Quantification of performance degradation due to wind turbine aging: Estimating the reduction in annual energy production using the annual degradation rate

Daeyoung Kim and Bumsuk Kim

Energy, 2025, vol. 324, issue C

Abstract: Wind power plays a crucial role in reducing carbon emissions and combating climate change, holding a key position in the energy portfolios of many countries. However, alongside this growth, turbine aging has emerged. Turbine aging leads to performance degradation, increased maintenance costs, and reduced energy production efficiency. Despite this, standardized methods for accurately predicting power performance degradation and energy loss due to turbine aging remain insufficient. This study developed a method to quantify the Annual Degradation Rate (ADR) caused by turbine aging and applied it to operational wind farms to estimate the power curve and the corresponding decrease in Annual Energy Production (AEP). The results showed that the power curve prediction model had high predictive accuracy, with a relative error rate of less than 1.6 %. Additionally, AEP was found to decrease by 0.72 % annually due to turbine aging, equivalent to a reduction of 0.04 % per MW. Finally, ADR was assessed based on the aging rate of the turbines, classifying them into three categories: slow aging, normal aging, and accelerated aging. This method provides a systematic tool for analyzing and predicting wind turbine performance degradation, offering a practical metric for developing management and maintenance strategies.

Keywords: Wind turbine aging; Annual degradation rate; Annual energy production reduction; Performance decline analysis; SCADA data driven (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:324:y:2025:i:c:s0360544225017840

DOI: 10.1016/j.energy.2025.136142

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