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Review of solar irradiance forecasting methods and a proposition for small-scale insular grids

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  1. Shamshirband, Shahaboddin & Mohammadi, Kasra & Khorasanizadeh, Hossein & Yee, Por Lip & Lee, Malrey & Petković, Dalibor & Zalnezhad, Erfan, 2016. "Estimating the diffuse solar radiation using a coupled support vector machine–wavelet transform model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 428-435.
  2. 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.
  3. 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.
  4. Mari R. Tye & Sue Ellen Haupt & Eric Gilleland & Christina Kalb & Tara Jensen, 2019. "Assessing Evidence for Weather Regimes Governing Solar Power Generation in Kuwait," Energies, MDPI, vol. 12(23), pages 1-17, November.
  5. Majid Hosseini & Satya Katragadda & Jessica Wojtkiewicz & Raju Gottumukkala & Anthony Maida & Terrence Lynn Chambers, 2020. "Direct Normal Irradiance Forecasting Using Multivariate Gated Recurrent Units," Energies, MDPI, vol. 13(15), pages 1-15, July.
  6. Theo, Wai Lip & Lim, Jeng Shiun & Ho, Wai Shin & Hashim, Haslenda & Lee, Chew Tin, 2017. "Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 531-573.
  7. Feng, Cong & Zhang, Jie & Zhang, Wenqi & Hodge, Bri-Mathias, 2022. "Convolutional neural networks for intra-hour solar forecasting based on sky image sequences," Applied Energy, Elsevier, vol. 310(C).
  8. Gherboudj, Imen & Zorgati, Mohamed & Chamarthi, Phani-Kumar & Tuomiranta, Arttu & Mohandes, Baraa & Beegum, Naseema S. & Al-Sudairi, Jood & Al-Owain, Omar & Shibli, Hussain & El-Moursi, Mohamed & Ghed, 2021. "Renewable energy management system for Saudi Arabia: Methodology and preliminary results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
  9. Ren, Xiaoying & Zhang, Fei & Zhu, Honglu & Liu, Yongqian, 2022. "Quad-kernel deep convolutional neural network for intra-hour photovoltaic power forecasting," Applied Energy, Elsevier, vol. 323(C).
  10. Aguiar, L. Mazorra & Pereira, B. & Lauret, P. & Díaz, F. & David, M., 2016. "Combining solar irradiance measurements, satellite-derived data and a numerical weather prediction model to improve intra-day solar forecasting," Renewable Energy, Elsevier, vol. 97(C), pages 599-610.
  11. Boland, John, 2015. "Spatial-temporal forecasting of solar radiation," Renewable Energy, Elsevier, vol. 75(C), pages 607-616.
  12. Panagiotis Kosmopoulos & Dimitris Kouroutsidis & Kyriakoula Papachristopoulou & Panagiotis Ioannis Raptis & Akriti Masoom & Yves-Marie Saint-Drenan & Philippe Blanc & Charalampos Kontoes & Stelios Kaz, 2020. "Short-Term Forecasting of Large-Scale Clouds Impact on Downwelling Surface Solar Irradiation," Energies, MDPI, vol. 13(24), pages 1-22, December.
  13. Michael Kostmann & Wolfgang K. Härdle, 2019. "Forecasting in Blockchain-Based Local Energy Markets," Energies, MDPI, vol. 12(14), pages 1-27, July.
  14. Javier Borquez & Hector Chavez & Karina A. Barbosa & Marcela Jamett & Rodrigo Acuna, 2020. "A Simple Distribution Energy Tariff under the Penetration of DG," Energies, MDPI, vol. 13(8), pages 1-17, April.
  15. 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.
  16. 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.
  17. Reikard, Gordon & Hansen, Clifford, 2019. "Forecasting solar irradiance at short horizons: Frequency and time domain models," Renewable Energy, Elsevier, vol. 135(C), pages 1270-1290.
  18. Cheng, Hsu-Yung, 2016. "Hybrid solar irradiance now-casting by fusing Kalman filter and regressor," Renewable Energy, Elsevier, vol. 91(C), pages 434-441.
