吴艳敏,安艳军,和萍,等.考虑故障与抢修协同优化的有源配电网多时段供电恢复[J].河南理工大学学报(自然科学版)，doi:10.16186/j.cnki.1673-9787.2025120093.

WU Y M,AN Y J,HE P,et al．Multi-period power restoration for distribution networks considering collaborative optimization of fault recovery and emergency［J］.Journal of Henan Polytechnic University( Natural Science) ，doi:10.16186/j.cnki.1673-9787.2025120093.

考虑故障与抢修协同优化的有源配电网多时段供电恢复(网络首发)

吴艳敏¹，安艳军¹，和萍²，郭瑞良¹，宋祺鹏³，朱向前¹

（1.郑州轻工业大学 建筑环境工程学院，河南 郑州 450000；2. 郑州轻工业大学 电气信息工程学院，河南 郑州 450000；3. 中国电力科学研究院有限公司，北京 100192）

摘要: 目的 极端天气事件的频发严重影响有源配电网的安全稳定运行，为了提高灾后配电网的供电恢复能力，建立高效的供电恢复策略具有重要价值。方法 针对极端天气事件引起的故障，提出了故障恢复与抢修协同优化的多时段恢复策略。首先，形成光储联合系统减小分布式光伏出力波动性，并考虑负荷不同时段的需求和重要等级得到各时段负荷恢复优先级系数，建立以失负荷成本、网损成本和开关动作成本为目标的故障恢复模型，提出孤岛划分与故障恢复性重构协同优化策略求解；其次，建立以失电负荷最小和抢修时间最短为目标的抢修模型，改进星鸦优化算法求解最优抢修元件，利用故障恢复模型与抢修模型滚动优化配电网结构，同时引入配电网韧性评估指标量化所提策略恢复效果。结果 应用改进IEEE33节点和交通网组成的耦合系统为算例进行仿真并对比分析，本文方法相比方案2负荷失供率降低了51.61%，负荷平均恢复时长缩短了53.33%，负荷恢复速率提高了一倍，相比方案1配电网的灾后性能恢复提升更多。结论 所提多时段故障恢复与抢修模型综合考虑了元件恢复对系统性能提升与抢修时间，改进星鸦优化算法高效求解最优抢修线路，并与故障恢复模型滚动优化配电网结构，有效提高了灾后配电网的性能。

关键词: 故障抢修；孤岛划分；故障恢复；韧性提升；供电恢复

doi:10.16186/j.cnki.1673-9787.2025120093

基金项目: 国家自然科学基金资助项目(52377125)

收稿日期：2025-12-27

修回日期：2026-06-02

网络首发日期：2026-09-21

Multi-period power restoration for distribution networks considering collaborative optimization of fault recovery and emergency

WU Yanmin¹, AN Yanjun¹, HE Ping², GUO Ruiliang¹, SONG Qipeng³, ZHU Xiangqian¹

(1.College of Building Environment Engineering, Zhengzhou University of Light Industry, Zhengzhou 450000, Henan, China；2. College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450000, Henan, China；3. China Electric Power Research Institute, Beijing 100192, Beijing, China)

Abstract: Objectives The frequent occurrence of extreme weather events had severely impacted the safe and stable operation of active distribution networks. To improve the fault recovery capability of the distribution network after a disaster, the establishment of efficient restoration strategies was of great value. Methods Aiming at faults caused by extreme weather events, a multi-period restoration strategy with collaborative optimization of fault recovery and emergency repair was proposed. First, a photovoltaic-storage combined system was formed to reduce the output volatility of distributed photovoltaics. By considering the load demand and importance levels in different periods, the load restoration priority coefficients for each period were obtained. A fault recovery model was established with objectives of load shedding cost, network loss cost, and switch operation cost, and a collaborative optimization strategy for island division and fault recovery reconfiguration was proposed for solution. Second, an emergency repair model was established with objectives of minimizing power-outage load and shortest repair time. The improved Nutcracker optimization algorithm was used to solve for optimal repair components. The fault recovery model and emergency repair model were employed to iteratively optimize the distribution network structure, while resilience evaluation indicators of the distribution network were introduced to quantify the restoration effect of the proposed strategy. Results A comparative analysis and test simulation were conducted using the coupled system composed of IEEE 33-node network and transportation network system. Compared with Scheme 2, the load loss rate was reduced by 51.61%, the average load recovery duration was shortened by 53.33%, and the load recovery rate was two-fold increased by the method proposed in this paper. Moreover, it brought about a more significant improvement in the post-disaster performance recovery of the distribution network than Scheme 1. Conclusions The proposed multi-period fault recovery and repair model comprehensively considered the improvement of system performance brought by component restoration and the required repair time. The improved Nutcracker optimization algorithm efficiently solved the optimal repair route, and performed rolling optimization of the distribution network structure in combination with the fault recovery model, which effectively enhanced the post-disaster performance of the distribution network.

Key words: fault repair; islanding division; fault recovery; resilience enhancement; power restoration