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Short-term solar power prediction using a support vector machine

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  1. Dukhwan Yu & Wonik Choi & Myoungsoo Kim & Ling Liu, 2020. "Forecasting Day-Ahead Hourly Photovoltaic Power Generation Using Convolutional Self-Attention Based Long Short-Term Memory," Energies, MDPI, vol. 13(15), pages 1-17, August.
  2. Veena Raj & Sam-Quarcoo Dotse & Mathew Sathyajith & M. I. Petra & Hayati Yassin, 2023. "Ensemble Machine Learning for Predicting the Power Output from Different Solar Photovoltaic Systems," Energies, MDPI, vol. 16(2), pages 1-15, January.
  3. Terrén-Serrano, G. & Martínez-Ramón, M., 2023. "Kernel learning for intra-hour solar forecasting with infrared sky images and cloud dynamic feature extraction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
  4. Monika Zielińska-Sitkiewicz & Mariola Chrzanowska & Konrad Furmańczyk & Kacper Paczutkowski, 2021. "Analysis of Electricity Consumption in Poland Using Prediction Models and Neural Networks," Energies, MDPI, vol. 14(20), pages 1-21, October.
  5. Lima, Marcello Anderson F.B. & Carvalho, Paulo C.M. & Fernández-Ramírez, Luis M. & Braga, Arthur P.S., 2020. "Improving solar forecasting using Deep Learning and Portfolio Theory integration," Energy, Elsevier, vol. 195(C).
  6. Happy Aprillia & Hong-Tzer Yang & Chao-Ming Huang, 2020. "Short-Term Photovoltaic Power Forecasting Using a Convolutional Neural Network–Salp Swarm Algorithm," Energies, MDPI, vol. 13(8), pages 1-20, April.
  7. Lee, Donghun & Kim, Kwanho, 2021. "PV power prediction in a peak zone using recurrent neural networks in the absence of future meteorological information," Renewable Energy, Elsevier, vol. 173(C), pages 1098-1110.
  8. Salcedo-Sanz, Sancho & Deo, Ravinesh C. & Cornejo-Bueno, Laura & Camacho-Gómez, Carlos & Ghimire, Sujan, 2018. "An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia," Applied Energy, Elsevier, vol. 209(C), pages 79-94.
  9. Gawusu, Sidique & Zhang, Xiaobing & Yakubu, Sufyan & Debrah, Seth Kofi & Das, Oisik & Bundela, Nishant Singh, 2025. "Optimizing solar photovoltaic system performance: Insights and strategies for enhanced efficiency," Energy, Elsevier, vol. 319(C).
  10. Ramedani, Zeynab & Omid, Mahmoud & Keyhani, Alireza & Shamshirband, Shahaboddin & Khoshnevisan, Benyamin, 2014. "Potential of radial basis function based support vector regression for global solar radiation prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1005-1011.
  11. Liu, Huizhou & Han, Qichen & Huang, Mengxing & Huang, Zhong & Feng, Siling, 2025. "Enhanced wind power prediction via adaptive fusion of multi-dimensional spatial graph and global features," Energy, Elsevier, vol. 337(C).
  12. Abu Danish Aiman Bin Abu Sofian & Hooi Ren Lim & Heli Siti Halimatul Munawaroh & Zengling Ma & Kit Wayne Chew & Pau Loke Show, 2024. "Machine learning and the renewable energy revolution: Exploring solar and wind energy solutions for a sustainable future including innovations in energy storage," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(4), pages 3953-3978, August.
  13. Gabriel Mendonça de Paiva & Sergio Pires Pimentel & Bernardo Pinheiro Alvarenga & Enes Gonçalves Marra & Marco Mussetta & Sonia Leva, 2020. "Multiple Site Intraday Solar Irradiance Forecasting by Machine Learning Algorithms: MGGP and MLP Neural Networks," Energies, MDPI, vol. 13(11), pages 1-28, June.
  14. Deo, Ravinesh C. & Wen, Xiaohu & Qi, Feng, 2016. "A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset," Applied Energy, Elsevier, vol. 168(C), pages 568-593.
  15. Pang, Zhihong & Niu, Fuxin & O’Neill, Zheng, 2020. "Solar radiation prediction using recurrent neural network and artificial neural network: A case study with comparisons," Renewable Energy, Elsevier, vol. 156(C), pages 279-289.