  19. Sabo, Mahmoud Lurwan & Mariun, Norman & Hizam, Hashim & Mohd Radzi, Mohd Amran & Zakaria, Azmi, 2016. "Spatial energy predictions from large-scale photovoltaic power plants located in optimal sites and connected to a smart grid in Peninsular Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 79-94.
  20. Paulescu, Marius & Stefu, Nicoleta & Dughir, Ciprian & Sabadus, Andreea & Calinoiu, Delia & Badescu, Viorel, 2022. "A simple but accurate two-state model for nowcasting PV power," Renewable Energy, Elsevier, vol. 195(C), pages 322-330.
  21. Julián Urrego-Ortiz & J. Alejandro Martínez & Paola A. Arias & Álvaro Jaramillo-Duque, 2019. "Assessment and Day-Ahead Forecasting of Hourly Solar Radiation in Medellín, Colombia," Energies, MDPI, vol. 12(22), pages 1-29, November.
  22. Gianfranco Chicco & Valeria Cocina & Paolo Di Leo & Filippo Spertino & Alessandro Massi Pavan, 2015. "Error Assessment of Solar Irradiance Forecasts and AC Power from Energy Conversion Model in Grid-Connected Photovoltaic Systems," Energies, MDPI, vol. 9(1), pages 1-27, December.
  23. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
  24. 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).
  25. Verbois, Hadrien & Blanc, Philippe & Huva, Robert & Saint-Drenan, Yves-Marie & Rusydi, Andrivo & Thiery, Alexandre, 2020. "Beyond quadratic error: Case-study of a multiple criteria approach to the performance assessment of numerical forecasts of solar irradiance in the tropics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
  26. John Boland & Sleiman Farah & Lei Bai, 2022. "Forecasting of Wind and Solar Farm Output in the Australian National Electricity Market: A Review," Energies, MDPI, vol. 15(1), pages 1-18, January.
  27. Cervone, A. & Santini, E. & Teodori, S. & Romito, Donatella Zaccagnini, 2015. "Impact of regulatory rules on economic performance of PV power plants," Renewable Energy, Elsevier, vol. 74(C), pages 78-86.
  28. Halabi, Laith M. & Mekhilef, Saad & Hossain, Monowar, 2018. "Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation," Applied Energy, Elsevier, vol. 213(C), pages 247-261.
  29. Trapero, Juan R., 2016. "Calculation of solar irradiation prediction intervals combining volatility and kernel density estimates," Energy, Elsevier, vol. 114(C), pages 266-274.
  30. Alfredo Nespoli & Emanuele Ogliari & Sonia Leva & Alessandro Massi Pavan & Adel Mellit & Vanni Lughi & Alberto Dolara, 2019. "Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques," Energies, MDPI, vol. 12(9), pages 1-15, April.
  31. 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.
  32. Giuseppe La Tona & Maria Carmela Di Piazza & Massimiliano Luna, 2021. "Effect of Daily Forecasting Frequency on Rolling-Horizon-Based EMS Reducing Electrical Demand Uncertainty in Microgrids," Energies, MDPI, vol. 14(6), pages 1-16, March.
  33. Takahiro Takamatsu & Hideaki Ohtake & Takashi Oozeki & Tosiyuki Nakaegawa & Yuki Honda & Masahiro Kazumori, 2021. "Regional Solar Irradiance Forecast for Kanto Region by Support Vector Regression Using Forecast of Meso-Ensemble Prediction System," Energies, MDPI, vol. 14(11), pages 1-18, June.
  34. Schwarz, Hannes & Bertsch, Valentin & Fichtner, Wolf, 2015. "Two-stage stochastic, large-scale optimization of a decentralized energy system - a residential quarter as case study," Working Paper Series in Production and Energy 10, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
  35. 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).
  36. VanDeventer, William & Jamei, Elmira & Thirunavukkarasu, Gokul Sidarth & Seyedmahmoudian, Mehdi & Soon, Tey Kok & Horan, Ben & Mekhilef, Saad & Stojcevski, Alex, 2019. "Short-term PV power forecasting using hybrid GASVM technique," Renewable Energy, Elsevier, vol. 140(C), pages 367-379.
