Large-Eddy-Simulation Studies and In-situ Observations of Land Atmosphere Exchanges in Large Wind Farms

大型风电场陆地大气交换的大涡模拟研究和现场观测

基本信息

  • 批准号:
    1045189
  • 负责人:
  • 金额:
    $ 29.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-03-01 至 2016-02-29
  • 项目状态:
    已结题

项目摘要

The study will develop and apply computational tools for predicting and understanding fluxes of scalars such as heat and moisture in very large wind farms. These fluxes play a crucial role in the land-atmosphere couplings and in possible perturbations stemming from modifications of the land-atmosphere interface with the anticipated global growth of wind energy. At present, effects of wind farms are parameterized in regional scale and global scale models using effective roughness lengths and, sometimes, increased turbulence kinetic energy due to wakes. Such approaches continue to be based on classical similarity theory of the atmospheric boundary layer (ABL). The theory assumes a uniform land surface yet has also often been found acceptable in flows over heterogeneous features of the land surface such as heterogeneities induced by wakes and other effects from wind turbines. This is due to the turbulent flow in the ABL, which efficiently blends the various sources and inhomogeneities across the landscape. However, the appropriateness of such parameterizations, and the values of parameters to be used, are highly uncertain especially in the case of wind farms under general atmospheric conditions (convective, stable, neutral).Intellectual merit:The relevant high-resolution data will be generated via a series of suitably chosen parametric Large-Eddy-Simulations (LES) that quantify accurately the land-atmosphere exchanges of sensible heat and moisture to be expected at the ground surface, underneath wind turbine arrays. These LES resolve significant portions of the individual wakes behind wind turbines and the concomitant modifications to mixing and entrainment.The simulations will cover a wide range of atmospheric conditions (neutral, convective, stable) and wind farm arrangements (turbine spacings, ground properties, loading factors). The computational results obtained under fairly idealized, and thus manageable, conditions will be complemented with in-situ observations in a wind farm. Field studies will take place through an international collaboration with researchers in Switzerland who have access to the La Muela wind farm near Zaragoza in Spain. The results of the validated simulations will be analyzed with the specific purpose of deriving new Monin-Obukhov-type relationships for atmospheric boundary layers including wind turbine arrays. For instance, modified stability corrections and modified effective scalar roughness lengths will be derived as function of relevant parameters. The results of this study will enable more accurate prediction of possible feedback mechanisms of extensive wind farms with local and regional meteorological conditions, regional scale evaporation, etc.Broader impacts: Regional scale surface fluxes of momentum, sensible heat and water vapor play a crucial role in quantifying and understanding the water and energy cycles at various spatial and temporal scales. With the advent of computational modeling, there has been much increased understanding of the effects of manmade modifications to the land surface on land-atmosphere interactions. The growth of wind energy as an important contributor to the renewable energy portfolio suggests the possibility that non-negligible portions of the land surface of the U.S. and the world may ultimately be used for large wind farms. Predicting and better understanding the physical processes coupling the land and atmosphere under such conditions is a very timely and critical area of research.Graduate education and training will stress the interplay between simulation, parameterization, and in-situ field experimental campaigns. Recruiting and educational outreach will leverage an Integrative Graduate Education and Research Traineeship (IGERT) on modeling complex systems and the PI's ongoing efforts to recruit U.S. Hispanic graduate students through contacts in Puerto Rico. The PI's ongoing outreach to a local Baltimore high-school will be actively continued by providing research experiences for junior or senior high-school students.
这项研究将开发和应用计算工具,用于预测和了解超大型风电场的热量和水分等标量通量。 这些通量在陆地-大气耦合和由于预期的全球风能增长而改变陆地-大气界面可能产生的扰动方面发挥着至关重要的作用。 目前,风力发电场的影响在区域尺度和全球尺度模型中使用有效粗糙度长度进行参数化,有时,由于尾流增加湍流动能。 这种方法仍然是基于经典的相似理论的大气边界层(ABL)。 该理论假设均匀的陆地表面,但也经常被发现可以接受的流动在陆地表面的非均匀特征,如尾流和风力涡轮机的其他影响引起的非均匀性。 这是由于ABL中的湍流,它有效地混合了景观中的各种来源和不均匀性。然而,这种参数化的适当性,以及所使用的参数值,是高度不确定的,特别是在一般大气条件下(对流,稳定,中性)的风力发电场的情况下。智力优点:相关的高分辨率数据将通过一系列适当选择的参数大涡模拟(LES),准确地量化的土地-大气交换的显热和水分预计在地面,下面的风涡轮机阵列。 这些LES解决了风力涡轮机后面的单个尾流的重要部分,以及随之而来的混合和卷吸的修改。模拟将涵盖广泛的大气条件(中性、对流、稳定)和风电场布置(涡轮机间距、地面特性、载荷因子)。 在相当理想化的条件下获得的计算结果,因此可以管理,将补充现场观测的风力发电场。 实地研究将通过与瑞士研究人员的国际合作进行,这些研究人员可以进入西班牙萨拉戈萨附近的La Muela风力发电场。 将对验证模拟的结果进行分析,具体目的是推导包括风力涡轮机阵列在内的大气边界层的新的Monin-Obukhov型关系。 例如,修正的稳定性修正和修正的有效标量粗糙度长度将作为相关参数的函数导出。 本研究的结果将使人们能够更准确地预测大型风电场与当地和区域气象条件、区域尺度蒸发等的可能反馈机制。更广泛的影响:区域尺度的动量、显热和水汽通量在量化方面发挥着至关重要的作用和理解各种空间和时间尺度的水和能量循环。 随着计算模型的出现,人们对人为改变地表对陆-气相互作用的影响有了更多的了解。风能作为可再生能源组合的重要贡献者的增长表明,美国和世界陆地表面不可忽视的部分最终可能用于大型风电场。预测和更好地理解在这种条件下耦合陆地和大气的物理过程是一个非常及时和关键的研究领域。研究生教育和培训将强调模拟,参数化和现场实验活动之间的相互作用。招聘和教育推广将利用综合研究生教育和研究培训(IGERT)对复杂系统进行建模,以及PI正在努力通过波多黎各的联系人招聘美国西班牙裔研究生。 PI正在进行的推广到当地的巴尔的摩高中将继续积极为初中或高中学生提供研究经验。

