This short paper investigates distribution-level synchrophasor measurement errors with online and offline tests, and mathematically and systematically identifies the actual distribution of the measurement errors through graphical and numerical analysis. It is observed that the measurement errors in both online and offline case studies follow a non-Gaussian distribution, instead of the traditionally assumed Gaussian distribution. It suggests the use of non-Gaussian models, such as Gaussian mixture models, for representing the measurement errors more accurately and realistically. The presented tests and analysis are helpful for the understanding of distribution-level measurement characteristics, and for the modeling and simulation of distribution system applications, such as state estimation.
Abstract-Phasor Measurement units (PMU's) are becoming standard equipment in electrical grids around the world. They are capable of generating a significant amount of data on a continuous basis from distribution and transmission networks. Several months of data from 2 PMU's situated on a distribution network were captured in raw format. This data was separated by measurement type and compressed using a number of standard compression algorithms.The results show the compressibility of PMU data for these algorithms and are used to estimate the space requirements for storing a day of data from a single PMU.
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