Real time simulation of nonlinear generalized predictive control for wind energy conversion system with nonlinear observer.

In order to make a wind power generation truly cost-effective and reliable, an advanced control techniques must be used. In this paper, we develop a new control strategy, using nonlinear generalized predictive control (NGPC) approach, for DFIG-based wind turbine. The proposed control law is based on two points: NGPC-based torque-current control loop generating the rotor reference voltage and NGPC-based speed control loop that provides the torque reference. In order to enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. Finally, a real-time simulation is carried out to illustrate the performance of the proposed controller.

[1]  António P. Martins,et al.  Nonlinear control of the doubly-fed induction generator in wind power systems , 2010 .

[2]  M. Yamamoto,et al.  Active and reactive power control of doubly-fed wound rotor induction generator , 1990, 21st Annual IEEE Conference on Power Electronics Specialists.

[3]  F. Poitiers,et al.  Advanced control of a doubly-fed induction generator for wind energy conversion , 2009 .

[4]  Tayeb Allaoui,et al.  Robust control of doubly fed induction generator for stand-alone applications , 2010 .

[5]  J. Rodriguez,et al.  Predictive Torque Control for Inverter-Fed Induction Machines , 2005, IEEE Transactions on Industrial Electronics.

[6]  Heng Nian,et al.  Dynamic Modeling and Improved Control of DFIG Under Distorted Grid Voltage Conditions , 2011, IEEE Transactions on Energy Conversion.

[7]  J. Richalet,et al.  Industrial applications of model based predictive control , 1993, Autom..

[8]  Peter J. Gawthrop,et al.  Optimal control of nonlinear systems: a predictive control approach , 2003, Autom..

[9]  Barry W. Williams,et al.  Predictive Current Control of Doubly Fed Induction Generators , 2009, IEEE Transactions on Industrial Electronics.

[10]  Tomonobu Senjyu,et al.  Output power leveling of wind turbine Generator for all operating regions by pitch angle control , 2006 .

[11]  Mitja Nemec,et al.  Predictive Torque Control of Induction Machines using Immediate Flux Control , 2005, IEEE International Conference on Electric Machines and Drives, 2005..

[12]  Whei-Min Lin,et al.  Fuzzy neural network output maximization control for sensorless wind energy conversion system , 2010 .

[13]  F. Valenciaga.  Second order sliding power control for a variable speed-constant frequency energy conversion system , 2010 .

[14]  Didier Dumur,et al.  Two cascaded nonlinear predictive controls of induction motor , 2003, Proceedings of 2003 IEEE Conference on Control Applications, 2003. CCA 2003..

[15]  Peter J. Gawthrop,et al.  Nonlinear PID predictive controller , 1999 .

[16]  Heng Nian,et al.  Direct Active and Reactive Power Regulation of DFIG Using Sliding-Mode Control Approach , 2010, IEEE Transactions on Energy Conversion.

[17]  M Soliman,et al.  Multiple Model Predictive Control for Wind Turbines With Doubly Fed Induction Generators , 2011, IEEE Transactions on Sustainable Energy.

[18]  D. J. Ballance,et al.  MIMO nonlinear PID predictive controller , 2002 .

[19]  David J. Atkinson,et al.  Stator-flux-oriented control of a doubly-fed induction machine with and without position encoder , 2000 .

[20]  Werner Leonhard,et al.  Control of Electrical Drives , 1990 .

[21]  S. Joe Qin,et al.  A survey of industrial model predictive control technology , 2003 .

[22]  Lie Xu,et al.  Dynamic Modeling and Control of DFIG-Based Wind Turbines Under Unbalanced Network Conditions , 2007, IEEE Transactions on Power Systems.

[23]  S. M. Islam,et al.  Impacts of Symmetrical and Asymmetrical Voltage Sags on DFIG-Based Wind Turbines Considering Phase-Angle Jump, Voltage Recovery, and Sag Parameters , 2011, IEEE Transactions on Power Electronics.