DocumentCode :
2382398
Title :
Electromechanical mode on-line estimation using regularized robust RLS methods
Author :
Zhou, Ning ; Trudnowski, Dan ; Pierre, John ; Mittelstadt, William
fYear :
2010
fDate :
25-29 July 2010
Firstpage :
1
Lastpage :
1
Abstract :
Summary form only given. This paper proposes a regularized robust recursive least squares (R3LS) method for on-line estimation of power-system electromechanical modes based on synchronized phasor measurement unit (PMU) data. The proposed method utilizes an autoregressive moving average exogenous (ARMAX) model to account for typical measurement data, which includes low-level pseudo-random probing, ambient, and ringdown data. fn A robust objective function is utilized to reduce the negative influence from non-typical data, which include outliers and missing data. A dynamic regularization method is introduced to help include a priori knowledge about the system and reduce the influence of under-determined problems. Based on a 17-machine simulation model, it is shown through the Monte-Carlo method that the proposed R3LS method can estimate and track electromechanical modes by effectively using combined typical and non-typical measurement data.
Keywords :
autoregressive moving average processes; electric variables measurement; least mean squares methods; power system measurement; power system state estimation; recursion method; 17-machine simulation model; ARMAX model; Monte-Carlo method; a priori knowledge; autoregressive moving average exogenous model; dynamic regularization method; electromechanical mode online estimation; low-level pseudo-random probing; power-system electromechanical modes; regularized robust RLS methods; regularized robust recursive least squares method; ringdown data; robust objective function; synchronized phasor measurement unit data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2010 IEEE
Conference_Location :
Minneapolis, MN
ISSN :
1944-9925
Print_ISBN :
978-1-4244-6549-1
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PES.2010.5589746
Filename :
5589746
Link To Document :
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