Development of a multi-axis closed-loop solar radiation tracking system by the fuzzy logic

This thesis research aims to optimize the utilization of solar radiation by employing solar cells and addressing any potential barriers that may impede the efficiency of power generation. Hence, it was imperative to consider the planning, design, and implementation of an intelligent system capable of fulfilling this requirement. Consequently, we opted for an external structure that aligns with the concept of a smart tracking system, eliminating the need to determine the azimuth angle. Instead, the focus is on ensuring the system remains perpendicular to the source of solar radiation. The external structure was designed with two interconnected components to enable a 360° horizontal movement and a 180° vertical movement, ensuring optimal tracking and precise outcomes. This design incorporates two motors (DC and servo) and utilizes eight LDR sensors to effectively overcome obstacles, including partial shading, and maintain accurate tracking even if one of the sensors malfunctions. These sensors operate based on a unique mathematical and programming algorithm. An optimal control device for managing these motors and sensors is the Arduino, which utilizes the fuzzy logic algorithm and is known for its precision in handling relative values and components. The fuzzy logic controller will be responsible for controlling and directing all elements of the system and determining the time to move the panels so that they face direct sunlight. The fuzzy logic algorithm, consisting of 524 lines of programming, incorporates comprehensive instructions, inputs, and control mechanisms to achieve precise and optimal outcomes while effectively addressing challenges such as partial shade and the malfunction of an LDR sensor. Data was collected by using a recording unit (SD card) and storing it on a memory card, which may be accessed at any time, to ii verify the system's efficiency and identify weak points. The practical results showed that the use of 8 LDR sensors enabled us to overcome all the obstacles facing the system, in addition, to accurately aligning the solar radiation source and choosing the best angles to reach the desired target. Moreover, the utilization of both DC and servo motors played a crucial role in surmounting the primary obstacles encountered in this study. Specifically, it facilitated the identification of the optimal angle that is perpendicular to the radiation source, eliminating the necessity for the azimuth angle and the most favorable starting angle. This system can be categorized as a fusion of the advantages of conventional tracking systems and the integration of artificial intelligence into the tracking process in this research.