PMU-Based Distribution Linear State Estimation to Improve Data Quality and Application Reliability

Abstract

Synchrophasor data quality issues have been a challenge for robust application deployment in the power grid. This paper presents the ability of a three-phase distribution linear state estimator (DLSE) to detect various types of synchrophasor bad data. The DLSE is the first application layer that pre-processes the synchrophasor data and produces state estimates for all observable nodes of the system. This work represents the DLSE software for real-time monitoring, analysis, and situational awareness of the Commonwealth Edison Company (ComEd) Bronzeville Community Microgrid (BCM). The DLSE software platform, used for state estimation, can perform observability analysis, optimize distribution phasor measurement unit (PMU) placement, identify topology change, and detect bad data. This paper focusses on the software's module that supports bad data detection. Demonstration of the PMU-based platform was performed in ComEd's real-time digital simulation (RTDS) enabled Hardware in the Loop (HIL) environment.