A case study in experimentally-infused plant and controller optimization for airborne wind energy systems

Abstract

This paper presents a combined plant and controller optimization process for airborne wind energy systems (AWEs) that fuses numerical optimization with lab-scale experimental results. The methodology introduced in this paper, referred to as experimentally-infused optimization, addresses several challenges faced by AWE system designers, including a strong coupling between the controller and plant design, significant modeling uncertainties (which require the use of experiments), and high costs associated with full-scale experimental prototypes. This paper presents an initial case study of the proposed experimentally-infused optimization, where experiments were conducted on a 1/100th-scale model of Altaeros Buoyant Air Turbine (BAT), which was tethered and flown in the University of North Carolina at Charlotte 1m × 1m water channel. The lab-scale experimental platform reduced the cost of evaluating flight dynamics and control by more than two orders of magnitude, while resulting in substantially improved flight performance, quantified by a 15.2 percent improvement in an objective function value, as compared to a purely numerical optimization.