含有耦合特性的电动汽车充电负荷计算方法

YANG Bing

您当前的位置：

首页 >

文章列表页 >

含有耦合特性的电动汽车充电负荷计算方法

更新时间：2025-08-13

- 含有耦合特性的电动汽车充电负荷计算方法
- Automation of Electric Power Systems Vol. 39, Issue 22, Pages: 76-82(2015)
- 作者机构：
  
  中国科学院电力电子与电气驱动重点实验室(中国科学院电工研究所),北京市,100190
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2015
- 稿件说明：
移动端阅览
YANG Bing. [J]. Automation of electric power systems, 2015, 39(22): 76-82.
DOI：

YANG Bing. [J]. Automation of electric power systems, 2015, 39(22): 76-82. DOI：

摘要

基于核密度函数改进了含有耦合特性的电动汽车充电负荷计算模型。模型中

采用核密度函数代替确定性的概率分布函数拟合电动汽车的行驶规律

采用多维概率分布函数生成含有耦合特性的行驶规律随机数

采用充电概率表示不确定的充电行为。通过与示范运行电动汽车充电负荷数据对比

验证了该方法的优越性。基于改进模型

预测了未来规模化居民私家电动汽车的充电负荷情况

研究发现:不确定充电行为对电动汽车充电负荷的影响很大

随着充电概率的减小充电负荷峰值的降低很大

峰值变化范围及充电持续时间均增大

并给电网负荷造成不确定的影响。

Abstract

Based on the kernel density function

a charging load calculation model with coupling characteristics is improved. In this model

the kernel density function instead of deterministic probability distribution function is selected to fit electric vehicles’ (EVs’) driving characteristics

the multi-dimensional probability distribution function to generate EVs’ driving random numbers with coupling features

and the charging probability to describe users’ uncertainty charging behavior. By comparing the calculated charging load with the actual charging load of a normal EVs’ charging station

the superiority of this method is verified. And then based on the improved model

the charging load of future large-scale residents’ private EVs is predicted. It is shown by research that the uncertain charging behavior exerts a great impact on EVs’ charging load. With decreased charging probability

the peak of charging load is greatly reduced

the peak value variation range and charging duration both increased and uncertain effects are brought to the grid load. This work is supported by National High Technology Research and Development Program of China (863 Program) (No. 2011AA05A109).

关键词

Keywords

references

Views

2687

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Medium- and Long-term Charging Load Forecasting Method for Electric Vehicles Considering Battery Aging

Coordination of Urban Integrated Electric Power and Traffic Network from Perspective of System Interconnection

基于TOPSIS方法的居民区电动汽车有序充电策略

典型家用大功率负载精细化建模及能量管理策略

基于电动汽车无功补偿的配电网电压调控策略

Related Author

MU Yunfei

YU Xiaodan

WANG Mingshen

DING Fei

KONG Huazhi

DONG Xiaohong

Qinglai GUO

Yujie SHENG

Related Institution

Key Laboratory of Ministry of Education on Smart Power Grids (Tianjin University)

Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd.

State Key Laboratory of Reliability and Intelligence of Electrical Equipment (Hebei University of Technology)

State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Tsinghua University

Department of Electrical Engineering, Tsinghua University

⁰