本文针对船舶中压直流电力系统潮流计算精度不足与故障重构效率低的问题，融合全纯嵌入法（HEM）和改进布谷鸟搜索算法（GBNN-CS），提出交直流混合潮流计算模型与故障重构策略；通过建立环状网络拓扑和换流器协同控制机制，构建多目标优化框架。仿真结果表明，HEM法减少迭代次数40%、提升计算效率35%，电压误差低于0.001%；GBNN-CS算法在母线短路工况下实现98.2%负载恢复率，重构时间缩短至3.2 s；换流器控制策略成功抑制电压越限，关键负荷电压波动严格控制在±5%额定范围，验证了该方法在提升船舶电力系统稳态精度与故障恢复能力方面的工程有效性，已应用于18万吨级LNG船设计。
Aiming at the problems of insufficient power flow calculation accuracy and low fault reconstruction efficiency in the medium-voltage DC power system of ships, by integrating the holomorphic embedding method (HEM) and the improved cuckoo search algorithm (GBNN-CS), an AC/DC hybrid power flow calculation model and fault reconstruction strategy are proposed. A multi-objective optimization framework is constructed by establishing a ring network topology and a converter collaborative control mechanism. The simulation results show that the HEM method reduces the number of iterations by 40%, improves the computing efficiency by 35%, and the voltage error is less than 0.001%. The GBNN-CS algorithm achieves a load recovery rate of 98.2% under the busbar short-circuit condition, and the reconstruction time is shortened to 3.2 s. The converter control strategy successfully suppressed voltage over-limit, and the voltage fluctuation of key loads was strictly controlled within ±5% of the rated range, verifying the engineering effectiveness of this method in improving the steady-state accuracy and fault recovery capability of the ship's power system. It has been applied to the design of 180000 t LNG carriers.
2026,48(7): 69-76 收稿日期：2025-7-28
DOI：10.3404/j.issn.1672-7649.2026.07.012
分类号：U664.81
基金项目：国家自然科学基金资助项目（61673081，51979020）；中国船级社总部重点项目（CCS-HQ-BJH2541）
作者简介：杨宝明(1995-),男,硕士,工程师,研究方向为船舶动力装置及电气系统
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