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Machine learning methods for solar radiation forecasting: A review

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  1. Duchaud, Jean-Laurent & Notton, Gilles & Fouilloy, Alexis & Voyant, Cyril, 2019. "Hybrid renewable power plant sizing – Graphical decision tool, sensitivity analysis and applications in Ajaccio and Tilos," Applied Energy, Elsevier, vol. 254(C).
  2. Adel Alblawi & M. H. Elkholy & M. Talaat, 2019. "ANN for Assessment of Energy Consumption of 4 kW PV Modules over a Year Considering the Impacts of Temperature and Irradiance," Sustainability, MDPI, vol. 11(23), pages 1-24, November.
  3. Marchesoni-Acland, Franco & Alonso-Suárez, Rodrigo, 2020. "Intra-day solar irradiation forecast using RLS filters and satellite images," Renewable Energy, Elsevier, vol. 161(C), pages 1140-1154.
  4. Guosheng Duan & Lifeng Wu & Fa Liu & Yicheng Wang & Shaofei Wu, 2022. "Improvement in Solar-Radiation Forecasting Based on Evolutionary KNEA Method and Numerical Weather Prediction," Sustainability, MDPI, vol. 14(11), pages 1-20, June.
  5. Liang Gong & Fei Huang & Wei Zhang & Yanming Li & Chengliang Liu, 2023. "Precise Short-Term Small-Area Sunshine Forecasting for Optimal Seedbed Scheduling in Plant Factories," Agriculture, MDPI, vol. 13(9), pages 1-19, September.
  6. Voyant, Cyril & Motte, Fabrice & Notton, Gilles & Fouilloy, Alexis & Nivet, Marie-Laure & Duchaud, Jean-Laurent, 2018. "Prediction intervals for global solar irradiation forecasting using regression trees methods," Renewable Energy, Elsevier, vol. 126(C), pages 332-340.
  7. Mehmood, Faiza & Ghani, Muhammad Usman & Asim, Muhammad Nabeel & Shahzadi, Rehab & Mehmood, Aamir & Mahmood, Waqar, 2021. "MPF-Net: A computational multi-regional solar power forecasting framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
  8. Trigo-González, Mauricio & Batlles, F.J. & Alonso-Montesinos, Joaquín & Ferrada, Pablo & del Sagrado, J. & Martínez-Durbán, M. & Cortés, Marcelo & Portillo, Carlos & Marzo, Aitor, 2019. "Hourly PV production estimation by means of an exportable multiple linear regression model," Renewable Energy, Elsevier, vol. 135(C), pages 303-312.
  9. Cheng, Hsu-Yung & Yu, Chih-Chang & Lin, Chih-Lung, 2021. "Day-ahead to week-ahead solar irradiance prediction using convolutional long short-term memory networks," Renewable Energy, Elsevier, vol. 179(C), pages 2300-2308.
  10. Miriam Steurer & Robert Hill, 2019. "Metrics for Evaluating the Performance of Automated Valuation Models," Graz Economics Papers 2019-02, University of Graz, Department of Economics.
  11. Pedro, Hugo T.C. & Lim, Edwin & Coimbra, Carlos F.M., 2018. "A database infrastructure to implement real-time solar and wind power generation intra-hour forecasts," Renewable Energy, Elsevier, vol. 123(C), pages 513-525.
  12. Liu, Fa & Wang, Xunming & Sun, Fubao & Wang, Hong, 2022. "Correct and remap solar radiation and photovoltaic power in China based on machine learning models," Applied Energy, Elsevier, vol. 312(C).
  13. Chun-Wei Chen, 2023. "A Feasibility Discussion: Is ML Suitable for Predicting Sustainable Patterns in Consumer Product Preferences?," Sustainability, MDPI, vol. 15(5), pages 1-21, February.
  14. 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).
