Dissertation
Frequency domain dynamic analysis in power systems using data from phasor measurement units
Doctor of Philosophy (PhD), Washington State University
01/2018
Handle:
https://hdl.handle.net/2376/108006
Abstract
The data provided by phasor measurement units or PMUs being time-synchronized with a sampling rate of 30-60 Hz has made it possible to monitor system dynamics in real-time through various measurement-based modal analysis techniques. These methods are categorized into two general groups based on the type of their inputs; Ringdown methods that use temporary, transient signals for modal analysis and, ambient methods that apply system identification techniques on the ambient part of data which is considered the system’s response to random and small load fluctuations. A tool that can provide comprehensive modal analyses in all data situations is the one that is able to identify each type of data, apply accurate ambient and ringdown modal algorithms on the selected set of data and, offer a quantitative evaluation on the quality of its estimation.
Given the sensitivity of PMU-based methods to the quality of input data, threshold-based event detection methods that distinguish transient from ambient data might not be sufficient for a modal analysis tool. In chapter two of this dissertation, a supervisory framework for identifying the best part of data for dynamic analysis is suggested which is based on the characteristics of the empirical distribution of data. Data from real PMUs were collected and two hypotheses, Gaussian distribution and one sinusoidal component plus Gaussian noise, were tested for their probability density function. The proposed framework reveals quality issues of the data as well as sustained or transient oscillations.
In chapter three, for the cases of transients, this dissertation introduces an accurate iterative frequency-domain algorithm to estimate the oscillatory modes of a system from post-disturbance measured data of multiple PMUs. The proposed algorithm estimates the modal content of the signal and then modifies the previous estimation based on the new estimations. The parameter estimation in this method is solely based on the Fourier transform of the signal.
In chapter four, quantitative indicators founded in rigorous theory to assess the quality of estimation are proposed. Two different indicators, based on frequency domain and time domain formulations respectively, are introduced and are illustrated on power system identification problems.
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Details
- Title
- Frequency domain dynamic analysis in power systems using data from phasor measurement units
- Creators
- Ebrahim Rezaei
- Contributors
- Vaithianathan Venkatasubramanian (Advisor)Anjan Bose (Committee Member)Krishnamoorthy Sivakumar (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- School of Electrical Engineering and Computer Science
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Number of pages
- 103
- Identifiers
- 99900581819401842
- Language
- English
- Resource Type
- Dissertation