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Dissertation
OSCILLATION DETECTION AND ANALYSIS IN POWER SYSTEMS WITH SCADA USING INFERENTIAL STATISTICS
Doctor of Philosophy (PhD), Washington State University
12/2025
DOI:
https://doi.org/10.7273/000008350
Abstract
The analysis of oscillations is of vital importance for stable, secure, and reliable power system operations. Recently, many algorithms have been proposed to identify potential forced oscillation sources using synchrophasors. However, the synchrophasor coverage is limited in several systems, and the oscillation source may not be monitored by nearby synchrophasor measurements. In this regard, SCADA measurements are helpful because of their extensive presence in the power grids worldwide. Although SCADA has a much lower reporting rate than synchrophasors, the asynchronous polling nature of SCADA data can be utilized to estimate the amplitude of oscillations at different locations. In this dissertation, two rigorous algorithms based on inferential statistics are developed to analyze the amplitude of oscillations seen in the SCADA data. These algorithms initially depend on the timestamp information corresponding to the start and end of an oscillation event from synchrophasors for analysis purposes. In the later chapter of the dissertation, it is investigated and tested with field measurements that the proposed algorithms with proper modifications can also detect and analyze high amplitude signals from an oscillation event with SCADA data only. The amplitude analysis offers valuable insights into the potential source and nature of forced oscillations. Several simulation-based test cases and archived event data from the European and Western American interconnections have been tested with the proposed algorithms, which provide the correct ranking of generator oscillation amplitudes in all these events.
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Details
- Title
- OSCILLATION DETECTION AND ANALYSIS IN POWER SYSTEMS WITH SCADA USING INFERENTIAL STATISTICS
- Creators
- Salman Siddique Shiuab
- Contributors
- Mani V. Venkatasubramanian (Chair)Anjan Bose (Committee Member)Krishnamoorthy Sivakumar (Committee Member)Venkata K. Jandhyala (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
- 110
- Identifiers
- 99901357595901842
- Language
- English
- Resource Type
- Dissertation