Photovoltaic panel cleaning device installation plan

How to clean a PV panel?

Consequently, specific cleaning techniques are required to mitigate the accumulated dust and restore the plant's efficiency. The most popular PV panel cleaning techniques include natural, manual, automatic, and electrostatic cleaning. Each cleaning technique is associated with both positive and negative impacts.

Which cleaning technique is best for solar PV panels?

The TOPSIS method is employed to compare the cleaning techniques and rank them from most favored to least favored. Manual cleaning of the PV panels is the highest ranked cleaning technique according to the TOPSIS ranking. The efficiency and power output of photovoltaic (PV) panels are vital to the solar PV plant.

How many solar PV panels are used in a cleaning robot?

Two solar PV panels are connected in series, the capacity of each panel is 335 W, and their total is 670 W, to test, operate, and evaluate the proposed cleaning robot. The specifications of the solar PV panel used are shown in Table 1.

How often should PV solar panels be cleaned?

As a result, there are many recommendations that cleaning operations for PV solar panels should be carried out regularly. As strongly recommended, the photovoltaic panels are cleaned 3 to 4 times a year, especially that weather conditions are not extreme, and this number of cleaning processing should increase during dry periods.

How long does it take to clean solar panels?

As a result of the great variance in the results of the power produced by the different solar panels in the degree of surface cleanliness, the cleaning robot was operated to clean the dust-density gradient solar panels, where the time required to carry out one cleaning round was from 10 seconds at a speed of 300 rpm = ~ (0.7 m/s).

How can a PV system be optimally cleaned?

The need for an optimal cleaning intervention by using advanced scientific tools rather than by visual inspection is drawing the attention of PV experts. The authors finally suggest a schematic of a decision-making model which involves the use of probable parameters, data processing techniques and machine learning tools.