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Analysis of the Gearbox Oil Maintenance Procedures in Wind Energy II

Author

Listed:
  • José Ramón del Álamo Salgado

    (Eolia Renovables, 29010 Málaga, Spain)

  • Mario J. Durán Martínez

    (Department of Electrical Engineering, School of Engineering, University of Malaga, 29016 Málaga, Spain)

  • Francisco J. Muñoz Gutiérrez

    (Department of Electrical Engineering, School of Engineering, University of Malaga, 29016 Málaga, Spain)

  • Jorge Alarcon

    (Bureau Veritas—Oil Condition Monitoring, Houston, TX 77477, USA)

Abstract

Recent works have addressed the analysis of some situations that alter the gearbox oil results in wind energy conversion systems (WECS). This work contributes by completing the analysis of additional situations, based on key operational data collected from 10 different multi-megawatt wind turbines at two different locations with two top-tier technologies, and has demonstrated that the oil analysis results can be altered in practice. As important as detecting these situations is to verify how the data collected by the different operators and transferred to the laboratories, this relevant information is not included in most cases. The issues that can stem from this lack of valuable data can be mitigated with a new and more complete template. This paper proposes a detailed template that is ready for an industrial use and contributes to standardizing the information handled by all actors. The suggested template, which is designed based on extensive experimental results and an in-depth analysis, provides detailed information for laboratories to improve conclusions, recommendations and action plans. The investigation provides a high archival value for researchers whose investigation deals with gearbox oil maintenance. Furthermore, the global impact of the proposal on the wind industry can be very relevant in terms of benefits and it will ultimately be an advance in the evolution of the operation and maintenance of wind farms.

Suggested Citation

  • José Ramón del Álamo Salgado & Mario J. Durán Martínez & Francisco J. Muñoz Gutiérrez & Jorge Alarcon, 2021. "Analysis of the Gearbox Oil Maintenance Procedures in Wind Energy II," Energies, MDPI, vol. 14(12), pages 1-18, June.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:12:p:3572-:d:575646
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    References listed on IDEAS

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    1. José Ramón del Álamo & Mario J. Duran & Francisco J. Muñoz, 2020. "Analysis of the Gearbox Oil Maintenance Procedures in Wind Energy," Energies, MDPI, vol. 13(13), pages 1-18, July.
    2. Sathishkumar Nachimuthu & Ming J. Zuo & Yi Ding, 2019. "A Decision-making Model for Corrective Maintenance of Offshore Wind Turbines Considering Uncertainties," Energies, MDPI, vol. 12(8), pages 1-13, April.
    3. Francesc Pozo & Yolanda Vidal & Josep M. Serrahima, 2016. "On Real-Time Fault Detection in Wind Turbines: Sensor Selection Algorithm and Detection Time Reduction Analysis," Energies, MDPI, vol. 9(7), pages 1-22, July.
    4. Cristian Velandia-Cardenas & Yolanda Vidal & Francesc Pozo, 2021. "Wind Turbine Fault Detection Using Highly Imbalanced Real SCADA Data," Energies, MDPI, vol. 14(6), pages 1-26, March.
    5. Leite, Gustavo de Novaes Pires & Araújo, Alex Maurício & Rosas, Pedro André Carvalho, 2018. "Prognostic techniques applied to maintenance of wind turbines: a concise and specific review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1917-1925.
    6. Shafiee, Mahmood & Sørensen, John Dalsgaard, 2019. "Maintenance optimization and inspection planning of wind energy assets: Models, methods and strategies," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    7. Ackermann, Thomas & Söder, Lennart, 2000. "Wind energy technology and current status: a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 4(4), pages 315-374, December.
    8. Francesc Pozo & Yolanda Vidal & Óscar Salgado, 2018. "Wind Turbine Condition Monitoring Strategy through Multiway PCA and Multivariate Inference," Energies, MDPI, vol. 11(4), pages 1-19, March.
    9. Roggenburg, Michael & Esquivel-Puentes, Helber A. & Vacca, Andrea & Bocanegra Evans, Humberto & Garcia-Bravo, Jose M. & Warsinger, David M. & Ivantysynova, Monika & Castillo, Luciano, 2020. "Techno-economic analysis of a hydraulic transmission for floating offshore wind turbines," Renewable Energy, Elsevier, vol. 153(C), pages 1194-1204.
    10. Mingzhu Tang & Qi Zhao & Steven X. Ding & Huawei Wu & Linlin Li & Wen Long & Bin Huang, 2020. "An Improved LightGBM Algorithm for Online Fault Detection of Wind Turbine Gearboxes," Energies, MDPI, vol. 13(4), pages 1-16, February.
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    Cited by:

    1. Gang Li & Weidong Zhu, 2022. "A Review on Up-to-Date Gearbox Technologies and Maintenance of Tidal Current Energy Converters," Energies, MDPI, vol. 15(23), pages 1-24, December.

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