Real-time train regulation method for metro lines with substation peak power reduction

Jin, Bo; Feng, Xiaoyun; Wang, Hongtao; Sun, Pengfei

doi:10.1016/j.cie.2022.108113

Cited by 8 publications

(2 citation statements)

References 38 publications

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“…As shown in Figure 4, the total consuming time T of passengers consists of two components, which are the waiting time before boarding T wb and the travelling time after boarding T wa T = T wb + T wa (17)…”

Section: Passenger Consuming Timementioning

confidence: 99%

“…About EETT, the key is to provide the regenerative braking energy (RBE) generated by the train to the nearby accelerating train for reuse [15,16]. Due to the superiority of mathematical programming methods in solving the optimal solution, a large number of studies have been carried out, such as mixed integer QP [17], dynamic programming [18], and pseudo-spectrum method [19]. However, since the use of RBE is limited by strict power matching and transmission distance, it can only be fully utilized when there is an accelerating train nearby and the traction power is sufficient.…”

Section: Introductionmentioning

confidence: 99%

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Two‐objective train operation optimization based on eco‐driving and timetabling

Wang,

Feng,

Sun

et al. 2023

IET Intelligent Trans Sys

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In urban railway systems, the timetable guides the section operation of the single train and the arrangement of the train group to meet the dual needs of cost and passengers. This paper proposes a two‐objective train operation optimization based on eco‐driving and timetabling to restore a more realistic scene, including a method level and an objective level. For the method level, the speed curve optimization of the single train and the timetable optimization of the train group are adopted jointly. For the objective level, both the total energy consumption of the train group and the consuming time of passengers are considered. A hybrid solution strategy based on quadratic programming and improved artificial bee colony algorithm is proposed. A hardware‐in‐the‐loop platform is built to carry out validation experiments. Both the cases in general hours and special hours are verified based on the actual data from Beijing Metro Line 15. The results show that both the energy consumption and the passenger consuming time are reduced simultaneously. Correspondingly, the speed curve and the time distribution of the timetable are individually optimized based on the fluctuating passenger flow.

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Section: Passenger Consuming Timementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Two‐objective train operation optimization based on eco‐driving and timetabling

Wang,

Feng,

Sun

et al. 2023

IET Intelligent Trans Sys

Self Cite

View full text Add to dashboard Cite

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Urban rail transit disruption management: Research progress and future directions

Wang,

Jin,

Sun

et al. 2024

Front. Eng. Manag.

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Urban rail transit (URT) disruptions present considerable challenges due to several factors: i) a high probability of occurrence, arising from facility failures, disasters, and vandalism; ii) substantial negative effects, notably the delay of numerous passengers; iii) an escalating frequency, attributable to the gradual aging of facilities; and iv) severe penalties, including substantial fines for abnormal operation. This article systematically reviews URT disruption management literature from the past decade, categorizing it into pre-disruption and post-disruption measures. The pre-disruption research focuses on reducing the effects of disruptions through network analysis, passenger behavior analysis, resource allocation for protection and backup, and enhancing system resilience. Conversely, post-disruption research concentrates on restoring normal operations through train rescheduling and bus bridging services. The review reveals that while post-disruption strategies are thoroughly explored, pre-disruption research is predominantly analytical, with a scarcity of practical pre-emptive solutions. Moreover, future research should focus more on increasing the interchangeability of transport modes, reinforcing redundancy relationships between URT lines, and innovating post-disruption strategies.

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