Preprints
https://doi.org/10.5194/wes-2024-35
https://doi.org/10.5194/wes-2024-35
04 Apr 2024
 | 04 Apr 2024
Status: a revised version of this preprint was accepted for the journal WES and is expected to appear here in due course.

Challenges in Detecting Wind Turbine Power Loss: The Effects of Blade Erosion, Turbulence and Time Averaging

Tahir H. Malik and Christian Bak

Abstract. Blade leading-edge erosion (LEE), atmospheric turbulence intensity (TI) and shear can significantly impact wind turbine performance and annual energy production (AEP). This study employs aeroelastic simulations to investigate their combined effects. An offshore original equipment manufacturer (OEM) provided aeroelastic model was used to simulate various scenarios. Turbulence intensity was varied for a range of wind speeds and the blade polars were modified to simulate different degrees of erosion, represented by varying levels of roughness. Also, simulations with and without the inclusion of wind shear were investigated. Findings reveal that even mild simulated erosion can reduce AEP by 0.82 %, while more severe erosion leads to a 2.83 % decrease. Increasing TI exacerbates these losses, with a 25 % TI causing up to a 3.5 % AEP reduction for eroded blades. These effects were most pronounced at lower wind speeds. Furthermore, standard time-averaging practices in power curve analyses can obscure the true magnitude of TI and LEE's impact on short-term power fluctuations. This work emphasises the critical importance of considering both blade condition and TI for accurate AEP assessments, optimal maintenance scheduling and improved wind turbine design in the context of site-specific atmospheric conditions.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Tahir H. Malik and Christian Bak

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2024-35', Anonymous Referee #1, 23 Apr 2024
    • AC1: 'Reply on RC1', Tahir Malik, 14 Jun 2024
  • RC2: 'Comment on wes-2024-35', Anonymous Referee #2, 23 Apr 2024
    • AC2: 'Reply on RC2', Tahir Malik, 14 Jun 2024
  • RC3: 'Comment on wes-2024-35', Anonymous Referee #3, 04 May 2024
    • AC3: 'Reply on RC3', Tahir Malik, 14 Jun 2024
  • EC1: 'Comment on wes-2024-35', Alessandro Bianchini, 04 May 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2024-35', Anonymous Referee #1, 23 Apr 2024
    • AC1: 'Reply on RC1', Tahir Malik, 14 Jun 2024
  • RC2: 'Comment on wes-2024-35', Anonymous Referee #2, 23 Apr 2024
    • AC2: 'Reply on RC2', Tahir Malik, 14 Jun 2024
  • RC3: 'Comment on wes-2024-35', Anonymous Referee #3, 04 May 2024
    • AC3: 'Reply on RC3', Tahir Malik, 14 Jun 2024
  • EC1: 'Comment on wes-2024-35', Alessandro Bianchini, 04 May 2024
Tahir H. Malik and Christian Bak
Tahir H. Malik and Christian Bak

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Short summary
This study investigates how wind turbine blades damaged by erosion, along with changing wind conditions, affect power output. Even minor blade damage can lead to significant energy losses, especially in turbulent winds. Using simulations, we discovered that standard power data analysis methods, including time-averaging, can hide these losses. This research highlights the need for better blade damage detection and careful wind data analysis to optimize wind farm performance.
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