Optimization of Internet of Things-Based Solar Panel Cooling Using Splash Fill

Solar panel performance is strongly affected by module surface temperature because a large portion of incident solar radiation is converted into heat rather than electrical energy. Although water-based photovoltaic cooling has been widely investigated, many existing systems still rely on open-loop or manually activated cooling and provide limited integration between thermal recovery, adaptive control, and real-time monitoring. This study proposes an Internet of Things-based automatic solar panel cooling system that combines closed-loop water circulation, splash fill-assisted water temperature reduction, MQTT communication, and Home Assistant monitoring for tropical operating conditions. The system was evaluated using two 100 Wp monocrystalline photovoltaic panels under identical environmental conditions, where one panel was equipped with the proposed cooling system and the other was operated without cooling. Key parameters, including panel temperature, water temperature, voltage, current, output power, irradiance, daily energy, and efficiency, were measured at 10-minute intervals over two experimental days. The results show that the proposed system reduced panel temperature by 19.22-20.10°C, increased output power by 26.35-28.89 W, and improved average efficiency by 3.42-4.18%. Net daily energy increased by 154.88-167.04 Wh after considering pump consumption. These findings demonstrate that integrating splash fill cooling with Internet of Things-based adaptive monitoring provides a practical and scientifically relevant approach for improving photovoltaic performance in tropical environments.