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

摘要：

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.

关键词： Neural network modeling doubly-fed induction generator

作者: LIN Wang XIAOBING Kong XIANGJIE Liu

作者单位: School of Control and Computer engineering, North China Electric Power University, Beijing, P.R.China, 102206

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 1871-1876

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）