Visible to the public Rapid Security Situation Prediction of Smart Grid Based on Markov Chain

TitleRapid Security Situation Prediction of Smart Grid Based on Markov Chain
Publication TypeConference Paper
Year of Publication2019
AuthorsGao, Jian, Bai, Huifeng, Wang, Dongshan, Wang, Licheng, Huo, Chao, Hou, Yingying
Conference Name2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)
Date Publishedmar
KeywordsAutomation, component state prediction, component state transition probability matrix, composability, Conferences, Markov chain analysis method, Markov Mode, Markov processes, Markov state transition probability matrix, Matlab program, Metrics, Microelectronics Security, Monte Carlo methods, power system stability, Predictive Metrics, probability, pubcrawl, rapid security situation prediction, Resiliency, Scalability, security assessment, sequential Monte Carlo method, Situation Prediction, Situation Transition Probability Matrix, smart grid security, smart grid stability, smart power grid, smart power grids, state probability distribution, state transition matrix, system state distribution, system state prediction
Abstract

Based on Markov chain analysis method, the situation prediction of smart grid security and stability can be judged in this paper. First component state transition probability matrix and component state prediction were defined. A fast derivation method of Markov state transition probability matrix using in system state prediction was proposed. The Matlab program using this method was compiled to analyze and obtain the future state probability distribution of grid system. As a comparison the system state distribution was simulated based on sequential Monte Carlo method, which was in good agreement with the state transition matrix, and the validity of the method was verified. Furthermore, the situation prediction of the six-node example was analyzed, which provided an effective prediction and analysis tool for the security situation.

DOI10.1109/ITNEC.2019.8729202
Citation Keygao_rapid_2019