A study of a high-precision deep-sea wind resource modelling method based on Observation Nudging
In order to improve the accuracy of wind resource assessment in the deep and distant sea region,the Observation Nudging method is applied to the mesoscale meteorological model WRF,and the wind speed simulation is improved by assimilating multiple offshore LiDAR data.By comparing the unassimilated CTRL model,the commonly used Grid Nudging method(GN model)and the Observation Nudging method(ON model),the advantages of the ON model in wind speed simulation,wind profile accuracy and wind energy density estimation are systematically evaluated.It is shown that the ON model significantly improves the wind speed simulation correlation by 5%and reduces the root mean square error and mean absolute error.In addition,the ON model has higher simulation accuracy of wind contours in the wind turbine critical operating height(50～150m)region and reduces the error by 3%compared to the CTRL model in wind energy density estimation.Although Observation Nudging can effectively improve the local simulation accuracy,the ability to physically constrain the offshore surface wind contours needs to be improved.Secondly,the GN model is deficient in small-scale feature portrayal,and thus is not suitable for the refined analysis of wind resources.In conclusion,the ON model has a strong potential for engineering application in the deep and distant sea region where observations are lacking,and can provide strong support for the rational planning of wind farms.
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