Covert Attack Detection for LFC Systems of Electric Vehicles: A Dual Time-Varying Coding Method

In recent years, electric vehicles (EVs) have been widely used due to their remarkable decrease in carbon emissions and gasoline consumption. When the EVs are incorporated into the load frequency control (LFC) system, which can be seen as both the power supply and load of the power systems. However, the LFC system with EVs is vulnerable to the covert attacks and consequently the reliable operation performance and security of the power system will be affected. To solve this security issue, the real-time monitoring and detection problems are investigated in this article. First, a networked LFC system with EVs is well established, which takes load disturbances, measurement noises, and covert attacks into account so as to truly reflect the operation process of the power system. Then, an
${\mathcal {H}}_{\infty }$
sliding mode observer (SMO) is proposed to accurately estimate the internally physical state of the LFC system with EVs. In order to detect and disclose the covert attacker, a dual time-varying coding detection scheme is proposed, wherein both the control and measurement signals are encrypted before transmitting to the communication network. Subsequently, a dual time-varying coding-based detection algorithm is established, which ensures that the covert attacks can be detected without significant delay. Finally, one simulation is presented to provide tangible evidence of the effectiveness of the proposed real-time monitoring and detection methodology.