基于多模态图卷积网络的新型电力系统通信数据融合方法  

A Novel Communication Data Fusion Method for Power Systems Based on Multimodal Graph Convolutional Networks

作　　者：李昂 杜猛俊 钱锦 童俊 杨涛 陈国涛 靳文星 LI Ang;DU Mengjun;QIAN Jin;TONG Jun;YANG Tao;CHEN Guotao;JIN Wenxing(State Grid Zhejiang Electric Power Co.,Ltd.,Hangzhou Power Supply Company,Hangzhou 310000,China;National Key Laboratory of Electromagnetic Energy,Naval University of Engineering,Wuhan 430033,China)

机构地区：[1]国网浙江省电力有限公司杭州供电公司,浙江杭州310000 [2]海军工程大学电磁能技术全国重点实验室,湖北武汉430033

出　　处：《计算机与现代化》2025年第2期64-69,共6页Computer and Modernization

基　　金：国家自然科学基金青年基金资助项目(52007196)。

摘　　要：新型电力系统大量设备的接入,带来了设备间通信数据杂乱、难以处理的难题。本文采用多模态图卷积网络来对新型电力系统通信数据进行融合。首先,通过对数据来源设备进行分类,构建通信数据流的节点方程;其次,根据数据传输的过程,使用多模态方法,构建全链接的数据边;最后,采用图卷积的方法对所得通信数据流进行卷积与数据融合,将数据传输过程,简化为数据向量,完成特征级数据融合的过程,并指导决策。通过对浙江电网通信数据集的仿真测试,验证基于多模态图卷积网络的新型电力系统通信数据融合方法,具备良好的应用效果。The integration of a large number of devices in the new power system has brought about the problem of chaotic and dif-ficult to handle communication data between devices.This article adopts a multimodal graph convolutional network to fuse com-munication data of a new type of power system.Firstly,by classifying the data source devices,a node equation for communica-tion data flow is constructed.Secondly,based on the process of data transmission,multi-modal methods are used to construct fully linked data edges.Finally,the graph convolution method is used to convolution and fuse the obtained communication data stream,simplifying the data transmission process into data vectors,completing the feature level data fusion process,and guiding decision-making.Through simulation testing on the communication dataset of Zhejiang Power Grid,it is verified that the new power system communication data fusion method based on multimodal graph convolutional network has good application effects.

关 键 词：电力系统通信 数据融合 多模态特征 图卷积 

分 类 号：TM769[电气工程—电力系统及自动化]