  15. Kaba, Kazım & Sarıgül, Mehmet & Avcı, Mutlu & Kandırmaz, H. Mustafa, 2018. "Estimation of daily global solar radiation using deep learning model," Energy, Elsevier, vol. 162(C), pages 126-135.
  16. Alessandro Niccolai & Seyedamir Orooji & Andrea Matteri & Emanuele Ogliari & Sonia Leva, 2022. "Irradiance Nowcasting by Means of Deep-Learning Analysis of Infrared Images," Forecasting, MDPI, vol. 4(1), pages 1-11, March.
  17. Sabarathinam Srinivasan & Suresh Kumarasamy & Zacharias E. Andreadakis & Pedro G. Lind, 2023. "Artificial Intelligence and Mathematical Models of Power Grids Driven by Renewable Energy Sources: A Survey," Energies, MDPI, vol. 16(14), pages 1-56, July.
  18. Miguel Ángel Rodríguez López & Diego Rodríguez Rodríguez, 2024. "La aplicación de datos masivos en economía de la energía: una revisión," Working Papers 2024-08, FEDEA.
  19. Jesús Ferrero Bermejo & Juan Francisco Gómez Fernández & Rafael Pino & Adolfo Crespo Márquez & Antonio Jesús Guillén López, 2019. "Review and Comparison of Intelligent Optimization Modelling Techniques for Energy Forecasting and Condition-Based Maintenance in PV Plants," Energies, MDPI, vol. 12(21), pages 1-18, October.
  20. Hasna Hissou & Said Benkirane & Azidine Guezzaz & Mourade Azrour & Abderrahim Beni-Hssane, 2023. "A Novel Machine Learning Approach for Solar Radiation Estimation," Sustainability, MDPI, vol. 15(13), pages 1-21, July.
  21. Seul-Gi Kim & Jae-Yoon Jung & Min Kyu Sim, 2019. "A Two-Step Approach to Solar Power Generation Prediction Based on Weather Data Using Machine Learning," Sustainability, MDPI, vol. 11(5), pages 1-16, March.
  22. Fan, Junliang & Wu, Lifeng & Zhang, Fucang & Cai, Huanjie & Wang, Xiukang & Lu, Xianghui & Xiang, Youzhen, 2018. "Evaluating the effect of air pollution on global and diffuse solar radiation prediction using support vector machine modeling based on sunshine duration and air temperature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 732-747.
  23. Chibuzor N. Obiora & Ali N. Hasan & Ahmed Ali, 2023. "Predicting Solar Irradiance at Several Time Horizons Using Machine Learning Algorithms," Sustainability, MDPI, vol. 15(11), pages 1-17, June.
  24. 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.
  25. Javier Huertas Tato & Miguel Centeno Brito, 2018. "Using Smart Persistence and Random Forests to Predict Photovoltaic Energy Production," Energies, MDPI, vol. 12(1), pages 1-12, December.
  26. 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.
  27. Shab Gbémou & Julien Eynard & Stéphane Thil & Emmanuel Guillot & Stéphane Grieu, 2021. "A Comparative Study of Machine Learning-Based Methods for Global Horizontal Irradiance Forecasting," Energies, MDPI, vol. 14(11), pages 1-23, May.
  28. Ozoegwu, Chigbogu G. & Akpan, Patrick U., 2021. "A review and appraisal of Nigeria's solar energy policy objectives and strategies against the backdrop of the renewable energy policy of the Economic Community of West African States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
  29. Chen, Qi & Li, Xinyuan & Zhang, Zhengjia & Zhou, Chao & Guo, Zhiling & Liu, Zhengguang & Zhang, Haoran, 2023. "Remote sensing of photovoltaic scenarios: Techniques, applications and future directions," Applied Energy, Elsevier, vol. 333(C).
  30. 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.
  31. Agga, Ali & Abbou, Ahmed & Labbadi, Moussa & El Houm, Yassine, 2021. "Short-term self consumption PV plant power production forecasts based on hybrid CNN-LSTM, ConvLSTM models," Renewable Energy, Elsevier, vol. 177(C), pages 101-112.
