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Hourly forecasting of solar irradiance based on CEEMDAN and multi-strategy CNN-LSTM neural networks

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  1. Jiaan Zhang & Yan Hao & Ruiqing Fan & Zhenzhen Wang, 2023. "An Ultra-Short-Term PV Power Forecasting Method for Changeable Weather Based on Clustering and Signal Decomposition," Energies, MDPI, vol. 16(7), pages 1-15, March.
  2. Alex Sleiman & Wencong Su, 2024. "Combined K-Means Clustering with Neural Networks Methods for PV Short-Term Generation Load Forecasting in Electric Utilities," Energies, MDPI, vol. 17(6), pages 1-27, March.
  3. 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.
  4. Liu, Jiarui & Fu, Yuchen, 2023. "Renewable energy forecasting: A self-supervised learning-based transformer variant," Energy, Elsevier, vol. 284(C).
  5. Tang, Xianlun & Xia, Yu & Jiang, Lin & Xiong, Deyi & Wang, Lejun & Wang, Ying, 2025. "Dynamic adaptive hierarchical TCN driven by IHOA-VMD optimization for short term load forecasting," Energy, Elsevier, vol. 335(C).
  6. Hanif, M.F. & Mi, J., 2024. "Harnessing AI for solar energy: Emergence of transformer models," Applied Energy, Elsevier, vol. 369(C).
  7. Ghadah Alkhayat & Syed Hamid Hasan & Rashid Mehmood, 2022. "SENERGY: A Novel Deep Learning-Based Auto-Selective Approach and Tool for Solar Energy Forecasting," Energies, MDPI, vol. 15(18), pages 1-55, September.
  8. Hamid Ebrahimi, 2026. "A Novel Evidential Uncertainty Framework for Hybrid Models in Rainfall Simulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 40(2), pages 1-24, January.
  9. Yong Zhou & Lingyu Wang & Junhao Qian, 2022. "Application of Combined Models Based on Empirical Mode Decomposition, Deep Learning, and Autoregressive Integrated Moving Average Model for Short-Term Heating Load Predictions," Sustainability, MDPI, vol. 14(12), pages 1-20, June.
  10. Xiao, Zenan & Huang, Xiaoqiao & Liu, Jun & Li, Chengli & Tai, Yonghang, 2023. "A novel method based on time series ensemble model for hourly photovoltaic power prediction," Energy, Elsevier, vol. 276(C).
  11. Caston Sigauke & Thakhani Ravele & Lordwell Jhamba, 2022. "Extremal Dependence Modelling of Global Horizontal Irradiance with Temperature and Humidity: An Application Using South African Data," Energies, MDPI, vol. 15(16), pages 1-25, August.
  12. 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).
  13. Xiaoyu Liu & Jiangfeng Song & Hai Tao & Peng Wang & Haihua Mo & Wenjie Du, 2025. "Quarter-Hourly Power Load Forecasting Based on a Hybrid CNN-BiLSTM-Attention Model with CEEMDAN, K-Means, and VMD," Energies, MDPI, vol. 18(11), pages 1-29, May.
  14. Gao, Bixuan & Kong, Xiangyu & Li, Shangze & Chen, Yi & Zhang, Xiyuan & Liu, Ziyu & Lv, Weijia, 2024. "Enhancing anomaly detection accuracy and interpretability in low-quality and class imbalanced data: A comprehensive approach," Applied Energy, Elsevier, vol. 353(PB).
  15. Huang, Xiaoqiao & Li, Qiong & Tai, Yonghang & Chen, Zaiqing & Zhang, Jun & Shi, Junsheng & Gao, Bixuan & Liu, Wuming, 2021. "Hybrid deep neural model for hourly solar irradiance forecasting," Renewable Energy, Elsevier, vol. 171(C), pages 1041-1060.
  16. Nourani, Vahid & Sharghi, Elnaz & Behfar, Nazanin & Zhang, Yongqiang, 2022. "Multi-step-ahead solar irradiance modeling employing multi-frequency deep learning models and climatic data," Applied Energy, Elsevier, vol. 315(C).
  17. Zhang, Yandi, 2025. "Enhancing solar irradiance prediction for sustainable energy solutions employing a hybrid machine learning model; improving hydrogen production through Photoelectrochemical device," Applied Energy, Elsevier, vol. 382(C).
  18. 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).
  19. 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).
  20. Wang, Zhenyu & Zhang, Yunpeng & Li, Guorong & Zhang, Jinlong & Zhou, Hai & Wu, Ji, 2024. "A novel solar irradiance forecasting method based on multi-physical process of atmosphere optics and LSTM-BP model," Renewable Energy, Elsevier, vol. 226(C).
  21. 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).
  22. Vu, Ba Hau & Chung, Il-Yop, 2022. "Optimal generation scheduling and operating reserve management for PV generation using RNN-based forecasting models for stand-alone microgrids," Renewable Energy, Elsevier, vol. 195(C), pages 1137-1154.
