Abstract
Original language | English |
---|---|
Pages (from-to) | 610-620 |
Journal | IEEE Transactions on Power Systems |
Volume | 24 |
Issue number | 2 |
DOIs | |
Publication status | Published - 10 Apr 2009 |
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Bibliographical note
The full text is not available on the repository.Keywords
- masking
- Convolution filter
- empirical mode decomposition
- Hilbert–Huang transform
- interarea oscillation
- nonstationary oscillation analysis
- refined Hilbert-Huang transform
- interarea oscillation monitoring
- power systems transient response
- masking techniques
- local Hilbert transformer
- power system model
- critical system modes
- power system transients
- Hilbert transforms
- oscillations
- Monitoring
- Power system modeling
- Power system simulation
- Power system analysis computing
- Power system dynamics
- Data mining
- Power system harmonics
- Frequency
- Power system stability
- Filters
Cite this
A Refined Hilbert–Huang Transform With Applications to Interarea Oscillation Monitoring. / Laila, Dina Shona; Messina, A. R.; Pal, B. C.
In: IEEE Transactions on Power Systems, Vol. 24, No. 2, 10.04.2009, p. 610-620.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A Refined Hilbert–Huang Transform With Applications to Interarea Oscillation Monitoring
AU - Laila, Dina Shona
AU - Messina, A. R.
AU - Pal, B. C.
N1 - The full text is not available on the repository.
PY - 2009/4/10
Y1 - 2009/4/10
N2 - This paper focuses on the refinement of standard Hilbert-Huang transform (HHT) technique to accurately characterize time varying, multicomponents interarea oscillations. Several improved masking techniques for empirical mode decomposition (EMD) and a local Hilbert transformer are proposed and a number of issues regarding their use and interpretation are identified. Simulated response data from a complex power system model are used to assess the efficacy of the proposed techniques for capturing the temporal evolution of critical system modes. It is shown that the combination of the proposed methods result in superior frequency and temporal resolution than other approaches for analyzing complicated nonstationary oscillations.
AB - This paper focuses on the refinement of standard Hilbert-Huang transform (HHT) technique to accurately characterize time varying, multicomponents interarea oscillations. Several improved masking techniques for empirical mode decomposition (EMD) and a local Hilbert transformer are proposed and a number of issues regarding their use and interpretation are identified. Simulated response data from a complex power system model are used to assess the efficacy of the proposed techniques for capturing the temporal evolution of critical system modes. It is shown that the combination of the proposed methods result in superior frequency and temporal resolution than other approaches for analyzing complicated nonstationary oscillations.
KW - masking
KW - Convolution filter
KW - empirical mode decomposition
KW - Hilbert–Huang transform
KW - interarea oscillation
KW - nonstationary oscillation analysis
KW - refined Hilbert-Huang transform
KW - interarea oscillation monitoring
KW - power systems transient response
KW - masking techniques
KW - local Hilbert transformer
KW - power system model
KW - critical system modes
KW - power system transients
KW - Hilbert transforms
KW - oscillations
KW - Monitoring
KW - Power system modeling
KW - Power system simulation
KW - Power system analysis computing
KW - Power system dynamics
KW - Data mining
KW - Power system harmonics
KW - Frequency
KW - Power system stability
KW - Filters
U2 - 10.1109/TPWRS.2009.2016478
DO - 10.1109/TPWRS.2009.2016478
M3 - Article
VL - 24
SP - 610
EP - 620
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
SN - 0885-8950
IS - 2
ER -