计及路-网-车交互作用的电动汽车充电实时优化调度

大量电动汽车（electric vehicle, EV）无引导地自由充电会对城市交通系统和配电系统的运行带来负面影响, 而EV充电负荷的时空分布又与城市交通系统和配电系统密切相关。因此, 需在综合考虑城市交通系统、配电系统和EV交互作用的基础上, 研究EV的充电调度与控制。在此背景下, 首先提出一种计及路-网-车交互特性的电气化交通协同系统架构。接着, 建立基于出行链追踪的微观交通配流模型, 模拟EV用户的驾驶行为、位置分布、荷电状态、充电需求等实时信息。然后, 提出一种选择充电站和导航策略, 并构建兼顾配电系统安全和用户充电等待成本的双层实时优化调度模型, 以确定各充电站内EV的具体充电方案。最后, 采用包括某地区交通系统和修改的IEEE 33节点配电系统的集成算例系统, 对所发展的模型与方法进行说明。

Real-time Optimal Charging Scheduling for Electric Vehicles Considering Interactions Among Traffic Network,Distribution System and Electric Vehicles#br#

Potential applications of massive electric vehicles （EVs） may have negative impacts on the operation of the concerned urban traffic system and distribution system. Meanwhile, the temporal and spatial distribution of the EV charging load is closely related to the urban traffic system and distribution system. Therefore, the charging scheduling and control of EVs taking into account the interactions among the urban traffic system, distribution system and EVs, are important issues to be addressed. Given this background, a framework of an electrified transportation coordinated system considering the interactions in the traffic-distribution-vehicle framework is first proposed. A microscopic traffic flow model based on trip chain is next established to simulate the traveling behavior, temporal and spatial distribution, charging state and charging demand of EV drivers. A strategy for selecting the charging station and navigation is then proposed. Further, a bi-level real-time optimal scheduling model is presented to determine the optimum charging schemes of EVs in each charging station, with the security of the distribution system and charging waiting cost of EV drivers taken into consideration. Finally, an integrated sample system including a regional traffic system and a modified IEEE 33-node distribution system is employed to demonstrate the presented model and method.