  Moving clouds affect the global solar irradiance that reaches the surface of
the Earth. As a consequence, the amount of resources available to meet the
energy demand in a smart grid powered using Photovoltaic (PV) systems depends
on the shadows projected by passing clouds. This research introduces an
algorithm for tracking clouds to predict Sun occlusion. Using thermal images of
clouds, the algorithm is capable of estimating multiple wind velocity fields
with different altitudes, velocity magnitudes and directions.
