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

Abstract

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.

Keywords

• Charging stations
• correlation coefficient
• electric vehicle
• genetic algorithm
• slow and fast chargers