Construction Method of Equipment Knowledge Graph in Power Grid Monitoring Field Based on Multi-source Data Fusion

Abstract

With the rapid development of large-scale distributed power generation, energy storage, and dispatch monitoring in the power grid, the connections between the various business departments of the power grid are getting closer. There is an urgent need to integrate multiple types of equipment with a “grid diagram” topology correlation model. Therefore, the power industry introduces knowledge graphs to store associated massive amounts of data. However, currently, the research of knowledge graphs in the field of a power grid is still in its infancy. In order to solve the problem of single data and poor scalability of equipment knowledge graphs in the area of power grid monitoring, this paper proposes a method for constructing equipment knowledge graphs based on multi-source data fusion and expounds the process of integrating multi-source data into graphs. Finally, through the comparison of calculation examples, the results show that constructing equipment knowledge graphs in the power grid monitoring field based on multi-source data fusion enriches the original data, improves the graph coverage rate, and broadens the application scenarios of equipment knowledge graphs. Furthermore, it provides new ideas for the further development of knowledge graphs in the field of power grids.