Blockage Effects In Large Scale Wind Farms

EPSRC项目描述：随着对可持续和可再生能源的需求不断增加，很明显，近海潮汐和风能资源将在实现净零目标方面发挥关键作用。为了满足对可再生能源的高需求，新的大型潮汐和风力发电场即将建成。这些多台机器的阵列表现出几个复杂的相互作用，这些相互作用极大地改变了它们的效率。一种这样的效应被称为阻塞效应。堵塞效应是由于相邻的涡轮机减速并使其周围的流场偏转而导致的涡轮机效率的变化。这既可以提高涡轮机效率，也可以降低涡轮机效率，这在拥有许多机器的大型阵列中最为普遍。阻塞效应取决于许多因素，例如涡轮机之间的间距和大气稳定性。了解堵塞效应是一个复杂的流体动力学问题，需要新的计算方法和分析模型的使用。该项目有几个目标：1。量化任意规模海上风电场的堵塞效应。使用新的方法模拟这些效果。建立预测堵塞效应大小的数学和计算模型。利用这项工作来告知和优化风力发电场的设计。实现这些目标将是最大化可再生能源输出的关键。要实现这些目标，必须使用许多方法。计算流体力学是一种研究得很好的方法，将在这些大规模动态结构的模拟中发挥关键作用。大涡模拟(LES)和雷诺平均Navier-Stokes(RANS)模拟在这一领域取得了很大的成功，但它们的计算复杂性很高，限制了模拟的规模。因此，探索替代的新方法是至关重要的。其中一种很有前途的方法是使用物理信息神经网络(PINN)。这些网络依赖于统计技术，同时确保物理性质，如守恒定律，保持不变。训练这样的模型允许对否则代价高昂的模拟进行快速计算。此外，这种技术还可以用来改进现有的简化模型，例如执行机构盘模型。该项目的影响延伸到了学术界、工业界和公众。公众越来越关注能源供应对环境的影响。作为回应，政府实体正在制定雄心勃勃的扩张计划，以解决这些担忧。执行此类计划需要与行业合作伙伴的合作，这些合作伙伴在生产高效和财务上可行的产品方面发挥着关键作用。因此，能源生产的优化设计受到很多方面的追捧，在向净零排放转变方面将是无价的。该项目属于EPSRC工程主题以及EPSRC能源和脱碳主题，是EPSRC风能和海洋能源系统与结构(WAMESS)博士培训中心(CDT)的一部分。

EPSRC Project Description:With the increasing demand for sustainable and renewable energy sources, it is clear offshore tidal and wind energy sources will play a pivotal role in reaching the net zero target. To meet the high demand for renewable energy, new large-scale tidal and wind farms are soon to be constructed. These arrays of multiple machines exhibit several complex interactions that drastically alter their efficiency. One such effect is known as the blockage effect. The blockage effect is the change in efficiency of a turbine due to neighbouring turbines slowing and deflecting the flow field around them. This can work to both increase and decrease turbine efficiency and is most prevalent in large scale arrays with many machines. The blockage effect depends on a number of factors such an inter-turbine spacing and atmospheric stability. Understanding blockage effects poses a complex fluid dynamic problem and will require novel use of computational methods and analytical modelling. This project has a number of aims:1. Quantify blockage effects in arbitrary size offshore wind farms.2. Simulate these effects using novel methodologies.3. Develop mathematical and computational models for predicting the magnitude of the blockage effect.4. Use this work to inform and optimise wind farm design.Achieving these aims will be key in maximising renewable energy output.To achieve these aims, a number of methods must be used. Computational fluid dynamics is a well-researched methodology and will play a crucial role in the simulation of these large-scale dynamic structures. Large eddy simulations (LES) and Reynolds averaged Navier-Stokes (RANS) simulations have seen great success in this field but have high computational complexity putting restraints on the scale of the simulations performed. For this reason, it is vital to explore alternative novel methods. One such promising method is the use of physics-informed neural networks (PINNs). These networks rely on statistical techniques while ensuring physical properties, such as conservation laws, remain unaltered. Training such a model allows for fast computation of otherwise costly simulations. In addition, such techniques can be used to enhance existing simplified models such as the actuator disk model. The project's impact extends to academia, industry, and the public. The public are becoming increasingly concerned with the environmental impact of their energy supply. In response, governmental entities are formulating ambitious plans for expansion to address these concerns. The execution of such plans requires collaboration with industrial partners, who play a crucial role in producing efficient and financially viable products. Thus, optimal design in energy production is heavily sought after by many parties and will be invaluable in the transfer to net zero emissions.This project falls within the EPSRC engineering theme as well as the EPSRC energy and decarbonisation theme and is part of the EPSRC Wind & Marine Energy Systems & Structures (WAMESS) Centre for Doctoral Training (CDT).