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

ERI：风电场尾流曲流的形成机制和建模

基本信息

批准号：
2136371
负责人：
Daniel Foti
金额：
$ 19.88万
依托单位：
University of Memphis
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-02-01 至 2025-01-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2136371&HistoricalAwards=false
关键词：
ERI Formation Mechanisms Modeling Wake

项目摘要

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.

该病房是由2021年的《美国救援计划法》的全部资助。摩ress骨表面层中的随机相互作用和风力涡轮机产生的湍流特征驱动了主要的挑战，以解释和模型的风场中的涡轮机构。与其他大气相比，生产变异性和增强风能的波动和SMA LL涡轮尺度动力学被分别假设，以启动唤醒曲折的现象，这是风力涡轮机的一致性振荡。唤醒恢复，尾流相互作用的动态和风电场的不确定性将阐明其基本的形成行为，这对于降低了风能的水平成本至关重要。孟菲斯非营利组织通过湍流来组织公共科学意识和教育。研究和模拟大型连贯量表的传输，使用驱动的分析n驱动d的唤醒deckure deckure deckure deckure deckure deckure deckure deckure of the方法论利用多分辨率的风电场模型。涡轮机和农场。 - 可以缓解风电场模型，并可以引入设计以修改唤醒饮食作用的设计。该奖项反映了NSF'Stututs值得通过使用Toundatual功绩评估和ER ER影响评估评估标准来获得支持。