An investigation of the key parameters for predicting PV soiling losses. (25th January 2017)

• Record Type: Journal Article
• Authors: Micheli, Leonardo; Muller, Matthew
• Is Part Of: Progress in photovoltaics. Volume 25:Number 4(2017)
• Page Start: 291
• Page End: 307
• Publication Date: 2017-01-25
• Subjects: soiling -- photovoltaic performance -- soiling losses -- particulate matter -- precipitation -- linear regression; Solar cells -- Periodicals; Photovoltaic cells -- Periodicals; Solar power plants -- Periodicals; 621.31245
• DOI: 10.1002/pip.2860
• Languages: English
• ISSNs: 1062-7995

Abstract

Abstract: One hundred and two environmental and meteorological parameters have been investigated and compared with the performance of 20 soiling stations installed in the USA, in order to determine their ability to predict the soiling losses occurring on PV systems. The results of this investigation showed that the annual average of the daily mean particulate matter values recorded by monitoring stations deployed near the PV systems are the best soiling predictors, with coefficients of determination ( R 2 ) as high as 0.82. The precipitation pattern was also found to be relevant: among the different meteorological parameters, the average length of dry periods had the best correlation with the soiling ratio. A preliminary investigation of two‐variable regressions was attempted and resulted in an adjusted R 2 of 0.90 when a combination of PM2.5 and a binary classification for the average length of the dry period was introduced. Copyright © 2017 John Wiley & Sons, Ltd. Abstract : Coefficient of determination of the linear single‐variable correlations between the most significant soiling predictors considered in this study and the soiling ratios registered by 20 PV systems deployed in the USA.