交直流配电网中电动汽车充换储一体站规划

首先,以马尔可夫和速度-流量模型对快充车辆和电动公交进行时空负荷预测,结合快充站、换电站和梯级储能站的充放电功率构建充换储一体站(CSSIS)模型.然后,建立含CSSIS的交直流潮流模型,构建计及电动汽车到站行驶时间、排队等待时间和交直流配电网电压偏差的多目标选址模型,采用动态权重结合二进制遗传算法进行求解.其次,采用Voronoi图划分CSSIS服务范围,以综合投资成本最小为目标建立优化模型来确定最终站址,通过排队论优化充电机数量,以系统节点电压和CSSIS功率平衡为约束来确定站内设备容量.最后,通过算例验证了所提模型和方法的有效性.

Planning of Electric Vehicle Charging-Swapping-Storage Integrated Station in AC/DC Distribution Network

First, this paper uses the Markov and velocity-flow models to predict the space-time load of fast-charging vehicles and electric buses. The charging and discharging power of fast-charging stations, switching stations and cascade energy storage stations are combined to construct the charging-swapping-storage integrated station (CSSIS) model. Then, a power flow model of AC/DC with CSSIS is established, and a multi-objective siting model that takes into account travel time of electric vehicles (EVs) to the station, queuing time and voltage deviation of AC/DC distribution networks is constructed. The dynamic weights combined with binary genetic algorithm are used to solve the model. Further, the Voronoi diagram is used to delineate the CSSIS service area. An optimization model is established to determine the final station site with the objective of minimizing the comprehensive investment cost. The number of chargers is optimized by the queuing theory, and the system bus voltage and CSSIS power balance are used as constraints to determine the station equipment capacity. Finally, the effectiveness of the proposed model and method is verified by examples.