This research aims to experimentally improve the overall eciency of solar photovoltaic
(PV) panels by coating them with hydrophobic SiO2 nanomaterial. Also, an accurate mathematical
model was used to estimate the parameters of the PV panel, which is a non-linear optimization
problem. Based on the experimental data and using the particle swarm optimization (PSO) algorithm,
the optimal five parameters of a single diode model of a PV panel were determined in this study.
This experimental work was conducted and carried out in the Renewable Energy Laboratory of Assiut
University, Egypt. A comparative analysis was completed for three identical solar PV panels; the first
panel was coated with hydrophobic SiO2 nanomaterial, so it was considered to be a self-cleaning
panel; the second panel was uncoated and cleaned manually on a daily basis; and the third panel
was kept dusty all the time through the experimental investigation, and was used as a reference.
Experimentally, the output power of the PV panels was monitored for each panel in this study.
Also, the anti-static and anti-reflection eects of coating solar PV panels with hydrophobic SiO2
nanomaterial were investigated experimentally. According to the obtained experimental results,
it was found that the use of SiO2 coating for PV panels results in the better performance of the PV
panels. The overall eciency of the coated panel increased by 15% and 5%, compared to the dusty
panel and the uncoated panel which was manually cleaned daily, respectively.