Bivariate reliability analysis for floating wind turbines

被引:28
作者
Gaidai, Oleg [1 ]
Yakimov, Vladimir [2 ]
Wang, Fang [1 ]
Sun, Jiayao [3 ]
Wang, Kelin [1 ]
机构
[1] Shanghai Ocean Univ, Coll Engn Sci & Technol, 999 Huchenghuan Rd, Shanghai, Peoples R China
[2] Cent Marine Res & Design Inst, 6 Kavalergardskaya St, St Petersburg, Russia
[3] Jiangsu Univ Sci & Technol, 2 Mengxilu St, Zhenjiang, Peoples R China
关键词
floating wind turbine; wind turbine; green energy; sustainability; renewable energy; EXTREME LOADS; STATISTICAL EXTRAPOLATION; DESIGN; PREDICTION; FATIGUE;
D O I
10.1093/ijlct/ctad108
中图分类号
O414.1 [热力学];
学科分类号
摘要
Wind turbines are designed to withstand extreme wind- and wave-induced loads, hence a reliability study is vital. This study presents a bivariate reliability approach, suitable for accurate assessment of critical forces and moments, occurring within the wind turbine's critical mechanical parts, such as the drivetrain. A ecently developed bivariate modified Weibull method has been utilized in this study. Multivariate statistical analysis is more appropriate than a univariate one, as it accounts for cross-correlations between different system components. This study employed a bivariate modified Weibull method to estimate extreme operational loads acting on a 10-mega watt (MW) semi-submersible type floating wind turbine (FWT). Longitudinal, bending, twisting, and cyclic loads being among typical load types that FWTs and associated parts are susceptible to. Furthermore, environmental loads acting on an operating FWT being impacted by incoming wind's stochastic behavior in terms of wind speed, direction, shear, vorticity, necessitates accurate nonlinear extreme load analysis for FWT critical parts such as the drivetrain. Appropriate numerical methods were used in this study to model dynamic, structural, aerodynamic, and control aspects of the FWT system. Bending moments acting on the FWT drivetrain have been obtained from SIMPACK (Multibody Simulation Method), given realistic in-situ environmental conditions. For a 5-year return period of interest, a bivariate modified Weibull method offered robust assessment of FWT's coupled drivetrain's bending moments.
引用
收藏
页码:55 / 64
页数:10
相关论文
共 65 条
  • [1] Abdallah I., 2015, Assessment of extreme design loads for modern wind turbines using the probabilistic approach
  • [2] Extreme Loads for an Offshore Wind Turbine using Statistical Extrapolation from Limited Field Data
    Agarwal, Puneet
    Manuel, Lance
    [J]. WIND ENERGY, 2008, 11 (06) : 673 - 684
  • [3] Effects of Simulation Length and Flexible Foundation on Long-Term Response Extrapolation of a Bottom-Fixed Offshore Wind Turbine
    Barreto, David
    Karimirad, Madjid
    Ortega, Arturo
    [J]. JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING-TRANSACTIONS OF THE ASME, 2022, 144 (03):
  • [4] Cheng Y., 2022, 32 INT OC POL ENG C
  • [5] Comparative analysis of methods for modelling the short-term probability distribution of extreme wind turbine loads
    Dimitrov, Nikolay
    [J]. WIND ENERGY, 2016, 19 (04) : 717 - 737
  • [6] Investigation of Site-Specific Wind Field Parameters and Their Effect on Loads of Offshore Wind Turbines
    Ernst, Benedikt
    Seume, Joerg R.
    [J]. ENERGIES, 2012, 5 (10) : 3835 - 3855
  • [7] Falzarano J., 2012, P 11 INT C STABILITY
  • [8] Predicting the long term distribution of extreme loads from limited duration data: Comparing full integration and approximate methods
    Fitzwater, LM
    Cornell, CA
    [J]. JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME, 2002, 124 (04): : 378 - 386
  • [9] Predicting design wind turbine loads from limited data: Comparing random process and random peak models
    Fitzwater, LM
    Winterstein, SR
    [J]. JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME, 2001, 123 (04): : 364 - 371
  • [10] Towards an Improved Understanding of Statistical Extrapolation for Wind Turbine Extreme Loads
    Fogle, Jeffrey
    Agarwal, Puneet
    Manuel, Lance
    [J]. WIND ENERGY, 2008, 11 (06) : 613 - 635