Observability analysis and identification of critical measurements 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 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 matrix HΔ3θ, the approach enables the identification of critical measurements. Numerical examples to show the performance of the approach are presented.