The use of state-of-the-art WRF-ARW models that have proven track of results verified by the worldwide scientific community and the combination of A.I. neural-networks produce unprecedented levels of accuracy in prediction of mesoscale and microscale weather.
Meteorologica owns gliders equipped with scientific instruments and gear that fly near the wind farms and collect data regarding the state of the atmosphere. With gliders flights we are able to capture and monitor the exact movements of air currents close to the wind farms. The collected data are fed into our models in an attempt to fine-tune results to the specific features of each site
The output of WRF model, enriched with atmoshperic measurements from glider flights, is ingested by a machine learning model (neural network) that learns microscale weather patterns specific to each wind farm site.
”Local wind due to the convergence line north (left) of the wind turbines. Perfectly forecasted increase of the power output regardless of the synoptic North wind. “
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