Wind Flow Estimation in Thermal Sky Images for Sun Occlusion Prediction

TL;DR

This paper presents an algorithm that uses thermal sky images to track cloud movement and predict sun occlusion, aiding in solar energy resource management.

Contribution

It introduces a novel method for estimating multi-altitude wind velocity fields from thermal cloud images for sun occlusion prediction.

Findings

Successfully estimates wind velocities at different altitudes.

Accurately predicts sun occlusion due to cloud movement.

Enhances solar resource forecasting in smart grids.

Abstract

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.