MIPV-NWP-PINNs V1.0: development of a multi-scale photovoltaic power forecasting framework integrating numerical weather prediction with physics-informed neural networks

Zhang, Fei; Li, Xingcai; Wang, Zifa; Wen, Yunyun; Zhou, Xuyang; Wu, Zichen; Wang, Zhuoran; Chen, Huansheng; Wang, Zhe; Chen, Xueshun

doi:10.5194/gmd-19-4999-2026

Articles | Volume 19, issue 11

https://doi.org/10.5194/gmd-19-4999-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-4999-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 11

Model description paper

|

12 Jun 2026

Model description paper |

| 12 Jun 2026

MIPV-NWP-PINNs V1.0: development of a multi-scale photovoltaic power forecasting framework integrating numerical weather prediction with physics-informed neural networks

Fei Zhang, Xingcai Li, Zifa Wang, Yunyun Wen, Xuyang Zhou, Zichen Wu, Zhuoran Wang, Huansheng Chen, Zhe Wang, and Xueshun Chen

Supplement

https://doi.org/10.5194/gmd-19-4999-2026-supplement

Data sets

MIPV-NWP-PINN V1.0: Development of a Multi-scale Photovoltaic Power Forecasting Framework Integrating Numerical Weather Prediction with Physics-Informed Neural Networks Fei Zhang et al. https://doi.org/10.5281/zenodo.19551487

Model code and software

MIPV-NWP-PINN V1.0: Development of a Multi-scale Photovoltaic Power Forecasting Framework Integrating Numerical Weather Prediction with Physics-Informed Neural Networks Fei Zhang et al. https://doi.org/10.5281/zenodo.19551487

Short summary

Solar power generation depends on weather conditions and photovoltaic modules, making accurate forecasts crucial for reliable grid operation. We combined weather prediction and artificial intelligence to improve the solar power prediction at different time scales for a plant. By improving sunlight predictions and incorporating physical constraints into the model, our approach reduced errors significantly. This can help integrate clean energy into power grids safely and efficiently.