Malicious Mode Attack on EV Coordinated Charging Load and MIADRC Defense Strategy

26 Oct 2021  ·  Yichen Zhou, Weidong Liu, Jing Ma, Xinghao Zhen, Yonggang Li ·

The Internet of Things (IoT) provides a salient communication environment to facilitate the coordinated charging of electric vehicle (EV) load. However, as IoT is connected with the public network, the coordinated charging system is in a low-level cyber security and greatly vulnerable to malicious attacks. This paper investigates the malicious mode attack (MMA), which is a new cyberattack pattern that simultaneously attacks massive EV charging piles to generate continuous sinusoidal power disturbance with the same frequency as the poorly-damped wide-area electromechanical mode. Thereby, high amplitude forced oscillations could be stimulated by MMA, which seriously threats the power system stability. First, the potential threat of MMA is clarified by investigating the vulnerability of the IoT-based coordinated charging load control system, and an MMA process like Mirai is pointed out as an example. And then, based on the attack process, an MMA model is established for impact analysis where expressions of the mean and stochastic responses of the MMA forced oscillation are derived to discover main impact factors. Further, to mitigate the impact of MMA, a defense strategy based on multi-index information active disturbance rejection control is proposed to improve the stability and anti-disturbance ability of the power system, which considers the impact factors of both mode damping and disturbance compensation. Simulations are conducted to verify the existence and characteristics of MMA threats, and the efficiency of the proposed defense strategy is also validated.

PDF Abstract
No code implementations yet. Submit your code now



  Add Datasets introduced or used in this paper

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.


No methods listed for this paper. Add relevant methods here