Fast Algorithms for Estimating the Disturbance Inception Time in Power Systems Based on Time Series of Instantaneous Values of Current and Voltage with a High Sampling Rate

Simple item page
dc.contributor.authorSenyuk, Mihail
dc.contributor.authorBeryozkina, Svetlana
dc.contributor.authorGubin, Pavel
dc.contributor.authorDmitrieva, Anna
dc.contributor.authorKamalov, Firuz
dc.contributor.authorSafaraliev, Murodbek
dc.contributor.authorZicmane, Inga
dc.date.accessioned2022-12-22T06:49:46Z
dc.date.available2022-12-22T06:49:46Z
dc.date.copyright© 2022
dc.date.issued2022-11
dc.description.abstractThe study examines the development and testing of algorithms for disturbance inception time estimation in a power system using instantaneous values of current and voltage with a high sampling rate. The algorithms were tested on both modeled and physical data. The error of signal extremum forecast, the error of signal form forecast, and the signal value at the so-called joint point provided the basis for the suggested algorithms. The method of tuning for each algorithm was described. The time delay and accuracy of the algorithms were evaluated with varying tuning parameters. The algorithms were tested on the two-machine model of a power system in Matlab/Simulink. Signals from emergency event recorders installed on real power facilities were used in testing procedures. The results of this study indicated a possible and promising application of the suggested methods in the emergency control of power systems. © 2022 by the authors.
dc.identifier.citationSenyuk, M., Beryozkina, S., Gubin, P., Dmitrieva, A., Kamalov, F., Safaraliev, M., & Zicmane, I. (2022). Fast algorithms for estimating the disturbance inception time in power systems based on time series of instantaneous values of current and voltage with a high sampling rate. Mathematics, 10(21) doi:10.3390/math10213949
dc.identifier.issn22277390
dc.identifier.urihttps://doi.org/10.3390/math10213949
dc.identifier.urihttps://hdl.handle.net/20.500.12519/736
dc.language.isoen_US
dc.publisherMDPI
dc.relationAuthors Affiliations : Senyuk, M., Department of Automated Electrical Systems, Ural Federal University, Yekaterinburg, 620002, Russian Federation; Beryozkina, S., College of Engineering and Technology, American University of the Middle East, Kuwait; Gubin, P., Department of Automated Electrical Systems, Ural Federal University, Yekaterinburg, 620002, Russian Federation; Dmitrieva, A., Department of Automated Electrical Systems, Ural Federal University, Yekaterinburg, 620002, Russian Federation; Kamalov, F., Department of Electrical Engineering, Canadian University Dubai, Dubai, 117781, United Arab Emirates; Safaraliev, M., Department of Automated Electrical Systems, Ural Federal University, Yekaterinburg, 620002, Russian Federation; Zicmane, I., Faculty of Electrical and Environmental Engineering, Riga Technical University, Riga, LV-1048, Latvia
dc.relation.ispartofseriesMathematics; Volume 10, Issue 21
dc.rightsCreative Commons Attribution (CC BY) license
dc.rights.holderCopyright : © 2022 by the authors.
dc.rights.uri(https://creativecommons.org/licenses/by/4.0/).
dc.subjectapproximation
dc.subjectdigital signal processing
dc.subjectmathematical modeling
dc.subjectpower system
dc.subjectstatistical analysis
dc.subjecttime-series analysis
dc.titleFast Algorithms for Estimating the Disturbance Inception Time in Power Systems Based on Time Series of Instantaneous Values of Current and Voltage with a High Sampling Rate
dc.typeArticle

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
736.pdf
Size:
860.18 KB
Format:
Adobe Portable Document Format
Description:
Download

Collections

Department of Electrical Engineering