Integrating Weather Foundation Model and Satellite to Enable Fine-Grained Solar Irradiance Forecasting
Accurate day-ahead solar irradiance forecasting is critical for the effective integration of solar energy into the power grid. Despite its importance, achieving precision in forecasting remains a significant challenge, primarily due to complex cloud dynamics and the pronounced diurnal cycle. Traditional forecasting methods often falter in providing the necessary fine-scale resolution or degrade in performance over longer lead times. In addressing these issues, researchers have proposed a novel solution known as Baguan-solar.
Overview of Baguan-solar
Baguan-solar is a two-stage multimodal framework designed to enhance solar irradiance forecasting accuracy. This innovative system merges predictions from Baguan, a global weather foundation model, with high-resolution geostationary satellite imagery. The primary goal is to produce 24-hour irradiance forecasts with a resolution at the kilometer scale.
Key Features of Baguan-solar
- Decoupled Two-Stage Design: The framework first forecasts continuous day-night intermediates such as cloud cover before inferring the actual solar irradiance. This stepwise approach allows for more precise predictions.
- Modality Fusion: Baguan-solar uniquely combines fine-scale cloud structures derived from satellite imagery with large-scale constraints from Baguan forecasts, ensuring a comprehensive understanding of atmospheric conditions.
- Enhanced Performance: Evaluated over East Asia using CLDAS as ground truth, Baguan-solar has demonstrated superior performance compared to existing strong baselines, including ECMWF IFS, vanilla Baguan, and SolarSeer. The framework has achieved a remarkable 16.08% reduction in RMSE, effectively resolving cloud-induced transients.
Operational Deployment and Future Implications
Since July 2025, Baguan-solar has been operationally deployed to support solar power forecasting in an eastern province of China. This implementation marks a significant step towards improving the reliability of solar energy forecasts, which are essential for optimizing energy distribution and enhancing grid stability. The successful integration of Baguan-solar into real-world applications illustrates its potential to transform solar energy forecasting on a larger scale.
Access to Research and Code
For those interested in exploring the underlying technology and methodologies of Baguan-solar, the research code is publicly accessible. Researchers and practitioners can find the code at https://github.com/DAMO-DI-ML/Baguan-solar.git, encouraging further development and potential enhancements in the field of solar irradiance forecasting.
Conclusion
The integration of Baguan and satellite imagery through the Baguan-solar framework represents a significant advancement in solar irradiance forecasting. By addressing the challenges posed by cloud dynamics and diurnal cycles, this innovative approach not only improves forecasting accuracy but also supports the broader goal of sustainable energy integration into power grids. As solar energy continues to play a crucial role in global energy production, technologies like Baguan-solar will be pivotal in harnessing this renewable resource effectively.
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