Power Grid Engineering Knowledge Graph and Physical Elements Alignment Algorithm Designs

Traditional feasibility evaluation of power grid engineering projects primarily focuses on either individual or overall evaluations. The existing approach overlooks the identification and assessment of cluster projects spanning the feasibility and implementation phases, resulting in resource wastage and schedule stagnation throughout the project management lifecycle. To address this issue, this study proposes a methodology based on knowledge graphs to align the physical elements of completed projects and those under feasibility study. This paper (i) defines the Power Grid Engineering Knowledge Graph from the perspective of physical elements (PGKG), (ii) extracts information on physical elements from feasibility study reports and constructs the initial topology of physical element nodes, and (iii) designs two physical element alignment algorithms for node - structure and node - line alignment. Finally, the two algorithms are tested on the constructed PGKG, and ablation experiments are conducted to verify their effectiveness and rationality. This paper offers a reliable method for constructing the power grid engineering knowledge graph and a physical element alignment method to tackle the problems of information deficiency and misalignment of spatio - temporal information in power grid engineering knowledge graphs.