Thesis
Power spectrum estimation for frequency domain ambient modal analysis and oscillation monitoring
Washington State University
Master of Science (MS), Washington State University
12/2020
DOI:
https://doi.org/10.7273/000000062
Handle:
https://hdl.handle.net/2376/111079
Abstract
This thesis studies the effect of different Power Spectrum Density (PSD) estimation
techniques on the accuracy of the Fast Frequency Domain Decomposition (FFDD) method. The
FFDD technique utilizes ambient synchrophasor measurements to estimate the frequency,
damping ratio, energy and mode shape of dominant system modes by analyzing the PSD matrix
from multiple synchrophasor measurements. In this thesis, the impact of three different methods
for PSD estimation on the accuracy of FFDD modal estimates is investigated: PWelch,
MultiTaper Method (MTM) using Slepian Tapers, and MTM using Sine Tapers. Tests are done
using synthetic and archived synchrophasor data. All three PSD methods are shown to work well
for oscillation detection of synthetic sustained oscillations using FFDD. However, for ambient
modal analysis, it is shown that FFDD based on MTM with Slepian Tapers has the most reliable
modal estimations among the three methods. FFDD using both MTM with Sine Tapers and
PWelch have bias issues in estimating well-damped system modes, requiring more research for
them to be suitable for FFDD.
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Details
- Title
- Power spectrum estimation for frequency domain ambient modal analysis and oscillation monitoring
- Creators
- CHAD E THOMAS
- Contributors
- VAITHIANATH VENKATASUBRAMANIAN (Degree Supervisor) - Washington State University, Electrical Engineering and Computer Science, School ofANJAN BOSE (Committee Member) - Washington State University, Electrical Engineering and Computer Science, School ofKRISHNAMOORTHY SIVAKUMAR (Committee Member) - Washington State University, Voiland College of Engineering and Architecture
- Awarding Institution
- Washington State University
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University
- Format
- pdf
- Number of pages
- 50
- Identifiers
- 99900586063501842
- Resource Type
- Thesis