DocumentCode
134062
Title
Distribution system event detection and classification using local voltage measurements
Author
Phillips, Desiree ; Overbye, Thomas
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
fYear
2014
fDate
Feb. 28 2014-March 1 2014
Firstpage
1
Lastpage
4
Abstract
Wide-Area Measurement Systems (WAMS) are being implemented in order to help increase situational awareness within the electric grid. These systems use Phasor Measurement Units (PMUs), devices which can measure the voltage and current within the power system. One kind of PMU is the Frequency Disturbance Recorder (FDR), which measures voltage magnitude, frequency, and phase angle at 10 data samples per second. These measurements are taken at the 120V level, resulting in a relatively low-cost, rapidly deployable alternative to other PMUs. This paper presents an approach to distribution system event detection and classification using voltage data obtained from FDRs installed around the University of Illinois at Urbana-Champaign (UIUC). This model-free classification of events will use pattern recognition techniques to help identify features that may be unique to these disturbances. Analysis will be applied to a sliding window of voltage data, and the results from each window are compared against one another in order to help determine what kind of event occurred.
Keywords
pattern recognition; power distribution; power grids; power system measurement; voltage measurement; FDR; PMU; University of Illinois; Urbana-Champaign; WAMS; distribution system event classification; distribution system event detection; electric grid; frequency disturbance recorder; local voltage measurements; model-free classification; pattern recognition techniques; phasor measurement units; voltage 120 V; voltage data; wide-area measurement systems; Feature extraction; Frequency measurement; Noise; Pattern recognition; Phasor measurement units; Standards; Voltage measurement; Distribution System; Frequency Disturbance Recorder; Pattern Recognition; Power;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Conference at Illinois (PECI), 2014
Conference_Location
Champaign, IL
Type
conf
DOI
10.1109/PECI.2014.6804576
Filename
6804576
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