  23. Li, You & Zhou, Weisheng & Wang, Yafei & Miao, Sheng & Yao, Wanxiang & Gao, Weijun, 2025. "Interpretable deep learning framework for hourly solar radiation forecasting based on decomposing multi-scale variations," Applied Energy, Elsevier, vol. 377(PA).
  24. Xie, Qiyue & Ma, Lin & Liu, Yao & Fu, Qiang & Shen, Zhongli & Wang, Xiaoli, 2023. "An improved SSA-BiLSTM-based short-term irradiance prediction model via sky images feature extraction," Renewable Energy, Elsevier, vol. 219(P2).
  25. 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).
  26. 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).
  27. Quanhui Qiu & Dejun Ning & Qiang Guo & Jiang Wei & Huichang Chen & Lihui Sui & Yi Liu & Zibing Du & Shipeng Liu, 2025. "DTCformer: A Temporal Convolution-Enhanced Autoformer with DILATE Loss for Photovoltaic Power Forecasting," Energies, MDPI, vol. 18(10), pages 1-16, May.
  28. Hongchao Zhang & Tengteng Zhu, 2022. "Stacking Model for Photovoltaic-Power-Generation Prediction," Sustainability, MDPI, vol. 14(9), pages 1-16, May.
  29. Su, Yixin & Wang, Zeyu & Dong, Zhengcheng & Hua, Xiaojun & Ye, Tao & Song, Zida & Shao, Yun, 2025. "Frequency-aware ultra-short-term wind power forecasting using CEEMDAN–VMD–SE and Transformer–GRU networks," Energy, Elsevier, vol. 338(C).
  30. Li, Ke & Mu, Yuchen & Yang, Fan & Wang, Haiyang & Yan, Yi & Zhang, Chenghui, 2023. "A novel short-term multi-energy load forecasting method for integrated energy system based on feature separation-fusion technology and improved CNN," Applied Energy, Elsevier, vol. 351(C).
  31. Yiling Fan & Zhuang Ma & Wanwei Tang & Jing Liang & Pengfei Xu, 2024. "Using Crested Porcupine Optimizer Algorithm and CNN-LSTM-Attention Model Combined with Deep Learning Methods to Enhance Short-Term Power Forecasting in PV Generation," Energies, MDPI, vol. 17(14), pages 1-17, July.
  32. 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).
  33. Gupta, Priya & Singh, Rhythm, 2023. "Combining simple and less time complex ML models with multivariate empirical mode decomposition to obtain accurate GHI forecast," Energy, Elsevier, vol. 263(PC).
  34. Sumit Saroha & Marta Zurek-Mortka & Jerzy Ryszard Szymanski & Vineet Shekher & Pardeep Singla, 2021. "Forecasting of Market Clearing Volume Using Wavelet Packet-Based Neural Networks with Tracking Signals," Energies, MDPI, vol. 14(19), pages 1-21, September.
  35. Rathore, Abhijeet & Gupta, Priya & Sharma, Raksha & Singh, Rhythm, 2025. "Day ahead solar forecast using long short term memory network augmented with Fast Fourier transform-assisted decomposition technique," Renewable Energy, Elsevier, vol. 247(C).
  36. Wang, Jianzhou & Zhou, Yilin & Li, Zhiwu, 2022. "Hour-ahead photovoltaic generation forecasting method based on machine learning and multi objective optimization algorithm," Applied Energy, Elsevier, vol. 312(C).
  37. Wang, Shuangxin & Shi, Jiarong & Yang, Wei & Yin, Qingyan, 2024. "High and low frequency wind power prediction based on Transformer and BiGRU-Attention," Energy, Elsevier, vol. 288(C).
  38. Huang, Xiaoqiao & Liu, Jun & Xu, Shaozhen & Li, Chengli & Li, Qiong & Tai, Yonghang, 2023. "A 3D ConvLSTM-CNN network based on multi-channel color extraction for ultra-short-term solar irradiance forecasting," Energy, Elsevier, vol. 272(C).
  39. Eşlik, Ardan Hüseyin & Akarslan, Emre & Hocaoğlu, Fatih Onur, 2022. "Short-term solar radiation forecasting with a novel image processing-based deep learning approach," Renewable Energy, Elsevier, vol. 200(C), pages 1490-1505.
  40. Chao Zhang & Yihang Zhao & Huiru Zhao, 2022. "A Novel Hybrid Price Prediction Model for Multimodal Carbon Emission Trading Market Based on CEEMDAN Algorithm and Window-Based XGBoost Approach," Mathematics, MDPI, vol. 10(21), pages 1-16, November.
  41. Haoran Zhao & Sen Guo, 2023. "Carbon Trading Price Prediction of Three Carbon Trading Markets in China Based on a Hybrid Model Combining CEEMDAN, SE, ISSA, and MKELM," Mathematics, MDPI, vol. 11(10), pages 1-21, May.
  42. Zhang, Chu & Hua, Lei & Ji, Chunlei & Shahzad Nazir, Muhammad & Peng, Tian, 2022. "An evolutionary robust solar radiation prediction model based on WT-CEEMDAN and IASO-optimized outlier robust extreme learning machine," Applied Energy, Elsevier, vol. 322(C).
