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On Wind Speed Sensor Configurations and Altitude Control in Airborne Wind Energy Systems

机译:机载风能系统中的风速传感器配置和高度控制

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Real-time altitude control of airborne wind energy (AWE) systems can improve performance by allowing turbines to track favorable wind speeds across a range of operating altitudes. The current work explores the performance implications of deploying an AWE system with sensor configurations that provide different amounts of data to characterize wind speed profiles. We examine various control objectives that balance trade-offs between exploration and exploitation, and use a persistence model to generate a probabilistic wind speed forecast to inform control decisions. We assess system performance by comparing power production against baselines such as omniscient control and stationary flight. We show that with few sensors, control strategies that reward exploration are favored. We also show that with comprehensive sensing, the implications of choosing a sub-optimal control strategy decrease. This work informs and motivates the need for future research exploring online learning algorithms to characterize vertical wind speed profiles.
机译:机载风能(AWE)系统的实时高度控制可通过允许涡轮机在整个运行高度范围内跟踪有利的风速来提高性能。当前的工作探讨了部署带有传感器配置的AWE系统的性能含义,该传感器配置提供不同数量的数据以表征风速曲线。我们研究了在勘探与开发之间权衡取舍的各种控制目标,并使用持久性模型来生成概率风速预测,以为控制决策提供依据。我们通过将发电量与全能控制和固定飞行等基准进行比较来评估系统性能。我们表明,在传感器很少的情况下,奖励探索的控制策略受到青睐。我们还表明,通过全面感知,选择次优控制策略的含义会减少。这项工作为将来研究探索在线学习算法以表征垂直风速剖面的研究提供了动力,并激发了他们的需求。

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