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Comparison of Physical,Gaussian Process,and Physics-Informed Gaussian Process Models for Wind Turbine Power Curve Estimation

Samuel Martínez-Gutiérrez Carlos Gutiérrez Alejandro Merino Diego García-Álvarez Daniel Sarabia

Computer Modeling in Engineering & Sciences2026，Vol.147Issue(6)：P.695-717,23.

Computer Modeling in Engineering & Sciences2026，Vol.147Issue(6)：P.695-717,23.DOI:10.32604/cmes.2026.081247

Comparison of Physical,Gaussian Process,and Physics-Informed Gaussian Process Models for Wind Turbine Power Curve Estimation

Samuel Martínez-Gutiérrez ¹Carlos Gutiérrez ¹Alejandro Merino ¹Diego García-Álvarez ²Daniel Sarabia¹

作者信息

1. Department of Digitalization,Area of Systems Engineering and Automatic Control,University of Burgos,Avda.Cantabria,s/n,Burgos,Spain
2. Department of Informatics,University of Valladolid,P.°de Belén,15,Valladolid,Spain
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摘要

关键词

Wind turbine power curve/wind turbine power coefficient/physical model/Gaussian processes/physicsinformed machine learning

分类

信息技术与安全科学

引用本文复制引用

Samuel Martínez-Gutiérrez,Carlos Gutiérrez,Alejandro Merino,Diego García-Álvarez,Daniel Sarabia..Comparison of Physical,Gaussian Process,and Physics-Informed Gaussian Process Models for Wind Turbine Power Curve Estimation[J].Computer Modeling in Engineering & Sciences,2026,147(6):P.695-717,23.

基金项目

by financed by the Spanish Ministry of Science, Innovation andUniversities, the Spanish State Research Agency （）

by the European Union (FSE+), through the projects‘Control and Planning of Processes Subject toHighVariability andUncertainty’ (CyPVar) PID2024-157718OB-C33 （FSE+）

‘Optimal real-timemanagement under uncertainty for digital twins (OptiDit)’, PID2021-123654OB-C33 （OptiDit）

‘AdvancedLearning for Improving Productivity in Smart Factories’ (PID2021-126659OB-I00) （PID2021-126659OB-I00）

funded withSamuel Martinez-Gutierrez pre-doctoral contract for University Teacher Training (FPU), call 2022, awarded by theSpanish ministry of Science, Innovation and Universities. （FPU）

Computer Modeling in Engineering & Sciences

ISSN：1526-1492

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