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New artificial neural network based direct virtual torque control and direct power control for DFIG in wind energy systems

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3 Author(s)
Phan Quoc Dzung ; Faculty of Electrical & Electronic Engineering, HCMC University of Technology, Ho Chi Minh City, Vietnam ; Anh Nguyen Bao ; Hong Hee Lee

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.

Published in:

Power Electronics and Drive Systems (PEDS), 2011 IEEE Ninth International Conference on

Date of Conference:

5-8 Dec. 2011