电力系统自动化2025，Vol.49Issue(7)：198-207,10.DOI:10.7500/AEPS20240412005
基于时序二维变换和多尺度Transformer的电能质量扰动分类方法
Power Quality Disturbance Classification Method Based on Time-series Two-dimensional Transformation and Multi-scale Transformer
摘要
Abstract
With the increasing penetration of renewable energy,the power quality disturbance(PQD)problem faced by the power grid has become more complicated.The traditional classification method based on one-dimensional PQD signals has difficulty in extracting and identifying periodic and trend disturbances at the same time.To address this problem,this paper proposes a PQD classification method based on time-series two-dimensional transformation and multi-scale Transformer.First,the time-series two-dimensional transformation is used to convert the one-dimensional PQD time series into a set of two-dimensional tensors based on multiple periods,to deeply mine the characteristic information contained in the PQD signals in the two-dimensional space.Then,the multi-scale feature map of the PQD signal is extracted through the multi-scale Transformer encoder module.And the multi-scale Transformer decoder module is used to splice and fuse the multi-scale feature maps,for effectively merging the feature maps extracted on different scales.Finally,the PQD classification task is accomplished through a fully connected layer and a Softmax classifier.To verify the effectiveness of the proposed method,a dataset containing 24 kinds of PQD is established to test the model.The results indicate that the proposed method has a high classification accuracy and noise robustness for PQD signals.关键词
电能质量/扰动/分类/时序二维变换/多尺度Transformer/特征提取/特征融合Key words
power quality/disturbance/classification/time-series two-dimensional transformation/multi-scale Transformer/feature extraction/feature fusion引用本文复制引用
王守相,李慧强,赵倩宇,郭陆阳,王同勋,王洋..基于时序二维变换和多尺度Transformer的电能质量扰动分类方法[J].电力系统自动化,2025,49(7):198-207,10.基金项目
国家重点研发计划资助项目(2023YFB2407500). This work is supported by National Key R&D Program of China(No.2023YFB2407500). （2023YFB2407500）
