Performance Comparison of Quantitative Methods for PMU Data Event Detection with Noisy Data

被引：0

作者：

Souto, L. ^{[1
]}

Herraiz, S. ^{[1
]}

Melendez, J. ^{[1
]}

机构：

[1] Univ Girona, Intelligent Syst & Control Engn Grp, Girona, Girona, Spain

来源：

2020 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES EUROPE (ISGT-EUROPE 2020): SMART GRIDS: KEY ENABLERS OF A GREEN POWER SYSTEM | 2020年

基金：

欧盟地平线“2020”;

关键词：

fault detection; phasor measurement units; power system faults; principal component analysis;

D O I：

10.1109/isgt-europe47291.2020.9248826

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This article compares distinct signal-based and knowledge-based approaches often applied to process and detect events in vast amounts of data collected by phasor measurement units (PMU). The computation times and the accuracy of correct event detections are tested and evaluated in a 1-hour data file from the UT-Austin Independent Texas Synchrophasor Network with phasor quantities plus an additive noise gathered at different PMU substations. A sliding time window is considered to build a representative model of the system operating conditions on the fly and search for power system phenomena as soon as new data are available.

引用

页码：232 / 236

页数：5

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