基于图注意力网络的配电网故障行波定位方法
作者:
作者单位:

(1.长沙理工大学电气与信息工程学院,湖南 长沙 410114; 2.中国电力科学研究院有限公司,北京 100192)

通讯作者:

邓 丰(1983—),女,博士,教授,主要从事电力系统继电保护等研究;E?mail:df_csust@126.com

中图分类号:

TM721

基金项目:

国家自然科学基金(52377073);2023年国家级大学生创新训练计划(S202310536025)


A fault traveling wave localization method for distribution networks based on graph attention networks
Author:
Affiliation:

(1.School of Electrical & Information Engineering, Changsha University of Science & Technology, Changsha 410114, China;2.China Electric Power Research Institute, Beijing 100192, China)

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    摘要:

    拓扑变化会改变故障信号特征,传统配电网行波故障定位方法基于固定拓扑设计,通过时域或频域等单一特征信息判断故障位置,拓扑变化条件下定位准确率低,为此,提出基于图注意力网络的故障定位方法。首先,定量分析故障行波在时域与频域中的分布特性,发现单一时域或频域信息难以有效区分不同故障位置,故提出基于小波变换的故障行波全景信息表现形式;随后,将测点和架空线作为图的节点与边,以行波全景信息为节点特征,构建图数据,建立基于图注意力网络的故障定位方法,通过挖掘节点特征、网络拓扑结构信息与故障位置之间的关联关系,实现配电网故障定位,提升方法对拓扑变化的适应能力。仿真结果表明:所提方法定位准确率高达98.8%,不受过渡电阻、噪声等因素影响,对拓扑变化具有较强的适应能力。

    Abstract:

    Topology change will change the fault signal characteristics. The traditional fault traveling wave localization method for distribution networks is based on the fixed topology design. Through the single feature information of the time or frequency domain, the fault is located, and the localization accuracy is low under the topology change conditions. For this reason, a fault localization method based on a graph attention network is proposed. First, the distribution characteristics of fault traveling wave in time and frequency domains are quantitatively analyzed, and it is found that it is difficult to effectively distinguish different fault locations with a single time or frequency domain information, so the panoramic information representation of fault traveling wave based on wavelet transform is proposed. Then, the measurement points and overhead lines are taken as the nodes and edges of the graph. The panoramic information of traveling waves is used as the node features to construct the graph data, so as to establish the fault localization method based on the graph attention network and locate the fault of the distribution network by mining the correlation between the node features, the information of the network topology, and the fault location, thus enhancing the adaptability of the method to topological changes. Simulation results show that the method has a high localization accuracy of 98.8%. It is not affected by transition resistance, noise, and other factors and has a strong adaptive ability to topology changes.

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舒佳蕾,陈依林,曹 虹,等.基于图注意力网络的配电网故障行波定位方法[J].电力科学与技术学报,2025,40(1):85-91.
SHU Jialei, CHEN Yilin, CAO Hong, et al. A fault traveling wave localization method for distribution networks based on graph attention networks[J]. Journal of Electric Power Science and Technology,2025,40(1):85-91.

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  • 在线发布日期: 2025-03-18
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