Electric buses (EBs) have been implemented worldwide and exhibited great potential for air pollution reduction and traffic noise control. In regular charging scenarios, the deployment of charging facilities and the operational scheduling of the transit system is crucial to bus transit system management. In this paper, we proposed a joint optimization model of regular charging electric bus transit network schedule and stationary charger deployment considering partial charging policy and time-of-use electricity prices. The objective of the model is to minimize the total investment cost of the transit system including the capital and maintenance cost of EBs and chargers, the power consumption cost, and time-related in-service cost. A solving procedure based on the improved adaptive genetic algorithm (AGA) is further designed and a transit network at inner Anting Town, Shanghai, with 8 individual bus routes and 867 daily service trips is adopted for the model validation. The validation results illustrated that the methodology considering the partial charging policy can arrange the charging schedule adaptive to the time-of-use electricity prices. Compared with the benchmark of single line separate scheduling, the proposed model can yield 3 million RMB investment saving by highly utilizing EBs and battery chargers.

中文翻译：

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考虑部分充电政策和分时电价的联合优化定期充电电动公交网络时间表和固定充电器部署

电动巴士（EB）已在全球范围内实施，并且在减少空气污染和控制交通噪音方面显示出巨大潜力。在常规收费方案中，收费设施的部署和公交系统的运行调度对于公交系统的管理至关重要。在本文中，我们提出了基于部分充电策略和分时电价的常规充电电动公交运输网络调度和固定充电器部署的联合优化模型。该模型的目的是最大程度地减少运输系统的总投资成本，包括EB和充电器的资本和维护成本，功耗成本以及与时间相关的服务成本。进一步设计了基于改进的自适应遗传算法（AGA）的求解程序，并采用上海市内安亭镇的公交网络，该公交网络具有8条单独的公交路线和867条日常服务行程，用于模型验证。验证结果表明，考虑部分充电策略的方法可以根据使用时间的电价安排充电时间表。与单线单独调度的基准相比，该模型通过充分利用电子束和电池充电器可以节省300万元人民币的投资。验证结果表明，考虑部分充电策略的方法可以根据使用时间的电价安排充电时间表。与单线单独调度的基准相比，该模型通过充分利用电子束和电池充电器可以节省300万元人民币的投资。验证结果表明，考虑部分充电策略的方法可以根据使用时间的电价安排充电时间表。与单线单独调度的基准相比，该模型通过充分利用电子束和电池充电器可以节省300万元人民币的投资。