田晓, 刘志全. 基于复杂网络理论的船舶电网脆性源辨识方法[J]. 中国舰船研究, 2024, 19(3): 1–12. doi: 10.19693/j.issn.1673-3185.03350
引用本文: 田晓, 刘志全. 基于复杂网络理论的船舶电网脆性源辨识方法[J]. 中国舰船研究, 2024, 19(3): 1–12. doi: 10.19693/j.issn.1673-3185.03350
TIAN X, LIU Z Q. Brittle source identification method for ship power grid based on complex network[J]. Chinese Journal of Ship Research, 2024, 19(3): 1–12 (in Chinese). doi: 10.19693/j.issn.1673-3185.03350
Citation: TIAN X, LIU Z Q. Brittle source identification method for ship power grid based on complex network[J]. Chinese Journal of Ship Research, 2024, 19(3): 1–12 (in Chinese). doi: 10.19693/j.issn.1673-3185.03350

基于复杂网络理论的船舶电网脆性源辨识方法

Brittle source identification method for ship power grid based on complex network

  • 摘要:
    目的 针对船舶电网关键元件辨识方法的考虑角度单一,未计及节点的局部和全局特征、对节点承载负荷的重要度考虑不足等问题,提出一种基于复杂网络理论的博弈组合赋权脆性源辨识方法。
    方法 船舶电力系统发生中断和连锁崩溃的内在机理是其本身具有脆性。首先,从脆性角度出发,基于复杂网络理论建立节点度、特征向量中心性、节点凝聚度、接近中心性、脆性电气介数等5项指标;然后,提出博弈组合赋权法,以纳什均衡为协调目标,确定直觉模糊层次分析法(IFAHP)和熵权法(EWM)的最优组合权重,并综合赋值5项指标以得到综合脆性指标;最后,利用典型四电站环形船舶电网,验证该脆性源辨识方法的有效性和可行性。
    结果 根据不同脆性指标的网络效能,得到了4个等级的脆性源。对比结果表明,所提方法可以更全面合理地辨识脆性源。
    结论 研究成果可为船舶电网连锁故障的预防控制提供有效指导。

     

    Abstract:
    Objective Existing brittle source identification methods have such problems as their single-perspective approach, disregard for the local and global characteristics of nodes, and insufficient consideration of the loads carried by nodes.
    Methods The method proposed herein identifies the inherent brittleness of the ship power system as the root cause of interruption and chain collapse. To establish a brittleness index, the method first considers node degree, eigenvector centrality, node cohesiveness, closeness centrality and brittle electrical betweenness from a brittleness perspective based on complex network theory. The combinatorial intuitionistic fuzzy analytic hierarchy process (IFAHP)and entropy weight method (EWM) with the Nash equilibrium as the coordination objective. The five indexes are then combined through comprehensive assignment to obtain a comprehensive brittleness index. Finally, the proposed brittle source identification method is validated using a typical four-station annular ship grid.
    Results The method identifies four levels of brittle sources based on the network efficiency of different brittleness indexes, and the results demonstrate its ability to identify brittle sources more comprehensively and reasonably.
    Conclusion The results of this study can provide effective guidance for the prevention and control of inter-locking faults in ship power networks.

     

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