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Deep learning neural networks for short-term photovoltaic power forecasting

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Cited by:

  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. Daxini, Rajiv & Sun, Yanyi & Wilson, Robin & Wu, Yupeng, 2022. "Direct spectral distribution characterisation using the Average Photon Energy for improved photovoltaic performance modelling," Renewable Energy, Elsevier, vol. 201(P1), pages 1176-1188.
  3. Li, Jingtao & Ren, Xiaoying & Zhang, Fei & Gao, Lu & Li, Jierui & Cui, Tonghe, 2025. "Multi-timescale photovoltaic station power prediction based on Reformer model," Energy, Elsevier, vol. 327(C).
  4. Cheng Zhang & Wei Fang & Changjun Xie & Banghua Du & Xiaolan Dai & Qicheng Zhang & Hui Wu, 2025. "Day-Ahead Dispatch Optimization of an Integrated Hydrogen–Electric System Considering PEMEL/PEMFC Lifespan Degradation and Fuzzy-Weighted Dynamic Pricing," Energies, MDPI, vol. 18(18), pages 1-31, September.
  5. Wang, Min & Rao, Congjun & Xiao, Xinping & Hu, Zhuo & Goh, Mark, 2024. "Efficient shrinkage temporal convolutional network model for photovoltaic power prediction," Energy, Elsevier, vol. 297(C).
  6. Wang, Tao & Xu, Ye & Qin, Yu & Wang, Xu & Zheng, Feifan & Li, Wei, 2025. "Short-term PV forecasting of multiple scenarios based on multi-dimensional clustering and hybrid transformer-BiLSTM with ECPO," Energy, Elsevier, vol. 334(C).
  7. Gao, Xifeng & Zang, Yuesong & Ma, Qian & Liu, Mengmeng & Cui, Yiming & Dang, Dazhi, 2025. "A physics-constrained deep learning framework enhanced with signal decomposition for accurate short-term photovoltaic power generation forecasting," Energy, Elsevier, vol. 326(C).
  8. Zhou, Jianli & Ran, Jia & Ren, Jiayi & Zhao, Ruige & Wang, Yaqi & Wu, Yunna, 2025. "Digital intelligence-driven synergistic optimization of capacity configuration for wind-solar-hydrogen multi-energy systems integrated with shared energy storage," Energy, Elsevier, vol. 341(C).
  9. Yu, Sheng & He, Bin & Fang, Lei, 2025. "Multi-step short-term forecasting of photovoltaic power utilizing TimesNet with enhanced feature extraction and a novel loss function," Applied Energy, Elsevier, vol. 388(C).
  10. Limouni, Tariq & Yaagoubi, Reda & Bouziane, Khalid & Guissi, Khalid & Baali, El Houssain, 2023. "Accurate one step and multistep forecasting of very short-term PV power using LSTM-TCN model," Renewable Energy, Elsevier, vol. 205(C), pages 1010-1024.
  11. Wang, Xinyu & Ma, Wenping, 2024. "A hybrid deep learning model with an optimal strategy based on improved VMD and transformer for short-term photovoltaic power forecasting," Energy, Elsevier, vol. 295(C).
  12. Shitao Wang & Mingjian Sun & Yi Shen, 2022. "Semantic Segmentation Algorithm-Based Calculation of Cloud Shadow Trajectory and Cloud Speed," Energies, MDPI, vol. 15(23), pages 1-15, November.
  13. Gang Li & Chen Lin & Yupeng Li, 2025. "Probabilistic Forecasting of Provincial Regional Wind Power Considering Spatio-Temporal Features," Energies, MDPI, vol. 18(3), pages 1-17, January.
  14. Paulescu, Marius & Blaga, Robert & Dughir, Ciprian & Stefu, Nicoleta & Sabadus, Andreea & Calinoiu, Delia & Badescu, Viorel, 2023. "Intra-hour PV power forecasting based on sky imagery," Energy, Elsevier, vol. 279(C).
