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Communication Dans Un Congrès Année : 2015

Review and analysis of SCADA data-based methods for health monitoring of wind turbines

Résumé

The need for renewable energy has led to a fast increase of number of the wind turbines constructed each year. To monitor wind turbines farms, operating and maintenance managers need new effective and automatic tools compatible with a large number of wind turbines. This monitoring task is usually completed by Condition Monitoring System, but researches have been conducted on the utilization of SCADA (Supervisory Control And Data Acquisition) data for condition and predictive maintenance. This paper explains the difficulty of using this new source of information, and introduces the different techniques presented in the literature form 2001 up to 2014. Two classes of approaches can be identified: “internal” approaches using only data from one turbine, and “external” approaches relying on the comparison of one turbine to the other within the same farm. Both approaches have different pros and cons: internal approaches make use of the link between the components in the same turbine and so reduce the influence of operating conditions on fault indicators; external approaches make use of the correlation between SCADA variables measured on different turbines and can thus reduce the influence of wind conditions on the fault indicators. This paper sums up the latest available techniques and it shows that new areas of research can be explored with SCADA data. The obtained fault indicators still remain sensitive to the operating conditions and stochastic variations of the wind load. Combining advantages of the two approaches could reduce both influences.
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Dates et versions

hal-01237912 , version 1 (04-12-2015)

Identifiants

  • HAL Id : hal-01237912 , version 1

Citer

Alexis Lebranchu, Sylvie Charbonnier, Christophe Bérenguer, Frédéric Prevost. Review and analysis of SCADA data-based methods for health monitoring of wind turbines. ESREL 2015 - 25th European Safety and Reliability Conference, Sep 2015, Zurich, Switzerland. pp.2413-2421. ⟨hal-01237912⟩
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