Squirrel-cage induction generator system using probabilistic fuzzy neural network for wind power applications

Faa Jeng Lin, Kuang Hsiung Tan

研究成果: 書貢獻/報告類型會議論文篇章同行評審

8 引文 斯高帕斯(Scopus)

摘要

An intelligent controlled three-phase squirrel-cage induction generator (SCIG) system for grid-connected power application using probabilistic fuzzy neural network (PFNN) is proposed in this study. First, an AC/DC power converter and a DC/AC power inverter are developed to convert the electric power generated by a three-phase SCIG to power grid. Then, the characteristics of wind turbine emulator are described in detail. Moreover, in order to improve the transient and steady-state responses of the DC-link voltage of the SCIG system, the intelligent PFNN controller is proposed for DC/AC power inverter to replace the conventional proportional-integral (PI) controller. The online trained PFNN using back propagation learning algorithm is implemented as the tracking controller for the DC-link voltage of the DC/AC power inverter. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the SCIG system for grid-connected wind power applications is verified with experimental results.

原文???core.languages.en_GB???
主出版物標題FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems
編輯Adnan Yazici, Nikhil R. Pal, Hisao Ishibuchi, Bulent Tutmez, Chin-Teng Lin, Joao M. C. Sousa, Uzay Kaymak, Trevor Martin
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781467374286
DOIs
出版狀態已出版 - 25 11月 2015
事件IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015 - Istanbul, Turkey
持續時間: 2 8月 20155 8月 2015

出版系列

名字IEEE International Conference on Fuzzy Systems
2015-November
ISSN(列印)1098-7584

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015
國家/地區Turkey
城市Istanbul
期間2/08/155/08/15

指紋

深入研究「Squirrel-cage induction generator system using probabilistic fuzzy neural network for wind power applications」主題。共同形成了獨特的指紋。

引用此