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Details of Grant 

EPSRC Reference: EP/S012141/1
Title: Modelling the Impact of Large Floating Wind Turbines on Offshore Navigation and Safety Critical Radar Systems
Principal Investigator: Danoon, Dr L
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Easat Radar Systems Limited
Department: Electrical and Electronic Engineering
Organisation: University of Manchester, The
Scheme: New Investigator Award
Starts: 01 February 2019 Ends: 30 April 2020 Value (£): 138,218
EPSRC Research Topic Classifications:
RF & Microwave Technology Wind Power
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
04 Sep 2018 EPSRC ICT Prioritisation Panel September 2018 Announced
Summary on Grant Application Form
It has been well reported that wind farms can impact and degrade the performance of radar systems for air traffic control, air surveillance, early warning systems and navigational. The potential interference generated by the scattering characteristics of wind turbines on radar systems is considered a significant issue and has received a lot of attention from the research community and industry alike. However, due to the geometrical complexity of the turbine structure and its enormous electrical size at radar frequencies, the study and modelling of the radar scattering presented a substantial challenge to the research community. The use of commercial Computational Electromagnetic (CEM) tools and other full-wave solvers was limited to a small number of predefined turbine orientations due to the inherent requirement of supercomputing environment or extended modelling runtimes.

To accommodate for the growth in demand for renewable energy, larger wind farms are being planned for deployment further offshore -in deeper waters and less favourable seabed conditions. Floating foundations are being widely proposed to reduce costs and enable more rapid growth of offshore wind turbines. Future wind developments (Such as Hornsea Project Two and Three) included floating foundations within their Design Envelope. Some of these projects are located near a number of key shipping routes as well as offshore O&G platforms with REWS installations.

To date, the effects of floating foundation on the operation and efficiency of navigational and safety radar systems operating near or within the wind farm is currently largely unknown. Large floating wind turbines will have unique scattering characteristics due to its size, construction materials, vibration profile and movements under wind loading and adverse weather/sea conditions. Floating turbines are likely to dramatically change the radar cross section and its dynamics and consequently impact radar systems.

This project will study the effects of wind turbines mounted on floating foundations on offshore radar operations. The project will develop radar scattering models for the floating foundations and account for important parameters such as geometry, materials and platform movement under adverse weather conditions. This project will build on the recently awarded Supergen funding to measure and model the radar scattering from the large 7MW turbine managed by ORE Catapult. The project will analyse the measured data from the ORE Catapult turbine as well as the large dataset of wind farm/radar measurements made available to the University of Manchester by the Council for Scientific and Industrial Research (CSIR) in South Africa to further develop the existing turbine models and integrate them with the new models of the floating foundations. The analysis, verification and integration of measurements with the modelling capabilities will give a good representation of future offshore turbine. This will then be used to model the static radar returns and Doppler signature generated from the turbines under typical and adverse conditions for safety critical radar operations such as navigation under poor visibility, search and rescue efforts and REWS for collision prevention with offshore O&G assets.
Key Findings
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Organisation Website: http://www.man.ac.uk