Solar Detection and Tracking System Using Artificial Intelligence: An ESP32-Based Automated Solar Panel Orientation System for Enhanced Energy Harvesting

Abstract

The growing need for clean and sustainable energy has accelerated progress in solar power technologies. This project presents the development of an
intelligent solar detection and tracking system designed to enhance energy harvesting efficiency. Fixed solar panels suffer from reduced performance because they
cannot continuously follow the sun’s movement. To address this issue, the proposed system combines automation with real-time monitoring using advanced
embedded solutions. At the core of the system is an ESP32 microcontroller, selected for its high processing capability, energy efficiency, and integrated wireless
features. A photovoltaic panel converts sunlight into electrical energy based on the photovoltaic effect. The output voltage is continuously measured through a
voltage sensor module, which sends feedback to the controller for analysis and system optimization. A servo motor is used to adjust the panel’s position dynamically,
controlled by signals from the ESP32 to enable accurate angular movement so that ensuring the panel remains aligned with the sun throughout the day. This
tracking system operates on a closed-loop mechanism, where sensor feedback is used to make real-time corrections. Additionally, a 16x2 LCD display provides a
simple interface to show key data such as voltage levels and system status. This improves usability, especially in remote setups. Overall, the system offers an
affordable and efficient solution for enhancing solar energy output and supports future upgrades like IoT-based monitoring and remote control.