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Title: Simultaneous Estimation of Electromechanical Modes and Forced Oscillations

Abstract

Over the past several years, great strides have been made in the effort to monitor the small-signal stability of power systems. These efforts focus on estimating electromechanical modes, which are a property of the system that dictate how generators in different parts of the system exchange energy. Though the algorithms designed for this task are powerful and important for reliable operation of the power system, they are susceptible to severe bias when forced oscillations are present in the system. Forced oscillations are fundamentally different from electromechanical oscillations in that they are the result of a rogue input to the system, rather than a property of the system itself. To address the presence of forced oscillations, the frequently used AutoRegressive Moving Average (ARMA) model is adapted to include sinusoidal inputs, resulting in the AutoRegressive Moving Average plus Sinusoid (ARMA+S) model. From this model, a new Two-Stage Least Squares algorithm is derived to incorporate the forced oscillations, thereby enabling the simultaneous estimation of the electromechanical modes and the amplitude and phase of the forced oscillations. The method is validated using simulated power system data as well as data obtained from the western North American power system (wNAPS) and Eastern Interconnection (EI).

Authors:
; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1398177
Report Number(s):
PNNL-SA-119156
Journal ID: ISSN 0885-8950; TE1101000
DOE Contract Number:
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: IEEE Transactions on Power Systems; Journal Volume: 32; Journal Issue: 5
Country of Publication:
United States
Language:
English
Subject:
Electromechanical modes; Forced oscillations; Least squares; Phasor Measurement Units (PMUs); Power system dynamics; Spectral analysis

Citation Formats

Follum, Jim, Pierre, John W., and Martin, Russell. Simultaneous Estimation of Electromechanical Modes and Forced Oscillations. United States: N. p., 2017. Web. doi:10.1109/TPWRS.2016.2633227.
Follum, Jim, Pierre, John W., & Martin, Russell. Simultaneous Estimation of Electromechanical Modes and Forced Oscillations. United States. doi:10.1109/TPWRS.2016.2633227.
Follum, Jim, Pierre, John W., and Martin, Russell. 2017. "Simultaneous Estimation of Electromechanical Modes and Forced Oscillations". United States. doi:10.1109/TPWRS.2016.2633227.
@article{osti_1398177,
title = {Simultaneous Estimation of Electromechanical Modes and Forced Oscillations},
author = {Follum, Jim and Pierre, John W. and Martin, Russell},
abstractNote = {Over the past several years, great strides have been made in the effort to monitor the small-signal stability of power systems. These efforts focus on estimating electromechanical modes, which are a property of the system that dictate how generators in different parts of the system exchange energy. Though the algorithms designed for this task are powerful and important for reliable operation of the power system, they are susceptible to severe bias when forced oscillations are present in the system. Forced oscillations are fundamentally different from electromechanical oscillations in that they are the result of a rogue input to the system, rather than a property of the system itself. To address the presence of forced oscillations, the frequently used AutoRegressive Moving Average (ARMA) model is adapted to include sinusoidal inputs, resulting in the AutoRegressive Moving Average plus Sinusoid (ARMA+S) model. From this model, a new Two-Stage Least Squares algorithm is derived to incorporate the forced oscillations, thereby enabling the simultaneous estimation of the electromechanical modes and the amplitude and phase of the forced oscillations. The method is validated using simulated power system data as well as data obtained from the western North American power system (wNAPS) and Eastern Interconnection (EI).},
doi = {10.1109/TPWRS.2016.2633227},
journal = {IEEE Transactions on Power Systems},
number = 5,
volume = 32,
place = {United States},
year = 2017,
month = 9
}
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