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Offshore Wind Infrastructure Application Lab (OWI-Lab)

Info  Publications 
Parent institute: SIRRIS, more

The ‘Offshore Wind Infrastructure Application Lab’ (OWI-Lab) is a R&D initiative which aims to initiate and support innovation projects concerning offshore wind energy. The project itself aims to increase the reliability and efficiency of offshore wind farms by investing in testing and monitoring equipment that can help the industry in reaching these goals.

Onshore wind energy becomes a mature technology, offshore wind energy is rather new and technology has to be adapted to this harsh environment. Next to that the offshore wind kwh-cost must go down to coming years in order to reach grid parity and become competitive to onshore technologies. To reach this goal we must invest in R&D and stimulate incentives in this growing industry.

But Belgian and other European companies still miss access to test infrastructure and relevant datasets to support and accelerate their innovation process in order make their wind turbine components reliable and efficient. OWI-Lab wil be one of the offshore wind energy supporters by investing in specific test and monitoring infra-structure and initiate innovation projects together with industry and academic players.

This initiative is a collaboration between Hansen Transmissions, 3E, GeoSea (DEME), CG Power Belgium, VUB, Agoria Renewable Energy Club, Generaties and Sirris. The OWI-Lab will be implemented and coordinated by Sirris, the collective centre of the Belgian technological industry.

Publications (6)  Top 
    ( 4 peer reviewed ) split up filter
  • Peer reviewed article Weijtjens, W.; Verbelen, T.; Capello, E.; Devriendt, C. (2017). Vibration based structural health monitoring of the substructures of five offshore wind turbines. Procedia Engineering 199: 2294-2299., more
  • Peer reviewed article Janssens, O.; Noppe, N.; Devriendt, C.; Van de Walle, R.; Van Hoecke, S. (2016). Data-driven multivariate power curve modeling of offshore wind turbines. Engineering Applications of Artificial Intelligence 55: 331-338., more
  • Peer reviewed article Devriendt, C.; Weijtjens, W.; El-Kafafy, M.; De Sitter, G. (2014). Monitoring resonant frequencies and damping values of an offshore wind turbine in parked conditions. IET Renew. Power Gener. 8(4): 433-441., more
  • Peer reviewed article Devriendt, C.; Jordaens, P.J.; De Sitter, G.; Guillaume, P. (2013). Damping estimation of an offshore wind turbine on a monopile foundation. IET Renew. Power Gener. 7(4): 401-412., more
  • Helsen, J.; De Sitter, G.; Jordaens, P.J. (2016). Long-term monitoring of wind farms using big data approach, in: IEEE BigDataService 2016. Second IEEE international conference on big data computing service and applications, Oxford, United Kingdom. pp. 265-268., more
  • Weijtjens, W.; De Sitter, G.; Devriendt, C.; Guillaume, P. (2015). Automated operational modal analysis on an offshore wind turbine: challenges, results and opportunities, in: Aenlle, M.L. et al. (Ed.) IOMAC'15. 6th International Operational Modal Analysis Conference. pp. 713-730, more

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