文章基本信息

标题：Optimal Charging/discharging Strategy of Electric Vehicles in Residential Area Considering User Comprehensive Satisfaction
本地全文：下载
作者：Jilong Liu ; Ping Li ; Wentao Zhong 等
期刊名称：E3S Web of Conferences
印刷版ISSN：2267-1242
电子版ISSN：2267-1242
出版年度：2018
卷号：53
页码：1-7
DOI：10.1051/e3sconf/20185302012
出版社：EDP Sciences
摘要：At present, the research on charging/discharging of electric vehicles (EVs) lacks consideration of the user experience, particularly with the aspects of user's convenience and profitability. Therefore, this paper analyses the travelling characteristics and travelling demand of EV users in a residential area and establishes the user comprehensive satisfaction model considering travel convenience and charging/discharging economy. Based on this model, a genetic algorithm is used to optimize the charging/discharging strategy of EVs with the aim of maximizing user comprehensive satisfaction, the validity of the proposed optimization model is verified by results of example. The model is also used to study the impact of large-scale EVs charging/discharging optimization strategy on grid load fluctuation. Based on the load data of a residential area, the simulation is carried out, and the influence of different peak-valley prices on EVs charging/discharging strategy is analysed. Our case analysis shows that the load peak-valley difference is reduced. With the increase of peak-valley electricity price, more users discharge during the peak hours and charge during the peak-off hours, the load peak-valley difference and the load fluctuation decrease accordingly.
其他摘要：At present, the research on charging/discharging of electric vehicles (EVs) lacks consideration of the user experience, particularly with the aspects of user's convenience and profitability. Therefore, this paper analyses the travelling characteristics and travelling demand of EV users in a residential area and establishes the user comprehensive satisfaction model considering travel convenience and charging/discharging economy. Based on this model, a genetic algorithm is used to optimize the charging/discharging strategy of EVs with the aim of maximizing user comprehensive satisfaction, the validity of the proposed optimization model is verified by results of example. The model is also used to study the impact of large-scale EVs charging/discharging optimization strategy on grid load fluctuation. Based on the load data of a residential area, the simulation is carried out, and the influence of different peak-valley prices on EVs charging/discharging strategy is analysed. Our case analysis shows that the load peak-valley difference is reduced. With the increase of peak-valley electricity price, more users discharge during the peak hours and charge during the peak-off hours, the load peak-valley difference and the load fluctuation decrease accordingly.