Statistical Analysis of Electric Vehicle Charging Based on AC Slow Chargers

Author:

Kim Dong Sik1ORCID,Chung Young Mo2ORCID,Chung Beom Jin3ORCID

Affiliation:

1. Deparment of Electronics Engineering, Hankuk University of Foreign Studies, Yongin-si 17035, Republic of Korea

2. Department of Electronics and Information Engineering, Hansung University, Seoul 02876, Republic of Korea

3. Research Center for Electrical and Information Technology, Seoul National University of Science & Technology, Seoul 01811, Republic of Korea

Abstract

Regarding DC fast chargers, various studies, such as the charge scheduling, have been conducted. On the other hand, research on AC slow chargers has rarely been conducted due to the predictable and simple usage pattern. Despite the long charging times of AC slow chargers, which use the existing electric outlets with relatively low supplied power, these chargers are suitable for daily home charging of electric vehicles (EVs) during the night. Due to their low installation costs, they are likely to be the dominant type of charging equipment. In this paper, the EV charging process based on AC slow chargers, which supply a maximum power of 3 kW from an AC 220 V outlet, is analyzed by constructing a simple charging model. The charging time and fees are statistically derived and investigated. Furthermore, power load curves for charging EVs with the 3 kW charger are observed. From the statistical analyses, we conclude that daily charging of EVs can be an appropriate scenario in using the AC slow chargers, and the power load can be spread without employing any demand response schemes.

Funder

Korea Institute of Energy Technology Evaluation and Planning (KETEP), the Ministry of Trade, Industry and Energy (MOTIE) of the Republic of Korea

Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education

Hansung University

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

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4. Bloomberg (2022). Electric Vehicle Outlook 2020. Bloomberg New Energy Finance, Bloomberg.

5. Modeling and analysis of a fast charging station and evaluation of service quality for electric vehicles;Ucer;IEEE Trans. Transp. Electrif.,2019

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