Real Time Energy Supervision for Battery Storage System in a Hybrid DC Railway Smart Grid

This paper proposes a real time energy supervision tool to manage the operation of a wayside energy storage system (ESS) connected in a DC railway smart grid. This energy management system (EMS) is adapted to the unique nature of railway substation load demand and the uncertain behavior of renewable energy production. It aims to solicit the ESS in a way that ensures the services it provides are well obtained while respecting economic and technical criteria. The EMS in this paper is composed of two supervision levels, dayahead and real time. The day-ahead is a predictive mode that finds the optimal economic ESS schedule, and the real time is a fuzzy logic model that adjusts the power reference set point provided by the day-ahead in real time based on the current state of the electrical network and actual measurement.