Nanocoated solar panel cleaning system using high pressure water jet nozzle

Currently, renewable energy sources are seen as feasible solutions for solving the concerns of global warming and stabilizing the energy crisis. The most accessible kind of renewable energy is solar energy. Solar photovoltaic (PV) modules are used to turn the heat energy from the sun’s energy into electricity, which can then be consumed. The solar PV modules are often employed in arid locations, such as desert areas, where there is an abundance of heat, sand, dust particles, etc. As a result, dust particles gathers on photovoltaic panels, decreasing the amount of sunlight that reaches the photovoltaic cells and thus minimizing the overall power output. As a result, cleaning the solar panels has become absolutely essential. However, cleaning the panels is extremely difficult if the plant size is large, requiring large amount of water and being expensive. Overall, cleaning the panels is a laborious and time-consuming task, also brushing them may cause damage. As a result, a contact-less cleaning system has developed which consist of high pressure jet nozzle that sprays compressed air and pressurized water to remove dust and hard stains. CFD analysis was conducted on the nozzle using ANSYS software to determine the ideal velocity applied by air and water on panels and the area covered by the nozzles in order to improve the panel’s efficiency, their lifespan, and to minimize water waste. The project’s objective is to showcase a contact-less cleaning system and finding out the effectiveness of anti-reflective and self-cleaning NanoCoating SiO2 and TiO2 on solar panel surface in terms of efficiency of solar panels. Self-cleaning NanoCoating is used to improve light transmission and preventing any form of dust from adhering. It eliminate dust and other sticky particles from the panels while consuming less water, hence enhancing solar panel’s capacity to generate electricity. In addition, Cost Analysis and Data Analysis was conducted on the power generated data which was collected for three respective months in the years 2020 (Uncoated and Irregular cleaning), 2021 (Uncoated and regular cleaning), & 2022 (NanoCoating with regular cleaning) to examine the effectiveness of cleaning in terms of power generation and to evaluate the cost required for cleaning.