Abstract:
However, conventional PV monitoring and maintenance methods rely heavily
on manual inspection, leading to inefficiencies, delayed fault detection, and reduced
system performance. To address these challenges, this study presents an intelligent
monitoring and self-maintenance system designed to enhance the performance and
reliability of solar PV installations. The proposed approach is based on sensor-driven data
acquisition, where multiple sensors, including a Light-Dependent Resistor (LDR),
temperature sensor, light intensity sensor, rain sensor, and DHT11 humidity sensor, are
integrated to continuously collect environmental and operational data such as panel
temperature, ambient temperature, humidity, light intensity, rainfall duration, and dust
accumulation. Data communication and control are achieved using the SIM800L GSM
module and ESP32 Wi-Fi microcontroller, enabling real-time monitoring, automated
alerts, and IoT-based management through Firebase, Google Sheets, and a custom Flutter
mobile application. The 20x4 LCD display and ESP32 web server provide a user-friendly
local interface, while the Flutter app offers remote access to data visualization and control.
The system incorporates automatic cooling and cleaning mechanisms that activate based
on sensor readings, reducing manual intervention and ensuring optimal power generation
efficiency. Field testing conducted on fifteen solar PV systems across Sri Lanka
demonstrated measurable improvements in energy output and a significant reduction in
manual maintenance requirements. Furthermore, an AI-based analytical framework was
introduced to evaluate performance trends and generate predictive maintenance
recommendations using data from cloud storage platforms, supporting proactive
maintenance decisions. This intelligent and cost-effective self-maintenance system
minimizes human involvement, lowers operational costs, and enhances the lifespan and
efficiency of solar panels, thereby improving the overall sustainability of solar PV systems.
The proposed approach provides a sustainable and scalable solution for smart solar
management, making it highly suitable for developing countries like Sri Lanka, where
maximizing renewable energy utilization and reducing maintenance costs are critical
objectives.
