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 Our ability to optimise wind farms is currently hampered by an over-reliance on out-of-date empiricism.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.

Potential Impact:
The beneficiaries of the research, beyond academia, will be in the wind energy industry, the public sector and ultimately the general public. Wind energy, and in particular offshore wind energy, is the single most important constituent of the UK's sustainable energy strategy for achieving a de-carbonised economy by 2050. The UK boasts Europe's best wind resource yet offshore wind energy only accounted for 8% of the UK's power in 2018. The UK government has agreed with the industry to install in excess of 30GW of offshore wind capacity by 2030. However, to meet these targets requires improvements in efficiency since the UK Government's agreed strike price per MWh produced from new offshore wind farms has fallen from £150 to £40 in just 10 years. This has happened concurrently to a realisation within the industry that existing models for predicting the power output from offshore wind farms are no longer reliable since they rely on out-dated empiricism. This research will revolutionise the field of wind farm optimisation by producing a physics-based tool to design optimally laid out wind farms and thereby generate immediate impact in ensuring that the UK is able to meet its 2030 and 2050 targets. In particular it will tackle key roadblocks to the improvement of efficiency of offshore wind power as identified by the industry itself. These include accurate near-wake modelling, accurate prediction of wake spreading and the global blockage phenomenon for wind farms.

To accelerate the impact that I will produce I have partnered with three organisations to assist with the following:
1. Reassurance of the scalability of the models that are developed from laboratory-scale to reality
2. Access to specific datasets that are an essential for the development of the optimisation tool
3. Delivering and disseminating the open-source tool directly to the industry

For these reasons I have partnered with Vestas who are one of the largest wind turbine manufacturers in the world, Frazer-Nash Consultancy who work with numerous offshore wind energy customers and the University of Oldenburg. The University of Oldenburg have the pre-eminent wind-energy wind tunnel in Europe which they are making available to the present research. With their expertise in producing realistic, atmospheric like turbulence within their enormous (3 x 3 x 30m test section) wind tunnel they will accelerate the impact that this research will deliver by ensuring that the question of scalability from laboratory to reality is addressed. Vestas will provide me with blade geometry data, as well as wake data from their offshore wind sites that will help with the formation and tuning of the predictive models embedded within the wind-farm optimisation tool. Frazer-Nash will provide technical advice and a direct dissemination route to the companies that will be responsible for building the UK's next generation of wind farms.

I will organise an industry/academia engagement workshop towards the conclusion of the project. I will exploit the fact that one of my collaborators at the University of Oldenburg is a former president of the European Academy of Wind Energy to ensure that a high-calibre list of attendees from across Europe attends the workshop. I will also include key UK stakeholders in the offshore wind energy sector, including Government, to ensure that the output of this research translates to impact as quickly as possible. Frazer-Nash have agreed to give guest lectures at Imperial College London for the duration of the project to highlight the attractiveness of working in the offshore wind energy sector to Imperial's talented cohort of students. The project will also directly feed four talented young researchers into the UK's employment market place, whether academic or industrial.