Cellular automata-based simulation of cross-space transmission of Energy Local Area Network risks: A case study of a power supply station in Beijing

• Published in: Sustainable Energy, Grids and Networks Grids and Networks, 2021-09, Vol.27, p.100521, Article 100521
• Main Authors: Li, Xiaopeng, Ji, Liyan, Zhu, Hanyu, Li, Peng, Jia, Xuefeng, Li, Cunbin
• Format: Article
• Language: English
• Subjects: Cellular automata; Energy Local Area Network; Power information fusion; Risk transmission across space
• ISSN: 2352-4677; 2352-4677
• DOI: 10.1016/j.segan.2021.100521

Energy Internet (EI) is an important way to solve the problem of clean utilization and effective management of energy. The features of EI , such as distributed autonomy and fusion of electric power and information, make its underlying subnet – Energy Local Area Network (ELAN) face greater risks and challenges of multiple devices, heterogeneous standards and real-time interaction in operation. Therefore, it is quite worth for the scientific and orderly development of the EI to study the traditional and new risks during the operation of the ELAN and simulate the transmission and evolution of risks between information and electricity. This article selects the risk of cyber attacks and discusses it based on a power supply station area in Beijing by building a cellular automaton model for risk transmission simulation. First, it constructs the cell architecture and conversion rules of the ELAN, set the information cell infection and defense mode and explains the power cell dispatching and shutdown mechanism. Secondly, the case station area is topologically transformed into a ”binary dependent” adjacent cellular network, and the simulation parameters are set. Finally, it simulates the risk transmission situation with different attack and defense strategies (A–D), different node self-healing rates β and different power over-limit thresholds γ. The simulation result shows the capability of ELAN to resist the transmission of risks across space will be significantly improved by protecting high-level nodes, improving the self-healing ability of information nodes and enhancing the callable power redundancy of autonomous units.