Accurate modelling of wind turbine wake spreading through consideration of realistic turbulent entrainment: revolutionising wind farm optimisation

风能目前占英国电力的18%，但为了到2050年实现低碳经济，这一比例必须在未来十年内大幅增加。英国政府已承诺在2030年之前每年增加1-2吉瓦的海上风电容量，这反映了该国拥有欧洲海上风电的一些最佳地点。随着英国越来越依赖风能，提高风电场的效率和可靠性变得越来越重要。由于位于上游机器的尾流中的风力涡轮机产生的功率较小，并且比上游机器经历更高的疲劳载荷，因此通过提高我们预测风力涡轮机产生的尾流的能力，从而在已知盛行风条件的情况下设计最佳布局的风力发电场，可以实现这一目标。我们优化风力发电场的能力目前受到过度依赖过时风力发电的阻碍。该提案旨在通过开发基于物理的建模工具来纠正这一点，以更好地描述单个风力涡轮机尾流以及风电场内相互作用的尾流之间的相互作用。与陆上风电场相比，海上风电场的主导风况稳定，因此海上风电场特别适合优化。风力涡轮机的最佳间距取决于几个因素。这些都是希望从给定地点产生尽可能多的功率，同时最小化维护成本，以响应由位于上游机器的高度不稳定的湍流尾流中的涡轮机引起的疲劳损坏。这需要可靠地预测风力涡轮机尾流的扩散，以及响应于预测的流入条件来估计风力涡轮机部件的疲劳寿命的方法。此外，存在预测全局阻塞的问题，其中风力发电场作为整体具有使风转向风力发电场上方/周围的效果，这意味着到发电场的真实流入风速与盛行风不同。具体来说，我们将：1。进行创新实验，以更好地了解支撑湍流尾流传播的流动物理学。这将涉及探索在多个长度尺度同时引入的相干性之间的近尾流中的相互作用，例如，塔架、机舱和叶尖涡流。此外，我们将探索由于夹带现象而产生的尾流扩散背后的物理学，夹带现象是质量/能量从背景转移到尾流中的过程。特别是，我们将集中在大气，尾流，湍流对湍流的影响。把这种新的物理理解转化为一个基于物理的模型，用于单个风力涡轮机尾流的传播。设计一种方法，对脆弱的风力涡轮机部件（例如齿轮箱/后缘粘合等）的疲劳寿命进行准确预测。响应大气/尾流湍流引起的波动入流。制作一个模型来校正整个风电场对迎面而来的风的全球阻塞。最后，开发一种低成本、基于物理的风电场优化工具，并将其推广到英国的风能部门。该模型将采用待安装涡轮机的详细信息、指定地点的大气条件以及为发电量支付的商定履约价格/兆瓦时作为输入。输出将是高效海上风电场的风力涡轮机的最佳数量和布局。我们已经吸引了来自风能行业的三个合作伙伴，他们将在确保这项研究的成果以行业可以立即实施的形式传播给英国的主要利益相关者方面发挥重要作用。

Wind energy currently produces 18% of the UK's power but, in a drive towards a de-carbonised economy by 2050, this proportion must increase substantially over the next decade. The UK government has committed to increase offshore wind power capacity by 1-2 GW per year until 2030, reflecting the fact that the country contains some of the best locations for offshore wind in Europe. As the UK becomes more reliant upon wind energy, it is of increasing importance to improve both the efficiency and reliability of wind farms. Since wind turbines which lie in the wakes of upstream machines produce less power and experience higher fatigue loading than those upstream, there is scope to achieve this goal by improving our ability to predict the wakes generated by wind turbines and thereby design an optimally laid out wind farm given knowledge of the prevailing wind conditions. Our ability to optimise wind farms is currently hampered by an over-reliance on out-of-date empiricism. This proposal seeks to rectify this by developing physics-based modelling tools to better describe individual wind-turbine wakes as well as the interactions between interacting wakes within a wind farm. Offshore wind farms are particularly amenable to optimisation due to the stability of the prevailing wind conditions in comparison to onshore sites.Optimal spacing of wind turbines revolves around several factors. These are the desire to produce as much power as possible from a given site whilst at the same time minimising maintenance costs in response to fatigue damage caused by turbines sitting in the highly unsteady, turbulent wake of an upstream machine. This requires confident prediction of the spreading of wind turbine wakes plus a methodology to estimate the fatigue lifetime of wind turbine components in response to their predicted inflow conditions. In addition, there is the problem of predicting the global blockage in which the wind farm as a whole has the effect of diverting the wind over/around the wind farm meaning that the true inflow wind speed to the farm is not the same as the prevailing wind. Specifically, we will:1. Perform innovative experiments in order to better understand the flow physics underpinning the spreading of turbulent wakes. This will involve exploring the interactions in the near wake between the coherence introduced at multiple length scales simultaneously by, for example, the tower, nacelle and blade-tip vortices. In addition we will explore the physics behind the spreading of the produced wake due to the phenomenon of entrainment, which is the process by which mass/energy is transferred from the background into the wake. In particular we will focus on the effect of atmospheric, and wake, turbulence on entrainment.2. Take this new physical understanding and translate it into a physics-based model for the spreading of an individual wind-turbine wake.3. Devise a methodology to make accurate predictions for the fatigue lifetime of vulnerable wind-turbine components (e.g. the gear box/trailing edge bond etc.) in response to the fluctuating inflow caused by atmospheric/wake turbulence.4. Produce a model to correct for the global blockage that an entire wind farm represents to the oncoming wind.5. Finally, develop a low-cost, physics-based wind farm optimisation tool and disseminate it to the UK's wind-energy sector. The model will take as inputs the details of the turbines to be erected, the atmospheric conditions at the specified site and the agreed strike price/MWh to be paid for the generated power. The output will be the optimal number and layout of wind turbines for an efficient offshore wind farm. We have attracted three partners from across the wind-energy sector who will play a vital role in ensuring that the output of this research is disseminated to the key stakeholders in the UK in a form that can be implemented by the industry straight away.