利用实时交通信息感知的电动汽车路径选择和充电导航策略

适当选择电动汽车(EV)路径并优化充电导航,有助于提高用户出行效率及缓解大量EV同时充电对配电系统安全运行的影响。在此背景下,提出借助群智感知技术来获得实时交通路况和充电站服务信息,并在此基础上利用矩阵分解得到交通信息矩阵。之后,在考虑路径选择、到达时间、电池容量及充放电状态互斥约束的前提下,构建了分时电价机制下以用户出行总成本最小为目标的EV路径选择和充电导航优化模型。以某市中心25km×25km区域内所包含的4座快速充电站连接到IEEE 33节点配电系统为例来说明所述方法的基本特征,并针对考虑和不考虑实时交通信息情形,分析了参与群智感知的EV数量对用户出行路径及EV充放电对配电系统的影响。

Route Selection and Charging Navigation Strategy for Electric Vehicles Employing Real-time Traffic Information Perception

A route selection and charging navigation optimization model for electric vehicles(EVs)is presented for reducing traveling costs of EV users and improving the security of the distribution system concerned. With the aid of crowd sensing, a traffic information matrix acquisition method based on the matrix factorization technique is first addressed. The formulated objective of the presented model is to minimize the sum of driving and waiting costs, fast and regular EV charging costs based on the time of use(TOU)price mechanism, subject to a variety of technical constraints such as path selections, time, battery capacities, and charging or discharging state mutual exclusion constraints. A sample system is built by connecting four EV charging stations to the IEEE 33-bus distribution system, and the four EV charging stations are within a city center within a 25 km×25 km zone, and served for demonstrating the essential feature of the presented method. With respect to the situations with and without real-time traffic information, the impacts of the EV quantities participating in crowd sensing on the travel route and charging/discharging of EVs, as well as on the distribution system are also analyzed.