Super-twisting sliding mode control for brushless doubly fed reluctance generator based on wind energy conversion system
DOI:
https://doi.org/10.20998/2074-272X.2023.2.13Keywords:
wind power, brushless doubly-fed reluctance generator, maximum power point tracking, vector control, super-twisting algorithmAbstract
Introduction. Recently, wind power generation has grown at an alarming rate in the past decade and will continue to do so as power electronic technology continues to advance. Purpose. Super-twisting sliding mode control for brushless doubly-fed reluctance generator based on wind energy conversion system. Methods. This paper deals with the robust power control of a grid-connected brushless doubly-fed reluctance generator driven by the variable speed wind turbine using a variable structure control theory called sliding mode control. The traditional sliding mode approach produces an unpleasant chattering phenomenon that could harm the system. To eliminate chattering, it is necessary to employ a high-order sliding mode controller. The super-twisting algorithm is one type of nonlinear control presented in order to ensure the effectiveness of the control structure we tested these controllers in two different ways reference tracking, and robustness. Results. Simulation results using MATLAB/Simulink have demonstrated the effectiveness and robustness of the super-twisting sliding mode controller.
References
Fateh L., Ahmed O., Amar O., Abdelhak D., Lakhdar B. Modeling and control of a permanent magnet synchronous generator dedicated to standalone wind energy conversion system. Frontiers in Energy, 2016, vol. 10, no. 2, pp. 155-163. doi: https://doi.org/10.1007/s11708-016-0410-1.
Sami I., Ullah S., Ali Z., Ullah N., Ro J.-S. A Super Twisting Fractional Order Terminal Sliding Mode Control for DFIG-Based Wind Energy Conversion System. Energies, 2020, vol. 13, no. 9, art. no. 2158. doi: https://doi.org/10.3390/en13092158.
Wind power capacity worldwide reaches 744 GW, 147 GW added in 2019. Available at. https://wwindea.org/information-2/statistics-news/ (Accessed 11 May 2022).
Ullah N., Asghar Ali M., Ibeas A., Herrera J. Adaptive Fractional Order Terminal Sliding Mode Control of a Doubly Fed Induction Generator-Based Wind Energy System. IEEE Access, 2017, vol. 5, pp. 21368-21381. doi: https://doi.org/10.1109/ACCESS.2017.2759579.
Ademi S., Jovanovic M. Vector control strategies for brushless doubly-fed reluctance wind generators. 2012 2nd International Symposium On Environment Friendly Energies And Applications, 2012, pp. 44-49. doi: https://doi.org/10.1109/EFEA.2012.6294084.
Hopfensperger B., Atkinson D.J. Doubly-fed AC machines: classification and comparison. European Power Electronics Conference, 2001, vol. 200, no. 1.
Ademi S., Jovanovic M.G. Vector Control Methods for Brushless Doubly Fed Reluctance Machines. IEEE Transactions on Industrial Electronics, 2015, vol. 62, no. 1, pp. 96-104. doi: https://doi.org/10.1109/TIE.2014.2327564.
Jovanovic M. Sensored and sensorless speed control methods for brushless doubly fed reluctance motors. IET Electric Power Applications, 2009, vol. 3, no. 6, pp. 503-513. doi: https://doi.org/10.1049/iet-epa.2008.0227.
Moazen M., Kazemzadeh R., Azizian M.-R. Mathematical proof of BDFRG model under unbalanced grid voltage condition. Sustainable Energy, Grids and Networks, 2020, vol. 21, art. no. 100327. doi: https://doi.org/10.1016/j.segan.2020.100327.
Betz R.E., Jovanovic M.G. Theoretical analysis of control properties for the brushless doubly fed reluctance machine. IEEE Transactions on Energy Conversion, 2002, vol. 17, no. 3, pp. 332-339. doi: https://doi.org/10.1109/TEC.2002.801997.
Jovanovic M. Control of Brushless Doubly-Fed Reluctance Motors. Proceedings of the IEEE International Symposium on Industrial Electronics (ISIE 2005), 2005, pp. 1667-1672. doi: https://doi.org/10.1109/ISIE.2005.1529182.
Ademi S., Jovanovic M. Vector control strategies for brushless doubly-fed reluctance wind generators. 2012 2nd International Symposium On Environment Friendly Energies And Applications, 2012, pp. 44-49. doi: https://doi.org/10.1109/EFEA.2012.6294084.
Ademi S., Jovanovic M.G., Hasan M. Control of Brushless Doubly-Fed Reluctance Generators for Wind Energy Conversion Systems. IEEE Transactions on Energy Conversion, 2015, vol. 30, no. 2, pp. 596-604. doi: https://doi.org/10.1109/TEC.2014.2385472.
Oualah O., Kerdoun D., Boumassata A. Comparative study between sliding mode control and the vector control of a brushless doubly fed reluctance generator based on wind energy conversion systems. Electrical Engineering & Electromechanics, 2022, no. 1, pp. 51-58. doi: https://doi.org/10.20998/2074-272X.2022.1.07.
