Comparative Study of Linear and Nonlinear Controllers for DFIG-Based Wind Power Systems Under Different Operating Conditions

Authors

  • Achraf El Ouali Department Team of Engineering and Applied Physics Higher School of Technology of Beni Mellal
  • Yassine Lakhal Department Team of Engineering and Applied Physics Higher School of Technology of Beni Mellal
  • Mohamed Benchagra Department Team of Engineering and Applied Physics Higher School of Technology of Beni Mellal
  • Hamid Chojaa Sidi Mohamed Ben Abdellah University
  • Mohamed Vall O. Mohamed Jouf University
  • Alfian Maarif Universitas Ahmad Dahlan
  • Mahmoud A. Mossa Minia University https://orcid.org/0000-0002-0308-3038

DOI:

https://doi.org/10.18196/jrc.v6i3.24721

Keywords:

Doubly-Fed Induction Generator (DFIG), Wind Energy, Linear-Nonlinear Controller, Proportional-Integral (PI), Sliding Mode (SMC), Backstepping (BSC), Robustness

Abstract

When doubly-fed induction generators (DFIGs) powered by wind energy are connected to the grid, unstable grid voltage causes distortion in the control of statoric active and reactive powers, especially if the controller uses this grid value for efficiency control, as well as parameter variation. Accordingly, this study focuses on evaluating the DFIG dynamics using different control topologies. The study presents a comparative analysis of linear and nonlinear control techniques for the DFIG, including both classical and robust controllers. A voltage converter based on Pulse Width Modulation (PWM) is employed to interface with the rotor, enabling independent control of active and reactive powers. Active and reactive powers are controlled using a linear proportional-integral (PI) controller and two types of nonlinear controllers: Backstepping (BSC) and Sliding Mode (SMC). This comparative study seeks to identify the most effective controller for tracking power reference, response to speed variations, sensitivity to external disturbances, and resilience against fluctuations in machine parameters. Three sets of evaluation tests are considered: normal operation with constant rotational speed while varying power references, robustness test under DFIG's parameters variation and rotor speed perturbation. The obtained results confirm the superiority of the nonlinear BSC and SMC approaches in comparison with the FOC, giving the BSC more priority than the SMC.

References

B. Yang, L. Jiang, L. Wang, W. Yao, and Q. Wu, “Nonlinear maximum power point tracking control and modal analysis of DFIG based wind turbine,” International Journal of Electrical Power & Energy Systems, vol. 74, pp. 429-436, 2016, doi: 10.1016/j.ijepes.2015.07.036.

M. A. Mossa, H. Echeikh, and A. Iqbal, “Enhanced control technique for a sensor-less wind driven doubly fed induction generator for energy conversion purpose,” Energy Reports, vol. 7, pp. 5815-5833, 2021, doi: 10.1016/j.egyr.2021.08.183.

M. A. Mossa, M. K. Abdelhamid, A. A. Hassan, and N. Bianchi, “Improving the Dynamic Performance of a Variable Speed DFIG for Energy Conversion Purposes Using an Effective Control System,” Processes, vol. 10, no. 3, p. 456, 2022, doi: 10.3390/pr10030456.

H. Chojaa et al., “Robust Control of DFIG-Based WECS Integrating an Energy Storage System With Intelligent MPPT Under a Real Wind Profile,” IEEE Access, vol. 11, pp. 90065-90083, 2023, doi: 10.1109/ACCESS.2023.3306722.

M. S. Ali, A. Sharma, T. A. Joy, and M. A. Halim, “A Comprehensive Review of Integrated Energy Management for Future Smart Energy System,” Control Systems and Optimization Letters, vol. 2, no. 1, pp. 43-51, 2024, doi: 10.59247/csol.v2i1.77.

S. D. Perkasa, A. R. Muzadi, P. Megantoro, and V. Pandi, “Audio-Based Telemetry Using HT Radios for Remote Monitoring of Renewable Energy Systems,” Control Systems and Optimization Letters, vol. 3, no. 1, pp. 68-74, 2025, doi: 10.59247/csol.v3i1.181.

