Snow-Induced PV Loss Modeling Using Production-Data Inferred PV System Models

Michiel van Noord, Tomas Landelius and Sandra Andersson
Additional contact information
Michiel van Noord: RISE Research Institutes of Sweden, Division Built Environment, Energy and Resources, Box 5604, SE-114 86 Stockholm, Sweden
Tomas Landelius: Swedish Meteorological and Hydrological Institute (SMHI), SE-601 76 Norrköping, Sweden
Sandra Andersson: Swedish Meteorological and Hydrological Institute (SMHI), SE-601 76 Norrköping, Sweden

Energies, 2021, vol. 14, issue 6, 1-19

Abstract: Snow-induced photovoltaic (PV)-energy losses (snow losses) in snowy and cold locations vary up to 100% monthly and 34% annually, according to literature. Levels that illustrate the need for snow loss estimation using validated models. However, to our knowledge, all these models build on limited numbers of sites and winter seasons, and with limited climate diversity. To overcome this limitation in underlying statistics, we investigate the estimation of snow losses using a PV system’s yield data together with freely available gridded weather datasets. To develop and illustrate this approach, 263 sites in northern Sweden are studied over multiple winters. Firstly, snow-free production is approximated by identifying snow-free days and using corresponding data to infer tilt and azimuth angles and a snow-free performance model incorporating shading effects, etc. This performance model approximates snow-free monthly yields with an average hourly standard deviation of 6.9%, indicating decent agreement. Secondly, snow losses are calculated as the difference between measured and modeled yield, showing annual snow losses up to 20% and means of 1.5–6.2% for winters with data for at least 89 sites. Thirdly, two existing snow loss estimation models are compared to our calculated snow losses, with the best match showing a correlation of 0.73 and less than 1% bias for annual snow losses. Based on these results, we argue that our approach enables studying snow losses for high numbers of PV systems and winter seasons using existing datasets.

Keywords: PV system modeling; PV system performance; snow losses; reanalysis data; remote sensing; soiling; shading; snow; photovoltaics (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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