Cyber-Security Attacks on Microgrid and Its Mitigation via Adaptive Fuzzy PID Controller

Abstract

Cyberattacks on frequency stability problems pose a significant threat to microgrids. Furthermore, frequency fluctuations brought on by cyberattacks in any region of the microgrid impact the system, endangering the stability of the network. This problem can be fixed using a self-adaptive virtual inertia control strategy, which enhances the microgrid’s stability and damping capabilities. When using this control method, the evaluation of the microgrid’s frequency data is obtained through the usage of a phase-locked loop (PLL). However, because of its system dynamics, PLL implementation in microgrids produces more frequency oscillation. Once more, this work addresses the above problem by presenting a robust adaptive fuzzy PID controller (AFPID) for virtual inertia control. This controller will simultaneously increase the stability of the microgrid system and reduce the undesired frequency measurement impacts caused by cyberattacks. A unique modified artificial ecosystem-based optimization technique (mAEO) is put forth to fine-tune the controller parameters further. The effectiveness of the suggested solutions is examined by contrasting the simulation results with a few common strategies while considering changes in system parameters and varying rates of cyberattacks.