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Schedulable capacity assessment method for PV and storage integrated fast charging stations with V2G

Authors :
Kaiyu Zhang
Shuhe Zhan
Shanshan Shi
Chen Fang
Donghan Feng
Haojing Wang
Hua Zhang
Bing Shen
Yun Wang
Yun Zhou
Source :
The Journal of Engineering, Vol 2023, Iss 5, Pp n/a-n/a (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract An accurate estimation of schedulable capacity (SC) is especially crucial given the rapid growth of electric vehicles, their new energy charging stations, and the promotion of vehicle‐to‐grid (V2G) technology. In this study, an evaluation approach for a photovoltaic (PV) and storage‐integrated fast charging station is established. The energy relationship between the SC of electric vehicles (EVs), the SC of centralized energy storage, and the PV power generation is constructed to solve for the upward SC and downward SC of the entire charging station based on the detailed explanation of the electrical structure of the PV and storage integrated fast charging station. To facilitate the grid to improve the dispatching efficiency, a strategy for solving the daytime SC is developed. This work uses an actual charging station as the research object for case analysis, and fine‐grained modeling of its component characteristics is finished in order to test the validity and robustness of the model. Four views are used to examine the variable properties and affecting elements of the schedulable capacity: light circumstances, EV load typical scenarios, dispatching interval length, and centralized energy storage configuration.

Details

Language :
English
ISSN :
20513305
Volume :
2023
Issue :
5
Database :
Directory of Open Access Journals
Journal :
The Journal of Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.64c490c6d7a4812a466f899911f8860
Document Type :
article
Full Text :
https://doi.org/10.1049/tje2.12271