Electric vehicle charging in smart grid: A spatial-temporal simulation method
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
Electric vehicles (EVs) play an important role in the future energy system. The large-scale adoption of moving EV load significantly accelerates the integration of transportation and distribution systems. The method to simulate the mobility and charging of a single or aggregated EVs is the key to analyze EVs’ flexibility on the operation of distribution network. Considering the integrated impacts from both the transportation and power systems, and the uncertainty of user’s driving behavior and charging intention, this paper proposes a spatial-temporal simulation method based on the vehicle-transportation-grid trajectory. The trajectory can not only describe the destination location and time like the trip chain, but also give the key information including the driving path in a whole travel process. The driving, parking, and charging are analyzed by the proposed spatial-temporal simulation method. It models the driving behavior based on statistical results and transportation systems, EV energy consumption pattern based on battery energy, and the charging demand based on the user’s subjective intention at the coupled systems. Finally, a 30-node transportation system is developed and integrated with a 33-bus distribution network to illustrate the proposed method. Two typical days, “workday” and “holiday”, are simulated and compared under different EV penetration levels (0%, 20%, 50% and 100%), different trip chain ratio (the ratio of 3-trip chains is 50%, 70%, 90%) to demonstrate the effectiveness of the spatial-temporal simulation method.
Date Issued
2019-12-15
Date Acceptance
2019-09-25
Citation
Energy, 2019, 189, pp.1-12
ISSN
0360-5442
Publisher
Elsevier BV
Start Page
1
End Page
12
Journal / Book Title
Energy
Volume
189
Copyright Statement
© 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Innovate UK
Identifier
https://www.sciencedirect.com/science/article/pii/S0360544219319164?via%3Dihub
Grant Number
104224 / 16369
Subjects
0913 Mechanical Engineering
0915 Interdisciplinary Engineering
0914 Resources Engineering and Extractive Metallurgy
Energy
Publication Status
Published online
Article Number
116221
Date Publish Online
2019-09-25