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考虑路网-电网交互和用户心理的电动汽车充电负荷预测
作者:
作者单位:

武汉大学电气与自动化学院,湖北省 武汉市 430072

摘要:

文中提出了一种考虑路网-电网信息交互和用户心理的电动汽车充电负荷预测框架。首先,利用出行链和原点-终点(OD)矩阵得到电动汽车出行目的地;然后,考虑行驶、排队时间和充电电价,提出基于后悔理论的充电站选择模型;接着,基于跟驰模型对车辆在路网中的行驶过程进行微观交通分析,建立基于电价驱动的路网-电网交互式负荷预测框架;最后,采用蒙特卡洛方法模拟电动汽车的出行和充电情况,以预测电动汽车充电负荷时空分布。通过在中国北京市三环路网和相应电网上的仿真,验证了所提电动汽车充电负荷预测框架的有效性。仿真结果也表明路网和电网通过电价相互作用,使得电动私家车和出租车的充电负荷在时间与空间上分布差异明显。

关键词:

基金项目:

国家重点研发计划资助项目(2017YFB0902900);教育部人文社会科学研究规划项目(17YJCZH212);国家自然科学基金资助项目(51977154)。

通信作者:

杨军(1977—),男,通信作者,博士,教授,博士生导师,主要研究方向:电动汽车与电网互动、电网安全运行等。E-mail:JYang@whu.edu.cn

作者简介:

龙雪梅(1996—),女,硕士研究生,主要研究方向:电动汽车与交通路网。E-mail:2014302540112@whu.edu.cn
吴赋章(1992—),男,博士研究生,主要研究方向:新能源接入、电动汽车运行调度。E-mail:wufuzhangwfz@163.com


Prediction of Electric Vehicle Charging Load Considering Interaction Between Road Network and Power Grid and User’s Psychology
Author:
Affiliation:

School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China

Abstract:

A prediction framework of electric vehicle (EV) charging load is proposed, which considers user’s psychology and information interaction between road network and power grid. Firstly, the destination of EV is obtained through trip chain and origin-destination (OD) matrix. Secondly, considering driving time, queuing time and charging price, a model of choosing charging station based on regret theory is proposed. Thirdly, based on the following model, the microscopic traffic analysis on vehicle driving process in the road network is carried out, and the framework of charging load prediction considering the interaction between road network and power grid driven by charging price is established. Finally, Monte Carlo method is used to simulate the travelling and charging situations of EVs, so as to predict the time-space distribution of EV charging load. Through the simulation on the Third Ring Road Network in Beijing, China and the corresponding power grid, the effectiveness of the proposed EV charging load prediction framework is verified. The simulation results also show that the interaction between road network and power grid through charging price make the charging load distribution of electric private cars and taxis significantly different in time and space.

Keywords:

Foundation:
This work is supported by National Key R&D Program of China (No. 2017YFB0902900), Projects of Humanities and Social Sciences of the Ministry of Education (No. 17YJCZH212) and National Natural Science Foundation of China (No. 51977154).
引用本文
[1]龙雪梅,杨军,吴赋章,等.考虑路网-电网交互和用户心理的电动汽车充电负荷预测[J].电力系统自动化,2020,44(14):86-93. DOI:10.7500/AEPS20191011008.
LONG Xuemei, YANG Jun, WU Fuzhang, et al. Prediction of Electric Vehicle Charging Load Considering Interaction Between Road Network and Power Grid and User’s Psychology[J]. Automation of Electric Power Systems, 2020, 44(14):86-93. DOI:10.7500/AEPS20191011008.
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  • 收稿日期:2019-10-11
  • 最后修改日期:2020-03-24
  • 录用日期:
  • 在线发布日期: 2020-07-20
  • 出版日期:
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