Identification of Interarea Modes From Ambient Data of Phasor Measurement Units Using an Autoregressive Exogenous Model
Various modal identification methods for interarea modes have been developed to improve identification accuracy by overcoming the measurement noise in ambient data of phasor measurement units (PMUs). In this study, a modal identification method that is insensitive to measurement noise is proposed by...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9381196/ |
| _version_ | 1818640024171708416 |
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| author | Jin Kwon Hwang Jeonghoon Shin |
| author_facet | Jin Kwon Hwang Jeonghoon Shin |
| author_sort | Jin Kwon Hwang |
| collection | DOAJ |
| description | Various modal identification methods for interarea modes have been developed to improve identification accuracy by overcoming the measurement noise in ambient data of phasor measurement units (PMUs). In this study, a modal identification method that is insensitive to measurement noise is proposed by introducing bandpass filters, which extract a modal signal from an autocorrelation function of PMU ambient data. The bandwidth of the filters is set to be adequately narrow such that the noise can be rejected sufficiently. To reduce the computational burden of the proposed method, the filters are designed by transforming a reference lowpass filter. An autoregressive exogenous (ARX) model of interarea modes is applied to the extracted modal signal. The parameters of the ARX model are estimated for modal identification via the least squares method. The identification accuracy of the proposed method is compared with those of conventional modified extended Yule Walker and discrete Fourier transform methods with respect to the signal-to-noise ratio and modal damping by using synthetic ambient data. Finally, the feasibility of the proposed method is demonstrated by identifying interarea modes of Kundur’s two-area four-machine system and two real power systems in South Korea. |
| first_indexed | 2024-12-16T23:04:41Z |
| format | Article |
| id | doaj.art-d7013c46b6cc4690b64893fb0fb7c126 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T23:04:41Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d7013c46b6cc4690b64893fb0fb7c1262022-12-21T22:12:36ZengIEEEIEEE Access2169-35362021-01-019456954570510.1109/ACCESS.2021.30672139381196Identification of Interarea Modes From Ambient Data of Phasor Measurement Units Using an Autoregressive Exogenous ModelJin Kwon Hwang0https://orcid.org/0000-0003-4536-3545Jeonghoon Shin1Department of Energy Electrical Engineering, Woosuk University, Jinchon-gun, South KoreaPower Grid Group, KEPCO Research Institute, Daejeon, South KoreaVarious modal identification methods for interarea modes have been developed to improve identification accuracy by overcoming the measurement noise in ambient data of phasor measurement units (PMUs). In this study, a modal identification method that is insensitive to measurement noise is proposed by introducing bandpass filters, which extract a modal signal from an autocorrelation function of PMU ambient data. The bandwidth of the filters is set to be adequately narrow such that the noise can be rejected sufficiently. To reduce the computational burden of the proposed method, the filters are designed by transforming a reference lowpass filter. An autoregressive exogenous (ARX) model of interarea modes is applied to the extracted modal signal. The parameters of the ARX model are estimated for modal identification via the least squares method. The identification accuracy of the proposed method is compared with those of conventional modified extended Yule Walker and discrete Fourier transform methods with respect to the signal-to-noise ratio and modal damping by using synthetic ambient data. Finally, the feasibility of the proposed method is demonstrated by identifying interarea modes of Kundur’s two-area four-machine system and two real power systems in South Korea.https://ieeexplore.ieee.org/document/9381196/Ambient dataautocorrelation functionautoregressive exogenous modelbandpass filterimpulse functioninterarea oscillations |
| spellingShingle | Jin Kwon Hwang Jeonghoon Shin Identification of Interarea Modes From Ambient Data of Phasor Measurement Units Using an Autoregressive Exogenous Model IEEE Access Ambient data autocorrelation function autoregressive exogenous model bandpass filter impulse function interarea oscillations |
| title | Identification of Interarea Modes From Ambient Data of Phasor Measurement Units Using an Autoregressive Exogenous Model |
| title_full | Identification of Interarea Modes From Ambient Data of Phasor Measurement Units Using an Autoregressive Exogenous Model |
| title_fullStr | Identification of Interarea Modes From Ambient Data of Phasor Measurement Units Using an Autoregressive Exogenous Model |
| title_full_unstemmed | Identification of Interarea Modes From Ambient Data of Phasor Measurement Units Using an Autoregressive Exogenous Model |
| title_short | Identification of Interarea Modes From Ambient Data of Phasor Measurement Units Using an Autoregressive Exogenous Model |
| title_sort | identification of interarea modes from ambient data of phasor measurement units using an autoregressive exogenous model |
| topic | Ambient data autocorrelation function autoregressive exogenous model bandpass filter impulse function interarea oscillations |
| url | https://ieeexplore.ieee.org/document/9381196/ |
| work_keys_str_mv | AT jinkwonhwang identificationofinterareamodesfromambientdataofphasormeasurementunitsusinganautoregressiveexogenousmodel AT jeonghoonshin identificationofinterareamodesfromambientdataofphasormeasurementunitsusinganautoregressiveexogenousmodel |