DGMM Based Network Traffic Prediction for Smart Substation

Abstract:

Compared with traditional substation, smart substation process layer network, which has the same meaning as relay protection and safety automatic devices, is actually equivalent to the secondary circuit of traditional substation protection. Once an exception occurs in the network traffic of process layer, it will directly affect the reliability, rapidity and agility of relay protection action. According to the characteristics of network traffic of smart substation, this paper proposed a novel dynamic grey Markov model (DGMM) based network traffic prediction approach, which could assist decision making for the network performance analysis and prediction, network failures and viruses invasion warning of smart substation. Experiments demonstrated the effective and efficiency of the proposed approach, which could guarantee the security operation of power grid.

• Periodical: Applied Mechanics and Materials (Volume 339)
• Pages: 401-408
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.339.401
• Online since: July 2013
• Authors: Jin Wang, Zeng Kai Wang
• Keywords: DGMM, Network Traffic Prediction, Smart Substation

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