The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Digital Twin Frameworks for AI-Driven Wind Turbine Monitoring and Predictive Maintenance
|
|
Author(s): Nguyen Duc Thuan (Hanoi University of Science and Technology, Vietnam)
Copyright: 2026
Pages: 46
Source title:
AI-Powered Analysis, Modeling, and Monitoring of Wind Energy Systems
Source Author(s)/Editor(s): Jackson J. Justo (University of Dar es Salaam, Dar es Salaam, Tanzania & ITMO University, St. Petersburg, Russia), Galina Demidova (Hangzhou Dianzi University, China & ITMO University, St. Petersburg, Russia), Francis A. Mwasilu (University of Dar es Salaam, Tanzania), Dmitry V. Lukichev (ITMO University, Russia)and Ramesh C. Bansal (University of Sharjah, Sharjah, UAE & University of Pretoria, Pretoria, South Africa)
DOI: 10.4018/979-8-3373-4159-0.ch007
Purchase
|
Abstract
The rapid digitalization of renewable energy systems has made digital twin technology a transformative approach for modeling, monitoring, and optimizing wind turbines. This chapter presents a framework for an AI-powered digital twin that integrates multi-physics modeling, machine learning, and real-time data synchronization. It develops detailed aerodynamic, mechanical, electrical, structural, and thermal models forming a hybrid simulation grounded in physics. Artificial intelligence methods, from machine learning to physics-informed neural networks, enhance fault detection, anomaly diagnosis, and life prediction. A small-scale turbine simulation validates the framework, showing real-time operation, improved torque prediction, and precise anomaly detection. The discussion highlights future directions in multi-agent wind farm twins, uncertainty quantification, explainable AI, and self-evolving models, outlining a roadmap toward autonomous and trustworthy digital energy ecosystems.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|