One-Hour Prediction of the Global Solar Irradiance from All-Sky Images Using Artificial Neural Networks
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- Logothetis, Stavros-Andreas & Salamalikis, Vasileios & Wilbert, Stefan & Remund, Jan & Zarzalejo, Luis F. & Xie, Yu & Nouri, Bijan & Ntavelis, Evangelos & Nou, Julien & Hendrikx, Niels & Visser, Lenna, 2022. "Benchmarking of solar irradiance nowcast performance derived from all-sky imagers," Renewable Energy, Elsevier, vol. 199(C), pages 246-261.
- Muzhou Hou & Tianle Zhang & Futian Weng & Mumtaz Ali & Nadhir Al-Ansari & Zaher Mundher Yaseen, 2018. "Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model," Energies, MDPI, vol. 11(12), pages 1-19, December.
- Giorgio Guariso & Giuseppe Nunnari & Matteo Sangiorgio, 2020. "Multi-Step Solar Irradiance Forecasting and Domain Adaptation of Deep Neural Networks," Energies, MDPI, vol. 13(15), pages 1-18, August.
- 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.
- Qu, Jiaqi & Qian, Zheng & Pei, Yan, 2021. "Day-ahead hourly photovoltaic power forecasting using attention-based CNN-LSTM neural network embedded with multiple relevant and target variables prediction pattern," Energy, Elsevier, vol. 232(C).
- Musaed Alhussein & Syed Irtaza Haider & Khursheed Aurangzeb, 2019. "Microgrid-Level Energy Management Approach Based on Short-Term Forecasting of Wind Speed and Solar Irradiance," Energies, MDPI, vol. 12(8), pages 1-27, April.
- Bikhtiyar Ameen & Heiko Balzter & Claire Jarvis & James Wheeler, 2019. "Modelling Hourly Global Horizontal Irradiance from Satellite-Derived Datasets and Climate Variables as New Inputs with Artificial Neural Networks," Energies, MDPI, vol. 12(1), pages 1-28, January.
- Cristian Crisosto & Eduardo W. Luiz & Gunther Seckmeyer, 2021. "Convolutional Neural Network for High-Resolution Cloud Motion Prediction from Hemispheric Sky Images," Energies, MDPI, vol. 14(3), pages 1-11, February.
- 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.
- Tang, Yugui & Yang, Kuo & Zhang, Shujing & Zhang, Zhen, 2022. "Photovoltaic power forecasting: A hybrid deep learning model incorporating transfer learning strategy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
- Vateanui Sansine & Pascal Ortega & Daniel Hissel & Marania Hopuare, 2022. "Solar Irradiance Probabilistic Forecasting Using Machine Learning, Metaheuristic Models and Numerical Weather Predictions," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
- Mahmoud Dhimish & Pavlos I. Lazaridis, 2022. "Approximating Shading Ratio Using the Total-Sky Imaging System: An Application for Photovoltaic Systems," Energies, MDPI, vol. 15(21), pages 1-16, November.
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Keywords
solar energy; all-sky image; solar irradiance prediction; artificial neural networks;All these keywords.
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