电气化公交网络中跨线路调度的最优车队规模

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2024-08-20 DOI:10.1109/TNSE.2024.3445915

Kianoosh Keshavarzian;Ali MoradiAmani;Mahdi Jalili

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引用次数: 0

摘要

本手稿提出了一种利用跨线路调度优化电气化公交网络车队规模的模型。电池电动公交车通常需要白天充电，这可能需要较长的闲置时间。总闲置时间越长，车队规模就越大。在这里，我们展示了通过对整个公交网络应用交叉路线调度方法，可以减少总空闲时间，从而减少车队规模。所提出的模型还能找到快速途中充电站的位置，并管理其最大所需功率。此外，该模型还能适用于具有不同巴士尺寸、电池容量和所需充电负荷的网络。我们在美国纽约市、澳大利亚墨尔本市和英国曼彻斯特市的公交车网络上验证了该模型，结果表明它能显著减少这些城市的车队规模。

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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Optimal Fleet Size for Cross-Route Dispatching in Electrified Bus Networks

This manuscript proposes a model for optimal fleet size in electrified bus networks using cross-route dispatching. Battery Electric Buses often require day-time charging, which might require long idle time. The longer total idle time results in a bigger fleet size. Here, we show that we can reduce the total idle time, and consequently the fleet size, by applying the cross-route dispatching method to the entire bus network. The proposed model can also find the location of fast en-route charging stations and manage their maximum required power. In addition, the model can adopt a network with different bus sizes, battery capacities and required charging loads. We verified the model on bus networks of New York City, USA, Melbourne, AU and Manchester, U.K., and showed that it can significantly reduce the fleet size in these cities.

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.