System Identification Methods for Refined Fault Detection in LVDC-Microgrids

A specific refinement of fault detection in LVDC-microgrids requires model-based knowledge about the system due to possible variations in topology, component parameters and line lengths. In order to gain this information, passive system identification methods based on current and voltage measurement data are applied. Further using machine learning tools for parameter validation, refined and fast model-based fault identification methods can be set up.