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

• Published in: IEEE transactions on instrumentation and measurement Vol. 74; pp. 1 - 16
• Main Authors: Xygkis, Themistoklis C., Lofberg, Johan, Korres, George N.
• Format: Journal Article
• Language: English
• Published: New York IEEE 2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Configuration management; Costs; Energy sources; Load modeling; Measurement; Measurement uncertainty; Metering; Observability; Observability (systems); Optimization; Phasor measurement units; Phasors; power distribution networks; pseudo-measurements; Resource management; Robustness; Semidefinite programming; semidefinite programming (SDP); State estimation; state estimation (SE); Topology; uncertainties; Uncertainty; state estimation (SE); Uncertainty; Costs; Topology; Optimization; power distribution networks; semidefinite programming (SDP); Accuracy; Measurement uncertainty; pseudo-measurements; Phasor measurement units; Resource management; Observability; State estimation; uncertainties; Load modeling
• ISSN: 0018-9456; 1557-9662; 1557-9662
• DOI: 10.1109/TIM.2025.3590849

Optimal measurement selection for distribution system state estimation (DSSE) has been a key research focus for efficient grid monitoring, given the increasingly active nature of distribution grids. Lately, the integration of synchrophasor technology, the reduction of pseudo-measurements that compromise DSSE performance, and the consideration of uncertainties (topology changes, distributed energy resource (DER) penetration, and load growth) are the most interesting directions to follow. This article 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 (OEDs) 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 U.K. 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.