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Title: Quantifying Year-to-Year Variations in Solar Panel Soiling from PV Energy-Production Data

Abstract

We present a method for quantifying solar panel soiling loss from PV energy-production data and show how it can be used to quantify year-to-year variations in soiling loss. Cleaning events are automatically detected, eliminating the need for precipitation data or assumptions about cleaning. The method also calculates the reduction of energy yield due to soiling, not just a soiling rate. We apply the method annually and also to multi-year datasets. We find significant year-to-year variation in soiling loss, a result with important implications for site planning and financing. The method presented here can leverage existing datasets of daily energy yield to quantify annual and total soiling risk without the need for new hardware and serves as a supplement to standard plant planning practices.

Authors:
 [1]; ORCiD logo [1];  [1]
  1. National Renewable Energy Laboratory (NREL), Golden, 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), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1514829
Report Number(s):
NREL/CP-5K00-67848
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2017 IEEE 44th Photovoltaic Specialist Conference (PVSC), 25-30 June 2017, Washington, D.C.
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; 47 OTHER INSTRUMENTATION; inverters; harmonics; power quality; inverter stability; resonances; Thevenin equivalent

Citation Formats

Deceglie, Michael G, Micheli, Leonardo, and Muller, Matthew. Quantifying Year-to-Year Variations in Solar Panel Soiling from PV Energy-Production Data. United States: N. p., 2018. Web. doi:10.1109/PVSC.2017.8366290.
Deceglie, Michael G, Micheli, Leonardo, & Muller, Matthew. Quantifying Year-to-Year Variations in Solar Panel Soiling from PV Energy-Production Data. United States. doi:10.1109/PVSC.2017.8366290.
Deceglie, Michael G, Micheli, Leonardo, and Muller, Matthew. Mon . "Quantifying Year-to-Year Variations in Solar Panel Soiling from PV Energy-Production Data". United States. doi:10.1109/PVSC.2017.8366290.
@article{osti_1514829,
title = {Quantifying Year-to-Year Variations in Solar Panel Soiling from PV Energy-Production Data},
author = {Deceglie, Michael G and Micheli, Leonardo and Muller, Matthew},
abstractNote = {We present a method for quantifying solar panel soiling loss from PV energy-production data and show how it can be used to quantify year-to-year variations in soiling loss. Cleaning events are automatically detected, eliminating the need for precipitation data or assumptions about cleaning. The method also calculates the reduction of energy yield due to soiling, not just a soiling rate. We apply the method annually and also to multi-year datasets. We find significant year-to-year variation in soiling loss, a result with important implications for site planning and financing. The method presented here can leverage existing datasets of daily energy yield to quantify annual and total soiling risk without the need for new hardware and serves as a supplement to standard plant planning practices.},
doi = {10.1109/PVSC.2017.8366290},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {11}
}

Conference:
Other availability
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