The increasing adoption of solar photovoltaic systems has brought attention to performance degradation factors, such as soiling, that hinder their efficiency. This study investigates the impact of dust particle thermophysical properties on solar cell temperature and energy losses, using transient thermal analysis and computational fluid dynamics simulations to analyse the complex interactions between dust and solar panels specifically focusing on solar cell temperature. By analyzing dust particle thermophysical characteristics and their interaction with solar collectors, this study provides a comprehensive understanding of performance degradation in solar energy systems. Simulation results reveal that velocity distributions around the solar panel, particularly in low-pressure zones and regions of high turbulence, significantly affect dust dispersion and deposition. Thermal emissions from the panel further influence dust accumulation through thermophoresis. Response surface methodology and contour analysis identified dust particle size as the most critical factor affecting cell temperature, followed by density and specific heat capacity. Thermal conductivity exhibited an inverse relationship with cell temperature, acting as an insulator at lower values. The developed response surface model demonstrated high accuracy (R2 = 0.9964) and statistical significance (p-value = 0.0001), predicting temperature variations based on different dust thermophysical parameters. Energy computations, extrapolated from the computational fluid dynamics and thermal simulations for a 50 kW grid-tied solar system over six months, indicated an overall energy loss of 18.93 %, due to transmittance loss (14.89 %), normal cell temperature rise (3.31 %), and temperature rise due to soiling (0.73 %). The study further revealed an overall revenue loss of 4.3 %, with 0.83 % attributed to thermal losses due to soiling. By understanding the influence of dust particle characteristics on solar cell temperature and performance, the findings can inform better maintenance practices and improve long-term energy yield predictions for solar installations.