@inproceedings{f479098635a7419e9fb34477096db456,
title = "Identification of stable and unstable power swings using pattern recognition",
abstract = "Faults during symmetrical power swings cause maloperation of distance relay. Undesired operation also occurs during unstable power swings causing uncontrolled islanding. Faster detection of faults during power swings and classification of power swings can assist the protection system in making reliable decisions on blocking or unblocking a relay's operation. This paper segregates the faults, faults during power swing from power swings in one-cycle with an accuracy of 99.3%. It then identifies the different power swings in 10 cycles that occur in a 9-bus WSCC power system. Support Vector Machines (SVM), Decision Tree (DT), and k-Nearest Neighbor (kNN) classifiers are trained and tested on six features obtained from 3-phase(ph) relay voltage and current to test the validity of the detection and classification scheme. The different faults, faults during swings, and power swings are simulated in PSCAD/EMTDC.",
keywords = "DT, Distance Protection, KNN, SVM, Stable Unstable Power Swings, Symmetrical Asymmetrical Swings",
author = "Bera, {Pallav Kumar} and Can Isik",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 13th Annual IEEE Green Technologies Conference, GREENTECH 2021 ; Conference date: 07-04-2021 Through 09-04-2021",
year = "2021",
month = apr,
doi = "10.1109/GreenTech48523.2021.00053",
language = "English (US)",
series = "IEEE Green Technologies Conference",
publisher = "IEEE Computer Society",
pages = "286--291",
booktitle = "Proceedings - 2021 13th Annual IEEE Green Technologies Conference, GREENTECH 2021",
address = "United States",
}