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Title: A Method to Extract Soiling Loss Data from Soiling Stations with Imperfect Cleaning Schedules: Preprint

Abstract

Typical PV soiling stations determine the natural soiling losses by comparing the output of a naturally soiled PV cell to that of a PV cell maintained in the clean state. Inadequate cleaning frequency or human error provides opportunity for the cleaned cell to soil, directly resulting in error in the reported soiling ratio. This work investigates an algorithm to automatically detect and correct the data stream for errors associated with soiling of the clean cell. The methodology is tested on several soiling stations with irregular cleaning schedules as well as a soiling station where both ideal and imperfect cleaning schedules are in place. The initial results show that the algorithm can reduce error associated with imperfect cleaning but also confirms the benefits of maintaining an optimal cleaning schedule.

Authors:
ORCiD logo [1];  [2];  [3]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. National Renewable Energy Laboratory (NREL), Golden, CO (United States); Colorado School of Mines
  3. University of California, Riverside
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:
1458903
Report Number(s):
NREL/CP-5J00-68225
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 44th IEEE Photovoltaic Specialists Conference, 25-30 June 2017, Washington, D.C.
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; PV soiling; soiling algorithm; cleaning schedule

Citation Formats

Micheli, Leonardo, Muller, Matthew T, and Martinez-Morales, Alfredo A. A Method to Extract Soiling Loss Data from Soiling Stations with Imperfect Cleaning Schedules: Preprint. United States: N. p., 2018. Web.
Micheli, Leonardo, Muller, Matthew T, & Martinez-Morales, Alfredo A. A Method to Extract Soiling Loss Data from Soiling Stations with Imperfect Cleaning Schedules: Preprint. United States.
Micheli, Leonardo, Muller, Matthew T, and Martinez-Morales, Alfredo A. Thu . "A Method to Extract Soiling Loss Data from Soiling Stations with Imperfect Cleaning Schedules: Preprint". United States. doi:. https://www.osti.gov/servlets/purl/1458903.
@article{osti_1458903,
title = {A Method to Extract Soiling Loss Data from Soiling Stations with Imperfect Cleaning Schedules: Preprint},
author = {Micheli, Leonardo and Muller, Matthew T and Martinez-Morales, Alfredo A},
abstractNote = {Typical PV soiling stations determine the natural soiling losses by comparing the output of a naturally soiled PV cell to that of a PV cell maintained in the clean state. Inadequate cleaning frequency or human error provides opportunity for the cleaned cell to soil, directly resulting in error in the reported soiling ratio. This work investigates an algorithm to automatically detect and correct the data stream for errors associated with soiling of the clean cell. The methodology is tested on several soiling stations with irregular cleaning schedules as well as a soiling station where both ideal and imperfect cleaning schedules are in place. The initial results show that the algorithm can reduce error associated with imperfect cleaning but also confirms the benefits of maintaining an optimal cleaning schedule.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jun 28 00:00:00 EDT 2018},
month = {Thu Jun 28 00:00:00 EDT 2018}
}

Conference:
Other availability
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