  15. Ukwuoma, Chiagoziem C. & Cai, Dongsheng & Bamisile, Olusola & Yin, Hongbo & Nneji, Grace Ugochi & Monday, Happy N. & Oluwasanmi, Ariyo & Huang, Qi, 2024. "An attention fused sequence -to-sequence convolutional neural network for accurate solar irradiance forecasting and prediction using sky images," Renewable Energy, Elsevier, vol. 237(PB).
  16. 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).
  17. Askr, Heba & Basha, Sameh H. & Abdelnapi, Noha MM. & Elgeldawi, Enas & Darwish, Ashraf & Hassanien, Aboul Ella, 2025. "Artificial intelligence for sustainable green hydrogen production: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 224(C).
  18. 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).
  19. Wentao Ma & Lihong Qiu & Fengyuan Sun & Sherif S. M. Ghoneim & Jiandong Duan, 2022. "PV Power Forecasting Based on Relevance Vector Machine with Sparrow Search Algorithm Considering Seasonal Distribution and Weather Type," Energies, MDPI, vol. 15(14), pages 1-24, July.
  20. Wang, Yong & Yan, Gaowei & Xiao, Shuyi & Ren, Mifeng & Cheng, Lan & Zhu, Zhujun, 2025. "Day-ahead solar irradiance prediction based on multi-feature perspective clustering," Energy, Elsevier, vol. 320(C).
  21. Luo, Xing & Zhang, Dongxiao & Zhu, Xu, 2022. "Combining transfer learning and constrained long short-term memory for power generation forecasting of newly-constructed photovoltaic plants," Renewable Energy, Elsevier, vol. 185(C), pages 1062-1077.
  22. Chao Gao & Shuai Zhang & Zhiqin Li & Bin Zhou & Dong Guo & Wenqi Shao & Haowen Li, 2025. "Photovoltaic Power Prediction Based on Similar Day Clustering Combined with CNN-GRU," Sustainability, MDPI, vol. 17(16), pages 1-20, August.
  23. Wang, Lu & Yuan, JianJuan & Qiao, Xu & Kong, Xiangfei, 2023. "Optimal rule based double predictive control for the management of thermal energy in a distributed clean heating system," Renewable Energy, Elsevier, vol. 215(C).
  24. Yang, Shaomei & Luo, Yuman, 2025. "Short-term photovoltaic power prediction based on RF-SGMD-GWO-BiLSTM hybrid models," Energy, Elsevier, vol. 316(C).
  25. Rita Teixeira & Adelaide Cerveira & Eduardo J. Solteiro Pires & José Baptista, 2024. "Advancing Renewable Energy Forecasting: A Comprehensive Review of Renewable Energy Forecasting Methods," Energies, MDPI, vol. 17(14), pages 1-30, July.
  26. Zheng, Lingwei & Su, Ran & Sun, Xinyu & Guo, Siqi, 2023. "Historical PV-output characteristic extraction based weather-type classification strategy and its forecasting method for the day-ahead prediction of PV output," Energy, Elsevier, vol. 271(C).
  27. Bintao Wu & Jianlong Hao, 2025. "Enhanced xPatch for Short-Term Photovoltaic Power Forecasting: Supporting Sustainable and Resilient Energy Systems," Sustainability, MDPI, vol. 17(16), pages 1-22, August.
  28. Yang, Yanru & Liu, Yu & Zhang, Yihang & Shu, Shaolong & Zheng, Junsheng, 2025. "DEST-GNN: A double-explored spatio-temporal graph neural network for multi-site intra-hour PV power forecasting," Applied Energy, Elsevier, vol. 378(PA).
  29. 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.
  30. Luo, Xing & Zhang, Dongxiao, 2023. "A cascaded deep learning framework for photovoltaic power forecasting with multi-fidelity inputs," Energy, Elsevier, vol. 268(C).
