A Statistical Analysis of EV Charging Behavior in the UK

被引：0
|
作者：
Quiros-Tortos, Jairo [1 ]
Ochoa, Luis F. [1 ]
Lees, Becky [2 ]
机构：
[1] Univ Manchester, Manchester, Lancs, England
[2] EA Technol Ltd, Chester, Cheshire, England
来源：
2015 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES LATIN AMERICA (ISGT LATAM) | 2015年
关键词：
Electric vehicles; real data; statistical analysis;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
To truly quantify the impact of electric vehicles (EVs) on the electricity network and their potential interactions in the context of Smart Grids, it is crucial to understand their charging behavior. However, as EVs are yet to be widely adopted, these data are scarce. This work presents results of a thorough statistical analysis of the charging behavior of 221 real residential EV users (Nissan LEAF, i.e., 24kWh, 3.6 kW) spread across the UK and monitored over one year (68,000+ samples). Probability distribution functions (PDFs) of different charging features (e.g., start charging time) are produced for both weekdays and weekends. Crucially, these unique PDFs can be used to create stochastic, realistic and detailed EV profiles to carry out impact and/or Smart Grid-related studies. Finally, the effects of the EV demand on future UK distribution networks are discussed.
引用
收藏
页码：445 / 449
页数：5
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