考虑城市不同功能区的电动汽车负荷时空分布建模方法

doi:10.12204/j.issn.1000-7229.2021.06.007

电力建设 ›› 2021, Vol. 42 ›› Issue (6): 67-75.doi: 10.12204/j.issn.1000-7229.2021.06.007

• 电动汽车参与电网调度的关键技术·栏目主持傅质馨副教授· • 上一篇下一篇

考虑城市不同功能区的电动汽车负荷时空分布建模方法

范磊¹^,², 陈良亮³^,⁴, 罗雯茜⁵, 董晓霄⁵, 袁越⁵

1.国网江苏省电力有限公司,南京市 210016
2.国网江苏省电力有限公司苏州供电分公司, 江苏省苏州市 215004
3.国电南瑞南京控制系统有限公司,南京市 211106
4.南瑞集团有限公司(国网电力科学研究院有限公司),南京市 211106
5.河海大学能源与电气学院,南京市 211100

收稿日期:2020-08-13 出版日期:2021-06-01 发布日期:2021-05-28
作者简介:范磊(1984),男,硕士,工程师,主要研究方向为电网调度运行、电网运行方式技术、电力系统负荷预测、新能源入网等;|陈良亮(1975),男,博士,教授级高级工程师,主要研究方向为电动汽车充换电技术;|罗雯茜(1997),女,硕士研究生,主要研究方向为电动汽车负荷预测和建模;|董晓霄(1990),女,博士,讲师,主要研究方向为微特电机、压电发电技术和节能新技术等;|袁越(1966),男,博士,教授,博士生导师,主要研究方向为电力系统优化运行、电力系统稳定分析与控制、可再生能源与节能新技术。
基金资助:
国家电网有限公司总部科技项目“电动汽车集群优化虚拟储能与负荷控制关键技术研究及示范应用”(5418-202018247A-0-0-00)

Spatial and Temporal Distribution Model of Electric Vehicle Load Considering Different Urban Functional Areas

FAN Lei¹^,², CHEN Liangliang³^,⁴, LUO Wenqian⁵, DONG Xiaoxiao⁵, YUAN Yue⁵

1. State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210016, China
2. Suzhou Power Supply Branch of State Grid Jiangsu Electric Power Co., Ltd., Suzhou 215004 ,Jiangsu Province, China
3. NARI-TECH Control System Ltd., Nanjing 211106, China
4. NARI Group Corporation(State Grid Electric Power Research Institute), Nanjing 211106, China
5. College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China

Received:2020-08-13 Online:2021-06-01 Published:2021-05-28
Supported by:
State Grid Corporation of China Research Program(5418-202018247A-0-0-00)

摘要/Abstract

摘要：

研究电动汽车充电负荷特性是推进电动汽车接入电网的基础,电动汽车充电负荷在时间和空间上具有随机性。文章充分考虑城市不同功能区的特性,提出了一种基于改进重力模型的电动汽车负荷时空分布建模方法。首先,确定电动汽车的类别与出行特性,并进行城市功能区划分;其次,依据改进的重力模型获取城市各时段各区域的出行矩阵,得到电动汽车入网的时空分布;最后,抽取电动汽车的出行里程,结合电动汽车充电方式与充放电的荷电状态模型,建立电动汽车负荷的时空分布模型。算例分析表明,不同类别功能区之间的负荷分布与各区域吸引力相关且存在较大差异,同一类别功能区中位于城市中心地区的负荷较高。算例通过设置不同场景,分析不同因素对充电负荷分布的影响,验证了所提模型的准确性。

关键词: 电动汽车, 时空分布, 城市功能区, 重力模型

Abstract:

Study of the charging load characteristics of electric vehicles (EVs) is the basis for promoting the integration of EVs into the power grid. The charging load of electric vehicles has both temporal and spatial randomness. In this paper, a temporal and spatial distribution model of EVs, which considers the characteristics of different urban functional areas, is proposed on the basis of the improved gravity model. Firstly, the travel characteristics and the categories of EVs are determined, and urban areas are reasonably divided according to the categories of functional areas. Secondly, the travel matrices of urban areas at different time period, as well as the spatial distribution of EVs, are achieved according to the improved gravity model. Finally, combining with the charging modes and the state-of-charge (SOC) model of EVs, the temporal and spatial distribution model is established. Case studies show that there exists a huge discrepancy in the load distributions among different types of functional areas due to the attractiveness of each area. For the same type of functional area, areas closer to the city center generally pick up more load than their outlying counterparts. The accuracy of the proposed model is verified by analyzing the influence of different factors on the charging load distribution in various preset scenarios.

Key words: electric vehicle (EV), spatial and temporal distribution, urban functional area, gravity model

中图分类号:

TM73

范磊, 陈良亮, 罗雯茜, 董晓霄, 袁越. 考虑城市不同功能区的电动汽车负荷时空分布建模方法[J]. 电力建设, 2021, 42(6): 67-75.

FAN Lei, CHEN Liangliang, LUO Wenqian, DONG Xiaoxiao, YUAN Yue. Spatial and Temporal Distribution Model of Electric Vehicle Load Considering Different Urban Functional Areas[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(6): 67-75.

图/表 16

图1 电动汽车出行分布预测建模思想

Fig.1 Modelling idea of EV travel distribution prediction

图2 电动汽车充电负荷预测流程图

Fig.2 Flow chart of EV charging load prediction

图3 A市的功能区划分

Fig.3 The urban functional area division of city A

表1 A市各区域所属的城市功能区名称

Table 1 Names of the urban functional area of each region in city A

图4 A市的各区域之间的阻抗函数

Fig.4 The travel intention between different regions in city A

表2 电动汽车的参数

Table 2 Parameters of electric vehicles

图5 各时刻入网电动汽车行驶里程分布

Fig.5 Distance distribution of EVs integrated into power gird at each moment

图6 各时刻居民区的充电功率

Fig.6 Charging power of different regions of residential areas at each moment

图7 传统和改进重力模型的充电功率结果对比

Fig.7 Results comparison of charging power between traditional and improved gravity models

图8 公共服务区有无电动公交车的充电功率

Fig.8 Charging power of public service area with or without the charging power of electric buses

图9 城市商业区扩建前后城市的充电功率

Fig.9 Charging power of the city with or without the expansion of urban business district

图10 办公时间增加前后城市的充电功率

Fig.10 Charging power of the city with or without the increase of working hours

表A1 A市各区域之间的距离

Table A1 The distance between different regions in city A距离/km

表A2 A市各区域之间的出行阻抗函数

Table A2 The travel intention between different regions in city A

图A1 地区吸引力

Fig.A1 Attractiveness of each area

图A2 地区出行力

Fig.A2 Travel rate of each area

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考虑城市不同功能区的电动汽车负荷时空分布建模方法

Spatial and Temporal Distribution Model of Electric Vehicle Load Considering Different Urban Functional Areas

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