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Short-term solar irradiation forecasting based on Dynamic Harmonic Regression

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Cited by:

  1. Wang, Fei & Lu, Xiaoxing & Mei, Shengwei & Su, Ying & Zhen, Zhao & Zou, Zubing & Zhang, Xuemin & Yin, Rui & Duić, Neven & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "A satellite image data based ultra-short-term solar PV power forecasting method considering cloud information from neighboring plant," Energy, Elsevier, vol. 238(PC).
  2. 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).
  3. Pin Li & Jinsuo Zhang, 2019. "Is China’s Energy Supply Sustainable? New Research Model Based on the Exponential Smoothing and GM(1,1) Methods," Energies, MDPI, vol. 12(2), pages 1-30, January.
  4. 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).
  5. Hasala Dharmawardena & Ganesh Kumar Venayagamoorthy, 2022. "Distributed Volt-Var Curve Optimization Using a Cellular Computational Network Representation of an Electric Power Distribution System," Energies, MDPI, vol. 15(12), pages 1-18, June.
  6. 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.
  7. Xing Zhang & Zhuoqun Wei, 2019. "A Hybrid Model Based on Principal Component Analysis, Wavelet Transform, and Extreme Learning Machine Optimized by Bat Algorithm for Daily Solar Radiation Forecasting," Sustainability, MDPI, vol. 11(15), pages 1-20, July.
  8. Trapero, Juan R., 2016. "Calculation of solar irradiation prediction intervals combining volatility and kernel density estimates," Energy, Elsevier, vol. 114(C), pages 266-274.
  9. Niu, Tong & Li, Jinkai & Wei, Wei & Yue, Hui, 2022. "A hybrid deep learning framework integrating feature selection and transfer learning for multi-step global horizontal irradiation forecasting," Applied Energy, Elsevier, vol. 326(C).
  10. Spiliotis, Evangelos & Petropoulos, Fotios & Kourentzes, Nikolaos & Assimakopoulos, Vassilios, 2018. "Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption," MPRA Paper 91762, University Library of Munich, Germany.
  11. Perera, Maneesha & De Hoog, Julian & Bandara, Kasun & Senanayake, Damith & Halgamuge, Saman, 2024. "Day-ahead regional solar power forecasting with hierarchical temporal convolutional neural networks using historical power generation and weather data," Applied Energy, Elsevier, vol. 361(C).
  12. 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.
  13. Wang, Yuhan & Zhang, Chu & Fu, Yongyan & Suo, Leiming & Song, Shihao & Peng, Tian & Shahzad Nazir, Muhammad, 2023. "Hybrid solar radiation forecasting model with temporal convolutional network using data decomposition and improved artificial ecosystem-based optimization algorithm," Energy, Elsevier, vol. 280(C).
  14. 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.
  15. Michel Fliess & Cédric Join & Cyril Voyant, 2018. "Prediction bands for solar energy: New short-term time series forecasting techniques," Post-Print hal-01736518, HAL.
  16. 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.
  17. 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.
  18. Akarslan, Emre & Hocaoglu, Fatih Onur, 2016. "A novel adaptive approach for hourly solar radiation forecasting," Renewable Energy, Elsevier, vol. 87(P1), pages 628-633.
  19. Pedro, Hugo T.C. & Coimbra, Carlos F.M. & David, Mathieu & Lauret, Philippe, 2018. "Assessment of machine learning techniques for deterministic and probabilistic intra-hour solar forecasts," Renewable Energy, Elsevier, vol. 123(C), pages 191-203.
  20. Basetti, Vedik & Chandel, Ashwani K. & Chandel, Rajeevan, 2016. "Power system dynamic state estimation using prediction based evolutionary technique," Energy, Elsevier, vol. 107(C), pages 29-47.
  21. Wen, Yan & Pan, Su & Li, Xinxin & Li, Zibo & Wen, Wuzhenghong, 2024. "Improving multi-site photovoltaic forecasting with relevance amplification: DeepFEDformer-based approach," Energy, Elsevier, vol. 299(C).
  22. Arumugham, Dinesh Rajan & Rajendran, Parvathy, 2021. "Modelling global solar irradiance for any location on earth through regression analysis using high-resolution data," Renewable Energy, Elsevier, vol. 180(C), pages 1114-1123.
  23. Kaur, Amanpreet & Nonnenmacher, Lukas & Coimbra, Carlos F.M., 2016. "Net load forecasting for high renewable energy penetration grids," Energy, Elsevier, vol. 114(C), pages 1073-1084.
  24. 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.
  25. Ahmad, Tanveer & Zhang, Dongdong & Huang, Chao, 2021. "Methodological framework for short-and medium-term energy, solar and wind power forecasting with stochastic-based machine learning approach to monetary and energy policy applications," Energy, Elsevier, vol. 231(C).
  26. Kovács, András & Bátai, Roland & Csáji, Balázs Csanád & Dudás, Péter & Háy, Borbála & Pedone, Gianfranco & Révész, Tibor & Váncza, József, 2016. "Intelligent control for energy-positive street lighting," Energy, Elsevier, vol. 114(C), pages 40-51.
  27. Luo, Xing & Zhang, Dongxiao & Zhu, Xu, 2021. "Deep learning based forecasting of photovoltaic power generation by incorporating domain knowledge," Energy, Elsevier, vol. 225(C).
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