Abstract
Soiling of photovoltaic (PV) panels is typically quantified through the use of specialized sensors. Here, we describe and validate a method for estimating soiling loss experienced by PV systems directly from system yield without the need for precipitation data. The method, termed the stochastic rate and recovery (SRR) method, automatically detects soiling intervals in a dataset, then stochastically generates a sample of possible soiling profiles based on the observed characteristics of each interval. In this paper, we describe the method, validate it against soiling station measurements, and compare it with other PV-yield-based soiling estimation methods. The broader application of the SRR method will enable the fleet scale assessment of soiling loss to facilitate mitigation planning and risk assessment.
Original language | American English |
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Pages (from-to) | 547-551 |
Number of pages | 5 |
Journal | IEEE Journal of Photovoltaics |
Volume | 8 |
Issue number | 2 |
DOIs | |
State | Published - 2018 |
Bibliographical note
Publisher Copyright:© 2011-2012 IEEE.
NREL Publication Number
- NREL/JA-5J00-70668
Keywords
- Field performance
- Monte Carlo methods
- photovoltaic cells
- photovoltaic systems
- soiling
- solar energy
- solarpanels
- time series analysis