|本期目录/Table of Contents|

[1]李伟生,张继龙,漆建平.基于动态分时电价的电动汽车有序充放电研究[J].工业仪表与自动化装置,2017,(04):46-49.
　LI Weisheng,ZHANG Jilong,QI Jianping.A dynamic time-of-use price based order for charging and discharging of electric vehicles[J].Industrial Instrumentation & Automation,2017,(04):46-49.
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基于动态分时电价的电动汽车有序充放电研究

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2017年04期
页码:
46-49
栏目:
出版日期:
2017-08-15

文章信息/Info

Title:
A dynamic time-of-use price based order for charging and discharging of electric vehicles
文章编号:
1000-0682（2017）04-0000-00
作者:
李伟生1; 张继龙1; 漆建平3
（1. 山东省科学院 自动化研究所，济南0250014；2.兰州理工大学 电气工程与信息工程学院，兰州 730050；3.太原理工大学 机械工程学院，太原030024）
Author(s):
LI Weisheng1; ZHANG Jilong1;  QI Jianping2
(1.Institute of Automation,Shandong Academy of Science,Jianan 250050,China;2.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China;3.College of Mechanical Engineering ,Taiyuan University of Technology, Taiyuan 030024,China )
关键词:
电动汽车; 动态分时电价; 粒子群优化算法; 用户充电成本; 峰谷差率
Keywords:
electric vehicles;  dynamic time-of-use price;  particle swarm optimization;  charge cost of user;  peak-valley ratio
分类号:
TM73
DOI:
-
文献标志码:
A
摘要:
大规模电动汽车随机无序充电将对电网安全运行带来巨大挑战，诸如增大负荷峰谷差、加大运营成本、增加谐波污染等。该文在考虑电动汽车充放电功率约束、电池容量约束的前提下，基于动态分时电价制度，建立电动汽车多目标优化调度模型，以降低电网负荷峰谷差率和用户充电成本，并采用改进学习因子与惯性权重的粒子群优化算法对模型进行求解。仿真结果表明，基于动态分时电价的调度策略比固定电价下优化效果更优，能够更好的减小系统负荷峰谷差率，提高负荷率，增加电力设备的利用率，降低电动汽车充电成本。
Abstract:
The out -of -order charging of electric vehicles will bring great challenges to the safe operation of power grid，such as increasing the load of the peak-valley ratio, the operating costs,the harmonic pollution etc.In this paper,considering the constraints of the charging/ discharging power and the electricity quantity stored in the battery of electric vehicles，based on dynamic time-of-use price system,establishing a multi-objective optimization scheduling model for electric vehicles，in order to reduce peak-valley ratio of grid load and valley load and charge cost of user.The model is solved by modifying particle swarm optimization based on learning factor and inertia weight.Simulation results show that the scheduling strategy based on dynamic time-of-use price is better than the fixed price,and it can reduce the system load peak-valley ratio better,increasing the load rate and the utilization of power equipment,reducing the charge cost of electric vehicles.

参考文献/References:

[1] 胡泽春,宋永华,徐智威,等.电动汽车接入电网的影响与利用[J].中国电机工程学报, 2012, 32(4): 1-10.

[2] 杨秀菊,白晓清,李佩杰,等.电动汽车规模化接入配电网的充电优化[J].电力自动化设备, 2015, 35(6): 31-36.
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[7] 魏大钧,张承慧,孙波,等.基于分时电价的电动汽车充放电多目标优化调度[J].电网技术，2014,38(11):2972-2977.
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备注/Memo

备注/Memo:
收稿日期：2016-06-06
基金项目：国家自然科学基金(51267011)
作者简介：包广清（1972），女，甘肃兰州人，博士，教授，博士生导师，研究方向为
更新日期/Last Update: 1900-01-01