Solar variability zones: Satellite-derived zones that represent high-frequency ground variability. (15th July 2017)

• Record Type: Journal Article
• Authors: Lave, Matthew; Broderick, Robert J.; Reno, Matthew J.
• Is Part Of: Solar energy. Volume 151(2017)
• Page Start: 119
• Page End: 128
• Publication Date: 2017-07-15
• Subjects: Solar variability -- Distribution grid integration -- Satellite-derived irradiance -- Tap changes; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2017.05.005
• Languages: English
• ISSNs: 0038-092X

Abstract

Highlights: A relationship is found between 1-h and 30-s solar variability. Relationship improved through adjustments such as using clear-sky index. A map of solar variability across the United States is presented. Variability zones well-correlated with simulated tap change operations. Variability zones methodology accurate for timescales as short as 10 s. Abstract: To determine the impact of solar variability to electric grid operations, appropriate samples of solar variability must be used, but determining appropriate variability samples is difficult for locations without ground measurements. In this work, we evaluate and model the relationship between high-frequency and low-frequency solar variability. The developed model is then used to define solar variability zones – zones of similar high-frequency solar variability – using low-frequency satellite data. A map of the United States is presented indicating areas of high, moderate, and low solar variability. To demonstrate the value of the variability zones, quasi-static time series (QSTS) simulations are used to determine the impact of variability samples from each zone on distribution grid voltage regulator tap change operations (a measure of the impact of solar variability to electric grid operations). Strong correlation is found between satellite-derived variability zone and QSTS simulated tap changes based on ground samples of solar variability, showing that solar variability zones can be useful to approximate the impacts of high-frequency solar variability. The relationship between high-frequency and low-frequency variability is found to apply to timescales as short as 10-s.