This study investigated the group maintenance (GM) strategy based on condition-based maintenance (CBM) of a parallel wind farm with multiple identical wind turbines. In terms of this strategy, the state of deterioration of the system is determined by periodic inspection, with the GM activities at each inspection point performed according to the number of failed turbines, which are determined by the corresponding state of deterioration of the system. Under this strategy, the probabilities that influence GM are derived by the stationary probability density function, which is based on the stationary law of the state of the wind farm system. Furthermore, employing numerical experiments and a case study, we verified the correctness and effectiveness of the stationary probability density function under different deterioration-related parameters and obtained the optimal number of failed turbines when GM is performed, as well as the optimal interval between two consecutive inspection points. Finally, through comparison of strategies and sensitivity analysis, we demonstrated the economic advantages and the effectiveness of the proposed strategy. For a parallel system with high maintenance set-up cost owing to severe environmental conditions, our proposed GM policy based on CBM outperformed other existing strategies in terms of cost benefit and ease of implementation.

中文翻译：

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基于状态检修的风电场群检修最优决策

本研究调查了具有多个相同风力涡轮机的并联风电场的基于状态维护 (CBM) 的组维护 (GM) 策略。在该策略中，系统的劣化状态通过定期检查来确定，每个检查点的GM活动根据故障涡轮机的数量进行，这由相应的系统劣化状态决定。在该策略下，影响GM的概率由平稳概率密度函数导出，该函数基于风电场系统状态的平稳规律。此外，采用数值实验和案例研究，我们验证了不同劣化相关参数下平稳概率密度函数的正确性和有效性，得到了进行GM时的最佳失效涡轮机数，以及两个连续检查点之间的最佳间隔。最后，通过策略比较和敏感性分析，我们证明了所提出策略的经济优势和有效性。对于由于恶劣的环境条件而具有高维护设置成本的并行系统，我们提出的基于 CBM 的 GM 策略在成本效益和易于实施方面优于其他现有策略。通过策略比较和敏感性分析，我们证明了所提出策略的经济优势和有效性。对于由于恶劣的环境条件而具有高维护设置成本的并行系统，我们提出的基于 CBM 的 GM 策略在成本效益和易于实施方面优于其他现有策略。通过策略比较和敏感性分析，我们证明了所提出策略的经济优势和有效性。对于由于恶劣的环境条件而具有高维护设置成本的并行系统，我们提出的基于 CBM 的 GM 策略在成本效益和易于实施方面优于其他现有策略。