메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Daniel Thenathayalan (Soongsil University) Ashraf Ahmed (Soongsil University) Byung-Min Choi (Soongsil University) Jeong-Hyun Park (Soongsil University) Joung-Hu Park (Soongsil University)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.12 No.2
발행연도
2017.3
수록면
790 - 802 (13page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
This paper proposes the modeling and control strategy to track the MPPs of hybrid PV and Wind power systems, using a new dual input boost converter. The dual input power conditioning system with an independent MPPT control scheme is introduced with minimum number of circuit elements in order to reduce the switching loss, size and cost of the system. Since the operating conditions for the PV and Wind power systems are very distinct from each other, an efficient and superior control system is required to track the MPPs of both renewable sources with the use of a simply-structured single-ended single-inductor converter. The design of Power-Conditioning System (PCS) and detail control strategy are presented in this paper. To provide independent tracking of MPPs, a variable duty-cycle control strategy is employed for the wind system and a variable frequency strategy is employed for the PV system. Finally, the proposed dual-input converter for hybrid power conditioning system is implemented and the hardware test results are presented. From the hardware experiment, it is concluded that the proposed system successfully tracks the MPPs of both of the renewable power systems independently.

목차

Abstract
1. Introduction
2. Proposed Dual Input Single-ended PV-Wind Hybrid Power Conditioning System
3. Small Signal Modeling
4. Transient Analysis
5. Hardware Result
6. Conclusion
References

참고문헌 (32)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

이 논문과 함께 이용한 논문

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2017-560-002172707