ABSTRACT

As a vital key part of the modern offshore wind energy industry, floating offshore wind turbines (FOWT) are built to generate green renewable energy. Robust prediction of extreme loads during FOWT operation is an important safety concern. In this paper, the FAST code has been used to analyse offshore wind turbine internal bending moments due to environmental hydrodynamic wave loads, acting on a specific FOWT under actual local sea conditions. This paper advocates a computationally efficient Monte Carlo based methodology for estimating extreme load or response statistics, based on simulations or measurements. For this purpose, the averaged conditional exceedance rate (ACER) method is proposed. The described approach may be well used at the design stage, while defining optimal wind turbine parameters that would minimise potential FOWT mechanical damage due to excessive environmental loadings.

摘要

作为现代海上风能产业至关重要的关键部分，浮动式海上风轮机（FOWT）可以产生绿色可再生能源。FOWT操作期间对极端载荷的可靠预测是重要的安全考虑。在本文中，FAST代码已被用于分析在实际局部海况下作用于特定FOWT的，由于环境水动力波载荷引起的海上风机内部弯矩。本文提倡一种基于计算的有效蒙特卡洛方法，用于基于模拟或测量来估计极限载荷或响应统计量。为此，提出了平均条件超出率（ACER）方法。所描述的方法可以在设计阶段很好地使用，