基于分层优化的电动汽车有序充电策略*

doi:10.11985/2021.03.019

电气工程学报 ›› 2021, Vol. 16 ›› Issue (3): 137-144.doi: 10.11985/2021.03.019

• 新能源发电与电能存储 • 上一篇下一篇

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基于分层优化的电动汽车有序充电策略^*

冯仕杰¹^,²(), 刘韬¹(), 潘萨¹^,³, 陈正浩¹, 王青¹()

1.南昌大学信息工程学院南昌 330031
2.国网江西省电力有限公司景德镇供电分公司景德镇 333000
3.国网重庆市电力有限公司万州供电公司重庆 404155

收稿日期:2020-12-24 修回日期:2021-03-16 出版日期:2021-09-25 发布日期:2021-10-29
通讯作者: 王青 E-mail:2191635115@qq.com;tliu@ncu.edu.cn;wangq@ncu.edu.cn
作者简介:* 王青,男,1990年生,博士,讲师。主要研究方向为新能源发电、电动汽车驱动系统等。E-mail： wangq@ncu.edu.cn
冯仕杰,男,1997年生,硕士研究生。主要研究方向为新能源系统稳定与控制。E-mail： 2191635115@qq.com
刘韬,男,1978年生,硕士,讲师。主要研究方向为新能源发电。E-mail： tliu@ncu.edu.cn
基金资助:
* 国家自然科学基金(51967013);南昌大学研究生创新专项资金立项(CX2019074)

Coordinated Charging Strategy for Electric Vehicles Based on Hierarchical Optimization

FENG Shijie¹^,²(), LIU Tao¹(), PAN Sa¹^,³, CHEN Zhenghao¹, WANG Qing¹()

1. School of Information Engineering, Nanchang University, Nanchang 330031
2. Jingdezhen Power Supply Company, State Grid Jiangxi Electric Power Company, Jingdezhen 333000
3. Wanzhou Power Supply Company, State Grid Chongqing Electric Power Company, Chongqing 404155

Received:2020-12-24 Revised:2021-03-16 Online:2021-09-25 Published:2021-10-29
Contact: WANG Qing E-mail:2191635115@qq.com;tliu@ncu.edu.cn;wangq@ncu.edu.cn

摘要/Abstract

摘要：

针对电动汽车集中式充电优化方式计算量大、通信要求高的问题,提出一种基于分层优化的电动汽车有序充电策略。以用户充电费用最少、配电网负荷方差最小为目标建立了电动汽车双层充电优化模型;针对粒子群算法收敛精度差、易陷入局部最优的问题,利用Tent混沌映射初始化粒子种群,引入动态权重更改粒子速度的更新方式,加入Levy飞行策略扰动粒子种群;运用改进的粒子群算法优化电动汽车的充电起始时间。结合算例,分析了不同用户响应度、不同充电数量对优化结果的影响,验证了所提策略的有效性。

关键词: 电动汽车, 分层优化, 充电费用, 负荷方差, 改进粒子群算法

Abstract:

An orderly charging strategy is proposed for electric vehicles based on hierarchical optimization to reduce calculation and communication requirements of electric vehicles centralized control. Firstly, a two level optimization model for electric vehicles charging is established with the minimum total charging cost of users and the minimum variance for the total load of the distribution network. Secondly, aiming at the problem that the particle swarm algorithm is easy to fall into local optimality, the Tent chaotic map is used to initialize the particle population, the dynamic weight is introduced to change the updating mode of particle velocity, and Levy flight strategy is added to disturb the particle population. Finally, the improved particle swarm algorithm is used to optimize the charging start time of electric vehicles. Combined with an example, the influence of different user responsiveness and different charging quantities on the optimization result is compared to verify the effectiveness of the proposed strategy.

Key words: Electric vehicle, hierarchical optimization, charging cost, load variance, improved particle swarm algorithm

中图分类号:

TM73

冯仕杰, 刘韬, 潘萨, 陈正浩, 王青. 基于分层优化的电动汽车有序充电策略^*[J]. 电气工程学报, 2021, 16(3): 137-144.

FENG Shijie, LIU Tao, PAN Sa, CHEN Zhenghao, WANG Qing. Coordinated Charging Strategy for Electric Vehicles Based on Hierarchical Optimization[J]. Journal of Electrical Engineering, 2021, 16(3): 137-144.

图/表 8

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时段	电价/[元/(kW·h)]
00:00—08:00	0.36
08:00—21:00	0.56
21:00—24:00	0.36

参与模式	峰谷差/kW	方差/kW²	总充电费用/元
常规负荷	1 068.5	105 194.1	—
r=0%	1 296.5	137 995.0	919.1
r=50%	944.8	85 028.6	787.1
r=75%	859.6	70 896.1	729.2
r=100%	748.2	55 651.6	666.8

充电数量/辆	峰谷差/kW	方差/kW²	总充电费用/元
200	916.6	82 612.3	478.0
300	859.6	70 896.1	729.2
400	805.5	60 204.0	1 020.8

基于分层优化的电动汽车有序充电策略^*

Coordinated Charging Strategy for Electric Vehicles Based on Hierarchical Optimization

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