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Minimizing maintenance cost for offshore wind turbines following multi-level opportunistic preventive strategy

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  • Sarker, Bhaba R.
  • Faiz, Tasnim Ibn

Abstract

Cost of energy generated from offshore wind is impacted by maintenance cost to a great extent. Cost of maintenance depends primarily on the strategy for performing maintenance. In this paper a maintenance cost model for offshore wind turbine components following multilevel opportunistic preventive maintenance strategy is formulated. In this strategy, opportunity for performing preventive actions on components is taken while a failed component is replaced. Two kinds of preventive actions are considered, preventive replacement and preventive maintenance. In the former, components that undergo that action become as good as new (i.e., the replaced components, are not just as good as new, but are actually new), but in the latter, ages of components are reduced to some degree depending on the level of maintenance action. Total cost associated with maintenance depends on the setting of age groups that determine which component should be preventively maintained and to what degree. Through optimum selection of the number of age groups, cost of maintenance can be minimized. A model is formulated where total maintenance cost is expressed as a function of number of age groups for components. A numerical study is used to illustrate the model. The results show that total cost of maintenance is significantly impacted by number of age groups and age thresholds set for components.

Suggested Citation

  • Sarker, Bhaba R. & Faiz, Tasnim Ibn, 2016. "Minimizing maintenance cost for offshore wind turbines following multi-level opportunistic preventive strategy," Renewable Energy, Elsevier, vol. 85(C), pages 104-113.
    • Handle: RePEc:eee:renene:v:85:y:2016:i:c:p:104-113
    DOI: 10.1016/j.renene.2015.06.030
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    References listed on IDEAS

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    1. Nielsen, Jannie Jessen & Sørensen, John Dalsgaard, 2011. "On risk-based operation and maintenance of offshore wind turbine components," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 218-229.
    2. Nguyen, Trinh Hoang & Prinz, Andreas & Friisø, Trond & Nossum, Rolf & Tyapin, Ilya, 2013. "A framework for data integration of offshore wind farms," Renewable Energy, Elsevier, vol. 60(C), pages 150-161.
    3. Shafiee, Mahmood, 2015. "Maintenance logistics organization for offshore wind energy: Current progress and future perspectives," Renewable Energy, Elsevier, vol. 77(C), pages 182-193.
    4. Tian, Zhigang & Jin, Tongdan & Wu, Bairong & Ding, Fangfang, 2011. "Condition based maintenance optimization for wind power generation systems under continuous monitoring," Renewable Energy, Elsevier, vol. 36(5), pages 1502-1509.
    5. Ding, Fangfang & Tian, Zhigang, 2012. "Opportunistic maintenance for wind farms considering multi-level imperfect maintenance thresholds," Renewable Energy, Elsevier, vol. 45(C), pages 175-182.
    6. Laura, Castro-Santos & Vicente, Diaz-Casas, 2014. "Life-cycle cost analysis of floating offshore wind farms," Renewable Energy, Elsevier, vol. 66(C), pages 41-48.
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