Power system disturbance monitoring using spectrum analysis

Miroslav M. Begovic; Petar M. Djuric

Power system disturbance monitoring using spectrum analysis

Miroslav M. Begovic
, Petar M. Djuric

Electrical Engineering

Stony Brook University

Georgia Institute of Technology

Research output: Contribution to journal › Conference article › peer-review

Abstract

The advent of new and emerging technologies for monitoring and control of power networks opens possibilities for implementation of new algorithms. Spectrum analysis is one of the techniques which has a potential for real-time control. This paper proposes a new and computationally non-demanding algorithm for spectrum analysis of the sampled instantaneous frequency data, based on recursive least squares tracking. The algorithm, which has remarkably low computational requirements, is illustrated by simulation on a 16-machine test system.

Original language	English
Pages (from-to)	689-692
Number of pages	4
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	1
State	Published - 1996
Event	Proceedings of the 1996 IEEE International Symposium on Circuits and Systems, ISCAS. Part 1 (of 4) - Atlanta, GA, USA Duration: May 12 1996 → May 15 1996

Cite this

@article{b63ef0602f7049808b0507d39e9107e7,

title = "Power system disturbance monitoring using spectrum analysis",

abstract = "The advent of new and emerging technologies for monitoring and control of power networks opens possibilities for implementation of new algorithms. Spectrum analysis is one of the techniques which has a potential for real-time control. This paper proposes a new and computationally non-demanding algorithm for spectrum analysis of the sampled instantaneous frequency data, based on recursive least squares tracking. The algorithm, which has remarkably low computational requirements, is illustrated by simulation on a 16-machine test system.",

author = "Begovic, \{Miroslav M.\} and Djuric, \{Petar M.\}",

year = "1996",

language = "English",

volume = "1",

pages = "689--692",

journal = "Proceedings - IEEE International Symposium on Circuits and Systems",

issn = "0271-4310",

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

note = "Proceedings of the 1996 IEEE International Symposium on Circuits and Systems, ISCAS. Part 1 (of 4) ; Conference date: 12-05-1996 Through 15-05-1996",

}

TY - JOUR

T1 - Power system disturbance monitoring using spectrum analysis

AU - Begovic, Miroslav M.

AU - Djuric, Petar M.

PY - 1996

Y1 - 1996

N2 - The advent of new and emerging technologies for monitoring and control of power networks opens possibilities for implementation of new algorithms. Spectrum analysis is one of the techniques which has a potential for real-time control. This paper proposes a new and computationally non-demanding algorithm for spectrum analysis of the sampled instantaneous frequency data, based on recursive least squares tracking. The algorithm, which has remarkably low computational requirements, is illustrated by simulation on a 16-machine test system.

AB - The advent of new and emerging technologies for monitoring and control of power networks opens possibilities for implementation of new algorithms. Spectrum analysis is one of the techniques which has a potential for real-time control. This paper proposes a new and computationally non-demanding algorithm for spectrum analysis of the sampled instantaneous frequency data, based on recursive least squares tracking. The algorithm, which has remarkably low computational requirements, is illustrated by simulation on a 16-machine test system.

UR - https://www.scopus.com/pages/publications/0029720739

M3 - Conference article

SN - 0271-4310

VL - 1

SP - 689

EP - 692

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

T2 - Proceedings of the 1996 IEEE International Symposium on Circuits and Systems, ISCAS. Part 1 (of 4)

Y2 - 12 May 1996 through 15 May 1996

ER -

Power system disturbance monitoring using spectrum analysis

Abstract

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