📄 Sciences Methods and Technologies
International Journal (SciMeTech)

Volume 2 · Issue 1 · 2026
ISSN: 3085-5284
Toward Robust Wind Turbine Control: From Disturbance Management Using LADRC to AI-Based Fault Prediction (GEO-ANN)
Chahri Marouane, Ali Boukhris
Pages 99–104 · Department of Environmental and Energy Engineering, Higher School of Technology of Essaouira, Cadi Ayyad University
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Abstract
The large-scale integration of wind energy using Doubly Fed Induction Generators (DFIGs) poses significant challenges to grid stability. Due to the inherent intermittency of wind and the sensitivity of power converters to disturbances, maintaining a stable and high-quality power output remains a critical issue. This paper presents a comprehensive review of advanced control strategies for DFIG-based wind energy systems, with particular emphasis on Linear Active Disturbance Rejection Control (LADRC) combined with Bi-LSTM neural networks, the nonlinear Integral Backstepping (IBSC) controller, and the GEO-ANN method. These approaches, as reported in the literature, demonstrate significant improvements in mitigating power oscillations, enhancing power quality, and increasing system robustness under grid disturbances such as voltage dips. The reviewed results highlight the effectiveness of these techniques in reducing total harmonic distortion (THD) and improving fault detection capabilities. Overall, this study underscores the growing role of intelligent and hybrid control methods in stabilizing modern power systems and outlines future research directions toward large-scale industrial implementation.
Keywords: Wind energy conversion systems, DFIG, LADRC, LVRT, Bi-LSTM, Backstepping Control, GEO-ANN, Grid Stability

References

  1. Ahmed, S. D., Al-Ismail, F. S. M., Shafiullah, M., Al-Sulaiman, F. A., & El-Amin, I. M. (2020). Grid Integration Challenges of Wind Energy: A Review. IEEE Access, 8, 10857-10878.
  2. Blaabjerg, F., & Ma, K. (2013). Future on Power Electronics for Wind Turbine Systems. IEEE Journal of Emerging and Selected Topics in Power Electronics, 1(3), 139-152.
  3. Lopez, J., Sanchis, P., Roboam, X., & Marroyo, L. (2007). Dynamic analysis of the doubly fed induction generator during three-phase fault. IEEE Transactions on Energy Conversion, 22(1), 193-201.
  4. Boukhris, A., Nasser, T., Essadki, A., & Boualouch, A. (2014). Improved control for DFIG used in wind energy conversion systems. International Review of Automatic Control (IREACO), 7(4), 403-411.
  5. Ibrahim, A., Al-Shamma'a, A. A., Xu, J., Aboudrar, I., Ameur, K., Al Dawood, R., & Mwakipunda, G. C. (2025). An enhanced uncertainty and disturbance estimator based on Bi-LSTM-OTC-LADRC of grid-connected wind energy conversion system. Computers & Electrical Engineering, 121, 110534.
  6. Beltran, B., Benbouzid, M. E. H., & Ahmed-Ali, T. (2009). Second-order sliding mode control of a doubly fed induction generator driven wind turbine. IEEE Transactions on Energy Conversion, 24(3), 831-838.
  7. Ibrahim, A., Al-Shamma'a, A. A., Aboudrar, I., Ameur, K., Al-Saffar, M. A., & Mwakipunda, G. C. (2025). Integrated intelligent control for DFIG-based wind energy system using GEO-ANN and LADRC under grid fault. Journal of Energy Storage, 84, 110756.
  8. Ibrahim, A., Al-Shamma'a, A. A., Xu, J., Aboudrar, I., Ameur, K., Al Dawood, R., & Mwakipunda, G. C. (2025). An enhanced uncertainty and disturbance estimator based on Bi-LSTM-OTC-LADRC of grid-connected wind energy conversion system. Computers & Electrical Engineering, 121, 110534.
  9. Atallah, M., Benmahdjoub, M. A., Salhi, I., Mezouar, A., Saidi, Y., & Gaillard, A. (2025). Efficient nonlinear integral backstepping control for doubly fed induction generators-based wind farm under unbalanced electrical grid voltage. International Journal of Electrical Power & Energy Systems, 164, 111141.
  10. Parameswari, G. A., & Arunsankar, G. (2025). Hybrid approach based optimal low voltage ride through capability in DFIG-based wind energy systems. Energy, 324, 135418.
SciMeTech · Volume 2, Issue 1 · 2026 · ISSN 3085-5284