Matthew Lave, Robert J. Broderick, Matthew J. Reno, Solar variability zones: Satellite-derived zones that represent high-frequency ground variability, Solar Energy, Volume 151, 15 July 2017, Pages 119-128, ISSN 0038-092X.
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.
This page describes how to retrieve a representative sample of high-frequency irradiance data using the solar variability zones.
1. Determine Solar Variability Zone
Solar variability zones are zones of similar high-frequency data. The first step is to determine the variability zone for your location of interest using the map below or this Google Earth file
Variability_Zones.zip (1717 downloads)
2. Download High-Frequency Irradiance Sample
3. Use the Irradiance Sample for PV Integration Studies
The high-frequency irradiance samples can be converted to PV power output using an irradiance scaling model to account for spatial smoothing (e.g., the Wavelet Variability Model (WVM)) and an irradiance to PV power model (e.g., PVSyst or the Sandia Array Performance Model). Then, the PV power can be used in a grid integration study and will have representative PV variability.
- Broderick, R., Reno, M., Lave, M., and Quiroz, J. 2015. “Final Technical Report to DOE on Accelerating Cost- Effective Deployment of Solar Generation on the Distribution Grid.” Sandia National Laboratories.
- Lave, M., Broderick, R., Reno, M. 2016. “Solar Variability Zones.” To be submitted to Solar Energy.
Thanks to Idaho Power, SunPower Corporation, the Sacramento Municipal Utility District, and the University of California, San Diego for sharing high-frequency irradiance data.