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Intelligent terminal security technology of power grid sensing layer based upon information entropy data mining

Authors :
Ren Shuai
Chen Defeng
Tao Yaodong
Xu Shuheng
Wang Gang
Yang Zhibin
Source :
Journal of Intelligent Systems, Vol 31, Iss 1, Pp 817-834 (2022)
Publication Year :
2022
Publisher :
De Gruyter, 2022.

Abstract

The power grid is an important connection between power sources and users, responsible for supplying and distributing electric energy to users. Modern power grids are widely distributed and large in scale, and their security faces new problems and challenges. Information entropy theory is an objective weighting method that compares the information order of each evaluation index to judge the weight value. With the wide application of entropy theory in various disciplines, the subject of introducing entropy into the power system has been gradually concerned. This article aims to study the smart terminal security technology of the power grid perception layer based on information entropy data mining. This article analyzes its related methods and designs a smart terminal for the power grid. On this basis, a data analysis platform is built and a safety plan is designed. The result is that the average absolute error, root mean square error, average absolute percentage error, and mean square error of the platform's power load forecast are 1.58, 1.96, 8.2%, and 3.93, respectively. These error values are within the ideal range, and the data processing ability is strong. The packet loss rate of the adversary's eavesdropping was tested, and the average packet loss rates at locations a, b, c, and d were 1.05, 1.2, 1.81, and 2.2%, respectively. Data packets will be definitely lost, so the platform is highly secure.

Details

Language :
English
ISSN :
2191026X
Volume :
31
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Journal of Intelligent Systems
Publication Type :
Academic Journal
Accession number :
edsdoj.f5fe334cf5414684980abfaec5e711
Document Type :
article
Full Text :
https://doi.org/10.1515/jisys-2022-0117