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Solar radiation prediction using recurrent neural network and artificial neural network: A case study with comparisons

Citations

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Cited by:

  1. Chika Maduabuchi & Chinedu Nsude & Chibuoke Eneh & Emmanuel Eke & Kingsley Okoli & Emmanuel Okpara & Christian Idogho & Bryan Waya & Catur Harsito, 2023. "Renewable Energy Potential Estimation Using Climatic-Weather-Forecasting Machine Learning Algorithms," Energies, MDPI, vol. 16(4), pages 1-20, February.
  2. Maduabuchi, Chika & Eneh, Chibuoke & Alrobaian, Abdulrahman Abdullah & Alkhedher, Mohammad, 2023. "Deep neural networks for quick and precise geometry optimization of segmented thermoelectric generators," Energy, Elsevier, vol. 263(PC).
  3. Lu, Xin & Qiu, Jing & Lei, Gang & Zhu, Jianguo, 2022. "Scenarios modelling for forecasting day-ahead electricity prices: Case studies in Australia," Applied Energy, Elsevier, vol. 308(C).
  4. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
  5. Muhammed Cavus & Dilum Dissanayake & Margaret Bell, 2025. "Deep-Fuzzy Logic Control for Optimal Energy Management: A Predictive and Adaptive Framework for Grid-Connected Microgrids," Energies, MDPI, vol. 18(4), pages 1-25, February.
  6. Diaa Salman & Mehmet Kusaf, 2021. "Short-Term Unit Commitment by Using Machine Learning to Cover the Uncertainty of Wind Power Forecasting," Sustainability, MDPI, vol. 13(24), pages 1-22, December.
  7. Wadim Strielkowski & Andrey Vlasov & Kirill Selivanov & Konstantin Muraviev & Vadim Shakhnov, 2023. "Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review," Energies, MDPI, vol. 16(10), pages 1-31, May.
  8. Dalibor Dobrilovic & Jasmina Pekez & Eleonora Desnica & Ljiljana Radovanovic & Ivan Palinkas & Milica Mazalica & Luka Djordjević & Sinisa Mihajlovic, 2023. "Data Acquisition for Estimating Energy-Efficient Solar-Powered Sensor Node Performance for Usage in Industrial IoT," Sustainability, MDPI, vol. 15(9), pages 1-22, April.
  9. Thilker, Christian Ankerstjerne & Madsen, Henrik & Jørgensen, John Bagterp, 2021. "Advanced forecasting and disturbance modelling for model predictive control of smart energy systems," Applied Energy, Elsevier, vol. 292(C).
  10. 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).
  11. Rizwan Raheem Ahmed & Dalia Streimikiene & Zahid Ali Channar & Hassan Abbas Soomro & Justas Streimikis & Grigorios L. Kyriakopoulos, 2022. "The Neuromarketing Concept in Artificial Neural Networks: A Case of Forecasting and Simulation from the Advertising Industry," Sustainability, MDPI, vol. 14(14), pages 1-24, July.
  12. 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.
  13. Dwi Sudarno Putra & Seng-Chi Chen & Hoai-Hung Khong & Chin-Feng Chang, 2023. "Realization of Intelligent Observer for Sensorless PMSM Drive Control," Mathematics, MDPI, vol. 11(5), pages 1-20, March.
  14. Gao, Yuan & Miyata, Shohei & Akashi, Yasunori, 2022. "Multi-step solar irradiation prediction based on weather forecast and generative deep learning model," Renewable Energy, Elsevier, vol. 188(C), pages 637-650.
  15. Mo, Fan & Jiao, Xuan & Li, Xingshuo & Du, Yang & Yao, Yunting & Meng, Yuxiang & Ding, Shuye, 2024. "A novel multi-step ahead solar power prediction scheme by deep learning on transformer structure," Renewable Energy, Elsevier, vol. 230(C).
  16. Goutte, Stéphane & Klotzner, Klemens & Le, Hoang-Viet & von Mettenheim, Hans-Jörg, 2024. "Forecasting photovoltaic production with neural networks and weather features," Energy Economics, Elsevier, vol. 139(C).
  17. Tang, Zhenhao & Wang, Shikui & Chai, Xiangying & Cao, Shengxian & Ouyang, Tinghui & Li, Yang, 2022. "Auto-encoder-extreme learning machine model for boiler NOx emission concentration prediction," Energy, Elsevier, vol. 256(C).
  18. Tan, Quanwei & Cao, Chunhua & Xue, Guijun & Xie, Wenju, 2024. "Short-term heating load forecasting model based on SVMD and improved informer," Energy, Elsevier, vol. 312(C).
