Predicting solar photovoltaic electrical output under variable environmental conditions: Modified semi-empirical correlations for dust.

The current study investigated the simultaneous impacts of dust as well as other environmental parameters on cell temperature and the electrical outputs of photovoltaic systems. Based on the experimental and analytical analysis, several linear and polynomial semi-empirical correlation forms were proposed. It was shown that cell temperature depends directly on irradiation and ambient temperature, as well as inversely on humidity, wind speed, and the amount of accumulated dust on the surface. During the four-year outdoor experiments and further indoor measurements, the surface dust density varied from 0 to 10.1174 g.m⁻², which resulted in up to a 28 % current loss. Although, it was shown that dust affects the output voltage less, and the most recorded variation was <0.5 % reduction. The electrical behavior of the photovoltaic system was also simulated with a modified single-diode model. Comparing the simulation results, correlation predictions, and experimental measurements confirmed consistency. Moreover, it was shown that considering the prediction precision, simplicity, and computational cost, the proposed correlation forms should be preferred when just the output current, voltage, and power are of concern. The proposed modified semi-empirical correlation forms can be easily coupled with other models to improve their precision and accuracy. • Experimental investigation of parameters affecting a photovoltaic cell temperature. • Provide a semi-empirical correlation form to predict cell temperature. • Provide semi-empirical correlation forms to predict output current and voltage. • Provide semi-empirical correlation forms to predict output power. • Increase precision and reduce computational costs for predicting output behavior. [ABSTRACT FROM AUTHOR]