publication . Article . Other literature type . 2018

quantifying soiling loss directly from pv yield

Deceglie, Michael G.; Micheli, Leonardo; Muller, Matthew;
Open Access
  • Published: 01 Mar 2018 Journal: IEEE Journal of Photovoltaics, volume 8, pages 547-551 (issn: 2156-3381, eissn: 2156-3403, Copyright policy)
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
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 br...
Subjects
free text keywords: Electrical and Electronic Engineering, Electronic, Optical and Magnetic Materials, Condensed Matter Physics, Reliability engineering, Optics, business.industry, business, Time series, Photovoltaic system, Physics, Monte Carlo method, Solar energy
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publication . Article . Other literature type . 2018

quantifying soiling loss directly from pv yield

Deceglie, Michael G.; Micheli, Leonardo; Muller, Matthew;