False Data Injection Attack Detection and Improved WLS Power System State Estimation Based on Node Trust

• Published in: Journal of electrical engineering & technology 2022, 17(2), , pp.803-817
• Main Authors: Qu, Zhengwei, Zhang, Jianxuan, Wang, Yunjing, Georgievitch, Popov Maxim, Guo, Kai
• Format: Article
• Language: English
• Subjects: Electrical Engineering; Electrical Machines and Networks; Electronics and Microelectronics; Engineering; Instrumentation; Original Article; Power Electronics; 전기공학
• ISSN: 1975-0102; 2093-7423
• DOI: 10.1007/s42835-021-00923-1

To solve the problem that the false data injection attack can evade the unfavorable data recognition mechanism and tamper with the state estimation, this paper proposes a detection and defense scheme for the fake data injecting attack based on the trust degree of the nodes. Considering the failure of the attacker’ s carefully constructed implicit data injection attack with residual threshold method, this paper proposes a node trust model and a trust update algorithm based on the characteristics of state estimation of power system nodes. Feasibility of detecting false data injection based on trustworthiness and using IEEE-14 and IEEEE-118 nodes to systematically analyze different false information injection scenarios. Secondly, in order to eliminate the interference of the false data injected by the attacker to the normal operation of power network, this paper combines the process of trust updating algorithm with the classical weighted least square algorithm to improve the robustness of state estimation and to mitigate the influence of fake data injection attacks on power networks. In this paper, simulation experiments are carried out on 14 nodes and 118 nodes system to test the accuracy of the optimized state estimation algorithm.