Investigation of Optimal Phasor Measurement Selection for Distribution System State Estimation Under Various Uncertainties

Optimal measurement selection for distribution state system estimation (DSSE) has been on a key research focus for efficient grid monitoring, given the increasingly active nature of distribution grids. Lately, the integration of synchrophasor techology, the reduction of pseudo-measurements that compromise DSSE performance, and the consideration of uncertainties (topology changes, DER penetration, load growth), are the most interesting directions to follow. This paper tackles these challenges by utilizing semidefinite programming (SDP) to develop a robust optimization framework for optimal planning of metering unit installations, concentrating on synchrophasors. The objective is to ensure concrete grid observability and quality DSSE while accommodating various uncertainties. To achieve this, the study employs the SDP-formulated A-, E- and M- optimal experiment designs under budget constraints, alongside a new SDP-based model for selecting minimal measurement sets subject to accuracy criteria. The proposed approach is tested on the IEEE 33-node test feeder and the 95-node UK distribution grid, demonstrating its ability to deliver optimal measurement configurations that enhance DSSE performance, improve economic efficiency, reduce reliance on pseudo-measurements, and remain robust to diverse grid uncertainties.