The Solar Forecasting and Artificial Intelligence course offers an in-depth exploration of the latest advancements and methodologies in solar energy forecasting. This course is essential for those looking to understand the complexities of integrating solar power into electricity grids and managing renewable energy resources efficiently. Key topics include:

• Overview of solar forecasting techniques, from traditional methods to cutting-edge AI applications.
• Detailed examination of time horizons for solar forecasting, ranging from ultrashort (1 minute) to extended periods (up to 24 hours).
• In-depth study of AI techniques such as Neural Networks, supervised learning, and regression for improving solar forecasting accuracy.
• Integration of satellite imagery, weather predictions, and historical data to enhance forecasting precision.
• Evaluation of forecasting models using standardized datasets and error metrics to ensure accurate and reliable predictions.

This course aims to equip participants with the knowledge and tools needed to develop and implement effective solar forecasting models, thereby supporting the advancement of renewable energy integration and smart grid technologies.