Integrated condition-based maintenance modelling and optimisation for offshore wind farms

Dao, Cuong D.; Kazemtabrizi, Behzad; Crabtree, Christopher J.; Tavner, Peter J.

Abstract

Maintenance is essential in keeping wind energy assets operating efficiently. With the development of advanced condition monitoring, diagnostics and prognostics, condition‐based maintenance has attracted much attention in the offshore wind industry in recent years. This paper models various maintenance activities and their impacts on the degradation and performance of offshore wind turbine components. An integrated maintenance strategy of corrective maintenance, imperfect time‐based preventive maintenance and condition‐based maintenance is proposed and compared with other traditional maintenance strategies. A maintenance simulation programme is developed to simulate the degradation and maintenance of offshore wind turbines and estimate their performance. A case study on a 10‐MW offshore wind turbine (OWT) is presented to analyse the performance of different maintenance strategies. The simulation results reveal that the proposed strategy not only reduces the total maintenance cost but also improves the energy generation by reducing the total downtime and expected energy not supplied. Furthermore, the proposed maintenance strategy is optimised to find the best degradation threshold and balance the trade‐off between the use of condition‐based maintenance and other maintenance activities.

Citation

Dao, C. D., Kazemtabrizi, B., Crabtree, C. J., & Tavner, P. J. (2021). Integrated condition-based maintenance modelling and optimisation for offshore wind farms. Wind Energy, 24(11), 1180-1198. https://doi.org/10.1002/we.2625

• Journal Article Type: Article
• Acceptance Date: Jan 20, 2021
• Online Publication Date: Feb 4, 2021
• Publication Date: Oct 21, 2021
• Deposit Date: Feb 8, 2021
• Publicly Available Date: Feb 9, 2021
• Journal: Wind Energy
• Print ISSN: 1095-4244
• Electronic ISSN: 1099-1824
• Publisher: Wiley Open Access
• Peer Reviewed: Peer Reviewed
• Volume: 24
• Issue: 11
• Pages: 1180-1198
• DOI: https://doi.org/10.1002/we.2625
• Public URL: https://durham-repository.worktribe.com/output/1246866