Completed Clean Energy Mathematics & Statistics

MAXFARM (MAXimizing wind Farm Aerodynamic Resource via advanced Modelling)

In plain English

AI plain-English summary

Offshore wind turbines in a large farm interfere with each other through their wakes, reducing power output and causing structural damage that drives up costs. This project tackles a fundamental gap in wind farm design: current models treat turbines as independent units, but in a large offshore array, each turbine’s wake affects the wind flow, loads, and fatigue on every turbine downstream. The team brings together meteorology, aerodynamics, structural mechanics, and control systems to model the entire flow-field through a wind farm—including turbulence and wake interactions—rather than simulating turbines in isolation. If successful, the research could lower the levelised cost of electricity from offshore wind by enabling smarter control strategies. Instead of each turbine maximising its own output, the farm would be managed as a whole: some turbines may run below peak power to reduce damaging loads on downstream machines, keeping maintenance costs low while maximising total farm output. This directly supports the UK’s need for large-scale, cost-effective offshore wind to meet emissions targets.

View original technical description
This is a multidisciplinary project that brings together researchers from different academic backgrounds in order to address reliability, lifetime and efficiency in offshore wind farms, and to meet the needs of the UK electricity generation industry. The overarching aim is the reduction of the (levelised) cost of generation of the large offshore wind farms that the UK will need in order to meet national and international objectives in the reduction of CO2 emissions. The multidisciplinary aspect reflects the different but, in context, linked disciplines and brings together the growing discipline of energy meteorology, of aerodynamics and aeroelasticity, of fatigue and structural mechanics, and of systems control. That is, the approach is a holistic one, linking the environmental conditions with their impact on each rotor and the mechanisms to improve farm performance as a whole. The meteorological contribution is essential because of the range of wind flow conditions that exist, subjecting the turbines and - importantly for large wind farms - the wakes of the turbines to a range of unsteady conditions that are known to reduce wind farm efficiency, and to cause increased structural damage (when compared to small-scale onshore wind farms). Both these contribute to increased capital and operating costs. The energy potential for the UK from offshore wind is huge, but offshore wind energy is still at a relatively early stage in technological terms. The aerodynamic response of each turbine to a variety of conditions imposed by the wind flow and the wakes of upstream turbines depends on the aeroelastic behaviour of the blades, the load in turn imposed upon the turbine generator, and the response by the turbine control system. In a large wind farm, the behaviour of one turbine - principally how much energy it is extracting from the wind flow - affects the behaviour, efficiency and lifetime of wind turbines in its wake; the turbines are not independent of each other. In fact, all aspects of the performance of wind turbines within large offshore wind farms, whether power output, loads or operations, are affected by their interaction through the wakes. Hence, to improve the cost effectiveness of offshore wind energy requires a better understanding of the flow-field through the wind farm. The project will address this issue and develop models to better represent the flow-field including the wakes and turbulence. Furthermore, capitalising on this, the implication for loads on the individual wind turbines will be investigated and the design of control strategies will be explored that achieve optimal operation of a large wind farm with each turbine controlled to keep operations and maintenance costs to acceptably low levels whilst (subject to this constraint) maximising farm output.

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Researchers

Alan Robins (Co-Investigator)Bill Leithead (Co-Investigator)David Birch (Co-Investigator)Hong Yue (Co-Investigator)Jim Halliday (Co-Investigator)John Graham (Co-Investigator)Matteo Carpentieri (Co-Investigator)Philip Hancock (Principal Investigator)Rafael Palacios Nieto (Co-Investigator)Simon Watson (Co-Investigator)

Related Research

Grants with similar aims, by meaning.

Extremes, Performance and Longevity for Offshore Renewable Energy Resilience
HOME-Offshore: Holistic Operation and Maintenance for Energy from Offshore Wind Farms
Accurate modelling of wind turbine wake spreading through consideration of realistic turbulent entrainment: revolutionising wind farm optimisation
Data-driven Infrastructure Planning for Offshore Wind Farms
CBET-EPSRC: Unwinding entrainment processes in wind farm to wind farm interactions

Original classification

Research Grant

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