Adaptive Flight Path Control of Airborne Wind Energy Systems

Tarek N. Dief,Roland Schmehl,Shigeo Yoshida,Uwe Fechner,Mostafa A. Rushdi

doi:10.3390/en13030667

Tarek N. Dief, Roland Schmehl + Show 3 more

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https://doi.org/10.3390/en13030667

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Abstract

In this paper, we applied a system identification algorithm and an adaptive controller to a simple kite system model to simulate crosswind flight maneuvers for airborne wind energy harvesting. The purpose of the system identification algorithm was to handle uncertainties related to a fluctuating wind speed and shape deformations of the tethered membrane wing. Using a pole placement controller, we determined the required locations of the closed-loop poles and enforced them by adapting the control gains in real time. We compared the path-following performance of the proposed approach with a classical proportional-integral-derivative (PID) controller using the same system model. The capability of the system identification algorithm to recognize sudden changes in the dynamic model or the wind conditions, and the ability of the controller to stabilize the system in the presence of such changes were confirmed. Furthermore, the system identification algorithm was used to determine the parameters of a kite with variable-length tether on the basis of data that were recorded during a physical flight test of a 20 kW kite power system. The system identification algorithm was executed in real time, and significant changes were observed in the parameters of the dynamic model, which strongly affect the resulting response.

Highlights

Airborne wind energy (AWE) is an emerging renewable energy technology that uses flying devices that are tethered to the ground [1,2,3]
We investigated the flight dynamic responses of the kite for the two wind speed signals shown in Figures 9 and 10
We implicitly considered the effects of the fluctuating wind velocity and deforming wing due to a varying aerodynamic load distribution and actuation of the bridle line system

Summary

Introduction

Airborne wind energy (AWE) is an emerging renewable energy technology that uses flying devices that are tethered to the ground [1,2,3]. Compared to horizontal axis wind turbines (HAWTs), AWE systems have a number of distinct advantages in terms of costs, maintenance, operating altitude, and capacity factor. As wind turbines have matured over decades of continuous research and development, AWE technologies, which are at a comparatively early stage of development, are still considered to be less reliable. The rated power of the generator typically determines the installation. For the same rated power, an AWE system generally gives a higher annual yield than a HAWT because it can operate at a higher capacity factor. This higher capacity factor is a result of the more persistent

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