Adaptive Control of a Variable-Speed Variable-Pitch Wind Turbine Using Radial-Basis Function Neural Network

In order to be economically competitive, various control systems are used in large scale wind turbines. These systems enable the wind turbine to work efficiently and produce the maximum power output at varying wind speed. In this paper, an adaptive control based on radial-basis-function neural network (NN) is proposed for different operation modes of variable-speed variable-pitch wind turbines including torque control at speeds lower than rated wind speeds, pitch control at higher wind speeds and smooth transition between these two modes The adaptive NN control approximates the nonlinear dynamics of the wind turbine based on input/output measurements and ensures smooth tracking of the optimal tip-speed-ratio at different wind speeds. The robust NN weight updating rules are obtained using Lyapunov stability analysis. The proposed control algorithm is first tested with a simplified mathematical model of a wind turbine, and then the validity of results is verified by simulation studies on a 5 MW wind turbine simulator.

[1]  Jonathan Charles Berg.  Wind Turbine Modeling and Control Investigation. , 2007 .

[2]  R. Sanner,et al.  Gaussian Networks for Direct Adaptive Control , 1991 .

[3]  J. Farrell,et al.  Adaptive Approximation Based Control: General Theory , 2006 .

[4]  B. Karimi,et al.  Robust Adaptive Control of Nonaffine Nonlinear Systems Using Radial Basis Function Neural Networks , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[5]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[6]  R.G. Harley,et al.  Wind Speed Estimation Based Sensorless Output Maximization Control for a Wind Turbine Driving a DFIG , 2008, IEEE Transactions on Power Electronics.

[7]  Jakob Stoustrup,et al.  Estimation of effective wind speed , 2007 .

[8]  S. Żak.  Systems and control , 2002 .

[9]  Bimal K. Bose,et al.  Fuzzy logic based intelligent control of a variable speed cage machine wind generation system , 1995 .

[10]  J. Jonkman,et al.  Definition of a 5-MW Reference Wind Turbine for Offshore System Development , 2009 .

[11]  Henrik Bindner,et al.  Sensor Selection and State Estimation for Wind Turbine Controls , 2007 .

[12]  Miguel Angel Mayosky,et al.  Direct adaptive control of wind energy conversion systems using Gaussian networks , 1999, IEEE Trans. Neural Networks.

[13]  H. Jafarnejadsani,et al.  Adaptive control of a variable-speed variable-pitch wind turbine using RBF neural network , 2012, 2012 IEEE Electrical Power and Energy Conference.

[14]  Jason Jonkman,et al.  FAST User's Guide , 2005 .

[15]  Kellen Petersen August.  Real Analysis , 2009 .

[16]  Ahmet Serdar Yilmaz,et al.  Pitch angle control in wind turbines above the rated wind speed by multi-layer perceptron and radial basis function neural networks , 2009, Expert Syst. Appl..

[17]  F. Bianchi,et al.  Wind turbine control systems , 2006 .

[18]  B. Jonkman,et al.  TurbSim User's Guide , 2005 .

[19]  A. Bakhshai,et al.  A new adaptive control algorithm for maximum power point tracking for wind energy conversion systems , 2008, 2008 IEEE Power Electronics Specialists Conference.

[20]  Houria Siguerdidjane,et al.  Nonlinear control with wind estimation of a DFIG variable speed wind turbine for power capture optimization , 2009 .