Crosswind Kite Control - A Benchmark Problem for Advanced Control and Dynamic Optimization

This article presents a kite control and optimization problem intended as a benchmark problem for advanced control and optimization. We provide an entry point to this exciting renewable energy system for researchers in control and optimization methods looking for a realistic test bench, and/or a useful application case for their theory. The benchmark problem in this paper can be studied in simulation, and a complete Simulink model is provided to facilitate this. The simulated scenario, which reproduces many of the challenges presented by a real system, is based on experimental studies from the literature, industrial data and the first author’s own experience in experimental kite control. In par- ticular, an experimentally validated wind turbulence model is included, which subjects the kite to realistic disturbances. The benchmark problem is that of controlling a kite such that the average line tension is maximized. Two different models are provided: A more comprehensive one is used to simulate the ’plant’, while a simpler ’model’ is used to design and implement control and optimization strategies. This way, uncertainty is present in the form of plant-model mismatch. The outputs of the plant are corrupted by measurement noise. The maximum achievable average line tension for the plant is calculated, which should facilitate the performance comparison of different algorithms. A simple control strategy is implemented on the plant and found to be quite suboptimal, even if the free parameters of the algorithm are well tuned. An open question is whether or not more advanced control algorithms could do better

Aerodynamics of a rigid curved kite wing

A preliminary numerical study on the aerodynamics of a kite wing for high altitude wind power generators is proposed. Tethered kites are a key element of an innovative wind energy technology, which aims to capture energy from the wind at higher altitudes than conventional wind towers. We present the results obtained from three-dimensional finite volume numerical simulations of the steady air flow past a three-dimensional curved rectangular kite wing (aspect ratio equal to 3.2, Reynolds number equal to 3x10^6). Two angles of incidence -- a standard incidence for the flight of a tethered airfoil (6{\deg}) and an incidence close to the stall (18{\deg}) -- were considered. The simulations were performed by solving the Reynolds Averaged Navier-Stokes flow model using the industrial STAR-CCM+ code. The overall aerodynamic characteristics of the kite wing were determined and compared to the aerodynamic characteristics of the flat rectangular non twisted wing with an identical aspect ratio and section (Clark Y profile). The boundary layer of both the curved and the flat wings was considered to be turbulent throughout. It was observed that the curvature induces only a mild deterioration of the aerodynamics properties. Pressure distributions around different sections along the span are also presented, together with isolines of the average pressure and kinetic energy fields at a few sections across the wing and the wake. Our results indicate that the curvature induces a slower spatial decay of the vorticity in the wake, and in particular, inside the wing tip vortices.Comment: 13 pages, 13 figures. Submitted to "Renewable Energy

Real-Time Optimizing Control of an Experimental Crosswind Power Kite

The contribution of this article is to propose and experimentally validate an optimizing control strategy for power kites flying crosswind. The control strategy provides both path control (stability) and path optimization (efficiency). The path following part of the controller is capable of robustly following a reference path, despite significant time delays, using position measurements only. The path-optimization part adjusts the reference path in order to maximize line tension. It uses a real-time optimization algorithm that combines off-line modeling knowledge and on-line measurements. The algorithm has been tested comprehensively on a small-scale prototype, and this article focuses on experimental results

Airborne Wind Energy - To fly or not to fly?