  43. Zhong-kai Feng & Wen-jie Liu & Wen-jing Niu & Tao Yang & Wen-chuan Wang & Sen Wang, 2025. "Compound Hydrological Forecasting Model by Long Short-term Memory Network Coupled with Adaptive Mode Decomposition and Evolutionary Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 39(6), pages 2651-2672, April.
  44. Cabello-López, Tomás & Carranza-García, Manuel & Riquelme, José C. & García-Gutiérrez, Jorge, 2023. "Forecasting solar energy production in Spain: A comparison of univariate and multivariate models at the national level," Applied Energy, Elsevier, vol. 350(C).
  45. Isaac Gallardo & Daniel Amor & Álvaro Gutiérrez, 2023. "Recent Trends in Real-Time Photovoltaic Prediction Systems," Energies, MDPI, vol. 16(15), pages 1-17, July.
  46. Tovar Rosas, Mario A. & Pérez, Miguel Robles & Martínez Pérez, E. Rafael, 2022. "Itineraries for charging and discharging a BESS using energy predictions based on a CNN-LSTM neural network model in BCS, Mexico," Renewable Energy, Elsevier, vol. 188(C), pages 1141-1165.
  47. Li, Qingyang & Wang, Guosong & Wu, Xinrong & Gao, Zhigang & Dan, Bo, 2024. "Arctic short-term wind speed forecasting based on CNN-LSTM model with CEEMDAN," Energy, Elsevier, vol. 299(C).
  48. Zhang, Chu & Ma, Huixin & Hua, Lei & Sun, Wei & Nazir, Muhammad Shahzad & Peng, Tian, 2022. "An evolutionary deep learning model based on TVFEMD, improved sine cosine algorithm, CNN and BiLSTM for wind speed prediction," Energy, Elsevier, vol. 254(PA).
  49. Lv, Sheng-Xiang & Wang, Lin, 2022. "Deep learning combined wind speed forecasting with hybrid time series decomposition and multi-objective parameter optimization," Applied Energy, Elsevier, vol. 311(C).
  50. Natei Ermias Benti & Mesfin Diro Chaka & Addisu Gezahegn Semie, 2023. "Forecasting Renewable Energy Generation with Machine Learning and Deep Learning: Current Advances and Future Prospects," Sustainability, MDPI, vol. 15(9), pages 1-33, April.
  51. Liu, Tianhao & Shan, Linke & Jiang, Meihui & Li, Fangning & Kong, Fannie & Du, Pengcheng & Zhu, Hongyu & Goh, Hui Hwang & Kurniawan, Tonni Agustiono & Huang, Chao & Zhang, Dongdong, 2025. "Multi-dimensional data processing and intelligent forecasting technologies for renewable energy generation," Applied Energy, Elsevier, vol. 398(C).
  52. Yuan, Feng & Chen, Zhongsheng & Liang, Yujia, 2024. "Precise solar radiation forecasting for sustainable energy integration: A hybrid CEEMD-SCM-GA-LGBM model for day-ahead power and hydrogen production," Renewable Energy, Elsevier, vol. 237(PC).
  53. Kumari, Pratima & Toshniwal, Durga, 2021. "Long short term memory–convolutional neural network based deep hybrid approach for solar irradiance forecasting," Applied Energy, Elsevier, vol. 295(C).
  54. Wang, Lining & Mao, Mingxuan & Xie, Jili & Liao, Zheng & Zhang, Hao & Li, Huanxin, 2023. "Accurate solar PV power prediction interval method based on frequency-domain decomposition and LSTM model," Energy, Elsevier, vol. 262(PB).
  55. Neethu Elizabeth Michael & Manohar Mishra & Shazia Hasan & Ahmed Al-Durra, 2022. "Short-Term Solar Power Predicting Model Based on Multi-Step CNN Stacked LSTM Technique," Energies, MDPI, vol. 15(6), pages 1-20, March.
  56. Rubasinghe, Osaka & Zhang, Tingze & Zhang, Xinan & Choi, San Shing & Chau, Tat Kei & Chow, Yau & Fernando, Tyrone & Iu, Herbert Ho-Ching, 2023. "Highly accurate peak and valley prediction short-term net load forecasting approach based on decomposition for power systems with high PV penetration," Applied Energy, Elsevier, vol. 333(C).
  57. 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.
  58. Ziyu Li & Xianqi Zhang, 2024. "A Novel Coupled Model for Monthly Rainfall Prediction Based on ESMD-EWT-SVD-LSTM," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(9), pages 3297-3312, July.
  59. 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).
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  61. Gupta, Priya & Singh, Rhythm, 2023. "Combining a deep learning model with multivariate empirical mode decomposition for hourly global horizontal irradiance forecasting," Renewable Energy, Elsevier, vol. 206(C), pages 908-927.
  62. Xuliang Tang & Heng Wan & Weiwen Wang & Mengxu Gu & Linfeng Wang & Linfeng Gan, 2023. "Lithium-Ion Battery Remaining Useful Life Prediction Based on Hybrid Model," Sustainability, MDPI, vol. 15(7), pages 1-18, April.
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