  37. 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.
  38. Stefano Alessandrini & Tyler McCandless, 2020. "The Schaake Shuffle Technique to Combine Solar and Wind Power Probabilistic Forecasting," Energies, MDPI, vol. 13(10), pages 1-18, May.
  39. Khorasanizadeh, Hossein & Mohammadi, Kasra, 2016. "Diffuse solar radiation on a horizontal surface: Reviewing and categorizing the empirical models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 338-362.
  40. Terrén-Serrano, Guillermo & Martínez-Ramón, Manel, 2021. "Comparative analysis of methods for cloud segmentation in ground-based infrared images," Renewable Energy, Elsevier, vol. 175(C), pages 1025-1040.
  41. 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).
  42. Zografidou, Eleni & Petridis, Konstantinos & Petridis, Nikolaos E. & Arabatzis, Garyfallos, 2017. "A financial approach to renewable energy production in Greece using goal programming," Renewable Energy, Elsevier, vol. 108(C), pages 37-51.
  43. Jin, Ming & Feng, Wei & Marnay, Chris & Spanos, Costas, 2018. "Microgrid to enable optimal distributed energy retail and end-user demand response," Applied Energy, Elsevier, vol. 210(C), pages 1321-1335.
  44. 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).
  45. 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.
  46. Rodrigues, Eugénio & Gomes, Álvaro & Gaspar, Adélio Rodrigues & Henggeler Antunes, Carlos, 2018. "Estimation of renewable energy and built environment-related variables using neural networks – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 959-988.
  47. Wu, Ji & Chan, Chee Keong & Zhang, Yu & Xiong, Bin Yu & Zhang, Qing Hai, 2014. "Prediction of solar radiation with genetic approach combing multi-model framework," Renewable Energy, Elsevier, vol. 66(C), pages 132-139.
  48. Demirhan, Haydar & Renwick, Zoe, 2018. "Missing value imputation for short to mid-term horizontal solar irradiance data," Applied Energy, Elsevier, vol. 225(C), pages 998-1012.
  49. 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).
  50. Elena Collino & Dario Ronzio, 2021. "Exploitation of a New Short-Term Multimodel Photovoltaic Power Forecasting Method in the Very Short-Term Horizon to Derive a Multi-Time Scale Forecasting System," Energies, MDPI, vol. 14(3), pages 1-30, February.
  51. 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.
  52. 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.
  53. Mohammadi, Kasra & Shamshirband, Shahaboddin & Petković, Dalibor & Khorasanizadeh, Hossein, 2016. "Determining the most important variables for diffuse solar radiation prediction using adaptive neuro-fuzzy methodology; case study: City of Kerman, Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1570-1579.
  54. Mohamed Massaoudi & Ines Chihi & Lilia Sidhom & Mohamed Trabelsi & Shady S. Refaat & Fakhreddine S. Oueslati, 2021. "Enhanced Random Forest Model for Robust Short-Term Photovoltaic Power Forecasting Using Weather Measurements," Energies, MDPI, vol. 14(13), pages 1-20, July.
  55. 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.
  56. Michel Fliess & Cédric Join & Cyril Voyant, 2018. "Prediction bands for solar energy: New short-term time series forecasting techniques," Post-Print hal-01736518, HAL.
  57. 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.
  58. Yadav, Amit Kumar & Chandel, S.S., 2015. "Solar energy potential assessment of western Himalayan Indian state of Himachal Pradesh using J48 algorithm of WEKA in ANN based prediction model," Renewable Energy, Elsevier, vol. 75(C), pages 675-693.
  59. Finck, Christian & Li, Rongling & Zeiler, Wim, 2020. "Optimal control of demand flexibility under real-time pricing for heating systems in buildings: A real-life demonstration," Applied Energy, Elsevier, vol. 263(C).
  60. 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.
