PREDICTION OF WIND TURBINE BLADE FATIGUE LOADS USING FEED-FORWARD NEURAL NETWORKS

PREDICTION OF WIND TURBINE BLADE FATIGUE LOADS USING FEED-FORWARD NEURAL NETWORKS

In recent years, machine learning applications have gained great attention in the wind power industry. Among these, artificial neural networks have been utilized to predict the fatigue loads of wind turbine components such as rotor blades. However, the limited number of contributions and differences...

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Bibliographic Details
Main Author: Mohammadi, Mohammad Mehdi
Format: Others
Language:English
Published: Uppsala universitet, Institutionen för geovetenskaper 2021
Subjects:
Machine Learning
Feed-Forward Artificial Neural Network
Wind Power
Damage Equivalent Loads
Fatigue
Wind Turbine Blades
NEWA Data
SCADA
Lillgrund Wind Farm
Energy Engineering
Energiteknik
Applied Mechanics
Teknisk mekanik
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-444115

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-444115

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