Comparative Study Between Back-Stepping Control and ANN-Sliding Mode Control of DFIG-Based Wind Turbine System
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This paper deals with the control of the rotor-side converter of a doubly fed induction generator integrated in a wind turbine system for regulating independently the active and the reactive power of the DFIG stator by two non-linear control methods: backstepping (BSC) and artificial neural network sliding mode control (ANN-SMC). A comparative study of the two control strategies is performed in order to determine which one is the most efficient and robust in terms of the response time on the one hand and the power ripple minimizing on the other hand, under the effect of the variation of DFIG’s internal parameters. The modeling of the wind turbine system based on DFIG and the controller’s implementation are performed using Matlab/Simulnk environment. Simulation results have proven the robustness of both controllers, although with a slight superiority of the ANN-SMC.
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Future of wind deployment, investment, technology, grid integration and socio-economic aspects. Abu Dhabi: International Renewable Energy Agency, 2020.
Yaramasu, V. and Wu, B., 2017. Power Electronics for High-Power Wind Energy Conversion Systems. Encyclopedia of Sustainable Technologies, pp.37-49.
Zohoori, A., Vahedi, A., Noroozi, M.A., Meo, S., A new outer-rotor flux switching permanent magnet generator for wind farm applications, (2017) Wind Energy, 20 (1), pp. 3-17.
Vahedi, A., Meo, S., Zohoori, A., An AHP-based approach for design optimization of flux-switching permanent magnet generator for wind turbine applications, (2016) International Transactions on Electrical Energy Systems, 26 (6), pp. 1318-1338.
Damiano, A., Gatto, G., Marongiu, I., Meo, S., Perfetto, A., Serpi, A., A direct-drive wind turbine control for a wind power plant with an internal DC distribution system, (2012) International Review of Electrical Engineering (IREE), 7 (4), pp. pp. 4845-4856.
Brando, G., Di Noia, L.P., Del Pizzo, A., Meo, S., Second order variable structure control for wind turbine PMSG-based and generator-side converter system, (2017) 6th International Conference on Renewable Energy Research and Applications, ICRERA 2017, 2017-January, pp. 797-801.
A. Tamaarat and A. Benakcha, "Performance of PI controller for control of active and reactive power in DFIG operating in a grid-connected variable speed wind energy conversion system", Frontiers in Energy, vol. 8, no. 3, pp. 371-378, 2014.
Merabet, L., Chaker, A., Kouzou, A., Boulouiha, H., Elaguab, M., Investigation on the Control of DFIG Used in Power Generation Based on Sliding Mode Control and SV-PWM, (2019) International Journal on Energy Conversion (IRECON), 7 (4), pp. 148-161.
B. Belabbas, T. Allaoui, M. Tadjine and M. Denai, "Comparative study of back-stepping controller and super twisting sliding mode controller for indirect power control of wind generator", International Journal of System Assurance Engineering and Management, vol. 10, no. 6, pp. 1555-1566, 2019.
Benbouzid, M., Beltran, B., Ezzat, M., Breton, S., DFIG Driven Wind Turbine Grid Fault-Tolerance Using High-Order Sliding Mode Control, (2013) International Review on Modelling and Simulations (IREMOS), 6 (1), pp. 29-32.
H. Benbouhenni, Sliding Mode with Neural Network Regulator for DFIG Using Two-Level NPWM Strategy, Iranian Journal of Electrical and Electronic Engineering, Vol. 14, No. 4, 2018.
M. Benmeziane, S. Zebirate, A. Chaker and Z. Boudjema, Fuzzy sliding mode control of doubly-fed induction generator driven by wind turbine, International Journal of Power Electronics and Drive System (IJPEDS) ,Vol. 10, No. 3, pp. 1592~1602 Sep 2019.
