基于动态分时电价引导的电动汽车需求侧响应  

Demand response of electric vehicle based on dynamic time-to-use electricity price

作　　者：叶文浩 陈耀红 颜勤 涂晓帆 YE Wenhao;CHEN Yaohong;YAN Qin;TU Xiaofan(State Grid Hunan Electric Power Co.,Ltd.,Changsha 410000,China;School of Electrical&Information Engineering,Changsha University of Science&Technology,Changsha 410114,China)

机构地区：[1]国网湖南电力有限公司,湖南长沙410000 [2]长沙理工大学电气与信息工程学院,湖南长沙410114

出　　处：《电力科学与技术学报》2024年第4期138-145,共8页Journal of Electric Power Science And Technology

基　　金：湖南省战略性新兴产业科技攻关与重大科技成果转化项目(2018GK4002);国网湖南省电力有限公司管理咨询项目(SGHN0000ZHWT2200128)。

摘　　要：为激励电动汽车(electric vehicles,EVs)参与需求侧响应以减小电网负荷峰谷差,同时提高电动汽车用电经济性,首先,利用蒙特卡罗法模拟出电动汽车无序充电负荷,再根据电动汽车是否受电网调控或者受价格信号引导,将电动汽车分为3类进行处理;然后,以电网峰谷差均方值最小和用户充放电费用最小为目标,搭建基于电价需求弹性矩阵的动态分时电价(time-of-use,TOU)需求响应模型;最后,根据湖南某地区历史负荷数据对一天的电价进行分段,再通过仿真分析,验证考虑实时负荷反馈的动态分时电价可以有效地应对负荷波动,并且对于减小峰谷差和降低用户用电成本的效果更明显。To incentivize electric vehicles(EVs)to participate in demand-side response to reduce the peak-to-valley difference in grid load and enhance the economic viability of EV electricity usage,the Monte Carlo method is used to simulate the unordered charging load of EVs.EVs are then categorized into three types based on whether they are regulated by the grid or guided by price signals.Subsequently,a dynamic time-of-use(TOU)pricing demand response model is established on the basis of the electricity price demand elasticity matrix,with the objectives of minimizing the mean square value of the grid's peak-to-valley difference and minimizing user charging and discharging costs.Using historical load data from a region in Hunan and segmenting the electricity prices for a day,simulation analysis is conducted to verify that dynamic TOU pricing considering real-time load feedback can effectively manage load fluctuations,and it has a more pronounced effect on reducing the peak-to-valley difference and lowering user electricity costs.

关 键 词：动态分时电价 价格需求弹性矩阵 电动汽车 需求响应 蒙特卡罗法 

分 类 号：TM73[电气工程—电力系统及自动化]