Soft computing and IoT based solar tracker

• Published in: International Journal of Power Electronics and Drive Systems Vol. 12; no. 3; p. 1880
• Main Authors: Kumar, Kanhaiya, Varshney, Lokesh, Ambikapathy, A., Mittal, Vrinda, Prakash, Sachin, Chandra, Prashant, Khan, Namya
• Format: Journal Article
• Language: English
• Published: Yogyakarta IAES Institute of Advanced Engineering and Science 01.09.2021
• Subjects: Algorithms; Artificial neural networks; Azimuth; Centroids; Decision making; Error reduction; Global positioning systems; GPS; Image processing; Power gain; Soft computing; Solar energy; Sun; Tracking errors; Tracking systems; Weather
• ISSN: 2088-8694; 2722-256X; 2088-8694
• DOI: 10.11591/ijpeds.v12.i3.pp1880-1889

The significance of the solar energy is to intensify the effectiveness of the Solar Panel with the use of a primordial solar tracking system. Here we propounded a solar positioning system with the use of the global positioning system (GPS) , artificial neural network (ANN) and image processing (IP) . The azimuth angle of the sun is evaluated using GPS which provide latitude, date, longitude and time. The image processing used to find sun image through which centroid of sun is calculated and finally by comparing the centroid of sun with GPS quadrate to achieve optimum tracking point. Weather conditions and situation observed through AI decision making with the help of IP algorithms. The presented advance adaptation is analyzed and established via experimental effects which might be made available on the memory of the cloud carrier for systematization. The proposed system improve power gain by 59.21% and 10.32% compare to stable system (SS) and two-axis solar following system (TASF) respectively. The reduced tracking error of IoT based Two-axis solar following system (IoT-TASF) reduces their azimuth angle error by 0.20 degree.