인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
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
Jeju Island is faced with considerable challenges in day-ahead load forecasting due to its high share of renewable energy, unique industrial structure, and strong seasonal tourism influence. Particularly on special days such as national holidays and vacation periods, significant fluctuations in load patterns are observed, which complicate accurate forecasting. While existing forecasting models have been developed primarily for mainland power grids, their direct application to Jeju Island has been shown to yield lower accuracy, due to the island’s distinctive demand characteristics. To overcome these limitations, a statistical forecasting model based on similar-day analysis has been developed. In this model, analogous weekdays are selected using key meteorological and calendar variables, and Jeju’s high weather sensitivity along with the impact of behind-the-meter solar generation is incorporated. A case study using real grid data from Jeju Island was conducted. As a result, the proposed model achieved a mean absolute percentage error (MAPE) of 3.24% for hourly demand on the day ahead. This approach is expected to enhance the reliability of power market operations and supply planning, particularly for regions like Jeju Island where conventional forecasting methods are less effective.
본문·목차
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오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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