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Effects of wake on gearbox design load cases identified from fleet-wide operational data

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Abstract

Drivetrains play an essential role in guaranteeing the reliability of wind turbines. A challenge in their design is the wide range of loading conditions they are exposed to. Several design load cases are required to be simulated in order to ensure that the ultimate loads are not exceeded, and to validate that the fatigue lifetime matches the design requirements. These loading conditions include among other (emergency) stops, start-ups, and normal and parked operation in different ambient conditions (wind speed, wave height, …). The design requirements are validated through a combination of functional, robustness and system tests when the turbine is operated in the design load cases. Within the context of Industry 4.0, turbines are becoming increasingly equipped with sensors. This offers opportunities for the in-depth validation of design hypotheses, as it allows to obtain detailed insights in the occurrence of loading events to which turbines are exposed to throughout their lifetime. This can be incorporated in future design iterations to further optimize the design based on more realistic loading conditions. The goal of this paper is to automatically and continuously classify SCADA data of an offshore farm in the aforementioned design load cases on a farm-wide level. Using this framework, the effects of wake on loading conditions are assessed in a data-driven manner.

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Acknowledgements

The authors gratefully acknowledge the financial support via the MaDurOS program from VLAIO (Flemish Agency for Innovation and Entrepre-neurship) and SIM (Strategic Initiative Materials) through project SBO MaSiWEC (HBC.2017.0606). The authors would also like to acknowledge the support of De Blauwe Cluster through the project Supersized 4.0. The authors would also like to acknowledge FWO (Fonds Wetenschappelijk Onderzoek) for their support through the SB grant of Timothy Verstraeten (#1S47617N).

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Authors and Affiliations

  1. OWI-Lab, Vrije Universiteit Brussel, Pleinlaan 2, 1020, Elsene, Belgium

    Pieter-Jan Daems, Timothy Verstraeten, Cédric Peeters & Jan Helsen

  2. AI-Lab, Vrije Universiteit Brussel, Pleinlaan 9, 1020, Elsene, Belgium

    Timothy Verstraeten

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  1. Pieter-Jan Daems
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  2. Timothy Verstraeten
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  3. Cédric Peeters
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  4. Jan Helsen
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Correspondence to Pieter-Jan Daems.

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Daems, PJ., Verstraeten, T., Peeters, C. et al. Effects of wake on gearbox design load cases identified from fleet-wide operational data. Forsch Ingenieurwes 85, 553–558 (2021). https://doi.org/10.1007/s10010-021-00444-3

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  • DOI: https://doi.org/10.1007/s10010-021-00444-3

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