Design and Implementation of IoT-Based Single Axis Solar Tracker with Auto-Manual Mode - Throvinus Purba; Dewi Sholeha; Winner Parluhutan Nainggolan (Lembaga Riset Ilmiah, 2026)
The utilization of solar energy is often suboptimal in static installations, while conventional light-sensor-based trackers suffer from the hunting effect, random actuator movements that waste mechanical power during cloudy weather. A critical research gap exists: no prior micro-scale solar tracker has simultaneously eliminated Light Dependent Resistor (LDR) dependency and provided bidirectional IoT remote control to counteract weather-induced actuator instability. This research addresses that gap by designing and implementing an IoT-based Single Axis Solar Tracker with a novel Auto-Manual Mode that completely removes LDR reliance, enabling users to remotely lock the panel angle via the Blynk application, rendering the system inherently immune to the hunting effect under any weather anomaly. The system employs an ESP32 microcontroller, a DS3230 servo motor as the actuator, an INA219 digital sensor for electrical data acquisition, and a 10 WP solar panel with a 12V DC lamp load. Real-time monitoring of voltage, current, and power output is performed through the Blynk mobile interface. System testing was conducted in an open outdoor area over ten operational hours (07:00–17:00 WIB) with angular increments of 9° per hour, tracking from 45° East to 135° West. The actuator angle deviation, validated using a digital inclinometer, averaged only 0.27°. The system recorded a peak power output of 4,217.97 mW (4.21 Watts) at 99° at 13:00 WIB. Ultimately, the Auto-Manual mode effectively locked the panel position along the sun’s time trajectory despite sudden irradiance fluctuations, completely eliminating parasitic mechanical power consumption and optimizing daily solar energy absorption throughout the operational period.