Improvement of the Energy Efficiency of Subway Traction Systems Through the Use of Genetic Algorithm in Traffic Control

AbstractThis paper proposes a subway energy regeneration model, based on control stops and train departures throughout his trip, with the use of energy from the regenerative braking in the drive system. The goal is to optimize the power consumption and improve efficiency, in view of sustainable management. Applying genetic algorithm to get the better of the trains’ traffic configuration, the research develops and tests the Traction Control Algorithm for Subway Energy Regeneration (ACTREM), using the Scilab program. To analyze the performance of ACTREM control algorithm in enhancing energy efficiency, there were fifteen simulations of applying ACTREM on line 4—Yellow subway in São Paulo. These simulations showed the ACTREM efficiency to generate automatically diagram schedules optimized for energy savings in metro systems, considering the system’s operational constraints such as maximum each train capacity, total wait time, total travel time and interval between trains. The results show that the proposed algorithm can save 9.5% of the energy and does not cause significant impacts on the transportation system capacity passengers and also suggest possible continuity studies.