F. Ahmed, A. Uzzaman, M. I. Adam, M. Islam, M. M. Rahman, and A. M. Islam, “AI-Driven Microgrid Solutions for Enhancing Energy Access and Reliability in Rural and Remote Areas: A Comprehensive Review,” Control Systems and Optimization Letters, vol. 3, no. 1, pp. 110-116, 2025, doi: 10.59247/csol.v3i1.183.

J. A. Pranto, M. M. Kadir, and M. Y. A. Khan, “A Comprehensive Study of the Importance of Materials for Renewable Energy Generation,” Control Systems and Optimization Letters, vol. 2, no. 3, pp. 310-316, 2024, doi: 10.59247/csol.v2i3.119.

M. A. Halim, M. S. Akter, S. Biswas, and M. S. Rahman, “Integration of Renewable Energy Power Plants on a Large Scale and Flexible Demand in Bangladesh's Electric Grid-A Case Study,” Control Systems and Optimization Letters, vol. 1, no. 3, pp. 157-168, 2023, doi: 10.59247/csol.v1i3.48.

T. Aziz, Z. Dodaev, M. Halim, and M. Khan, “A Review on Integration Challenges for Hybrid Energy Generation Using Algorithms,” Control Systems and Optimization Letters, vol. 2, no. 2, pp. 162-171, 2024, doi: 10.59247/csol.v2i2.85.

S. I. Khan, Z. Al Dodaev, and A. Haque, “The Integration of Renewable Energy Sources into Mechanical Systems, Focusing on Efficiency and Reliability - A Case Study,” Control Systems and Optimization Letters, vol. 2, no. 2, pp. 172-177, 2024, doi: 10.59247/csol.v2i2.92.

M. N. Hussain, K. A. Kader, M. S. Ali, A. Ullah, and Z. Al Dodaev, “An Extensive Analysis of the Significance and Difficulties of Microgrids Based on Renewable Energy in Wireless Sensor Networks,” Control Systems and Optimization Letters, vol. 2, no. 2, pp. 178-183, 2024, doi: 10.59247/csol.v2i2.102.

M. M. Mahmoud, I. Benlaloui, B. Benbouya, and N. F. Ibrahim, “Investigations on Grid-Connected DFIWGs Development and Performance Analysis with the Support of Crowbar and STATCOM,” Control Systems and Optimization Letters, vol. 2, no. 2, pp. 191-197, 2024, doi: 10.59247/csol.v2i2.109.

H. H. H. Mousa, K. Mahmoud, and M. Lehtonen, “Book Review on Hosting Capacity for Smart Power Grids, Ahmed F. Zobaa, Shady H. E. Abdel Aleem et al. Springer, 1 2020,” Control Systems and Optimization Letters, vol. 2, no. 2, pp. 150-153, 2024, doi: 10.59247/csol.v2i2.98.

J. Mohammadi, S. Vaez-Zadeh, S. Afsharnia, and E. Daryabeigi, “A Combined Vector and Direct Power Control for DFIG-Based Wind Turbines,” IEEE Transactions on Sustainable Energy, vol. 5, no. 3, pp. 767-775, 2014, doi: 10.1109/TSTE.2014.2301675.

M. A. Mossa, H. Echeikh, A. A. Z. Diab, and N. V. Quynh, “Effective Direct Power Control for a SensorLess Doubly Fed Induction Generator with a Losses Minimization Criterion,” Electronics, vol. 9, no. 8, p. 1269, 2020, doi: 10.3390/electronics9081269.

G. Abad, J. López, M. Rodríguez, L. Marroyo, and G. Iwanski, Doubly Fed Induction Machine: Modeling and Control for Wind Energy Generation Applications. John Wiley & Sons, 2011.

