Improved vertical wind profile estimations to support offshore wind farm maintenance and operations activities
PhD project title and outline, including interdisciplinary dimension:
Improved vertical wind profile estimations to support offshore wind farm maintenance and operation activities
This work will improve vertical wind profile estimations to better manage wind turbine operations and
maintenance (O&M) tasks (e.g. deterioration of rotors, nacelle, bearings, seals and joints, delivery and
booking of parts, access platform, cranage and helicopter operations and safer work environments)1, 2.
Currently O&M tasks are dependent on favourable wind conditions up to turbine rotor height and above.
Events such as high wind shear, wind veer and gusts negatively impact such operations result in structural
imbalance and dynamics with resultant deterioration, lost energy resource harnessing, extra down time and
lower energy production3. In fact O&M accounts for 25–30%4 of the total lifecycle costs for wind farms,
estimated at 3.5 c€/kWh5 for older turbines based on experience in the UK, Germany and Denmark. The aim
of the project is to use a weather window approach to incorporate information on vertical wind profiles
including wind shear, wind veer and turbulence into wind turbine O&M tasks.
First, an analysis framework to profile the wind shear, wind veer and turbulence impacts on the structural
mechanisms, transients and dynamics of a wind turbine will be designed in QUB. Second, site measurements
and the high‐resolution wind forecasts available from Dr Paul Leahy at UCC will be examined to extract
atmospheric stability information and develop improved stability‐corrected vertical wind profile models.
Third the site measurements and the high‐resolution wind forecasts developed will be proved using Dr Paul
Leahy LiDAR ZephIR 175 vertical wind profiler. This is take place during a one month planned placement in
Year 1 at UCC. Next, the outputs of this ground‐toothing exercise will be looped into the framework using the
QUB expertise in wind power systems, O&M, materials performance of blades/rotors and structural analysis
expertise during the planned 3 to 6 month placement in ServusNet Informatics Limited (ServusNet). The
project will ultimately determine the potential benefits and challenges of ‘O&M weather windows’ using
improved atmospheric stability estimates for vertical shear and the key deliverable will be a proprietary
software tool called ‘Platooning O&M weather window (POWW).’
The interdisciplinary aspects of the project are combining meteorological data with data analytics framework,
advanced computational fluid dynamics (CFD) and forecasting and datamining techniques with logistics and
O&M planning across mechanical, aerospace, civil and environmental and electrical engineering. The
innovative and novel aspect of the project will be an intelligent POWW proprietary software tool framework
developed as part of the project will enhance significantly array and individual wind turbine operation and
performance in order to;
1) optimise power extraction from the wind stream,
2) minimise fatigue loading on the turbine blades and tower and,
3) minimise wake effects within the array and 4) get ready for ‘extreme’ events in the order of 5%, which is
significant in monetary terms.
Primary supervisor: Dr. Aoife Foley (Mechanical and Aerospace Engineering)
Professor Jian‐Fei Chen (Natural and Built Environment)
Dr. Giuseppe Catalanotti (Mechanical and Aerospace Engineering)