电动出租车充电负荷的时空随机分布特性

doi:10.3969/j.issn.1000－7229.2017.01.002

电力建设 ›› 2017, Vol. 38 ›› Issue (1): 8-.doi: 10.3969/j.issn.1000－7229.2017.01.002

电动出租车充电负荷的时空随机分布特性

廖斌杰1，杨俊1，文福拴1,2，李波3，李梁3，毛建伟3

1.浙江大学电气工程学院，杭州市 310027；2.文莱科技大学电机与电子工程系，文莱
斯里巴加湾 BE1410；3. 国网浙江省电力公司电动汽车服务分公司，杭州市 310007

出版日期:2017-01-01
作者简介:廖斌杰(1990)，男，硕士，主要从事电动汽车与电力系统交互方面的研究工作；杨俊(1988)，男，硕士，主要从事电动汽车与电力系统交互方面的研究工作；文福拴(1965)，男，博士，教授，博士生导师，主要从事电力系统故障诊断与系统恢复、电力经济与电力市场、智能电网与电动汽车等方面的研究工作；李波(1981)，男，硕士，高级工程师，主要从事电动汽车与电力系统交互影响分析与管理方面的工作；李梁(1981)，男，本科，工程师，主要从事电动汽车与电力系统交互影响分析与管理方面的工作；毛建伟(1976)，男，硕士，高级工程师，主要从事电动汽车与电力系统交互影响分析与管理方面的工作。
基金资助:
国家重点基础研究发展计划项目(973计划) (2013CB228202)；国家自然科学基金项目(51477151)；国网浙江省电力公司科技项目(5211DF150007)

Temporal and Spatial Stochastic Distribution Characteristics of Charging Loads of Electric Taxis

LIAO Binjie1, YANG Jun1, WEN Fushuan1,2, LI Bo3, LI Liang3, MAO Jianwei3

1.College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China;
2.Department of Electrical & Electronic Engineering, Universiti Teknologi Brunei, Bandar Seri Begawan BE1410, Brunei;

3. Division of Electric Vehicle Service, State Grid Zhejiang Electric Power Company, Hangzhou 310007, China

Online:2017-01-01
Supported by:
Project supported by National Basic Research Program of China (973 Program) (2013CB228202); National Natural Science Foundation of China (51477151)

摘要/Abstract

摘要： 随着电动汽车 (electric vehicle，EV)普及程度的不断提高，其充电负荷的时空分布随机特性给电力系统安全与经济运行带来了挑战。在此背景下，提出一种计及电动出租车行为时空随机特性的充电负荷分析方法。首先，针对乘客出行特性和2种充电运营模式即快速充电和换电模式，分析电动出租车的行为模式。接着，通过对城市交通路网进行网格划分，确定各交通小区的地理坐标信息。然后，基于网格化的交通路网，构建描述电动出租车行驶、目的地与路径选择、充/换电行为的数学模型并采用蒙特卡洛仿真实现。最后，以杭州市电动出租车的运行情况为例说明所提方法的基本特征，计算电动出租车的日充电负荷，比较2种充电运营模式对充电负荷时空随机分布特性的影响。

关键词: 电动汽车（EV）, 电动出租车, 充电运营模式, 快速充电, 换电, 充电负荷, 时空分布, 交通小区

Abstract:

With the development of electric vehicles (EVs), the temporal and spatial stochastic distribution characteristics of EV charging are imposing challenges for power system secure and economic operation. Given this background, this paper proposes a systematical method for analyzing the charging load of electric taxis considering the temporal and the spatial stochastic distribution characteristics. First, driving patterns of electric taxis are discussed on account of typical passenger trip characteristics and the influences of two charging operation modes, i.e. fast charging and battery swapping. Then, the urban area of a given city is divided into several traffic zones by road map grid divisions, and the corresponding geographical coordinates are thus determined. Based on the grid-based traffic network, mathematical models for describing the driving, destination and path selection of electric taxis and charging/swapping behaviors are next presented, and the Monte Carlo simulation method is employed for attaining the solution. Finally, the operation scenarios of electric taxis in Hangzhou city are employed to demonstrate the essential features of the proposed method; specifically, the daily charging loads of electric taxis are investigated, and the impacts of two charging operation modes on the temporal and spatial distribution characteristics of electric taxi charging loads are compared.

Key words: electric vehicle（EV）, electric taxi, charging operation mode, fast charging, battery swapping, charging load, temporal and spatial distribution, traffic zone

中图分类号:

廖斌杰，杨俊，文福拴，李波，李梁，毛建伟. 电动出租车充电负荷的时空随机分布特性[J]. 电力建设, 2017, 38(1): 8-.

LIAO Binjie, YANG Jun, WEN Fushuan, LI Bo3, LI Liang, MAO Jianwei. Temporal and Spatial Stochastic Distribution Characteristics of Charging Loads of Electric Taxis[J]. Electric Power Construction, 2017, 38(1): 8-.

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电动出租车充电负荷的时空随机分布特性

Temporal and Spatial Stochastic Distribution Characteristics of Charging Loads of Electric Taxis

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