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，预测风力涡轮机尾流在不同大气条件下的演变对于优化来自风力发电场的功率生产和减轻由于有害的尾流相互作用而导致的涡轮机上的破坏性负载是重要的。 该项目旨在研究在叶片表面附近的空气层（称为大气边界层（ABL））中演变的超大规模运动（VLSM）的起源，演变和再生，以及它们与公用事业规模风力涡轮机的相互作用。随着风力发电场规模的持续增长以及风力涡轮机尺寸的增加，预计VLSM将深刻地影响风力发电和风力涡轮机尾流的下游演变。然而，在某些情况下，VLSM的起源和动力学还没有得到很好的理解，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是难以预测的。该项目推进了关于这一主题的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移动的激光雷达（光成像、探测和测距）站接受测量风速的培训，该站是一个独特的教育和推广活动设施。 这种培训影响来自广泛背景的学生，使他们了解重要的主题，如气象学，极端天气现象，对环境和可再生能源的人为影响。本研究项目的目标是：1）更好地理解VLSM产生的物理机制及其随大气稳定度日循环、不同地形和土地覆盖而变化的结果; 2）探索VLSM如何影响公用事业规模风力涡轮机产生的尾流的下游演变; 3）开发数值工具，通过再现VLSM引起的雷诺应力调制，实现风力涡轮机尾流的全面和及时预测。本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，第一个是在德克萨斯州北部相对平坦的地形上的一个站点，第二个是在复杂的地形上。 第三个任务使用由此产生的实验数据建模VLSM引起的调制风涡轮机唤醒通过最佳调整的湍流封闭模型内的一个伴随的雷诺平均Navier-Stokes框架。 该研究项目有助于回答与VLSM的形态和能量含量相关的一些关键问题，以及它们在不同的大气稳定性制度下如何变化，控制VLSM生成的物理机制和ABL流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成因和动力学中的作用。该研究项目还旨在量化VLSM引起的振幅调制对公用事业规模风力涡轮机的空气动力学性能和风力涡轮机尾流的下游演变的影响。

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.