Research on security situation awareness method of power network Monitoring system based on data mining. Issue 1 (1st October 2022)

• Record Type: Journal Article
• Authors: Chen, Haiguang; Hu, Zhaohui; Chen, Shanfeng; Yang, Yiyue; Fan, Suchun
• Is Part Of: Journal of physics. Volume 2351:Issue 1(2022)
• Publication Date: 2022-10-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2351/1/012043
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract : In the traditional security situation awareness methods of power network monitoring systems, there are deviations in the analysis of different sample data sets, which affect the security situation threat value perception results of power network monitoring systems. Therefore, this paper designs a security situation awareness method for a power network monitoring system based on data mining. The identification structure of security situation elements is determined, the self-encoder is used for mapping, the security situation elements of the power network monitoring system are extracted according to the obtained parameter samples, and the security situation awareness model of the power network monitoring system is established. The RBF neural network is used for data mining of the monitoring system, and the design of the security situation awareness method of the power network monitoring system based on data mining is completed. The experimental results show that the recognition accuracy of the design method for samples with different threat levels is more than 90%. Compared with the traditional methods, the security situation awareness results obtained by the design method are closer to the expected output threat value.