Optimization and Observation of EV Charging Station Deployment in the Republic of Korea: An Analysis of the Charging History and Correlation With Socioeconomic Factors

被引:2
作者
Gong, Youngmin [1 ]
Kim, Insu [1 ]
机构
[1] Inha Univ, Dept Elect & Comp Engn, Incheon 22212, South Korea
来源
IEEE ACCESS | 2024年 / 12卷
关键词
Electric vehicle charging; Charging stations; Statistics; Sociology; Population density; Correlation; Public transportation; Genetic algorithms; Greenhouse gases; Carbon emissions; correlation coefficient; electric vehicle; genetic algorithm; slow and fast chargers; LOCATIONS;
D O I
10.1109/ACCESS.2024.3397231
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The demand for electric vehicles is increasing due to the recent focus on reducing greenhouse gas emissions. Hence, the number of electric-vehicle charging stations must be increased to meet the growing demand for electric vehicles. To this end, supportive policies are being established to increase the deployment of electric vehicle charging stations worldwide. On the other hand, it is not possible to subsidize all facilities simultaneously. This study developed a model to prioritize the deployment of electric vehicle charging stations. The Republic of Korea was analyzed as a case study region to develop this model, and the correlations between the amount of charging energy of electric vehicle charging stations and socioeconomic factors (traffic volume, population, number of electric vehicles, and land value) were analyzed. The correlations were analyzed differently depending on the purpose (e.g., residential or commercial) of the facilities where electric vehicle charging stations were installed. Correlation analysis was conducted to determine the factors that affect the amount of charging energy, and a model was developed to prioritize the deployment of electric vehicle charging stations through a genetic algorithm. A model with a correlation of more than 0.2 was developed, except for residential facilities with slow chargers and public institutions with slow chargers. The results of this paper can help identify the key factors to be analyzed by facility use when installing electric vehicle charging stations and determine the priorities for subsidizing the deployment of electric vehicle charging stations.
引用
收藏
页码:68285 / 68302
页数:18
相关论文
共 44 条
[1]  
[Anonymous], 2022, 4th Mid-to Long-Term Comprehensive Plan To Facilitate Electric Vehicle Distribution and Forster Its Industry in Jeju-do for 2022 To 2030
[2]  
[Anonymous], 2022, Population and Housing Census
[3]  
[Anonymous], 2023, Enforcement Decree Of The Act On Promotion Of Development and Distribution Of Environment-friendly Motor Vehicles
[4]  
[Anonymous], 2022, 2023 Electric Vehicle Slow Charger Subsidy .ProgramSubsidy, Installation and Operation Guidelines
[5]  
Arya A., 2023, P INT C ADV EL COMM, P99, DOI DOI 10.1109/ICAECIS58353.2023.10170101
[6]   Public electric vehicle charging station utilization in the United States [J].
Borlaug, Brennan ;
Yang, Fan ;
Pritchard, Ewan ;
Wood, Eric ;
Gonder, Jeff .
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2023, 114
[7]   Identifying optimal locations for community electric vehicle charging [J].
Charly, Anna ;
Thomas, Nikita Jayan ;
Foley, Aoife ;
Caulfield, Brian .
SUSTAINABLE CITIES AND SOCIETY, 2023, 94
[8]   Multi-period planning for electric car charging station locations: A case of Korean Expressways [J].
Chung, Sung Hoon ;
Kwon, Changhyun .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2015, 242 (02) :677-687
[9]   Electric vehicles standards, charging infrastructure, and impact on grid integration: A technological review [J].
Das, H. S. ;
Rahman, M. M. ;
Li, S. ;
Tan, C. W. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2020, 120
[10]  
DF Transport, Government Sets Out Path To Zero Emis1 sion Vehicles By 2035