Renewable Generation

Renewable energy generation, characterized by its intermittent and unpredictable nature, presents significant challenges for grid stability and efficient energy management. Current research focuses on improving forecasting accuracy using advanced machine learning models, such as deep neural networks, transformer architectures, and hybrid models combining machine learning with physical models, to predict solar and wind power output at various time scales (from nowcasting to long-term scenarios). These advancements are crucial for optimizing grid operations, integrating energy storage effectively, and reducing reliance on fossil fuels, ultimately contributing to a more sustainable and reliable energy system.