M. A. Mossa and Y. S. Mohamed, “Novel Scheme for Improving the Performance of a Wind Driven Doubly Fed Induction Generator During Grid Fault,” Wind Engineering, vol. 36, no. 3, pp. 305-334, 2012, doi: 10.1260/0309-524X.36.3.305.

O. Bachir and A. F. Zoubir, “Comparative analysis of robust controller based on classical proportional-integral controller approach for power control of wind energy system,” Revue roumaine des sciences techniques Série Électrotechnique et Énergétique, vol. 63, no. 2, pp. 210-216, 2018.

M. S. Chabani, M. T. Benchouia, A. Golea, A. Y. Abdealziz, and M. A. Mossa, “A new sensor-less voltage and frequency control of stand-alone DFIG based dead-beat direct-rotor flux control-experimental validation,” ISA Transactions, vol. 158, pp. 715-734, 2025, doi: 10.1016/j.isatra.2024.12.039.

A. Loulijat, A. Hilali, M. Makhad, H. Chojaa, N. Ababssi, and M. A. Mossa, “Low-voltage ride-through capability of DFIG-based WECS improved by nonlinear backstepping controller synthesized in novel power state model,” e-Prime - Advances in Electrical Engineering, Electronics and Energy, vol. 11, p. 100864, 2025, doi: 10.1016/j.prime.2024.100864.

K. Sayed, M. Aref, M. A. Mossa, and A. G. Abokhalil, “Intelligent Control of DFIG-Based Wind Energy Conversion Systems Using Artificial Intelligence Techniques,” Energy Conversion Systems-Based Artificial Intelligence, pp. 83-106, 2025, doi: 10.1007/978-981-96-2665-6_5.

A. Chantoufi, A. Derouich, N. E. Ouanjli, S. Mahfoud, A. E. Idrissi, and M. A. Mossa, “Fuzzy Logic Speed Controller for DTC of Doubly Fed Induction Traction Motor in Electric Vehicles,” Energy Conversion Systems-Based Artificial Intelligence, pp. 139-155, 2025, doi: 10.1007/978-981-96-2665-6_7.

M. A. Mossa, T. Duc Do, A. Saad Al-Sumaiti, N. V. Quynh, and A. A. Z. Diab, “Effective Model Predictive Voltage Control for a Sensorless Doubly Fed Induction Generator,” IEEE Canadian Journal of Electrical and Computer Engineering, vol. 44, no. 1, pp. 50-64, 2021, doi: 10.1109/ICJECE.2020.3018495.

M. A. Mossa, N. E. Ouanjli, O. Gam, and O. M. Kamel, “Performance improvement of a hybrid energy system feeding an isolated load,” 2022 23rd International Middle East Power Systems Conference (MEPCON), pp. 1-8, 2022, doi: 10.1109/MEPCON55441.2022.10021715.

M. A. Mossa, O. Gam, N. Bianchi, and N. V. Quynh, “Enhanced Control and Power Management for a Renewable Energy-Based Water Pumping System,” IEEE Access, vol. 10, pp. 36028-36056, 2022, doi: 10.1109/ACCESS.2022.3163530.

M. A. Mossa, T. D. Do, H. Echeikh, and A. A. Z. Diab, “A Predictive Voltage Control Scheme For A Variable Speed Doubly Fed Induction Generator,” 2021 IEEE 12th Energy Conversion Congress & Exposition - Asia (ECCE-Asia), pp. 1491-1497, 2021, doi: 10.1109/ECCE-Asia49820.2021.9479146.

M. A. Mossa and S. Bolognani, “Predictive Power Control for a Linearized Doubly Fed Induction Generator Model,” 2019 21st International Middle East Power Systems Conference (MEPCON), pp. 250-257, 2019, doi: 10.1109/MEPCON47431.2019.9008085.

