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Title: Mapping Photovoltaic Soiling Using Spatial Interpolation Techniques

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%.

Authors:
 [1];  [1];  [2]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States); Univ. de Jaen (Spain); Leidos, Denver, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
OSTI Identifier:
1479873
Report Number(s):
NREL/JA-5K00-71624
Journal ID: ISSN 2156-3381
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
IEEE Journal of Photovoltaics
Additional Journal Information:
Journal Volume: 9; Journal Issue: 1; Journal ID: ISSN 2156-3381
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; 29 ENERGY PLANNING, POLICY, AND ECONOMY; map; photovoltaic (PV) systems; soiling; spatial interpolation

Citation Formats

Micheli, Leonardo, Deceglie, Michael G., and Muller, Matthew. Mapping Photovoltaic Soiling Using Spatial Interpolation Techniques. United States: N. p., 2018. Web. doi:10.1109/JPHOTOV.2018.2872548.
Micheli, Leonardo, Deceglie, Michael G., & Muller, Matthew. Mapping Photovoltaic Soiling Using Spatial Interpolation Techniques. United States. https://doi.org/10.1109/JPHOTOV.2018.2872548
Micheli, Leonardo, Deceglie, Michael G., and Muller, Matthew. 2018. "Mapping Photovoltaic Soiling Using Spatial Interpolation Techniques". United States. https://doi.org/10.1109/JPHOTOV.2018.2872548. https://www.osti.gov/servlets/purl/1479873.
@article{osti_1479873,
title = {Mapping Photovoltaic Soiling Using Spatial Interpolation Techniques},
author = {Micheli, Leonardo and Deceglie, Michael G. and Muller, Matthew},
abstractNote = {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%.},
doi = {10.1109/JPHOTOV.2018.2872548},
url = {https://www.osti.gov/biblio/1479873}, journal = {IEEE Journal of Photovoltaics},
issn = {2156-3381},
number = 1,
volume = 9,
place = {United States},
year = {Fri Oct 12 00:00:00 EDT 2018},
month = {Fri Oct 12 00:00:00 EDT 2018}
}

Journal Article:
Free Publicly Available Full Text
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Cited by: 13 works
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Figures / Tables:

Fig. 1 Fig. 1: Screenshot of the soiling map published in October 2017 on www.nrel.gov/pv/soiling.html. Triangular markers (▲) are are soiling stations; squared markers (■) are PV installations. The markers are color-coded according to the severity of soiling.

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Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.