  31. D'Adamo, Idiano & Mammetti, Marco & Ottaviani, Dario & Ozturk, Ilhan, 2023. "Photovoltaic systems and sustainable communities: New social models for ecological transition. The impact of incentive policies in profitability analyses," Renewable Energy, Elsevier, vol. 202(C), pages 1291-1304.
  32. Rai, Amit & Shrivastava, Ashish & Jana, Kartick C., 2023. "Differential attention net: Multi-directed differential attention based hybrid deep learning model for solar power forecasting," Energy, Elsevier, vol. 263(PC).
  33. Sarmas, Elissaios & Spiliotis, Evangelos & Stamatopoulos, Efstathios & Marinakis, Vangelis & Doukas, Haris, 2023. "Short-term photovoltaic power forecasting using meta-learning and numerical weather prediction independent Long Short-Term Memory models," Renewable Energy, Elsevier, vol. 216(C).
  34. Deng, Feng & Wang, Tianhang & Tao, Wanting & Darkwa, Jo & Li, Yilin, 2025. "A LSTM-model based approach for long-term forecasting of high-rise residential building integrated photovoltaic system," Energy, Elsevier, vol. 338(C).
  35. Zhang, Weiyi & Zhou, Haiyang & Bao, Xiaohua & Cui, Hongzhi, 2023. "Outlet water temperature prediction of energy pile based on spatial-temporal feature extraction through CNN–LSTM hybrid model," Energy, Elsevier, vol. 264(C).
  36. Olexandr Shavolkin & Iryna Shvedchykova & Juraj Gerlici & Kateryna Kravchenko & František Pribilinec, 2022. "Use of Hybrid Photovoltaic Systems with a Storage Battery for the Remote Objects of Railway Transport Infrastructure," Energies, MDPI, vol. 15(13), pages 1-19, July.
  37. Thomas Shering & Eduardo Alonso & Dimitra Apostolopoulou, 2024. "Investigation of Load, Solar and Wind Generation as Target Variables in LSTM Time Series Forecasting, Using Exogenous Weather Variables," Energies, MDPI, vol. 17(8), pages 1-23, April.
  38. Junwei Ma & Min Zhao & Wendong Shen & Zepeng Yang & Xiaokun Yu & Shunfa Lu, 2024. "Photovoltaic Power Prediction Based on NRS-PCC Feature Selection and Multi-Scale CNN-LSTM Network," International Journal of Web Services Research (IJWSR), IGI Global Scientific Publishing, vol. 21(1), pages 1-15, January.
  39. Abhishek Yadav, 2024. "A Comparative Study of Time Series, Machine Learning, and Deep Learning Models for Forecasting Global Price of Wheat," SN Operations Research Forum, Springer, vol. 5(4), pages 1-24, December.
  40. Liu, Zhi-Feng & Chen, Xiao-Rui & Huang, Ya-He & Luo, Xing-Fu & Zhang, Shu-Rui & You, Guo-Dong & Qiang, Xiao-Yong & Kang, Qing, 2024. "A novel bimodal feature fusion network-based deep learning model with intelligent fusion gate mechanism for short-term photovoltaic power point-interval forecasting," Energy, Elsevier, vol. 303(C).
  41. Gong, Jianqiang & Qu, Zhiguo & Zhu, Zhenle & Xu, Hongtao, 2025. "Parallel TimesNet-BiLSTM model for ultra-short-term photovoltaic power forecasting using STL decomposition and auto-tuning," Energy, Elsevier, vol. 320(C).
  42. Wu, Zhiyuan & Fang, Guohua & Ye, Jian & Zhu, David Z. & Huang, Xianfeng, 2025. "A reinforcement learning-based ensemble forecasting framework for renewable energy forecasting," Renewable Energy, Elsevier, vol. 244(C).
  43. 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.
  44. Weihui Xu & Zhaoke Wang & Weishu Wang & Jian Zhao & Miaojia Wang & Qinbao Wang, 2024. "Short-Term Photovoltaic Output Prediction Based on Decomposition and Reconstruction and XGBoost under Two Base Learners," Energies, MDPI, vol. 17(4), pages 1-19, February.
