Advanced Diagnosis and Control Approaches for Wind Turbine Systems: Challenges, Limitations, and Future Perspectives

Dear Colleagues,

Wind energy systems have become one of the most important technologies supporting the global transition toward sustainable and clean energy production. However, the increasing complexity of modern wind turbines, combined with harsh environmental conditions and variable operating regimes, introduces significant challenges in reliability, fault detection, control performance, and maintenance optimization. Efficient diagnostic and advanced control approaches are therefore essential to improve system stability, operational safety, and energy efficiency.

This Topic focuses on recent advances in diagnostic techniques and intelligent control strategies for wind turbine systems. It aims to highlight innovative methods for fault detection, condition monitoring, predictive maintenance, and health assessment of critical components such as generators, gearboxes, bearings, converters, and blades. Particular attention is given to artificial intelligence, machine learning, signal processing, and data-driven diagnostic methods capable of improving fault identification accuracy under uncertain operating conditions.

In addition, this Topic addresses advanced control approaches designed to enhance wind turbine performance, power quality, grid integration, and energy conversion efficiency. Topics include nonlinear control, adaptive and robust control, fault-tolerant strategies, smart optimization algorithms, and real-time energy management systems. Challenges and limitations associated with current technologies, such as modeling complexity, data uncertainty, and system scalability, are also explored.

The objective of this Topic is to provide future perspectives and emerging solutions for developing more reliable, efficient, and intelligent wind energy systems.

Prof. Dr. Habib Benbouhenni
Dr. Abdelkadir Belhadj Djilali
Dr. Hamza Gasmi
Topic Editors