Utility planners and operators are concerned about how short-term PV system output changes may affect utility system stability. Short-term output changes are driven by changes in the clearness index. This paper analyzes the correlation coefficient of the change in the clearness index between two locations as a function of distance, time interval, and other parameters. The paper presents a method to estimate correlation coefficients that uses location-specific input parameters. The method is derived empirically and validated using 12 years of hourly satellite-derived data from SolarAnywhere~? in three geographic regions in the United States (Southwest, Southern Great Plains, and Hawaii). Results from 70,000 station pair combinations suggest that: (1) correlation coefficients decrease predictably with increasing distance; (2) correlation coefficients decrease at a similar rate when evaluated versus distance divided by the considered variability time interval; and (3) the accuracy of results is improved by including an implied cloud speed term. The approach has potential financial benefits to systems that are concerned about PV power output variability, ranging from individual distribution feeders to state-wide balancing regions.
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