Development of Weather Monitoring System for Photovoltaic System Performance Prediction and Evaluation

Abstract

With the rising prominence of solar energy as a renewable power source, there is a critical need for accurate forecasting to enable its efficient integration into power grids. This work addresses the challenge of unpredictable climatic conditions that affect the efficiency of solar energy utilization. We developed an IoT-based weather monitoring system designed specifically for solar prediction, leveraging an integrated sensor suite to accurately measure temperature, humidity, atmospheric pressure, and precipitation. Utilizing Google Sheets for real-time monitoring, the system allows for autonomous data acquisition and offers the unique capability of online data logging, ensuring rapid decision-making capabilities in variable weather conditions. To validate the reliability and accuracy of the system, we compared our recorded data with established PVSyst software models. Results indicate a significant alignment between the real-time data from the proposed system and the PVSyst models, confirming the system's potential in enhancing the predictability and utilization of solar energy. This work sets a foundation for advanced weather monitoring, ensuring the predictive models are representative of real-world conditions, ultimately advancing the solar industry's efficacy and reliability.