Artificial neural network-based maximum power point tracking control for variable speed wind energy conversion systems

A new maximum power point tracking (MPPT) controller using artificial neural networks (ANN) for variable speed wind energy conversion system (WECS) is proposed. The algorithm uses Jordan recurrent ANN and is trained online using back propagation. The inputs to the networks are the instantaneous output power, maximum output power, rotor speed and wind speed, and the output is the rotor speed command signal for the WECS. The network output after a time step delay is used as the feed-back signal completing the Jordan recurrent ANN. Simulation is carried out in order to verify the performance of the proposed algorithm.

[1]  K. Tan,et al.  Optimum control strategies in energy conversion of PMSG wind turbine system without mechanical sensors , 2004, IEEE Transactions on Energy Conversion.

[2]  Bong-Hwan Kwon,et al.  A line-voltage-sensorless synchronous rectifier , 1999 .

[3]  Adel M. Sharaf,et al.  A rule-based fuzzy logic controller for a PWM inverter in a stand alone wind energy conversion scheme , 1993 .

[4]  Richard D. Braatz,et al.  On the "Identification and control of dynamical systems using neural networks" , 1997, IEEE Trans. Neural Networks.

[5]  Liuchen Chang,et al.  An intelligent maximum power extraction algorithm for inverter-based variable speed wind turbine systems , 2004, IEEE Transactions on Power Electronics.

[6]  Bimal K. Bose,et al.  Design and performance evaluation of a fuzzy logic based variable speed wind generation system , 1996 .

[7]  二见基生,et al.  Variable-speed wind power generation system , 2007 .

[8]  Hui Li,et al.  Neural-network-based sensorless maximum wind energy capture with compensated power coefficient , 2004, IEEE Transactions on Industry Applications.

[9]  J. D. van Wyk,et al.  A study of a wind power converter with micro-computer based maximal power control utilising an over-synchronous electronic scherbius cascade , 1992 .

[10]  Dong-Choon Lee,et al.  Variable speed wind power generation system based on fuzzy logic control for maximum output power tracking , 2004, 2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551).

[11]  Torbjörn Thiringer,et al.  Control by variable rotor speed of a fixed-pitch wind turbine operating in a wide speed range , 1993 .

[12]  J.H.R. Enslin,et al.  Performance optimization for doubly-fed wind power generation systems , 1998, Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242).

[13]  Hassan K. Khalil,et al.  Adaptive control of a class of nonlinear discrete-time systems using neural networks , 1995, IEEE Trans. Autom. Control..

[14]  Muammer Ermis,et al.  Autonomous wind energy conversion system with a simple controller for maximum-power transfer , 1992 .

[15]  M. Thamodharan,et al.  System management of a wind-energy converter , 2001 .

[16]  Siegfried Heier,et al.  Grid Integration of Wind Energy Conversion Systems , 1998 .

[17]  R. Chedid,et al.  Intelligent control of a class of wind energy conversion systems , 1999 .

[18]  T. Tanaka,et al.  Output control by hill-climbing method for a small scale wind power generating system , 1997 .

[19]  Lennart Söder,et al.  An overview of wind energy-status 2002 , 2002 .

[20]  V. T. Ranganathan,et al.  A Method of Tracking the Peak Power Points for a Variable Speed Wind Energy Conversion System , 2002, IEEE Power Engineering Review.

[21]  M. Chinchilla,et al.  Control of permanent-magnet generators applied to variable-speed wind-energy systems connected to the grid , 2006, IEEE Transactions on Energy Conversion.

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

[23]  F. Martinez Rodrigo,et al.  Sensorless control of a squirrel cage induction generator to track the peak power in a wind turbine , 2002 .

[24]  B. G. Fernandes,et al.  A simple maximum power point tracker for grid connected variable speed wind energy conversion system with reduced switch count power converters , 2003, IEEE 34th Annual Conference on Power Electronics Specialist, 2003. PESC '03..