  61. Finck, Christian & Li, Rongling & Zeiler, Wim, 2019. "Economic model predictive control for demand flexibility of a residential building," Energy, Elsevier, vol. 176(C), pages 365-379.
  62. Fabio Corti & Antonino Laudani & Gabriele Maria Lozito & Alberto Reatti, 2020. "Computationally Efficient Modeling of DC-DC Converters for PV Applications," Energies, MDPI, vol. 13(19), pages 1-18, September.
  63. Takahiro Takamatsu & Hideaki Ohtake & Takashi Oozeki, 2022. "Support Vector Quantile Regression for the Post-Processing of Meso-Scale Ensemble Prediction System Data in the Kanto Region: Solar Power Forecast Reducing Overestimation," Energies, MDPI, vol. 15(4), pages 1-18, February.
  64. Rodríguez, Fermín & Galarza, Ainhoa & Vasquez, Juan C. & Guerrero, Josep M., 2022. "Using deep learning and meteorological parameters to forecast the photovoltaic generators intra-hour output power interval for smart grid control," Energy, Elsevier, vol. 239(PB).
  65. Zang, Haixiang & Liu, Ling & Sun, Li & Cheng, Lilin & Wei, Zhinong & Sun, Guoqiang, 2020. "Short-term global horizontal irradiance forecasting based on a hybrid CNN-LSTM model with spatiotemporal correlations," Renewable Energy, Elsevier, vol. 160(C), pages 26-41.
  66. Luigi Cirocco & Martin Belusko & Frank Bruno & John Boland & Peter Pudney, 2014. "Optimisation of Storage for Concentrated Solar Power Plants," Challenges, MDPI, vol. 5(2), pages 1-31, December.
  67. Reikard, Gordon & Haupt, Sue Ellen & Jensen, Tara, 2017. "Forecasting ground-level irradiance over short horizons: Time series, meteorological, and time-varying parameter models," Renewable Energy, Elsevier, vol. 112(C), pages 474-485.
  68. Lan, Hai & Yin, He & Hong, Ying-Yi & Wen, Shuli & Yu, David C. & Cheng, Peng, 2018. "Day-ahead spatio-temporal forecasting of solar irradiation along a navigation route," Applied Energy, Elsevier, vol. 211(C), pages 15-27.
  69. Ines Sansa & Zina Boussaada & Najiba Mrabet Bellaaj, 2021. "Solar Radiation Prediction Using a Novel Hybrid Model of ARMA and NARX," Energies, MDPI, vol. 14(21), pages 1-26, October.
  70. Àlex Alonso & Jordi de la Hoz & Helena Martín & Sergio Coronas & Pep Salas & José Matas, 2020. "A Comprehensive Model for the Design of a Microgrid under Regulatory Constraints Using Synthetical Data Generation and Stochastic Optimization," Energies, MDPI, vol. 13(21), pages 1-26, October.
  71. Yadav, Amit Kumar & Chandel, S.S., 2017. "Identification of relevant input variables for prediction of 1-minute time-step photovoltaic module power using Artificial Neural Network and Multiple Linear Regression Models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 955-969.
  72. N. Yogambal Jayalakshmi & R. Shankar & Umashankar Subramaniam & I. Baranilingesan & Alagar Karthick & Balasubramaniam Stalin & Robbi Rahim & Aritra Ghosh, 2021. "Novel Multi-Time Scale Deep Learning Algorithm for Solar Irradiance Forecasting," Energies, MDPI, vol. 14(9), pages 1-23, April.
  73. Martins, Guilherme Santos & Giesbrecht, Mateus, 2021. "Clearness index forecasting: A comparative study between a stochastic realization method and a machine learning algorithm," Renewable Energy, Elsevier, vol. 180(C), pages 787-805.
  74. Trapero, Juan R. & Kourentzes, Nikolaos & Martin, A., 2015. "Short-term solar irradiation forecasting based on Dynamic Harmonic Regression," Energy, Elsevier, vol. 84(C), pages 289-295.
  75. Li, Jiaming & Ward, John K. & Tong, Jingnan & Collins, Lyle & Platt, Glenn, 2016. "Machine learning for solar irradiance forecasting of photovoltaic system," Renewable Energy, Elsevier, vol. 90(C), pages 542-553.