  32. Dania Ortiz & Vera Migueis & Vitor Leal & Janelle Knox-Hayes & Jungwoo Chun, 2022. "Analysis of Renewable Energy Policies through Decision Trees," Sustainability, MDPI, vol. 14(13), pages 1-31, June.
  33. Mousavi, Navid & Kothapalli, Ganesh & Habibi, Daryoush & Das, Choton K. & Baniasadi, Ali, 2020. "A novel photovoltaic-pumped hydro storage microgrid applicable to rural areas," Applied Energy, Elsevier, vol. 262(C).
  34. Hassan, Muhammed A. & Al-Ghussain, Loiy & Ahmad, Adnan Darwish & Abubaker, Ahmad M. & Khalil, Adel, 2022. "Aggregated independent forecasters of half-hourly global horizontal irradiance," Renewable Energy, Elsevier, vol. 181(C), pages 365-383.
  35. 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).
  36. Pedregal, Diego J. & Trapero, Juan R., 2021. "Adjusted combination of moving averages: A forecasting system for medium-term solar irradiance," Applied Energy, Elsevier, vol. 298(C).
  37. Nie, Yuhao & Li, Xiatong & Paletta, Quentin & Aragon, Max & Scott, Andea & Brandt, Adam, 2024. "Open-source sky image datasets for solar forecasting with deep learning: A comprehensive survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
  38. Byung-ki Jeon & Eui-Jong Kim, 2020. "Next-Day Prediction of Hourly Solar Irradiance Using Local Weather Forecasts and LSTM Trained with Non-Local Data," Energies, MDPI, vol. 13(20), pages 1-16, October.
  39. Bazine, Hasnaa & Mabrouki, Mustapha, 2019. "Chaotic dynamics applied in time prediction of photovoltaic production," Renewable Energy, Elsevier, vol. 136(C), pages 1255-1265.
  40. Jebli, Imane & Belouadha, Fatima-Zahra & Kabbaj, Mohammed Issam & Tilioua, Amine, 2021. "Prediction of solar energy guided by pearson correlation using machine learning," Energy, Elsevier, vol. 224(C).
  41. Gao, Bixuan & Huang, Xiaoqiao & Shi, Junsheng & Tai, Yonghang & Zhang, Jun, 2020. "Hourly forecasting of solar irradiance based on CEEMDAN and multi-strategy CNN-LSTM neural networks," Renewable Energy, Elsevier, vol. 162(C), pages 1665-1683.
  42. Guijo-Rubio, D. & Durán-Rosal, A.M. & Gutiérrez, P.A. & Gómez-Orellana, A.M. & Casanova-Mateo, C. & Sanz-Justo, J. & Salcedo-Sanz, S. & Hervás-Martínez, C., 2020. "Evolutionary artificial neural networks for accurate solar radiation prediction," Energy, Elsevier, vol. 210(C).
  43. Hanany Tolba & Nouha Dkhili & Julien Nou & Julien Eynard & Stéphane Thil & Stéphane Grieu, 2020. "Multi-Horizon Forecasting of Global Horizontal Irradiance Using Online Gaussian Process Regression: A Kernel Study," Energies, MDPI, vol. 13(16), pages 1-23, August.
  44. 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.
  45. 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.
  46. Victor Hugo Wentz & Joylan Nunes Maciel & Jorge Javier Gimenez Ledesma & Oswaldo Hideo Ando Junior, 2022. "Solar Irradiance Forecasting to Short-Term PV Power: Accuracy Comparison of ANN and LSTM Models," Energies, MDPI, vol. 15(7), pages 1-23, March.
  47. Gao, Datong & Zhao, Bin & Kwan, Trevor Hocksun & Hao, Yong & Pei, Gang, 2022. "The spatial and temporal mismatch phenomenon in solar space heating applications: status and solutions," Applied Energy, Elsevier, vol. 321(C).
