Abstract:  The integration of a large number of devices in the new power system has brought about the problem of chaotic and difficult to handle communication data between devices. This article adopts a multimodal graph convolutional network to fuse communication data of a new type of power system. Firstly， by classifying the data source devices， a node equation for communication 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.

Key words:  , power system communication； data fusion； multimodal features； graph convolution