Fuzzy Logic Control System for Optimizing Dual-Axis Solar Panel Tracking

Abstract

The utilization of solar energy through solar panels has gained considerable attention in renewable energy applications. However, the effectiveness of energy conversion is hindered by the misalignment of solar panels with the incident sunlight. To address this issue, a dual-axis solar tracker system is proposed to automatically adjust the orientation of solar panels, enhancing energy generation efficiency. This research introduces a novel approach using a fuzzy logic control system to regulate the movement of stepper motors responsible for adjusting the solar panel positions. The system relies on input data from Light-Dependent Resistor (LDR) sensors to detect the sunlight’s position. Additionally, voltage, current, and angle sensors are integrated to accurately determine the solar panels angular position. The fuzzy logic control system employs the Mamdani method with Mean of Maximum (MOM) defuzzification. A comprehensive analysis of the systems performance was conducted, demonstrating that the manual calculations yielded 0.87 and 0.59 micro steps, while the Fuzzy Inference System (FIS) produced 0.35 and 0.26 micro steps. These results were verified through the serial monitor in the Arduino Integrated Development Environment (IDE). This research focuses on the development of a microcontroller-based two-axis solar panel control system using fuzzy logic. The system’s primary objective is to maximize solar energy utilization by ensuring that solar panels consistently align with the direction of sunlight, both vertically and horizontally. The proposed system offers an effective means of enhancing the efficiency of solar panel energy generation by continuously optimizing their alignment with the incident sunlight.