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.
학술저널
Full-text XML
오류 신고하기해당 페이지 내 제목·저자·목차·페이지정보가 잘못된 경우 알려주세요!
초록·키워드
The number of wind farms in Korea is expected to increase due to the pressure of the post-2020 climate targets. However, this may result in some difficulties for the operation and expansion planning of our power system, due to the characteristics of wind energy, such as its intermittency and non-dispatchability. Generally, a decrease in these characteristics is called the ‘smoothing effect’. In this study, the smoothing effect is defined as a decrease in the variability of the power output. it is well known that the variability of the power output from wind farms is reduced when more wind farms are integrated into the system. A quantitative analysis of the smoothing effect is necessary to predict the variability of wind energy and this can help the power system to be operated or planned more efficiently. In this study, the methodologies of previous studies were applied to 6 wind farms in Korea. As a result, it was found that the smoothing effect in spring and winter was more effective than that in summer and fall and increased with increasing distance between the wind farms. The expected variability obtained from the equation estimated using the quantitative analysis of the smoothing effect was analogous to the variability of the aggregate power output from the entire wind farms in the power system.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2018-505-001800821
