An Under Voltage Load Shedding Scheme Based on a Short Term Voltage Instability Detection Method

Arun Joseph; Milos Cvetkovic; Peter Palensky

doi:10.1049/cp.2018.1881

An Under Voltage Load Shedding Scheme Based on a Short Term Voltage Instability Detection Method

Arun Joseph, Milos Cvetkovic, Peter Palensky

Intelligent Electrical Power Grids

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

70 Downloads (Pure)

Abstract

Faster detection of faults, can lead to better and
more efficient control of power system against cascading failures
triggered by the faults. This article presents a novel detection
algorithm using statistical methods for the detection of events
that lead to FIDVR. Furthermore we show that the algorithm is
computationally efficient and quick enough to provide the control
inputs to an UVLS scheme using in-feed PMU data. Thus, it is
ensured that the minimal level of load to be shed is determined
on-the-fly as the event develops.

Original language	English
Title of host publication	Proceedings of 2018 MEDPOWER conference
Publisher	IEEE
Number of pages	6
ISBN (Print)	978-1-83953-133-0
DOIs	https://doi.org/10.1049/cp.2018.1881
Publication status	Published - 2019
Event	11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion - Dubrovnik, Croatia Duration: 12 Nov 2018 → 15 Nov 2018 http://medpower2018.com/

Conference

Conference	11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion
Abbreviated title	MEDPOWER 2018
Country	Croatia
City	Dubrovnik
Period	12/11/18 → 15/11/18
Internet address	http://medpower2018.com/

Access to Document

10.1049/cp.2018.1881

Medpower-AJAccepted author manuscript, 449 KBLicence: Unspecified

Fingerprint Dive into the research topics of 'An Under Voltage Load Shedding Scheme Based on a Short Term Voltage Instability Detection Method'. Together they form a unique fingerprint.

Cite this

@inproceedings{3170094e14464106b17cb57eb3f86f61,

title = "An Under Voltage Load Shedding Scheme Based on a Short Term Voltage Instability Detection Method",

abstract = "Faster detection of faults, can lead to better andmore efficient control of power system against cascading failurestriggered by the faults. This article presents a novel detectionalgorithm using statistical methods for the detection of eventsthat lead to FIDVR. Furthermore we show that the algorithm iscomputationally efficient and quick enough to provide the controlinputs to an UVLS scheme using in-feed PMU data. Thus, it isensured that the minimal level of load to be shed is determinedon-the-fly as the event develops.",

author = "Arun Joseph and Milos Cvetkovic and Peter Palensky",

year = "2019",

doi = "10.1049/cp.2018.1881",

language = "English",

isbn = "978-1-83953-133-0",

booktitle = "Proceedings of 2018 MEDPOWER conference",

publisher = "IEEE",

address = "United States",

note = "11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, MEDPOWER 2018 ; Conference date: 12-11-2018 Through 15-11-2018",

url = "http://medpower2018.com/",

}

TY - GEN

T1 - An Under Voltage Load Shedding Scheme Based on a Short Term Voltage Instability Detection Method

AU - Joseph, Arun

AU - Cvetkovic, Milos

AU - Palensky, Peter

PY - 2019

Y1 - 2019

N2 - Faster detection of faults, can lead to better andmore efficient control of power system against cascading failurestriggered by the faults. This article presents a novel detectionalgorithm using statistical methods for the detection of eventsthat lead to FIDVR. Furthermore we show that the algorithm iscomputationally efficient and quick enough to provide the controlinputs to an UVLS scheme using in-feed PMU data. Thus, it isensured that the minimal level of load to be shed is determinedon-the-fly as the event develops.

AB - Faster detection of faults, can lead to better andmore efficient control of power system against cascading failurestriggered by the faults. This article presents a novel detectionalgorithm using statistical methods for the detection of eventsthat lead to FIDVR. Furthermore we show that the algorithm iscomputationally efficient and quick enough to provide the controlinputs to an UVLS scheme using in-feed PMU data. Thus, it isensured that the minimal level of load to be shed is determinedon-the-fly as the event develops.

U2 - 10.1049/cp.2018.1881

DO - 10.1049/cp.2018.1881

M3 - Conference contribution

SN - 978-1-83953-133-0

BT - Proceedings of 2018 MEDPOWER conference

PB - IEEE

T2 - 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion

Y2 - 12 November 2018 through 15 November 2018

ER -