Fusion of Weather Radar and Passive Satellite Data over Wind Parks

In recent years, as wind energy has gained interest as a sustainable source of electricity, the proliferation of large Wind Parks (WP) with a large number of Wind Turbines (WT) has become common. However, this development brings with it challenges related to weather radar systems. WTs, characterised by their height and Radar Cross Section (RCS), significantly degrade radar performance, causing erroneous data known as Wind Turbine Clutter (WTC) or Wind Turbine Interference (WTI). This interference, combined with Multipath Interference (MPI) and shadowing effects, extends beyond the main beam of the radar. To address this issue, recent advancements in passive satellite remote sensing technology, particularly Sentinel-2 with its 10-meter resolution, offer a promising solution. This study proposes a novel approach to identify and classify WP areas by fusing polarimetric Doppler weather radar and passive satellite data. The process entails calculating reflectivity (Z) from raw IQ radar data, analyzing reflectivity values within WP regions, and examining reflectance values from satellite data. These findings are used to establish an index (Wind Turbine Index (WTI)) capable of detecting the presence of WT. Finally, a data fusion method combines the datasets, enhancing the accuracy and reliability of WP identification and classification techniques.