Decentralized Coordinated Cyberattack Detection and Mitigation Strategy in DC Microgrids Based on Artificial Neural Networks

DC microgrids can be considered as cyber-physical systems (CPSs) and they are vulnerable to cyberattacks. Therefore, it is highly recommended have effective plans detect remove cyberattacks in dc microgrids. This article shows how artificial neural networks help mitigate coordinated false data injection attacks (FDIAs) on current measurements a type of FDIAs try inject the into system disrupt control application, which make microgrid shutdown. The proposed method decentralized approach has capability estimate value injected data. In addition, strategy even for unfair with high domains all units at same time. tested detailed simulated using MATLAB/Simulink environment. Finally, real-time simulations by OPAL-RT implemented evaluate strategy.