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Integration of Automatic Cleaning and Adaptive Cooling for Soiling Mitigation in Solar Panel Maintenance Pelangi Firmansyah; Agung Trihasto; Dwi Novianto
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 2 (2026): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i2.4187

Abstract

The accumulation of soiling on the surface of the solar panel module inhibits the process of absorbing sunlight and causes uneven heat distribution, thus impacting the decline in solar panel performance. This study introduces a new solar panel maintenance mechanism through the integration of cleaning and cooling with voltage drop detection, weather condition, temperature monitoring and centralized control features based on the ESP32 microcontroller. The primary contribution is the system-level integration of previously separate maintenance mechanism functions into a conditionally integrated control architecture. The implementation of the cleaning mechanism is carried out based on the detection of a voltage drop below the baseline persistently for 30 minutes as a temporal filter to prevent momentary maintenance. Meanwhile, the adaptive cooling mechanism through the detection of the DS18B20 temperature sensor controls the activation of the water pump motor when the temperature is > 40 °C and is inactive when the temperature is ≤ 25 °C. Both maintenance methods are complemented by LDR and rain sensors for adaptive operation to the environment. At prototype scale, the maintained panel recorded an average voltage of 13.22 V and average temperature of 34.06 °C, compared to 12.71 V and 40.59 °C for the unmaintained panel. This represents a 4.013% increase in output voltage and a 16.09% decrease in temperature, both statistically significant (paired t-test, p<0.001). These test findings are based on voltage and temperature parameters. Power output and electrical energy were not directly measured, so the results represent prototype-level operational feasibility, not overall efficiency improvements.