in terms of their impact on product development cycle and cost. The second part of the presentation discusses technical challenges of hardware and software component development for the AWE industry. We plan to offer four products in 2017: a fast and reliable wireless link (Ariadne), a flight control computer tailored for the needs of the airborne wind energy industry (Athena), a ground control computer and a small scale ground-station (1.4 kW continuous electrical power, total mass below 30 kg). Distributed control challenges will be reviewed together with opportunities for recycling know-how from the conventional drone industry. We are integrating Pixhawk (hardware) and PX4 (software) stacks within a Linux based framework that was developed from scratch to handle the specific needs of airborne wind energy. All systems are resilient and share the transversal concern of enabling safe launch and landing procedures in both regular, strong and turbulent wind conditions. Wind tunnel validation is planned for the end of the year and involves both internal aerodynamic know-how and cooperation with leading European wing designers. @en

This work demonstrates the derivation of the equations governing the operation of a kite power system, followed by adaptive control with time-varying gains. Because the availablemathematical kite models are generally derived with aggressive assumptions,we use least square estimation as a system identification (SI) algorithm [1] to predict the kite parameters in real-time and compare between the measured and expected course angle to check the accuracy of the model as shown in the figure. The SI algorithms are chosen to minimize the computational effort per time step. Two different controllers are tested separately to stabilize the kite motion; the first controller is a fuzzy controller which is chosen due to its strength in stabilizing non-linear systems. The other controller is an adaptive pole placement controller which updates its control gains in real-time depending on the parameters generated from the SI algorithms. The SI algorithms with fuzzy and adaptive controllers are compared with the mathematical model of the fixed-tether-length kite system with PID controller at different wind conditions. The novelty of this work is to predict the governing equation of the kite in real-time. Thus, the change in kite’s size, wind speed, and tether length [2] would be updated in the mathematical model of the kite. Moreover, the governing equations resulting from the SI algorithms are used to design an adaptive controller that adapts its gains in real-time based on the change of the governing equations of the kite. @en

Pumping-mode airborne wind energy systems (PM-AWE) consist of an airborne drone (UAV) that flies tethered to a ground station. The tethered UAV is expected to generate high lifts when reeling the tether out, descend with low force and damp gusts during take-off or landing events. These missions take place in unpredictable environmental conditions. Winds can be more or less turbulent, ground proximity prompts leading edge soiling and aerostructural effects induce shape deformations. Conventional aviation airfoils were not designed for these conditions but wing designers miss specialized alternatives. The need for specialized airborne wind energy airfoils was first identified by Venturato [1]. He redesigned the Clark Y airfoil with a genetic optimization approach based on a simple performance goal and a RANS CFD solver. This type of CFD model cannot capture important physical phenomena like laminar bubbles or turbulent transition but Venturato’s work had the groundbreaking merrit of raising awareness about specialized airfoils. Here we present a collection of airfoils designed for the needs of the airborne wind energy industry. The design exercise builds upon an established airfoil optimization framework with a proven track record in the conventional wind turbine industry [2,3,4,5]. The method is known to provide a broad coverage of the design space thanks to the use of a CST parametrization, a tuned version of the RFOIL viscous-inviscid solver and multi-objective genetic optimization algorithms. Candidate airfoils are assessed in terms of conflicting structural and aerodynamic goals. Pareto fronts quantify compromises between glide ratio, maximum lift, building height, stall harshness and resilience to leading edge soiling. Finally, desirable pitching moment characteristics are framed within the broader question of planform design, a question on which we hope to engage the audience in a lively discussion. @en

Airborne wind energy systems provide a novel solution to harvest wind energy from altitudes that can not be reached by wind turbines with a similar nominal generator power. The use of a lightweight but strong tether in place of an expensive tower provides an additional cost advantage, next to the higher capacity factor and much lower total mass. This paper investigates the scaling e
ects of airborne wind energy systems. The energy yield of airborne wind energy systems, that work in pumping mode of operation is at least ten times higher than the energy yield of conventional solar systems. For airborne wind energy systems the yield is defined per square meter wing area. In this paper the dependency of the energy yield on the nominal generator power for systems in the range of 1 kW to 1 MW is investigated. For the onshore location Cabauw, The Netherlands, it is shown, that a generator of just 1.4 kW nominal power and a total system mass of less then 30 kg has the theoretical potential to harvest energy at only twice the price per kWh of large scale airborne wind energy systems. This would make airborne wind energy systems a very attractive choice for small scale remote and mobile applications as soon as the remaining challenges for commercialization are solved. @en

Converting the traction power of kites into electricity can be a low cost solution for wind energy. A reliable and robust control system is considered to be crucial for the commercial success of the technology. The focus of this paper is the control of the flight path projected onto the unit sphere. The proposed algorithm is straightforward to implement because it uses mainly LPV and PID control components and is thus easy to certify by the authorities, it allows to define limits for the maximal turn rate to avoid sensor failures, and it allows to use a low gain in the feedback loop to be robust against control loop delays up to 200 ms. This is achieved by splitting the control of the flight path into two different modes of operation: Turn maneuvers and parts of the flight path, where the course angle is constant. During the turning maneuvers mainly feedforward control is used, therefore reducing stability problems. During the straight flight path segments feedback control in combination with Nonlinear Dynamic Inversion (NDI) is used and thus deviations from the planned flight path can be compensated. NDI is needed to compensate the effect of gravity on the turn rate, but also the changes of the steering sensitivity, depending on the apparent wind speed and the angle of attack. A dynamic 4-point model of the kite is used for the validation of the controller performance. The kite is flown in a turbulent 3D wind field using the Mann-model for modeling the turbulence. The results show a low tracking error even in very turbulent wind conditions and even in the presence of large sensor errors and control loop delays: At a turbulence intensity of 26.5% the elevation error was still lower than 1.5°.

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Kite power is a promising innovative technology for converting wind energy into electricity at a higher capacity factor and, for many applications, at a lower cost than conventional wind turbines. However, accessing this potential depends substantially on the availability of sophisticated control systems. Delft University of Technology is developing a kite power generator which operates a tethered inflatable membrane wing in a pumping cycle. The flight trajectory is controlled by an actuator unit suspended below the wing and communicates with the ground station control centre via a fast and reliable wireless link. The link is also used to transmit the data of the on-board sensors to the ground. In a future wind park of many kite power systems, the individual kites and ground stations have to communicate among each other, to avoid collisions and to optimize the total energy output of the park. A preparatory analysis has shown that the current prototype would significantly benefit from a distributed control system approach, achieving higher efficiency and increased operational flexibility. For larger installations a distributed control system would be mandatory anyway. For these reasons, a distributed control system with a flexible architecture has been developed. The unique design and first test results are presented.

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