中国电机工程学报2026，Vol.46Issue(5)：1914-1927,中插15,15.DOI:10.13334/j.0258-8013.pcsee.242297
基于差分编码嵌入的两阶段多通道电能质量扰动分类与时间定位网络
Two-stage Multi-channel Power Quality Disturbance Classification and Timing Estimation Network Based on Differential Encoding and Embedding
摘要
Abstract
With the large-scale utilization of renewable energy sources,power quality disturbances(PQDs)in power systems are becoming increasingly complex and diverse.Traditional methods struggle to simultaneously achieve type identification of multiple composite disturbances and precise timing estimation of these disturbances.This paper proposes a two-stage multi-channel network based on differential encoding and embedding to address this issue.In the first stage,a differential multi-head self-attention(DMHSA)mechanism is proposed to detect signal mutation points,allowing for the encoding of disturbance differential features.In the second stage,the original signal is combined with the encoded differential signal to create multi-channel features,and an improved temporal convolutional network,TCN-SENet,is designed for channel feature extraction and feature learning to achieve point classification of PQDs.The PQDs detection model based on these two modules can achieve efficient and accurate disturbance identification and timing estimation.In simulation experiments,the proposed model outperforms others in classification accuracy for disturbance dataset at a 30 dB signal-to-noise ratio,with an average timing error of less than 1.3ms.In the hardware experiment,the proposed model shows the best generalization capability,significantly outperforming other models in disturbance identification accuracy and average timing error.关键词
电能质量扰动/点分类任务/时间卷积网络/多头自注意力机制/差分特征提取Key words
power quality disturbance/point classification task/temporal convolutional network/multi-head self-attention mechanism/differential feature extraction分类
信息技术与安全科学引用本文复制引用
金涛,陈煌滨,郑熙东,黄钦瑜,刘宇龙..基于差分编码嵌入的两阶段多通道电能质量扰动分类与时间定位网络[J].中国电机工程学报,2026,46(5):1914-1927,中插15,15.基金项目
国家自然科学基金项目(52377088).Project Supported by National Natural Science Foundation of China(52377088). （52377088）
