Automated alarm method for abnormal data in power grid reports based on Paxos algorithm

With the increasing scale and complexity of the power system, timely monitoring and accurate identification of abnormal data in power grid reports are crucial for ensuring the safe operation of the power grid. This paper proposes an automated alarm method for abnormal data in power grid reports based on the Paxos algorithm. Automatically collect power grid report data using RPA technology, and then use the isolated forest algorithm of sub forest progressive update incremental learning to detect anomalies in the collected data. Based on the anomaly detection results, the Paxos algorithm is used to trigger the automated alarm system and promptly notify the operation and maintenance personnel. The experimental results show that this method can accurately detect abnormal situations in the power grid and improve the comprehensiveness of alarms, which is beneficial for improving the security of the power grid.