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

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posted on 03.11.2019 by Leonardo Micheli, Eduardo F. Fernandez, Matthew Muller, Florencia Almonacid
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.

Funding

European Union’s Hori- zon 2020 research and innovation programme under the NoSoilPV project (Marie Skłodowska-Curie Grant agreement no. 793120)

History

Email Address of Submitting Author

lmicheli@ujaen.es

ORCID of Submitting Author

0000-0001-7986-7560

Submitting Author's Institution

University of Jaén

Submitting Author's Country

Spain

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