船舶电力网络脆弱性分析过程中，主要以单点位的电力变化状态实现评估，映射范围与目标较为单一，导致评估结果可靠性下降。为此提出对基于模糊熵的船舶电力网络脆弱性评估方法分析与设计。明确电力网络的覆盖区间，关联区间内的电力变动节点，实现深度挖掘处理。融合模糊熵原理输出挖掘目标的模糊熵值，以其作为约束条件，设计脆弱性评估矩阵，将多周期的评估目标导入矩阵之中，利用TOPSIS算法计算出相对临近度，以临近度划分矩阵内的评估结果，扩展综合映射范围。采用散度比对的方式，以基础评估结果为驱动，输出持续更新评估结果，完成验证研究。实验结果表明，所提出方法得到的连通性损失结果由98.5%下降到37.2%，下降幅度较大，说明电力网络的分裂程度较低，评估精度明显提升，反映了该方法的优越性及可靠性。
In the process of vulnerability analysis of ship power networks, the assessment is mainly carried out based on the power change status at a single point. The mapping scope and target are relatively single, resulting in a decline in the reliability of the assessment results. For this purpose, an analysis and design of the vulnerability assessment method for ship power networks based on fuzzy entropy are proposed. Clarify the coverage range of the power network, associate the power variation nodes within the range, and achieve in-depth mining and processing. The fuzzy entropy value of the mining target is output by integrating the principle of fuzzy entropy, and it is used as a constraint condition to design a vulnerability assessment matrix. The assessment targets of multiple periods are imported into the matrix, and the relative proximity degree is calculated by using the TOPSIS algorithm. The assessment results within the matrix are divided by the proximity degree to expand the comprehensive mapping range. By using the divergence comparison method and driven by the basic assessment results, the continuously updated assessment results are output to complete the verification research. The experimental results show that the proposed method reduces the connectivity loss from 98.5% to 37.2%, with a significant decrease. This indicates that the degree of fragmentation in the power network is relatively low and the evaluation accuracy has been significantly improved, reflecting the superiority and reliability of this method.
2026,48(3): 186-190 收稿日期：2025-7-30
DOI：10.3404/j.issn.1672-7649.2026.03.029
分类号：U665.12；TM711
基金项目：国家自然科学基金资助项目（62076152）
作者简介：张宇耀(1994-),男,硕士研究生,研究方向为电力电子与电力传动
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