基于用户出行模拟的电动汽车快充站负荷预测及其优化调度

电动汽车作为一种新型交通工具,其充放电优化问题得到越来越广泛的关注。论文提出一种基于用户出行模拟的电动汽车光储充一体式直流快充站优化调度方案。首先结合用户出行链概念,基于城市道路网络和改进的路阻函数模型,运用实时路径搜索算法和基于模糊理论的用户充电方式选择方法对一天内城市电动汽车充电负荷的时空分布进行预测;然后以预测结果为基础,以用户"充电贴合度"指标最大的原则将区域充电负荷落实到建设在特定节点处的充电站,接着以站内综合运行成本最小为目标,在满足设备功率、用户出行需求和储能电池状态等约束的条件下,构建优化调度模型。最后将优化方案与仅需满足设备功率平衡且电动汽车用户以额定功率随到随充的常规调度方案进行比较,结果显示,论文所提优化调度方案能够较大限度地降低充电站的运行成本,具有推广应用价值。

Charging Load Prediction and Optimized Scheduling of Electric Vehicle Quick Charging Station According to User Travel Simulation

As a new kind of green means of transportation, electric vehicle has drawn wide attention in the society. This paper presents an optimized scheduling scheme of integrated DC quick charging station for EV according to user travel simulation. Firstly, combining with the concept of user trip-chain, on the basis of the urban road network and the improved road resistance function model, real-time path search algorithm and user charging manner selection method based on fuzzy theory are used to predict the spatial and temporal distribution of charging load of urban EV within a day. Then on the basis of the prediction results, with the principle that the biggest user "charging joint degree" regional charging load will be implemented to construct charging stations in a specific node. In order to minimize the integrated operation cost of the station, the optimal scheduling model is constructed under the constraints of equipment power, user trip demand and battery status. Finally, the optimization scheme is compared with the conventional scheduling scheme that only needs to meet the power balance of the equipment and the EV user needs to charge at rated power on the spot. The results show that the optimized scheduling scheme proposed in this paper can greatly reduce the operating cost of charging stations and has the value of popularization and application.