NDLI: Neural network modeling of a doubly fed induction generator wind turbine system

Content Provider	IEEE Xplore Digital Library
Author	Lin Wang Xiaobing Kong Xiangjie Liu
Copyright Year	2012
Description	Author affiliation: School of Control and Computer engineering, North China Electric Power University, Beijing, P.R. China, 102206 (Lin Wang; Xiaobing Kong; Xiangjie Liu)
Abstract	A wind power plant is an energy conversion system consisting of wind turbine, rotor, gear and doubly-fed induction generator respectively. It is a complex multivariable system associated with severe nonlinearity, uncertainties and multivariable couplings. In many cases, it is almost impossible to build a mathematical model of the system using conventional analytic methods. The paper presents our recent work in modeling of a 1.5MW doubly-fed induction generator. Using on-site measurement data, two different structures of neural networks are employed to model the doubly-fed induction generator. The method is compared with the typical recursive least squares (RLS) method, which obviously demonstrated the merit of efficiency of the neural networks in modeling of the 1.5MW doubly-fed induction generator.
Starting Page	1871
Ending Page	1876
File Size	327769
Page Count	6
File Format	PDF
ISBN	9781467325813
ISSN	21612927
e-ISBN	9789881563811
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Assoc of Automati
Subject Keyword	Reactive power doubly-fed induction generator modeling Induction generators Neural networks Rotors Stators Data models Neural network Mathematical model
Content Type	Text
Resource Type	Article

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