Extracting and Generating PV Soiling Profiles for Analysis, Forecasting, and Cleaning Optimization

Journal Article · Fri Oct 23 00:00:00 EDT 2020 · IEEE Journal of Photovoltaics

DOI:https://doi.org/10.1109/jphotov.2019.2943706· OSTI ID:1593090

Micheli, Leonardo ^[1]; Fernandez, Eduardo F. ^[1]; Muller, Matthew ^[2]; Almonacid, Florencia ^[1]

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1. Univ. of Jaen (Spain)
2. National Renewable Energy Lab. (NREL), Golden, CO (United States)

The identification and prediction of the daily soiling profiles of a photovoltaic site is essential to plan the optimal cleaning schedule. In this article, we analyze and propose various methods to extract and generate photovoltaic soiling profiles, in order to improve the analysis and the forecast of the losses. New soiling rate extraction methods are proposed to reflect the seasonal variability of the soiling rates and, for this reason, are found to identify the most convenient cleaning day with the highest accuracy for the investigated sites. Also, we present an approach that could be used to predict future soiling losses through the implementation of stochastic weather generation algorithms whose ability to identify in advance the best cleaning schedule is also successfully tested. The methods presented in this article can optimize the operation and maintenance schedule and could make it possible, in the future, to predict soiling losses through analysis based only on environmental parameters, such as rainfall and particulate matter, without the need of long-term soiling data.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: European Union’s Horizon 2020 research and innovation programme; USDOE Office of Energy Efficiency and Renewable Energy (EERE)
• Grant/Contract Number: AC36-08GO28308
• OSTI ID: 1593090
• Report Number(s): NREL/JA-5K00-75844; MainId:12179; UUID:0c1e7f18-e137-ea11-9c2f-ac162d87dfe5; MainAdminID:659
• Journal Information: IEEE Journal of Photovoltaics, Journal Name: IEEE Journal of Photovoltaics Journal Issue: 1 Vol. 10; ISSN 2156-3381
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

14 SOLAR ENERGY
47 OTHER INSTRUMENTATION
field performance
optimization
photovoltaic systems
prediction methods
soiling
solar energy
stochastic processes
time series analysis