Volume 3, issue 1 | Copyright
Wind Energ. Sci., 3, 149-162, 2018
https://doi.org/10.5194/wes-3-149-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research articles 26 Mar 2018

Research articles | 26 Mar 2018

Application of a Monte Carlo procedure for probabilistic fatigue design of floating offshore wind turbines

Kolja Müller and Po Wen Cheng Kolja Müller and Po Wen Cheng
  • Stuttgart Wind Energy at Institute of Aircraft Design, University of Stuttgart, Stuttgart, Germany

Abstract. Fatigue load assessment of floating offshore wind turbines poses new challenges on the feasibility of numerical procedures. Due to the increased sensitivity of the considered system with respect to the environmental conditions from wind and ocean, the application of common procedures used for fixed-bottom structures results in either inaccurate simulation results or hard-to-quantify conservatism in the system design. Monte Carlo-based sampling procedures provide a more realistic approach to deal with the large variation in the environmental conditions, although basic randomization has shown slow convergence. Specialized sampling methods allow efficient coverage of the complete design space, resulting in faster convergence and hence a reduced number of required simulations. In this study, a quasi-random sampling approach based on Sobol sequences is applied to select representative events for the determination of the lifetime damage. This is calculated applying Monte Carlo integration, using subsets of a resulting total of 16200 coupled time–domain simulations performed with the simulation code FAST. The considered system is the Danmarks Tekniske Universitet (DTU) 10MW reference turbine installed on the LIFES50+ OO-Star Wind Floater Semi 10MW floating platform. Statistical properties of the considered environmental parameters (i.e., wind speed, wave height and wave period) are determined based on the measurement data from the Gulf of Maine, USA. Convergence analyses show that it is sufficient to perform around 200 simulations in order to reach less than 10% uncertainty of lifetime fatigue damage-equivalent loading. Complementary in-depth investigation is performed, focusing on the load sensitivity and the impact of outliers (i.e., values far away from the mean). Recommendations for the implementation of the proposed methodology in the design process are also provided.

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An efficient and accurate Monte Carlo approach is presented to assess the lifetime fatigue loading on a floating offshore wind turbine accurately. This is typically challenging in simulation effort due to the many different combinations of relevant environmental conditions which need to be considered. The applied method uses quasi-random Sobol sequences and shows promising performance with respect to convergence and accuracy.
An efficient and accurate Monte Carlo approach is presented to assess the lifetime fatigue...
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