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This paper presents a model for detecting high-impedance faults (HIFs) usingparameter error modeling and a two-step per-phase weighted least squares stateestimation (SE) process. The proposed scheme leverages the use of phasormeasurement units and synthetic measurements to identify per-phase power flowand injection measurements which indicate a parameter error through $\chi^2$Hypothesis Testing applied to the composed measurement error (CME). Althoughcurrent and voltage waveforms are commonly analyzed for high-impedance faultdetection, wide-area power flow and injection measurements, which are alreadyinherent to the SE process, also show promise for real-world high-impedancefault detection applications. The error distributions after detection share themeasurement function error spread observed in proven parameter errordiagnostics and can be applied to HIF identification. Further, this errorspread related to the HIF will be clearly discerned from measurement error.Case studies are performed on the 33-Bus Distribution System in Simulink.

High Impedance Fault Detection Through Quasi-Static State Estimation: A Parameter Error Modeling Approach