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A Stochastic Petri Net Model for O&M Planning of Floating Offshore Wind Turbines

Author

Listed:
  • Tobi Elusakin

    (Department of Energy and Power, Cranfield University, College Road, Bedfordshire MK43 0AL, UK)

  • Mahmood Shafiee

    (Mechanical Engineering Group, School of Engineering, University of Kent, Canterbury CT2 7NT, UK)

  • Tosin Adedipe

    (Department of Energy and Power, Cranfield University, College Road, Bedfordshire MK43 0AL, UK)

  • Fateme Dinmohammadi

    (The Bartlett Centre for Advanced Spatial Analysis (CASA), University College London (UCL), Gower Street, London WC1E 6BTL, UK)

Abstract

With increasing deployment of offshore wind farms further from shore and in deeper waters, the efficient and effective planning of operation and maintenance (O&M) activities has received considerable attention from wind energy developers and operators in recent years. The O&M planning of offshore wind farms is a complicated task, as it depends on many factors such as asset degradation rates, availability of resources required to perform maintenance tasks (e.g., transport vessels, service crew, spare parts, and special tools) as well as the uncertainties associated with weather and climate variability. A brief review of the literature shows that a lot of research has been conducted on optimizing the O&M schedules for fixed-bottom offshore wind turbines; however, the literature for O&M planning of floating wind farms is too limited. This paper presents a stochastic Petri network (SPN) model for O&M planning of floating offshore wind turbines (FOWTs) and their support structure components, including floating platform, moorings and anchoring system. The proposed model incorporates all interrelationships between different factors influencing O&M planning of FOWTs, including deterioration and renewal process of components within the system. Relevant data such as failure rate, mean-time-to-failure (MTTF), degradation rate, etc. are collected from the literature as well as wind energy industry databases, and then the model is tested on an NREL 5 MW reference wind turbine system mounted on an OC3-Hywind spar buoy floating platform. The results indicate that our proposed model can significantly contribute to the reduction of O&M costs in the floating offshore wind sector.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:1134-:d:503039
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    References listed on IDEAS

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    Cited by:

    1. McMorland, J. & Collu, M. & McMillan, D. & Carroll, J., 2022. "Operation and maintenance for floating wind turbines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    2. Arthur Henrique de Andrade Melani & Miguel Angelo de Carvalho Michalski & Carlos Alberto Murad & Adherbal Caminada Netto & Gilberto Francisco Martha de Souza, 2022. "Generalized Stochastic Petri Nets for Planning and Optimizing Maintenance Logistics of Small Hydroelectric Power Plants," Energies, MDPI, vol. 15(8), pages 1-16, April.
    3. Brooks, Sam & Mahmood, Minhal & Roy, Rajkumar & Manolesos, Marinos & Salonitis, Konstantinos, 2023. "Self-reconfiguration simulations of turbines to reduce uneven farm degradation," Renewable Energy, Elsevier, vol. 206(C), pages 1301-1314.
    4. Centeno-Telleria, Manu & Aizpurua, Jose Ignacio & Penalba, Markel, 2023. "Computationally efficient analytical O&M model for strategic decision-making in offshore renewable energy systems," Energy, Elsevier, vol. 285(C).
    5. 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).

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