项目成果

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Charles Meneveau其他文献

An airfoil-based synthetic actuator disk model for wind turbine aerodynamic and structural analysis
基于翼型的风力涡轮机气动和结构分析的合成致动器盘模型
  • DOI:
    10.1016/j.renene.2025.123780
  • 发表时间:
    2025-12-15
  • 期刊:
  • 影响因子:
    9.100
  • 作者:
    Muhammad Rubayat Bin Shahadat;Mohammad Hossein Doranehgard;Weibing Cai;Charles Meneveau;Benjamin Schafer;Zheng Li
  • 通讯作者:
    Zheng Li
Multifractality in a nested velocity gradient model for intermittent turbulence
间歇性湍流嵌套速度梯度模型中的多重分形
  • DOI:
    10.1103/physrevfluids.7.014609
  • 发表时间:
    2022-01
  • 期刊:
  • 影响因子:
    2.7
  • 作者:
    Yuan Luo;Yipeng Shi;Charles Meneveau
  • 通讯作者:
    Charles Meneveau
Large-eddy simulation of wind turbines immersed in the wake of a cube-shaped building
浸没在立方体建筑尾流中的风力涡轮机的大涡模拟
  • DOI:
    10.1016/j.renene.2020.08.156
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    8.7
  • 作者:
    Mingwei Ge;Dennice F. Gayme;Charles Meneveau
  • 通讯作者:
    Charles Meneveau

Charles Meneveau的其他文献

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{{ truncateString('Charles Meneveau', 18)}}的其他基金

