| Issue |
E3S Web Conf.
Volume 53, 2018
2018 3rd International Conference on Advances in Energy and Environment Research (ICAEER 2018)
|
|
|---|---|---|
| Article Number | 02012 | |
| Number of page(s) | 7 | |
| Section | Energy Equipment and Application | |
| DOI | https://doi.org/10.1051/e3sconf/20185302012 | |
| Published online | 14 September 2018 | |
Optimal Charging/discharging Strategy of Electric Vehicles in Residential Area Considering User Comprehensive Satisfaction
1
State Grid Binzhou Power Supply Company, No.521 Yellow River Fourth Road, Binzhou, Shandong Province, China
2
Sichuan University, No.24 South Section 1, Yihuan Road, Chengdu, Sichuan Province, China
* Corresponding author: 343369391@qq.com
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.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.