April 2nd 2017 – March 31st 2020
This project will undertake the research necessary for the remote inspection and asset management of offshore wind farms and their connection to shore, an industry which will be worth £2billion annually by 2025 in the UK alone. At present most asset management is still undertaken manually onsite. Remote monitoring therefore has significant potential to improve safety and reduce costs. This project aims to use artificial intelligence, robotics, advanced sensing and the latest in state of the art modelling to achieve a step-change in actionable data for wind farm operators, manufacturers and so reduce costs for the electricity bill- and tax payer.
Typically, 80-90% of the cost of offshore Operation and Maintenance (O&M) according to the Crown Estate is a function of accessibility during inspection – the need to get engineers and technicians to remote sites to evaluate a problem and decide what remedial action to undertake. Minimising the need for human intervention offshore, is a key route to maximising the potential, and minimising the cost, for offshore low-carbon generation. This will also ensure potential problems are picked up early, when the intervention required is minimal, before major damage has occurred and when maintenance can be scheduled during a good weather window. As the Crown Estate has identified: ‘There is an increased focus on design for reliability and maintenance in the industry in general, but the reality is that there is a still a long way to go. Wind turbine, foundation and electrical elements of the project infrastructure would all benefit from innovative solutions which can demonstrably reduce O&M spending and downtime’.
This programme grant will bring together and consolidate theoretical underpinning research from a variety of disparate prior research grants, in different subject areas and at different universities. Life-time, reliability and physics of failure models will be adapted to provide a holistic view of wind-farms system health and include these new automated information flows (Theme 1). Advanced robotic monitoring (Theme 2) and advanced sensing techniques (Theme 3) will be integrated into diagnostic and prognostic schemes which will allow improved information to be streamed into multi-physics operational models for offshore windfarms. While aspects of the techniques required in this offshore application have been previously used in other fields, they are new for the complex problems and harsh environment in this offshore system-of-systems. ‘Marinising’ these methods is a substantial challenge in itself.
Figure 1 – Project Overview by Theme (first number) and Workpackage
HomeOffshore brings together leading international experts in the fields of wind-engineering, offshore generation connection, condition monitoring, robotics, power electronics and reliability, and data analytics:
- Electrical power chain and connection to shore modelling – Prof. Mike Barnes and Peter Green, University of Manchester have investigated power electronic interfaces for grid connection with funded research by utilities and major manufacturers. Prof Barnes was part of the management committee for EPSRC Supergen Wind (EP/H018662/1, 2010-4), a six university, 24 partner project which was the EPSRC’s main focus of wind farm design research, and he leads this project.
- Offshore mechanical structures modelling – Dr Maurizio Collu, Cranfield University is a Senior Lecturer in Dynamics of Offshore Structures, is a member of the ITTC Offshore Engineering Committee, and led the conceptual design of the foundation in the £2.8m ETI project NOVA.
- System reliability modelling – Dr Chris Crabtree and Dr Behzad Kazemtabrizi at Durham University specialise in operation and maintenance aspects of wind energy, Their research has been supported by industrial partners including DONG Energy, DNV GL (formerly Garrad Hassan) and E.ON.
- Data analytics – Prof Goran Nenadic and Prof John Keane at the University of Manchester have research focused on actionable data and text analytics. Their work is multi-disciplinary and applied to data-intensive fault-critical systems such as in clinical sciences, military intelligence and industrial biotechnology. In 2013 they received an IBM Faculty Award in “Big Data Engineering”.
- Aerial assist robot monitoring – Dr Bill Crowther at the University of Manchester is a CAA approved UAV operator with a research focus on Unmanned Air Vehicles (UAVs) and autonomous systems.
- Robotic station monitoring – Dr. Simon Watson at the University of Manchester researches mobile robotic systems for the exploration and characterisation of hazardous environments.
- Subsea robot assist monitoring and cable monitoring – Dr. David Flynn, Prof David Lane, FRS, CBE and Dr Keith Brown have a long track record in innovation in Robotics. They are key partners in the EPSRC Centre of Doctoral Training in Embedded Intelligence (EP/L014998/1), the EPSRC sponsored Centre for Robotics, and have shaped the development of the UK’s national Robotics innovation strategy for the UK Minister for Universities and Science.
- Electro-mechanical condition monitoring – Dr Sinisa Durovic, University of Manchester researches the fault analysis and condition monitoring of electromagnetic and electromechanical systems such as wind turbines.
- Power electronics condition monitoring – Professor Li Ran and Prof Phil Mawby at Warwick University have been working on power conversion and reliability and condition monitoring of power electronics in industry and academia.
The research is undertaken with a consortium of leading international companies and will demonstrate its outputs at a demonstration in Salford Quays in 2019/20.
Offshore turbine maintenance is already a significant industry, with a potential for huge growth in the UK, Europe and world-wide. In addition to the 5000MW of offshore wind already installed, a further 12,000MW is in construction or has planning approval, with a further 5,000MW in the planning process. Newer-build installations are increasingly further offshore, with greater and more costly maintenance challenges. Ensuring that the UK remains at the forefront of this emerging industry, and maintaining a world-leading skill-set is vital for the UK, for which this could be another opportunity similar to North-Sea oil.
Operation and Maintenance (O&M) cost is a quarter of the total cost of an offshore installation, i.e. as much as £40billion for future UK offshore wind. Substantially reducing this cost, has a major part to play in transitioning the UK to a sustainable low-carbon economy and addressing key EPSRC roadmap challenges.