  Proliferation of grid resources on the distribution network along with the
inability to forecast them accurately will render the existing methodology of
grid operation and control untenable in the future. Instead, a more distributed
yet coordinated approach for grid operation and control will emerge that models
and analyzes the grid with a larger footprint and deeper hierarchy to unify
control of disparate T&D grid resources under a common framework. Such approach
will require AC state-estimation (ACSE) of joint T&D networks. Today, no
practical method for realizing combined T&D ACSE exists. This paper addresses
that gap from circuit-theoretic perspective through realizing a combined T&D
ACSE solution methodology that is fast, convex and robust against bad-data. To
address daunting challenges of problem size (million+ variables) and
data-privacy, the approach is distributed both in memory and computing
resources. To ensure timely convergence, the approach constructs a distributed
circuit model for combined T&D networks and utilizes node-tearing techniques
for efficient parallelism. To demonstrate the efficacy of the approach,
combined T&D ACSE algorithm is run on large test networks that comprise of
multiple T&D feeders. The results reflect the accuracy of the estimates in
terms of root mean-square error and algorithm scalability in terms of
wall-clock time.
