Research on key node identification scheme for power system considering malicious data attacks

State estimation is an important part of ensuring the stable operation of smart grids. By analyzing the measurements and the power system topology, the best estimate can be obtained. However, the false data injection attack (FDIA) is a new threat to the state estimation. It can bypass the traditional bad data detection, make the result of the state estimation deviation, cause the system to make wrong decisions, and affect the security of the smart grid. Therefore, in this paper, an effective defensive scheme against FDIA is proposed. We first study the impact of the FDIA on the node voltage stability index (NVSI) of each node of the power system and find the correspondence between them. Secondly, we use the CFPSO-based K-means++ clustering algorithm to cluster all the nodes in the system into different classes based on their NVSIs. Finally, vulnerability levels are defined based on the clustering results and proactive defenses are taken in advance. The simulation results fully demonstrate the feasibility and effectiveness of the method. (C) 2021 The Author(s). Published by Elsevier Ltd.

Automated summary

This paper proposes an effective defensive scheme against false data injection attacks, studying the impact of attacks on node stability indices and clustering nodes based on the results, defining vulnerability levels and taking proactive defense measures. Simulation results demonstrate the feasibility and effectiveness of the method.