  48. Stephan Schlüter & Fabian Menz & Milena Kojić & Petar Mitić & Aida Hanić, 2022. "A Novel Approach to Generate Hourly Photovoltaic Power Scenarios," Sustainability, MDPI, vol. 14(8), pages 1-16, April.
  49. 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).
  50. Bayrakçı, Hilmi Cenk & Demircan, Cihan & Keçebaş, Ali, 2018. "The development of empirical models for estimating global solar radiation on horizontal surface: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2771-2782.
  51. Hundi, Prabhas & Shahsavari, Rouzbeh, 2020. "Comparative studies among machine learning models for performance estimation and health monitoring of thermal power plants," Applied Energy, Elsevier, vol. 265(C).
  52. Ghimire, Sujan & Deo, Ravinesh C. & Casillas-Pérez, David & Salcedo-Sanz, Sancho, 2022. "Boosting solar radiation predictions with global climate models, observational predictors and hybrid deep-machine learning algorithms," Applied Energy, Elsevier, vol. 316(C).
  53. Su-Chang Lim & Jun-Ho Huh & Seok-Hoon Hong & Chul-Young Park & Jong-Chan Kim, 2022. "Solar Power Forecasting Using CNN-LSTM Hybrid Model," Energies, MDPI, vol. 15(21), pages 1-17, November.
  54. Moldovan, Camelia Liliana & Păltănea, Radu & Visa, Ion, 2020. "Improvement of clear sky models for direct solar irradiance considering turbidity factor variable during the day," Renewable Energy, Elsevier, vol. 161(C), pages 559-569.
  55. 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.
  56. Zambrano, Andres Felipe & Giraldo, Luis Felipe, 2020. "Solar irradiance forecasting models without on-site training measurements," Renewable Energy, Elsevier, vol. 152(C), pages 557-566.
  57. Antonio Ruano & Alvaro Hernandez & Jesus Ureña & Maria Ruano & Juan Garcia, 2019. "NILM Techniques for Intelligent Home Energy Management and Ambient Assisted Living: A Review," Energies, MDPI, vol. 12(11), pages 1-29, June.
  58. Alonso-Suárez, R. & David, M. & Branco, V. & Lauret, P., 2020. "Intra-day solar probabilistic forecasts including local short-term variability and satellite information," Renewable Energy, Elsevier, vol. 158(C), pages 554-573.
  59. Liu, Da & Sun, Kun, 2019. "Random forest solar power forecast based on classification optimization," Energy, Elsevier, vol. 187(C).
  60. Erik Heilmann & Janosch Henze & Heike Wetzel, 2021. "Machine learning in energy forecasts with an application to high frequency electricity consumption data," MAGKS Papers on Economics 202135, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  61. Edna S. Solano & Payman Dehghanian & Carolina M. Affonso, 2022. "Solar Radiation Forecasting Using Machine Learning and Ensemble Feature Selection," Energies, MDPI, vol. 15(19), pages 1-18, September.
  62. 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.
  63. Qin, Jun & Jiang, Hou & Lu, Ning & Yao, Ling & Zhou, Chenghu, 2022. "Enhancing solar PV output forecast by integrating ground and satellite observations with deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  64. Khawaja Haider Ali & Marvin Sigalo & Saptarshi Das & Enrico Anderlini & Asif Ali Tahir & Mohammad Abusara, 2021. "Reinforcement Learning for Energy-Storage Systems in Grid-Connected Microgrids: An Investigation of Online vs. Offline Implementation," Energies, MDPI, vol. 14(18), pages 1-18, September.
  65. Yagli, Gokhan Mert & Yang, Dazhi & Srinivasan, Dipti, 2019. "Automatic hourly solar forecasting using machine learning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 487-498.
  66. Zarazua de Rubens, Gerardo, 2019. "Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market," Energy, Elsevier, vol. 172(C), pages 243-254.
