基于停车需求模型的电动汽车V2G放电负荷时空分布预测  

Temporal and Spatial Distribution Forecast for V2G Discharge Load Based on Parking Demand Model

作　　者：刘晓飞[1] 崔淑梅[1] 谢富鸿 徐石明 

机构地区：[1]哈尔滨工业大学电气工程及自动化学院,哈尔滨150001 [2]国家电网电力科学研究院,南京211000

出　　处：《电气工程学报》2015年第8期22-28,79,共8页Journal of Electrical Engineering

基　　金：NSFC-RCUK_EPSRC项目(中英)(51361130153);国家能源应用技术研究及工程示范项目(NY20110703-1)资助

摘　　要：当前电动汽车负荷时空分布预测研究主要侧重于充电负荷,而对V2G放电能力的预测考虑较少。为此,本文从交通规划的角度进行考虑,提出了一种电动汽车V2G放电负荷时空分布预测方法。以城市停车需求预测模型为基础,分析了工商业区和居住区内电动汽车在时空上的停放分布特性,建立了电动汽车V2G负荷容量模型,并给出了基于蒙特卡洛模拟的预测方法。最后以某城市为算例进行了仿真,分析了工商业区和居住区电动汽车的V2G负荷特性,以及备用行驶容量、充放电功率和日均行驶里程对V2G放电能力的影响。Currently, the research on V2 G load temporal and spatial distribution forecast mainly focuses on charging load, with less consideration for discharging. A V2 G discharging load temporal and spatial distribution forecast method is proposed, from the aspect of traffic planning. Based on city parking demand model, parking characteristics of EVs in industrial/commercial and residential areas are analyzed and V2 G load capacity model is built. Also, forecast method based on Monte Carlo simulation is given. Finally, taking a city for a computing example, V2 G load characteristics in industrial/commercial and residential areas are analyzed. Meanwhile, it is given how V2 G load is impacted by reserve driving capacity, charging and discharging power, and daily average driving range.

关 键 词：电动汽车 V2G放电负荷 时空分布预测 停车需求模型 

分 类 号：U469.7[机械工程—车辆工程]