Title: Integrated Charging Scheduling and Operational Control for an Electric Bus Network Show Chinese title

Title: 电动公交网络的集成充电调度与运行控制

Abstract: The last few years have seen the massive deployment of electric buses in many existing transit networks. However, the planning and operation of an electric bus system differ from that of a bus system with conventional vehicles, and some key problems have not yet been studied in the literature. In this work, we address the integrated operational control and charging scheduling problem for a network of electric buses with a limited opportunity charging capacity. We propose a hierarchical control framework to solve this problem, where the charging and operational decisions are taken jointly by solving a mixed-integer linear program in the high-level control layer. Since this optimization problem might become very large as more bus lines are considered, we propose to apply Lagrangian relaxation in such a way as to exploit the structure of the problem and enable a decomposition into independent subproblems. A local search heuristic is then deployed in order to generate good feasible solutions to the original problem. This entire Lagrangian heuristic procedure is shown to scale much better on transit networks with an increasing number of bus lines than trying to solve the original problem with an off-the-shelf solver. The proposed procedure is then tested in the high-fidelity microscopic traffic environment Vissim on a bus network constructed from an openly available dataset of the city of Chicago. The results show the benefits of combining the charging scheduling decisions together with the real-time operational control of the vehicles as the proposed control framework manages to achieve both a better level of service and lower charging costs over control baselines with predetermined charging schedules. Show Chinese abstract

Abstract: 过去几年，许多现有的公共交通网络都大规模部署了电动公交车。 然而，电动公交车系统的规划和运营与传统车辆的系统有所不同，文献中尚未研究一些关键问题。 在本工作中，我们解决了具有有限机会充电能力的电动公交车网络的集成运行控制和充电调度问题。 我们提出了一种分层控制框架来解决这个问题，在高层控制层中通过求解一个混合整数线性规划问题来共同做出充电和运营决策。 由于随着考虑的公交线路增多，这个优化问题可能会变得非常大，因此我们提出了一种应用拉格朗日松弛的方法，以利用问题的结构并将其分解为独立的子问题。 然后部署一种局部搜索启发式方法，以生成原始问题的良好可行解。 整个拉格朗日启发式过程被证明在具有越来越多公交线路的公共交通网络中，比尝试使用现成求解器求解原始问题要扩展性更好。 然后在高保真微观交通环境Vissim中对从芝加哥市公开数据集构建的公交网络进行了测试。 结果表明，将充电调度决策与车辆的实时运行控制相结合的好处，因为所提出的控制框架能够在服务级别和充电成本方面优于具有预定义充电计划的控制基线。