Integration of Sensors for Monitoring and Analysis of Photovoltaic and Atmospheric Parameters

This study focuses on the impact of local atmospheric conditions on photovoltaic panels and their effect on power generation. The study aimed to develop multiple linear regression models that relate meteorological variables, dust, and the panel's output parameters with its generated power. An experiment was conducted using two identical photovoltaic panels installed in Mexicali, Baja California, Mexico; one panel was kept clean and the other dirty, and both were exposed to the arid conditions characterizing the region. These photovoltaic systems were integrated with a weather station, radiometric sensors, and a dust collection mechanism. Meteorological parameters, short-wave radiation, and the amount of dust deposited, were measured. The results indicated that dust accumulation reduces energy generation efficiency in photovoltaic panels and increases the reflection of short-wave radiation. Linear regression was used to quantify the influence of the parameters on the power generated by the dirty panel, which amounted to between 57% and 94 % for the atmospheric parameters involved.