Machine learning boosts wind turbine efficiency with smart failure detection and strategic placement

Machine learning boosts wind turbine efficiency with smart failure detection and strategic placement

Abstract The research study objective seeks to improve the efficiency of wind turbines using state-of-the-art techniques in the domain of ML, making wind energy the key player in fashioning a favorable future. Wind Turbine Health Monitoring (WTHM) is typically achieved through either vibration analy...

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Bibliographic Details
Main Authors: Sekar Kidambi Raju, Muthusamy Periyasamy, Amel Ali Alhussan, Subhash Kannan, Srikanth Raghavendran, El-Sayed M. El-kenawy
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Wind turbine health monitoring
Machine learning
Optimizing wind energy generation
Failure detection
Strategic wind turbine placement
Online Access:https://doi.org/10.1038/s41598-025-85563-5
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https://doi.org/10.1038/s41598-025-85563-5

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