基于用户出行链和调控意愿的城市级私家电动汽车调控能力评估

doi:10.12204/j.issn.1000-7229.2021.05.011

电力建设 ›› 2021, Vol. 42 ›› Issue (5): 100-112.doi: 10.12204/j.issn.1000-7229.2021.05.011

基于用户出行链和调控意愿的城市级私家电动汽车调控能力评估

李瑶虹¹, 陈良亮²^,³, 刘卫东⁴, 傅质馨⁴

1.国网江苏省电力有限公司,南京市 211106
2.国电南瑞南京控制系统有限公司,南京市 211106
3.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
4.河海大学能源与电气学院,南京市 211100

收稿日期:2020-08-26 出版日期:2021-05-01 发布日期:2021-05-06
作者简介:李瑶虹(1972),女,硕士,高级经济师,研究方向为电力营销与管理、综合能源服务、系统工程;|陈良亮(1975),男,博士,教授级高级工程师,研究方向为电动汽车充换电技术;|刘卫东(1996),男,硕士研究生,研究方向为电动汽车虚拟储能调控能力;|傅质馨(1983),女,博士,副教授,硕士生导师,研究方向为可再生能源发电技术、物联网技术。
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)

Regulation Ability Estimation of Private EVs at City Level Considering Users’ Trip Chain and Regulation Willingness

LI Yaohong¹, CHEN Liangliang²^,³, LIU Weidong⁴, FU Zhixin⁴

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

Received:2020-08-26 Online:2021-05-01 Published:2021-05-06
Supported by:
State Grid Corporation of China Research Program(5418-202018247A-0-0-00)

摘要/Abstract

摘要：

提出一种基于电动汽车出行链的私家电动汽车(electrical vehicle,EV)参与电网调控能力的评估方法。由用户出行链的特征,从工作日和非工作日两种情况对私家EV的出行链进行模拟,得到EV在城市各类功能区的空间分布变化特征;考虑影响EV参与电网调控的关键性因素,以电动汽车荷电状态约束和功率约束建立单辆私家EV参与电网调控的能力模型,进而建立集群EV在不同城市功能区的调控能力模型。最后通过仿真分析,对工作日和非工作日的私家EV调控能力进行评估和对比,并着重考虑私家EV参与调控意愿下的调控能力变化。仿真分析结果表明,私家EV的调控能力变化与某城市功能区EV数量变化相关,用户参与意愿比例的下降使得调控能力水平整体下降,但变化特征仍以EV时空分布变化特征为主导。

关键词: 电动汽车, 出行链, 城市功能区, 调控能力, 参与意愿

Abstract:

This paper presents a method to evaluate the ability of private electric vehicle (EV) to participate in power grid regulation based on EV trip chain. According to the characteristics of users’ trip chain, the trip chain of private EVs is simulated during working days and non-working days, and the spatial distribution variation characteristics of EVs in various functional areas of the city are obtained. Considering the key factors affecting users’ participation in power grid regulation, the capacity model of single private EV is established according to the SOC constraint and power constraint of EV, and then the regulation capacity model of cluster EVs in different urban functional areas is established. Finally through the simulation analysis, the regulation ability of private EVs during working days and non-working days is evaluated and compared. Furthermore, the regulatory capacity changes of private EVs under the willingness to participate in regulation are considered. The results show that the change of the regulatory capability of private EVs is related to the change of EV number in a functional area of a city, and the decrease of the proportion of users’ willingness to participate makes the overall regulatory capability decrease, but the change feature is still dominated by the change feature of EV spatial distribution.

Key words: electrical vehicle, trip chain, urban functional area, regulation ability, participation willingness

中图分类号:

TM73

李瑶虹, 陈良亮, 刘卫东, 傅质馨. 基于用户出行链和调控意愿的城市级私家电动汽车调控能力评估[J]. 电力建设, 2021, 42(5): 100-112.

LI Yaohong, CHEN Liangliang, LIU Weidong, FU Zhixin. Regulation Ability Estimation of Private EVs at City Level Considering Users’ Trip Chain and Regulation Willingness[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(5): 100-112.

