This paper studies an interesting logistical problem related to maintaining a set of selected turbines in offshore wind farms. A service operation vessel (SOV), used to support maintenance activities, also carries a safe transfer boat (STB), which is used to transport technicians, parts, and equipment to the turbines. The maintenance activities are optimised over a planning horizon by simultaneously coordinating the SOV and the STB. A mixed-integer linear programming model is designed, where the objective function is to minimise the total maintenance cost. As the proposed mathematical model is hard to solve with a commercial solver, a decomposition approach is developed. A two-stage stochastic programming model is also designed to tackle uncertain conditions, including the duration of maintenance and the STB’s travel time. The performance of the solution method is evaluated using the Thanet Offshore Wind Farm, in the southeast of the UK. The results of our experiments show that joint use of an SOV and an STB can yield a lower total maintenance cost than only using an SOV or crew travel vessels (CTVs) that are currently the common practice in maintaining offshore turbines.

本文研究了一个有趣的后勤问题，该问题与在海上风电场中维护一组选定的涡轮机有关。用于支持维护活动的服务操作船 (SOV) 还携带安全转运船 (STB)，用于将技术人员、零件和设备运送到涡轮机。通过同时协调 SOV 和 STB，维护活动在规划范围内得到优化。设计了一个混合整数线性规划模型，其目标函数是最小化总维护成本。由于所提出的数学模型难以用商业求解器求解，因此开发了一种分解方法。还设计了一个两阶段随机规划模型来解决不确定条件，包括维护持续时间和 STB 的行程时间。使用英国东南部的 Thanet Offshore Wind Farm 评估求解方法的性能。我们的实验结果表明，联合使用 SOV 和 STB 可以产生比仅使用目前维护海上涡轮机的常见做法的 SOV 或船员旅行船 (CTV) 更低的总维护成本。