摘要
文中提出了考虑电网稳定性的电动汽车充电策略优化方法,综合充电策略包括随机充电、里程焦虑充电和电价引导的充电策略。建立基于路网的蒙特卡洛模拟电动汽车充电负荷模型,以电网均方差和最小以及节省用户充电成本为多目标函数。采用人工蜂群算法搜寻综合充电策略的权重,在考虑电网稳定性的前提下选择电动汽车充电概率值大于可充电阈值的时刻进行充电。仿真结果表明,考虑电网稳定性的电动汽车充电策略优化比无序充电策略在充电费用方面节省了35.6%、峰谷差降低了11.05%。因此该充电策略能有效地提高电网稳定性和电动汽车用户的满意度。
An optimization of EV charging strategy considering the stability of the power grid is proposed.The comprehensive charging strategies include random charging,range anxiety charging and electricity price guidance.A Monte Carlo simulation of EV charging load model based on road network is established.The minimization of the mean squared deviation sum of the power grid and saving of the charging cost of users are taken as the multi⁃objective function.The artificial bee colony(ABC)algorithm is used to search for the weight of the comprehensive charging strategy.The moment when the charging probability value of the EV is greater than the chargeable threshold value is selected for charging under the premise of considering the stability of the power grid.The simulation results show that,in comparison with the disorderly charging strategy,the charging costs of the optimization of the EV charging strategy considering the stability of the power grid is saved by 35.6%,and its peak valley difference is reduced by 11.05%.Therefore,the proposed charging strategy can effectively improve the stability of the power grid and the satisfaction of EV users.
作者
石庆升
师凌云
赵非凡
SHI Qingsheng;SHI Lingyun;ZHAO Feifan(Henan University of Technology,Zhengzhou 450000,China)
出处
《现代电子技术》
2022年第13期118-123,共6页
Modern Electronics Technique
基金
国家自然科学基金资助项目(61403124)
2019年度河南省高等学校青年骨干教师培养计划(2019GGJS095)
关键词
电网稳定性
综合充电策略
人工蜂群
蒙特卡洛
路网
多目标函数
电价引导
无序充电
里程焦虑
power grid stability
comprehensive charging strategy
ABC
Monte Carlo
road network
multi⁃objective function
electricity price guidance
disorderly charging
range anxiety
