Refined Fault Detection in LVDC-Grids with Signal Processing, System Identification and Machine Learning Methods

Direct current microgrids in the low voltage range require specific system protection. In addition to the basic functionality of conventional protective devices, a refined and model-based analysis of measured current and voltage signals is necessary. Signal processing, system identification and machine learning methods are helpful to identify, classify and localize faults and gradual malfunction. Online condition monitoring allows the realization of predictive maintenance concepts, a thorough analysis of occurring events guards against grid sector breakdown by an appropriate and selective tripping of protective devices.