@inproceedings{5d10414a6fb84016b0079afde96a0324,
title = "Event analysis of distribution system voltage data",
abstract = "Discussion of the future of the Smart Grid brings with it issues regarding the current level of distribution system visibility. Phasor Measurement Units (PMU) have been proliferating throughout the electric power grid in order to support future distribution system analysis. One type of PMU is the Frequency Disturbance Recorder (FDR); it records voltage magnitude, frequency, and phase angle at the 120 V outlet level. Previous work has introduced ways in which distribution system events can be read from this voltage data, but this paper focuses on defining similarity measures for comparing detected events. Discrete Signal Processing (DSP) techniques such as correlation and convolution can be used to determine how similar events are, even in the presence of a time delay. Euclidean distance and mean-squared error are used as similarity measurements to help confirm the correctness of the time-delay estimation. Beyond detecting positively and negatively correlated events, the similarity measures support the correlation results by determining that some events aren't correlated at all.",
keywords = "Correlation, Distribution Systems, Electric Power, Frequency Disturbance Recorder, Signal Processing, Voltage",
author = "Desiree Phillips and Overbye, {Thomas J}",
year = "2015",
month = mar,
day = "20",
doi = "10.1109/PECI.2015.7064891",
language = "English (US)",
series = "2015 IEEE Power and Energy Conference at Illinois, PECI 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 IEEE Power and Energy Conference at Illinois, PECI 2015",
address = "United States",
note = "2015 IEEE Power and Energy Conference at Illinois, PECI 2015 ; Conference date: 20-02-2015 Through 21-02-2015",
}