Solar Power Heliostat Control Using Image Processing Technology and Artificial Neural Networks

Abstract

Sun tracking is very important to improve the efficiency of the concentrated solar panels (CSP) output power. Hence, high-accuracy sun tracking is needed. In this paper, we propose an innovative approach for the heliostat optimal orientation, overall, the solar tower using a hybrid image processing technique (IPT) and artificial neural networks (ANN). The main objective is to minimize the tracking error and increase the solar power tower plant performance. Image processing is used to locate the Sun position and help the heliostat to achieve its optimal direction. Moreover, using MATLAB/Simulink, the neural network approach is applied in order to simulate the IPT and generalize the heliostat tracking positions.