This thesis investigates crosswind Airborne Wind Energy Systems (AWESs) in terms of power production and potential role in future electricity generation systems. The perspective ranges from the small scale, modelling AWE as a single system, to the large, implementing AWESs in regional electricity systems. \ua0To estimate the AWES power production, the thesis provides a dynamic system model that serves as the basis for all the work. The model describes the flight dynamics of a rigid wing that is exposed to tether and aerodynamic forces controlled by flight control surfaces. Index-3 Differential Algebraic Equations (DAEs) based on Lagrangian mechanics describe the dynamics. \ua0This model is validated by fitting it to real flight measurements obtained with a pumping-mode AWES, the prototype AP2 by Ampyx Power. The optimal power production of an AWES depends on complex trade-offs; this motivates formulating the power production computation as an Optimal Control Problem (OCP). The thesis presents the numerical methods needed to discretize the OCP and solve the resulting Nonlinear Program (NLP). \ua0Large-scale implementation of AWESs raises challenges related to variability in power production on the time scale of minutes to weeks. For the former, we investigate the periodic fluctuations in the power output of a single AWES. These fluctuations can be severe when operating a wind farm and have to be considered and reduced for an acceptable grid integration. We analyse the option of controlling the flight trajectories of the individual systems in a farm so that the total power output of the farm is smoothed. This controlled operation fixes the system\u27s trajectory, reducing the ability to maximize the power output of individual AWESs to local wind conditions. We quantify the lost power production if the systems are controlled such that the total farm power output is smoothed. Results show that the power difference between the optimal and fixed trajectory does not exceed 4% for the systems modelled in the study.\ua0The variations in AWESs power production on the timescale of hours to weeks are particularly relevant to the interaction between AWE and other power generation technologies. Investigating AWESs in an electricity system context requires power-generation profiles with high spatio-temporal resolution, which means solving a large number of OCPs. In order to efficiently solve these numerous OCPs in a sequential manner, this thesis presents a homotopy-path-following method combined with modifications to the NLP solver. The implementation shows a 20-fold reduction in computation time compared to the original method for solving the NLP for AWES power optimization.\ua0 For large wind-data sets, a random forest regression model is trained to a high accuracy, providing an even faster computation.The annual generation profiles for the modelled systems are computed using ERA5 wind data for several locations and compared to the generation profile for a traditional wind turbine. The results show that the profiles are strongly correlated in time, which is a sobering fact in terms of technology competition. However, the correlation is weaker in locations with high wind shear.\ua0 \ua0The potential role of AWESs in the future electricity system is further investigated. This thesis implements annual AWE-farm generation profiles into a cost-optimizing electricity system model. We find that AWE is most valuable to the electricity system if installed at sites with low wind speed within a region. At greater shares of the electricity system, even if AWESs could demonstrate lower costs compared to wind turbines, AWE would merely substitute for them instead of increasing the total share of wind energy in the system. This implies that the economic value of an AWES is limited by its cost relative to traditional wind turbines

Airborne Wind Energy - to fly or not to fly?

This thesis investigates crosswind Airborne Wind Energy Systems (AWESs) in terms of power production and potential role in future electricity generation systems. The perspective ranges from the small scale, modelling AWE as a single system, to the large, implementing AWESs in regional electricity systems. \ua0To estimate the AWES power production, the thesis provides a dynamic system model that serves as the basis for all the work. The model describes the flight dynamics of a rigid wing that is exposed to tether and aerodynamic forces controlled by flight control surfaces. Index-3 Differential Algebraic Equations (DAEs) based on Lagrangian mechanics describe the dynamics. \ua0This model is validated by fitting it to real flight measurements obtained with a pumping-mode AWES, the prototype AP2 by Ampyx Power. The optimal power production of an AWES depends on complex trade-offs; this motivates formulating the power production computation as an Optimal Control Problem (OCP). The thesis presents the numerical methods needed to discretize the OCP and solve the resulting Nonlinear Program (NLP). \ua0Large-scale implementation of AWESs raises challenges related to variability in power production on the time scale of minutes to weeks. For the former, we investigate the periodic fluctuations in the power output of a single AWES. These fluctuations can be severe when operating a wind farm and have to be considered and reduced for an acceptable grid integration. We analyse the option of controlling the flight trajectories of the individual systems in a farm so that the total power output of the farm is smoothed. This controlled operation fixes the system\u27s trajectory, reducing the ability to maximize the power output of individual AWESs to local wind conditions. We quantify the lost power production if the systems are controlled such that the total farm power output is smoothed. Results show that the power difference between the optimal and fixed trajectory does not exceed 4% for the systems modelled in the study.\ua0The variations in AWESs power production on the timescale of hours to weeks are particularly relevant to the interaction between AWE and other power generation technologies. Investigating AWESs in an electricity system context requires power-generation profiles with high spatio-temporal resolution, which means solving a large number of OCPs. In order to efficiently solve these numerous OCPs in a sequential manner, this thesis presents a homotopy-path-following method combined with modifications to the NLP solver. The implementation shows a 20-fold reduction in computation time compared to the original method for solving the NLP for AWES power optimization.\ua0 For large wind-data sets, a random forest regression model is trained to a high accuracy, providing an even faster computation.The annual generation profiles for the modelled systems are computed using ERA5 wind data for several locations and compared to the generation profile for a traditional wind turbine. The results show that the profiles are strongly correlated in time, which is a sobering fact in terms of technology competition. However, the correlation is weaker in locations with high wind shear.\ua0 \ua0The potential role of AWESs in the future electricity system is further investigated. This thesis implements annual AWE-farm generation profiles into a cost-optimizing electricity system model. We find that AWE is most valuable to the electricity system if installed at sites with low wind speed within a region. At greater shares of the electricity system, even if AWESs could demonstrate lower costs compared to wind turbines, AWE would merely substitute for them instead of increasing the total share of wind energy in the system. This implies that the economic value of an AWES is limited by its cost relative to traditional wind turbines

