Electric Power ›› 2022, Vol. 55 ›› Issue (10): 23-31.DOI: 10.11930/j.issn.1004-9649.202206114

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Analysis of Distribution Network Information Risks Based on Knowledge Graph and Cellular Automata

MEI Bingxiao, ZHOU Jinhui, SUN Xiang   

  1. State Grid Zhejiang Electric Power Company Research Institute, Hangzhou 310007, China
  • Received:2022-06-27 Revised:2022-08-25 Online:2022-10-28 Published:2022-10-20
  • Supported by:
    This work is supported by National Natural Science Foundation of China (Development of Video Image Detection Platform for Characterizing Defection of Power Transmission and Transformation Equipment, No.62127803).

Abstract: In order to describe the propagation process of the information system risks in distribution networks and ensure the safe and reliable operation of power systems, the knowledge graph and cellular automata technology are used to analyze the distribution network information system risks. Firstly, the knowledge graph method is used to extract and fuse the risk knowledge of the multi-source heterogeneous information collected from distribution networks, so as to realize static analysis of the information risks. Secondly, a cellular automata model is built for risk analysis of the distribution networks, and the transition mechanism between the normal state and the fault state of the cell is designed to realize dynamic analysis of the evolution process of the distribution network information risks. Finally, based on simulation experiments, it is verified that the proposed method can effectively describe the cross-spatial propagation process of the distribution network information risks.

Key words: knowledge graph, distribution network, information system, risk analysis, cellular automata