High performances of Grid-connected DFIG based on Direct Power Control with Fixed Switching Frequency via MPPT Strategy using MRAC and Neuro-Fuzzy Control
Abstract
This paper presents high performance improved direct power control (DPC) based on model reference adaptivecontrol (MRAC) and neuro-fuzzy control (NFC) for grid connected doubly fed induction generator (DFIG), to overcomethe drawbacks of conventional DPC which was based only on PID controllers, namely the speed/efficiencytrade-off and divergence from peak power under fast variation of wind speed. A mathematical model of DFIGimplemented in the d-q reference frame is achieved. Then, a direct power control algorithm for controlling rotorcurrents of DFIG is incorporated using PID controllers, and space-vector modulation (SVM) is used to determinea fixed switching frequency. The condition of the stator side power factor is controlled at unity level via MPPTstrategy. The MRAC which is based on DPC is investigated instead of PID regulators. Also, the performancesof NFC based on DPC are tested and compared to those achieved using MRAC controller. The results obtainedin the Matlab/Simulink environment using robustness tests show that the NFC is efficient, has superior dynamicperformance and is more robust during parameter variations.References
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[9] E.G. Shehata. Sliding mode direct power control of RSC for DFIGs driven by variable speed wind turbines. Alexandria Engineering Journal. 2015
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Power Electronics, Vol. 29, No. 2, 2014
[2] Jafar Mohammadi, SadeghVaez-Zadeh, Saeed Afsharnia, and Ehsan Daryabeigi, “A Combined Vector and Direct Power Control for DFIG-Based
Wind Turbines”, IEEE Transactions On Sustainable Energy, Vol. 5, No. 3, 2014
[3] Jafar Mohammadi, SadeghVaez-Zadeh, Saeed Afsharnia, and Ehsan Daryabeigi, “A Combined Vector and Direct Power Control for DFIG-Based Wind Turbines”, IEEE Transactions On Sustainable Energy, Vol. 5, No. 3, 2014
[4] Murali M. Baggu, Badrul H. Chowdhury, and Jonathan W. Kimball, “Comparison of Advanced Control Techniques for Grid Side Converter of
Doubly-Fed Induction Generator Back-to-Back Converters to Improve Power Quality Performance During Unbalanced Voltage Dips”, IEEE Journal
Of Emerging And Selected Topics In Power Electronics, Vol. 03, No. 2, 2015
[5] Michael K. Bourdoulis, and Antonio T. Alexandridis. Direct Power Control of DFIG Wind Systems Based on Nonlinear Modeling and
Analysis, IEEE Journal of Emerging and Selected Topics in Power Electronics, Vol. 2, No. 4, 2014
[6] Bhim Singh, and N. K. Swami Naidu. Direct Power Control of Single VSC-Based DFIG without Rotor Position Sensor, IEEE Transactions On Industry Applications, Vol. 50, No. 6, 2014
[7] Jiefeng Hu, Jianguo Zhu, and David G. Dorrell. Predictive Direct Power Control of Doubly Fed Induction Generators Under Unbalanced Grid
Voltage Conditions for Power Quality Improvement, IEEE Transactions on Sustainable Energy, Vol. 6, No. 3, 2015
[8] Jiefeng Hu, Jianguo Zhu and David G. Dorrell. Model-predictive direct power control of doublyfed induction generators under unbalanced grid
voltage conditions in wind energy applications. IET Renewable Power Generation, vol. 8, pp. 687- 695, 2015
[9] E.G. Shehata. Sliding mode direct power control of RSC for DFIGs driven by variable speed wind turbines. Alexandria Engineering Journal. 2015
[10] S. Taraft , D. Rekioua, D. Aouzellag and S. Bacha. A proposed strategy for power optimization of a wind energy conversion system connected to the grid. Energy Conversion and Management.2015
[11] M’hamed Doumi, Abdel Ghani Aissaoui, Ahmed Tahour, Mohamed Abid, “Commande Adaptative D’un Système Éolien”, Rev. Roum. Sci. Techn. Électrotechn. Et Énerg., 60, 1, pp. 99–110, 2015
[12] Badre Bossoufi, Mohammed Karim, Ahmed Lagrioui, Mohammed Taoussi, and Aziz Derouich. Observer backstepping control of DFIG-Generators for wind turbines variable-speed: FPGA-based
implementation. Renewable Energy, 2015
[13] Yacine Daili, Jean-Paul Gaubert and LazharRahmani. Implementation of a new maximum power point tracking control strategy for small
wind energy conversion systems without mechanical sensors. Energy Conversion and Management. Vol 97, pp. 298–306, 2015
[14] Tejavathu Ramesh n, AnupKumarPanda, S.ShivaKumar. Type-2 fuzzy logic control based MRAS speed estimator for speed sensorless direct
torque and flux control of an induction motor drive. ISATransactions, 2015
[15] Youcef Bekakra and Djilani Ben Attous, “DFIG Sliding Mode Control Driven by Wind Turbine with Using a SVM Inverter for Improve the Quality
of Energy Injected into the Electrical Grid”, ECTI transactions on electrical Eng., electronics, and communications vol.11, no.1, pp 36-75, 2013
[16] G. Abad J. Lopez, M.A. Rodrıguez, L. Marroyo, G. Iwanski, “Doubly fed induction machine: modeling and control for wind energy generation”, IEEE press Series on Power Engineering, 2011
[17] Y. Lei, A. Mullane, G. Lightbody, R. Yacamini, “Modeling of the wind turbine with a doubly-fed induction generator for grid integration studies”,
IEEE Trans. Energy Conversion, 21, 1, pp. 257-264, 2006
[18] Astrom, K.J., Wittenmark, B.: Adaptive Control. Addison Wesley, 1995
[19] Khalil, H.K.: Nonlinear systems. Macmillan, New York, 1992
[20] A. Chaiba, R. Abdessemed, M. L. Bendaas, A. Dendouga “Performances Of Torque Tracking Control For Doubly Fed Asynchronous Motor Using Pi And Fuzzy Logic Controllers”. Journal of Electrical Engineering, 2005
[21] A. Chaiba, R. Abdessemed M. L. Bendaas, L. A Hybrid Intelligent Control based Torque Tracking approach for Doubly Fed Asynchronous Motor (DFAM) drive, Journal of Electrical Systems. pp. 262-272, 2012
[22] Elmas, C., Ustun, O. & Sayan, H. H, A neurofuzzy controller for speed control of a permanent magnet synchronous motor drive.. Expert Systems
with Applications, 34.1, pp. 657-664, 2008.
[23] Gökbulut, M., Dandil, B; & Bal, C., A hybrid neuro-fuzzy controller for brushless DC motors. Lecture Notes in Computer Science, 3949. pp. 125-132, 2006
Published
2016-04-04
How to Cite
AMRANE, Fayssal; CHAIBA, Azeddine; MEKHILEF, Saad.
High performances of Grid-connected DFIG based on Direct Power Control with Fixed Switching Frequency via MPPT Strategy using MRAC and Neuro-Fuzzy Control.
Journal of Power Technologies, [S.l.], v. 96, n. 1, p. 27--39, apr. 2016.
ISSN 2083-4195.
Available at: <https://papers.itc.pw.edu.pl/index.php/JPT/article/view/757>. Date accessed: 26 apr. 2024.
Issue
Section
Renewable and Sustainable Energy
Keywords
Model reference adaptive control (MRAC), Neuro-Fuzzy Control (NFC), Wind energy conversion system (WECS), Doubly fed induction generator (DFIG), Direct power control (DPC), Space vector modulation (SVM), Maximum power point tracking (MPPT).
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