基于山地城市电动汽车负荷特性的充电设施规划

Charging Facility Planning Based on Load Characteristics of Electric Vehicles in Mountain Cities

针对山地城市电动汽车充电站的规划需求,研究了山地城市道路特性,改进了充电负荷预测与充电站规划方法,主要包括:研究了山地城市道路空间特性,建立了电动汽车单车耗电模型;分析了山地城市单车耗电特性对充电负荷时空分布的影响,结合改进Floyd最短路径算法建立了群体充电负荷预测模型;考虑了充电负荷时空分布受充电站选址的影响,提出负荷预测与充电站规划迭代计算方法;以充电负荷时间维度波动更小与空间分布更均衡为目标,提出了新型山地城市充电站规划方法。通过遗传算法Matlab仿真求解表明,上述建模方法能够实现对山地城市充电站的更合理规划:一方面,显著降低电动汽车充电负荷波动;另一方面,使得各站充电负荷更加均衡。

In order to meet the needs of planning electric vehicle charging stations in mountainous cities,the characteristics of roads in mountainous cities are studied in this paper to improve the methods charging load forecasting and charging station planning.The main contributions of this study are as follows.Firstly,the spatial characteristics of roads in mountainous cities were explored,and a single-vehicle power consumption model was established for electric vehicles.Secondly,an analysis was conducted as to the impact caused by the power consumption characteristics of single vehicles in mountainous cities on the temporal and spatial distributions of charging load.Also,the improved Floyd shortest path algorithm was applied to establish a group charging load prediction model.Thirdly,an iterative calculation method is developed for load forecasting and charging station planning by taking into account the influence exerted by the temporal and spatial distributions of charging load on the location of charging stations.Lastly,a novel model of charging station planning in mountainous cities is proposed to reduce the temporal fluctuation of charging load and further balance its spatial distribution.According to the solution obtained through genetic algorithm MATLAB simulation,the above modeling method is capable to achieve a more reasonable planning of charging stations in mountainous cities.On the one hand,it significantly reduces the fluctuation of charging load for electric vehicles.On the other hand,it makes the charging load more balanced between different charging stations.