Mapping Photovoltaic Soiling Using Spatial Interpolation Techniques

Leonardo Micheli, Michael Deceglie, Matthew Muller

Research output: Contribution to journalArticlepeer-review

21 Scopus Citations

Abstract

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%.

Original languageAmerican English
Article number8490659
Pages (from-to)272-277
Number of pages6
JournalIEEE Journal of Photovoltaics
Volume9
Issue number1
DOIs
StatePublished - Jan 2019

Bibliographical note

Publisher Copyright:
© 2011-2012 IEEE.

NREL Publication Number

  • NREL/JA-5K00-71624

Keywords

  • Map
  • photovoltaic (PV) systems
  • soiling
  • spatial interpolation

Fingerprint

Dive into the research topics of 'Mapping Photovoltaic Soiling Using Spatial Interpolation Techniques'. Together they form a unique fingerprint.

Cite this