  76. Ahmed, Adil & Khalid, Muhammad, 2019. "A review on the selected applications of forecasting models in renewable power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 9-21.
  77. Stéphanie Monjoly & Maina André & Rudy Calif & Ted Soubdhan, 2019. "Forecast Horizon and Solar Variability Influences on the Performances of Multiscale Hybrid Forecast Model," Energies, MDPI, vol. 12(12), pages 1-20, June.
  78. Benali, L. & Notton, G. & Fouilloy, A. & Voyant, C. & Dizene, R., 2019. "Solar radiation forecasting using artificial neural network and random forest methods: Application to normal beam, horizontal diffuse and global components," Renewable Energy, Elsevier, vol. 132(C), pages 871-884.
  79. Agüera-Pérez, Agustín & Palomares-Salas, José Carlos & González de la Rosa, Juan José & Florencias-Oliveros, Olivia, 2018. "Weather forecasts for microgrid energy management: Review, discussion and recommendations," Applied Energy, Elsevier, vol. 228(C), pages 265-278.
  80. Erdinc, Ozan & Paterakis, Nikolaos G. & Catalão, João P.S., 2015. "Overview of insular power systems under increasing penetration of renewable energy sources: Opportunities and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 333-346.
  81. Si-Ya Wang & Jun Qiu & Fang-Fang Li, 2018. "Hybrid Decomposition-Reconfiguration Models for Long-Term Solar Radiation Prediction Only Using Historical Radiation Records," Energies, MDPI, vol. 11(6), pages 1-17, May.
  82. 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.
  83. Gairaa, Kacem & Voyant, Cyril & Notton, Gilles & Benkaciali, Saïd & Guermoui, Mawloud, 2022. "Contribution of ordinal variables to short-term global solar irradiation forecasting for sites with low variabilities," Renewable Energy, Elsevier, vol. 183(C), pages 890-902.
  84. Guerrero-Lemus, Ricardo & González-Díaz, Benjamín & Ríos, Gerardo & Dib, Ramzi N., 2015. "Study of the new Spanish legislation applied to an insular system that has achieved grid parity on PV and wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 426-436.
  85. Da Liu & Kun Sun & Han Huang & Pingzhou Tang, 2018. "Monthly Load Forecasting Based on Economic Data by Decomposition Integration Theory," Sustainability, MDPI, vol. 10(9), pages 1-22, September.
  86. Kong, Xiangfei & Du, Xinyu & Xue, Guixiang & Xu, Zhijie, 2023. "Multi-step short-term solar radiation prediction based on empirical mode decomposition and gated recurrent unit optimized via an attention mechanism," Energy, Elsevier, vol. 282(C).
  87. Notton, Gilles & Nivet, Marie-Laure & Voyant, Cyril & Paoli, Christophe & Darras, Christophe & Motte, Fabrice & Fouilloy, Alexis, 2018. "Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 87(C), pages 96-105.
  88. Chen, Yunxiao & Bai, Mingliang & Zhang, Yilan & Liu, Jinfu & Yu, Daren, 2023. "Proactively selection of input variables based on information gain factors for deep learning models in short-term solar irradiance forecasting," Energy, Elsevier, vol. 284(C).
  89. Louis Desportes & Inbar Fijalkow & Pierre Andry, 2021. "Deep Reinforcement Learning for Hybrid Energy Storage Systems: Balancing Lead and Hydrogen Storage," Energies, MDPI, vol. 14(15), pages 1-22, August.
  90. Rodríguez-Benítez, Francisco J. & López-Cuesta, Miguel & Arbizu-Barrena, Clara & Fernández-León, María M. & Pamos-Ureña, Miguel Á. & Tovar-Pescador, Joaquín & Santos-Alamillos, Francisco J. & Pozo-Váz, 2021. "Assessment of new solar radiation nowcasting methods based on sky-camera and satellite imagery," Applied Energy, Elsevier, vol. 292(C).
