This book examines and develops digital control techniques for wind power systems and their integration into the grid, with the goal of addressing issues related to the efficiency and quality of energy injected into the electrical network. It provides a comprehensive examination of digital control technologies for wind energy systems, covering a range of configurations, including existing ones (DFIG, PMSG, IM, etc.) as well as new ones (VIENNA, Quadri‑rotor, etc.). This book discusses various control strategies, such as backstepping, sliding mode, and predictive control, and explores their development through artificial intelligence (AI) and the Internet of Things (IoT). These strategies underpin the control systems used in speed variators (e.g., Siemens, ABB) that are highly robust for alternating current machines.
- Addresses the challenges of designing and implementing advanced wind turbine control techniques to convert kinetic energy into electrical energy
- Studies AI control techniques for wind systems
- Discusses adaptive control, new configuration, backward control of wind systems, and algorithms to optimize control systems of wind systems
- Focuses on new control techniques and their implementation on electronic platforms (such as dSPACE, FPGA, STM, etc)
This book is intended for students, researchers, and professionals working on digital technologies for wind turbine control and integration.
Badre Bossoufi (Eng., Ph.D., IEEE Senior Member). He received his Ph.D. in electrical engineering from the Faculty of Sciences at Sidi Mohammed Ben Abdellah University in Fez, and a joint Ph.D. from the Faculty of Electronics and Computer at the University of Pitești, Romania, and the Montefiore Institute of Electrical Engineering in Liège, Belgium, in 2012. He was a professor of electrical engineering at the Faculty of Sciences at Sidi Mohammed Ben Abdellah University. His research interests include static converters, electrical motor drives, power electronics, smart grids, renewable energy, and artificial intelligence. He has published numerous papers in journals and conferences over the past few years, most of which relate to wind power control and microgrid systems. He has edited several books and served as a guest editor for various special issues and topical collections. He is a reviewer and is on the editorial boards of several journals. He has been associated with more than 20 international conferences as a program committee member, advisory board member, or review board member.
Ibtihal Ait Abdelmoula is an R&D Engineer and the Head of the Digitalization and Data Science Group in Green Energy Park. She was previously responsible for electrical systems in the Green Energy Park. She holds an electrical engineering and embedded systems degree from the National School of Applied Science, Marrakesh, Morocco. She is currently pursuing a PhD degree in anomaly detection and predictive maintenance of PV systems using Edge computing and federated learning techniques. She is also a certified Renewable energy project manager for PV and Diesel. Mrs. Ibtihal has experience in monitoring and supervision of PV plants and has the lead of the team behind the development of the SCADA systems of the Green Energy Park platforms. She has managed projects related to photovoltaic monitoring, Big Data Analytics and the digitalization of energy systems.
