Improved Detection of Sunlight Source Determination Using Raspberry Pi 4-Based Fuzzy Logic on Solar Tracking System

Abstract

Solar panels are the main component of a solar power generation system, converting sunlight into electrical energy. This study develops a solar cell monitoring method to collect output data in a specific text format and uses solar cell modules to maximize the efficiency of solar energy absorption that moves from east to west throughout the day. The solar panel tracking system uses the Raspberry Pi 4 as the central controller to follow the sun's movement. It is supported by LDR sensors to detect light intensity and move the panel according to the direction of light. In addition, the BH1750 and BME280 sensors are used to measure additional factors, such as temperature, wind pressure, humidity, light intensity, and light angle, that also affect the panels' power production. The collected data is processed using fuzzy logic to convert the exact values from the sensor into fuzzy data, allowing for more precise control in panel position optimization. The results showed that the system can improve the efficiency of solar energy absorption, with an optimal intensity level of 53,999.99 lux in very bright conditions and a fuzzy-lux difference of 1.1%, which is lower than previous research, indicating that the system is more efficient and supports accurate real-time monitoring.