Prediction of short-term distributions of load extremes of offshore wind turbines

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• 作者：Ying-guang Wang 王迎光
• 关键词：extreme responses ; monopile ; supported ; offshore wind turbine ; peak over threshold method ; optimal threshold level ; variance ; to ; mean ratio ; generalized Pareto distribution ; maximum spacing estimation
• 刊名：China Ocean Engineering
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：30
• 期：6
• 页码：851-866
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Offshore Engineering; Oceanography; Coastal Sciences; Fluid- and Aerodynamics; Marine & Freshwater Sciences; Numerical and Computational Physics, Simulation;
• 出版者：Chinese Ocean Engineering Society
• ISSN：2191-8945
• 卷排序：30

文摘

This paper proposes a new methodology to select an optimal threshold level to be used in the peak over threshold (POT) method for the prediction of short-term distributions of load extremes of offshore wind turbines. Such an optimal threshold level is found based on the estimation of the variance-to-mean ratio for the occurrence of peak values, which characterizes the Poisson assumption. A generalized Pareto distribution is then fitted to the extracted peaks over the optimal threshold level and the distribution parameters are estimated by the method of the maximum spacing estimation. This methodology is applied to estimate the short-term distributions of load extremes of the blade bending moment and the tower base bending moment at the mudline of a monopile-supported 5MW offshore wind turbine as an example. The accuracy of the POT method using the optimal threshold level is shown to be better, in terms of the distribution fitting, than that of the POT methods using empirical threshold levels. The comparisons among the short-term extreme response values predicted by using the POT method with the optimal threshold levels and with the empirical threshold levels and by using direct simulation results further substantiate the validity of the proposed new methodology.