ABSTRACT

In the present paper, we present a surrogate model, which can be used to estimate extreme tower loads on a wind turbine from a number of signals and a suitable simulation tool. Due to the requirements of the International Electrotechnical Commission (IEC) Standard 61400-1, assessing extreme tower loads on wind turbines constitutes a key component of the design phase. The proposed model imputes tower loads by matching observed signals with simulated quantities using proximities induced by random forests. In this way, the algorithm's adaptability to high-dimensional and sparse settings is exploited without using regression-based surrogate loads (which may display misleading probabilistic characteristics). Finally, the model is applied to estimate tower loads on an operating wind turbine from data on its operational statistics.

摘要

在本文中，我们提出了一个替代模型，该模型可用于从多个信号和合适的仿真工具估计风力涡轮机上的极端塔架负载。由于国际电工委员会 (IEC) 标准 61400-1 的要求，评估风力涡轮机的极端塔架负载是设计阶段的关键组成部分。所提出的模型通过使用随机森林诱导的近似值将观察到的信号与模拟量相匹配来估算塔的负载。通过这种方式，可以利用算法对高维和稀疏设置的适应性，而无需使用基于回归的代理负载（这可能会显示出误导性的概率特征）。最后，该模型用于根据运行统计数据估计运行中的风力涡轮机的塔架负载。