Co-optimizing electric bus dispatching and charging considering limited resources and battery degradation

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引用次数: 0

Abstract

This paper aims to formulate a mathematical model for a multi-type electric bus scheduling problem to determine the optimal fleet composition, bus-to-trip assignment, and partial charging schedule, where the battery degradation, nonlinear charging, and the constraint of charging station capacity are considered. A time-expanded network is proposed to represent the bus-to-trip assignment and partial charging. An adaptive large neighborhood search algorithm is designed to solve the problem. Using a multi-line bus network in Nanjing as the case, empirical operational data is used to generate monthly timetable samples to simulate the uncertainty of trip travel time and energy consumption. The result shows that the charging station capacity can be reduced from 20 (real-world case) to 12, considering the cost-effectiveness and robustness of the bus system. The result of this study also provides suggestions on the charging duration choices and the starting state-of-charge for different periods of the day. In peak and off-peak hours, 20-30-minute charging is recommended for electric buses with state-of-charge lower than 30 %, and 10-minute charging is more recommended when the state-of-charge of the electric bus is between 30 % and 70 %.

考虑到有限资源和电池衰减,共同优化电动公交车的调度和充电
本文旨在建立一个多类型电动公交车调度问题的数学模型,以确定最优的车队组成、公交车到行程分配和部分充电计划,其中考虑了电池衰减、非线性充电和充电站容量约束。我们提出了一个时间扩展网络来表示公交车到班次的分配和部分充电。设计了一种自适应大邻域搜索算法来解决该问题。以南京的多线公交网络为例,利用经验运营数据生成月度时刻表样本,模拟出行时间和能耗的不确定性。结果表明,考虑到公交系统的成本效益和稳健性,充电站容量可从 20 个(实际情况)减少到 12 个。研究结果还为一天中不同时段的充电时间选择和起始充电状态提供了建议。在高峰和非高峰时段,建议对充电状态低于 30% 的电动公交车充电 20-30 分钟,而当电动公交车的充电状态介于 30% 和 70% 之间时,更建议充电 10 分钟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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