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
학술대회자료
저자정보
Ariya Sangwongwanich (Aalborg University) Yanfeng Shen (University of Cambridge) Andrii Chub (TalTech University) Elizaveta Liivik (Aalborg University) Dmitri Vinnikov (TalTech University) Huai Wang (Aalborg University) Frede Blaabjerg (Aalborg University)
저널정보
전력전자학회 ICPE(ISPE)논문집 ICPE 2019-ECCE Asia
발행연도
2019.5
수록면
1,867 - 1,872 (6page)

이용수

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

초록· 키워드

오류제보하기
The dc-link capacitor is one of the lifetime-limiting components in the photovoltaic (PV) micro-inverters, whose reliability should be evaluated carefully during the design. In micro-inverters, the PV module size (e.g., number of cells) is the parameter that determines the power rating of the PV module. The PV module size employed in the micro-inverter can vary for different manufacturers, and this variation can strongly affect the thermal stress and reliability of the dc-link capacitor in micro-inverters. To address this issue, an experimental-based reliability assessment is carried out in this paper using a twostage micro-inverter where 60-cell and 72-cell PV modules are considered. Three different daily mission profiles are employed during the experimental test. The thermal stress and reliability of the dc-link capacitor under different operating conditions are evaluated together with the energy yield. The results indicate that employing a 60-cell PV module is more beneficial for the micro-inverter, especially during a clear day, where 19 % more energy can be captured during the entire lifespan of the microinverter. Thus, using the 60-cell PV module offers a better tradeoff between the reliability and energy yield of the micro-inverter.

목차

Abstract
I. INTRODUCTION
II. PHOTOVOLTAIC MICRO-INVERTERS
III. RELIABILITY ASSESSMENT OF DC-LINK CAPACITORS
IV. CASE STUDIES
V. CONCLUSIONS
REFERENCES

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

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

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0