An Integrated Energy-Efficient Operation Methodology for Metro Systems Based on a Real Case of Shanghai Metro Line One

Gong, Cheng; Zhang, Shiwen; Zhang, Feng; Jiang, Jianguo; Wang, Xinheng

doi:10.3390/en7117305

Cited by 48 publications

(37 citation statements)

References 49 publications

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“…Underground transportation has known advantages in heavily populated cities and its relationship with sustainability has been well studied (Jackson and Holden, 2013;Gong et al, 2014). The enhancement proposed consists in finishing an uncompleted underground line which connects the south east area of Valencia with the city center.…”

Section: First Questionnaire and Decision Hierarchy Structurementioning

confidence: 99%

Prioritization by consensus of enhancements for sustainable mobility in urban areas

Curiel-Esparza

Mazario-Diez

Canto-Perello

et al. 2016

Environmental Science & Policy

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ElsevierCuriel Esparza, J.; Mazario-Diez, JL.; Canto-Perello, J.; Martín Utrillas, MG. (2016). Prioritization by consensus of enhancements for sustainable mobility in urban areas. Environmental Science and Policy. 55 (1) ABSTRACTNowadays the European cities usually present important problems at economic, social and environmental levels. The European Union has published policies to ease this issue, and several European cities are creating sustainable mobility urban plans with the measures which can be taken to improve the mobility system. Transport decisions have direct impact on transit times, urban connectivity, and have also effects in the environment, public health and society. Choosing the best enhancement to implement is a complex decision, depending on tangible and intangible criteria, which have to be taken into account together. A compromise solution that weighs travel quality, cost and sustainability inputs has to be achieved. This research work presents a decision support system to select the optimal sustainability enhancement integrating the Delphi technique with the Analytic Hierarchy Process and the VIKOR method. GRAPHICAL ABSTRACT HIGHLIGHTSSelect optimal strategies in achieving sustainable mobility.Analytic Hierarchy Process combined with a Delphi technique and the VIKOR method.Framework to achieve consensus decision-making in urban mobility.Applying tangible and intangible criteria in sustainable urban transport.

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Section: First Questionnaire and Decision Hierarchy Structurementioning

confidence: 99%

Prioritization by consensus of enhancements for sustainable mobility in urban areas

Curiel-Esparza

Mazario-Diez

Canto-Perello

et al. 2016

Environmental Science & Policy

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“…(4) The train's departure times at each station are equal to the ones of the initial timetable. (5) In this model, the motor efficiency is simplified.…”

Section: Passenger Characteristicsmentioning

confidence: 99%

“…The timetable optimization model formulated in this paper allows trains to drive as the optimal control strategy with a fixed running time of the section contributed by the reduction of dwelling time at the station, which has a significant reduction in energy consumption (more than 20%). Compared with [5], when we construct the train movement model, both the track gradients and the curves are taken into account in order to describe train energy consumption more accurately.…”

Section: Introductionmentioning

confidence: 99%

“…There are two main levels of train energy-efficient operation approaches. A recent emerging research interest is in the field of regenerative energy utilization [1][2][3][4][5][6], which focuses on developing a timetable including the dwelling time at stations and running time at sections (between two adjacent stations) in order to improve the utilization of regenerative energy by synchronizing the operations of accelerating and braking trains [7]. Compared with the upper level of timetable optimization, the lower level of energy-efficient control strategy design at sections has long attracted widespread attention [8][9][10][11][12][13][14][15][16][17][18][19][20][21] to calculate the speed profile with minimum tractive energy consumption under the timetable constraints [22].…”

Section: Introductionmentioning

confidence: 99%

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Optimizing the Energy-Efficient Metro Train Timetable and Control Strategy in Off-Peak Hours with Uncertain Passenger Demands

Feng

Liu

et al. 2017

Energies

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How to reduce the energy consumption of metro trains by optimizing both the timetable and control strategy is a major focus. Due to the complexity and difficulty of the combinatorial operation problem, the commonly-used method to optimize the train operation problem is based on an unchanged dwelling time for all trains at a specific station. Here, we develop a simulation-based method to design an energy-efficient train control strategy under the optimized timetable constraints, which assign the dwelling time margin to the running time. This time margin is caused by dynamically uncertain passenger demands in off-peak hours. Firstly, we formulate a dwelling time calculation model to minimize the passenger boarding and alighting time. Secondly, we design an optimal train control strategy with fixed time and develop a time-based model to describe mass-belt train movement. Finally, based on this simulation module, we present numerical examples based on the real-world operation data from the Beijing metro Line 2, in which the energy consumption of one train can be reduced by 21.9%. These results support the usefulness of the proposed approach.

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“…As previously, an important number of projects and test were been developed in terms of speed profiles (Asnis et al 1985, Calderaro et al 2014and Gong et al 2014, manual driving for freight trains (Lukaszewicz, 2001), genetic algorithms (Khmelnitsky 2000 andBigharaz et al 2014) and high speed driving speed profiles (Sicre et al 2012). In addition, other recent researches were focused on the use of energy storage systems (Fournier, 2014 andWang et al 2014).…”

Section: Introductionmentioning

confidence: 99%

An energy-efficient metro speed profiles for energy savings: application to the Valencia metro

Sanchís

Zuriaga²

2016

Libro De Actas CIT2016. XII Congreso De Ingeniería Del Transporte

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Nowadays one of the main priorities for metro line operators is the reduction of energy consumption, due to the environmental impact and economic cost. In order to achieve this objective different strategies can be applied, normally focused into rolling stock, infrastructure and/or operation.Considering short-term measures and related to the traffic operation strategies, different approaches are being researched. One of the most effective strategy which reduce net energy consumption is the use of efficient driving techniques. These techniques produces a speed profile between two stations that requires the minimum net energy consumption, without degrading commercial running times or passenger comfort.In this paper, a computer model for calculating the metro vehicles speed profiles minimizing the energy consumption was developed. The equations considered in the model represent the behavior of a single vehicle operated under manual driving, subject to different constraints such as the headway, cycle time, distances and acceleration limits. The proposed model calculates different commands to be systematically executed by the driver.The resulting simulator has been tuned by means of on board measurements of speed, accelerations and energy consumption obtained along different lines in Metro de Valencia network. For this purpose, different scenarios are analyzed to assess the achievable energy savings. In general terms and comparing with the actual energy consumption, the solutions proposed can reduce the net energy consumption around 19%.

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An Integrated Energy-Efficient Operation Methodology for Metro Systems Based on a Real Case of Shanghai Metro Line One

Cited by 48 publications

References 49 publications

Prioritization by consensus of enhancements for sustainable mobility in urban areas

Prioritization by consensus of enhancements for sustainable mobility in urban areas

Optimizing the Energy-Efficient Metro Train Timetable and Control Strategy in Off-Peak Hours with Uncertain Passenger Demands

An energy-efficient metro speed profiles for energy savings: application to the Valencia metro

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