Enhance the performance of photovoltaic solar panels by a self-cleaning and hydrophobic nanocoating

Tayel, Samir; El-Maaty, Ashour Eid Abu; Mostafa, Eman Mohamed; El-Saadawi, Y. F.

doi:10.1038/s41598-022-25667-4

Cited by 12 publications

(3 citation statements)

References 23 publications

(24 reference statements)

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“…As shown in Figure 9c, the friction of the sandpaper on the coating caused rough structures on the coating surface, which may also be the reason for some upward fluctuations in the contact angle. Most of the gradual deterioration in the hydrophobicity is due to the destruction of some protrusions on the coating surface, and the wear marks become more and more visible with increasing wear cycles [23,24]. In contrast, the nanoscale flat surface coating improved the hydrophobic degradation due to the destruction of the surface rough structure compared to most reported stable hydrophobic coatings, showing better mechanical stability and maintaining its hydrophobicity even after 200 cycles.…”

Section: Mechanical Robustness and Self-cleaning Performance Of The C...mentioning

confidence: 99%

Micron-Smooth, Robust Hydrophobic Coating for Photovoltaic Panel Surfaces in Arid and Dusty Areas

Guo,

Wang,

et al. 2024

Coatings

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Photovoltaic (PV) power generation is a clean energy source, and the accumulation of ash on the surface of PV panels can lead to power loss. For polycrystalline PV panels, self-cleaning film is an economical and excellent solution. However, the main reasons why self-cleaning coatings are currently difficult to use on a large scale are poor durability and low transparency. It is a challenge to improve the durability and transparency of self-cleaning thin films for PV panel surface against ash accumulation. Therefore, in this paper, a resin composite film containing modified silica components was designed and synthesized, mainly by the organic/inorganic composite method. A transparent hydrophobic coating with nano-micro planar structures was constructed, which primarily relies on the hydrophobic properties of the compound itself to build the hydrophobic oleophobic coating. The layer has a micrometer-scale smooth surface structure and high transparency, with a 0.69% increase in light transmittance compared with uncoated glass, and the durability is good. It is mainly applied to the surface of photovoltaic devices, which can alleviate the dust accumulation problem of photovoltaic panels in arid, high-temperature, and dusty areas and reduce the maintenance cost of them.

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Section: Mechanical Robustness and Self-cleaning Performance Of The C...mentioning

confidence: 99%

Micron-Smooth, Robust Hydrophobic Coating for Photovoltaic Panel Surfaces in Arid and Dusty Areas

Guo,

Wang,

et al. 2024

Coatings

View full text Add to dashboard Cite

show abstract

“…Dust is one of the most critical environmental factors affecting the performance of solar panels and belongs to the category of irreversible factors. It can reduce the performance of PV panels by causing physical damage, reducing incoming solar radiation, increasing the temperature, and altering the electrical properties of the panel 9 , 10 . The degree of depreciation depends mainly on the deposit concentration and is controlled by several factors.…”

Section: Introductionmentioning

confidence: 99%

A stacking ensemble classifier-based machine learning model for classifying pollution sources on photovoltaic panels

Byun

Jeong

2023

Sci Rep

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Solar energy is a very efficient alternative for generating clean electric energy. However, pollution on the surface of solar panels reduces solar radiation, increases surface transmittance, and raises the surface temperature. All these factors cause photovoltaic (PV) panels to be less efficient. To address this problem, a stacking ensemble classifier-based machine learning model is proposed. In this study, different sources of pollution on each solar panel are used, and their power generation is recorded. The proposed model includes gradient boost, extra tree, and random forest classifiers, with the extra tree classifier serving as a meta-learner. The model takes into account various weather features during the training process, including irradiance and temperature, aiming to increase its accuracy and robustness in identifying pollution sources on the PV panel. Moreover, the proposed model is evaluated using various methods in order to examine performance metrics such as accuracy, F1 score, and precision. Results show that the model can achieve an accuracy score of 97.37%. The model’s performance is also compared to state-of-the-art machine learning models, demonstrating its superiority in accurately classifying pollution sources on PV panels. By utilizing different sources of pollution and weather features during training, the model can accurately classify different pollution sources, resulting in increased power generation efficiency and the longevity of PV panels. The main results of this study can be used to manage and maintain PV panels since the model can identify PV modules that need to be cleaned to keep producing the most power. Furthermore, the efficiency, reliability, and sustainability of PV panels can be further enhanced by the proposed model.

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“…In this work, we showcase the effectiveness of this approach by applying a nano-structured hydrophobic coat on the surface of a welding electrode with a basic covering. We chose a nanosilica coating due to its specific characteristics: (i) SiO 2 nanoparticles can exhibit hydrophobic characteristics 25 , (ii) SiO 2 is insoluble in water, and (iii) SiO 2 is not expensive. To enhance resistance to moisture absorption, we applied a nanosilica coating on the surface of the E7018 electrode-covering using a simple dip-coating method.…”

Section: Introductionmentioning

confidence: 99%

Nanosilica treatment enables moisture-resistant hydrophobic arc welding covered electrodes

Pasandeh

Pouranvari

2023

Sci Rep

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Controlling the moisture content of the electrode-covering is crucial in the production of defect-free, high-quality welds during shielded metal arc welding of steels. The welding industry has long faced the challenge of the high susceptibility of basic electrodes (e.g., E7018) to moisture absorption. In this paper, we demonstrate that applying a nanosilica coating to the surface of the E7018 electrode-covering using a dip-coating technique can effectively reduce the moisture absorption capability of the electrode-covering. The moisture measurement results before and after exposure to a moist environment of 80% humidity and a temperature of 27 °C for 9 h indicate that the moisture absorption values of conventional and nano-treated E7018 electrodes during exposure are 0.67 wt% and 0.03 wt%, respectively. While reducing the size of the pores on the surface of the electrode-covering can to some extent enhance the resistance to moisture absorption, it has been identified that turning the wetting behavior of the electrode-covering surface from hydrophilic to hydrophobic by the nanosilica coating is the most effective mechanism that contributes to the enhanced moisture absorption resistance of the nanosilica-treated electrode-covering. The results indicate that this approach does not have any deleterious effects on the chemical analysis and tensile properties of the weld metal. This simple modification to the electrode-covering can be generally applied to a wide range of electrode-covering types to produce hydrophobic, moisture-resistant electrodes.

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Enhance the performance of photovoltaic solar panels by a self-cleaning and hydrophobic nanocoating

Cited by 12 publications

References 23 publications

Micron-Smooth, Robust Hydrophobic Coating for Photovoltaic Panel Surfaces in Arid and Dusty Areas

Micron-Smooth, Robust Hydrophobic Coating for Photovoltaic Panel Surfaces in Arid and Dusty Areas

A stacking ensemble classifier-based machine learning model for classifying pollution sources on photovoltaic panels

Nanosilica treatment enables moisture-resistant hydrophobic arc welding covered electrodes

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