This dissertation describes the procedure of estimating and predicting the shading of the Sun by analyzing the sequence of images of the sky, which is based on the analysis of images recorded by a wide-angle camera. The camera is installed on the ground so that it can monitor the movement of the Sun from sunrise to sunset. The motivation for this research is the design of a microgrid with solar energy and different types of energy storage. The described methodology uses images of the sky taken every five seconds to estimate the future movement of clouds and predict the moment of shading of the Sun and the duration of the shadow of clouds in front of the Sun. Sky images taken with a wide-angle camera were first processed to eliminate the distortion effect of the wide-angle camera lens using the built-in module from the MATLAB software package, which is called the Omni Directional Camera Calibration Toolbox. Given the dynamic nature of the shape change, the clouds were estimated to be rectangular in shape to make the algorithm itself as simple and fast as possible. The processing of the recorded images predicts the level of solar radiation based on the predicted shading, i.e., the predicted level of the visible part of the Sun and the prediction of the mean value of direct solar radiation by the meteorological service. The obtained results of solar radiation prediction are presented in the form of a curve of the amount of direct solar radiation in the next period, which is then used in the process of optimizing energy flows in the microgrid with photovoltaic systems and storage systems based on short-term solar radiation prediction and energy storage system characteristics. The analyzed microgrid also consists of several types of energy storage with different efficiency, capacity, and response time.