Mapping Photovoltaic Soiling Using Spatial Interpolation Techniques

Micheli, Leonardo; Deceglie, Michael G.; Muller, Matthew

doi:10.1109/JPHOTOV.2018.2872548

Title: Mapping Photovoltaic Soiling Using Spatial Interpolation Techniques

Journal Article · Fri Oct 12 00:00:00 EDT 2018 · IEEE Journal of Photovoltaics

DOI:https://doi.org/10.1109/JPHOTOV.2018.2872548· OSTI ID:1479873

Micheli, Leonardo ^[1]; Deceglie, Michael G. ^[1]; Muller, Matthew ^[2]

National Renewable Energy Lab. (NREL), Golden, CO (United States)
National Renewable Energy Lab. (NREL), Golden, CO (United States); Univ. de Jaen (Spain); Leidos, Denver, CO (United States)

In this paper, we present a new soiling map developed at the National Renewable Energy Laboratory, showing data from 83 sites in the United States. Soiling has been measured through soiling stations or extracted by photovoltaic system performance data using referenced techniques. The data on the map have been used to conduct the first regional analysis of soiling distribution in the United States. We found that most of the soiling occurs in the southwestern United States, with Southern California counties experiencing the greatest losses because of the high particulate matter concentrations and the long dry periods. Moreover, we employed five spatial-interpolation techniques to investigate the possibility of estimating soiling at a site using data from nearby sites. We found that coefficients of determination of up to 78% between estimated and measured soiling ratios, meaning that, by using selective sampling, soiling losses can be predicted using the data on the map with a root-mean-square error of as low as 1.1%.

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