학술논문
Comparison of Principal Component Analysis Techniques for PMU Data Event Detection
Document Type
Conference
Author
Source
2020 IEEE Power & Energy Society General Meeting (PESGM) Power & Energy Society General Meeting (PESGM), 2020 IEEE. :1-5 Aug, 2020
Subject
Language
ISSN
1944-9933
Abstract
Principal component analysis (PCA) is a dimensionality reduction technique often applied to process and detect events in large amounts of data collected by phasor measurement units (PMU) at transmission and distribution level. This article considers five different approaches to select an appropriate number of principal components, builds the statistical model of the PMU data online over a sliding window of 10 seconds and 1 minute, and evaluates the computation times and the accuracy of correct event detections with use of two statistical tests in a 1-hour data file from the UT-Austin Independent Texas Synchrophasor Network with phasor quantities collected at different PMU substations.