Generation method of power grid fault disposal plan based on knowledge graph reasoning

Traditional rule-based systems struggle with complex power grid faults due to limited flexibility and dynamic response. This study proposes an automated fault disposal approach using a power grid fault knowledge graph combined with reasoning algorithms. The system models equipment, fault types, and disposal steps as a graph, where nodes represent entities and edges denote fault relations. Real-time monitoring data feeds into the graph, enabling automated reasoning to identify fault causes, affected areas, and disposal options. Based on this, the system dynamically generates accurate disposal plans with high automation, reducing manual intervention, and supports over 80% of fault types with a maximum response time of 3.5 s, significantly improving diagnosis accuracy and emergency response efficiency. This method offers a robust technical path for intelligent grid operations.