Impact of Low Data Quality on Disturbance Triangulation Application Using High-Density PMU Measurements

Abstract

High-density PMUs can be implemented to estimate the location of a large power system disturbances based on the theory of Time Difference of Arrival (TDOA). Unfortunately, real-world measurements suffer from low data quality issues frequently caused by various uncontrollable and unpredictable factors. In this paper, four types of practical low data quality issues from onsite PMUs are first identified from the industry perspective. Then, the impacts of each low-quality data issue on disturbance triangulation are explored using real-time measurement cases from Jiangsu power grid with a high-density PMU network. This paper provides valuable guidance for utility operators and academic researchers to use actual PMU data for power grid applications.