Abstract: Multimodal data throughout the entire life cycle of substation project lead to information silo. The 3D modeling software of departments such as equipment suppliers, design institutes and construction units have not been unified. The problems of data format conversion and integration are obvious. Based on knowledge graph(KG) and retrieval-augmented generation (RAG), this study proposes an Enhanced grid information model(EGiM), which integrates multiple 3D data formats of substation project through the GraphRAG method. KG builds models of complex power grid relationships to obtain various connections among substation, transformers and distribution network. RAG improves the accuracy of relationship description by extracting relevant data from the knowledge base and combining it with the 3D model. This study designs semantic mapping rules adapted to power grid multimodal data, realizing standardized semantic alignment of heterogeneous formats, and constructs a dynamic weight retrieval mechanism based on vector and graph to accurately get implicit equipment associations. This method increases the data integration success rate to 98.2% and the cross-format call success rate to 95.6%, improves data processing efficiency, and provides core technical support for the efficiency improvement of substation engineering design collaboration and fault diagnosis.

Key words: substation project, interoperability, knowledge graph, large language model, agent