Physics-Informed Neural Network surrogate model for bypassing Blade Element Momentum theory in wind turbine aerodynamic load estimation-Reference-Cited by-同舟云学术

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Physics-Informed Neural Network surrogate model for bypassing Blade Element Momentum theory in wind turbine aerodynamic load estimation

Published:2024-04 Issue: Volume:224 Page:120122
ISSN:0960-1481
Container-title:Renewable Energy
language:en
Short-container-title:Renewable Energy

Author:

Baisthakur Shubham^ORCID,Fitzgerald Breiffni^ORCID

Funder

Science Foundation Ireland

Sustainable Energy Authority of Ireland

Publisher

Elsevier BV

Reference48 articles.

1. Climate policy of the European union: What to expect from the Paris agreement;Strielkowski;Romanian J. Eur. Aff.,2016

2. Net-zero emission targets for major emitting countries consistent with the Paris agreement;Van Soest;Nature Commun.,2021

3. IEA;IEA WIND Energy and A. IEA;Renew. Energy Mark. Update,2020

4. Why offshore wind energy?;Esteban;Renew. Energy,2011

5. Recent technology and challenges of wind energy generation: A review;Roga;Sustain. Energy Technol. Assess.,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-driven time series forecasting of offshore wind turbine loads;Journal of Physics: Conference Series;2024-06-01

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