  16. M. Sridharan, 2023. "Generalized Regression Neural Network Model Based Estimation of Global Solar Energy Using Meteorological Parameters," Annals of Data Science, Springer, vol. 10(4), pages 1107-1125, August.
  17. Mariz B. Arias & Sungwoo Bae, 2020. "Design Models for Power Flow Management of a Grid-Connected Solar Photovoltaic System with Energy Storage System," Energies, MDPI, vol. 13(9), pages 1-14, April.
  18. Jawed Mustafa & Shahid Husain & Saeed Alqaed & Uzair Ali Khan & Basharat Jamil, 2022. "Performance of Two Variable Machine Learning Models to Forecast Monthly Mean Diffuse Solar Radiation across India under Various Climate Zones," Energies, MDPI, vol. 15(21), pages 1-32, October.
  19. Wang, Yong & He, Xinbo & Zhou, Ying & Luo, Yongxian & Tang, Yanbing & Narayanan, Govindasami, 2024. "A novel structure adaptive grey seasonal model with data reorganization and its application in solar photovoltaic power generation prediction," Energy, Elsevier, vol. 302(C).
  20. Aurelia Rybak & Aleksandra Rybak & Jarosław Joostberens & Spas D. Kolev, 2025. "Assessment of the Impact of Renewable Energy Sources and Clean Coal Technologies on the Stability of Energy Systems in Poland and Sweden," Energies, MDPI, vol. 18(16), pages 1-21, August.
  21. Chu, Yinghao & Li, Mengying & Pedro, Hugo T.C. & Coimbra, Carlos F.M., 2015. "Real-time prediction intervals for intra-hour DNI forecasts," Renewable Energy, Elsevier, vol. 83(C), pages 234-244.
  22. 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.
  23. Yao, Wanxiang & Zhang, Chunxiao & Hao, Haodong & Wang, Xiao & Li, Xianli, 2018. "A support vector machine approach to estimate global solar radiation with the influence of fog and haze," Renewable Energy, Elsevier, vol. 128(PA), pages 155-162.
  24. Santamaría-Bonfil, G. & Reyes-Ballesteros, A. & Gershenson, C., 2016. "Wind speed forecasting for wind farms: A method based on support vector regression," Renewable Energy, Elsevier, vol. 85(C), pages 790-809.
  25. Aneela Zameer & Fatima Jaffar & Farah Shahid & Muhammad Muneeb & Rizwan Khan & Rubina Nasir, 2023. "Short-term solar energy forecasting: Integrated computational intelligence of LSTMs and GRU," PLOS ONE, Public Library of Science, vol. 18(10), pages 1-25, October.
  26. 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).
  27. 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.
  28. Syed Saqib Ali & Mazhar Ali & Dost Muhammad Saqib Bhatti & Bong Jun Choi, 2025. "Explainable Clustered Federated Learning for Solar Energy Forecasting," Energies, MDPI, vol. 18(9), pages 1-19, May.
  29. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
  30. De Felice, Matteo & Petitta, Marcello & Ruti, Paolo M., 2015. "Short-term predictability of photovoltaic production over Italy," Renewable Energy, Elsevier, vol. 80(C), pages 197-204.
  31. 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).
  32. Aurelia Rybak & Aleksandra Rybak & Spas D. Kolev, 2023. "Modeling the Photovoltaic Power Generation in Poland in the Light of PEP2040: An Application of Multiple Regression," Energies, MDPI, vol. 16(22), pages 1-17, November.
  33. Chenhua Ni & Xiandong Ma, 2018. "Prediction of Wave Power Generation Using a Convolutional Neural Network with Multiple Inputs," Energies, MDPI, vol. 11(8), pages 1-18, August.
  34. Hocaoglu, Fatih Onur & Serttas, Fatih, 2017. "A novel hybrid (Mycielski-Markov) model for hourly solar radiation forecasting," Renewable Energy, Elsevier, vol. 108(C), pages 635-643.
  35. Chia-Sheng Tu & Chih-Ming Hong & Hsi-Shan Huang & Chiung-Hsing Chen, 2020. "Short Term Wind Power Prediction Based on Data Regression and Enhanced Support Vector Machine," Energies, MDPI, vol. 13(23), pages 1-18, November.
