Effective Analysis Utilizing Artificial Intelligence to Characterize the Efficient Dynamic Performance of the Tracking System

Mohammad Reza Hedayati

A chapter in Solar Radiation - Enabling Technologies, Recent Innovations, and Advancements for Energy Transition from IntechOpen

Abstract: In recent years, artificial intelligence has been widely used in renewable energy. Several solar panels have been installed in the direction of maximum solar radiation for various applications around the world. But in the case of moving platforms, for instance, an application like ships, military and solar vehicles, satellites, etc., the maximum solar radiation at all the positions and displacements is not obtained. In addition, the sun is still in motion depending on the variation of the calendar. Consequently, there are problems with the energy collected by solar panels and their production which differs considerably at different times, positions, and bearings. This research work aims to model the dynamic behavior of a two degree of freedom (2-DOF) mechanism, which can be used as a dual axis solar moving base. As a verification, the equation of motion examines several important issues in implementing an expert system for the robust controller design of the proposed intelligent mechanism. It is evident that the movement of the panels toward the direction of solar motion uses the maximum radiation at all times and, as a result, the higher efficiency of the solar panels is achieved. The proposed objective of the current research is to devise dynamic modeling of artificial intelligence two-axis of freedom solar moving base mechanism in conjunction with the tracker system mounted on the specifically designed and fabricated moving base platform.

Keywords: expert systems; artificial neural networks; moving base solar panel; tracking the sun; dynamic equation; stepper motor (search for similar items in EconPapers)
JEL-codes: Q20 Q40 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:283127

DOI: 10.5772/intechopen.113318

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