Autonomous, robotic and AI enabled biofouling monitoring, cleaning and management system for offshore wind turbine monopile foundations (RobFMS)

Abstract

Offshore wind is proving very attractive for operators, especially due to the higher yields and less resistance from onshore homeowners and stakeholders. It is predicted that it could provide all the UK's electricity requirement, with minimal emission and visual impacts. However, there exist a major barrier to further exploitation due to the high levelised cost of electricity (LCOE) from offshore wind (£140/MWhr), which is 2-3 times higher than other key renewable sources (onshore wind and solar) and nuclear (a large non-renewable, but low emission source).

The high LCOE is caused by the severe environmental conditions, which results in high operational, reliability and maintenance (O&M) costs, with the seabed turbine foundations (largely monopiles) accounting for over 25% of all lifecycle O&M costs, often caused by marine biofouling.

Current methods of fouling prevention (dangerous: diver-deployed cleaning tools such as brushes and power jets) or ROVs (high annual costs ~ £30k/MW) are proving very costly and ineffective -- creating the need for an innovative solution to tackle this problem.

The project will develop a fouling management system consisting of a mobile survey and cleaning robot that will eliminate the need for divers and ROVs. The robot will be placed on the turbine structure at sea level and will journey down below sea level to the work place. The robot will travel autonomously over the entire subsea monopile surface, imaging the fouling in real time. It will simultaneously activate its cleaning function at every fouled location and remove the fouling with an innovative guided power ultrasound technique. On returning to the sea surface the robot would simply be transported to the next turbine scheduled for treatment, and the cycle repeated. Overall O&M costs will be reduced by at least 50% compared with present diver/ROV techniques. This would mean a £7/MW (5%) reduction in LCOE.

Lead Participant

Project Cost

Grant Offer

INNOVATIVE TECHNOLOGY AND SCIENCE LIMITED £716,103 £ 479,802
 

Participant

BRUNEL UNIVERSITY LONDON £241,884 £ 241,884
THE EUROPEAN MARINE ENERGY CENTRE LIMITED £40,310 £ 40,310

Publications

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