电力系统保护与控制2026，Vol.54Issue(10)：127-138,12.DOI:10.19783/j.cnki.pspc.251301
基于动态门控数据融合的GCN-Transformer配电网故障区段定位方法
Fault section location method for distribution networks based on dynamic gated data fusion and GCN-Transformer
摘要
Abstract
With the rapid development of smart grids,effectively utilizing multi-source data obtained from different measurement devices to meet the fault location requirements under different fault scenarios is of great significance for improving the power supply reliability and operational safety of distribution networks with distributed generation.To this end,a fault section location method for distribution networks based on dynamic gated data fusion and a combination of graph convolution network(GCN)and Transformer is proposed.First,the synchrophasor data and synchronized waveform data are fused through a dynamic gated data fusion method based on mask perception.Then,a GCN-Transformer model is constructed to extract and fuse fault features,and a focal supervised contrastive hybrid loss function is introduced to optimize the model.Finally,the fault section location is achieved through a fully connected classification layer.Simulation results show that the proposed method exhibits strong fault location performance under different fault scenarios and sample imbalance conditions.关键词
同步相量数据/同步波形数据/数据融合/GCN-Transformer/故障区段定位Key words
synchrophasor data/synchronized waveform data/data fusion/GCN-Transformer/fault section location引用本文复制引用
杨楠,候少波,邢超,王灿,关钦月,叶学程,李斯吾,黄悦华..基于动态门控数据融合的GCN-Transformer配电网故障区段定位方法[J].电力系统保护与控制,2026,54(10):127-138,12.基金项目
This work is supported by the National Natural Science Foundation of China(No.62233006). 国家自然科学基金项目资助(62233006) （No.62233006）
