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Advanced Monitoring of Wind Turbine

In: Wind Solar Hybrid Renewable Energy System

Author

Listed:
  • Alexandre Teplaira Boum
  • Adolph Moukengue Imano
  • Steve Alan Talla Ouambo

Abstract

This chapter presents a general framework for the doubly fed induction generator (DFIG). We apply and analyze the behavior of three estimation techniques, which are the unscented Kalman filter (UKF), the high gain observer (HGO) and the moving horizon estimation (MHE). These estimations are used for parameters estimation of the doubly fed induction generator (DFIG) driven by wind turbine. A comparison of those techniques has been made under different aspects notably, computation time and estimation accuracy in two modes of operation of the DFIG, the healthy mode and the faulty mode. The performance of the MHE has been clearly superior to other estimators during our experiments. These estimation tools can be used for monitoring purposes.

Suggested Citation

  • Alexandre Teplaira Boum & Adolph Moukengue Imano & Steve Alan Talla Ouambo, 2020. "Advanced Monitoring of Wind Turbine," Chapters, in: Kenneth Eloghene Okedu & Ahmed Tahour & Abdel Ghani Aissaoui (ed.), Wind Solar Hybrid Renewable Energy System, IntechOpen.
    • Handle: RePEc:ito:pchaps:185064
    DOI: 10.5772/intechopen.84840
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    More about this item

    Keywords

    doubly-fed induction generator; high gain observer; unscented Kalman filter; moving horizon estimation; parameters estimation; monitoring;
    All these keywords.

    JEL classification:

    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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