Hybrid physical-statistical modelling of wind farms and complex terrain - CASE project

大型风力涡轮机阵列的空气动力学建模是一个复杂的多尺度问题，但在不断增长的风力发电厂或风力发电场的设计和优化中是必不可少的部分。每个涡轮机周围流动的小范围细节可以反馈到大范围环境中，从而影响整个涡轮机阵列的风能可用性。风电场模拟的这种多尺度性质与复杂地形上的流动模拟有许多共同的理论基础。在天气和气候模型中，小山、植被和建筑物等靠近地球表面的未解决的特征会对大气造成拖累。准确地模拟这一阻力不仅对于正确预测大气的近地表条件很重要，而且对于天气/气候模式在很长一段时间内的整体轨迹也很重要，因为信息会向上传输到已分解的气流上。对于这两个建模问题，关键问题是大尺度大气流动是如何通过与地球表面附近小尺度特征的动量交换来调制的。DPhil项目将建立在牛津大学和英国气象局在大型风电场多尺度建模领域的持续合作基础上。我们最近的研究表明，一个相对简单的理论模型，从动量守恒定律出发，以双尺度耦合的方式，可以满意地预测在各种实际大气稳定条件(或风廓线)下大气与风力涡轮机相互作用的关键效应。这促使双尺度耦合流动模拟扩展到更复杂的问题，包括复杂地形上的流动问题。复杂地形上流动模拟的主要困难之一是对小尺度地形的湍流地形阻力(TOFD)进行参数化，这在大气流动模型中是没有解决的。气象局最近对新的高分辨率地形数据集的使用进行的一项调查表明，气象局目前使用的天气预报模式(UM)不能处理新的地形数据集提供的更广泛的尺度范围。因此，发展了一种基于双尺度耦合流动模拟概念的新方法，并将其应用于DPhil项目中，以改进TOFD的参数化。这种针对复杂地形的双尺度耦合流动模型的扩展也将有助于进一步改进大型风力发电场的建模。学员将由牛津大学工程科学系土木工程研究小组的Takafumi Nishino博士和英国气象局大气过程和参数化组的Thomas Dunstein博士共同指导。学生还将有机会在实习期间(大约6个月)和气象局的科学家一起工作，以及通过定期的研究会议。该项目预计开工日期为2020年10月。

Modelling the aerodynamics of large wind turbine arrays is a complex multi-scale problem, but is an essential part in the design and optimisation of ever-growing wind power plants or wind farms. The small-scale details of the flow around each turbine can feed back onto the large-scale environment to affect the availability of wind energy across the whole turbine array. This multi-scale nature of wind farm modelling shares much common theoretical ground with the modelling of flow over complex terrain. In weather and climate models, unresolved features near the earth's surface such as small hills, vegetation and buildings impart a drag on the atmosphere. Accurately modelling this drag is important not only for correctly forecasting near-surface conditions of the atmosphere, but also for the overall trajectory of the weather/climate model over a long lead time due to an up-scale transfer of information onto the resolved flow. For both of these modelling problems, the key question is how the large-scale atmospheric flow is modulated by an exchange of momentum with small-scale features near the earth's surface.This DPhil project will build on an ongoing collaboration between the University of Oxford and the UK Met Office in the area of multi-scale modelling of large wind farms. Our recent study has demonstrated that a relatively simple theoretical model, derived from the law of momentum conservation in a two-scale coupled manner, can predict the key effect of atmospheric interaction with wind turbines satisfactorily under a variety of realistic atmospheric stability conditions (or wind profiles). This motivates an extension of the two-scale coupled flow modelling to more complex problems, including those of flow over complex terrain.One of the main difficulties in the modelling of flow over complex terrain is to parameterize Turbulent Orographic Form Drag (TOFD) for small-scale terrain that is unresolved in an atmospheric flow model. A recent investigation at the Met Office into the use of new high-resolution orographic data sets suggests that the formulation currently used in the Met Office's weather prediction model (UM) is not capable of handling the much broader spectrum of scales available from the new orographic data sets. A new approach based on the concept of two-scale coupled flow modelling is therefore developed and used in this DPhil project to improve the parameterization of TOFD. Such an extension of the two-scale coupled flow modelling for complex terrain will also help improve the modelling of large wind farms further.The student will be supervised jointly by Dr Takafumi Nishino (Civil Engineering Research Group in the Department of Engineering Science, University of Oxford) and Dr Thomas Dunstan (Atmospheric Processes and Parameterizations Group, UK Met Office). The student will also have opportunities to work together with scientists at the Met Office during a placement (for approximately 6 months) as well as through regular research meetings. The expected start date of the project is in October 2020.