Research on Multi-train Cooperative Utilization of Regenerative Braking Energy for Low-speed Maglev Traffic

JIAO Yanjun; LIU Sikai; MA Xiao; LIU Shaoke

doi:10.13890/j.issn.1000-128x.2017.04.106

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Research on Multi-train Cooperative Utilization of Regenerative Braking Energy for Low-speed Maglev Traffic

更新时间：2021-12-13

- Research on Multi-train Cooperative Utilization of Regenerative Braking Energy for Low-speed Maglev Traffic
- Electric Drive for Locomotives Issue 4, Pages: 85(2017)
- 作者机构：
  
  1. 国防科学技术大学机电工程与自动化学院,湖南,长沙,410073
- 作者简介：
- 基金信息：
- DOI：10.13890/j.issn.1000-128x.2017.04.106
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JIAO Yanjun, LIU Sikai, MA Xiao, et al. Research on Multi-train Cooperative Utilization of Regenerative Braking Energy for Low-speed Maglev Traffic. [J]. Electric Drive for Locomotives (4):85(2017)
DOI：

JIAO Yanjun, LIU Sikai, MA Xiao, et al. Research on Multi-train Cooperative Utilization of Regenerative Braking Energy for Low-speed Maglev Traffic. [J]. Electric Drive for Locomotives (4):85(2017) DOI： 10.13890/j.issn.1000-128x.2017.04.106.

摘要

首先分析了中低速磁浮交通单列车运行能耗和供电系统，在此基础上建立多列车运行能耗模型。为了充分利用再生制动能量，提出了可对运行间隔、停站时间和区间运行时分微调的列车运行时刻表制定方法。设计了多种群遗传算法，以多列车运行能耗最低和最大程度利用再生制动能量为目标，优化列车运行时刻表。通过采用精英保留策略和移民策略算法，提高了寻优过程的稳定性和速度。仿真结果表明，本文方法可将再生制动能量的利用率由传统14.8% 提高到80.9%，将被利用的再生制动能量与运行能耗比值由传统0.74% 提高到4.2%。

Abstract

Single train model of operation energy consumption and power supply system was analyzed firstly, and on the basis of this, a multi-train operation energy consumption model was established. In order to make full use of the regenerative braking energy, a method was put forward to set up the train operation schedule which could implement fine tune of departure interval, the stopping time and the running time. A multiple population genetic algorithm was designed to optimize the train operation schedule with the minimum energy consumption and the maximum utilization of the regenerative braking energy as the goal. The elite reservation strategy and migration strategy were adopted to improve the stability and speed of the optimization process in the algorithm. Simulation results showed that this method could increase the utilization rate of regenerative braking energy from 14.8% to 80.9%, and the ratio of regenerative braking energy utilization and operation energy consumption could be increased from 0.74% to 4.2%.

关键词

磁浮列车列车运行控制节能驾驶节能优化多种群遗传算法

Keywords

maglev traintrain operation controlenergy saving drivingenergy saving optimizationmulti population genetic algorithm

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