ERI: Formation Mechanisms and Modeling of Wake Meandering in Wind Farms

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。大气表层的随机波动和风力发电机产生的湍流特征之间的相互作用，给解释和模拟风电场中的湍流机制带来了重大挑战。了解潜在的行为可以降低电力生产的变化性，这会对电力成本的均衡化产生不利影响，并提高风能相对于其他形式电力生产的竞争力。具体地说，大的大气波动和小涡轮机尺度的动力学分别被假设为启动尾迹蜿蜒现象，即风力涡轮机远尾迹的相干振荡。尾迹漂移影响尾迹恢复的非定常动力学、尾迹相互作用以及风电场发电的不确定性。该项目将阐明其潜在的形成行为，这对于使设计和模型能够降低风能的水平成本至关重要。该项目还将包括重要的教育活动，包括与孟菲斯非营利性组织的外联计划，以及通过艺术及其与动荡的交集来提高公众科学意识和教育。拟议中的项目推进了对风力涡轮机主要不稳定性的基本见解。该项目将开发一系列高保真大涡模拟，以测量上风大气边界层和风力涡轮机尾迹中动能和涡度的光谱和演变。从模拟的尾迹流中利用数据驱动分析和计算发现，将发展一种研究和模拟大相干结构尺度动能传递和输送的方法。该方法和模拟将被用来研究风力机尾迹弯曲的形成机理，并利用该方法来开发多分辨率风电场模型。该项目建议(1)通过量化大气表层迎风特征和尾流蜿蜒之间的能量转移来发展和评估尾迹蜿蜒的成因机制；(2)开发风电场模型来捕捉风力机、风电场和大气的不同长度尺度。这项研究的预期成果包括对尾流曲折时空演变的基本理解和多分辨率、多尺度的风电场建模。通过解决风力涡轮机尾迹中大型相干结构形成和持续的不确定性，可以减少时间精确型风电场模型的不确定性和模型不足，并可以引入修改尾迹曲折在功率波动中的作用的设计。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Interactions between stochastic fluctuations in the atmospheric surface layer and turbulent features produced by wind turbines drive major challenges to explain and model turbulence mechanisms in wind farms. Understanding the underlying behaviors can reduce power production variability, which adversely influences the levelized cost of electricity, and enhance wind energy’s competitiveness compared to other forms of power production. Specifically, large atmospheric fluctuations and the small turbine-scale dynamics are separately hypothesized to initiate the wake meandering phenomenon, a coherent oscillation of the far wake of wind turbines. Wake meandering affects the unsteady dynamics of wake recovery, wake interactions, and uncertainty of power production in wind farms. This project will elucidate its underlying formation behavior, which is crucial to enable designs and models to lower the levelized cost of wind energy. The project will also include significant educational activities including outreach programs with Memphis non-profit organizations and increased public science awareness and education through art and its intersection with turbulence. The proposed project advances fundamental insights into dominant instabilities in wind turbines. The project will develop a series of high-fidelity large-eddy simulations to measure the spectra and evolution of kinetic energy and vorticity in the upwind atmospheric boundary layer and wind turbine wake. An approach to investigate and model the transfer and transport of kinetic energy of large coherent structure scales will be developed using data-driven analysis and computational-enabled discovery from the simulated wake flows. The methodology and simulations will be employed to investigate the formation mechanism of meandering of a wind turbine wake and leveraged to develop multi-resolution wind farm models. The project proposes to (1) develop and evaluate wake meandering genesis mechanisms by quantifying the energy transfer between upwind features in the atmospheric surface layer and wake meandering; and (2) develop wind farm models to capture disparate length scales of the wind turbine, wind farm, and atmosphere. Expected outcomes of this research include fundamental understanding of the spatio-temporal evolution of wake meandering and multi-resolution, multi-scale wind farm modeling. By addressing the uncertainty of the formation and persistence of large coherent structures in wind turbine wakes, the uncertainty and model inadequacy of time-accurate wind farm models can be mitigated, and designs to modify the role of wake meandering in power fluctuations can be introduced.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.