Implication of Wind Speed Data variant for Wind Power Simulation

Abstract

With the need for a shift from the use of fossil fuels to renewable energy, wind technology is one of the promising, clean, renewable, and cost-effective energy sources. For sub-Saharan regions where 600 million people still lack electricity, wind energy appears to be an opportunity to assure energy security especially, in southern Africa, where abundant wind energy potential exists. Basically, wind technology consists of the use of a wind turbine, which extracts the kinetic energy of moving air through a rotor. This implies the knowledge of wind speed at the rotor level, known as Hub height (around 100m), but wind measurements are typically done at ground level (around 10m). Therefore, it is crucial to find alternative ways for wind data assessment at the rotor level. Numerical atmospheric datasets and height scaling methods seem to be solutions. This study evaluates the impact of using different height scaling methods with and without numerical atmospheric datasets, the high-resolution ICON in Limited Area Mode (ICON-LAM), the ERA5 reanalysis, and the statistical downscaling variant of ERA5 (ERA5_GWA) on the multiple heights wind speed calculation and subsequently, on the wind power estimation over southern Africa from 2017 to 2019. The results show that ERA5_GWA outperforms ERA5 and ICON-LAM for the 10m wind speed simulation. ERA5 introduced the highest bias with an underestimation of the wind power at 20m, 40m and 60m, regardless of the used wind speed height scaling method. Most of the scaling methods performed similarly except for the Justus_Law, which introduced an overestimation of the wind power, and the Linear interpolation, which introduced an underestimation. The accuracy of scaling methods using vertical levels of wind speed from numerical atmospheric datasets is highly dependent on the choices of the nearest levels close to the target height wind speed. This study reveals that the choice of datasets has a greater impact than wind speed height scaling on wind energy assessment.