Study on Energy-Saving Optimization of Urban Rail Transit Train Timetable under Regenerative Braking

Yajing Zheng, Zihan Ma, Naiyu Liu, Wenzhou Jin and Zhihong Yao

Mathematical Problems in Engineering, 2022, vol. 2022, 1-10

Abstract: Energy-saving driving and regenerative braking energy utilization are two main ways to realize energy-saving optimization of urban rail transit train timetables. On the basis of the more mature energy-saving driving achievements of the predecessors, the absorption utilization rate of regenerative braking energy is improved by adjusting the dwell time of trains in the station so that while a train is braking, other trains in the same electric section are just under traction. In this paper, the overlap time between the traction and braking processes of different trains is used as a measure of the proportion of regenerative braking energy that is absorbed. In order to maximize this overlap time, an energy-saving optimization model of urban rail transit train timetable based on regenerative braking technology was established. To facilitate the solution, the nonlinear constraints are converted to linear at the time of model construction in this paper. In the solution, the spatio-temporal local rolling algorithm and the commercial optimization software ILOG CPLEX are used for the solution. The solution results show that the method in this paper can effectively improve the absorption and utilization of regenerative braking energy.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:5590736

DOI: 10.1155/2022/5590736

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