Robust load frequency control with honeypot-based compensation and AETM under FDI attacks

Area of Science:

• Electrical Engineering
• Control Systems
• Cybersecurity

Background:

• Load frequency control (LFC) is crucial for power system stability.
• False data injection (FDI) attacks pose a significant threat to LFC systems by corrupting control inputs.
• Existing LFC models often lack robustness against sophisticated cyberattacks targeting actuators.

Purpose of the Study:

• To develop a robust LFC model resilient to actuator-side FDI attacks.
• To enhance communication efficiency using an adaptive event-triggered mechanism (AETM).
• To propose a novel honeypot-gated adaptive compensation mechanism for mitigating FDI impacts.

Main Methods:

• Development of an FDI-aware LFC model incorporating transmission lag.
• Introduction of an adaptive event-triggered mechanism (AETM) for efficient communication.
• Design of a honeypot-gated adaptive compensation mechanism for real-time attack mitigation.
• Utilization of Lyapunov-Krasovskii functionals and Linear Matrix Inequalities (LMIs) for stability analysis and controller synthesis.

Main Results:

• The proposed FDI-aware LFC model effectively describes control input corruption.
• The AETM significantly improves communication efficiency by reducing transmissions.
• The honeypot-gated mechanism successfully attenuates the impact of FDI attacks on frequency regulation.
• Stability analysis confirmed robust performance with guaranteed [Formula: see text] bounds under attack scenarios.

Conclusions:

• The developed method provides a robust solution for LFC under FDI attacks.
• The proposed approach enhances both the security and efficiency of power system frequency control.
• Simulation results validate the effectiveness of the proposed defense strategy against FDI-induced errors.