A new distributed state estimation technique for power networks

The paper develops a new distributed state estimation technique for power networks. This distributed state estimator aims to provide the same optimal estimate as the centralized one via a small amount information exchange between neighbors, which are physically in parallel with the partition of power networks. Moreover, we show that the distributed state estimator converges to the optimal estimate in a finite number of iterations depending on the size of the abstract graph. Both rigorous analysis and simulations are provided to show the correctness.