scholarly journals Novel Modified Elman Neural Network Control for PMSG System Based on Wind Turbine Emulator

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Chih-Hong Lin
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Permanent Magnet ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Generator ◽  
Power Converter ◽  
Network Control ◽  
Elman Neural Network ◽  
Wind Speeds ◽  
Ac Power

The novel modified Elman neural network (NN) controlled permanent magnet synchronous generator (PMSG) system, which is directly driven by a permanent magnet synchronous motor (PMSM) based on wind turbine emulator, is proposed to control output of rectifier (AC/DC power converter) and inverter (DC/AC power converter) in this study. First, a closed loop PMSM drive control based on wind turbine emulator is designed to generate power for the PMSG system according to different wind speeds. Then, the rotor speed of the PMSG, the voltage, and current of the power converter are detected simultaneously to yield better power output of the converter. Because the PMSG system is the nonlinear and time-varying system, two sets online trained modified Elman NN controllers are developed for the tracking controllers of DC bus power and AC power to improve output performance of rectifier and inverter. Finally, experimental results are verified to show the effectiveness of the proposed control scheme.

Voltage Control of PM Synchronous Generator System Using Recurrent Wavelet Neural Network Controller

2013 ◽  
Vol 284-287 ◽  
pp. 2346-2350
Author(s):  
Chih Hong Lin ◽  
Chih Peng Lin
Keyword(s):  
Neural Network ◽  
Permanent Magnet ◽  
Learning Algorithm ◽  
Synchronous Generator ◽  
Power Converter ◽  
Wavelet Neural Network ◽  
Direct Drive ◽  
Generator System ◽  
Neural Network Controller ◽  
Three Phase

A recurrent wavelet neural network (RWNN) controller is proposed to control output voltages for a permanent magnet synchronous motor (PMSM) direct drive three-phase permanent magnet synchronous generator (PMSG) system at stand-alone power application in this paper. First, the field-oriented mechanism is implemented for the control of the PMSG system. Then, a rectifier (AC/DC power converter) and an inverter (DC/AC power converter) are developed to convert the electric power generated by a three-phase PMSG system. Moreover, two online trained RWNNs using backpropagation learning algorithm are developed as the regulating controllers for both the DC-link voltage of the rectifier and the AC line voltage of the inverter. Finally, to show the effectiveness of the proposed controller, comparative studies with PI controller are demonstrated by experimental results.

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