University of Hull academics are at the heart of a £400,000 project which hopes to drive improvements in the offshore wind sector.
The national Operations & Maintenance (O&M) Centre of Excellence, a £2m collaboration between the University and ORE Catapult, has partnered with global offshore wind leader Ørsted to develop an innovative new approach to sea state forecasting.
The project team, led by academics from the University of Hull, is working closely with Ørsted to help improve wave forecast modelling with direct industrial impact.
It is hoped better monitoring of sea conditions will help drive efficiency in the sector, and deliver a significant reduction in missed working days.
Dr Rob Dorrell, Project Lead from the Energy & Environment Institute at the University of Hull, said: “This project is tackling critical challenges in operations and maintenance at the interface of offshore wind and the hostile marine environment.
“We are delighted to translate state-of-the-art artificial intelligence and remote monitoring systems to provide new solutions and methods to meet industrial challenges, enabling the drive towards enhanced cost-efficiency in offshore wind, thus furthering its viability as a clean energy solution.
“My colleagues and I - Drs Evdokia Tapoglou and Rodney Forster - are very much enjoying working with our partners on this collaboration, adding value and impact to an industry challenge.”
The Humber-based O&M Centre of Excellence (OMCE) is a £2 million collaboration between the University of Hull and the Offshore Renewable Energy (ORE) Catapult to drive solution-focused innovation and improvements in O&M.
The new model will contribute to improving the accuracy of sea state forecasting at an individual offshore wind turbine level, with the potential to drive efficiency gains in operations and maintenance, increasing safety, as well as contribute to further reductions in the Levelized Cost of Energy (LCoE) for offshore wind.
Turbine accessibility is a key determinant of a wind farm’s profitability. Technicians attempting to undertake maintenance can face a number of barriers to safe access, which in turn can be a factor in limiting turbine performance and ultimately overall energy output of a wind farm.
This new project will result in a wave forecasting model that will give greater accuracy and offer a more granular insight into the sea state within an offshore wind farm than current state-of-the-art methods can.