Optimization Method of Subway Timetables for Regenerative Braking Energy Utilization

Abstract

Reducing the energy consumption of trains plays an important role in sustainable development of the subway system. When timetables are generated mainly considering passenger satisfaction, there are still some margins to optimize them to improve the energy efficiency. This paper slightly reoptimizes the planned timetable to reduce the energy consumption by improving the utilization of regenerative braking energy, while not changing the number of the subway trains. To this purpose, the authors innovatively propose a periodic or off-peak subway timetable optimization method to coordinate the arrivals and departures of all trains located in the same power supply section, so that the regenerative energy from braking trains can be more effectively utilized by other trains. First, we built a timetable optimization model with constraints derived from the planned timetable, which takes dwell time, the time shift of downbound timetable, and headway as decision variables, aiming to minimize the total energy consumption. Second, we designed a timetable optimization algorithm with two levels and high computational efficiency. In the upper level, the multiresolution-based traversal algorithm (MBTA) is proposed to search the feasible sets of time shift of the downbound timetable and the headway. And in the lower level, the decomposition coordination algorithm (DCA) is designed, in which the dwell times of the trains in the same power supply section are optimized in an optimization subproblem. Simulations are given using the real data of Beijing Metro Line 4 to evaluate the proposed method, and the results show that the proposed timetable optimization method can reduce energy consumption by 11.12%. In the random disturbance simulations, the proposed method showed robustness, which makes it possible to apply this method to real subway operations.