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Improving the performance of photovoltaic panels integrated with ultrasound and phase change materials: experimental study and CFD modeling
New phase change materials (PCMs) and ultrasound energy are used to enhance the performance of a photovoltaic (PV) panel. Design of experiment (DOE) method is applied to optimize the surface temperature and output power of the PV panel. In response surface methodology (RSM), volume fraction of glyce...
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Published in: | Journal of thermal analysis and calorimetry 2024-08, Vol.149 (15), p.8193-8213 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | New phase change materials (PCMs) and ultrasound energy are used to enhance the performance of a photovoltaic (PV) panel. Design of experiment (DOE) method is applied to optimize the surface temperature and output power of the PV panel. In response surface methodology (RSM), volume fraction of glycerol in the mixture of oleic acid and beeswax (0–50%), mass fraction of CuO nanoparticles (0–5%) and solar intensity (500–1000Wm
−2
) is investigated as three key parameters. At first, an experimental work is conducted in which a U-shape tube is installed inside the enclosure containing PCM with cold water flow. Secondly, CFD modeling is applied to propose a new method for the heat removal from the PCM integrated with the PV panel. A cold water jacket equipped with 1.7 MHz ultrasound waves is inserted instead of the U-shape tube and surrounds the PCM enclosure. Experimental data showed that the PCM with 22.52% glycerol shows the highest PV power. Adding 5%CuO nanoparticles to PCMs caused minimum temperature and the maximum power of the PV panel. Using U-shape tube at optimum condition led to electrical efficiency about 14.33%. CFD data proved that propagation of 1.7 MHz ultrasonic into water jacket led to remarkable reduction in the PV temperature compared to applying the U-shape tube. CFD results demonstrated a good agreement with experimental data with maximum error of 0.97%. |
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ISSN: | 1388-6150 1588-2926 |
DOI: | 10.1007/s10973-024-13295-1 |