  45. Sabadus, Andreea & Blaga, Robert & Hategan, Sergiu-Mihai & Calinoiu, Delia & Paulescu, Eugenia & Mares, Oana & Boata, Remus & Stefu, Nicoleta & Paulescu, Marius & Badescu, Viorel, 2024. "A cross-sectional survey of deterministic PV power forecasting: Progress and limitations in current approaches," Renewable Energy, Elsevier, vol. 226(C).
  46. Sameer Al-Dahidi & Manoharan Madhiarasan & Loiy Al-Ghussain & Ahmad M. Abubaker & Adnan Darwish Ahmad & Mohammad Alrbai & Mohammadreza Aghaei & Hussein Alahmer & Ali Alahmer & Piero Baraldi & Enrico Z, 2024. "Forecasting Solar Photovoltaic Power Production: A Comprehensive Review and Innovative Data-Driven Modeling Framework," Energies, MDPI, vol. 17(16), pages 1-38, August.
  47. Hongbo Gao & Shuang Qiu & Jun Fang & Nan Ma & Jiye Wang & Kun Cheng & Hui Wang & Yidong Zhu & Dawei Hu & Hengyu Liu & Jun Wang, 2023. "Short-Term Prediction of PV Power Based on Combined Modal Decomposition and NARX-LSTM-LightGBM," Sustainability, MDPI, vol. 15(10), pages 1-22, May.
  48. Miguel López Santos & Xela García-Santiago & Fernando Echevarría Camarero & Gonzalo Blázquez Gil & Pablo Carrasco Ortega, 2022. "Application of Temporal Fusion Transformer for Day-Ahead PV Power Forecasting," Energies, MDPI, vol. 15(14), pages 1-22, July.
  49. Wen, Yan & Pan, Su & Li, Xinxin & Li, Zibo & Wen, Wuzhenghong, 2024. "Improving multi-site photovoltaic forecasting with relevance amplification: DeepFEDformer-based approach," Energy, Elsevier, vol. 299(C).
  50. Zhijian Hou & Yunhui Zhang & Xuemei Cheng & Xiaojiang Ye, 2025. "Photovoltaic Power Forecasting Based on Variational Mode Decomposition and Long Short-Term Memory Neural Network," Energies, MDPI, vol. 18(13), pages 1-28, July.
  51. Lin, Huapeng & Gao, Liyuan & Cui, Mingtao & Liu, Hengchao & Li, Chunyang & Yu, Miao, 2025. "Short-term distributed photovoltaic power prediction based on temporal self-attention mechanism and advanced signal decomposition techniques with feature fusion," Energy, Elsevier, vol. 315(C).
  52. Zhou, Daixuan & Liu, Yujin & Wang, Xu & Wang, Fuxing & Jia, Yan, 2025. "Combined ultra-short-term photovoltaic power prediction based on CEEMDAN decomposition and RIME optimized AM-TCN-BiLSTM," Energy, Elsevier, vol. 318(C).
  53. Putri Nor Liyana Mohamad Radzi & Muhammad Naveed Akhter & Saad Mekhilef & Noraisyah Mohamed Shah, 2023. "Review on the Application of Photovoltaic Forecasting Using Machine Learning for Very Short- to Long-Term Forecasting," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
  54. Zhai, Chao & He, Xinyi & Cao, Zhixiang & Abdou-Tankari, Mahamadou & Wang, Yi & Zhang, Minghao, 2025. "Photovoltaic power forecasting based on VMD-SSA-Transformer: Multidimensional analysis of dataset length, weather mutation and forecast accuracy," Energy, Elsevier, vol. 324(C).
  55. 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).
  56. Verdone, Alessio & Panella, Massimo & De Santis, Enrico & Rizzi, Antonello, 2025. "A review of solar and wind energy forecasting: From single-site to multi-site paradigm," Applied Energy, Elsevier, vol. 392(C).
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