Operation and maintenance (OM) of offshore wind turbines contributes with a substantial part of the total levelized cost of energy (LCOE). The objective of this paper is to present how applications of risk and reliability based methods for planning of OM, can positively impact the cost of maintenance. The study focuses on maintenance of wind turbine blades, for which a fracture mechanics based degradation model is set up. Based on this model, and the uncertain input in terms of cracking on the blades at the start of the lifetime, an initial reliability estimate is made. During the operation period, inspections are performed at regular time intervals, and the results are then used to update the reliability estimates using Bayesian networks. Based on the updated estimate, decisions on repairs are taken, thus potentially minimizing the maintenance effort while maintaining a target reliability level. To showcase the potential cost reduction, a study is made using a discrete event simulator. Two different preventive approaches are used. The first is a traditional time/condition based strategy, where inspections are made with a fixed annual frequency and defects are repaired on detection. The second approach consists of risk based inspection planning, using the methodology described in the first part of the paper, and the cost and availability savings relative to the previous strategy are underlined. A detailed description on the advantages of disadvantages of the risk strategy is given in the end of the paper.
Florian, M., & Sørensen, J. D. (2017). Risk-based planning of operation and maintenance for offshore wind farms. In Energy Procedia (Vol. 137, pp. 261–272). Elsevier Ltd. https://doi.org/10.1016/j.egypro.2017.10.349