Energy optimisation of single train operation based on tabu search

Abstract

Amid concerns about rising energy prices and environmental issues, the optimisation of automatic train operation (ATO) is significant for energy-efficient operation of trains. Different from the previous researches, this paper presents a more accurate model of the train energy consumption by considering the control strategy of ATO. It then proposes two modifications of tabu search (TS) algorithm, which are named as up-down modification (UDM) and left-right modification (LRM), to optimise train recommended speed curve based on the presented model. The simulation results based on the Beijing Subway illustrate that the proposed approaches can achieve a good performance on energy reduction. Sensitivities of the parameters are analysed to illustrate that the proposed approach is practical and meaningful. In addition, the computation time is within 2 s, which is short enough to be applied in the real-time control of trains.