Since 2008, the Train Management System of Metro the Medellin (MdM) is “DaVinci”, a cutting-edge platform developed by Indra which covers the whole life-cycle of a railway organization. Proof of DaVinci’s spirit for continuously evolving, the Traction Power Saver (TPS) was developed three years ago. It was designed as a tool intended to optimize railway operational plans previously produced by DaVinci’s Planner. Its output is an operational plan like the input one, except for the fact that it saves traction power by synchronizing arrivals at and departures from stations of a line.
Genesis of the Project
MdM and Indra signed in 2010 a contract which implied the development, deployment and put into service of a TPS module integrated within DaVinci.
Metro de Medellin was aiming for high level objectives: Planning power consumption for efficient operation; committing to sustainable growth and environmental performance; C2O minimisation concerning urban mobility; increasing quality of service without modification of the legacy assets.
The module was envisioned to take advantage of the MdM’s railway electrification system and the characteristics of their rolling stock. Firstly, MdM’s Line A and Line B can be seen as two closed electrical circuits (all the stations of a line belong to the same section of power rail). Secondly, MdM’s trains have brakes that can feed back the electric network to a certain extent. Consequently, TPS focuses on the minuend of the global energy equation.
Development of the Project
TPS was designed to maximize the utilization of the energy from the regenerative braking by synchronizing braking and start between pairs of train services within a given electrical section (see figure 2).
TPS takes as input an operational plan produced by DaVinci’s Planner. The output is an efficient operational plan which minimizes traction energy consumption while keeping similar dispatching times and target frequency.
Validation and Benefits
In this phase, we went deep into the concepts of “brake energy regeneration index” (the power rate a braking feeds back), “traction curves” of the trains (strength vs. speed), and “running curves between stations” (speed vs. space).
The algorithm mirrors the railway exploitation. Specifically, traction power saving depends on the operational plan to be optimized, the rail section, the calendar, the timetable frame (when the optimization focuses on non-rush hours, the saving is greater than when rush hours are involved), and the user constraints.
Finally, it should be underlined that, besides the money saving, a development project of this kind has yielded a number of stimulating positive side effects:
◗ Reviewing and consolidating the electrical topology of the track
◗ Adjusting or confirming the train’s Brake Energy Regeneration Index
◗ Revisiting, sometimes correcting, elevation data and infrastructure speed restrictions
◗ Learning about the passenger demand for train services to be fulfilled
◗ Providing the MdM managers with more accurate reports
◗ Improving the service quality MdM offers to the city.
Authors. Carlos Redondo (MdM), Allan Guisao (MdM), José Miguel Rubio (Indra), and Julio Rives (Indra)