DocumentCode :
3260315
Title :
New artificial neural network based direct virtual torque control and direct power control for DFIG in wind energy systems
Author :
Dzung, Phan Quoc ; Bao, Anh Nguyen ; Lee, Hong Hee
Author_Institution :
Fac. of Electr. & Electron. Eng., HCMC Univ. of Technol., Ho Chi Minh City, Vietnam
fYear :
2011
fDate :
5-8 Dec. 2011
Firstpage :
219
Lastpage :
227
Abstract :
This paper presents direct power control (DPC) strategy for controlling power flow, direct virtual torque control (DVTC) strategy for synchronizing double-fed induction generator (DFIG) with grid and voltage oriented control (VOC) for controlling voltage of link capacitor. All strategies are implemented on artificial neural network (ANN) controller to decrease the time of calculation in comparison with the conventional DSP control system. The essence of three strategies is selection appropriate voltage vectors on the rotor side converter. The network is divided in two types: fixed weight and supervised models. The simulation results on a 4-kW machine are explained using MATLAB/SIMULINK together with the Neural Network Toolbox.
Keywords :
asynchronous generators; load flow control; machine control; microcontrollers; neurocontrollers; power control; power convertors; power generation control; torque control; voltage control; wind power plants; ANN controller; DFIG; DPC strategy; DSP control system; DVTC strategy; Matlab-Simulink; VOC; artificial neural network controller; direct power control; direct virtual torque control; double-fed induction generator; link capacitor voltage; neural network toolbox; power 4 kW; power flow control; rotor side converter; voltage oriented control; wind energy systems; Artificial neural networks; Hysteresis; Neurons; Rotors; Stators; Torque; Training; Artificial Neural Network (ANN); Direct Power Control (DPC); Direct Virtual Torque Control (DVTC); Doubly-Fed Induction Generator (DFIG); Grid-side converter (GSC); Rotor-side converter (RSC);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Electronics and Drive Systems (PEDS), 2011 IEEE Ninth International Conference on
Conference_Location :
Singapore
ISSN :
2164-5256
Print_ISBN :
978-1-61284-999-7
Electronic_ISBN :
2164-5256
Type :
conf
DOI :
10.1109/PEDS.2011.6147250
Filename :
6147250
Link To Document :
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