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
Ghulam Sarwar Kaloi (Shanghai Jiao Tong University) Jie Wang (Shanghai Jiao Tong University) Mazhar Hussain Baloch (Mehran University of Engineering and Technology)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.11 No.5
발행연도
2016.9
수록면
1,137 - 1,146 (10page)

이용수

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

초록· 키워드

오류제보하기
This paper presents a dynamic modeling and control of doubly fed induction-generator (DFIG) based variable speed wind-turbine. The dynamic model of DFIG is incorporated with all system components which provide simple design and controls. The penetration of wind power is increasing into electrical networks, which necessitates more comprehensive studies to recognize the interaction between the wind farms and the power grid. This paper presents the dynamic model of a DFIG based wind turbine connected to the grid system in the dq-synchronous reference frame. In this article, the feedback linearization method has proposed a controller in order to reduce the oscillation and stabilize the wind turbine system parameters based on feedback linearization concepts. Based on the nonlinear control system, the proposed approach is applied to the rotor side converter and grid side converter. The damping of the DFIG is improved in transient response. In addition, the oscillation of the stator current and DC link voltage during the generator voltage dip are reduced. To the best of author’s knowledge, the proposed control outcomes compared with conventional controller verified the effectiveness, having better performance through simulation tool Matlab.

목차

Abstract
1. Introduction
2. Wind Turbine Model
3. Nonlinear Dynamic Modeling of DFIG Wind Energy System
4. Proposed Controller Design for a DFIG Wind Turbine Generator
5. Simulation Results and Discussion
6. Conclusion and Future work
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

UCI(KEPA) : I410-ECN-0101-2017-560-000981648