Observability-Preserving Bad Data Processing for PMU-only Linear State Estimation of the Jeju Power System

Abstract

Phasor measurement units (PMUs) provide time-synchronized voltage and current phasors, enabling linear state estimation in rectangular coordinates. This paper evaluates PMU-only linear state estimation for the Jeju power system using its actual PMU measurement channel configuration and proposes an observability-preserving bad-data processing method. Monte Carlo simulations were performed under voltage, current, combined bad-data, and missing-measurement conditions. The proposed observability-preserving selective reweighting and removal method (OP-SRR) was compared with measurement removal and iterative reweighting methods using a weighted least-squares (WLS)-inspired post-processing residual screening index with a fixed threshold. The results show that OP-SRR mitigates estimation instability associated with measurement removal, particularly under combined voltage and current bad-data conditions, while requiring less computation time than iterative reweighting. The missing-measurement case was evaluated under conditions in which observability was preserved.