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A Review on Deep Learning Models for Forecasting Time Series Data of Solar Irradiance and Photovoltaic Power

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  1. Shriram S. Rangarajan & Chandan Kumar Shiva & AVV Sudhakar & Umashankar Subramaniam & E. Randolph Collins & Tomonobu Senjyu, 2023. "Avant-Garde Solar Plants with Artificial Intelligence and Moonlighting Capabilities as Smart Inverters in a Smart Grid," Energies, MDPI, vol. 16(3), pages 1-30, January.
  2. Llinet Benavides Cesar & Rodrigo Amaro e Silva & Miguel Ángel Manso Callejo & Calimanut-Ionut Cira, 2022. "Review on Spatio-Temporal Solar Forecasting Methods Driven by In Situ Measurements or Their Combination with Satellite and Numerical Weather Prediction (NWP) Estimates," Energies, MDPI, vol. 15(12), pages 1-23, June.
  3. Kazmi, Hussain & Tao, Zhenmin, 2022. "How good are TSO load and renewable generation forecasts: Learning curves, challenges, and the road ahead," Applied Energy, Elsevier, vol. 323(C).
  4. Pedro M. R. Bento & Jose A. N. Pombo & Maria R. A. Calado & Silvio J. P. S. Mariano, 2021. "Stacking Ensemble Methodology Using Deep Learning and ARIMA Models for Short-Term Load Forecasting," Energies, MDPI, vol. 14(21), pages 1-21, November.
  5. Richard Guanoluisa & Diego Arcos-Aviles & Marco Flores-Calero & Wilmar Martinez & Francesc Guinjoan, 2023. "Photovoltaic Power Forecast Using Deep Learning Techniques with Hyperparameters Based on Bayesian Optimization: A Case Study in the Galapagos Islands," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
  6. Sourav Malakar & Saptarsi Goswami & Bhaswati Ganguli & Amlan Chakrabarti & Sugata Sen Roy & K. Boopathi & A. G. Rangaraj, 2022. "Deep-Learning-Based Adaptive Model for Solar Forecasting Using Clustering," Energies, MDPI, vol. 15(10), pages 1-16, May.
  7. Verdone, Alessio & Scardapane, Simone & Panella, Massimo, 2024. "Explainable Spatio-Temporal Graph Neural Networks for multi-site photovoltaic energy production," Applied Energy, Elsevier, vol. 353(PB).
  8. 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.
  9. Ramadhan, Raden A.A. & Heatubun, Yosca R.J. & Tan, Sek F. & Lee, Hyun-Jin, 2021. "Comparison of physical and machine learning models for estimating solar irradiance and photovoltaic power," Renewable Energy, Elsevier, vol. 178(C), pages 1006-1019.
  10. Nguyen, Thi Ngoc & Müsgens, Felix, 2022. "What drives the accuracy of PV output forecasts?," Applied Energy, Elsevier, vol. 323(C).
  11. 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).
  12. Lilla Barancsuk & Veronika Groma & Dalma Günter & János Osán & Bálint Hartmann, 2024. "Estimation of Solar Irradiance Using a Neural Network Based on the Combination of Sky Camera Images and Meteorological Data," Energies, MDPI, vol. 17(2), pages 1-25, January.
  13. Wilson Castillo-Rojas & Fernando Medina Quispe & César Hernández, 2023. "Photovoltaic Energy Forecast Using Weather Data through a Hybrid Model of Recurrent and Shallow Neural Networks," Energies, MDPI, vol. 16(13), pages 1-25, July.
  14. Cheng-Hong Yang & Bo-Hong Chen & Chih-Hsien Wu & Kuo-Chang Chen & Li-Yeh Chuang, 2022. "Deep Learning for Forecasting Electricity Demand in Taiwan," Mathematics, MDPI, vol. 10(14), pages 1-19, July.
  15. Tiago Pinto, 2023. "Artificial Intelligence as a Booster of Future Power Systems," Energies, MDPI, vol. 16(5), pages 1-4, February.
  16. Victor Oliveira Santos & Felipe Pinto Marinho & Paulo Alexandre Costa Rocha & Jesse Van Griensven Thé & Bahram Gharabaghi, 2024. "Application of Quantum Neural Network for Solar Irradiance Forecasting: A Case Study Using the Folsom Dataset, California," Energies, MDPI, vol. 17(14), pages 1-26, July.
  17. Varaha Satra Bharath Kurukuru & Ahteshamul Haque & Mohammed Ali Khan & Subham Sahoo & Azra Malik & Frede Blaabjerg, 2021. "A Review on Artificial Intelligence Applications for Grid-Connected Solar Photovoltaic Systems," Energies, MDPI, vol. 14(15), pages 1-35, August.
  18. 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.
  19. Lillo, Fabrizio & Livieri, Giulia & Marmi, Stefano & Solomko, Anton & Vaienti, Sandro, 2023. "Analysis of bank leverage via dynamical systems and deep neural networks," LSE Research Online Documents on Economics 119917, London School of Economics and Political Science, LSE Library.
