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Safety Operation of Substation Intelligent Simulation System Based on Improved Genetic Algorithm.

Authors :
Lu, Jiashuo
Zhou, Yongqiang
Liu, Shourui
Niu, Zhimin
Source :
Procedia Computer Science; 2023, Vol. 228, p701-708, 8p
Publication Year :
2023

Abstract

With the widespread use of substation intelligent simulation systems, existing substation intelligent simulation systems have problems such as platform redundancy, system dispersion, and information sharing, which can lead to the insecurity of substation intelligent simulation systems. Therefore, this paper proposes a security operation analysis of substation intelligent simulation system based on improved genetic algorithms, aiming to improve the security of substation intelligent simulation system by using improved genetic algorithms. This paper experimentally tests that the number of vulnerabilities in a substation intelligent simulation system using improved genetic algorithms is between 0 and 20 within a month, while the number of vulnerabilities in a traditional substation intelligent simulation system is between 30 and 50, indicating that improved genetic algorithms do have the effect of improving the safety coefficient of the substation intelligent simulation system. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
228
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
173854108
Full Text :
https://doi.org/10.1016/j.procs.2023.11.081