인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
개인구독
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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
The uptake of electric vehicles (EVs) has risen with the global uptrend of many countries" decarbonization policies. EVs have received the world"s attention as the most effective method to reduce carbon dioxide on the road. Except for the forerunners in electric mobility, most countries have just started installing and providing public charging infrastructure. In the initial adoption stage of EVs, the public infrastructure for charging is crucial to appeal to the public, thereby accelerating its adoption. Previous studies on public fast-charging stations have rarely integrated real-world problems and spatial constraints into the optimal location. To solve this contextual gap, the study proposed identifying the optimal location for fast-charging public stations through a spatial location-allocation model based on a road network and demand analysis based on the total number of registered EVs by the districts. Seoul Metropolitan Government aims to supply 22,000 charging stations and 300 fast chargers by 2022. This study, therefore, considered the optimal allocation of the public fast-charging stations in Seoul. To identify the location points where new charging stations can be installed for 25 districts of Seoul, this study initially applied the Service Area Analysis and Minimum Facility methods of the spatial Location-Allocation Model. Identifying the number of the installation points was based on the criteria for the total number of registered EVs by the district through a demand analysis. This study recognized that the Service Area Analysis had its methodological limitation due to not reflecting the differentiated demand by considering only the optimal location, not the density of charging stations. The implementation of the demand analysis resolved this limitation. This complementary methodology demonstrated a significant approach, considering the charging station distribution and the density of chargers in charging stations when considering future expansions of the charging network.
본문·목차
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UCI(KEPA) : I410-ECN-0101-2022-453-001640176
