Dynamics of macro-vortices in horizontal axis turbine wind farms

水平轴涡轮风电场宏观涡动力学

• 批准号: 1949778
• 负责人: Charles Meneveau
• 金额: $ 39.97万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1949778&HistoricalAwards=false
• 关键词: Dynamics; macro; vortices; horizontal; axis

Fluid dynamics and turbulent flow phenomena are known to play dominant roles in the performance, efficiency and environmental impact of wind farms. There is growing interest in using fluid dynamics knowledge to improve wind energy harvesting and thereby achieve societal benefits such as reduced greenhouse gas emissions and a renewable energy economy. This research project aims to develop air flow models for use in wind plant design and control. The working hypothesis is that flow modifications resulting from turbine actions, such as adjusting the angle of the turbine rotor to the incoming flow (yawing or tilting) or pulsing the surfaces that regulate power extraction, can best be understood using models of very large swirling flow structures called "macro-vortices." Such vortices are believed to extend for many hundreds of meters downstream of turbines in a wind farm. These structures can be responsible for changing the speed, direction, and frequency of the wind exiting a turbine and impacting the performance of downstream turbines. This research project will use computer simulations to study the generation, evolution, and decay of large-scale vortices in turbulent flows. Educational and outreach activities will leverage national and international research networks through Johns Hopkins University Society of Women Engineers. K-12 outreach will be coordinated through the Center for Educational Outreach at Johns Hopkins University and will include lectures as part of Engineering Innovation, a summer program for high school students. The project researchers will also participate in an intersession program at a local elementary school.This research project will develop the fundamental knowledge required to harness the potential of large-scale flow actuation, using wind turbine yaw, tilt, and cycling, in order to improve wind farm performance. Various research questions will be addressed using high-fidelity numerical datasets from a suite of Large Eddy Simulations (LES) of yawed, tilted, and periodically forced turbines. The project will characterize the properties (strength, effective core-size, positions and trajectories) of the macro-vortices generated under various conditions, including shear, surface roughness, and thermal stratification of the atmosphere, e.g. under buoyant (daytime) and stably stratified (nighttime) conditions. The project will develop reduced models that leverage lessons learned from the various LES data, as well as from basic physics of vorticity dynamics and simplified descriptions such as lifting line theory. The resulting reduced models and LES insights will be used to find improved arrangements or optimal networks of macro-vortices. The objective would be to increase vertical entrainment of mean kinetic energy from the faster winds above the wind turbines down into the wind turbine region.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.

众所周知，流体动力学和湍流现象在风电场的性能，效率和环境影响中起主要作用。人们对利用流体动力学知识来改善风能收集的兴趣越来越大，从而获得了社会利益，例如减少温室气体排放和可再生能源经济。 该研究项目旨在开发用于风电厂设计和控制的空气流模型。 有效的假设是，涡轮动作作用引起的流动修饰，例如调节涡轮转子与传入流的角度（偏航或倾斜）或脉动调节功率提取的表面，最好使用称为“宏观涡流”的非常大的旋转流量结构的模型来理解。 据信，这种涡流在风电场的涡轮机下面延伸了数百米。这些结构可能负责改变涡轮机的速度，方向和频率并影响下游涡轮机的性能。 该研究项目将使用计算机模拟来研究湍流中大规模涡流的产生，进化和衰减。教育和外展活动将通过约翰·霍普金斯大学女工程师协会利用国家和国际研究网络。 K-12外展活动将通过约翰霍普金斯大学的教育外展中心进行协调，并将包括演讲，作为工程创新的一部分，这是一个针对高中生的夏季计划。 项目研究人员还将在当地一所小学的一项间交流计划中参加。本研究项目将使用风力涡轮机偏航，倾斜和骑自行车来发展利用大规模流动驱动的潜力所需的基本知识，以改善风电场的性能。将使用来自大型涡流模拟（LES）的高保真数字数据集来解决各种研究问题，偏压，倾斜和定期强迫涡轮机。该项目将表征在各种条件下生成的宏观涡流的特性（强度，有效的核心大小，位置和轨迹），包括剪切，表面粗糙度和大气的热分层，例如在浮力（白天）和稳定分层（夜间）条件下。该项目将开发简化的模型，以利用从各种LES数据中学到的经验教训，以及从涡度动态的基本物理学和简化描述（例如提升线理论）中学到的。由此产生的减少模型和LES洞察力将用于找到改进的宏观涡流安排或最佳网络。 目的是增加从风力涡轮机上方的较快风向风力涡轮机区域的垂直夹带。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估来评估的。

项目成果

Network based estimation of wind farm power and velocity data under changing wind direction

风向变化下风电场功率和风速数据的网络估计

• DOI: 10.23919/acc50511.2021.9483060
• 发表时间: 2021
• 期刊: American Control Conference (ACC
• 作者: Starke, Genevieve M.;Stanfel, Paul;Meneveau, Charles;Gayme, Dennice F.;King, Jennifer
• 通讯作者: King, Jennifer

Generation and decay of counter-rotating vortices downstream of yawed wind turbines in the atmospheric boundary layer

偏航风力发电机下游大气边界层反向旋转涡流的产生和衰减

• DOI: 10.1017/jfm.2020.717
• 发表时间: 2020
• 期刊: Journal of Fluid Mechanics
• 影响因子: 3.7
• 作者: Shapiro, Carl R.;Gayme, Dennice F.;Meneveau, Charles
• 通讯作者: Meneveau, Charles

The area localized coupled model for analytical mean flow prediction in arbitrary wind farm geometries

• DOI: 10.1063/5.0042573
• 发表时间: 2020-09
• 期刊: Journal of Renewable and Sustainable Energy
• 影响因子: 2.5
• 作者: Genevieve M. Starke;C. Meneveau;J. King;D. Gayme

Turbulence and Control of Wind Farms

风电场的湍流与控制

• DOI: 10.1146/annurev-control-070221-114032
• 发表时间: 2022
• 期刊: and Autonomous Systems
• 作者: Shapiro, Carl R.;Starke, Genevieve M.;Gayme, Dennice F.
• 通讯作者: Gayme, Dennice F.

A vortex sheet based analytical model of the curled wake behind yawed wind turbines

基于涡流片的偏航风力涡轮机后卷曲尾流分析模型

• DOI: 10.1017/jfm.2021.1010
• 发表时间: 2022
• 期刊: Journal of Fluid Mechanics
• 影响因子: 3.7
• 作者: Bastankhah, Majid;Shapiro, Carl R.;Shamsoddin, Sina;Gayme, Dennice F.;Meneveau, Charles
• 通讯作者: Meneveau, Charles