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Electromechanical Mode Online Estimation Using Regularized Robust RLS Methods
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DOI：10.1109/TPWRS.2008.2002173.png)
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Abstract
En 中文
This paper proposes a regularized robust recursive least squares (R3LS) method for online 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. A robust objective function is utilized to reduce the negative influence from nontypical 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 nontypical measurement data.
Keywords:
Autoregressive moving average processes
least squares methods
power system identification
power system measurements
power system monitoring
power system parameter estimation
power system stability
recursive estimation
robustness
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