Computationally Efficient Uncertainty Minimization in Wind Turbine Extreme Load Assessments
Computationally Efficient Uncertainty Minimization in Wind Turbine Extreme Load Assessments
复制标题
风力涡轮机极限负载评估中计算高效的不确定性最小化
DOI：
10.1115/1.4033511
复制
发表时间：
2016
影响因子：
2.3
通讯作者：
E. Byon
中科院分区：
文献类型：
--
作者：
Youngjun Choe;Qiyun Pan;E. Byon
为了从风中获取更多的能量，风力涡轮机的尺寸迅速增大，这引起了对风力涡轮机可靠性的严重关注。因此，国际标准要求涡轮机设计者估计在正常操作期间可能施加在涡轮机上的极端负载。在设计阶段，基于物理的负载模拟可用于此目的。然而，模拟与小的负载偏移概率相关联的极端负载在计算上是禁止的。在这项研究中，我们建议使用重要性抽样结合顺序统计量，以减少计算负担显着，同时实现更好的估计精度比现有的方法。
To harvest more energy from wind, wind turbine size has rapidly increased, entailing the serious concern on the reliability of the wind turbine. Accordingly, the international standard requires turbine designers to estimate the extreme load that could be imposed on a turbine during normal operations. At the design stage, physics-based load simulations can be used for this purpose. However, simulating the extreme load associated with a small load exceedance probability is computationally prohibitive. In this study, we propose using importance sampling combined with order statistics to reduce the computational burden significantly while achieving much better estimation accuracy than existing methods.