Global Offshore Wind is one of the premier offshore wind events and the world’s largest offshore wind market. This exciting sector comes to life over two jam-packed days of political keynotes, expert panels, debates, procurement tenders, sector deal updates, disruptive innovation, business partnering, international pavilions, inward delegations and poster presentation.
This year at Global Offshore Wind (GOW2019) Koorosh Aslansefat, PhD student in Computer Science at the University of Hull under supervision of Professor Yiannis Papadopoulos, won the best poster award. The poster was about “DREAM: Data-driven Reliability-centred Evolutionary and Automated Maintenance for Offshore Wind Farms”, and the following objectives were mentioned:
- Development of a tool to derive an experimental platform to provide a data-driven reliability-centred evolutionary automated maintenance. This tool can be an extension of the HIP-HOPS.
- Evaluation in a real case study of the offshore wind farm. This study used real SCADA data from Teesside Offshored Wind Farm and it going to be tested in this farm with the collaboration of EDF Energy and University of Hull.
- Using the tool in parallel with O&M managers to tune the platform through reinforcement learning.
This project is undertaken within the Dependable Intelligent Systems group in Computer Science, in collaboration with Professor Jim Gilbert in Engineering. We pioneer internationally methods and tools for design of dependable systems. Tools include HiP-HOPS and Safety Designer, the latter together with ESI-ITI GmbH. We have led new AI algorithms which imitate the hunting behaviour of Penguins, and have shown that they apply to the safety of autonomous cars. The BBC has run an article on “Hungry Penguins Keep Car Code Safe“. Our tools have been taken up by several major automotive and other corporations.
This project is supported by EDF Energy R&D UK Centre, AURA Innovation Centre and the University of Hull.