Unified Classification and Naming of Equipment Based on Substation Topological Graph Model

This paper proposed a topological intelligent device unified classification and naming method based on a graph database for substation equipment management. Initially, by collecting topological connection data, the paper utilized graph database technology to parse the topological connection data and establish a graphical model of substation equipment. Subsequently, device feature sets were extracted from topological analysis, and a hierarchical clustering algorithm was employed to group and analyze devices, revealing implicit commonalities and differences. Based on clustering results, an intelligent classification algorithm identified keywords or patterns from device names, further classifying devices to establish definitions and attributions for each device type. Additionally, the proposed method used a graph database to store complex topological connections between devices. Drawing on graph computing theory, it enabled rapid analysis of topological features, facilitating precise assessments of the importance of device nodes. Finally, corresponding naming rules were formulated based on the intelligent classification of device groups and attributions, significantly enhancing the refinement and intelligence of monitoring, control, and maintenance of equipment within the substation. This approach promoted the digitization transformation of power systems.