PMU-Based Distributed State Estimation to Enhance the Numerical Stability Using Equality Constraints

With the deployment of PMUs in large-scale power systems, distributed state estimation (DSE) plays a major role in wide-area monitoring systems (WAMS). Specifically, the convergence and time efficiency of state estimators are important properties that must be preserved regardless of operating conditions. In this article, an equality-constrained PMU-based DSE strategy is proposed to enhance the numerical stability and computational efficiency of DSE. First, we identify network conditions in terms of the current flow magnitudes inducing the numerical instability of DSE. Then, we define a new local set of measurements and form equality constraints that enable the DSE problem to have a significantly reduced condition number, meaning that the numerical stability of DSE is enhanced. Moreover, an accelerated ADMM method is adopted to improve time efficiency. Furthermore, even if the measured data were corrupted, the proposed DSE strategy converges and estimate the states successfully. Numerical simulations are performed on IEEE 14-, 118-, and 1,062-bus systems, and the 1,665-bus Korean power system, to validate the performance of the proposed method. The results demonstrate the effectiveness of the method in terms of numerical stability and time efficiency under various measurement conditions.