Exploring the Interdependence of Vertical Extrapolation Uncertainties in Repowering Wind Farms

Abstract

Abstract Assessing a wind farm’s annual energy production (AEP) involves modelling the wind resource and the wind-to-power conversion at the site. The greenfield pre-construction phase generally comprises the installation of wind measurement devices. For repowering projects, the wind data from the pre-construction phase of the existing farm can be used as wind input to assess the energy yield of the repowered wind farm. Indeed, one study demonstrates that when the modelling error correlations are known, the AEP prediction uncertainty of the repowered farm can be reduced by combining the energy production records of the existing farm with the AEP assessment for both farms. Previous studies have successfully identified the correlation structure for certain errors, especially for horizontal flow modelling, but not for vertical flow modelling. However, vertical extrapolation is essential, as the wind measurement heights are generally lower than the hub height on the repowered farm. This paper bridges this research gap and demonstrates that the correlation structure of errors in vertical profile modelling is Gaussian, with parameters dependent on shear values and heights. The distribution is validated against site data from simple to moderately complex sites in France.