Bayesian Approach in the Modal Analysis of Electromechanical Oscillations

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Bayesian Approach in the Modal Analysis of Electromechanical Oscillations. / Seppanen, Janne; Au, Siu Kui; Turunen, Jukka; Haarla, Liisa.

In: IEEE Transactions on Power Systems, Vol. 32, No. 1, 7465810, 01.01.2017, p. 316-325.

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Seppanen, Janne ; Au, Siu Kui ; Turunen, Jukka ; Haarla, Liisa. / Bayesian Approach in the Modal Analysis of Electromechanical Oscillations. In: IEEE Transactions on Power Systems. 2017 ; Vol. 32, No. 1. pp. 316-325.

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@article{8a493f000dc540f880264e5c06944f37,
title = "Bayesian Approach in the Modal Analysis of Electromechanical Oscillations",
abstract = "This paper presents a Bayesian approach for identifying the modal parameters (i.e., frequency, damping ratio, and modal excitation) of electromechanical modes. The proposed approach identifies the modal parameters and calculates their uncertainty using ambient phasor measurement unit (PMU) measurements from a power system. The method is applied in the frequency domain on a selected frequency band, which significantly simplifies the identification. The performance of the method is studied with simulated data from the IEEE New England test system and the Nordic power system simulation model. In addition, measured PMU data from the Nordic power system are used. The results indicate that the modal parameters of electromechanical modes can be identified reliably and their identification uncertainty can be fundamentally calculated using the proposed method. Thus, the Bayesian approach is a promising identification method for wide-area monitoring of electromechanical oscillations.",
keywords = "Bayes' theorem, electromechanical oscillation, modal analysis, PMU measurements, power system dynamics",
author = "Janne Seppanen and Au, {Siu Kui} and Jukka Turunen and Liisa Haarla",
year = "2017",
month = "1",
day = "1",
doi = "10.1109/TPWRS.2016.2561020",
language = "English",
volume = "32",
pages = "316--325",
journal = "IEEE Transactions on Power Systems",
issn = "0885-8950",
number = "1",

}

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TY - JOUR

T1 - Bayesian Approach in the Modal Analysis of Electromechanical Oscillations

AU - Seppanen, Janne

AU - Au, Siu Kui

AU - Turunen, Jukka

AU - Haarla, Liisa

PY - 2017/1/1

Y1 - 2017/1/1

N2 - This paper presents a Bayesian approach for identifying the modal parameters (i.e., frequency, damping ratio, and modal excitation) of electromechanical modes. The proposed approach identifies the modal parameters and calculates their uncertainty using ambient phasor measurement unit (PMU) measurements from a power system. The method is applied in the frequency domain on a selected frequency band, which significantly simplifies the identification. The performance of the method is studied with simulated data from the IEEE New England test system and the Nordic power system simulation model. In addition, measured PMU data from the Nordic power system are used. The results indicate that the modal parameters of electromechanical modes can be identified reliably and their identification uncertainty can be fundamentally calculated using the proposed method. Thus, the Bayesian approach is a promising identification method for wide-area monitoring of electromechanical oscillations.

AB - This paper presents a Bayesian approach for identifying the modal parameters (i.e., frequency, damping ratio, and modal excitation) of electromechanical modes. The proposed approach identifies the modal parameters and calculates their uncertainty using ambient phasor measurement unit (PMU) measurements from a power system. The method is applied in the frequency domain on a selected frequency band, which significantly simplifies the identification. The performance of the method is studied with simulated data from the IEEE New England test system and the Nordic power system simulation model. In addition, measured PMU data from the Nordic power system are used. The results indicate that the modal parameters of electromechanical modes can be identified reliably and their identification uncertainty can be fundamentally calculated using the proposed method. Thus, the Bayesian approach is a promising identification method for wide-area monitoring of electromechanical oscillations.

KW - Bayes' theorem

KW - electromechanical oscillation

KW - modal analysis

KW - PMU measurements

KW - power system dynamics

UR - http://www.scopus.com/inward/record.url?scp=85008627420&partnerID=8YFLogxK

U2 - 10.1109/TPWRS.2016.2561020

DO - 10.1109/TPWRS.2016.2561020

M3 - Article

VL - 32

SP - 316

EP - 325

JO - IEEE Transactions on Power Systems

JF - IEEE Transactions on Power Systems

SN - 0885-8950

IS - 1

M1 - 7465810

ER -

ID: 13560263