  67. Heo, Jae & Jung, Jaehoon & Kim, Byungil & Han, SangUk, 2020. "Digital elevation model-based convolutional neural network modeling for searching of high solar energy regions," Applied Energy, Elsevier, vol. 262(C).
  68. Juan D. Velásquez & Lorena Cadavid & Carlos J. Franco, 2023. "Intelligence Techniques in Sustainable Energy: Analysis of a Decade of Advances," Energies, MDPI, vol. 16(19), pages 1-45, October.
  69. Ceylin Şirin & Fatih Selimefendigil & Hakan Fehmi Öztop, 2023. "Performance Analysis and Identification of an Indirect Photovoltaic Thermal Dryer with Aluminum Oxide Nano-Embedded Thermal Energy Storage Modification," Sustainability, MDPI, vol. 15(3), pages 1-27, January.
  70. Moting Su & Zongyi Zhang & Ye Zhu & Donglan Zha & Wenying Wen, 2019. "Data Driven Natural Gas Spot Price Prediction Models Using Machine Learning Methods," Energies, MDPI, vol. 12(9), pages 1-17, May.
  71. 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.
  72. Ke Yan & Xudong Wang & Yang Du & Ning Jin & Haichao Huang & Hangxia Zhou, 2018. "Multi-Step Short-Term Power Consumption Forecasting with a Hybrid Deep Learning Strategy," Energies, MDPI, vol. 11(11), pages 1-15, November.
  73. Terrén-Serrano, Guillermo & Martínez-Ramón, Manel, 2021. "Multi-layer wind velocity field visualization in infrared images of clouds for solar irradiance forecasting," Applied Energy, Elsevier, vol. 288(C).
  74. Ngoc-Lan Huynh, Anh & Deo, Ravinesh C. & Ali, Mumtaz & Abdulla, Shahab & Raj, Nawin, 2021. "Novel short-term solar radiation hybrid model: Long short-term memory network integrated with robust local mean decomposition," Applied Energy, Elsevier, vol. 298(C).
  75. Caldas, M. & Alonso-Suárez, R., 2019. "Very short-term solar irradiance forecast using all-sky imaging and real-time irradiance measurements," Renewable Energy, Elsevier, vol. 143(C), pages 1643-1658.
  76. Yang, Liu & Cao, Qimeng & Yu, Ying & Liu, Yan, 2020. "Comparison of daily diffuse radiation models in regions of China without solar radiation measurement," Energy, Elsevier, vol. 191(C).
  77. Aslam, Sheraz & Herodotou, Herodotos & Mohsin, Syed Muhammad & Javaid, Nadeem & Ashraf, Nouman & Aslam, Shahzad, 2021. "A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
  78. Yang Hu & Weiwei Lian & Yutong Han & Songyuan Dai & Honglu Zhu, 2018. "A Seasonal Model Using Optimized Multi-Layer Neural Networks to Forecast Power Output of PV Plants," Energies, MDPI, vol. 11(2), pages 1-17, February.
  79. Yagli, Gokhan Mert & Yang, Dazhi & Gandhi, Oktoviano & Srinivasan, Dipti, 2020. "Can we justify producing univariate machine-learning forecasts with satellite-derived solar irradiance?," Applied Energy, Elsevier, vol. 259(C).
  80. du Plessis, A.A. & Strauss, J.M. & Rix, A.J., 2021. "Short-term solar power forecasting: Investigating the ability of deep learning models to capture low-level utility-scale Photovoltaic system behaviour," Applied Energy, Elsevier, vol. 285(C).
  81. Sylvain Cros & Jordi Badosa & André Szantaï & Martial Haeffelin, 2020. "Reliability Predictors for Solar Irradiance Satellite-Based Forecast," Energies, MDPI, vol. 13(21), pages 1-21, October.
  82. 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.
  83. Ping-Huan Kuo & Chiou-Jye Huang, 2018. "A Green Energy Application in Energy Management Systems by an Artificial Intelligence-Based Solar Radiation Forecasting Model," Energies, MDPI, vol. 11(4), pages 1-15, April.
