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Improved solar photovoltaic energy generation forecast using deep learning-based ensemble stacking approach

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  1. Zhang, Chu & Hu, Haowen & Ji, Jie & Liu, Kang & Xia, Xin & Nazir, Muhammad Shahzad & Peng, Tian, 2023. "An evolutionary stacked generalization model based on deep learning and improved grasshopper optimization algorithm for predicting the remaining useful life of PEMFC," Applied Energy, Elsevier, vol. 330(PA).
  2. Ganapathy Ramesh & Jaganathan Logeshwaran & Thangavel Kiruthiga & Jaime Lloret, 2023. "Prediction of Energy Production Level in Large PV Plants through AUTO-Encoder Based Neural-Network (AUTO-NN) with Restricted Boltzmann Feature Extraction," Future Internet, MDPI, vol. 15(2), pages 1-20, January.
  3. Vladimir Franki & Darin Majnarić & Alfredo Višković, 2023. "A Comprehensive Review of Artificial Intelligence (AI) Companies in the Power Sector," Energies, MDPI, vol. 16(3), pages 1-35, January.
  4. Tserenpurev Chuluunsaikhan & Jeong-Hun Kim & Yoonsung Shin & Sanghyun Choi & Aziz Nasridinov, 2022. "Feasibility Study on the Influence of Data Partition Strategies on Ensemble Deep Learning: The Case of Forecasting Power Generation in South Korea," Energies, MDPI, vol. 15(20), pages 1-20, October.
  5. Zhu, Jiebei & Li, Mingrui & Luo, Lin & Zhang, Bidan & Cui, Mingjian & Yu, Lujie, 2023. "Short-term PV power forecast methodology based on multi-scale fluctuation characteristics extraction," Renewable Energy, Elsevier, vol. 208(C), pages 141-151.
  6. Konduru Sudharshan & C. Naveen & Pradeep Vishnuram & Damodhara Venkata Siva Krishna Rao Kasagani & Benedetto Nastasi, 2022. "Systematic Review on Impact of Different Irradiance Forecasting Techniques for Solar Energy Prediction," Energies, MDPI, vol. 15(17), pages 1-39, August.
  7. Rotaru Cătălin-Laurențiu & Timiş Diana & Grădinaru Giani-Ionel, 2023. "Efficient Capture of Solar Energy in Romania: Approach in Territorial Profile Using Predictive Statistical Techniques," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 17(1), pages 1519-1533, July.
  8. Khan, Waqas & Somers, Ward & Walker, Shalika & de Bont, Kevin & Van der Velden, Joep & Zeiler, Wim, 2023. "Comparison of electric vehicle load forecasting across different spatial levels with incorporated uncertainty estimation," Energy, Elsevier, vol. 283(C).
  9. Sergio Cantillo-Luna & Ricardo Moreno-Chuquen & David Celeita & George Anders, 2023. "Deep and Machine Learning Models to Forecast Photovoltaic Power Generation," Energies, MDPI, vol. 16(10), pages 1-24, May.
  10. Hui Wang & Su Yan & Danyang Ju & Nan Ma & Jun Fang & Song Wang & Haijun Li & Tianyu Zhang & Yipeng Xie & Jun Wang, 2023. "Short-Term Photovoltaic Power Forecasting Based on a Feature Rise-Dimensional Two-Layer Ensemble Learning Model," Sustainability, MDPI, vol. 15(21), pages 1-26, November.
  11. Knolmajer, Attila & Bálint, Roland & Fodor, Attila & Vathy-Fogarassy, Ágnes, 2024. "Quaternion-based irradiance calculation method applicable to solar power plants energy production," Energy, Elsevier, vol. 309(C).
  12. Zhang, Meijuan & Yan, Qingyou & Guan, Yajuan & Ni, Da & Agundis Tinajero, Gibran David, 2024. "Joint planning of residential electric vehicle charging station integrated with photovoltaic and energy storage considering demand response and uncertainties," Energy, Elsevier, vol. 298(C).
  13. 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.
  14. Ashok Bhansali & Namala Narasimhulu & Rocío Pérez de Prado & Parameshachari Bidare Divakarachari & Dayanand Lal Narayan, 2023. "A Review on Sustainable Energy Sources Using Machine Learning and Deep Learning Models," Energies, MDPI, vol. 16(17), pages 1-18, August.
  15. 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).
  16. Zhang, Jinlai & Yang, Wenjie & Chen, Yumei & Ding, Mingkang & Huang, Huiling & Wang, Bingkun & Gao, Kai & Chen, Shuhan & Du, Ronghua, 2024. "Fast object detection of anomaly photovoltaic (PV) cells using deep neural networks," Applied Energy, Elsevier, vol. 372(C).
  17. 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).
  18. Mondal, Rakesh & Roy, Surajit Kr & Giri, Chandan, 2024. "Solar power forecasting using domain knowledge," Energy, Elsevier, vol. 302(C).
