Simulation of energy-efficient operation for metro trains: A discrete event-driven method based on multi-agent theory

Abstract

Along with the rapid development of urban rail transit systems, the increase in operating mileage is the direct result of the enormous energy consumption. Among them, the energy consumption of train traction operation is close to half of the total energy consumption, leading to a gradual increase in operation cost. Based on the discrete event-driven method of multi-agent simulation, this paper simulates the process of the train operation with four function modules. Ingenuity, trains with onboard equipment would store braking regenerative energy and then transmit regenerative energy to other traction trains in the same power supply section. Moreover, the evaluation method of renewable energy utilization efficiency also is proposed with different operation schemes to calculate train operation energy consumption. Further, an adaptive large neighborhood search algorithm is designed to improve computational efficiency for real-time applications. Lastly, the operation of the Beijing Metro Yizhuang line is utilized as a case study to evaluate the simulation model and algorithm. The results show that the simulation method can reasonably simulate the process of train operation according to the actual situation. By optimizing the train operation time and dwell time of different onboard power storage equipment scenarios, the traction energy consumption can be reduced by 3.95% and up to 17.71%, which has a remarkable effect on energy saving.