Anderson, NickTatsiankou, ViktarHinzer, KarinBeal, Richard M.Schriemer, Henry P.2022-04-262022-04-2620229781510648630http://hdl.handle.net/10393/43519https://doi.org/10.20381/ruor-27734Solar 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.enAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Solar irradiance variabilitycloud dynamicsspectral pyranometerprobability densityindex incrementsConference Proceeding10.1117/12.2616231