Investigation on the evolution of wind energy capture capability of wind turbines using historical field data

Juchuan Dai, Huifan Zeng, Kun Tang and Fan Zhang

Renewable Energy, 2025, vol. 249, issue C

Abstract: As the service life of wind turbines increases, their wind energy capture capability (WECC) gradually deteriorates. Effective assessment of this evolution behavior plays a crucial role in the operation and maintenance of wind turbines. However, there is currently a lack of effective assessment methods and case studies to reveal this evolution behavior in the field. To address this issue, WECC's evolution model is constructed based on wind turbines' energy information extraction strategy. A data-driven method for determining the time constant of wind turbines is proposed, which, in combination with moving average filtering (MAF), can be used to suppress the impact of high-frequency disturbances in wind speed. Additionally, a deviation compensation approach is adopted to overcome the inherent defects of nacelle wind speed data. Subsequently, based on the characteristics of field SCADA data, a pattern for determining the operating boundary of the maximum power point tracking (MPPT) area is constructed to obtain reliable comparison intervals. Taking SCADA data collected from a wind farm in southern China, the evolution behavior of WECC for two wind turbines are investigated using SCADA data from four consecutive years, and two different degradation degrees of 5.1 % and 2.2 % are observed.

Keywords: Wind turbines; Wind energy capture capability; Evolution behavior; SCADA data (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:249:y:2025:i:c:s0960148125008390

DOI: 10.1016/j.renene.2025.123177

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