Digital Technologies for Wind Turbine Control and Integration

Inbunden, Engelska, 2026

Del i serien Advances in Digital Technologies for Smart Applications

2 416 kr

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Beskrivning

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 energyStudies AI control techniques for wind systemsDiscusses adaptive control, new configuration, backward control of wind systems, and algorithms to optimize control systems of wind systemsFocuses 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.

Produktinformation

Utgivningsdatum:2026-02-09
Mått:156 x 234 x 21 mm
Vikt:720 g
Format:Inbunden
Språk:Engelska
Serie:Advances in Digital Technologies for Smart Applications
Antal sidor:290
Förlag:Taylor & Francis Ltd
ISBN:9781032957852

Utforska kategorier

Klassisk mekanik inom Naturvetenskap och teknik
Energiteknik inom Naturvetenskap och teknik
Artificiell intelligens inom Data och IT

Mer om författaren

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.

Innehållsförteckning

1. The Digital Turbine: Embracing New Skills for a Sustainable Tomorrow on Winds for Change 2. Artificial Intelligence based Control Strategies for Optimizing Wind Energy Systems 3. From Energy to Economy: An Empirical Study on the Effects of Renewables on Morocco’s Economic Development 4. Contribution to Advanced Control Strategies For a DFIG based Wind Turbine 5. Performance Enhancement of Direct power Control of wind energy conversion system (WECS) based on a Doubly Fed Induction Generator 6. Optimizing Wind Energy Integration into the Power Grid: Challenges and Solutions 7. Nonlinear Backstepping Control Strategy for Direct-drive Wind Turbine based on Permanent Magnet Synchronous Generator 8. Hybrid Optimization for Reconfigurable Manufacturing Systems: Combining Genetic Algorithms and Supervised Learning for Enhanced Efficiency 9. Modeling and Sliding Mode Control of DFIG-based Wind Turbines 10. Permanent magnet synchronous generator’s integrated optimal design in a large-scale wind turbine 11. Particle Swarm Optimization Approach for Maximum Power Point Tracking of a Grid Connected Wind Turbine Generator 12. Influence of the integration wind energy on network stability