Identification of Low-Frequency Oscillation Modes Using PMU Based Data-Driven Dynamic Mode Decomposition Algorithm
Power system inter-area oscillations curtail the power transferring capabilities of the transmission lines in a large interconnected power system. Accurate identification of dominant modes and associated contributing generators is important to avoid power system failures by taking appropriate remedi...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9383277/ |
| _version_ | 1819291238107447296 |
|---|---|
| author | Mohd Zuhaib Mohd Rihan |
| author_facet | Mohd Zuhaib Mohd Rihan |
| author_sort | Mohd Zuhaib |
| collection | DOAJ |
| description | Power system inter-area oscillations curtail the power transferring capabilities of the transmission lines in a large interconnected power system. Accurate identification of dominant modes and associated contributing generators is important to avoid power system failures by taking appropriate remedial measures. This paper proposes a multi-channel Improved Dynamic Mode Decomposition (IDMD) algorithm-based modal analysis technique using Synchrophasors measurement. First, a reduced-order dynamic power system model is estimated and using this model dominant oscillation modes, corresponding modes shapes, damping ratio, coherent group of generators, participation factors are determined. To improve the accuracy data stacking technique is used to capture detailed information of the system. An optimal hard threshold technique is utilized to select the most optimal model order to avoid uncertainties due to the presence of high level of measurement noise. The study results show that the proposed algorithm gives an accurate and robust solution even in systems having high level of noise in the measurement data. The performance of the proposed technique is tested on simulated data from two-area four-machine system and wNAPS 41-bus 16-generator system with PMU measurements corrupted with different levels of measurement noise. To further strengthen the viewpoint, the proposed method is validated on real-time PMU measurement from ISO New England data to validate the accuracy of the proposed work. |
| first_indexed | 2024-12-24T03:35:27Z |
| format | Article |
| id | doaj.art-3f7c8a7c06f348548e2d6ed3533ce85f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-24T03:35:27Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-3f7c8a7c06f348548e2d6ed3533ce85f2022-12-21T17:17:04ZengIEEEIEEE Access2169-35362021-01-019494344944710.1109/ACCESS.2021.30682279383277Identification of Low-Frequency Oscillation Modes Using PMU Based Data-Driven Dynamic Mode Decomposition AlgorithmMohd Zuhaib0https://orcid.org/0000-0001-8454-669XMohd Rihan1Department of Electrical Engineering, Z.H. College of Engineering and Technology (ZHCET), Aligarh Muslim University (AMU), Aligarh, IndiaDepartment of Electrical Engineering, Z.H. College of Engineering and Technology (ZHCET), Aligarh Muslim University (AMU), Aligarh, IndiaPower system inter-area oscillations curtail the power transferring capabilities of the transmission lines in a large interconnected power system. Accurate identification of dominant modes and associated contributing generators is important to avoid power system failures by taking appropriate remedial measures. This paper proposes a multi-channel Improved Dynamic Mode Decomposition (IDMD) algorithm-based modal analysis technique using Synchrophasors measurement. First, a reduced-order dynamic power system model is estimated and using this model dominant oscillation modes, corresponding modes shapes, damping ratio, coherent group of generators, participation factors are determined. To improve the accuracy data stacking technique is used to capture detailed information of the system. An optimal hard threshold technique is utilized to select the most optimal model order to avoid uncertainties due to the presence of high level of measurement noise. The study results show that the proposed algorithm gives an accurate and robust solution even in systems having high level of noise in the measurement data. The performance of the proposed technique is tested on simulated data from two-area four-machine system and wNAPS 41-bus 16-generator system with PMU measurements corrupted with different levels of measurement noise. To further strengthen the viewpoint, the proposed method is validated on real-time PMU measurement from ISO New England data to validate the accuracy of the proposed work.https://ieeexplore.ieee.org/document/9383277/Phasor measurement unitwide area monitoring systemdynamic mode decomposition algorithmeigensystem realization algorithmlow-frequency oscillations |
| spellingShingle | Mohd Zuhaib Mohd Rihan Identification of Low-Frequency Oscillation Modes Using PMU Based Data-Driven Dynamic Mode Decomposition Algorithm IEEE Access Phasor measurement unit wide area monitoring system dynamic mode decomposition algorithm eigensystem realization algorithm low-frequency oscillations |
| title | Identification of Low-Frequency Oscillation Modes Using PMU Based Data-Driven Dynamic Mode Decomposition Algorithm |
| title_full | Identification of Low-Frequency Oscillation Modes Using PMU Based Data-Driven Dynamic Mode Decomposition Algorithm |
| title_fullStr | Identification of Low-Frequency Oscillation Modes Using PMU Based Data-Driven Dynamic Mode Decomposition Algorithm |
| title_full_unstemmed | Identification of Low-Frequency Oscillation Modes Using PMU Based Data-Driven Dynamic Mode Decomposition Algorithm |
| title_short | Identification of Low-Frequency Oscillation Modes Using PMU Based Data-Driven Dynamic Mode Decomposition Algorithm |
| title_sort | identification of low frequency oscillation modes using pmu based data driven dynamic mode decomposition algorithm |
| topic | Phasor measurement unit wide area monitoring system dynamic mode decomposition algorithm eigensystem realization algorithm low-frequency oscillations |
| url | https://ieeexplore.ieee.org/document/9383277/ |
| work_keys_str_mv | AT mohdzuhaib identificationoflowfrequencyoscillationmodesusingpmubaseddatadrivendynamicmodedecompositionalgorithm AT mohdrihan identificationoflowfrequencyoscillationmodesusingpmubaseddatadrivendynamicmodedecompositionalgorithm |