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Modelling and simulation of the operation and maintenance of offshore wind turbines

Author

Listed:
  • Fernando Santos
  • Ângelo P Teixeira
  • C Guedes Soares

Abstract

The offshore environment limits the accessibility to the wind turbines and subjects them to faster degradation processes than in onshore. Thus, operation and maintenance is more challenging and costly and represents a considerable share of the cost of energy. It is therefore important to identify which factors most influence the turbines’ performance, namely, the availability, overall cost and revenues, so that actions can be taken to minimize their effect. This article addresses such issues by presenting a parametric study on how the variation of failure and repair models, vessels logistic times, weather windows and waiting times affect a wind turbine performance. Offshore failure models/data were not usually available on the public domain, being obtained herein from onshore ones using an empirical approach based on stress factors for mechanical systems. The baseline model results from the optimization of an operation and maintenance strategy based on corrective maintenance replacements and imperfect age-based preventive maintenance repairs. Generalized stochastic Petri nets with predicates coupled with Monte Carlo simulation are used for modelling and simulation. Results are discussed.

Suggested Citation

  • Fernando Santos & Ângelo P Teixeira & C Guedes Soares, 2015. "Modelling and simulation of the operation and maintenance of offshore wind turbines," Journal of Risk and Reliability, , vol. 229(5), pages 385-393, October.
    • Handle: RePEc:sae:risrel:v:229:y:2015:i:5:p:385-393
    DOI: 10.1177/1748006X15589209
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Eryilmaz, Serkan & Devrim, Yilser, 2019. "Theoretical derivation of wind plant power distribution with the consideration of wind turbine reliability," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 192-197.
    3. Masoud Asgarpour & John Dalsgaard Sørensen, 2018. "Bayesian Based Diagnostic Model for Condition Based Maintenance of Offshore Wind Farms," Energies, MDPI, vol. 11(2), pages 1-17, January.
    4. 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.
    5. Kang, Jichuan & Sun, Liping & Guedes Soares, C., 2019. "Fault Tree Analysis of floating offshore wind turbines," Renewable Energy, Elsevier, vol. 133(C), pages 1455-1467.

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