海上浮式风力机载荷数值模拟输入参数敏感性分析

IF 3.6 Q3 GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY Wind Energy Science Pub Date : 2023-10-24 DOI:10.5194/wes-8-1575-2023
Will Wiley, Jason Jonkman, Amy Robertson, Kelsey Shaler
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引用次数: 0

摘要

摘要浮动式风力涡轮机必须承受来自风和海洋环境的独特和具有挑战性的负载。为了降低开发的风险,对这些负荷的准确预测是必要的。建模预测的不确定性导致所需的安全系数增大,增加了项目成本和能源成本。复杂的气动-水弹性建模工具使用许多输入参数来表示风、波浪、电流、空气动力载荷、水动力载荷和结构特性。了解这些参数中的哪一个最终驱动设计是有帮助的。在这项工作中,对35个不同的输入参数进行了极限和疲劳代理负载敏感性分析,使用基本效应方法来确定最具影响力的参数,该案例研究涉及国家可再生能源实验室(NREL)在OC4-DeepCwind半潜式船正常运行时顶部的5mw基线风力涡轮机。每个参数的重要性是通过在三种风速条件下使用14个感兴趣的响应量来评估的。研究表明,湍流风速标准差是最敏感的参数;这个值不仅对涡轮负载很重要,而且对整个系统响应也很重要。系统质心风向对系统旋转和塔荷载的影响最大。发现当前速度是系统全局运动的最主要参数,因此是系泊载荷的最主要参数。除标准偏差外,所有被测风湍流参数也都有影响。波浪特性对某些疲劳代理载荷有影响,但对这些操作载荷情况下的极端极限载荷没有显著影响。考虑了随机环境条件下所需的随机种子数,以确保灵敏度是由输入参数而不是由种子决定的。确定了参数空间中所需的分析点的数量,从而使结论具有全局敏感性。结果是特定于平台,涡轮和参数范围的选择,但所证明的方法可以广泛应用于参数不确定性的指导焦点。
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Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads
Abstract. Floating wind turbines must withstand a unique and challenging set of loads from the wind and ocean environment. To de-risk development, accurate predictions of these loads are necessary. Uncertainty in modeling predictions leads to larger required safety factors, increasing project costs and the levelized cost of energy. Complex aero-hydro-elastic modeling tools use many input parameters to represent the wind, waves, current, aerodynamic loads, hydrodynamic loads, and structural properties. It is helpful to understand which of these parameters ultimately drives a design. In this work, an ultimate and fatigue-proxy load sensitivity analysis was performed with 35 different input parameters, using an elementary effects approach to identify the most influential parameters for a case study involving the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine atop the OC4-DeepCwind semisubmersible during normal operation. The importance of each parameter was evaluated using 14 response quantities of interest across three operational wind speed conditions. The study concludes that turbulent wind velocity standard deviation is the parameter with the strongest sensitivity; this value is important not just for turbine loads, but also for the global system response. The system center of mass in the wind direction is found to have the highest impact on the system rotation and tower loads. The current velocity is found to be the most dominating parameter for the system global motion and consequently the mooring loads. All tested wind turbulence parameters in addition to the standard deviation are also found to be influential. Wave characteristics are influential for some fatigue-proxy loading but do not significantly impact the extreme ultimate loads in these operational load cases. The required number of random seeds for stochastic environmental conditions is considered to ensure that the sensitivities are due to the input parameters and not due to the seed. The required number of analysis points in the parameter space is identified so that the conclusions represent a global sensitivity. The results are specific to the platform, turbine, and choice of parameter ranges, but the demonstrated approach can be applied widely to guide focus in parameter uncertainty.
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来源期刊
Wind Energy Science
Wind Energy Science GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY-
CiteScore
6.90
自引率
27.50%
发文量
115
审稿时长
28 weeks
期刊最新文献
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