Shanks' Method for Dynamic Phasor Estimation

• Published in: IEEE transactions on instrumentation and measurement Vol. 57; no. 4; pp. 813 - 819
• Main Authors: Munoz, Alejandro Torres, de la O. Serna, Jose Antonio
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2008; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Autoregressive moving average (ARMA) signal model; Autoregressive processes; complex envelope; Control systems; demodulation; digital filters; dynamic phasor; Frequency; frequency estimation; interpolation; Parameter estimation; phasor estimation; Power system control; Power system dynamics; Power system faults; Power system modeling; Power system stability; Power system transients; Shanks' method; interpolation; complex envelope; Shanks' method; Autoregressive moving average (ARMA) signal model; digital filters; dynamic phasor; demodulation; phasor estimation; frequency estimation
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2007.913824

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.