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Hybrid deep neural model for hourly solar irradiance forecasting

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  1. Liu, Xiangjie & Liu, Yuanyan & Kong, Xiaobing & Ma, Lele & Besheer, Ahmad H. & Lee, Kwang Y., 2023. "Deep neural network for forecasting of photovoltaic power based on wavelet packet decomposition with similar day analysis," Energy, Elsevier, vol. 271(C).
  2. Liu, Bingchun & Zhao, Shunfan & Zheng, Shize & Zhang, Fukai & Li, Zefeng & Gao, Xu & Wang, Ying, 2025. "Assessing the potential impact of aerosol scenarios for rooftop PV regional deployment," Renewable Energy, Elsevier, vol. 246(C).
  3. Hanif, M.F. & Mi, J., 2024. "Harnessing AI for solar energy: Emergence of transformer models," Applied Energy, Elsevier, vol. 369(C).
  4. Liu, Shuwei & Tian, Jianyan & Dai, Yuanyuan & Ji, Zhengxiong & Banerjee, Amit, 2025. "The physical-encoded Photovoltaic forecasting method combined with continuous learning and multi-digital twins mechanisms," Applied Energy, Elsevier, vol. 399(C).
  5. 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).
  6. 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).
  7. Xu, Shaozhen & Liu, Jun & Huang, Xiaoqiao & Li, Chengli & Chen, Zaiqing & Tai, Yonghang, 2024. "Minutely multi-step irradiance forecasting based on all-sky images using LSTM-InformerStack hybrid model with dual feature enhancement," Renewable Energy, Elsevier, vol. 224(C).
  8. Fadhilah A. Suwadana & Pranda M. P. Garniwa & Dhavani A. Putera & Dita Puspita & Ahmad Gufron & Indra A. Aditya & Hyunjin Lee & Iwa Garniwa, 2025. "Solar Irradiance Estimation in Tropical Regions Using Recurrent Neural Networks and WRF Models," Energies, MDPI, vol. 18(4), pages 1-17, February.
  9. Martins, Guilherme Santos & Giesbrecht, Mateus, 2023. "Hybrid approaches based on Singular Spectrum Analysis and k- Nearest Neighbors for clearness index forecasting," Renewable Energy, Elsevier, vol. 219(P1).
  10. Niu, Tong & Li, Jinkai & Wei, Wei & Yue, Hui, 2022. "A hybrid deep learning framework integrating feature selection and transfer learning for multi-step global horizontal irradiation forecasting," Applied Energy, Elsevier, vol. 326(C).
  11. Liao, Zhouyi & Coimbra, Carlos F.M., 2024. "Hybrid solar irradiance nowcasting and forecasting with the SCOPE method and convolutional neural networks," Renewable Energy, Elsevier, vol. 232(C).
  12. 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).
  13. He, Zhichao & Huang, Jianhua, 2023. "A novel non-ferrous metal price hybrid forecasting model based on data preprocessing and error correction," Resources Policy, Elsevier, vol. 86(PB).
  14. Yuan-Kang Wu & Cheng-Liang Huang & Quoc-Thang Phan & Yuan-Yao Li, 2022. "Completed Review of Various Solar Power Forecasting Techniques Considering Different Viewpoints," Energies, MDPI, vol. 15(9), pages 1-22, May.
  15. Hammond, Joshua E. & Lara Orozco, Ricardo A. & Baldea, Michael & Korgel, Brian A., 2024. "Short-term solar irradiance forecasting under data transmission constraints," Renewable Energy, Elsevier, vol. 233(C).
  16. Li, Bowen & Ampah, Jeffrey Dankwa & Li, Tiantian & Zhang, Xing & Liu, Haifeng & Feng, Hongqing & Yue, Zongyu & Hussain Ratlamwala, Tahir Abdul & Yao, Mingfa, 2025. "Enhancing renewable energy load forecasting through deep data analysis and feature extraction techniques," Energy, Elsevier, vol. 340(C).
