  It is critical that the qualities and features of synthetically-generated,
PMU measurements used for grid analysis matches those of measurements obtained
from field-based PMUs. This ensures that analysis results generated by
researchers during grid studies replicate those outcomes typically expected by
engineers in real-life situations. In this paper, essential features associated
with industry PMU-derived data measurements are analyzed for input
considerations in the generation of vast amounts of synthetic power system
data. Inherent variabilities in PMU data as a result of the random dynamics in
power system operations, oscillatory contents, and the prevalence of bad data
are presented. Statistical results show that in the generation of large
datasets of synthetic, grid measurements, an inclusion of different data
anomalies, ambient oscillation contents, and random cases of missing data
samples due to packet drops helps to improve the realism of experimental data
used in power systems analysis.
