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1.江苏大学电气信息工程学院,江苏省镇江市 212013
2.东南大学电气工程学院,江苏省南京市 210096
3.国网江苏省电力有限公司南京供电分公司,江苏省南京市 210019
4.国网智能电网研究院有限公司,北京市 102209
5.香港理工大学工程学院,香港 999077
张煜佳(1998—),女,硕士研究生,主要研究方向:基于图论的配电网故障溯源与恢复。E-mail:13961126415@163.com
袁野(1991—),男,通信作者,博士,副教授,博士生导师,主要研究方向:磁悬浮电机系统创新设计与先进控制。E-mail:1000050003@ujs.edu.cn
周苏洋(1987—),男,博士,副教授,博士生导师,主要研究方向:综合能源系统、人工智能、需求侧管理等。E-mail:suyang.zhou@seu.edu.cn
收稿:2024-01-12,
修回:2024-12-24,
网络出版:2025-04-23,
纸质出版:2025-07-10
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张煜佳,袁野,周苏洋等.基于动态图投影的大规模复杂配电网故障快速溯源方法[J].电力系统自动化,2025,49(13):177-186.
ZHANG Yujia,YUAN Ye,ZHOU Suyang,et al.Fast Fault Back-tracing Method for Large-scale Complex Distribution Networks Based on Dynamic Graph Projection[J].Automation of Electric Power Systems,2025,49(13):177-186.
张煜佳,袁野,周苏洋等.基于动态图投影的大规模复杂配电网故障快速溯源方法[J].电力系统自动化,2025,49(13):177-186. DOI: 10.7500/AEPS20240112003.
ZHANG Yujia,YUAN Ye,ZHOU Suyang,et al.Fast Fault Back-tracing Method for Large-scale Complex Distribution Networks Based on Dynamic Graph Projection[J].Automation of Electric Power Systems,2025,49(13):177-186. DOI: 10.7500/AEPS20240112003.
随着配电网规模的快速增长及分布式资源的高度渗透,配电网拓扑结构日益复杂,给配电网故障定位分析带来极大挑战。矩阵算法和智能优化算法应用于故障定位时需要根据变化的拓扑信息构造网络矩阵或建立寻优模型,极大增加了计算量和计算复杂度,数据处理和计算效率低下。文中首先构建了配电网拓扑的图数据模型,通过图投影技术从全景电网图中抽取适配故障溯源任务场景的优化子图;在此基础上,采用Yen最短路径搜索算法,查找电源至异常节点的潜在故障路径,通过遍历线路节点判断电流越限信息确定故障所在区段。所提方法解决了电网拓扑的精确表征和快速搜索问题,实现了面向大规模复杂配电网的故障源快速精准定位,在保证故障溯源准确性的基础上提升了故障搜索效率。
With the rapid expansion of distribution network scale and the high penetration of distributed resources
the increasing complexity of distribution network topology poses significant challenges to fault location analysis. Matrix-based algorithms and intelligent optimization algorithms require dynamic construction of network matrices or optimal models based on evolving topological information when applied to fault location
leading to excessive computational burden and complexity
as well as inefficient data processing and computation. This paper first constructs a graph data model for the distribution network topology. Through graph projection techniques
it extracts an optimal subgraph tailored to fault back-tracing task scenarios from the panoramic power grid graph. On this basis
the Yen shortest path search algorithm is employed to identify potential fault paths from the power source to abnormal nodes. By traversing line nodes and analyzing current limit violation information
the fault section is accurately identified. The proposed method addresses the challenges of precise topological representation and rapid searching in power grids
enabling fast and accurate fault location for large-scale complex distribution networks. While ensuring fault back-tracing accuracy
this method significantly enhances fault searching efficiency.
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