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Using a Hybrid Cost-FMEA Analysis for Wind Turbine Reliability Analysis

Author

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  • Nacef Tazi

    (Institut Charles Delaunay, LM2S/STMR, CNRS, University of Technology of Troyes, 12 rue Marie Curie, CS 42060, 10004 Troyes Cedex, France)

  • Eric Châtelet

    (Institut Charles Delaunay, LM2S/STMR, CNRS, University of Technology of Troyes, 12 rue Marie Curie, CS 42060, 10004 Troyes Cedex, France)

  • Youcef Bouzidi

    (Institut Charles Delaunay, CREIDD, CNRS, University of Technology of Troyes, 12 rue Marie Curie, CS 42060, 10004 Troyes Cedex, France)

Abstract

Failure mode and effects analysis (FMEA) has been proven to be an effective methodology to improve system design reliability. However, the standard approach reveals some weaknesses when applied to wind turbine systems. The conventional criticality assessment method has been criticized as having many limitations such as the weighting of severity and detection factors. In this paper, we aim to overcome these drawbacks and develop a hybrid cost-FMEA by integrating cost factors to assess the criticality, these costs vary from replacement costs to expected failure costs. Then, a quantitative comparative study is carried out to point out average failure rate, main cause of failure, expected failure costs and failure detection techniques. A special reliability analysis of gearbox and rotor-blades are presented.

Suggested Citation

  • Nacef Tazi & Eric Châtelet & Youcef Bouzidi, 2017. "Using a Hybrid Cost-FMEA Analysis for Wind Turbine Reliability Analysis," Energies, MDPI, vol. 10(3), pages 1-20, February.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:3:p:276-:d:91631
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    References listed on IDEAS

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    1. Xiyun Yang & Jinxia Li & Wei Liu & Peng Guo, 2011. "Petri Net Model and Reliability Evaluation for Wind Turbine Hydraulic Variable Pitch Systems," Energies, MDPI, vol. 4(6), pages 1-20, June.
    2. Mahmood Shafiee & Fateme Dinmohammadi, 2014. "An FMEA-Based Risk Assessment Approach for Wind Turbine Systems: A Comparative Study of Onshore and Offshore," Energies, MDPI, vol. 7(2), pages 1-24, February.
    3. Pierre Tchakoua & René Wamkeue & Mohand Ouhrouche & Fouad Slaoui-Hasnaoui & Tommy Andy Tameghe & Gabriel Ekemb, 2014. "Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges," Energies, MDPI, vol. 7(4), pages 1-36, April.
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    Cited by:

    1. Li, He & Diaz, H. & Guedes Soares, C., 2021. "A developed failure mode and effect analysis for floating offshore wind turbine support structures," Renewable Energy, Elsevier, vol. 164(C), pages 133-145.
    2. Bhattacharjee, Pushparenu & Dey, Vidyut & Mandal, U.K. & Paul, Susmita, 2022. "Quantitative risk assessment of submersible pump components using Interval number-based Multinomial Logistic Regression(MLR) model," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    3. Li, He & Teixeira, Angelo P. & Guedes Soares, C., 2020. "A two-stage Failure Mode and Effect Analysis of offshore wind turbines," Renewable Energy, Elsevier, vol. 162(C), pages 1438-1461.
    4. Li, He & Guedes Soares, C, 2022. "Assessment of failure rates and reliability of floating offshore wind turbines," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    5. Tazi, Nacef & Châtelet, Eric & Bouzidi, Youcef, 2018. "How combined performance and propagation of failure dependencies affect the reliability of a MSS," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 531-541.
    6. Mohamed, Emad & Seresht, Nima Gerami & Jafari, Parinaz & AbouRizk, Simaan, 2024. "Risk assessment for onshore wind projects in Canada," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    7. Bhardwaj, U. & Teixeira, A.P. & Soares, C. Guedes, 2019. "Reliability prediction of an offshore wind turbine gearbox," Renewable Energy, Elsevier, vol. 141(C), pages 693-706.
    8. Caputo, Antonio C. & Federici, Alessandro & Pelagagge, Pacifico M. & Salini, Paolo, 2023. "Offshore wind power system economic evaluation framework under aleatory and epistemic uncertainty," Applied Energy, Elsevier, vol. 350(C).

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