Transient stability assessment by pattern recognition in the frequency domain

Dejan R. Ostojic; G. Thomas Heydt

doi:10.1109/59.131067

Transient stability assessment by pattern recognition in the frequency domain

Dejan R. Ostojic, G. Thomas Heydt

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

Abstract

A pattern recognition methodology is presented which utilizes spectral monitoring of electromechanical oscillations to assess the transient stability of interconnected power systems. The proposed frequency-domain approach permits definitive recognition of unstable dynamic nodes. This is used to design an adaptive linear classifier which, in the developmental implementation, virtually eliminates both false dismissals and false alarms. The result is an accurate and reliable decision-making system which performs transient stability monitoring and assessment in real time.

Original language	English (US)
Pages (from-to)	231-237
Number of pages	7
Journal	IEEE Transactions on Power Systems
Volume	6
Issue number	2
DOIs	https://doi.org/10.1109/59.131067
State	Published - 1991
Externally published	Yes

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering

Access to Document

10.1109/59.131067

Cite this

@article{d0ba69c9100b413faa01e21b43a4b122,

title = "Transient stability assessment by pattern recognition in the frequency domain",

abstract = "A pattern recognition methodology is presented which utilizes spectral monitoring of electromechanical oscillations to assess the transient stability of interconnected power systems. The proposed frequency-domain approach permits definitive recognition of unstable dynamic nodes. This is used to design an adaptive linear classifier which, in the developmental implementation, virtually eliminates both false dismissals and false alarms. The result is an accurate and reliable decision-making system which performs transient stability monitoring and assessment in real time.",

author = "Ostojic, {Dejan R.} and Heydt, {G. Thomas}",

year = "1991",

doi = "10.1109/59.131067",

language = "English (US)",

volume = "6",

pages = "231--237",

journal = "IEEE Transactions on Power Systems",

issn = "0885-8950",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "2",

}

TY - JOUR

T1 - Transient stability assessment by pattern recognition in the frequency domain

AU - Ostojic, Dejan R.

AU - Heydt, G. Thomas

PY - 1991

Y1 - 1991

N2 - A pattern recognition methodology is presented which utilizes spectral monitoring of electromechanical oscillations to assess the transient stability of interconnected power systems. The proposed frequency-domain approach permits definitive recognition of unstable dynamic nodes. This is used to design an adaptive linear classifier which, in the developmental implementation, virtually eliminates both false dismissals and false alarms. The result is an accurate and reliable decision-making system which performs transient stability monitoring and assessment in real time.

AB - A pattern recognition methodology is presented which utilizes spectral monitoring of electromechanical oscillations to assess the transient stability of interconnected power systems. The proposed frequency-domain approach permits definitive recognition of unstable dynamic nodes. This is used to design an adaptive linear classifier which, in the developmental implementation, virtually eliminates both false dismissals and false alarms. The result is an accurate and reliable decision-making system which performs transient stability monitoring and assessment in real time.

UR - http://www.scopus.com/inward/record.url?scp=0026104649&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026104649&partnerID=8YFLogxK

U2 - 10.1109/59.131067

DO - 10.1109/59.131067

M3 - Article

AN - SCOPUS:0026104649

SN - 0885-8950

VL - 6

SP - 231

EP - 237

JO - IEEE Transactions on Power Systems

JF - IEEE Transactions on Power Systems

IS - 2

ER -

Transient stability assessment by pattern recognition in the frequency domain

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this