Development of an IoT Based Photovoltaic Monitoring System Using Hybrid Modeling

This abstract introduces a comprehensive Photovoltaic Monitoring System designed to enhance the efficiency and reliability of solar energy generation. The system leverages Raspberry Pi as its central controller and integrates various sensors to monitor critical parameters, including voltage, temperature, and light intensity. The system's functionality begins with the interfacing of sensors with the Raspberry Pi. Voltage sensors continuously monitor the electrical output of the photovoltaic panels, allowing for precise tracking of the power generated. Temperature sensors provide information about the operating temperature of the panels, a critical factor affecting their efficiency. Light Dependent Resistor (LDR) sensors measure the light intensity, enabling the system to assess the available solar irradiance.

To optimize power generation and ensure the panels operate within their ideal conditions, the collected sensor data is uploaded to a linear regression model. This model analyses historical and present data to predict the expected power output. The model's predictions are then compared to the actual power generated by the photovoltaic panels. To further enhance system reliability, the monitoring system is equipped to detect anomalies or discrepancies between the predicted and actual power outputs. When such anomalies are identified, an SMS alert is generated using a GSM module. This alert system provides immediate notification to relevant personnel, enabling them to take corrective action promptly, such as investigating and rectifying issues affecting the solar panel performance.

Keywords: Photovoltaic, Solar Energy, Power Generation. Linear Regression, GSM module