Resilient Event-Driven Distributed Control for DC Microgrids Against False Data Injection Attacks

Distributed controlled DC microgrids (DCmG) are highly subjected to cyber-attacks due to the sensor feedback and distributed communication. Though the cyber-attacks are a low-probability events in the distributed controlled DCmG, it significantly disrupts DCmG operation and the controller’s objectives and sometimes may lead to a total system shutdown. This paper proposes a localized attack detection and an event-driven mitigation to make distributed controlled DCmG resilient against false data injection (FDI) attacks. Firstly, an attack impact analysis is presented to determine the deviation in average voltage and output current caused from its pre-attacked values due to the FDI attack. Based on the analysis, the global control objectives are derived for the resilient DCmG operation. A localized attack detection based on the error between sensor measurement value and artificial neural network (ANN) estimated value is used to detect the FDI attack. Further, an event-driven resiliency is developed to mitigate the attack, where the attacked measurements are replaced with ANN based estimated values. The proposed event-driven resilient distributed secondary control and the theoretical impact analysis are validated using simulation and experimental results for different FDI attacks on voltage and current sensors measurements.