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

Dao, Cuong D. and Kazemtabrizi, Behzad and Crabtree, Christopher J. and Tavner, Peter J. (2021) 'Integrated condition-based maintenance modelling and optimisation for offshore wind farms.', Wind energy., 24 (11). pp. 1180-1198.


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.

Item Type:Article
Full text:Publisher-imposed embargo
(AM) Accepted Manuscript
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Available under License - Creative Commons Attribution 4.0.
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Publisher statement:© 2021 The Authors. Wind Energy published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Date accepted:20 January 2021
Date deposited:09 February 2021
Date of first online publication:04 February 2021
Date first made open access:09 February 2021

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