Application of aircraft's flight testing techniques to the aerodynamic characterization of power kites

This thesis has developed an experimental methodology for the flight testing and data analysis of power kites applied to Airborne Wind Energy Systems (AWES). In particular, the Estimation Before Modeling technique, a well-known method in the aerospace industry for the aerodynamic characterization of an aircraft using real flight data, has been adapted for tethered aircraft. The developed methodology has two main building blocks: (i) an experimental setup to record experimental data during the flight testing, and (ii) a Flight Path Reconstruction algorithm to estimate the state of the system from the experimental data. From them, the aerodynamic characteristics of two types of kites were investigated. The proposed experimental setup was designed to be low cost, portable and easily adaptable to both, rigid and semi-rigid kites. It is composed of an instrumented kite representative of the ones used in AWES, an instrumented control bar, a ground computer and a wind station. Whenever it was possible, commercial off the shelf components have been used, including low cost openhardware sensors based on the PixHawk platform. However, after the first flight tests were conducted and the obtained results were discussed, high precision sensors were also included. The Flight Path Reconstruction (FPR) algorithm for tethered aircraft is based on an Extended Kalman Filter (EKF). In addition to the standard set of estimated state variables (ie. Euler angles, position or ground speed), the algorithm also provides the aerodynamic torque and forces upon the kite as well as the tether tensions and wind velocity vector. The EBM technique, and the FPR algorithm have been used to identify the aerodynamic characteristics of both, four-line Leading Edge Inflatable (LEI) kites and two-line Rigid Frame Delta (RFD) kites. Quantitative and qualitative results have been obtained. Albeit both types of kites exhibited very high AoA during the flight, some significant differences were found. In particular, the estimated lift coefficient of the LEI kite showed a behavior identified with a post-stall condition, while the RFD showed a pre-stall behavior with a lower AoA and a positive relation between the lift coefficient and the kite AoA. The presented experimental methodology can be of great interest for AWE industry as it helps to improve modeling of tethered aircraft, leading to more accurate performance figures which may increase investors interest in the technology. Moreover, flight testing methodologies and experimental data analysis are of great interest for benchmarking AWES performances, contributing to de-risk their development process and providing better tools for AWE "best concept" identification. Finally, as a sub-product of the presented methodology, the FPR algorithm can be used as a validated state estimator of the tethered aircraft, which is a key element of a closed loop flight control system.Programa de Doctorado en Mecánica de Fluidos por la Universidad Carlos III de Madrid; la Universidad de Jaén; la Universidad de Zaragoza; la Universidad Nacional de Educación a Distancia; la Universidad Politécnica de Madrid y la Universidad Rovira i VirgiliPresidente: Marco Fontana.- Secretario: Manuel García-Villalba Navaridas.- Vocal: Félix Terroba Ramíre

Improved path following for kites with input delay compensation

In kite power systems, substantial input delay between the actuator and the tethered kite can severely hinder the performance of the control algorithm, limiting the capability of the system to track power-optimal loops. We propose a method that deals with this impediment by using a data-based adaptive filter that predicts future states despite variations in wind conditions, other exogenous disturbances and model mismatch. Moreover, we exploit the geometry of the path on a hemisphere to enhance the guidance algorithm for such kites at a fixed length tether. The objective is to improve the automatic crosswind operation of an airborne wind energy system. To test this under realistic conditions, a small-scale prototype was employed for a series of experiments. The robustness to disturbances and the performance of the algorithm in path following was evaluated for a number of different paths. © 2015 IEEE

Airborne Wind Energy Conference 2019 : (AWEC 2019)

[Book of Abstracts from the Airborne Wind Energy Conference 2019.