Building Model for Forecasting Dust Situation on Surface Photovoltaic Panel Based on Operation Data in Vietnam
摘要
This study focuses on calculating and predicting the deterioration in the photovoltaic conversion performance of solar panels due to the impact of the outdoors (mostly dust) on real data obtained from a rooftop solar farm at Da Nang Milk Plant. The linear regression method is employed to make initial predictions on the decline in performance resulting from many parameters, including panel surface clarity, temperature, tilt angle, radiation intensity, dirt, shade, and other technical considerations. The results of this study indicate a notable decline in the operational efficiency of the solar cells. Specifically, we highlight the importance of dust collection on the cell’s surface, which has a detrimental impact on the photovoltaic conversion capacity of the panels, resulting in a reduction in the overall output of the system. Hence, engaging in maintenance activities such as washing, cleaning, and maintaining cell panels can effectively enhance their conversion efficiency. In light of the projected outcomes pertaining to performance and cost reductions in sanitation services offered by enterprises in Vietnam, we present a cost-optimized function alongside the most efficient approach for operating and maintaining the system. In summary, our study yielded initial prediction findings regarding the decline in solar cell efficiency and proposed a maintenance and cleaning regimen that could result in substantial cost savings throughout the lifespan of the solar cells.