Wind Turbine Damage Equivalent Load Assessment Using Gaussian Process Regression Combining Measurement and Synthetic Data

Rad Haghi (), Cassidy Stagg and Curran Crawford
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Rad Haghi: Department of Mechanical Engineering, Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8P 5C2, Canada
Cassidy Stagg: Department of Mechanical Engineering, Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8P 5C2, Canada
Curran Crawford: Department of Mechanical Engineering, Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8P 5C2, Canada

Energies, 2024, vol. 17, issue 2, 1-24

Abstract: Assessing the structural health of operational wind turbines is crucial, given their exposure to harsh environments and the resultant impact on longevity and performance. However, this is hindered by the lack of data in commercial machines and accurate models based on manufacturers’ proprietary design data. To overcome these challenges, this study focuses on using Gaussian Process Regression (GPR) to evaluate the loads in wind turbines using a hybrid approach. The methodology involves constructing a hybrid database of aero-servo-elastic simulations, integrating publicly available wind turbine models, tools and Supervisory Control and Data Acquisition (SCADA) measurement data. Then, constructing GPR models with hybrid data, the prediction is validated against the hybrid and SCADA measurements. The results, derived from a year of SCADA data, demonstrate the GPR model’s effectiveness in interpreting and predicting turbine performance metrics. The findings of this study underscore the potential of GPR for the health and reliability assessment and management of wind turbine systems.

Keywords: GPR; SCADA; wind turbine; asset health; asset reliability (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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