  20. Guillermo Almonacid-Olleros & Gabino Almonacid & David Gil & Javier Medina-Quero, 2022. "Evaluation of Transfer Learning and Fine-Tuning to Nowcast Energy Generation of Photovoltaic Systems in Different Climates," Sustainability, MDPI, vol. 14(5), pages 1-15, March.
  21. Ewa Chodakowska & Joanicjusz Nazarko & Łukasz Nazarko & Hesham S. Rabayah, 2024. "Solar Radiation Forecasting: A Systematic Meta-Review of Current Methods and Emerging Trends," Energies, MDPI, vol. 17(13), pages 1-27, June.
  22. 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.
  23. Fachrizal Aksan & Yang Li & Vishnu Suresh & Przemysław Janik, 2023. "Multistep Forecasting of Power Flow Based on LSTM Autoencoder: A Study Case in Regional Grid Cluster Proposal," Energies, MDPI, vol. 16(13), pages 1-20, June.
  24. Chang, Weiguang & Dong, Wei & Wang, Yubin & Yang, Qiang, 2022. "Two-stage coordinated operation framework for virtual power plant with aggregated multi-stakeholder microgrids in a deregulated electricity market," Renewable Energy, Elsevier, vol. 199(C), pages 943-956.
  25. Joylan Nunes Maciel & Jorge Javier Gimenez Ledesma & Oswaldo Hideo Ando Junior, 2024. "Dataset for Machine Learning: Explicit All-Sky Image Features to Enhance Solar Irradiance Prediction," Data, MDPI, vol. 9(10), pages 1-12, September.
  26. Raihan Kamil & Pranda M. P. Garniwa & Hyunjin Lee, 2021. "Performance Assessment of Global Horizontal Irradiance Models in All-Sky Conditions," Energies, MDPI, vol. 14(23), pages 1-20, November.
  27. Serrano-Arévalo, Tania Itzel & López-Flores, Francisco Javier & Raya-Tapia, Alma Yunuen & Ramírez-Márquez, César & Ponce-Ortega, José María, 2023. "Optimal expansion for a clean power sector transition in Mexico based on predicted electricity demand using deep learning scheme," Applied Energy, Elsevier, vol. 348(C).
  28. Chang, Weiguang & Dong, Wei & Yang, Qiang, 2023. "Day-ahead bidding strategy of cloud energy storage serving multiple heterogeneous microgrids in the electricity market," Applied Energy, Elsevier, vol. 336(C).
  29. Raoult Teukam Dabou & Innocent Kamwa & Jacques Tagoudjeu & Francis Chuma Mugombozi, 2021. "Sparse Signal Reconstruction on Fixed and Adaptive Supervised Dictionary Learning for Transient Stability Assessment," Energies, MDPI, vol. 14(23), pages 1-20, November.
  30. Eugenio Borghini & Cinzia Giannetti & James Flynn & Grazia Todeschini, 2021. "Data-Driven Energy Storage Scheduling to Minimise Peak Demand on Distribution Systems with PV Generation," Energies, MDPI, vol. 14(12), pages 1-22, June.
  31. Wen-Chang Tsai & Chia-Sheng Tu & Chih-Ming Hong & Whei-Min Lin, 2023. "A Review of State-of-the-Art and Short-Term Forecasting Models for Solar PV Power Generation," Energies, MDPI, vol. 16(14), pages 1-30, July.
  32. Joe Yazbeck & John B. Rundle, 2023. "A Fusion of Geothermal and InSAR Data with Machine Learning for Enhanced Deformation Forecasting at the Geysers," Land, MDPI, vol. 12(11), pages 1-22, October.
  33. Fateh Mehazzem & Maina André & Rudy Calif, 2022. "Efficient Output Photovoltaic Power Prediction Based on MPPT Fuzzy Logic Technique and Solar Spatio-Temporal Forecasting Approach in a Tropical Insular Region," Energies, MDPI, vol. 15(22), pages 1-21, November.
  34. Yongju Son & Yeunggurl Yoon & Jintae Cho & Sungyun Choi, 2022. "Cloud Cover Forecast Based on Correlation Analysis on Satellite Images for Short-Term Photovoltaic Power Forecasting," Sustainability, MDPI, vol. 14(8), pages 1-24, April.
  35. 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.
  36. Ailton Gonçalves & Gustavo O. Cavalcanti & Marcílio A. F. Feitosa & Roberto F. Dias Filho & Alex C. Pereira & Eduardo B. Jatobá & José Bione de Melo Filho & Manoel H. N. Marinho & Attilio Converti & L, 2023. "Optimal Sizing of a Photovoltaic/Battery Energy Storage System to Supply Electric Substation Auxiliary Systems under Contingency," Energies, MDPI, vol. 16(13), pages 1-17, July.
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