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  85. Elsinga, Boudewijn & van Sark, Wilfried G.J.H.M., 2017. "Short-term peer-to-peer solar forecasting in a network of photovoltaic systems," Applied Energy, Elsevier, vol. 206(C), pages 1464-1483.
  86. Jean-Laurent Duchaud & Cyril Voyant & Alexis Fouilloy & Gilles Notton & Marie-Laure Nivet, 2020. "Trade-Off between Precision and Resolution of a Solar Power Forecasting Algorithm for Micro-Grid Optimal Control," Energies, MDPI, vol. 13(14), pages 1-16, July.
  87. Elham Alzain & Shaha Al-Otaibi & Theyazn H. H. Aldhyani & Ali Saleh Alshebami & Mohammed Amin Almaiah & Mukti E. Jadhav, 2023. "Revolutionizing Solar Power Production with Artificial Intelligence: A Sustainable Predictive Model," Sustainability, MDPI, vol. 15(10), pages 1-21, May.
  88. Mayer, Martin János & Biró, Bence & Szücs, Botond & Aszódi, Attila, 2023. "Probabilistic modeling of future electricity systems with high renewable energy penetration using machine learning," Applied Energy, Elsevier, vol. 336(C).
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  90. Anh Ngoc-Lan Huynh & Ravinesh C. Deo & Duc-Anh An-Vo & Mumtaz Ali & Nawin Raj & Shahab Abdulla, 2020. "Near Real-Time Global Solar Radiation Forecasting at Multiple Time-Step Horizons Using the Long Short-Term Memory Network," Energies, MDPI, vol. 13(14), pages 1-30, July.
  91. Alireza Tavakolian & Alireza Rezaee & Farshid Hajati & Shahadat Uddin, 2023. "Hospital Readmission and Length-of-Stay Prediction Using an Optimized Hybrid Deep Model," Future Internet, MDPI, vol. 15(9), pages 1-21, September.
  92. 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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  96. Hongbo Zhu & Bing Zhang & Weidong Song & Jiguang Dai & Xinmei Lan & Xinyue Chang, 2023. "Power-Weighted Prediction of Photovoltaic Power Generation in the Context of Structural Equation Modeling," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
  97. Goitia-Zabaleta, Nerea & Milo, Aitor & Gaztañaga, Haizea & Fernandez, Elvira, 2023. "Two-stage centralised management of Local Energy Market for prosumers integration in a community-based P2P," Applied Energy, Elsevier, vol. 348(C).
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  100. Paik, Chunhyun & Chung, Yongjoo & Kim, Young Jin, 2021. "ELCC-based capacity credit estimation accounting for uncertainties in capacity factors and its application to solar power in Korea," Renewable Energy, Elsevier, vol. 164(C), pages 833-841.
  101. Myeongchan Oh & Chang Ki Kim & Boyoung Kim & Changyeol Yun & Yong-Heack Kang & Hyun-Goo Kim, 2021. "Spatiotemporal Optimization for Short-Term Solar Forecasting Based on Satellite Imagery," Energies, MDPI, vol. 14(8), pages 1-18, April.
  102. Mondal, Rakesh & Roy, Surajit Kr & Giri, Chandan, 2024. "Solar power forecasting using domain knowledge," Energy, Elsevier, vol. 302(C).
  103. Prasad, Ramendra & Ali, Mumtaz & Xiang, Yong & Khan, Huma, 2020. "A double decomposition-based modelling approach to forecast weekly solar radiation," Renewable Energy, Elsevier, vol. 152(C), pages 9-22.
  104. Tyler McCandless & Susan Dettling & Sue Ellen Haupt, 2020. "Comparison of Implicit vs. Explicit Regime Identification in Machine Learning Methods for Solar Irradiance Prediction," Energies, MDPI, vol. 13(3), pages 1-14, February.
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