ABSTRACT
This paper presents an integrated solar tracking and weather monitoring system designed to accurately predict daily battery charge levels in off-grid renewable energy systems. The system combines advanced solar panel orientation control mechanisms with real-time weather data acquisition to optimize energy capture and estimate daily battery charging. Key components include a network of weather sensors strategically deployed across the installation site, a sophisticated control algorithm for dynamically adjusting solar panel angles, and a predictive model for estimating daily battery voltage based on historical charging patterns and weather forecasts. By continuously monitoring weather conditions and adjusting solar panel orientation accordingly, the system maximizes energy harvest while minimizing performance degradation due to environmental factors such as cloud cover and shading. The predictive model leverages historical data and current weather conditions to estimate daily battery charge levels, enabling proactive management of energy storage resources. This paper discusses the design principles, implementation details, and performance evaluation of the proposed system, demonstrating its effectiveness in accurately predicting daily battery charge levels and optimizing energy utilization in off-grid solar installations. Overall, our research contributes to the advancement of renewable energy technologies by offering a comprehensive solution for solar tracking, weather monitoring, and predictive battery charging, thereby enhancing the efficiency and reliability of off-grid power systems