  19. Udenze, Peter I. & Gong, Jiaqi & Soltani, Shohreh & Li, Dawen, 2025. "A deep neural network with two-step decomposition technique for predicting ultra-short-term solar power and electrical load," Applied Energy, Elsevier, vol. 382(C).
  20. Amini Toosi, Hashem & Del Pero, Claudio & Leonforte, Fabrizio & Lavagna, Monica & Aste, Niccolò, 2023. "Machine learning for performance prediction in smart buildings: Photovoltaic self-consumption and life cycle cost optimization," Applied Energy, Elsevier, vol. 334(C).
  21. 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).
  22. Yue Yu & Jiahui Guo & Zhaoyang Jin, 2023. "Optimal Extreme Random Forest Ensemble for Active Distribution Network Forecasting-Aided State Estimation Based on Maximum Average Energy Concentration VMD State Decomposition," Energies, MDPI, vol. 16(15), pages 1-25, July.
  23. Jose Cruz & Christian Romero & Oscar Vera & Saul Huaquipaco & Norman Beltran & Wilson Mamani, 2023. "Multiparameter Regression of a Photovoltaic System by Applying Hybrid Methods with Variable Selection and Stacking Ensembles under Extreme Conditions of Altitudes Higher than 3800 Meters above Sea Lev," Energies, MDPI, vol. 16(12), pages 1-21, June.
  24. 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.
  25. Pei, Jingyin & Dong, Yunxuan & Guo, Pinghui & Wu, Thomas & Hu, Jianming, 2024. "A Hybrid Dual Stream ProbSparse Self-Attention Network for spatial–temporal photovoltaic power forecasting," Energy, Elsevier, vol. 305(C).
  26. Jeongin Lee & Jongwoo Choi & Wanki Park & Ilwoo Lee, 2023. "A Dual-Stage Solar Power Prediction Model That Reflects Uncertainties in Weather Forecasts," Energies, MDPI, vol. 16(21), pages 1-19, October.
  27. Yin, Linfei & Lin, Chen, 2024. "Matrix Wasserstein distance generative adversarial network with gradient penalty for fast low-carbon economic dispatch of novel power systems," Energy, Elsevier, vol. 298(C).
  28. Wang, Yong & Yang, Zhongsen & Zhou, Ying & Liu, Hao & Yang, Rui & Sun, Lang & Sapnken, Flavian Emmanuel & Narayanan, Govindasami, 2025. "A novel structure adaptive new information priority grey Bernoulli model and its application in China's renewable energy production," Renewable Energy, Elsevier, vol. 239(C).
  29. Abdallah Abdellatif & Hamza Mubarak & Shameem Ahmad & Tofael Ahmed & G. M. Shafiullah & Ahmad Hammoudeh & Hamdan Abdellatef & M. M. Rahman & Hassan Muwafaq Gheni, 2022. "Forecasting Photovoltaic Power Generation with a Stacking Ensemble Model," Sustainability, MDPI, vol. 14(17), pages 1-21, September.
  30. 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).
  31. 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.
  32. Bowen Zhou & Xinyu Chen & Guangdi Li & Peng Gu & Jing Huang & Bo Yang, 2023. "XGBoost–SFS and Double Nested Stacking Ensemble Model for Photovoltaic Power Forecasting under Variable Weather Conditions," Sustainability, MDPI, vol. 15(17), pages 1-24, September.
  33. Hamza Mubarak & Mohammad J. Sanjari & Sascha Stegen & Abdallah Abdellatif, 2023. "Improved Active and Reactive Energy Forecasting Using a Stacking Ensemble Approach: Steel Industry Case Study," Energies, MDPI, vol. 16(21), pages 1-32, October.
  34. Li, Peidu & Luo, Yong & Xia, Xin & Gao, Xiaoqing & Chang, Rui & Li, Zhenchao & Zheng, Junqing & Shi, Wen & Liao, Zhouyi, 2024. "Factors and quantitative impact on electrical yield in fishery complementary photovoltaic power plant under different cloud cover conditions," Energy, Elsevier, vol. 309(C).
  35. 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).
  36. Nunes Maciel, Joylan & Javier Gimenez Ledesma, Jorge & Hideo Ando Junior, Oswaldo, 2024. "Hybrid prediction method of solar irradiance applied to short-term photovoltaic energy generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
  37. Linh Bui Duy & Ninh Nguyen Quang & Binh Doan Van & Eleonora Riva Sanseverino & Quynh Tran Thi Tu & Hang Le Thi Thuy & Sang Le Quang & Thinh Le Cong & Huyen Cu Thi Thanh, 2024. "Refining Long Short-Term Memory Neural Network Input Parameters for Enhanced Solar Power Forecasting," Energies, MDPI, vol. 17(16), pages 1-22, August.
  38. Rosen, Karol & Angeles-Camacho, César & Elvira, Víctor & Guillén-Burguete, Servio Tulio, 2023. "Intra-hour photovoltaic forecasting through a time-varying Markov switching model," Energy, Elsevier, vol. 278(PB).
