Modeling and Stability Analysis of an Active Islanding Detection Method in DC Microgrids Using Real-Time Wavelet Analysis

This paper presents a new real-time method for fast and reliable detection of islanding events in DC microgrids (MGs). The method involves injecting a distinct periodic perturbation signal from the controller of the main bidirectional dual active bridge (DAB) DC-DC converter at predetermined intervals. This discrete signal significantly reduces its impact on power quality. Intentionally injecting a narrow-band perturbation signal enhances the method’s ability to differentiate islanding events from random fluctuations and disturbances, demonstrating its robustness. Decentralized detectors at each MG sub-DC link monitor system parameters. Real-time wavelet analysis concurrently decides to disconnect the main DC grid and common DC bus during islanding events, eliminating the need for complex DC circuit breakers (CBs). The proposed method is easily implementable without requiring a separate communication infrastructure and is applicable in scenarios with or without power exchange between the main DC grid and MGs. Detailed mathematical stability analysis confirms the method’s stability, aligning with the IEEE 1547 Standard, and is supported by extensive simulation results.