Abstract
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.
| 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 |
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