Internet of Things Based Solar Panel Cooling Effectiveness: Automatic and Manual Pump Comparison
Abstract
The importance of photovoltaic (PV) systems is emphasized by the increasing demand for renewable energy. However, the increase in temperature on the surface of PV panels greatly affects the performance of PV systems. The impact of IoT-based cooling systems on PV systems is the focus of this study. We applied a comparative experimental design with three configurations: baseline (no cooling), manual (pump activated every 60 minutes for 5 minutes), and automatic (pump activated when the panel temperature 40°C or higher for 5 minutes). The PV panels were equipped with copper pipe cooling, an ESP32 microcontroller, RS485 Modbus communication, and IoT monitoring using Blynk, and were tested outdoors from 08:00 to 16:00. Data collected from the PV (voltage, current, Pmax) was recorded every 5 minutes and analyzed. Our research results show that automatic cooling produces the highest temperature reduction compared to manual cooling. Automatic cooling increases daily PV production by 69.19%, which is equivalent to a 36.05% increase in clean energy. However, the net efficiency of manual cooling is much lower due to fixed-interval pump operation. Therefore, under clear sky conditions, the results show that an automatic cooling system with IoT enables better PV module performance by providing better thermal stabilization. However, considering that this study was only conducted for one day, further research under various weather conditions is needed to prove long-term reliability and consistency.
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DOI: https://doi.org/10.33387/protk.v13i1.10741
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