Prediction of Extreme Wind Speed for Offshore Wind Farms Considering Parametrization of Surface Roughness

Large-scale offshore wind farms (OWF) are under construction along the southeastern coast of China, an area with a high typhoon incidence. Measured data and simulation model used to improve reliability extreme speed (EWS) forecasts for OWF affected by typhoons in this paper. Firstly, 70-year historical record database is statistically analyzed fit parameters probability distribution functions, which sample key when employing Monte Carlo Simulation (MCS). The sampled put into Yan Meng (YM) field generate massive virtual MCS. Secondly, carried out, change roughness caused wind-wave coupling studied. A simplified calculation method realizing phenomenon applied exchanging length parametric wave model. Finally, value theory adopted analyze simulated data, results verified using measured relevant standards codes. EWS 50-year recurrence six representative predicted as application examples. show that generally stronger than onshore; reason sea surface will not keep growing accordingly increases. traditional prediction does consider phenomenon, causing it overestimate roughness, result, underestimate typhoons. This paper’s methods make more precise, suggest planer should choose turbine prone areas.