Rached, B., Elharoussi, M., Abdelmounim, E., DSP in the Loop Implementation of a Backstepping Controller for Wind Energy Conversion System Based on a Doubly Fed Induction Generator Connected to Grid, (2019) International Journal on Energy Conversion (IRECON), 7 (4), pp. 136-147.
El Malah, M., Ba-razzouk, A., Abdelmounim, E., Madark, M., Robust Nonlinear Sensorless MPPT Control with Unity Power Factor for Grid Connected DFIG Wind Turbines, (2018) International Review on Modelling and Simulations (IREMOS), 11 (5), pp. 313-324.
Sabiri, Z., Machkour, N., Rabbah, N., Nahid, M., Kheddioui, E., Command of a Doubly-Fed Induction Generator with a Backstepping Controller for a Wind Turbine Application, (2017) International Review of Automatic Control (IREACO), 10 (1), pp. 56-62.
Majdoub, Y., Abbou, A., Akherraz, M., El Akhrif, R., Intelligent Backstepping Control of Variable Speed DFIG-Wind Turbine Under Unbalanced Grid Voltage Conditions Using Genetic Algorithm Optimization, (2015) International Review of Electrical Engineering (IREE), 10 (6), pp. 716-726.
Farhat, S., Alaoui, R., Kahaji, A., Bouhouch, L., Wind Turbine MPPT Strategy with DFIG Vector Control, (2018) International Review on Modelling and Simulations (IREMOS), 11 (6), pp. 406-413.
Lhachimi, H., Sayouti, Y., Elkouari, Y., The Comparison and Analysis of the DFIG Behavior Under PI, Fuzzy and Sliding Mode Controllers for Wind Energy Conversion System in the Grid Connected Mode, (2018) International Review of Automatic Control (IREACO), 11 (3), pp. 113-123.
Y. Dbaghi, S. Farhat and M. Mediouni, First Order Sliding Mode and Super-twisting Sliding Mode Control of Doubly Fed Induction Generator Driven by Wind Turbine System: A Comparative Study, Journal of Advanced Research in Dynamical and Control Systems, vol. 12, no. 04-, pp. 1656-1667, 2020.
F. Fateh, W. N. White and D. Gruenbacher, A Maximum Power Tracking Technique for Grid-Connected DFIG-Based Wind Turbines, in IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 3, no. 4, pp. 957-966, Dec. 2015.
P. V. Kokotovic, M. Krstic and I. Kanellakopoulos, Backstepping to passivity: recursive design of adaptive systems, Proceedings of the 31st IEEE Conference on Decision and Control, vol.4, pp. 3276-3280, Tucson, AZ, USA, 1992,
V. Utkin, Variable structure systems with sliding modes, in IEEE Transactions on Automatic Control, vol. 22, no. 2, pp. 212-222, April 1977.
Del Pizzo, A., Di Noia, L.P., Meo, S., Super Twisting Sliding mode control of Smart-Inverters grid-connected for PV applications, (2017) 6th International Conference on Renewable Energy Research and Applications, ICRERA 2017, 2017-January, pp. 793-796.
A. Daoud and N. Derbel, Direct Power Control of DFIG Using Sliding Mode Control Approach, Modeling, Identification and Control Methods in Renewable Energy Systems, pp. 193-204, 2018.
S. Farhat, R. Alaoui, A. Kahaji and L. Bouhouch, Estimating the photovoltaic MPPT by artificial neural network, International Renewable and Sustainable Energy Conference (IRSEC), Ouarzazate 2013.
Zohoori, A., Vahedi, A., Meo, S., Sorrentino, V., An Improved AHP Method for Multi-Objective Design of FSPM Machine for Wind Farm Applications, (2016) Journal of Intelligent and Fuzzy Systems, 30 (1), pp. 159-169.
Attia, H., Artificial Neural Networks Based Maximum Power Point Tracking Photovoltaic System for Remote Park LED Lighting Applications, (2018) International Review on Modelling and Simulations (IREMOS), 11 (6), pp. 396-405.
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