考虑电动汽车需求响应的微电网预测控制研究  

Research on predictive control of microgrid considering electric vehicle demand response

作　　者：史倩芸 吴传申 高山[1,2] SHI Qianyun;WU Chuanshen;GAO Shan(School of Electrical Engineering,Southeast University,Nanjing 210096,China;Key Laboratory of Smart Grid Technology and Equipment,Jiangsu Province,Nanjing 210096,China)

机构地区：[1]东南大学电气工程学院,南京210096 [2]江苏省智能电网技术与装备重点实验室,南京210096

出　　处：《电力需求侧管理》2022年第2期1-6,13,共7页Power Demand Side Management

基　　金：国家电网有限公司科技项目(5418-202199282A-0-0-00)。

摘　　要：电动汽车数量的日益增长使得微电网内的不确定性不断增加。针对集群电动汽车到达时刻的不确定性以及到达时刻剩余电量的不确定性,建立了一个双层模型预测控制策略对接入微电网的电动汽车进行最优充放电管理,以降低主网与微电网之间的交换功率。在上层集群电动汽车充放电优化中,考虑下层单个电动汽车的充电需求,并根据充电紧迫性将其划分为参与调控的电动汽车和不参与调控的电动汽车。仿真结果表明,所提方法在集群电动汽车充放电管理上具有更好的表现,且更加贴近现实情况,更易满足居民需求。The increasing number of electric vehicles(EVs)makes the uncertainty in the microgrid continue to increase. Aiming at the uncertainty of the arrival time of aggregated EVs and the remaining power at the arrival time, a two-layer model predictive control strategy is established to perform optimal charging and discharging management for EVs connected to the microgrid to minimize the power exchange between the grid and the microgrid. In the optimization of the charging and discharging of the upper-level aggregated electric vehicles, the charging demand of the lower-level individual electric vehicles is considered. According to the urgency of the user’s charging behavior, EVs that have arrived are divided into EVs participating in optimization and EVs without participating in optimization. The simulation results show that the proposed method has better performance in the charge and discharge management of aggregated EVs. In addition, it is closer to the reality and easier to meet the needs of residents.

关 键 词：微电网 电动汽车 预测控制 滚动优化 需求响应 

分 类 号：TM714[电气工程—电力系统及自动化] TK018[动力工程及工程热物理]