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A deep learning algorithm to estimate hourly global solar radiation from geostationary satellite data

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  1. Liu, Yujun & Yao, Ling & Jiang, Hou & Lu, Ning & Qin, Jun & Liu, Tang & Zhou, Chenghu, 2022. "Spatial estimation of the optimum PV tilt angles in China by incorporating ground with satellite data," Renewable Energy, Elsevier, vol. 189(C), pages 1249-1258.
  2. Liu, Jingxuan & Zang, Haixiang & Zhang, Fengchun & Cheng, Lilin & Ding, Tao & Wei, Zhinong & Sun, Guoqiang, 2023. "A hybrid meteorological data simulation framework based on time-series generative adversarial network for global daily solar radiation estimation," Renewable Energy, Elsevier, vol. 219(P1).
  3. Tan, Yunhui & Wang, Quan & Zhang, Zhaoyang, 2023. "Near-real-time estimation of global horizontal irradiance from Himawari-8 satellite data," Renewable Energy, Elsevier, vol. 215(C).
  4. Zhang, Xinyao & Yang, Kun & Shao, Changkun & Chen, Haochong, 2025. "A novel parameterization scheme for accurate and efficient radiation transfer modeling in large-scale PV power plants," Applied Energy, Elsevier, vol. 384(C).
  5. Ren, Simiao & Hu, Wayne & Bradbury, Kyle & Harrison-Atlas, Dylan & Malaguzzi Valeri, Laura & Murray, Brian & Malof, Jordan M., 2022. "Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis," Applied Energy, Elsevier, vol. 326(C).
  6. Chen, Jiang & Zhu, Weining & Yu, Qian, 2021. "Estimating half-hourly solar radiation over the Continental United States using GOES-16 data with iterative random forest," Renewable Energy, Elsevier, vol. 178(C), pages 916-929.
  7. Jiang, Hou & Lu, Ning & Huang, Guanghui & Yao, Ling & Qin, Jun & Liu, Hengzi, 2020. "Spatial scale effects on retrieval accuracy of surface solar radiation using satellite data," Applied Energy, Elsevier, vol. 270(C).
  8. Mao, Mingxuan & Wang, Lining & Jiang, Sheng & Zhang, Hao, 2026. "Meteorological element prediction for renewable energy systems: Comprehensive comparison on deep learning algorithms with/without hyperparameters tuning," Energy, Elsevier, vol. 346(C).
  9. Elena Esposito & Gianni Leanza & Girolamo Di Francia, 2024. "Comparative Analysis of Ground-Based Solar Irradiance Measurements and Copernicus Satellite Observations," Energies, MDPI, vol. 17(7), pages 1-21, March.
  10. Lu, Yunbo & Wang, Lunche & Zhu, Canming & Zou, Ling & Zhang, Ming & Feng, Lan & Cao, Qian, 2023. "Predicting surface solar radiation using a hybrid radiative Transfer–Machine learning model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
  11. Shi, Hongrong & Yang, Dazhi & Wang, Wenting & Fu, Disong & Gao, Ling & Zhang, Jinqiang & Hu, Bo & Shan, Yunpeng & Zhang, Yingjie & Bian, Yuxuan & Chen, Hongbin & Xia, Xiangao, 2023. "First estimation of high-resolution solar photovoltaic resource maps over China with Fengyun-4A satellite and machine learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
  12. Jiang, Hou & Yao, Ling & Lu, Ning & Qin, Jun & Zhang, Xiaotong & Liu, Tang & Zhang, Xingxing & Zhou, Chenghu, 2024. "Exploring the optimization of rooftop photovoltaic scale and spatial layout under curtailment constraints," Energy, Elsevier, vol. 293(C).
  13. Jiang, Hou & Zhang, Xiaotong & Yao, Ling & Lu, Ning & Qin, Jun & Liu, Tang & Zhou, Chenghu, 2023. "High-resolution analysis of rooftop photovoltaic potential based on hourly generation simulations and load profiles," Applied Energy, Elsevier, vol. 348(C).
  14. Ruan, Zhaohui & Sun, Weiwei & Yuan, Yuan & Tan, Heping, 2023. "Accurately forecasting solar radiation distribution at both spatial and temporal dimensions simultaneously with fully-convolutional deep neural network model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
  15. Li, Na & Zhen, Zhao & Wang, Fei, 2026. "Surface solar irradiance retrieval approach based on satellite band optimal combination and multi-spatial scale mapping," Renewable Energy, Elsevier, vol. 256(PD).
  16. Jiang, Hou & Lu, Ning & Yao, Ling & Qin, Jun & Liu, Tang, 2023. "Impact of climate changes on the stability of solar energy: Evidence from observations and reanalysis," Renewable Energy, Elsevier, vol. 208(C), pages 726-736.
  17. Fan, Junliang & Zheng, Jing & Wu, Lifeng & Zhang, Fucang, 2021. "Estimation of daily maize transpiration using support vector machines, extreme gradient boosting, artificial and deep neural networks models," Agricultural Water Management, Elsevier, vol. 245(C).
  18. Liu, Jingxuan & Zang, Haixiang & Ding, Tao & Cheng, Lilin & Wei, Zhinong & Sun, Guoqiang, 2023. "Harvesting spatiotemporal correlation from sky image sequence to improve ultra-short-term solar irradiance forecasting," Renewable Energy, Elsevier, vol. 209(C), pages 619-631.
  19. Shao, Guomin & Han, Wenting & Zhang, Huihui & Liu, Shouyang & Wang, Yi & Zhang, Liyuan & Cui, Xin, 2021. "Mapping maize crop coefficient Kc using random forest algorithm based on leaf area index and UAV-based multispectral vegetation indices," Agricultural Water Management, Elsevier, vol. 252(C).
  20. Qin, Jun & Jiang, Hou & Lu, Ning & Yao, Ling & Zhou, Chenghu, 2022. "Enhancing solar PV output forecast by integrating ground and satellite observations with deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  21. Shao, Changkun & Yang, Kun & Tang, Wenjun & He, Yanyi & Jiang, Yaozhi & Lu, Hui & Fu, Haohuan & Zheng, Juepeng, 2022. "Convolutional neural network-based homogenization for constructing a long-term global surface solar radiation dataset," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
  22. Chen, Shanlin & Li, Chengxi & Xie, Yuying & Li, Mengying, 2023. "Global and direct solar irradiance estimation using deep learning and selected spectral satellite images," Applied Energy, Elsevier, vol. 352(C).
  23. Jiang, Hou & Lu, Ning & Qin, Jun & Yao, Ling, 2021. "Hierarchical identification of solar radiation zones in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
  24. Chu, Yinghao & Wang, Yiling & Yang, Dazhi & Chen, Shanlin & Li, Mengying, 2024. "A review of distributed solar forecasting with remote sensing and deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 198(C).
  25. Narvaez, Gabriel & Giraldo, Luis Felipe & Bressan, Michael & Pantoja, Andres, 2021. "Machine learning for site-adaptation and solar radiation forecasting," Renewable Energy, Elsevier, vol. 167(C), pages 333-342.
  26. Gao, Yuan & Hu, Zehuan & Chen, Wei-An & Liu, Mingzhe, 2024. "Solutions to the insufficiency of label data in renewable energy forecasting: A comparative and integrative analysis of domain adaptation and fine-tuning," Energy, Elsevier, vol. 302(C).
  27. Hou Jiang & Ning Lu & Xuecheng Wang, 2023. "Assessing Carbon Reduction Potential of Rooftop PV in China through Remote Sensing Data-Driven Simulations," Sustainability, MDPI, vol. 15(4), pages 1-16, February.
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