Abstract:

To address the problems that current operation tickets lack effective anti-misoperation verification means and suffer from low intelligence level,a knowledge-graph construction method for intelligent anti-misoperation of substation switching operations is proposed.Firstly,using professional corpus data of power grid equipment,a deep learning model training method is adopted to construct a power grid equipment connection relationship graph,an error prevention regulation graph,and a historical operation ticket graph,and automatically fuse them to form an intelligent error prevention knowledge graph.Then,experiments are designed to verify the effectiveness of the error prevention model,with an F₁ value of 80% and an accuracy rate of 95%.Finally,the intelligent anti-misoperation knowledge graph is managed with high-level visualization by adopting the Neo4j graph database,and the corresponding whole-process application workflow is provided,which effectively improves operators’ emergency-handling capabilities when encountering switching-operation faults.

Key words: intelligent anti-misoperation, entity recognition, knowledge graph, auxiliary verification