  This paper presents a set of validation metrics for transmission network
parameters that is applicable in both creation of synthetic power system test
cases and validation of existing models. Using actual data from two real-world
power grids, statistical analyses are performed to extract some useful
statistics on transformers and transmission lines electrical parameters
including per unit reactance, MVA rating, and their X/R ratio. It is found that
conversion of per unit reactance calculated on system common base to
transformer own power base will significantly stabilize its range and remove
the correlation between per unit X and MVA rating. This is fairly consistent
for transformers with different voltage levels and sizes and can be utilized as
a strong validation metric for synthetic models. It is found that transmission
lines exhibit different statistical properties than transformers with different
distribution and range for the parameters. In addition, statistical analysis
shows that the empirical PDF of transmission network electrical parameters can
be approximated with mathematical distribution functions which would help
appropriately characterize them in synthetic power networks. Kullback-Leibler
divergence is used as a measure for goodness of fit for approximated
distributions.
