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Effects of tip speed ratio on wind turbine wake meandering

唤醒 涡轮机 机械 气象学 叶尖速比 海洋工程 环境科学 风速 地质学 物理 热力学 工程类
作者
Yan Wang,Guihua Zhao,Guoliang Liu,Yongze Zhou,Mingwei Ge,Zhen Ouyang,Zijing Ding,Ruifeng Hu
出处
期刊:Journal of Fluid Mechanics [Cambridge University Press]
卷期号:1014 被引量:9
标识
DOI:10.1017/jfm.2025.10276
摘要

This study utilises large-eddy simulation with the actuator line model to examine the effects of the tip speed ratio (TSR) on the wake-meandering characteristics of a wind turbine in uniform and turbulent inflows. It is shown that as the TSR grows, the onset position of the wake meandering moves closer to the rotor, and the magnitude of wake oscillation is stronger. This aligns with previous work showing that a higher TSR can accelerate the instability and breakdown of tip vortices. Without a nacelle, the Strouhal number of the wake meandering is found to be independent of the TSR under both the uniform and turbulent inflows. However, with a relatively large nacelle, the Strouhal number first increases and then decreases with TSR. Therefore, the current discovery elucidates the crucial role of the nacelle and clarifies the origin of the TSR dependence of the Strouhal number in wake meandering. In addition, the characteristic frequency of the wake meandering under the turbulent inflow is much smaller than that under the uniform inflow, because of the significant influence of the freestream turbulence. Furthermore, the proper orthogonal decomposition (POD) and spectral POD (SPOD) methods are employed to study the spatiotemporal characteristics of the meandering wake and its TSR dependence. It is found that the tip and root vortices are the prominent wake structures under the uniform inflow, whereas more complex multiscale structures from the interaction between the freestream turbulence and tip/root vortices exist under the turbulent inflow. Moreover, an amplitude modulation phenomenon of the POD time coefficients at the optimal TSR is observed in the uniform inflow case. Finally, a reduced-order model is constructed for predicting the wake dynamics by combining the SPOD and the ‘sparse identification of nonlinear dynamics’ algorithm with high accuracy and interpretability.
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