电动汽车充放电优化管理分析

doi:10.16180/j.cnki.issn1007-7820.2019.06.013

电子科技 ›› 2019, Vol. 32 ›› Issue (6): 64-69.doi: 10.16180/j.cnki.issn1007-7820.2019.06.013

电动汽车充放电优化管理分析

单知非¹,孙宇轩¹,张翔¹,陈强²,郑之艺¹

1. 三峡大学电气与新能源学院,湖北宜昌 443002
2. 国网新疆电力有限公司阿勒泰供电公司,新疆阿勒泰 836500

收稿日期:2018-07-06 出版日期:2019-06-15 发布日期:2019-07-01
作者简介:单知非(1995-),男,硕士研究生。研究方向:电动汽车优化调度。
基金资助:
国家级大学生创新创业训练计划项目(201811075003S)

Research on Optimization Management of Electric Vehicle Charging and Discharging

SHAN Zhifei¹,SUN Yuxuan¹,ZHANG Xiang¹,CHEN Qiang²,ZHENG Zhiyi¹

1. School of Electrical Engineering & New Energy,China Three Gorges University,Yichang 443002,China
2. Altay Power Supply Company, State Grid Electric Power Co. Ltd. Xinjiang Uygur Autonomous Region,Altay 836500,China

Received:2018-07-06 Online:2019-06-15 Published:2019-07-01
Supported by:
The National Students’ Platform for Innovation and EntreprEneurship Training Program(201811075003S)

摘要/Abstract

摘要：

随着电动汽车普及保有量逐年上升,电动汽车无序充放电将会对电力系统产生极大的冲击。文中首先对影响充电负荷的各个因素进行分析,建立数据特征函数,并通过最小二乘法拟合得出电动汽车的函数模型。然后,根据数学模型特征,对多个电动汽车的负荷进行规划,建立多目标优化函数,并使用蒙特卡洛算法构造概率过程从已知概率分布中抽样建立对电动汽车充电负荷曲线。通过仿真验证,证明提出的模型能通过少量样本精确的模拟大规模电动汽车接入状况。文中对电动汽车充放电优化问题进行的改良,能有效减少设备投资、降低无序充电的峰谷差,维护系统稳定运行。

关键词: 电动汽车, 数据拟合, 多目标优化, 蒙特卡洛算法, 优化管理, 充放电模型

Abstract:

With the increasing popularity of electric vehicles, the disordered charging and discharging of electric vehicles will have a great impact on the power system. Firstly, the factors affecting the charging load were analyzed, and the data feature function was established. The function model of electric vehicle had been fitted by least squares method. Secondly, according to the characteristics of the mathematical model, the load of multiple electric vehicles was planned. Then, the multi-objective optimization function was established by the Monte-Carlo algorithm used for constructing the probability process to sample the charging load curve of the electric vehicle from the known probability distribution. Finally, the simulation proved that the proposed model could accurately simulate the access situation of large-scale electric vehicles through a small number of samples. The improvement of the charging and discharging optimization problem of electric vehicles effectively reduced equipment investment, the peak-to-valley difference of disordered charging, and maintained stable operation of the system.

Key words: electric vehicle, data fitting, multi-objective optimization, Monte-Carlo algorithm, optimization management, charge and discharge model

中图分类号:

TN91

单知非,孙宇轩,张翔,陈强,郑之艺. 电动汽车充放电优化管理分析[J]. 电子科技, 2019, 32(6): 64-69.

SHAN Zhifei,SUN Yuxuan,ZHANG Xiang,CHEN Qiang,ZHENG Zhiyi. Research on Optimization Management of Electric Vehicle Charging and Discharging[J]. Electronic Science and Technology, 2019, 32(6): 64-69.

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电动汽车数量/万辆	年用电量/kWh
1	5.12×10⁷
8 000	4.10×10¹¹

电动汽车充放电优化管理分析

Research on Optimization Management of Electric Vehicle Charging and Discharging

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