机载风能系统实验注入装置和控制器优化实例研究

N. Deodhar, C. Vermillion, P. Tkacik
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引用次数: 10

摘要

本文提出了一种将数值优化与实验室规模实验结果相结合的机载风能系统(awe)植物和控制器组合优化过程。本文介绍的方法,被称为实验注入优化,解决了AWE系统设计者面临的几个挑战,包括控制器和设备设计之间的强耦合,显著的建模不确定性(需要使用实验),以及与全尺寸实验原型相关的高成本。本文提出了一个实验灌注优化的初步案例研究,在1/100比例的Altaeros浮力空气涡轮机(BAT)模型上进行了实验,该模型在北卡罗来纳大学夏洛特分校的1m × 1m水道中系住并飞行。实验室规模的实验平台将评估飞行动力学和控制的成本降低了两个数量级以上,同时大大提高了飞行性能,与纯粹的数值优化相比,目标函数值的量化提高了15.2%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A case study in experimentally-infused plant and controller optimization for airborne wind energy systems
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.
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