Shannon Wilcox | Jun 1, 2022
Satellite-derived solar irradiance data are known to underestimate temporal variability compared to point measurements because of their pixel-averaging nature. In this study, we apply an algorithm imposing random noise to enhance the temporal variability of 5-minute...
Shannon Wilcox | Jun 1, 2022
Small-scale variabilities of solar irradiance are important for many applications. Downscaling approaches need to be developed where only the averaged state of solar irradiance is known. In this study, we investigate the use of copula for temporally downscaling GHI...
Shannon Wilcox | Mar 1, 2022
The ability to forecast solar irradiance plays an indispensable role in solar power forecasting, which constitutes an essential step in planning and operating power systems under high penetration of solar power generation. Since solar radiation is an atmospheric...
Heather Van Schoiack | Jul 17, 2019
This presentation demonstrates how a new approach to PV fleet forecasting can address the problem of artificially high fleet variability when plants share the same solar resource data. The presentation was given at the ESIG 2018 Forecasting Workshop, June 19-21, 2018,...
Heather Van Schoiack | Jun 20, 2019
As interest in bifacial PV modules grows, there is a need to quantify the impact of additional energy generation for financing solar projects. A critical parameter for accurately modeling rear-side irradiation in bifacial modules is albedo. This paper identifies...
