As environmental concerns including climate change drive the strong regulations for car exhaust emissions, electric vehicles attract the public eye. The purpose of this study is to identify rural areas vulnerable for charging infrastructures based on the spatial distributions of the current gas stations and provide the target dissemination rates for promoting electric cars. In addition, we develop various scenarios for finding optimal way to expand the charging infrastructures through the administrative districts data including 11,677 gas stations, the number of whole national gas stations. Gas stations for charging infrastructures are randomly selected using the Monte Carlo Simulation (MCS) method. Evaluation criteria for vulnerability assessment include five considering the characteristic of rural areas. The optimal penetration rate is determined to 21% in rural areas considering dissemination efficiency. To reduce the vulnerability, the charging systems should be strategically installed in rural areas considering geographical characteristics and regional EV demands.

Car exhaust emissions are recognized as one of the key sources for climate change and electric vehicles have no emissions from tailpipe. However, the limited charging infrastructures could restrict the propagation of electric vehicles. The purpose of this study is to find the vulnerable districts limited to the charging station services after meeting the goal of Ministry of Knowledge Economy(12%). We assumed that the charging service can be provided by current gas stations. The range of the vulnerable grades was determined by the accessibility to current gas stations and the vulnerable regions were classified considering the optimal number of charging stations estimated by the efficiency function. We used 4,827 sub-municipal divisions and 11,677 gas station locations for this analysis. The results show that most of mountain areas are vulnerable and the fringe areas of large cities generally get a good grade for the charging infrastructure. The gangwon-do, jeollanam-do, gyeongsangbuk-do, and chungcheongnam-do include more than 40% vulnerable districts.