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Shanks' method for dynamic phasor estimation
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DOI：10.1109/TIM.2007.913824.png)
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Abstract
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A new algorithm for phasor estimation is proposed. It is based on a signal model that allows amplitude and phase dynamic variations. An autoregressive moving average (ARMA) model is assumed for the oscillating signal. Its autoregressive part is fixed, and it is defined only by the nominal fundamental frequency. Its best moving average parameters are estimated with Shanks' method. These parameters provide the key information from which the phasor state vector is estimated through the partial fraction expansion of the ARMA rational polynomial. These estimates could be useful, not only for the monitoring and controlling of the power system, but also for discriminating between a fault and an oscillation state.
Keywords:
autoregressive moving average (ARMA) signal model
complex envelope
demodulation
digital filters
dynamic phasor
frequency estimation
interpolation
phasor estimation
Shanks' method
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