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A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system

机译:最大化地铁系统再生能量利用的时间表优化模型和改进的人工蜂群算法

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Maximizing regenerative energy utilization in subway systems has become a hot research topic in recent years. By coordinating traction and braking trains in a substation, regenerative energy is optimally utilized and thus energy consumption from the substation can be reduced. This article proposes a timetable optimization problem to maximize regenerative energy utilization in a subway system with headway and dwell time control. We formulate its mathematical model, and some required constraints are considered in the model. To keep the operation time duration constant, the headway time between different trains can be different. An improved artificial bee colony algorithm is designed to solve the problem. Its main procedure and some related tasks are presented. Numerical experiments based on the data from a subway line in China are conducted, and improved artificial bee colony is compared with a genetic algorithm. Experimental results prove the correctness of the mathematical model and the effectiveness of i.
机译:近年来,最大化地铁系统中的再生能源利用已成为研究的热点。通过协调变电站中的牵引和制动系统,可最佳利用再生能量,因此可以减少变电站的能耗。本文提出了一个时间表优化问题,以在具有车距和停留时间控制的地铁系统中最大化再生能量的利用。我们制定其数学模型,并在模型中考虑了一些必需的约束。为了保持运行时间恒定,不同列车之间的行进时间可以不同。为了解决该问题,设计了一种改进的人工蜂群算法。介绍了其主要过程和一些相关任务。基于中国地铁线路的数据进行了数值实验,并将改进的人工蜂群与遗传算法进行了比较。实验结果证明了该数学模型的正确性和i的有效性。

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