A dynamic charging strategy with hybrid fast charging station for electric vehicles
Onur Elma
Energy, 2020, vol. 202, issue C
Abstract:
The popularity of electric vehicles (EV) have been on the rise with technological advancements and environmental concerns. The charging time and charging demand are important challenges for EV adaptation. In order to address these challenges, a DC fast charging technology with a dynamic energy management system is proposed in this study. However, DC fast chargers require high power demand periods to reduce the charging time. This, in turn, will cause negative effects on the grid such as stability, resilience, and efficiency problems. The purpose of the study is to evaluate a hybrid DC fast charging station with the aim of reducing peak demand during charging periods. The proposed energy management algorithm together with the dynamic data use provides more reliable results on such systems operations. With the proposed control algorithm, both peak demand from the grid is substantially reduced by 45% and the battery life span is extended thanks to more controlled charge/discharge coordination.
Keywords: Electric vehicle; Fast charging station; Demand response; Hybrid energy resources; Dynamic energy management (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544220307878
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:202:y:2020:i:c:s0360544220307878
DOI: 10.1016/j.energy.2020.117680
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().