Dust deposition effect on photovoltaic modules performance and optimization of cleaning period: A combined experimental–numerical study. (June 2022)

• Record Type: Journal Article
• Authors: Yazdani, Hamed; Yaghoubi, Mahmood
• Is Part Of: Sustainable energy technologies and assessments. Volume 51(2022)
• Publication Date: 2022-06
• Subjects: Photovoltaic soiling loss -- Maximum power point -- Short-circuit current -- PV power plant -- Optimal cleaning frequency -- Sensitivity analysis; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2021.101946
• Languages: English
• ISSNs: 2213-1388

Abstract

Highlights: Comparison between short-circuit current and power losses of PV module was done. The statistical analysis was conducted to support the findings in the study. Simple experimental models for estimating soiling efficiency loss were presented. Soiling short-circuit current loss underestimates actual power loss by about 9%. Variation in weather conditions can significantly change optimal cleaning schedule. Abstract: The main purposes of this study are: i) evaluating magnitude of error in predicting soiling power loss of photovoltaic (PV) modules based on the measurement of short-circuit current; ii) presenting simple experimental models for estimating dust effect on the PV power generation; and finally iii) finding an optimal cleaning schedule for a utility-scale solar power station located in a semi-arid environment. The results showed that, on average, soiling short-circuit current loss underestimates actual soiling power loss by approximately 9%, and with increasing dust density this value also increases. The soiling rate in the first week of dust deposition was evaluated to be 0.27%/day, meanwhile, for the last week it was 0.13%/day. This observation confirmed that the exponential model is more accurate than linear and power relations for estimating dust effect on PV systems in the case study. The optimal cleaning period of a solar farm was obtained 17.50 and 6.39 days, for the manual and machine-assisted washing methods, respectively. The sensitivity analysis regarding the effect of environmental variables on the optimal cleaning period was addressed at last. The results indicated that such analysis is necessary in order to find a reliable estimate for optimal cleaning period in PV power plants.