  36. Mashud Rana & Irena Koprinska, 2016. "Neural Network Ensemble Based Approach for 2D-Interval Prediction of Solar Photovoltaic Power," Energies, MDPI, vol. 9(10), pages 1-17, October.
  37. Paiho, Satu & Kiljander, Jussi & Sarala, Roope & Siikavirta, Hanne & Kilkki, Olli & Bajpai, Arpit & Duchon, Markus & Pahl, Marc-Oliver & Wüstrich, Lars & Lübben, Christian & Kirdan, Erkin & Schindler,, 2021. "Towards cross-commodity energy-sharing communities – A review of the market, regulatory, and technical situation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
  38. Nieto, P.J. García & Fernández, J.R. Alonso & Suárez, V.M. González & Muñiz, C. Díaz & García-Gonzalo, E. & Bayón, R. Mayo, 2015. "A hybrid PSO optimized SVM-based method for predicting of the cyanotoxin content from experimental cyanobacteria concentrations in the Trasona reservoir: A case study in Northern Spain," Applied Mathematics and Computation, Elsevier, vol. 260(C), pages 170-187.
  39. Na Sun & Nan Zhang & Shuai Zhang & Tian Peng & Wei Jiang & Jie Ji & Xiangmiao Hao, 2022. "An Integrated Framework Based on an Improved Gaussian Process Regression and Decomposition Technique for Hourly Solar Radiation Forecasting," Sustainability, MDPI, vol. 14(22), pages 1-22, November.
  40. 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.
  41. Sharma, Amandeep & Kakkar, Ajay, 2018. "Forecasting daily global solar irradiance generation using machine learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2254-2269.
  42. García Nieto, P.J. & García-Gonzalo, E. & Sánchez Lasheras, F. & de Cos Juez, F.J., 2015. "Hybrid PSO–SVM-based method for forecasting of the remaining useful life for aircraft engines and evaluation of its reliability," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 219-231.
  43. Dewangan, Chaman Lal & Singh, S.N. & Chakrabarti, S., 2020. "Combining forecasts of day-ahead solar power," Energy, Elsevier, vol. 202(C).
  44. Omid Rahbari & Noshin Omar & Joeri Van Mierlo & Marc A. Rosen & Thierry Coosemans & Maitane Berecibar, 2019. "Electric Vehicle Battery Lifetime Extension through an Intelligent Double-Layer Control Scheme," Energies, MDPI, vol. 12(8), pages 1-24, April.
  45. Lei Fu & Yiling Yang & Xiaolong Yao & Xufen Jiao & Tiantian Zhu, 2019. "A Regional Photovoltaic Output Prediction Method Based on Hierarchical Clustering and the mRMR Criterion," Energies, MDPI, vol. 12(20), pages 1-23, October.
  46. Teke, Ahmet & Yıldırım, H. Başak & Çelik, Özgür, 2015. "Evaluation and performance comparison of different models for the estimation of solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1097-1107.
  47. Raghu Raman & Sangeetha Gunasekar & Deepa Kaliyaperumal & Prema Nedungadi, 2024. "Navigating the Nexus of Artificial Intelligence and Renewable Energy for the Advancement of Sustainable Development Goals," Sustainability, MDPI, vol. 16(21), pages 1-25, October.
  48. Zeng, Tao & Zhang, Caizhi & Hao, Dong & Cao, Dongpu & Chen, Jiawei & Chen, Jinrui & Li, Jin, 2020. "Data-driven approach for short-term power demand prediction of fuel cell hybrid vehicles," Energy, Elsevier, vol. 208(C).
  49. 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).
  50. Xiaomin Xu & Dongxiao Niu & Ming Fu & Huicong Xia & Han Wu, 2015. "A Multi Time Scale Wind Power Forecasting Model of a Chaotic Echo State Network Based on a Hybrid Algorithm of Particle Swarm Optimization and Tabu Search," Energies, MDPI, vol. 8(11), pages 1-21, November.
  51. Fatemi, Seyyed A. & Kuh, Anthony & Fripp, Matthias, 2016. "Online and batch methods for solar radiation forecast under asymmetric cost functions," Renewable Energy, Elsevier, vol. 91(C), pages 397-408.
