基于动态实时电价的电动汽车集群分层优化调度

Hierarchical Real-time Scheduling Optimization for Electric Vehicle Cluster Based on Dynamic Real-time Electricity Price

针对大量电动汽车接入电网后的无序充放电对电网造成的不利影响,提出了一种基于实时电价的双层优化调度模型,根据接入电动汽车的可充放电时间段,将其划分为若干个集群,在保证配电网经济安全运行的同时,满足车主充电需求。该调度模型上层以负荷曲线方差及实时电价下用户的充放电总成本最小为目标,采用粒子群算法求解得到集群的实时最优充放电功率,并将集群的电动汽车充放电负荷与电价联动调整;下层引入充放电优先级指数,利用能量缓冲一致性算法,制定出集群内的各辆电动汽车的实时充放电策略。以典型的区域配电网负荷数据为例,通过仿真验证了所搭建的集群优化模型和求解算法的实用性和有效性。

In view of the large number of electric vehicles connected to the electricity grid disordered charge and discharge of the adverse impact of the power grid,this paper proposes a bi-level optimization scheduling model based on real-time electricity price,according to the access to the electric car can charge and discharge time,can be divided into several clusters,in ensuring economic and safe operation of the distribution network at the same time,meet the demand of the owner charging.The upper part of the scheduling model takes the variance of load curve and the total charge and discharge cost of users under the real-time electricity price as the target,USES the particle swarm optimization algorithm to obtain the real-time optimal charge and discharge power of the cluster,and adjusts the charge and discharge load of the cluster electric vehicles in tandem with the electricity price.In the lower layer,charging and discharging priority index is introduced,and the real-time charging and discharging strategy for each EV in the cluster is developed by using the energy buffer consistency algorithm.Taking typical load data of regional distribution network as an example,the validity and practicability of the cluster optimization model and algorithm are verified by simulation.