  17. Zhao, He & Huang, Xiaoqiao & Xiao, Zenan & Shi, Haoyuan & Li, Chengli & Tai, Yonghang, 2024. "Week-ahead hourly solar irradiation forecasting method based on ICEEMDAN and TimesNet networks," Renewable Energy, Elsevier, vol. 220(C).
  18. 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.
  19. Zheng, Jianqin & Du, Jian & Wang, Bohong & Klemeš, Jiří Jaromír & Liao, Qi & Liang, Yongtu, 2023. "A hybrid framework for forecasting power generation of multiple renewable energy sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 172(C).
  20. Jiang, Chengcheng & Zhu, Qunzhi, 2023. "Evaluating the most significant input parameters for forecasting global solar radiation of different sequences based on Informer," Applied Energy, Elsevier, vol. 348(C).
  21. Krishnan, Naveen & Ravi Kumar, K., 2025. "A novel evolutionary ensemble model to forecast hourly global horizontal irradiance under various climatic zones," Energy, Elsevier, vol. 340(C).
  22. Tawsif Ahmad & Ning Zhou & Ziang Zhang & Wenyuan Tang, 2024. "Enhancing Probabilistic Solar PV Forecasting: Integrating the NB-DST Method with Deterministic Models," Energies, MDPI, vol. 17(10), pages 1-19, May.
  23. Edna S. Solano & Carolina M. Affonso, 2023. "Solar Irradiation Forecasting Using Ensemble Voting Based on Machine Learning Algorithms," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
  24. 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.
  25. 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).
  26. Kong, Xiangfei & Du, Xinyu & Xue, Guixiang & Xu, Zhijie, 2023. "Multi-step short-term solar radiation prediction based on empirical mode decomposition and gated recurrent unit optimized via an attention mechanism," Energy, Elsevier, vol. 282(C).
  27. 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).
  28. Kumar Saini, Vikash & Al-Sumaiti, Ameena S. & Kumar, Ashok & Kumar, Rajesh & Zeineldin, Hatem & El-Saadany, Ehab Fahmy, 2025. "RSNN: Rate encoding mechanism-based spiking neural network for renewable energy forecasting," Energy, Elsevier, vol. 333(C).
  29. Negri, Simone & Giani, Federico & Blasuttigh, Nicola & Massi Pavan, Alessandro & Mellit, Adel & Tironi, Enrico, 2022. "Combined model predictive control and ANN-based forecasters for jointly acting renewable self-consumers: An environmental and economical evaluation," Renewable Energy, Elsevier, vol. 198(C), pages 440-454.
  30. Chen, Yunxiao & Bai, Mingliang & Zhang, Yilan & Liu, Jinfu & Yu, Daren, 2023. "Proactively selection of input variables based on information gain factors for deep learning models in short-term solar irradiance forecasting," Energy, Elsevier, vol. 284(C).
  31. Sun, Fengpeng & Li, Longhao & Bian, Dunxin & Bian, Wenlin & Wang, Qinghong & Wang, Shuang, 2025. "Photovoltaic power prediction based on multi-scale photovoltaic power fluctuation characteristics and multi-channel LSTM prediction models," Renewable Energy, Elsevier, vol. 246(C).
  32. Gyeltshen, Sangay & Hayashi, Kiichiro & Tao, Linwei & Dem, Phub, 2025. "Statistical evaluation of a diversified surface solar irradiation data repository and forecasting using a recurrent neural network-hybrid model: A case study in Bhutan," Renewable Energy, Elsevier, vol. 245(C).
  33. Elizabeth Michael, Neethu & Hasan, Shazia & Al-Durra, Ahmed & Mishra, Manohar, 2022. "Short-term solar irradiance forecasting based on a novel Bayesian optimized deep Long Short-Term Memory neural network," Applied Energy, Elsevier, vol. 324(C).
