New Model-Based Algorithm for Fault Detection and Identification in DC Railway Systems

At the early age of Railway Systems, the DC solution enabled the deployment of lightweight and efficient traction locomotives compared to AC systems as they do not have to carry a heavy step-down transformer and the rectifier bridge. Moreover, the contact line voltage is sustained by sub-stations connected in parallel along the line, determining a high supply reliability and a balanced load for the AC power grid. However, the protection of this system against short circuit is a challenging task as the configuration of the DC system can change and the short-circuit current is in the order of the sub-station rated current. The protection system currently installed in DC railway systems is effective in clearing faults, however, it has reached its performance limit, and in order to increase the global system performance, new protection technologies must be investigated. In this paper, a new model-based Fault Detection Algorithm (FDA) is proposed. The simulation results prove its ability to overcome the limitations of the current protection system and to localize the fault position in many operating conditions.