A consortium of scientists has received £4 million to develop a robotics solution, including remote inspection, for maintenance of subsea power cables on offshore wind farms. The grant will be to develop a human-robot hybrid solution for the operation of offshore wind farms. Heriot-Watt University will build the inspection system.
The remote inspection system will monitor the condition of subsea power cables on offshore windfarms. (Credit: Heriot-Watt University)
The Holistic Operation and Maintenance for Energy from Offshore Wind Farms (HOME-Offshore) consortium consisting of experts from the universities of Manchester, Warwick, Cranfield, Durham and Heriot-Watt.
Dr David Flynn, director of the Smart Systems Group at Heriot-Watt University, explained that currently, 70 per cent of subsea cable failure modes cannot be monitored in-situ, which is inhibiting their health being monitored accurately. ‘By integrating technologies, such as autonomous underwater vehicles and advanced sonar technology, we will gain a new insight into the condition of these subsea assets,’ he explained. The new technology is intended to identify any problems with subsea cables early and extend their lifespan as a result.
According to Flynn, The UK government intends to increase the present 5GW of power generated by offshore wind farms to 40GW by 2050. ‘The costs of achieving these targets has, until now, focused on the capital outlay for wind turbines, but budgets have largely ignored the operation and maintenance of wind farm assets including subsea cabling,’ he said.
‘As the UK works towards ambitious decarbonisation targets, we expect this industry to be worth more than £2 billion per year by 2020.’ Flynn continued. ‘Our hybrid, human-robotics, technology will seek to protect those most vulnerable to increases in the cost of energy by reducing the costs faced by both tax and bill payers.’
The £4 million research grant includes a £1 million industry contribution from companies such as Siemens Wind, GE Energy Solutions and Scottish Power Energy Networks and £3 million from the Engineering and Physical Sciences Research Council.