Adaptive Event-Triggered Sliding Mode Load Frequency Control for Cyber-Physical Power Systems Under False Data Injection Attacks

As the new generation of power systems, cyber-physical power systems (CPPSs) become more intelligent and convenient with the application of communication networks. However, the existence of time delays and cyber attacks brings challenges to the control of the system. In this article, the load frequency control (LFC) problem in the CPPS under false data injection (FDI) attacks is investigated and the sliding mode control scheme is applied to address the LFC problem based on an adaptive event-triggered mechanism. First, a dynamic multiarea LFC model with adaptive event-triggered sliding mode control (AET-SMC) scheme is established considering time delays and FDI attacks. Then, a novel Lyapunov–Krasovskii functional is constructed based on the delay-product-term-based looped functional to analyze the stability of the system. Furthermore, the AET-SMC scheme design method is developed by solving linear matrix inequalities. It is also proved that the control law can drive the system state trajectory to the designed sliding surface within a limited time. Finally, two LFC systems are employed to demonstrate the effectiveness and superiority of the proposed control scheme in MATLAB/Simulink. The steady-state error is decreased by about 95% and the transmission frequency is decreased by about 50% compared with the time-triggered scheme. The simulation results verify that the proposed scheme can improve the control performance and save the communication resources for the LFC system under FDI attacks. In addition, the real-time simulation is done based on OPAL-RTLAB 5707 to verify the feasibility of the proposed method.