  39. Leijiao Ge & Tianshuo Du & Changlu Li & Yuanliang Li & Jun Yan & Muhammad Umer Rafiq, 2022. "Virtual Collection for Distributed Photovoltaic Data: Challenges, Methodologies, and Applications," Energies, MDPI, vol. 15(23), pages 1-24, November.
  40. Pachauri, Nikhil & Ahn, Chang Wook, 2023. "Weighted aggregated ensemble model for energy demand management of buildings," Energy, Elsevier, vol. 263(PC).
  41. Xia, Lin & Ren, Youyang & Wang, Yuhong & Fu, Yiyang & zhou, Ke, 2024. "A novel dynamic structural adaptive multivariable grey model and its application in China's solar energy generation forecasting," Energy, Elsevier, vol. 312(C).
  42. Xin Ma & Yubin Cai & Hong Yuan & Yanqiao Deng, 2023. "Partially Linear Component Support Vector Machine for Primary Energy Consumption Forecasting of the Electric Power Sector in the United States," Sustainability, MDPI, vol. 15(9), pages 1-26, April.
  43. Kabulo Loji & Sachin Sharma & Nomhle Loji & Gulshan Sharma & Pitshou N. Bokoro, 2023. "Operational Issues of Contemporary Distribution Systems: A Review on Recent and Emerging Concerns," Energies, MDPI, vol. 16(4), pages 1-21, February.
  44. Liu, Bingchun & Huo, Xiankai, 2024. "Prediction of Photovoltaic power generation and analyzing of carbon emission reduction capacity in China," Renewable Energy, Elsevier, vol. 222(C).
  45. Yasemin Ayaz Atalan & Abdulkadir Atalan, 2023. "Integration of the Machine Learning Algorithms and I-MR Statistical Process Control for Solar Energy," Sustainability, MDPI, vol. 15(18), pages 1-20, September.
  46. Raeesi, Ramin & Sahebjamnia, Navid & Mansouri, S. Afshin, 2023. "The synergistic effect of operational research and big data analytics in greening container terminal operations: A review and future directions," European Journal of Operational Research, Elsevier, vol. 310(3), pages 943-973.
  47. Liu, Bingchun & Song, Jiangji & Wang, Qingshan & Xu, Yan & Liu, Yifan, 2023. "Charging station forecasting and scenario analysis in China," Transport Policy, Elsevier, vol. 139(C), pages 87-98.
  48. Yifei Chen & Zhihan Fu, 2023. "Multi-Step Ahead Forecasting of the Energy Consumed by the Residential and Commercial Sectors in the United States Based on a Hybrid CNN-BiLSTM Model," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
  49. Khan, Waqas & Liao, Juo Yu & Walker, Shalika & Zeiler, Wim, 2022. "Impact assessment of varied data granularities from commercial buildings on exploration and learning mechanism," Applied Energy, Elsevier, vol. 319(C).
  50. Zhenyuan Zhuang & Huaizhi Wang & Cilong Yu, 2025. "Prediction of Short-Term Solar Irradiance Using the ProbSparse Attention Mechanism for a Sustainable Energy Development Strategy," Sustainability, MDPI, vol. 17(3), pages 1-21, January.
  51. 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.
  52. Neshat, Mehdi & Sergiienko, Nataliia Y. & Rafiee, Ashkan & Mirjalili, Seyedali & Gandomi, Amir H. & Boland, John, 2024. "MetaWave Learner: Predicting wave farms power output using effective meta-learner deep gradient boosting model: A case study from Australian coasts," Energy, Elsevier, vol. 304(C).
  53. Yukta Mehta & Vincent Lo & Vijen Mehta & Kunal Agrawal & Charan Teja Madabathula & Eugene Chang & Jerry Gao, 2025. "Renewable Electricity Management Cloud System for Smart Communities Using Advanced Machine Learning," Energies, MDPI, vol. 18(6), pages 1-29, March.
  54. Shi, Jiaqi & Li, Chenxi & Yan, Xiaohe, 2023. "Artificial intelligence for load forecasting: A stacking learning approach based on ensemble diversity regularization," Energy, Elsevier, vol. 262(PB).
  55. Zhang, Qiongfang & Yan, Hao & Liu, Yongming, 2024. "Power generation forecasting for solar plants based on Dynamic Bayesian networks by fusing multi-source information," Renewable and Sustainable Energy Reviews, Elsevier, vol. 202(C).
  56. Xiao, Yulong & Zou, Chongzhe & Chi, Hetian & Fang, Rengcun, 2023. "Boosted GRU model for short-term forecasting of wind power with feature-weighted principal component analysis," Energy, Elsevier, vol. 267(C).
  57. Ghaemi, Ali & Safari, Amin & Quteishat, Anas & Younis, Mahmoud A., 2024. "A stacking-based fault forecasting study for power transmission lines under different weather conditions," Energy, Elsevier, vol. 306(C).
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