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

风电场和复杂地形的混合物理统计建模 - CASE 项目

基本信息

批准号：
2440351
负责人：
金额：
--
依托单位：
University of Oxford
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2440351
关键词：
Hybrid physical statistical modelling wind

项目摘要

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.

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电场的设计和优化中是必不可少的部分。每个涡轮机周围的流动的小尺度细节可以反馈到大尺度环境上，以影响整个涡轮机阵列上的风能的可用性。风力发电场建模的这种多尺度性质与复杂地形上的气流建模有许多共同的理论基础。在天气和气候模型中，靠近地球表面的未解决的特征，如小山，植被和建筑物对大气产生了阻力。准确地对这种阻力进行建模不仅对于正确预测大气近地表条件很重要，而且对于天气/气候模型在较长提前时间内的整体轨迹也很重要，因为信息会大规模传输到解析流中。对于这两个建模问题，关键问题是如何大规模的大气流动是调制的动量交换与小规模的功能在地球表面附近。这个博士项目将建立在牛津大学和英国气象局之间正在进行的合作，在该地区的多尺度建模的大型风力发电场。我们最近的研究表明，一个相对简单的理论模型，从动量守恒定律在两个尺度耦合的方式，可以预测的关键影响，大气与风力涡轮机的相互作用，令人满意的各种现实的大气稳定性条件下（或风廓线）。这促使扩展的两尺度耦合流模拟到更复杂的问题，包括那些复杂的地形上的流动，在复杂地形上的流动模拟的主要困难之一是参数化湍流地形形状阻力（TOFD）的小尺度地形，是在大气流动模式中无法解决的。英国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，目前英国气象局天气预报模型（UM）中使用的公式无法处理新地形数据集提供的更广泛的尺度。因此，开发了一种基于双尺度耦合流模型概念的新方法，并在此DPhil项目中使用，以改善TOFD的参数化。该学生将由Takafumi Nishino博士（牛津大学工程科学系土木工程研究组）和托马斯邓斯坦博士（英国气象局大气过程和参数化组）共同指导。学生还将有机会与英国气象局的科学家一起工作，在一个位置（约6个月），以及通过定期研究会议。该项目的预计开工日期为2020年10月。