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
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