Artificial Intelligence of Things for Wind Energy Systems

Erscheinungsjahr 2026
ISBN: 978-0-443-28905-7
Verlag: Elsevier Science

Buch, Englisch, 350 Seiten, Format (B × H): 152 mm x 229 mm

Artificial Intelligence of Things for Wind Energy Systems covers the novel concept of Artificial Intelligence (AI) combined with Internet of Things (IoT), for efficient data acquisition, analytics, and automated control, in wind energy systems. The book begins by introducing Artificial Intelligence of Things (AIoT), technologies, challenges, and future directions. Subsequent chapters provide in-depth coverage of specific technical areas and their applications in wind forecasting, generation, energy management, anomaly detection, digital twins, inspection of generators, recommendation systems, security concerns, and microgrid monitoring and control. Throughout the book, the information presented is supported by visuals, case studies, simulations, and code. A Volume in the Elsevier Wind Energy Engineering Series, this is a valuable resource for researchers, graduate students, engineers, operators, and other industry personnel with an interest in the use of AI and IoT in wind energy production and integration.

Autoren/Hrsg.

Kamel, Salah

Appasani, Bhargav

Kumar Mishra, Sunil

Fachgebiete

• Technische Wissenschaften Energietechnik | Elektrotechnik Alternative und erneuerbare Energien
• Technische Wissenschaften Energietechnik | Elektrotechnik Energieverteilung, Stromnetze
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Technische Wissenschaften Energietechnik | Elektrotechnik Energietechnik & Elektrotechnik

Inhaltsverzeichnis

1. AIoT for Wind Energy Systems: Technologies, Challenges and Future Directions
2. Deep Learning and IoT for Effective Forecasting of Wind
3. Novel Control Techniques for Reliable Wind Energy Generation Incorporating AI and IoT
4. Energy Management in Wind Farms Using IoT, Big Data and AI
5. Big Data, IoT and AI for Anomaly Detection in Wind Turbine Generators
6. Digital Twins for Wind Energy Systems Using IoT and AI
7. Internet of Drones and Deep Learning for Inspection of Wind Turbine Generators
8. AI and IoT based Recommendation Systems for Wind Energy Generation
9. Security Concerns in AIoT systems for Wind Energy Farms
10. Wind Energy Microgrid Monitoring and Control using AIoT

Über Autor(innen)

Kumar Mishra, Sunil
Dr. Sunil Kumar Mishra received his PhD in Electrical Engineering from Motilal Nehru National Institute of Technology (MNNIT) Allahabad, India. He is currently Assistant Professor in the School of Electronics Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India. His research areas are ocean wave energy (control perspectives) and nonlinear controller design. He has has published more than 30 research papers in reputed international journals and conferences, and is also a reviewer of the Transactions of Institute of Measurement and Control (TIMC) Journal.

Appasani, Bhargav
Dr. Bhargav Appasani received his Ph.D. from Birla Institute of Technology, Mesra, India. He is currently an Assistant Professor with the School of Electronics Engineering, KIIT University, Bhubaneswar, India. He has published more than 100 articles in international journals and conference proceedings, six book chapters, one authored book, and one edited book. He acts as an academic editor of the Journal of Electrical and Computer Engineering (Hindawi) and Applied Computational Intelligence and Soft Computing (Hindwai), and reviewer for IEEE Transactions on Smart Grid, IEEE Transactions on Antennas and Propagation, and IEEE Access. His research interests are smart grid, cyber-physical systems, 5G, vehicular networks, etc. He is a member of IEEE.

Kamel, Salah
Dr. Salah Kamel received his Ph.D. from the University of Jaén, Spain (Main), and Aalborg University, Denmark (Host), in January 2014. He is currently an Associate Professor with the Department of Electrical Engineering, Aswan University, Egypt, where he is also a Leader of the Advanced Power Systems Research Laboratory (APSR Laboratory), Power Systems Research Group. His research areas include power system analysis and optimization, smart grid, and renewable energy systems.