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Discussion on the Suitability of SCADA-Based Condition Monitoring for Wind Turbine Fault Diagnosis through Temperature Data Analysis

Author

Listed:
  • Alessandro Murgia

    (EluciDATA Lab of Sirris, Bd A. Reyerslaan 80, 1030 Brussels, Belgium)

  • Robbert Verbeke

    (EluciDATA Lab of Sirris, Bd A. Reyerslaan 80, 1030 Brussels, Belgium)

  • Elena Tsiporkova

    (EluciDATA Lab of Sirris, Bd A. Reyerslaan 80, 1030 Brussels, Belgium)

  • Ludovico Terzi

    (ENGIE Italia, Via Chiese, 20126 Milan, Italy)

  • Davide Astolfi

    (Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy)

Abstract

Wind turbines are expected to provide on the order of 50% of the electricity worldwide in the near future, and it is therefore fundamental to reduce the costs associated with this form of energy conversion, which regard maintenance as the first item of expenditure. SCADA-based condition monitoring for anomaly detection is commonly presented as a convenient solution for fault diagnosis on turbine components. However, its suitability is generally proven by empirical analyses which are limited in time and based on a circumscribed number of turbines. To cope with this lack of validation, this paper performs a controlled experiment to evaluate the suitability of SCADA-based condition monitoring for fault diagnosis in a fleet of eight turbines monitored for over 11 years. For the controlled experiment, a weakly supervised method was used to model the normal behavior of the turbine component. Such a model is instantiated as a convolutional neural network. The method, instantiated as a threshold-based method, proved to be suitable for diagnosis, i.e. the identification of all drivetrain failures with a considerable advance time. On the other hand, the wide variability between the time the alarm is raised and the fault is observed suggests its limited suitability for prognosis.

Suggested Citation

  • Alessandro Murgia & Robbert Verbeke & Elena Tsiporkova & Ludovico Terzi & Davide Astolfi, 2023. "Discussion on the Suitability of SCADA-Based Condition Monitoring for Wind Turbine Fault Diagnosis through Temperature Data Analysis," Energies, MDPI, vol. 16(2), pages 1-20, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:2:p:620-:d:1025275
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    References listed on IDEAS

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    Cited by:

    1. Davide Astolfi, 2023. "Wind Turbine Drivetrain Condition Monitoring through SCADA-Collected Temperature Data: Discussion of Selected Recent Papers," Energies, MDPI, vol. 16(9), pages 1-4, April.

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