M. Krstic, I. Kanellakopoulos, and P. V. Kokotovic, “Nonlinear Design of adaptive Controllers for linear Systems, IEEE Transactions on Automatic Control, vol. 39, pp. 738-752, 1994, doi: 10.1109/9.286250.

M. Krstic, P. V. Kokotovic, and I. Kanellakopoulos, Nonlinear and adaptive control design. John Wiley & Sons, 1995.

M. A. Mossa, N. V. Quynh, H. Echeikh, Hamdi, and T. D. Do, “Deadbeat-Based Model Predictive Voltage Control for a Sensorless Five-Phase Induction Motor Drive,” Mathematical Problems in Engineering, vol. 2020, no. 1, pp. 1-30, 2020, doi: 10.1155/2020/4164526.

M. A. M. Basri, A. R. Husain, and K. A. Danapalasingam, “Robust Chattering Free Backstepping Sliding Mode Control Strategy for Autonomous Quadrotor Helicopter,” International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS, vol. 14, no. 03, pp. 36-44, 2014.

L. Yassine, B. F. Zahra, Y. A. E. Kadi, and B. Mohammed, “The Efficiency of Fuzzy Logic Control on the Power Stabilization of Wind Turbine,” Advances in Electrical Systems and Innovative Renewable Energy Techniques, pp. 139–145, 2024, doi: 10.1007/978-3-031-49772-8_18.

S. Müller, M. Deicke, and R. W. de Doncker, “Doubly Fed Induction Generator Systems for Wind Turbines: A Viable Alternative to Adjust Speed over a Wide Range at Minimal Cost,” IEEE Industry Applications Magazine, vol. 8, no. 3, pp. 26-33, 2002, doi: 10.1109/2943.999610.

V. I. Utkin, “Sliding mode control design principles and applications to electric drives,” IEEE Transactions on Industrial Electronics, vol. 40, no. 1, pp. 23-36, 1993, doi: 10.1109/41.184818.

M. A. Mossa, R. A. Mohamed, and A. S. Al-Sumaiti, “Performance Enhancement of a Grid Connected Wind Turbine-Based PMSG Using Effective Predictive Control Algorithm,” IEEE Access, vol. 13, pp. 64160-64185, 2025, doi: 10.1109/ACCESS.2025.3557194.

M. A. Mossa, A. Saad Al-Sumaiti, T. Duc Do, and A. A. Zaki Diab, “Cost-Effective Predictive Flux Control for a Sensorless Doubly Fed Induction Generator,” IEEE Access, vol. 7, pp. 172606-172627, 2019, doi: 10.1109/ACCESS.2019.2951361.

M. A. Mossa and S. Bolognani, “Effective sensorless model predictive direct torque control for a doubly fed induction machine,” 2017 Nineteenth International Middle East Power Systems Conference (MEPCON), pp. 1201-1207, 2017, doi: 10.1109/MEPCON.2017.8301335.

M. A. Mossa and S. Bolognani, “High performance Direct Power Control for a doubly fed induction generator,” IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society, pp. 1930-1935, 2016, doi: 10.1109/IECON.2016.7793155.

S. Khadar, A. Benkhider, A. Amari, and M. A. Mossa, “A Robust DDTC Scheme Based on Artificial Neural Networks and Genetic Algorithm for Wind Power Generation,” Energy Conversion Systems-Based Artificial Intelligence, pp. 71-81, 2025, doi: 10.1007/978-981-96-2665-6_4.

M. A. Mossa, H. Echeikh, N. El Ouanjli, and H. H. Alhelou, “Enhanced Second-Order Sliding Mode Control Technique for a Five-Phase Induction Motor,” International Transactions on Electrical Energy Systems, vol. 2022, no. 1, pp. 1-19, 2022, doi: 10.1155/2022/8215525.

L. Xu and Y. Wang, “Dynamic Modeling and Control of DFIG-Based Wind Turbines Under Unbalanced Network Conditions,” in IEEE Transactions on Power Systems, vol. 22, no. 1, pp. 314-323, 2007, doi: 10.1109/TPWRS.2006.889113.

