Observability and measurement redundancy analysis on three-phase state estimation

This paper provides a numerical approach to observability analysis, pseudo-measurements selection to restore observability, and identification of critical measurements and critical sets on three-phase state estimation. The approach enables observability analysis and restoration (pseudo-measurements selection) in a straightforward and simple way, without iteration, via triangular factorization of the Jacobian matrix of the weighted least square three-phase state estimator. By analyzing the structure of the matrix resulting from this factorization, the H_Δ3φ matrix, the approach enables the identification of critical measurements and critical sets. Numerical examples to show the performance of the approach are presented.