Self-cleaning of photovoltaic modules: The role of liquid droplets on hydrophobic surfaces in surface dust removal

Dust accumulation on photovoltaic (PV) panels reduces their energy efficiency. Although droplets play a crucial role in the self-cleaning of dust on the surface of PV panels, the underlying mechanism of surface dust self-cleaning in the presence of droplets has not been fully understood. This study aims to investigate the dust removal mechanisms on the surface of blank and coated PV panels and analyze the effects of factors such as dust particle size, PV panel tilt angle, and ash density on droplet self-cleaning efficiency. Our experiments show that superhydrophobic coatings can significantly improve the droplet self-cleaning efficiency and output power of PV panels. The maximum relative power recovery rate of the coated sample is 78.53%, which is much higher than 27.83% of the blank sample. To better understand the droplet self-cleaning mechanism, we analyze the differences in droplet self-cleaning between blank and coated PV panels from a mechanical perspective. Our model explains the main forces and motion modes of dust particles in the presence of droplets, and we find that smaller dust particles are easier to remove than larger particles. Additionally, we find that a smaller inclination angle of the PV panel surface inhibits the dust particle removal process. Finally, we conduct a comparative study between droplet self-cleaning and other self-cleaning methods to evaluate their effectiveness. Our results show that droplet self-cleaning is a more efficient and effective method for removing dust from PV panels.

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Publication Details

Journal
Journal of Renewable and Sustainable Energy
Published
2024-11-01
DOI
https://doi.org/10.1063/5.0234282
Citations
7
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.72

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article

Self-cleaning of photovoltaic modules: The role of liquid droplets on hydrophobic surfaces in surface dust removal

Caijin Fan, Yue Shen, Jingya Zeng, Xinlong Yan et al.
7 citations
Journal of Renewable and Sustainable Energy
Photovoltaic System Optimization Techniques
0.72
article

Self-cleaning of photovoltaic modules: The role of liquid droplets on hydrophobic surfaces in surface dust removal

Caijin Fan, Yue Shen, Jingya Zeng, Xinlong Yan, Wang Ping, C. H. Cheng
article en
7 citations

Abstract

Dust accumulation on photovoltaic (PV) panels reduces their energy efficiency. Although droplets play a crucial role in the self-cleaning of dust on the surface of PV panels, the underlying mechanism of surface dust self-cleaning in the presence of droplets has not been fully understood. This study aims to investigate the dust removal mechanisms on the surface of blank and coated PV panels and analyze the effects of factors such as dust particle size, PV panel tilt angle, and ash density on droplet self-cleaning efficiency. Our experiments show that superhydrophobic coatings can significantly improve the droplet self-cleaning efficiency and output power of PV panels. The maximum relative power recovery rate of the coated sample is 78.53%, which is much higher than 27.83% of the blank sample. To better understand the droplet self-cleaning mechanism, we analyze the differences in droplet self-cleaning between blank and coated PV panels from a mechanical perspective. Our model explains the main forces and motion modes of dust particles in the presence of droplets, and we find that smaller dust particles are easier to remove than larger particles. Additionally, we find that a smaller inclination angle of the PV panel surface inhibits the dust particle removal process. Finally, we conduct a comparative study between droplet self-cleaning and other self-cleaning methods to evaluate their effectiveness. Our results show that droplet self-cleaning is a more efficient and effective method for removing dust from PV panels.

Journal of Renewable and Sustainable EnergyVol. 16(6)
Electric Power Research Institute (US), Chongqing University (CN), New Technology (Israel) (IL)
China Southern Power Grid
Openalex Percentile: Top 35%
Photovoltaic System Optimization Techniques
0.72
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