Sponsor
Funding for this work was provided by Portland General Electric.
Published In
2023 IEEE Conference on Technologies for Sustainability (SusTech)
Document Type
Post-Print
Publication Date
4-2023
Subjects
Electric power failures -- Mathematical models
Abstract
In power systems, frequency deviation from nominal value can occur due to reasons such as loss of generation, loss of load, or major faults in the grid. Such frequency fluctuations can lead to serious subsequent outages and damages to both end-user and utility equipment. Therefore, a proper frequency deviation detection methodology must be in place to effectively identify frequency events in a timely manner. This manuscript provides a comparative analysis between two frequency deviation detection algorithms. One is based on signal processing and statistical analysis. The other is a regression-based algorithm. Both of these algorithms have multiple adjustable parameters, making them highly tunable for different Balancing Authorities.
Rights
© 2023 IEEE
DOI
10.1109/SusTech57309.2023.10129580
Persistent Identifier
https://archives.pdx.edu/ds/psu/40116
Citation Details
H. A. Alghamdi, M. A. Adham, U. Farooq and R. B. Bass, "Detecting Fast Frequency Events in Power System: Development and Comparison of Two Methods," [POST-PRINT] 2023 IEEE Conference on Technologies for Sustainability (SusTech), Portland, OR, USA, 2023, pp. 55-62,
Description
This is the author’s version of a work that was accepted for publication in 2023 IEEE Conference on Technologies for Sustainability (SusTech). Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in 2023 IEEE Conference on Technologies for Sustainability (SusTech).