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首页> 外文期刊>Journal of control, automation and electrical systems >Improvement of the Energy Efficiency of Subway Traction Systems Through the Use of Genetic Algorithm in Traffic Control
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Improvement of the Energy Efficiency of Subway Traction Systems Through the Use of Genetic Algorithm in Traffic Control

机译:通过在流量控制中使用遗传算法来提高地铁牵引系统的能效

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摘要

This paper proposes a subway energy regeneration model, based on control stops and train departures throughout his trip, with the use of energy from the regenerative braking in the drive system. The goal is to optimize the power consumption and improve efficiency, in view of sustainable management. Applying genetic algorithm to get the better of the trains' traffic configuration, the research develops and tests the Traction Control Algorithm for Subway Energy Regeneration (ACTREM), using the Scilab program. To analyze the performance of ACTREM control algorithm in enhancing energy efficiency, there were fifteen simulations of applying ACTREM on line 4 - Yellow subway in Sao Paulo. These simulations showed the ACTREM efficiency to generate automatically diagram schedules optimized for energy savings in metro systems, considering the system's operational constraints such as maximum each train capacity, total wait time, total travel time and interval between trains. The results show that the proposed algorithm can save 9.5% of the energy and does not cause significant impacts on the transportation system capacity passengers and also suggest possible continuity studies.
机译:本文提出了一种地铁能量再生模型,基于在他的行程中的控制停止和火车脱落,利用驱动系统中的再生制动的能量。考虑到可持续管理,目标是优化功耗和提高效率。应用遗传算法以获得更好的列车流量配置,研究使用Scilab程序开发和测试地铁能量再生(Actrem)的牵引控制算法。为了分析CATREM控制算法在提高能源效率方面的性能,在圣保罗排队4 - 黄色地铁中施用Actrem的十五次模拟。这些模拟显示了ActREM效率,用于自动为地铁系统节省优化的图表时间表,考虑到系统的运行限制,例如最大每列列车,总等待时间,总旅行时间和列车之间的间隔。结果表明,该算法可以节省9.5%的能量,并对运输系统容量乘客产生重大影响,并提出可能的连续性研究。

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