IoT Based Framework: Mathematical Modelling and Analysis of Dust Impact on Solar Panels

The solar photovoltaic performance is governed by manifold parameters viz. temperature, irradiance, dust on solar module, photoactive material, panel orientation. Among these dust is a critical impediment, as its accumulation on panel surface degrades its productivity; while frequent cleaning sessions affect module's life and result into PV destruction. Accordingly, the need to know dust thickness responsible for deteriorating panel's capability and adequate cleaning time of solar panels to produce optimum yields is requisite. This paper aims to discern a right cleaning time, owing to a particular dust thickness so as to conserve the panel efficiency using internet of things (IoT). The mathematical correlations of PV efficiency and current with thickness of accumulated dust are derived using linear regression. Further, these equations are associated with an IoT-based platform which remotely monitors and records PV output current; thereafter dust thickness corresponding to a significant current reduction is estimated. For this, experimental data of 46 inverters with total 114,819.30kWh productions in a month with an average of 4416.13kWh/day is accessed and the results pertaining to mathematical analysis exhibit a decline in current by 1A with 5.51x10(-3)mm thickness of dust.