Monitoring the performance of a solar farm is critical for optimizing energy production and reducing costs. Traditional methods of solar farm performance monitoring, such as manual review of solar panel output or rule-based systems, can be time-consuming and may not provide real-time insights into the performance of each solar panel.

AI and machine learning (ML) can play a key role in solar farm performance monitoring for solar energy companies. By training an ML model on data from various sources, such as solar panel output, weather conditions, and energy demand, our solution can provide real-time insights into the performance of each solar panel and enable solar energy companies to make informed decisions about energy production. In addition, ML models can be used to adjust solar panel output in real-time based on weather conditions and energy demand, ensuring that solar energy companies are always optimizing their energy production.