  91. Khan, Zulfiqar Ahmad & Hussain, Tanveer & Baik, Sung Wook, 2023. "Dual stream network with attention mechanism for photovoltaic power forecasting," Applied Energy, Elsevier, vol. 338(C).
  92. Ramírez, Andres Felipe & Valencia, Carlos Felipe & Cabrales, Sergio & Ramírez, Carlos G., 2021. "Simulation of photo-voltaic power generation using copula autoregressive models for solar irradiance and air temperature time series," Renewable Energy, Elsevier, vol. 175(C), pages 44-67.
  93. Di Piazza, A. & Di Piazza, M.C. & La Tona, G. & Luna, M., 2021. "An artificial neural network-based forecasting model of energy-related time series for electrical grid management," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 184(C), pages 294-305.
  94. Akarslan, Emre & Hocaoglu, Fatih Onur & Edizkan, Rifat, 2018. "Novel short term solar irradiance forecasting models," Renewable Energy, Elsevier, vol. 123(C), pages 58-66.
  95. Tyler McCandless & Pedro Angel Jiménez, 2020. "Examining the Potential of a Random Forest Derived Cloud Mask from GOES-R Satellites to Improve Solar Irradiance Forecasting," Energies, MDPI, vol. 13(7), pages 1-15, April.
  96. Azhar Ahmed Mohammed & Zeyar Aung, 2016. "Ensemble Learning Approach for Probabilistic Forecasting of Solar Power Generation," Energies, MDPI, vol. 9(12), pages 1-17, December.
  97. Gairaa, Kacem & Khellaf, Abdallah & Messlem, Youcef & Chellali, Farouk, 2016. "Estimation of the daily global solar radiation based on Box–Jenkins and ANN models: A combined approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 238-249.
  98. Barbieri, Florian & Rajakaruna, Sumedha & Ghosh, Arindam, 2017. "Very short-term photovoltaic power forecasting with cloud modeling: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 242-263.
  99. Wen, Haoran & Du, Yang & Chen, Xiaoyang & Lim, Eng Gee & Wen, Huiqing & Yan, Ke, 2023. "A regional solar forecasting approach using generative adversarial networks with solar irradiance maps," Renewable Energy, Elsevier, vol. 216(C).
  100. Bisoi, Ranjeeta & Dash, Deepak Ranjan & Dash, P.K. & Tripathy, Lokanath, 2022. "An efficient robust optimized functional link broad learning system for solar irradiance prediction," Applied Energy, Elsevier, vol. 319(C).
  101. Yufei Wang & Li Zhu & Hua Xue, 2020. "Ultra-Short-Term Photovoltaic Power Prediction Model Based on the Localized Emotion Reconstruction Emotional Neural Network," Energies, MDPI, vol. 13(11), pages 1-21, June.
  102. Voyant, Cyril & Motte, Fabrice & Fouilloy, Alexis & Notton, Gilles & Paoli, Christophe & Nivet, Marie-Laure, 2017. "Forecasting method for global radiation time series without training phase: Comparison with other well-known prediction methodologies," Energy, Elsevier, vol. 120(C), pages 199-208.
  103. Xinyuan Hou & Kyriakoula Papachristopoulou & Yves-Marie Saint-Drenan & Stelios Kazadzis, 2022. "Solar Radiation Nowcasting Using a Markov Chain Multi-Model Approach," Energies, MDPI, vol. 15(9), pages 1-24, April.
  104. Voyant, Cyril & Notton, Gilles & Kalogirou, Soteris & Nivet, Marie-Laure & Paoli, Christophe & Motte, Fabrice & Fouilloy, Alexis, 2017. "Machine learning methods for solar radiation forecasting: A review," Renewable Energy, Elsevier, vol. 105(C), pages 569-582.
  105. Munir Husein & Il-Yop Chung, 2019. "Day-Ahead Solar Irradiance Forecasting for Microgrids Using a Long Short-Term Memory Recurrent Neural Network: A Deep Learning Approach," Energies, MDPI, vol. 12(10), pages 1-21, May.
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