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An autonomous decision-making agent for offshore wind turbine blades under leading edge erosion

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  • Lopez, Javier Contreras
  • Kolios, Athanasios

Abstract

The increasing pressure of offshore wind developments is leading to projects being located in areas with more difficult access and greater weather barriers. As these constraints increase, O&M costs also grow in importance. Therefore, the current scenario requires a careful planning to avoid unnecessary costly maintenance decisions or unexpected failures. To overcome the problem of increasing O&M costs and difficult access, this manuscript presents an autonomous decision-making Reinforcement Learning (RL) agent to improve O&M planning for the Leading Edge Erosion (LEE) problem. The method developed in this work makes use of a linear degradation model to account for the damage progression dynamics and site-specific weather models. The RL-based agent proposed in this manuscript is able to reduce expected O&M costs in the range of 12%–21% when compared with condition-based policies.

Suggested Citation

  • Lopez, Javier Contreras & Kolios, Athanasios, 2024. "An autonomous decision-making agent for offshore wind turbine blades under leading edge erosion," Renewable Energy, Elsevier, vol. 227(C).
    • Handle: RePEc:eee:renene:v:227:y:2024:i:c:s0960148124005901
    DOI: 10.1016/j.renene.2024.120525
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    References listed on IDEAS

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    1. Cevasco, D. & Koukoura, S. & Kolios, A.J., 2021. "Reliability, availability, maintainability data review for the identification of trends in offshore wind energy applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    2. Tobi Elusakin & Mahmood Shafiee & Tosin Adedipe & Fateme Dinmohammadi, 2021. "A Stochastic Petri Net Model for O&M Planning of Floating Offshore Wind Turbines," Energies, MDPI, vol. 14(4), pages 1-18, February.
    3. Li, Mingxin & Jiang, Xiaoli & Carroll, James & Negenborn, Rudy R., 2022. "A multi-objective maintenance strategy optimization framework for offshore wind farms considering uncertainty," Applied Energy, Elsevier, vol. 321(C).
    4. Mishnaevsky, Leon & Hasager, Charlotte Bay & Bak, Christian & Tilg, Anna-Maria & Bech, Jakob I. & Doagou Rad, Saeed & Fæster, Søren, 2021. "Leading edge erosion of wind turbine blades: Understanding, prevention and protection," Renewable Energy, Elsevier, vol. 169(C), pages 953-969.
    5. Hasager, C. & Vejen, F. & Bech, J.I. & Skrzypiński, W.R. & Tilg, A.-M. & Nielsen, M., 2020. "Assessment of the rain and wind climate with focus on wind turbine blade leading edge erosion rate and expected lifetime in Danish Seas," Renewable Energy, Elsevier, vol. 149(C), pages 91-102.
    6. López, Javier Contreras & Kolios, Athanasios & Wang, Lin & Chiachio, Manuel, 2023. "A wind turbine blade leading edge rain erosion computational framework," Renewable Energy, Elsevier, vol. 203(C), pages 131-141.
    7. Schouten, Thijs Nicolaas & Dekker, Rommert & Hekimoğlu, Mustafa & Eruguz, Ayse Sena, 2022. "Maintenance optimization for a single wind turbine component under time-varying costs," European Journal of Operational Research, Elsevier, vol. 300(3), pages 979-991.
    8. Shafiee, Mahmood, 2015. "Maintenance logistics organization for offshore wind energy: Current progress and future perspectives," Renewable Energy, Elsevier, vol. 77(C), pages 182-193.
    9. Charlotte Bay Hasager & Flemming Vejen & Witold Robert Skrzypiński & Anna-Maria Tilg, 2021. "Rain Erosion Load and Its Effect on Leading-Edge Lifetime and Potential of Erosion-Safe Mode at Wind Turbines in the North Sea and Baltic Sea," Energies, MDPI, vol. 14(7), pages 1-24, April.
    10. Zou, Guang & Kolios, Athanasios, 2022. "Quantifying the value of negative inspection outcomes in fatigue maintenance planning: Cost reduction, risk mitigation and reliability growth," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    11. Herring, Robbie & Dyer, Kirsten & Martin, Ffion & Ward, Carwyn, 2019. "The increasing importance of leading edge erosion and a review of existing protection solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    12. Matthias Schramm & Hamid Rahimi & Bernhard Stoevesandt & Kim Tangager, 2017. "The Influence of Eroded Blades on Wind Turbine Performance Using Numerical Simulations," Energies, MDPI, vol. 10(9), pages 1-15, September.
    13. Saleh, Ali & Chiachío, Manuel & Salas, Juan Fernández & Kolios, Athanasios, 2023. "Self-adaptive optimized maintenance of offshore wind turbines by intelligent Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
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