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Ganapathy Ramesh, Jaganathan Logeshwaran, Thangavel Kiruthiga and Jaime Lloret
In general, reliable PV generation prediction is required to increase complete control quality and avoid potential damage. Accurate forecasting of direct solar radiation trends in PV power production could limit the influence of uncertainties on photovol...
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Georgios Venitourakis, Christoforos Vasilakis, Alexandros Tsagkaropoulos, Tzouma Amrou, Georgios Konstantoulakis, Panagiotis Golemis and Dionysios Reisis
Aiming at effectively improving photovoltaic (PV) park operation and the stability of the electricity grid, the current paper addresses the design and development of a novel system achieving the short-term irradiance forecasting for the PV park area, whi...
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Seyed Mahdi Miraftabzadeh, Cristian Giovanni Colombo, Michela Longo and Federica Foiadelli
Climate change and global warming drive many governments and scientists to investigate new renewable and green energy sources. Special attention is on solar panel technology, since solar energy is considered one of the primary renewable sources and solar...
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Alessandro Niccolai, Seyedamir Orooji, Andrea Matteri, Emanuele Ogliari and Sonia Leva
This work proposes and evaluates a method for the nowcasting of solar irradiance variability in multiple time horizons, namely 5, 10, and 15 min ahead. The method is based on a Convolutional Neural Network structure that exploits infrared sky images acqu...
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Abdelkader Dairi, Fouzi Harrou, Ying Sun and Sofiane Khadraoui
The accurate modeling and forecasting of the power output of photovoltaic (PV) systems are critical to efficiently managing their integration in smart grids, delivery, and storage. This paper intends to provide efficient short-term forecasting of solar p...
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Photovoltaic (PV) modules convert renewable and sustainable solar energy into electricity. However, the uncertainty of PV power production brings challenges for the grid operation. To facilitate the management and scheduling of PV power plants, forecasti...
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Chao Huang, Longpeng Cao, Nanxin Peng, Sijia Li, Jing Zhang, Long Wang, Xiong Luo and Jenq-Haur Wang
Photovoltaic (PV) modules convert renewable and sustainable solar energy into electricity. However, the uncertainty of PV power production brings challenges for the grid operation. To facilitate the management and scheduling of PV power plants, forecasti...
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Claudio Monteiro, Tiago Santos, L. Alfredo Fernandez-Jimenez, Ignacio J. Ramirez-Rosado and M. Sonia Terreros-Olarte
This paper proposes a new model for short-term forecasting of electric energy production in a photovoltaic (PV) plant. The model is called HIstorical SImilar MIning (HISIMI) model; its final structure is optimized by using a genetic algorithm, based on d...
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