  19. Liu, Zizhen & Zhao, Xuejing, 2026. "LSTM-Transformer with decomposition–reconstruction for enhanced solar irradiance forecasting incorporating meteorological variables," Renewable Energy, Elsevier, vol. 258(C).
  20. Maduabuchi, Chika, 2022. "Thermo-mechanical optimization of thermoelectric generators using deep learning artificial intelligence algorithms fed with verified finite element simulation data," Applied Energy, Elsevier, vol. 315(C).
  21. Liu, Meng & Bu, Siqi & Zhu, Ziqing & Zhou, Bin, 2026. "Adaptive home energy management based on PI-DRA-PPO for integrated electricity, hydrogen, and heat storage systems," Applied Energy, Elsevier, vol. 407(C).
  22. 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).
  23. Dhowmya Bhatt & Danalakshmi D & A. Hariharasudan & Marcin Lis & Marlena Grabowska, 2021. "Forecasting of Energy Demands for Smart Home Applications," Energies, MDPI, vol. 14(4), pages 1-19, February.
  24. Jui-Tang Wang & Thi Anh Tuyet Nguyen & Yu-Hong Guo & Chau-Yun Hsu & Huang-Jun Xie, 2025. "An innovative cluster-based prediction approach for mass solar site management," Energy & Environment, , vol. 36(1), pages 212-230, February.
  25. Aschenaki Altaye & Istvan Farkas & Piroska Víg, 2025. "Impacts of Artificial Neural Network Training Algorithms on the Accuracy of PV System Voltage and Current Predictions," European Journal of Energy Research, European Open Science, vol. 5(3), pages 1-6, May.
  26. Bellido-Jiménez, Juan Antonio & Estévez Gualda, Javier & García-Marín, Amanda Penélope, 2021. "Assessing new intra-daily temperature-based machine learning models to outperform solar radiation predictions in different conditions," Applied Energy, Elsevier, vol. 298(C).
  27. 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.
  28. 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).
  29. Han, Tian & Li, Ruimeng & Wang, Xiao & Wang, Ying & Chen, Kang & Peng, Huaiwu & Gao, Zhenxin & Wang, Nannan & Peng, Qinke, 2024. "Intra-hour solar irradiance forecasting using topology data analysis and physics-driven deep learning," Renewable Energy, Elsevier, vol. 224(C).
  30. Putri Nor Liyana Mohamad Radzi & Muhammad Naveed Akhter & Saad Mekhilef & Noraisyah Mohamed Shah, 2023. "Review on the Application of Photovoltaic Forecasting Using Machine Learning for Very Short- to Long-Term Forecasting," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
  31. Rial A. Rajagukguk & Raden A. A. Ramadhan & Hyun-Jin Lee, 2020. "A Review on Deep Learning Models for Forecasting Time Series Data of Solar Irradiance and Photovoltaic Power," Energies, MDPI, vol. 13(24), pages 1-23, December.
  32. Mazzeo, Domenico & Herdem, Münür Sacit & Matera, Nicoletta & Bonini, Matteo & Wen, John Z. & Nathwani, Jatin & Oliveti, Giuseppe, 2021. "Artificial intelligence application for the performance prediction of a clean energy community," Energy, Elsevier, vol. 232(C).
  33. Quanwei, Tan & Guijun, Xue & Wenju, Xie, 2025. "Cakformer: Transformer model for long-term heat load forecasting based on Cauto-correlation and KAN," Energy, Elsevier, vol. 324(C).
  34. Mohammad Hijji & Tzu-Chia Chen & Muhammad Ayaz & Ali S. Abosinnee & Iskandar Muda & Yury Razoumny & Javad Hatamiafkoueieh, 2023. "Optimization of State of the Art Fuzzy-Based Machine Learning Techniques for Total Dissolved Solids Prediction," Sustainability, MDPI, vol. 15(8), pages 1-23, April.
  35. Gao, Yuan & Miyata, Shohei & Akashi, Yasunori, 2022. "Interpretable deep learning models for hourly solar radiation prediction based on graph neural network and attention," Applied Energy, Elsevier, vol. 321(C).
  36. Javad Saadat & Mohsen Farshad & Hussein Eliasi & Kazem Shokoohi Mehr, 2025. "Establishing Echo State Network in Order to Be Used in Online Application," SN Operations Research Forum, Springer, vol. 6(3), pages 1-15, September.
  37. Chika Maduabuchi & Hassan Fagehi & Ibrahim Alatawi & Mohammad Alkhedher, 2022. "Predicting the Optimal Performance of a Concentrated Solar Segmented Variable Leg Thermoelectric Generator Using Neural Networks," Energies, MDPI, vol. 15(16), pages 1-25, August.
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