Research Infrastructure: CC* Data Storage: 20 Petabyte Campus Research Storage Facility at Johns Hopkins University
研究基础设施:CC* 数据存储:约翰霍普金斯大学 20 PB 校园研究存储设施
  • 批准号:
    2322201
  • 财政年份:
    2023
  • 资助金额:
    $ 29.5万
  • 项目类别:
    Standard Grant
Frameworks: Advanced Cyberinfrastructure for Sustainable Community Usage of Big Data from Numerical Fluid Dynamics Simulations
框架:先进的网络基础设施,促进社区可持续利用数值流体动力学模拟中的大数据
  • 批准号:
    2103874
  • 财政年份:
    2021
  • 资助金额:
    $ 29.5万
  • 项目类别:
    Standard Grant
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
  • 财政年份:
    2020
  • 资助金额:
    $ 29.5万
  • 项目类别:
    Standard Grant
Collaborative Research: NISC SI2-S2I2 Conceptualization of CFDSI: Model, Data, and Analysis Integration for End-to-End Support of Fluid Dynamics Discovery and Innovation
合作研究:NISC SI2-S2I2 CFDSI 概念化:模型、数据和分析集成,用于流体动力学发现和创新的端到端支持
  • 批准号:
    1743179
  • 财政年份:
    2018
  • 资助金额:
    $ 29.5万
  • 项目类别:
    Continuing Grant
EPSRC-CBET:Turbulent flows over heterogeneous multiscale surfaces
EPSRC-CBET:异质多尺度表面上的湍流
  • 批准号:
    1738918
  • 财政年份:
    2017
  • 资助金额:
    $ 29.5万
  • 项目类别:
    Standard Grant
BIGDATA: IA: Democratizing Massive Fluid Flow Simulations via Open Numerical Laboratories and Applications to Turbulent Flow and Geophysical Modeling
BIGDATA:IA:通过开放数值实验室以及湍流和地球物理建模应用使大规模流体流动模拟大众化
  • 批准号:
    1633124
  • 财政年份:
    2016
  • 资助金额:
    $ 29.5万
  • 项目类别:
    Standard Grant
CDS&E: Studying Multiscale Fluid Turbulence via Open Numerical Laboratories
CDS
  • 批准号:
    1507469
  • 财政年份:
    2015
  • 资助金额:
    $ 29.5万
  • 项目类别:
    Standard Grant
Collaborative Research: Large-scale kinetic energy entrainment in the wind turbine array boundary layer - understanding and affecting basic flow physics
合作研究:风力涡轮机阵列边界层中的大规模动能夹带 - 理解和影响基本流动物理
  • 批准号:
    1133800
  • 财政年份:
    2012
  • 资助金额:
    $ 29.5万
  • 项目类别:
    Standard Grant
PIRE: USA/Europe Partnership for Integrated Research and Education in Wind Energy Intermittency: From Wind Farm Turbulence to Economic Management
PIRE:美国/欧洲风能间歇性综合研究和教育合作伙伴关系:从风电场湍流到经济管理
  • 批准号:
    1243482
  • 财政年份:
    2012
  • 资助金额:
    $ 29.5万
  • 项目类别:
    Continuing Grant
Studying turbulent scale and space interactions using active grid wind tunnel and DNS database experiments
使用主动网格风洞和 DNS 数据库实验研究湍流尺度和空间相互作用
  • 批准号:
    1033942
  • 财政年份:
    2010
  • 资助金额:
    $ 29.5万
  • 项目类别:
    Continuing Grant

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EAGER:基于 Liutex 的湍流大涡模拟子网格模型
  • 批准号:
    2422573
  • 财政年份:
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CBET-EPSRC: Deep Learning Closure Models for Large-Eddy Simulation of Unsteady Aerodynamics
CBET-EPSRC:用于非定常空气动力学大涡模拟的深度学习收敛模型
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Building-Block-Flow Model for Large-Eddy Simulation
用于大涡模拟的积木流模型
  • 批准号:
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  • 财政年份:
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Large Eddy Simulation in Complex Turbulent Flows with Coarse Resolution
复杂湍流中的粗分辨率大涡模拟
  • 批准号:
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  • 财政年份:
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    $ 29.5万
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CBET-EPSRC: Deep Learning Closure Models for Large-Eddy Simulation of Unsteady Aerodynamics
CBET-EPSRC:用于非定常空气动力学大涡模拟的深度学习收敛模型
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职业:利用空间发展云转变的大涡模拟来理解低云反馈
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Applying large eddy simulation to dissipative particle dynamics modeling toward better understanding of complex flow phenomena
将大涡模拟应用于耗散粒子动力学建模,以更好地理解复杂的流动现象
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    22K03904
  • 财政年份:
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用于大涡模拟和形状优化的高阶非结构化方法
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