Genesis and Dynamics of very-large-scale Motions in the Atmospheric Boundary Layer and their Interactions with Utility-scale Wind Turbines

在风能技术中，预测风力机尾迹在不同大气条件下的演变对于优化风电场的发电和减轻由于有害尾迹相互作用而对风力机造成的破坏性负荷具有重要意义。该项目旨在研究在叶片表面附近的空气层中演化的所谓超大规模运动(VLSM)的起源、演化和再生，以及它们与公用事业规模风力涡轮机的相互作用。随着风电场规模的不断扩大和风力涡轮机尺寸的增大，超大规模SM预计将对风力发电和风力涡轮机尾迹的下游演变产生深远的影响。然而，在某些情况下，VLSM的起源和动力学还不是很清楚，因此它们的影响和与公用事业规模的风力涡轮机的相互作用很难预测。本项目在这一主题上推进了数值模拟和概念验证实验室实验。此外，本科生正在德克萨斯大学达拉斯分校的移动LIDAR(光成像、探测和测距)站接受测量风速的培训，这是一个用于教育和推广活动的独特设施。这项培训影响了来自广泛背景的学生，并使他们意识到重要的主题，如气象学、极端天气现象、对环境的人为影响和可再生能源。这项研究项目的目标是：1)更好地了解产生VLSM的物理机制及其随大气稳定度、不同地形和土地覆盖的日循环而产生的变异性；2)探索VLSM如何影响公用事业规模的风力涡轮机产生的尾流的下游演变；3)开发能够通过再现VLSM诱导的雷诺应力的调制来实现对风力涡轮机尾迹的全面和及时预测的数值工具。这项研究项目由三个相互关联的任务组成。首先，有两个激光雷达测量活动，第一个是针对德克萨斯州北部相对平坦的地形的站点，第二个是针对复杂地形的站点。第三个任务使用得到的实验数据，通过在伴随雷诺平均的Navier-Stokes框架内对湍流闭合模型进行优化调整，来模拟VLSM诱导的风力机尾迹调制。这项研究项目正在帮助回答一些关键问题，这些问题涉及VLSM的形态和能量含量以及它们在不同大气稳定机制下的变化情况，控制VLSM产生的物理机制和ABL气流中不同长度尺度的相干结构之间的能量传输，以及土地覆盖和地形在VLSM发生和动力学中的作用。该研究项目还旨在量化VLSM引起的幅度调制对公用事业规模风力机的气动性能和风力机尾迹下游演变的影响。

In wind energy technology, predicting the evolution of wind turbine wakes under different atmospheric conditions is important for optimizing power production from a wind farm and mitigating damaging loads on the turbines due to detrimental wake interactions. This project aims to investigate the origin, evolution and regeneration of what are called very-large-scale motions (VLSMs) that evolve in the layer of air near the blade surface, termed the atmospheric boundary layer (ABL), and their interactions with utility-scale wind turbines. As the scale of wind farms continues to grow and as wind turbines increase in size, VLSMs are expected to profoundly influence wind power production and the downstream evolution of wind turbine wakes. However, the origin and dynamics of VLSMs are not well understood in some cases, and therefore their effects and interactions with utility-scale wind turbines are difficult to predict. This project advances numerical simulations and proof-of-concept laboratory experiments on this topic. Additionally, undergraduate students are being trained to measure wind velocities at the University of Texas Dallas mobile LIDAR (Light Imaging, Detection, And Ranging) station, which is a unique facility for education and outreach activities. This training impact students from a wide range of backgrounds and makes them aware of important topics, such as meteorology, extreme weather phenomena, anthropogenic effects on the environment and renewable energy. The goals of this research project are to: 1) better understand the physical mechanisms generating VLSMs and their variability as a consequence of the daily cycle of atmospheric stability, different topography and land cover; 2) explore how VLSMs affect downstream evolution of wakes produced by utility-scale wind turbines; 3) develop numerical tools that will enable thorough and timely predictions of wind turbine wakes by reproducing modulations of the Reynolds stresses induced by VLSMs. This research project is comprised of three interrelated tasks. First, there are two LIDAR measurement campaigns, the first one for a site over a relatively flat terrain in North Texas and a second one over a complex terrain. The third task uses the resulting experimental data for modeling VLSM-induced modulations on wind turbine wakes through optimal tuning of turbulence closure models within an adjoint Reynolds-averaged Navier-Stokes framework. This research project is helping to answer a number of key questions related to the morphology and energy content of VLSMs and how variable are they under different regimes of the atmospheric stability, the physical mechanisms governing generation of VLSMs and energy transport among coherent structures with different length-scales for ABL flows, and the role of land cover and topography in VLSM genesis and dynamics. The research project also aims to quantify the effects of the amplitude modulations induced by VLSMs on aerodynamic performance of utility-scale wind turbines and downstream evolution of wind turbine wakes.