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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. 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.
    2. 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.
    3. 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.
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    5. 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.
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    Cited by:

    1. Sara C. Pryor & Rebecca J. Barthelmie & Jacob J. Coburn & Xin Zhou & Marianne Rodgers & Heather Norton & M. Sergio Campobasso & Beatriz Méndez López & Charlotte Bay Hasager & Leon Mishnaevsky, 2024. "Prioritizing Research for Enhancing the Technology Readiness Level of Wind Turbine Blade Leading-Edge Erosion Solutions," Energies, MDPI, vol. 17(24), pages 1-29, December.
    2. Li, Mingxin & Jiang, Xiaoli & Carroll, James & Negenborn, Rudy R., 2024. "Operation and maintenance management for offshore wind farms integrating inventory control and health information," Renewable Energy, Elsevier, vol. 231(C).

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