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Blade-based maintenance policy of offshore wind turbine with the presence of covariate under random shock
... Besnard and Bertling [10] proposed a mathematical approach to optimize the inspection interval and condition monitoring strategies for a wind turbine blade whose deterioration is classified according to severity of the damages. Zhu et al. [11] used the Paris–Erdogan law to model the crack growth of wind turbine blades considering the intrinsic randomness of the fatigue crack propagation, random shock, random load, and dynamic environment . The authors also proposed two reactive maintenance policies to take the advantage of monitoring signals as well as periodic maintenance. ...
Many offshore wind farms are planned to be built in remote sea locations due to high wind resources. However, the difficulties in accessing and maintaining wind turbines lead to increased operation and maintenance (O&M) costs and subsequently, increased cost of energy (COE). In order to share the maintenance set-up costs and reduce the power production losses, the group maintenance policies are widely used in offshore wind energy industry. In this paper, we investigate an optimal group maintenance policy for a multi-unit wind turbine system located in cold, icy or remote offshore areas. Each individual unit is exposed to a gradual degradation phenomenon that takes place in different forms of wear, corrosion, erosion, fatigue and crack generation. The whole system undergoes an unplanned maintenance action when the degradation level of one of units reaches its critical size; otherwise a planned group maintenance task is conducted at the operational age T (>0). We propose an optimization model to determine the optimal time T* such that the average long-run maintenance cost per unit time is minimized. Finally, the proposed model is applied to a three-bladed rotor system and the results are compared with the individual maintenance of blades.
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