图/表 40

图1 出行链示意图

Fig.1 Diagram of trip chain

图2 工作日私家EV数量变化特征

Fig.2 Change in the number of private EVs during the working day

图3 非工作日私家EV数量变化特征

Fig.3 Change in the number of private EVs during the non-working day

图4 情形1调控能力示意图

Fig.4 Schematic diagram of regulatory capacity in scenario 1

图5 情形2调控能力示意图

Fig.5 Schematic diagram of regulatory capacity in scenario 2

图6 模糊推理原理图

Fig.6 A schematic of fuzzy reasoning

图7 SOH隶属度函数

Fig.7 Membership function of SOH

图8 充电意愿隶属度函数

Fig.8 Membership function of charging willingness

表1 充电意愿模糊规则(部分)

Table 1 Fuzzy rules for charging willingness (part)

图9 工作日各地点的充电容量

Fig.9 Charging capacity of each region during the working day

图10 工作日各地点的充电功率

Fig.10 Charging power of each region during the working day

图11 非工作日各地点的充电容量

Fig.11 Charging capacity of each region during the non-working day

图12 非工作日各地点的充电功率

Fig.12 Charging power of each region during the non-working day

图13 工作日各地点的EV集群充电容量

Fig.13 EV cluster charging capacity of each region during the working day

图14 工作日各地点的EV集群充电功率

Fig.14 EV cluster charging power of each region during the working day

图15 非工作日各地点的EV集群充电容量

Fig.15 EV cluster charging capacity of each region during the non-working day

图16 非工作日各地点的EV集群充电功率

Fig.16 EV cluster charging power of each region during the non-working day

图17 工作日各地点类型充电容量比较图

Fig.17 Comparison diagram of charging capacity of various regions during the working day

图18 工作日各地点类型充电功率比较图

Fig.18 Comparison diagram of charging power of various regions during the working day

图19 非工作日各地点类型充电容量比较图

Fig.19 Comparison diagram of charging capacity of various regions during the non-working day

图20 非工作日各地点类型充电功率比较图

Fig.20 Comparison diagram of charging power of various regions during the non-working day

表A1 工作日首次出行时刻拟合参数结果

Table A1 Results of fitting parameters at the time of the first trip during the working day

表A2 非工作日首次出行时刻拟合参数结果

Table A2 Results of fitting parameters at the time of the first trip during the non-working day

表A3 工作日行驶时长拟合参数

Table A3 The fitting parameters of driving time during the working day

表A4 非工作日行驶时长拟合参数

Table A4 The fitting parameters of driving time during the non-working day

表A5 工作日停车时长对数正态分布拟合参数

Table A5 The logarithmic normal distribution fitting parameters of the parking time during the working day

表A6 工作日停车时长GMM拟合参数

Table A6 The GMM fitting parameters of stopping time during the working day

表A7 非工作日H-W停车时长GMM拟合参数

Table A7 The GMM fitting parameters of stopping time during the non-working day

表A8 非工作日停车时长对数正态分布拟合

Table A8 The logarithmic normal distribution fitting parameters of the parking time during the non-working day

图B1 工作日不同时段内行程转移概率

Fig.B1 The stroke transfer probability of different time periods during the working day

图B2 非工作日不同时段内行程转移概率

Fig.B2 The stroke transfer probability of different time periods during the non-working day

图B3 工作日8至9时行程目的转移概率

Fig.B3 Trip destination transfer probability at 08:00-09:00 during the working day

图B4 非工作日8至9时行程目的转移概率

Fig.B4 Trip destination transfer probability at 08:00-09:00 during the non-working day

图C1 SOC隶属度函数

Fig.C1 Membership function of SOC

图C2 充电电价隶属度函数

Fig.C2 Membership function of charging price

图C3 放电电价隶属度函数

Fig.C3 Membership function of discharging price

图C4 停车时长隶属度函数

Fig.C4 Membership function of parking time

图C5 放电意愿隶属度函数

Fig.C5 Membership function of discharging willingness

表C1 充电意愿模糊规则

Table C1 Fuzzy rules for charging willingness

表C2 放电意愿模糊规则

Table C2 Fuzzy rules for discharging willingness

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基于用户出行链和调控意愿的城市级私家电动汽车调控能力评估

Regulation Ability Estimation of Private EVs at City Level Considering Users’ Trip Chain and Regulation Willingness

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