인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
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 phenomenon of worldwide climate change is affecting human life more seriously than ever before. Countries around the world have identified cars as an integral part of pollutive sources. This is why automobiles should be Eco-friendly. Electric vehicle, which are representatively Eco-friendly, have become a spotlight vehicle of the future. In this paper, we propose a strategy to place a large – scale charging theme park. Up until now, typical public charging station has 2~3 chargers to support charging needs of the Ev users. As the EV become more popular, a newly noticed problems such as either charger hopping or long waiting become eminent. In order to address this new but, a certain issue, large scale charging theme park concept which has more than 30 chargers is proposed. Furthermore, in order to maximize its effectiveness, a strategic approach to select the close-to-ideal locations for the charging them park is introduced as well. In this study, Jeju Island, which has many electric vehicle in Korea, is selected as an analysis model. We propose an algorithm for the assignment of weighting factors according to the location of tourist attractions, convenient supporting facilities and the density of population. The estimated locations are validated using actual charger usage data collected over time in Jeju island. The proposed strategy to identify appropriate location for large scale charging theme parks can be used in other tourist heavy island or even for small countries. If the algorithm is enhanced. With increased amount real charger usage data, it is expected to be further utilized for other sectors and countries.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
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오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2019-556-000207254
