Wind Turbine Blade Damage Evaluation under Multiple Operating Conditions and Based on 10-Min SCADA Data

Author:

Chrétien Antoine1,Tahan Antoine1ORCID,Pelletier Francis2

Affiliation:

1. Department of Mechanical Engineering, École de Technologie Supérieure, Montreal, QC H3C 1K3, Canada

2. Advanced Analytics Research Power Factors, Montreal, QC H3B 4W5, Canada

Abstract

The present paper aims to enable the assessment of the fatigue damage of wind turbine blades over a long duration (e.g., several months/years) in conjunction with different operating regimes and based on two information sources: the 10-min SCADA data and an interpolation using response surfaces identified using the FAST aeroelastic numerical tool. To assess blade damage, prior studies highlighted the need for a high-frequency (>1 Hz) sampling rate. Because of data availability and computation resource limitations, such methods limit the duration of the analysis period, making the direct use of such an approach based on a 1 Hz wind speed signal in current wind farms impractical. The present work investigates the possibility of overcoming these issues by estimating the equivalent damage using a 1 Hz wind speed for each 10-min sample stored in the SCADA data. In the literature, the influence of operating regimes is not considered in fatigue damage estimation, and for the first time, the present project takes a pioneering approach by considering these operating regimes.

Funder

CRSNG

Publisher

MDPI AG

Reference61 articles.

1. DNV GL Energy Transition Outlook (2020, December 04). DNV GL’s Energy Transition Outlook 2020. Available online: https://eto.dnvgl.com/2020/index.html.

2. Zhu, C., Li, Y., Zhu, C., and Li, Y. (2018). Reliability Analysis of Wind Turbines, IntechOpen.

3. Li, H., Peng, W., Huang, C.-G., and Guedes Soares, C. (2022). Failure Rate Assessment for Onshore and Floating Offshore Wind Turbines. JMSE, 10.

4. Repair of wind turbine blades: Review of methods and related computational mechanics problems;Mishnaevsky;Renew. Energy,2019

5. (2013). Technology Roadmap: Wind Energy 2013, IEA.

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