Probabilistic description of short-term cloud dynamics from rapid sampling of the solar spectral irradiance

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Title: Probabilistic description of short-term cloud dynamics from rapid sampling of the solar spectral irradiance
Authors: Anderson, Nick
Tatsiankou, Viktar
Hinzer, Karin
Beal, Richard M.
Schriemer, Henry P.
Date: 2022
Abstract: Solar irradiance variability due to stochastic cloud dynamics can cause unwanted fluctuations in the output voltage of photovoltaic (PV) modules. These dynamics must in particular be understood at very-short and short time scales if grid interconnection and generation/load balance requirements are to be maintained for PV distributed across the grid edge. Using a recently-created database for Ottawa, Canada, a 6-month longitudinal study was conducted with a specific focus on cloud dynamics. A spectral pyranometer was used to derive full-range spectral and broadband global horizontal irradiance under all sky conditions every 250 ms. Exploiting the infrared (IR) measurement channel of this software augmented multi-filter radiometer allowed the cloud dynamics to be probed across time scales ranging from the subsecond to ~30 minutes. Seven distinct sky conditions were self-consistently determined without sky imaging. Probability distributions, established via kernel density estimates (KDE), allowed the statistical dependence of these conditions on the spectral clear-sky index to be found. The stochastic nature of the spectral irradiance variability was probed using spectral clear-sky index increments, over time steps that were found to span three distinct variability regimes.
URL: http://hdl.handle.net/10393/43519
DOI: 10.1117/12.2616231
CollectionScience informatique et génie électrique - Publications // Electrical Engineering and Computer Science - Publications
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