Research projects
- Research area
Push the Frontiers of Offshore Wind Technology
- Institution
University of Hull
- Research project
OPtimisation EXplainability (OPEX) for Maintenance Scheduling of Offshore Wind Farms
- Lead supervisor
Professor Yiannis Papadopoulos (Professor – Faculty of Science and Engineering, University of Hull)
- PhD Student
- Supervisory Team
Professor Dhaval Thakker (Professor of Artificial Intelligence(AI) and Internet of Things(IoT) - Faculty of Science and Engineering, University of Hull, University of Hull)
Dr Koorosh Aslansefat (Lecturer/Assistant Professor - Faculty of Science and Engineering, University of Hull, University of Hull)
Project Description:
The increasing utilisation of Artificial Intelligence has brought revolutionary changes across various sectors, but the challenge of explainability often leads to mistrust among users. This problem is not exclusive to ‘black-box’ machine learning methods but also extends to ‘white-box’ algorithms like optimization. Our project aims to address this challenge by focusing on Optimisation Explainability (OPEX) in maintenance scheduling for offshore wind farms. The goal is to optimize maintenance schedules in a way that is not only efficient but also transparent, and interpretable, to the human user, fostering trust and contributing to sustainability in the energy sector. In other words, one should be able ask the algorithm how did you find this optimal solution? Which parameter(s) was/were more influential for getting the optimal solution?
