基于电动汽车两阶段充电站分配的聚合商定价方法

Aggregator pricing methodology based on two-stage charging station allocation for electric vehicles

随着“双碳”目标的提出,电动汽车数量与日俱增,充电桩数量不足导致电动汽车充电排队时间增加、聚合商定价等问题日益凸显。针对上述问题,提出电动汽车两阶段充电站分配的聚合商定价方法。首先将聚合商与电动汽车签约模式分为完全调度、奖罚机制调度和自由调度三类,考虑外部因素对电动汽车能耗影响并建立路网模型。然后采用改进A^(*)算法求解最短路径,在A^(*)算法的估价函数中引入时间因子。同时根据交通能耗、不间断行驶时间、红绿灯等待时间等因素改进估价函数。聚合商根据电动汽车的充放电需求、库伦定律得到充电站对电动汽车的吸引力。再建立电网-聚合商-电动汽车供应链,并进行两阶段的合理定价及充电站分配。最后通过算例验证聚合商定价方法可以显著提高调峰效率和聚合商利润,减少电动汽车排队时间及交通能耗。

With the introduction of the"dual-carbon"objectives,the number of electric vehicles is increasing day by day.The insufficient number of charging piles has led to extended queuing times for electric vehicles,as well as increasingly prominent pricing issues for aggregators.To address these challenges,an aggregator pricing methodology based on two-stage charging station allocation for electric vehicles is proposed.First,the contract signing modes between aggregator and electric vehicles are categorized into three types:complete dispatching,reward and punishment mechanism dispatching,and free dispatching.The impact of external factors on electric vehicle energy consumption is taken into account,and a road network model is established.Then,an enhanced A^(*)algorithm is employed to determine the shortest path,and a time factor is incorporated into the evaluation function to enhance path selection.Simultaneously,the evaluation function is refined to include factors such as traffic energy consumption,uninterrupted travel time,and traffic light waiting time.The aggregator obtains the attractiveness of charging stations to electric vehicles according to the charging and discharging demand of electric vehicles and Coulomb's law.Subsequently,a grid-aggregator-electric vehicle supply chain is established to facilitate a two-stage rational pricing and charging station allocation process.Finally,numerical examples are used to validate that the proposed aggregator pricing method significantly improves peak shaving efficiency,increases aggregator profits,and reduces both electric vehicle queuing time and transportation energy consumption.