DocumentCode :
2040757
Title :
A stepwise regression method for estimating dominant electromechanical modes
Author :
Ning Zhou ; Pierre, J. ; Trudnowski, D.
Author_Institution :
Pacific Northwest Nat. Lab., Richland, WA, USA
fYear :
2012
fDate :
22-26 July 2012
Firstpage :
1
Lastpage :
1
Abstract :
Summary form only given. Prony analysis has been applied to estimate inter-area oscillation modes using phasor measurement unit (PMU) measurements. To suppress noise and signal offset effects, a high-order Prony model usually is used to over-fit the data. As such, some trivial modes are intentionally added to improve the estimation accuracy of the dominant modes. Therefore, to reduce the rate of false alarms, it is important to distinguish between the dominant modes that reflect the dynamic features of a power system and the trivial modes that are artificially introduced to improve the estimation accuracy. In this paper, a stepwise-regression method is applied to automatically identify the dominant modes from Prony analysis. A Monte-Carlo method is applied to evaluate the performance of the proposed method using data obtained from simulations. Field-measured PMU data are used to verify the applicability of the proposed method. A comparison of results obtained using the proposed approach with results from a traditional energy-sorting method shows the improved performance of the proposed method.
Keywords :
Monte Carlo methods; phasor measurement; power system stability; regression analysis; signal denoising; Monte-Carlo method; PMU measurements; Prony analysis; dominant electromechanical mode estimation; energy-sorting method; false alarm rate; field-measured PMU data; high-order Prony model; interarea oscillation mode estimation; noise suppression; phasor measurement unit; power system; signal offset effects; stepwise regression method; Accuracy; Data models; Educational institutions; Estimation; Laboratories; Phasor measurement units; Power system dynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
ISSN :
1944-9925
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PESGM.2012.6344635
Filename :
6344635
Link To Document :
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