  52. Samu, Remember & Calais, Martina & Shafiullah, G.M. & Moghbel, Moayed & Shoeb, Md Asaduzzaman & Nouri, Bijan & Blum, Niklas, 2021. "Applications for solar irradiance nowcasting in the control of microgrids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
  53. Chao-Rong Chen & Unit Three Kartini, 2017. "k-Nearest Neighbor Neural Network Models for Very Short-Term Global Solar Irradiance Forecasting Based on Meteorological Data," Energies, MDPI, vol. 10(2), pages 1-18, February.
  54. Fatemi, Seyyed A. & Kuh, Anthony & Fripp, Matthias, 2018. "Parametric methods for probabilistic forecasting of solar irradiance," Renewable Energy, Elsevier, vol. 129(PA), pages 666-676.
  55. García Nieto, P.J. & García-Gonzalo, E. & Alonso Fernández, J.R. & Díaz Muñiz, C., 2019. "Water eutrophication assessment relied on various machine learning techniques: A case study in the Englishmen Lake (Northern Spain)," Ecological Modelling, Elsevier, vol. 404(C), pages 91-102.
  56. Vera Wendler-Bosco & Charles Nicholson, 2022. "Modeling the economic impact of incoming tropical cyclones using machine learning," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(1), pages 487-518, January.
  57. Ghimire, Sujan & Deo, Ravinesh C. & Raj, Nawin & Mi, Jianchun, 2019. "Wavelet-based 3-phase hybrid SVR model trained with satellite-derived predictors, particle swarm optimization and maximum overlap discrete wavelet transform for solar radiation prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
  58. Mariz B. Arias & Sungwoo Bae, 2021. "Solar Photovoltaic Power Prediction Using Big Data Tools," Sustainability, MDPI, vol. 13(24), pages 1-19, December.
  59. Trigo-González, Mauricio & Cortés-Carmona, Marcelo & Marzo, Aitor & Alonso-Montesinos, Joaquín & Martínez-Durbán, Mercedes & López, Gabriel & Portillo, Carlos & Batlles, Francisco Javier, 2023. "Photovoltaic power electricity generation nowcasting combining sky camera images and learning supervised algorithms in the Southern Spain," Renewable Energy, Elsevier, vol. 206(C), pages 251-262.
  60. Mohammad Rezaie-Balf & Niloofar Maleki & Sungwon Kim & Ali Ashrafian & Fatemeh Babaie-Miri & Nam Won Kim & Il-Moon Chung & Sina Alaghmand, 2019. "Forecasting Daily Solar Radiation Using CEEMDAN Decomposition-Based MARS Model Trained by Crow Search Algorithm," Energies, MDPI, vol. 12(8), pages 1-23, April.
  61. Mohammed Asloune & Gilles Notton & Cyril Voyant, 2025. "From Trends to Insights: A Text Mining Analysis of Solar Energy Forecasting (2017–2023)," Energies, MDPI, vol. 18(19), pages 1-30, October.
  62. Zheng, Jianqin & Zhang, Haoran & Dai, Yuanhao & Wang, Bohong & Zheng, Taicheng & Liao, Qi & Liang, Yongtu & Zhang, Fengwei & Song, Xuan, 2020. "Time series prediction for output of multi-region solar power plants," Applied Energy, Elsevier, vol. 257(C).
  63. Mandal, Dipak Kumar & Gupta, Kritesh Kumar & Biswas, Nirmalendu & Manna, Nirmal K. & Santra, Somnath & Benim, Ali Cemal, 2025. "Optimization of hybrid solar chimney power plants (HSCPPs): A review of multi-objective approaches," Applied Energy, Elsevier, vol. 396(C).
  64. Kim, Jimin & Obregon, Josue & Park, Hoonseok & Jung, Jae-Yoon, 2024. "Multi-step photovoltaic power forecasting using transformer and recurrent neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 200(C).
  65. Arsalan Masood & Ubaid Ahmed & Syed Zulqadar Hassan & Ahsan Raza Khan & Anzar Mahmood, 2025. "Economic Value Creation of Artificial Intelligence in Supporting Variable Renewable Energy Resource Integration to Power Systems: A Systematic Review," Sustainability, MDPI, vol. 17(6), pages 1-42, March.
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