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A Novel Sensorless MPPT for Wind Turbine Generators Using Very Sparse Matrix Converter Based on Hybrid Intelligent Control


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DOI: https://doi.org/10.15866/iree.v10i2.2980

Abstract


The maximum power of Wind Turbine Generators (WTGs) can be obtained by adjusting the rotor speed at the optimum Tip Speed Ratio (TSR), so that the Maximum Power Point Tracking (MPPT) algorithms is needed to obtain the reference speed. The conventional MPPT such as Pertubartion and Observation (PO), a reference speed is determined by a constant step. Choosing appropriate the step size is a problem, because it may cause problems in the response and the oscillations at the maximum point. To solve this problem, the flexible step size is proposed by using Least Squares-Support Vector Machine (LS-SVM).  Then, the Adaptive Type-2 Fuzzy Sliding Mode Control (AFSMOC) is applied to control a rotor speed at a reference speed through Very Sparse Matrix Converter (VSMC). To replace a rotor speed sensors, the Model Reference Adaptive System (MRAS) observers is proposed. The simulation results shows that the MPPT based LS-SVM is remarkably faster and more efficient than the PO algorithm. LS-SVM can generate the flexible steps with the accuracy of classification 94.29 %. The AFSMOC can regulating the rotor speed at reference point, so that the maximum power can be achieved at all wind speeds.
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Keywords


Wind Turbine Generator; MPPT; LS-SVM; Type-2 Fuzzy Sliding Mode Control; Very Sparse Matrix Converter

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References


Y. Chen, P. Pillay, A. Khan, PM Wind Generator Topologies, IEEE Trans. Industry Applications, vol. 41, n. 6, November/ December 2005, pp. 1619 – 1626.
http://dx.doi.org/10.1109/tia.2005.858261

Singh, N., Agrawal, V., A review on power quality enhanced converter of permanent magnet synchronous wind generator, (2013) International Review of Electrical Engineering (IREE), 8 (6), pp. 1681-1693.

Uygun, D., Ocak, C., Buyukbicakci, E., Design, analysis and experimental verification of an efficient 2 kW permanent magnet synchronous generator for WPAs, (2013) International Review of Electrical Engineering (IREE), 8 (2), pp. 603-607.

A. Meharrar, M. Tioursi, M. Hatti, A. B. Stambouli, A Variable Speed Wind Generator Maximum Power Tracking Based on Adaptative Neuro Fuzzy Inference System, Expert Systems with Applications, vol. 38, 2011, pp. 7659 – 7664.
http://dx.doi.org/10.1016/j.eswa.2010.12.163

M. E. Haque, M. Negnevitsky, K. M. Muttaqi, A Novel Control Strategy for a Variable-Speed Wind Turbine With a PMSG, IEEE Trans. Industry Applications, vol. 46, n. 1, January/February 2010, pp. 331 – 339.
http://dx.doi.org/10.1109/tia.2009.2036550

R. Melício, V.M.F. Mendes, J.P.S. Catalão, Comparative study of power converter topologies and control strategies for the harmonic performance of variable-speed wind turbine generator systems, Energy, vol. 36, 2011, pp. 520 – 529.
http://dx.doi.org/10.1016/j.energy.2010.10.012

J. W. Kolar, T. Friedli, J. Rodriguez, and Patrick W, Review of Three-Phase PWM AC–AC Converter Topologies, IEEE Trans. Industrial Electronics, vol. 58, n. 11, 2009, pp. 4988 – 5006.
http://dx.doi.org/10.1109/tie.2011.2159353

J. W. Kolar, F. Schafmeister, S. D. Round, H. Ertl, Novel Three-Phase AC–AC Sparse Matrix Converters, IEEE Trans. Power Electronics, vol. 22, n. 5, September 2007, pp. 1649 – 1661.
http://dx.doi.org/10.1109/tpel.2007.904178

M. Aner, E. Nowicki, D. Wood, Employing a Very Sparse Matrix Converter for Improved Dynamics of Grid-Connected Variable Speed Small Wind Turbines, IEEE Power and Energy Conference at Illinois (PECI), February 24-25, 2012, Champaign, Illionis USA.
http://dx.doi.org/10.1109/peci.2012.6184584

L. G. Gonzalez, E. Figueres, G. Garcera, O. Carranza, Maximum Power Point Tracking with Reduced Mechanical Stress Applied to Wind Energy Conversion Systems, Applied Energy, vol. 87, 2010, pp. 2304 – 2312.
http://dx.doi.org/10.1016/j.apenergy.2009.11.030

S. M. R. Kazmi, H. Goto, H. J. Guo, O. Ichinokura, A Novel Algorithm for Fast and Efficient Speed Sensorless Maximum Power Point Tracking in Wind Energy Conversion Systems, IEEE Trans. Industrial Electronics, vol. 58, n. 1, January 2011, pp. 29 – 36.
http://dx.doi.org/10.1109/tie.2010.2044732

W. M. Lin, C. M. Hong, Intelligent Approach to Maximum Power Point Tracking Control Strategy for Variable Speed Wind Turbine Generation System, Energy, vol. 35, 2010, pp. 2440 – 2447.
http://dx.doi.org/10.1016/j.energy.2010.02.033

