Detection of False Data Injection and Series Arc Faults in DC Microgrids Based on Unknown Input Observers

DC microgrid’s secondary control consists of physical and cyber layers with cooperative control structure that relies on the communication between different subsystems. This makes the system vulnerable to cyber attacks that can disrupt the system stability. Meanwhile, physical faults, such as series arc fault, can also cause significant threat to the stability and operation of the system. In this paper, an architecture to detect both false data injection and series arc faults for DC microgrids with distributed generation units (DGU) is proposed. Two types of unknown input observers (UIO) are used to achieve the detection and identification. The proposed UIOs are verified through hardware in the loop simulations.