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New artificial neural network based direct virtual torque control and direct power control for DFIG in wind energy systems | IEEE Conference Publication | IEEE Xplore

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


Abstract:

This paper presents direct power control (DPC) strategy for controlling power flow, direct virtual torque control (DVTC) strategy for synchronizing double-fed induction g...Show More

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.
Date of Conference: 05-08 December 2011
Date Added to IEEE Xplore: 09 February 2012
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Conference Location: Singapore
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Subscripts

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1.
Lie Xu and Phillip Cartwright, "Direct Active and Reactive Power Control of DFIG for Wind Energy Generation", IEEE Transactions on Energy Conversion, vol. 21, no. 3, September 2006.
2.
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3.
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4.
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5.
Jihen Arbi, Manel Jebali-Ben Ghorbal, Ilhem Slama-Belkhodja and Lotfi Charaabi, "Direct Virtual Torque Control for Doubly Fed Induction Generator Grid Connection", IEEE Transactions on Industrial Electronics, vol. 56, no. 10, October 2009.
6.
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7.
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9.
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References

References is not available for this document.