C. Y. Lee, P. H. Chen, Y. X. Shen, Maximum Power Point Tracking (MPPT) System of Small Wind Power Generator Using RBFNN Approach, Expert Systems with Applications, vol. 38, 2011, pp. 12058 – 12065.
http://dx.doi.org/10.1016/j.eswa.2011.02.054

H. Li, K. L. Shi, P. G. McLaren, Neural-Network-Based Sensorless Maximum Wind Energy Capture With Compensated Power Coefficient, IEEE Trans. Industry Applications, vol. 41, n. 6, November/December 2005, pp. 1548 – 1556.
http://dx.doi.org/10.1109/tia.2005.858282

J. A. K. Suykens, J. Vandewalle, Least squares support vector machine classifiers, Neural Processing Letters, vol. 9, no. 3, 1999, pp. 293–300.
http://dx.doi.org/10.1023/b:mach.0000008082.80494.e0

F. F. M. El-Sousy, Robust Wavelet Neural Network Sliding Mode Control System for Permanent Magnet Synchronous Motor Drive, IET Elect Power Applications, vol. 5, n. 1, 2011, pp. 113 - 132.
http://dx.doi.org/10.1049/iet-epa.2009.0229

Golshani, A., Alizadeh Bidgoli, M., Bathaee, S.M.T., Design of optimized sliding mode control to improve the dynamic behavior of PMSG wind turbine with NPC back-to-back converter, (2013) International Review of Electrical Engineering (IREE), 8 (4), pp. 1170-1180.

X. Yu, O. Kaynak, Sliding-Mode Control With Soft Computing: A Survey, IEEE Trans. Industrial Electronics, vol. 56, n. 9, September 2009, pp. 3275 – 3285.
http://dx.doi.org/10.1109/tie.2009.2027531

Q. Liang, J. M. Mendel, Interval Type-2 Fuzzy Logic Systems: Theory and Design, IEEE Trans. Fuzzy Systems, vol. 8, n. 5, October 2000, pp. 535 – 550.
http://dx.doi.org/10.1109/91.873577

J. M. Mendel, R. I. John, F. Liu, Interval Type-2 Fuzzy Logic Systems Made Simple, IEEE Trans. Fuzzy Systems, vol. 14, n. 6, December 2006, pp. 808 – 821.
http://dx.doi.org/10.1109/tfuzz.2006.879986

V. N. Vapnik, An overview of statistical learning theory, IEEE Trans. Neural Networks, vol. 10, no. 5, 1999, pp. 988–999.
http://dx.doi.org/10.1109/72.788640

J. A. K. Suykens, J. Vandewalle, Multiclass Least squares support vector machine classifiers, International Joint Conference on Neural Networks, July 10-16, 1999, Washington DC, USA.
http://dx.doi.org/10.1109/ijcnn.1999.831072

T. V. Gestel, J. A. K. Suykens, B. Baesens, Benchmarking LS-SVM Classifiers, Machine Learning, Vol. 54, 2004, pp. 5–32.
http://dx.doi.org/10.1023/b:mach.0000008082.80494.e0

Z. Noumir, P. Honeine, C. Richard, Multi-Class Least Squares Classification at Binary-Classification Complexity, Statistical Signal Processing Workshop, June 28-30, 2011, Nice, France
http://dx.doi.org/10.1109/ssp.2011.5967680

T. Van Gestel, J. A. K. Suykens,G . Lanckriet, Multiclass LS-SVMs: Moderated Outputs and Coding-Decoding Schemes, Neural Processing Letters, Vol. 15, 2002, pp. 45-58.

H. Zhang, W. Shi, K. Liu, Fuzzy-Topology-Integrated Support Vector Machine for Remotely Sensed Image Classification , IEEE Trans. Geoscience and Remote Sensing, Vol. 50, No. 3, March 2012, pp. 850-862.
http://dx.doi.org/10.1109/tgrs.2011.2163518

J. Brahmi, L. Krichen, A. Ouali, A comparative study between three sensorless control strategies for PMSG in WECS, Applied Energy, Vol. 86, 2009, pp. 1565 – 1573.
http://dx.doi.org/10.1016/j.apenergy.2008.11.010

Hamdi, N., Bouzid, A., New control of a doubly-fed induction generator of a variable speed wind turbine with Ku transformation, (2013) International Review of Automatic Control (IREACO), 6 (2), pp. 183-188.

Sundeep, S., Madhusudhana Rao, G., Sankar Ram, B.V., An ANN control of maximum power point tracking for grid connected wind machines, (2014) International Review of Automatic Control (IREACO), 7 (1), pp. 52-59.

Gharedaghi, F., Jamali, H., Deysi, M., Khalili, A., Maximum power point tracking of variable speed wind generation system connected to Permanent Magnet Synchronous generator, (2011) International Review on Modelling and Simulations (IREMOS), 4 (3), pp. 1044-1049.

Kareim, A.A., Mansor, M.B., Support vector machine for MPPT efficiency improvement in photovoltaic system, (2013) International Review of Automatic Control (IREACO), 6 (2), pp. 177-182.

Li, Y., Ma, P., Yu, L., LS-SVM soft sensing based on hybrid particle swarm optimization, (2012) International Review on Computers and Software (IRECOS), 7 (1), pp. 283-289.


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