Optimal Energy Management, Location and Size for  Stationary Energy Storage System in a Metro Line Based on Genetic Algorithm

Xia, Huan; Chen, Huaixin; Yang, Zhongping; Lin, Fei; Wang, Bin

doi:10.3390/en81011618

Cited by 75 publications

(33 citation statements)

References 24 publications

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“…Walter [18] gave an overview of the various possibilities of increased energy efficiency in electric railway systems, and highly reliable energy storage was focused on to save energy and operation cost in the paper. Wang [19] and Xia [20] studied the optimization on the location and size of the energy storage systems in metro lines, acting as a compromise between satisfying better energy savings, voltage profile and lower installation cost.…”

Section: %mentioning

confidence: 99%

Evaluation of Strategies to Reducing Traction Energy Consumption of Metro Systems Using an Optimal Train Control Simulation Model

Tang

Wang

2016

Energies

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Abstract:Increasing attention is being paid to the energy efficiency in metro systems to reduce the operational cost and to advocate the sustainability of railway systems. Classical research has studied the energy-efficient operational strategy and the energy-efficient system design separately to reduce the traction energy consumption. This paper aims to combine the operational strategies and the system design by analyzing how the infrastructure and vehicle parameters of metro systems influence the operational traction energy consumption. Firstly, a solution approach to the optimal train control model is introduced, which is used to design the Optimal Train Control Simulator(OTCS). Then, based on the OTCS, the performance of some important energy-efficient system design strategies is investigated to reduce the trains' traction energy consumption, including reduction of the train mass, improvement of the kinematic resistance, the design of the energy-saving gradient, increasing the maximum traction and braking forces, introducing regenerative braking and timetable optimization. As for these energy-efficient strategies, the performances are finally evaluated using the OTCS with the practical operational data of the Beijing Yizhuang metro line. The proposed approach gives an example to quantitatively analyze the energy reduction of different strategies in the system design procedure, which may help the decision makers to have an overview of the energy-efficient performances and then to make decisions by balancing the costs and the benefits.

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Section: %mentioning

confidence: 99%

Evaluation of Strategies to Reducing Traction Energy Consumption of Metro Systems Using an Optimal Train Control Simulation Model

Tang

Wang

2016

Energies

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“…The traffic model and the computation times in [16] have been replaced by the model in this paper and the simulation times obtained with our simulator. The average simulation times measured for a single traffic scenario are 0.77 s, 1.31 s, and 2.73 s for the 4-, 7-, and 15-min headways, respectively.…”

Section: Computational Burden Analysismentioning

confidence: 99%

“…Bae [14] Study of the effect of the inclusion of RSs in an MTS Several Lee et al [15] Peak power reduction using a wayside ESS One Xia et al [16] GA for optimising wayside ESS placement, sizing and energy management. Several…”

Section: Optimisation Study Scope Headways Remarksmentioning

confidence: 99%

“…For this reason, the optimiser presented in [16] has been used as a reference for obtaining computation time results. That work implements a genetic algorithm to search for optimum infrastructure configurations.…”

Section: Computational Burden Analysismentioning

confidence: 99%

“…The study only includes peak-time headway with a fixed dwell time (deterministic). References [16,17] are two rigorous studies by the same workgroup devoted to the optimal location and sizing of ESSs. They use three headways with a single traffic scenario per headway.…”

Section: Introductionmentioning

confidence: 99%

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Improving the Traffic Model to Be Used in the Optimisation of Mass Transit System Electrical Infrastructure

et al. 2017

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Among the different approaches for minimising the energy consumption of mass transit systems (MTSs), a common concern for MTS operators is the improvement of the electrical infrastructure. The traffic on the lines under analysis is one of the most important inputs to the studies devoted to improving MTS infrastructure, since it represents where and how frequently it is possible to save energy. However, on the one hand, MTS electrical studies usually simplify the traffic model, which may lead to a misrepresentation of the energy interactions between trains. On the other hand, if the stochastic traffic is rigorously modelled, the size of the simulation problem could grow excessively, which in turn could make the time to obtain results unmanageable. To cope with this issue, this paper presents a method to obtain a reduced-size set of representative scenarios. Firstly, a traffic model including the most representative stochastic traffic variables is developed. Secondly, a function highly correlated with energy savings is proposed to make it possible to properly characterise the traffic scenarios. Finally, this function is used to select the most representative scenarios. The representative scenario set obtained by the application of this method is shown to be sufficiently accurate with a limited number of scenarios. The traffic approach in this paper improves the accuracy with respect to the usual traffic approach used in the literature.

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Improving Chosen Elements of Energy Efficiency in Public Transport Through the Use of Supercapacitors

Krawczyk

Wojciechowski

2019

Advances in Intelligent Systems and Computing

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Optimal Energy Management, Location and Size for Stationary Energy Storage System in a Metro Line Based on Genetic Algorithm

Cited by 75 publications

References 24 publications

Evaluation of Strategies to Reducing Traction Energy Consumption of Metro Systems Using an Optimal Train Control Simulation Model

Evaluation of Strategies to Reducing Traction Energy Consumption of Metro Systems Using an Optimal Train Control Simulation Model

Improving the Traffic Model to Be Used in the Optimisation of Mass Transit System Electrical Infrastructure

Improving Chosen Elements of Energy Efficiency in Public Transport Through the Use of Supercapacitors

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