  The power grid is going through significant changes with the introduction of
renewable energy sources and incorporation of smart grid technologies. These
rapid advancements necessitate new models and analyses to keep up with the
various emergent phenomena they induce. A major prerequisite of such work is
the acquisition of well-constructed and accurate network datasets for the power
grid infrastructure. In this paper, we propose a robust, scalable framework to
synthesize power distribution networks which resemble their physical
counterparts for a given region. We use openly available information about
interdependent road and building infrastructures to construct the networks. In
contrast to prior work based on network statistics, we incorporate engineering
and economic constraints to create the networks. Additionally, we provide a
framework to create ensembles of power distribution networks to generate
multiple possible instances of the network for a given region. The
comprehensive dataset consists of nodes with attributes such as
geo-coordinates, type of node (residence, transformer, or substation), and
edges with attributes such as geometry, type of line (feeder lines, primary or
secondary) and line parameters. For validation, we provide detailed comparisons
of the generated networks with actual distribution networks. The generated
datasets represent realistic test systems (as compared to standard IEEE test
cases) that can be used by network scientists to analyze complex events in
power grids and to perform detailed sensitivity and statistical analyses over
ensembles of networks.