  34. Bisoi, Ranjeeta & Dash, Deepak Ranjan & Dash, P.K. & Tripathy, Lokanath, 2022. "An efficient robust optimized functional link broad learning system for solar irradiance prediction," Applied Energy, Elsevier, vol. 319(C).
  35. Feng, Zhong-kai & Huang, Qing-qing & Niu, Wen-jing & Yang, Tao & Wang, Jia-yang & Wen, Shi-ping, 2022. "Multi-step-ahead solar output time series prediction with gate recurrent unit neural network using data decomposition and cooperation search algorithm," Energy, Elsevier, vol. 261(PA).
  36. Hanifi, Shahram & Zare-Behtash, Hossein & Cammarano, Andrea & Lotfian, Saeid, 2023. "Offshore wind power forecasting based on WPD and optimised deep learning methods," Renewable Energy, Elsevier, vol. 218(C).
  37. Niu, Yunbo & Wang, Jianzhou & Zhang, Ziyuan & Luo, Tianrui & Liu, Jingjiang, 2024. "De-Trend First, Attend Next: A Mid-Term PV forecasting system with attention mechanism and encoder–decoder structure," Applied Energy, Elsevier, vol. 353(PB).
  38. Deng, Ruizhe & Wang, Yiming & Xu, Po & Luo, Futao & Chen, Qi & Zhang, Haoran & Chen, Yuntian & Zhang, Dongxiao, 2025. "A high-precision photovoltaic power forecasting model leveraging low-fidelity data through decoupled informer with multi-moment guidance," Renewable Energy, Elsevier, vol. 250(C).
  39. Liu, Jiarui & Fu, Yuchen, 2023. "Decomposition spectral graph convolutional network based on multi-channel adaptive adjacency matrix for renewable energy prediction," Energy, Elsevier, vol. 284(C).
  40. Bo Gu & Xi Li & Fengliang Xu & Xiaopeng Yang & Fayi Wang & Pengzhan Wang, 2023. "Forecasting and Uncertainty Analysis of Day-Ahead Photovoltaic Power Based on WT-CNN-BiLSTM-AM-GMM," Sustainability, MDPI, vol. 15(8), pages 1-27, April.
  41. Luo, Shihua & Hu, Weihao & Liu, Wen & Cao, Di & Du, Yuefang & Zhang, Zhenyuan & Chen, Zhe, 2022. "Impact analysis of COVID-19 pandemic on the future green power sector: A case study in the Netherlands," Renewable Energy, Elsevier, vol. 191(C), pages 261-277.
  42. Jiaxin He & Junjiao Zhang & Lezhong Wang & Xiaoying Hu & Junjie Xue & Ying Zhao & Xiaoqiang Wang & Changqing Dong, 2023. "Optimizing the Controlling Parameters of a Biomass Boiler Based on Big Data," Energies, MDPI, vol. 16(23), pages 1-16, November.
  43. Huang, Xiaoqiao & Li, Qiong & Tai, Yonghang & Chen, Zaiqing & Liu, Jun & Shi, Junsheng & Liu, Wuming, 2022. "Time series forecasting for hourly photovoltaic power using conditional generative adversarial network and Bi-LSTM," Energy, Elsevier, vol. 246(C).
  44. Cheng-Hong Yang & Tshimologo Molefyane & Yu-Da Lin, 2023. "The Forecasting of a Leading Country’s Government Expenditure Using a Recurrent Neural Network with a Gated Recurrent Unit," Mathematics, MDPI, vol. 11(14), pages 1-17, July.
  45. Azizi, Narjes & Yaghoubirad, Maryam & Farajollahi, Meisam & Ahmadi, Abolfzl, 2023. "Deep learning based long-term global solar irradiance and temperature forecasting using time series with multi-step multivariate output," Renewable Energy, Elsevier, vol. 206(C), pages 135-147.
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