DocumentCode :
1144616
Title :
Use of ARMA block processing for estimating stationary low-frequency electromechanical modes of power systems
Author :
Wies, Richard W. ; Pierre, John W. ; Trudnowski, Daniel J.
Author_Institution :
Univ. of Alaska Fairbanks, AK, USA
Volume :
18
Issue :
1
fYear :
2003
fDate :
2/1/2003 12:00:00 AM
Firstpage :
167
Lastpage :
173
Abstract :
Accurate knowledge of low-frequency electromechanical modes in power systems gives vital information about the stability of the system. Current techniques for estimating electromechanical modes are computationally intensive and rely on complex system models. This research complements model-based approaches and uses measurement-based techniques. This paper discusses the development of an autoregressive moving average (ARMA) block-processing technique to estimate these low-frequency electromechanical modes from measured ambient power system data without requiring a disturbance. This technique is applied to simulated data containing a stationary low-frequency mode generated from a 19-machine test model. The frequency and damping factor of the estimated modes are compared with the actual modes for various block sizes. This technique is also applied to 35-min blocks of actual ambient power system data before and after a disturbance and compared to results from Prony analysis on the ringdown from the disturbance.
Keywords :
autoregressive moving average processes; control system analysis computing; power system analysis computing; power system control; power system faults; power system stability; power system state estimation; 19-machine test model; ARMA block processing; computer simulation; damping factor; disturbance ringdown; frequency factor; power system stability; power system stationary low-frequency electromechanical modes estimation; Autoregressive processes; Damping; Frequency estimation; Power measurement; Power system measurements; Power system modeling; Power system simulation; Power system stability; Power systems; Testing;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2002.807116
Filename :
1178793
Link To Document :
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