Combined transmission and distribution state-estimation for future electric grids

The proliferation of grid resources on the distribution network along with the inability to forecast them accurately will render the current 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 an approach will require AC state estimation (ACSE) of joint T&D networks. Today, no practical method for realizing combined T&D ACSE exists. In this chapter, we will address the gap from a circuit-theoretic perspective by realizing a combined T&D ACSE solution approach, that is, fast, convex, and robust against bad data. To address the daunting challenges of problem size (million + variables) and data privacy, this approach will be distributed in memory and computing resources. To ensure timely convergence, the approach will construct a distributed circuit model for combined T&D networks and utilize node-tearing techniques for efficient parallelism. To demonstrate the efficacy of the approach, we will run the combined T&D ACSE approach on large test networks that comprise multiple T&D feeders. In the final sections, we will show results that reflect the accuracy of the estimates in terms of root-mean-square error and algorithm scalability in terms of wall-clock time.