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Design clustering of offshore wind turbines using probabilistic fatigue load estimation

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  • Ziegler, Lisa
  • Voormeeren, Sven
  • Schafhirt, Sebastian
  • Muskulus, Michael

Abstract

In large offshore wind farms fatigue loads on support structures can vary significantly due to differences and uncertainties in site conditions, making it necessary to optimize design clustering. An efficient probabilistic fatigue load estimation method for monopile foundations was implemented using Monte-Carlo simulations. Verification of frequency domain analysis for wave loads and scaling approaches for wind loads with time domain aero-elastic simulations lead to 95% accuracy on equivalent bending moments at mudline and tower bottom. The computational speed is in the order of 100 times faster than typical time domain tools. The model is applied to calculate location specific fatigue loads that can be used in deterministic and probabilistic design clustering. Results for an example wind farm with 150 turbines in 30–40 m water depth show a maximum load difference of 25%. Smart clustering using discrete optimization algorithms leads to a design load reduction of up to 13% compared to designs based on only the highest loaded turbine position. The proposed tool improves industry-standard clustering and provides a basis for design optimization and uncertainty analysis in large wind farms.

Suggested Citation

  • Ziegler, Lisa & Voormeeren, Sven & Schafhirt, Sebastian & Muskulus, Michael, 2016. "Design clustering of offshore wind turbines using probabilistic fatigue load estimation," Renewable Energy, Elsevier, vol. 91(C), pages 425-433.
    • Handle: RePEc:eee:renene:v:91:y:2016:i:c:p:425-433
    DOI: 10.1016/j.renene.2016.01.033
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    References listed on IDEAS

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    1. Fabian Vorpahl & Holger Schwarze & Tim Fischer & Marc Seidel & Jason Jonkman, 2013. "Offshore wind turbine environment, loads, simulation, and design," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 2(5), pages 548-570, September.
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    1. Pim van der Male & Marco Vergassola & Karel N. van Dalen, 2020. "Decoupled Modelling Approaches for Environmental Interactions with Monopile-Based Offshore Wind Support Structures," Energies, MDPI, vol. 13(19), pages 1-35, October.
    2. Velarde, Joey & Kramhøft, Claus & Sørensen, John Dalsgaard, 2019. "Global sensitivity analysis of offshore wind turbine foundation fatigue loads," Renewable Energy, Elsevier, vol. 140(C), pages 177-189.
    3. Jianhua Zhang & Won-Hee Kang & Ke Sun & Fushun Liu, 2019. "Reliability-Based Serviceability Limit State Design of a Jacket Substructure for an Offshore Wind Turbine," Energies, MDPI, vol. 12(14), pages 1-16, July.
    4. Rongyong Zhao & Daheng Dong & Cuiling Li & Steven Liu & Hao Zhang & Miyuan Li & Wenzhong Shen, 2020. "An Improved Power Control Approach for Wind Turbine Fatigue Balancing in an Offshore Wind Farm," Energies, MDPI, vol. 13(7), pages 1-20, March.
    5. Rezaei, Ramtin & Fromme, Paul & Duffour, Philippe, 2018. "Fatigue life sensitivity of monopile-supported offshore wind turbines to damping," Renewable Energy, Elsevier, vol. 123(C), pages 450-459.
    6. Marino, Enzo & Giusti, Alessandro & Manuel, Lance, 2017. "Offshore wind turbine fatigue loads: The influence of alternative wave modeling for different turbulent and mean winds," Renewable Energy, Elsevier, vol. 102(PA), pages 157-169.

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