A Dynamic Programming Model for Joint Optimization of Electric Drayage Truck Operations and Charging Stations Planning at Ports
A Dynamic Programming Model for Joint Optimization of Electric Drayage Truck Operations and Charging Stations Planning at Ports
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DOI：
10.1109/tits.2023.3285668
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发表时间：
2023-11
影响因子：
8.5
通讯作者：
Xuanke Wu;Yunteng Zhang;Yuche Chen
中科院分区：
文献类型：
--
作者：
Xuanke Wu;Yunteng Zhang;Yuche Chen
在港口采用电动汽车是实现可持续发展目标的一种有希望的方法。然而，实现这一战略的全部潜力取决于基础设施规划和运营调度之间的有效协调。在本文中，我们提出了一个联合优化框架，可以共同优化这两个组件，以最小化整体系统成本。为了捕捉调度决策的动态特性，我们使用动态规划技术对问题建模。我们的模型考虑了不同卡车行程的充电和驾驶成本的时空异质性。为了评估我们提出的框架的有效性，我们在洛杉矶港和长滩港进行了实证研究。具体来说，我们的目标是使用电动拖运卡车来完成每日20英尺当量单位集装箱的5%。我们的模型确定了满足集装箱吞吐量要求所需的电动卡车、充电站和卡车时间表的最佳数量。我们还分析了每个容器的成本作为各种场景的日吞吐量水平的函数。我们的研究结果为如何根据港口的日吞吐量确定充电器供应提供了见解，以及如何在不同吞吐量和电力价格的情况下选择卡车车队中合适的电动卡车比例和电池尺寸。
The adoption of electric vehicles at ports is a promising approach to achieve sustainability goals. However, realizing the full potential of this strategy depends on effective coordination between infrastructure planning and operational scheduling. In this paper, we propose a joint optimization framework that can co-optimize these two components to minimize the overall system cost. To capture the dynamic nature of scheduling decisions, we model the problem using dynamic programming techniques. Our model accounts for the spatial and temporal heterogeneities of charging and driving costs for different truck trips. To evaluate the effectiveness of our proposed framework, we conducted an empirical study at the Port of Los Angeles and Port of Long Beach. Specifically, we aimed to fulfill 5% of the daily 20-foot equivalent unit containers using electric drayage trucks. Our model identified the optimal number of electric trucks, charging stations, and truck schedules required to meet the container throughput requirement. We also analyzed the cost per container as a function of daily throughput level for various scenarios. Our findings provide insights on how to determine charger supply based on daily throughputs at ports, and how to choose the appropriate ratios of electric trucks and battery sizes in the truck fleet under different throughput and electric price cases.