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

Wei Xing; Tong Wu; Xiaoyu Wang

doi:10.1117/12.3023528

1 April 2024 Automated alarm method for abnormal data in power grid reports based on Paxos algorithm

Wei Xing, Tong Wu, Xiaoyu Wang

Proceedings Volume 12987, Third International Conference on Computer Technology, Information Engineering, and Electron Materials (CTIEEM 2023); 1298705 (2024) https://doi.org/10.1117/12.3023528
Event: Third International Conference on Computer Technology, Information Engineering, and Electron Materials (CTIEEM 2023), 2023, Zhengzhou, China

Abstract

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.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wei Xing, Tong Wu, and Xiaoyu Wang "Automated alarm method for abnormal data in power grid reports based on Paxos algorithm", Proc. SPIE 12987, Third International Conference on Computer Technology, Information Engineering, and Electron Materials (CTIEEM 2023), 1298705 (1 April 2024); https://doi.org/10.1117/12.3023528

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KEYWORDS

Power grids

Sensors

Data modeling

Data acquisition

Reliability

Automation

Education and training

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