Power System Real-Time Event Detection and Associated Data Archival Reduction Based on Synchrophasors

• Published in: IEEE transactions on smart grid 2015-07, Vol.6 (4), p.2088-2097
• Main Authors: Yinyin Ge, Flueck, Alexander J., Dae-Kyeong Kim, Jong-Bo Ahn, Jae-Duck Lee, Dae-Yun Kwon
• Format: Article
• Language: English
• Subjects: Archiving; Event detection; Microgrids; phasor measurement unit (PMU); Phasor measurement units; Principal component analysis; principal component analysis (PCA); Real-time systems; reduction; Signal processing algorithms; situational awareness (SA); synchrophasor
• ISSN: 1949-3053; 1949-3061
• DOI: 10.1109/TSG.2014.2383693

The aim of this paper is to present methods on real-time event detection and data archival reduction based on synchrophasor data produced by phasor measurement unit (PMU). Event detection is performed with principal component analysis and a second order difference method with a hierarchical framework for the event notification strategy on a small-scale microgrid. Compared with the existing methods, the proposed method is more practical and efficient in the combined use of event detection and data archival reduction. The proposed method on data reduction, which is an "event oriented auto-adjustable sliding window method," implements a curve fitting algorithm with a weighted exponential function-based variable sliding window accommodating different event types. It works efficiently with minimal loss in data information especially around detected events. The performance of the proposed method is shown on actual PMU data from the Illinois Institute of Technology campus microgrid, thus successfully improving the situational awareness of the campus power system network.