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

• 批准号: 1045189
• 负责人: Charles Meneveau
• 金额: $ 29.5万
• 依托单位: Johns Hopkins University
• 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
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1045189&HistoricalAwards=false
• 关键词: Large; Eddy; Simulation; Studies; situ

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.

该研究将开发和应用计算工具，以预测和理解非常大的风电场中的热量和水分等标量的通量。 这些通量在陆地大气耦合和可能的扰动中起着至关重要的作用，这可能是由于陆地 - 大气界面的修改而引起的，随着风能的预期全球增长。 目前，风电场的效果在区域尺度和全球尺度模型中使用有效的粗糙度长度进行了参数化，有时还会增加由于唤醒而增加的湍流动能。 这种方法继续基于大气边界层（ABL）的经典相似性理论。 该理论假定统一的土地表面，但也经常发现在土地表面的异质特征（例如由唤醒引起的异质性和风力涡轮机的其他影响）的流动中被发现。 这是由于ABL中的湍流，这有效地融合了整个景观中的各种来源和不均匀性。但是，这种参数化的适当性以及要使用的参数的值是高度不确定的，尤其是在一般大气条件下风电场（对流，稳定，中性）的情况下。智能优点：相关的高分辨率数据将通过一系列适当选择的参数范围（LES）的范围（LES）准确地量化，从而使相关的高分辨率数据可准确地产生。预计在地面下，在风力涡轮机阵列下方。 这些LE解决了风力涡轮机后面的大部分单个唤醒以及对混合和夹带的伴随修改。该模拟将涵盖广泛的大气条件（中性，对流，稳定）和风电场布置（涡轮间距，地面特性，负载因子）。 在相当理想化的条件下获得的计算结果将与风电场中的原位观察结果相辅相成。 现场研究将通过与瑞士的研究人员的国际合作进行，这些研究人员可以进入西班牙扎拉戈萨附近的拉穆拉风电场。 将分析经过验证的模拟的结果，其特定目的是为包括风力涡轮机阵列在内的大气边界层得出新的Monin-Obukhov型关系。 例如，修改后的稳定性校正和修改的有效标量粗糙度长度将作为相关参数的函数得出。 这项研究的结果将更准确地预测具有局部和区域气象条件，区域规模蒸发等广泛风电场的反馈机制。Baroader的影响：动量的区域尺度表面磁通量，明智的热和水蒸气在量化和理解各种山间和时间级别的水和能量周期中起着至关重要的作用。 随着计算建模的出现，人们对人造修饰对土地表面对土地大气相互作用的影响的影响有了很多了解。风能作为造成可再生能源投资组合的重要促进者的生长表明，美国和世界的不可忽略的部分最终可用于大型风电场。在这种情况下，预测和更好地理解与土地和气氛结合的物理过程是一个非常及时且关键的研究领域。毕业生教育和培训将强调模拟，参数化和原地实地实验活动之间的相互作用。招聘和教育外展将利用综合研究生教育和研究实习生（IGERT）来建模复杂系统以及PI通过波多黎各的联系来招募美国西班牙裔研究生的持续努力。 通过为初中或高中生提供研究经验，PI将积极继续进行巴尔的摩当地的高中生的持续宣传。