Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning

Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning

Abstract Hydropower systems face significant challenges in load control and fault detection due to their complex operational dynamics. This study presents an innovative framework combining Digital Twin technology with Deep Learning to enhance fault detection, optimize operations, and improve system...

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Bibliographic Details
Main Authors: Jun Tan, Raoof Mohammed Radhi, Kimia Shirini, Sina Samadi Gharehveran, Zamen Parisooz, Mohsen Khosravi, Hossein Azarinfar
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Hydropower systems
Digital twin technology
Deep learning
Fault detection
System optimization
Real-Time monitoring
Online Access:https://doi.org/10.1038/s41598-025-98235-1
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