I. Erlich, J. Kretschmann, S. Mueller-Engelhardt, F. Koch, and J. Fortmann, “Modeling of wind turbines based on doubly-fed induction generators for power system stability studies,” 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, pp. 1-8, 2008, doi: 10.1109/PES.2008.4596271.

Yazhou Lei, A. Mullane, G. Lightbody, and R. Yacamini, “Modeling of the wind turbine with a doubly fed induction generator for grid integration studies,” IEEE Transactions on Energy Conversion, vol. 21, no. 1, pp. 257-264, 2006, doi: 10.1109/TEC.2005.847958.

C. Mehdipour, A. Hajizadeh, and I. Mehdipour, “Dynamic modeling and control of DFIG-based wind turbines under balanced network conditions,” International Journal of Electrical Power & Energy Systems, vol. 83, pp. 560-569, 2016, doi: 10.1016/j.ijepes.2016.04.046.

K. D. E. Kerrouche, L. Wang, A. V. D. Bossche, A. Draou, A. Mezouar, and L. Boumediene, “Dual robust control of grid-connected dfigs-based wind-turbine-systems under unbalanced grid voltage conditions,” Stability Control and Reliable Performance of Wind Turbines, 2018, doi: 10.5772/intechopen.75518.

J. Hu and Y. He, “Modeling and enhanced control of DFIG under unbalanced grid voltage conditions,” Electric Power Systems Research, vol. 79, no. 2, pp. 273-281, 2009, doi: 10.1016/j.epsr.2008.06.017.

M. A. Mossa, H. Echeikh, A. Iqbal, T. D. Do, and A. S. Al-Sumaiti, “A novel sensorless control for multiphase induction motor drives based on singularly perturbed sliding mode observer-experimental validation,'' Applied Sciences, vol. 10, no. 8, p. 2776, 2020, doi: 10.3390/app10082776.

M. A. Mossa and H. Echeikh, “A novel fault tolerant control approach based on backstepping controller for a five-phase induction motor drive: Experimental investigation,” ISA Transactions, vol. 112, pp. 373–385, 2021, doi: 10.1016/j.isatra.2020.11.031.

Y. Lakhal, F. Z. Baghli, and L. E. Bakkali, “The efficiency of bond graph approach for a flexible wind turbine modeling,” Journal of Engineering Science and Technology (JESTEC), vol. 12, no. 11, pp. 2990-3010, 2017.

J. J. E. Slotine, W. Li, Applied nonlinear control, Prentice-Hall, 1998.

M. A. Mossa, M. K. Abdelhamid, and A. A. Hassan, “Enhancing the Dynamic Performance of a Wind Driven Grid Connected DFIG Using an Effective Control Approach,” 2023 IEEE Conference on Power Electronics and Renewable Energy (CPERE), pp. 1-7, 2023, doi: 10.1109/CPERE56564.2023.10119614.

M. Hussein, A. M. Mohamed, A. H. Ahmed, and A. M. Mahmoud, “Optimal predictive voltage control of a wind driven five phase PMSG system feeding an isolated load,” e-Prime - Advances in Electrical Engineering, Electron and Energy, vol. 9, p. 100697, 2024, doi: 10.1016/j.prime.2024.100697.

M. A. Mossa, H. Echeikh, N. V. Quynh, and N. Bianchi, “Performance dynamics improvement of a hybrid wind/fuel cell/battery system for standalone operation,” IET Renewable Power Generation, vol. 17, no. 2, pp. 349–375, 2023, doi: 10.1049/rpg2.12603.

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Published

2025-05-12

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Vol. 6 No. 3 (2025)

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Copyright (c) 2025 Achraf EL OUALI, Yassine LAKHAL, Mohamed BENCHAGRA, Hamid Chojaa, Mohamed vall O. Mohamed, Alfian Maarif, Mahmoud A. Mossa

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