基于分时电价的电动汽车多目标优化充电策略  

Multi-objective optimization charging strategy for plug-in electric vehicles based on time-of-use price

作　　者：佟晶晶[1] 温俊强[1] 王丹[1] 张建华[1] 刘文霞[1] 

机构地区：[1]华北电力大学新能源电力系统国家重点实验室,北京102206

出　　处：《电力系统保护与控制》2016年第1期17-23,共7页Power System Protection and Control

基　　金：国家高技术研究发展计划(863计划)(2011AA05A109)~~

摘　　要：随着电动汽车渗透率的增加,电动汽车的无序充电会给区域配电网的运行带来很大压力。为了减小电动汽车负荷对电网的影响,提出了一种电动汽车智能充电的调度策略。在分时电价的基础上,将充电成本最小化和负荷方差最小化作为目标函数,考虑了充电机最大充电功率限制等约束条件,建立了电动汽车集中充电的多目标优化调度模型。采用了非支配排序遗传算法(NSGA-II)对优化模型进行求解,通过Matlab算例的计算结果验证了该策略的可行性和有效性。分析了不同数量电动汽车和不同时间窗口的取值对优化结果的影响,并据此给出了相关建议。With the increase of plug-in electric vehicles（PEV）, the uncontrolled charging of them may pose a wide pressure on the operation of regional distribution network. In order to reduce adverse impacts of PEVs, an intelligent charging strategy for a cluster of PEVs is proposed. Considering several constraints such as the charger＇s maximum charging power, a multi-objective optimization scheduling model is proposed with the objectives of minimizing the total charging cost and minimizing load variance basing on time-of-use（TOU） price. The Non-dominated Sorting Genetic Algorithm II（NSGA-II） is adopted to solve the optimization problem, and the MATLAB calculation results prove the feasibility and effectiveness of the proposed strategy. Factors such as the number of PEVs, the TOU price and the length of time-window are also analyzed to further study PEV charging load＇s characteristics. Some operation advice is also given based on the analysis above.

关 键 词：电动汽车 充电策略 分时电价 多目标优化 影响分析 

分 类 号：TM73[电气工程—电力系统及自动化] U469.72[机械工程—车辆工程]