Security of Substation Information in Energy Networks Using the Markov Decision Process

Abstract

In recent years, as the amount of new energy production has steadily increased and new technologies have developed rapidly, energy networks have increasingly become more diverse and intricate. Being a vital social infrastructure, the smart grid will confront a growing number of network security risks as a result of the complicated network security environment and competing interests. Taking into account the significance of information security in the energy network and the need for its safe and stable operation, this research employs modelling and simulation to examine the security risk of smart substations when the network is under cyber-attacks. On the basis of the preceding background, this report first enumerates and analyses prevalent network attack methods and risk assessment methodologies in energy networks, and then determines the necessary components based on the features of smart substations. Second, this study analyses the probabilities of state transitions under various assault pathways. Lastly, a network assault model of smart substation based on the Markov Decision Process is developed from the standpoint of the attacker, and the solution analysis for network security risk assessment is conducted.

Date of Award	31 Dec 2023
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Haiyu Li (Supervisor) & Zhirun Hu (Supervisor)