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Electric Bus Scheduling Considering Limited Charging Facility Capacity for Large-Scale Operation
Electric buses (e-buses) have been increasingly introduced to urban transit systems in recent years. E-bus scheduling has become a critical problem to ensure cost-efficient transit service. To support continuous e-bus operation, charging facilities are established at the depots to provide charging service. In real-world scenarios, charging facility capacity measured by the number of chargers is always limited. To reduce charging congestions, it is critical to consider the charging facility capacity in the e-bus scheduling problem. In this study, we addressed a multidepot e-bus scheduling problem considering limited charging facility capacity and vehicle-depot constraint. A mixed-integer programming model based on discrete-event optimization method and a large neighborhood search (LNS) heuristic are proposed to solve the problem. Comprehensive numerical experiments based on the real-world operation cases in Shenzhen were conducted. The results verify the model and show that the LNS heuristic can generate near-optimal solutions for large-scale problem instances. Lack of charging facilities at the depots can lead to more e-buses charging at the peak time regarding the time-of-use tariff, resulting in increased total operational cost.
Electric Bus Scheduling Considering Limited Charging Facility Capacity for Large-Scale Operation
Electric buses (e-buses) have been increasingly introduced to urban transit systems in recent years. E-bus scheduling has become a critical problem to ensure cost-efficient transit service. To support continuous e-bus operation, charging facilities are established at the depots to provide charging service. In real-world scenarios, charging facility capacity measured by the number of chargers is always limited. To reduce charging congestions, it is critical to consider the charging facility capacity in the e-bus scheduling problem. In this study, we addressed a multidepot e-bus scheduling problem considering limited charging facility capacity and vehicle-depot constraint. A mixed-integer programming model based on discrete-event optimization method and a large neighborhood search (LNS) heuristic are proposed to solve the problem. Comprehensive numerical experiments based on the real-world operation cases in Shenzhen were conducted. The results verify the model and show that the LNS heuristic can generate near-optimal solutions for large-scale problem instances. Lack of charging facilities at the depots can lead to more e-buses charging at the peak time regarding the time-of-use tariff, resulting in increased total operational cost.
Electric Bus Scheduling Considering Limited Charging Facility Capacity for Large-Scale Operation
J. Transp. Eng., Part A: Systems
Jiang, Mengyan (Autor:in) / Zhang, Yi (Autor:in) / Zhang, Yi (Autor:in)
01.09.2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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