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Machine learning for site-adaptation and solar radiation forecasting

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Cited by:

  1. Sun, Jingbo & Wang, Yang & He, Yuan & Cui, Wenrui & Chao, Qingchen & Shan, Baoguo & Wang, Zheng & Yang, Xiaofan, 2024. "The energy security risk assessment of inefficient wind and solar resources under carbon neutrality in China," Applied Energy, Elsevier, vol. 360(C).
  2. Acikgoz, Hakan, 2022. "A novel approach based on integration of convolutional neural networks and deep feature selection for short-term solar radiation forecasting," Applied Energy, Elsevier, vol. 305(C).
  3. Bashir, Tasarruf & Wang, Huifang & Tahir, Mustafa & Zhang, Yixiang, 2025. "Wind and solar power forecasting based on hybrid CNN-ABiLSTM, CNN-transformer-MLP models," Renewable Energy, Elsevier, vol. 239(C).
  4. Hoyos-Gómez, Laura S. & Ruiz-Muñoz, Jose F. & Ruiz-Mendoza, Belizza J., 2022. "Short-term forecasting of global solar irradiance in tropical environments with incomplete data," Applied Energy, Elsevier, vol. 307(C).
  5. 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).
  6. Sibtain, Muhammad & Li, Xianshan & Saleem, Snoober & Ain, Qurat-ul- & Shi, Qiang & Li, Fei & Saeed, Muhammad & Majeed, Fatima & Shah, Syed Shoaib Ahmed & Saeed, Muhammad Hammad, 2022. "Multifaceted irradiance prediction by exploiting hybrid decomposition-entropy-Spatiotemporal attention based Sequence2Sequence models," Renewable Energy, Elsevier, vol. 196(C), pages 648-682.
  7. Oubah Isman Okieh & Serhat Seker & Seckin Gokce & Martin Dennenmoser, 2024. "An Enhanced Forecasting Method of Daily Solar Irradiance in Southwestern France: A Hybrid Nonlinear Autoregressive with Exogenous Inputs with Long Short-Term Memory Approach," Energies, MDPI, vol. 17(16), pages 1-21, August.
  8. Han, Jen-Yu & Vohnicky, Petr, 2022. "An optimized approach for mapping solar irradiance in a mid-low latitude region based on a site-adaptation technique using Himawari-8 satellite imageries," Renewable Energy, Elsevier, vol. 187(C), pages 603-617.
  9. Han, Jen-Yu & Li, Sin-Yi & Chen, Yi-Chien, 2025. "Estimation of solar photovoltaic efficiency under the urban heat island effect," Renewable Energy, Elsevier, vol. 242(C).
  10. Akhter, Muhammad Naveed & Mekhilef, Saad & Mokhlis, Hazlie & Ali, Raza & Usama, Muhammad & Muhammad, Munir Azam & Khairuddin, Anis Salwa Mohd, 2022. "A hybrid deep learning method for an hour ahead power output forecasting of three different photovoltaic systems," Applied Energy, Elsevier, vol. 307(C).
  11. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
  12. Cheng, Lilin & Zang, Haixiang & Wei, Zhinong & Zhang, Fengchun & Sun, Guoqiang, 2022. "Evaluation of opaque deep-learning solar power forecast models towards power-grid applications," Renewable Energy, Elsevier, vol. 198(C), pages 960-972.
  13. Zhu, Leyang & Huang, Xiaoqiao & Zhang, Zongbin & Li, Chengli & Tai, Yonghang, 2025. "A novel U-LSTM-AFT model for hourly solar irradiance forecasting," Renewable Energy, Elsevier, vol. 238(C).
  14. Muhammad Naveed Akhter & Saad Mekhilef & Hazlie Mokhlis & Ziyad M. Almohaimeed & Munir Azam Muhammad & Anis Salwa Mohd Khairuddin & Rizwan Akram & Muhammad Majid Hussain, 2022. "An Hour-Ahead PV Power Forecasting Method Based on an RNN-LSTM Model for Three Different PV Plants," Energies, MDPI, vol. 15(6), pages 1-21, March.
  15. Qiangsheng Bu & Shuyi Zhuang & Fei Luo & Zhigang Ye & Yubo Yuan & Tianrui Ma & Tao Da, 2024. "Improving Solar Radiation Forecasting in Cloudy Conditions by Integrating Satellite Observations," Energies, MDPI, vol. 17(24), pages 1-20, December.
  16. Christos Kyriakos & Manolis Vavalis, 2023. "Business Intelligence through Machine Learning from Satellite Remote Sensing Data," Future Internet, MDPI, vol. 15(11), pages 1-29, October.
  17. Zang, Haixiang & Jiang, Xin & Cheng, LiLin & Zhang, Fengchun & Wei, Zhinong & Sun, Guoqiang, 2022. "Combined empirical and machine learning modeling method for estimation of daily global solar radiation for general meteorological observation stations," Renewable Energy, Elsevier, vol. 195(C), pages 795-808.
  18. 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).
  19. Zhi Rao & Zaimin Yang & Xiongping Yang & Jiaming Li & Wenchuan Meng & Zhichu Wei, 2024. "TCN-GRU Based on Attention Mechanism for Solar Irradiance Prediction," Energies, MDPI, vol. 17(22), pages 1-17, November.
  20. Dong, Shiqian & Di, Yanqiang & Gao, Yafeng & Long, He & Fan, Zhixuan & Guan, Jingxuan & Han, Lijun & Wang, Yingming, 2025. "Multiple operational strategies investigations of the PV/T collectors based on 3 days ahead hourly radiation prediction," Applied Energy, Elsevier, vol. 377(PA).
  21. 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.
  22. Hongchao Zhang & Tengteng Zhu, 2022. "Stacking Model for Photovoltaic-Power-Generation Prediction," Sustainability, MDPI, vol. 14(9), pages 1-16, May.
  23. Salamalikis, Vasileios & Tzoumanikas, Panayiotis & Argiriou, Athanassios A. & Kazantzidis, Andreas, 2022. "Site adaptation of global horizontal irradiance from the Copernicus Atmospheric Monitoring Service for radiation using supervised machine learning techniques," Renewable Energy, Elsevier, vol. 195(C), pages 92-106.
  24. Sankara kumar, Sundarapandian & Karthick, Alagar & Shankar, R. & Dharmaraj, Ganeshaperumal, 2024. "Energy forecasting of the building integrated photovoltaic system based on deep learning dragonfly-firefly algorithm," Energy, Elsevier, vol. 308(C).
  25. Wang, Zhijin & Liu, Xiufeng & Huang, Yaohui & Zhang, Peisong & Fu, Yonggang, 2023. "A multivariate time series graph neural network for district heat load forecasting," Energy, Elsevier, vol. 278(PA).
  26. Abad-Alcaraz, V. & Castilla, M. & Carballo, J.A. & Bonilla, J. & Álvarez, J.D., 2025. "Multimodal deep learning for solar radiation forecasting," Applied Energy, Elsevier, vol. 393(C).
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