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Details of Grant 

EPSRC Reference: EP/R007470/1
Title: FENGBO-WIND - Farming the ENvironment into the Grid: Big data in Offshore Wind
Principal Investigator: Graham, Professor JM
Other Investigators:
Zhao, Professor X Palacios Nieto, Professor R Piggott, Professor MD
Researcher Co-Investigators:
Project Partners:
Centre for Env Fisheries Aqua Sci CEFAS DNV GL (UK) Energy Research Institute
Envision Energy FTI Consulting Illinois Institute of Technology
National Supercomputing Centre NSCC-Wuxi Queen's University of Belfast State Grid Corporation of China
State Oceanic Administration University of Cambridge University of Colorado at Boulder
Department: Aeronautics
Organisation: Imperial College London
Scheme: Standard Research - NR1
Starts: 03 July 2017 Ends: 02 January 2021 Value (£): 812,415
EPSRC Research Topic Classifications:
Energy - Marine & Hydropower Wind Power
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
04 Jun 2017 Joint UK China ORE Announced
18 May 2017 UK China ORE Announced
Summary on Grant Application Form
The proposed project will develop an integrated computational simulation approach capable of handling the complex interactions between the local atmosphere, the coastal ocean and sedimentary environment, farm aerodynamics, turbine response and grid integration in offshore wind farms. This will target a substantial reduction in the cost of energy in offshore wind by exploiting: high-fidelity optimization of array design and operation, tailored to a specific site and able to deal with realistic marine atmospheric boundary layer conditions, in particular the very slow dissipation of rotor wakes; combined with big-data analysis of very-large-scale simulations of the whole system under extreme conditions, to minimize integrity risks without overly conservative safety factors. Both situations will be investigated within the context of the development of offshore farms off the Chinese coast, which brings particular challenges regarding coastal characteristics (e.g. high sediment concentrations) and extreme events (in particular typhoons).

To achieve this we propose a multiscale approach to wind farm design and network integration that considers, first, a more accurate characterisation of extreme events (and active mitigation strategies) in the analysis through highly-resolved computer simulation; second, new optimization techniques for the design and operation of wind farms that allow for sustained power extraction using relevant knowledge of both the marine atmosphere and individual turbine (aeroservoelastic) dynamics; and third, robust grid design and operation strategies that accommodate wind resource variability and maximise the sustainability of energy generation. FENGBO-WIND will carry out the most ambitious computer simulations to date on farm dynamics and farm/environment interaction, to build physics-based predictive capabilities on farm output and investigate long-term interactions between farms and their local environment.

An interdisciplinary consortium of experts, including Earth/environmental scientists, civil and electrical engineers, and fluid dynamicists, have been assembled to tackle this challenging computational problem. The team will have access to (1) the world's largest supercomputer (Sunway TaihuLight) to carry out full system simulations of energy output and farm state for specific environmental scenarios, (2) operational data from existing wind farms off the Chinese coast as well as conditions at a target site through a partnership with a local grid company, and (3) performance data for a state-of-the-art wind turbine design from the leading Chinese manufacturer. The results will be benchmarked against state-of-the-art industrial design tools and protocols for grid integration for offshore wind farms.
Key Findings
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Potential use in non-academic contexts
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Organisation Website: http://www.imperial.ac.uk