Jovanovic M., Ademi S., Llano D.X. Control of Doubly-Fed Reluctance Machines without a Shaft Position or Speed Sensor. 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), 2018, pp. 1245-1250. doi: https://doi.org/10.1109/SPEEDAM.2018.8445405.
Kumar M., Das S., Sinha A.K. Sensorless speed control of brushless doubly-fed reluctance machine for pump storage and wind power application. 2018 IEEMA Engineer Infinite Conference (ETechNxT), 2018, pp. 1-6. doi: https://doi.org/10.1109/ETECHNXT.2018.8385316.
Zhu L., Zhang F., Jin S., Ademi S., Su X., Cao W. Optimized Power Error Comparison Strategy for Direct Power Control of the Open-Winding Brushless Doubly Fed Wind Power Generator. IEEE Transactions on Sustainable Energy, 2019, vol. 10, no. 4, pp. 2005-2014. doi: https://doi.org/10.1109/TSTE.2018.2877439.
Liu X., Han Y., Wang C. Second‐order sliding mode control for power optimisation of DFIG‐based variable speed wind turbine. IET Renewable Power Generation, 2017, vol. 11, no. 2, pp. 408-418. doi: https://doi.org/10.1049/iet-rpg.2015.0403.
Kiran K., Das S., Sahu A. Sensorless speed estimation and control of brushless doubly-fed reluctance machine drive using model reference adaptive system. 2016 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), 2016, pp. 1-6. doi: https://doi.org/10.1109/PEDES.2016.7914480.
Kiran K., Das S., Singh D. Model predictive field oriented speed control of brushless doubly-fed reluctance motor drive. 2018 International Conference on Power, Instrumentation, Control and Computing (PICC), 2018, pp. 1-6. doi: https://doi.org/10.1109/PICC.2018.8384760.
Benbouhenni H., Lemdani S. Combining synergetic control and super twisting algorithm to reduce the active power undulations of doubly fed induction generator for dual-rotor wind turbine system. Electrical Engineering & Electromechanics, 2021, no. 3, pp. 8-17. doi: https://doi.org/10.20998/2074-272X.2021.3.02.
Babes B., Hamouda N., Kahla S., Amar H., Ghoneim S.S.M. Fuzzy model based multivariable predictive control design for rapid and efficient speed-sensorless maximum power extraction of renewable wind generators. Electrical Engineering & Electromechanics, 2022, no. 3, pp. 51-62. doi: https://doi.org/10.20998/2074-272X.2022.3.08.
Oualah O., Kerdoun D., Boumassata A. Comparison between sliding mode and traditional PI controllers in a speed control of a brushless doubly fed reluctance machine. 1st International Conference on Scientific and Academic Research (ICSAR 2022), December 10-13, 2022, Konya, Turkey, pp. 1-6.
Boubzizi S., Abid H., El hajjaji A., Chaabane M. Comparative study of three types of controllers for DFIG in wind energy conversion system. Protection and Control of Modern Power Systems, 2018, vol. 3, no. 1, art. no. 21. doi: https://doi.org/10.1186/s41601-018-0096-y.
Kelkoul B., Boumediene A. Stability analysis and study between classical sliding mode control (SMC) and super twisting algorithm (STA) for doubly fed induction generator (DFIG) under wind turbine. Energy, 2021, vol. 214, art. no. 118871. doi: https://doi.org/10.1016/j.energy.2020.118871.
Boumassata A., Kerdoun D., Oualah O. Maximum power control of a wind generator with an energy storage system to fix the delivered power. Electrical Engineering & Electromechanics, 2022, no. 2, pp. 41-46. doi: https://doi.org/10.20998/2074-272X.2022.2.07.
Zhou D., Song Y., Blaabjerg F. Control of Wind Turbine System. In Book: Control of Power Electronic Converters and Systems, 2018, pp. 269-298. doi: https://doi.org/10.1016/B978-0-12-805245-7.00010-X.
Levant A. Introduction to high-order sliding modes. School of Mathematical Sciences, Israel, 2003. 55 p.
Durga Rao R. Implementation of fuzzy based power control of BDFIG with super-twisting sliding mode control. JAC : A Journal of Composition Theory (JCT), 2020, vol. 13, no. 3, pp. 454-461.
Shiralkar A., Kurode S. Generalized super-twisting algorithm for control of electro-hydraulic servo system. IFAC-PapersOnLine, 2016, vol. 49, no. 1, pp. 742-747. doi: https://doi.org/10.1016/j.ifacol.2016.03.145.
Mahgoun M.S., Badoud A.E. New design and comparative study via two techniques for wind energy conversion system. Electrical Engineering & Electromechanics, 2021, no. 3, 18-24. doi: https://doi.org/10.20998/2074-272X.2021.3.03.
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