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A major, international €4 million research collaboration between 10 European partners is leading the development of seven novel offshore wind turbine blade technologies, which collectively could lower the levelised cost of energy (LCOE) of offshore wind by as much as 4.7%.
The Offshore Demonstration Blade (ODB) project is supporting the research, development and demonstration of wind turbine blade innovations, including aerodynamic and structural enhancements, blade monitoring systems and blade erosion protection solutions. These products will be developed and retrofitted to the Offshore Renewable Energy (ORE) Catapult’s 7MW Levenmouth Demonstration Turbine in Scotland for demonstration purposes. The innovations will then be ready for deployment on existing or new offshore turbines.
The two-year Demowind-funded project will be coordinated by the UK’s ORE Catapult Development Services Ltd (ODSL), and involve leading organisations in wind turbine innovation including CENER, Bladena, TNO, Aerox, Siemens Gamesa Renewable Energy, Total Wind, Dansk IngeniørService A/S (DIS), the Technical University of Denmark (DTU) and the Cardenal Herrera University (CEU) in Spain.
Operations and maintenance costs represent almost a quarter of the total LCOE of an offshore wind turbine, with rotor operations and maintenance, specifically blade erosion and blade structural integrity, representing a large share of these costs. Therefore, improving the performance and operational lifetime of turbine blades will have a direct impact in lowering LCOE.
In the ODB project TNO will perform failure monitoring of the blade stiffeners with application of advanced fibre optic sensors, based on fiber bragg gratings (FBG). The solution will be a very robust and durable sensor system which uses state of the art FBG technology. Additionally, TNO will demonstrate an innovative and patented approach to detect leading edge erosion by incorporation of humidity sensors under the top coating on the leading edge of the blade. The data processing in combination with probabilistic modelling will produce input for a condition based maintenance tool. The Dutch contribution to the project is part of the ‘TKI Wind op Zee’ programme, part of ‘Topsector Energy’.
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