Neural Network Modeling of a Doubly Fed Induction Generator Wind Turbine System

作     者：LIN Wang XIAOBING Kong XIANGJIE Liu School of Control and Computer engineering North China Electric Power University Beijing P.R.China 102206 

会议名称：《第三十一届中国控制会议》

会议日期：2012年

学科分类：08[工学] 0807[工学-动力工程及工程热物理] 

基　　金：supported by National Natural Science Foundation(NNSF) of China under Grant 60974051 

关 键 词：Neural network modeling doubly-fed induction generator 

摘      要：正A wind power plant is an energy conversion system consisting of wind turbine,rotor,gear and doubly-fed induction generator *** is a complex multivariable system associated with severe nonlinearity,uncertainties and multivariable *** many cases,it is almost impossible to build a mathematical model of the system using conventional analytic *** paper presents our recent work in modeling of a 1.5MW doubly-fed induction *** on-site measurement data,two different structures of neural networks are employed to model the doubly-fed induction *** 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.