Prediction of Short-Term Voltage Instability Using a Digital Faster Than Real-Time Replica

Arun Joseph; Milos Cvetkovic; Peter Palensky

doi:10.1109/IECON.2018.8592818

Prediction of Short-Term Voltage Instability Using a Digital Faster Than Real-Time Replica

Arun Joseph, Milos Cvetkovic, Peter Palensky

Intelligent Electrical Power Grids

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

4 Citations (Scopus)

68 Downloads (Pure)

Abstract

Predictive analysis of post fault system dynamic behavior can be a vital resource for better control and reliability improvement of the overall system. This article presents methods for predictive analysis of Fault Induced Dynamic Voltage Recovery (FIDVR) event using a faster than real-time digital replica of a power system. The methods proposed include use of quick algorithms for detection of FIDVR events and metrics for predicting dynamic behavior of the power system impacted by the detected FIDVR event. We show that, using a digital faster than real-time replica, the FIDVR event can be detected in required time and that the transient voltage deviation index (TVDI) can be quickly calculated.

Original language	English
Title of host publication	Proceedings IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	3582-3587
Number of pages	6
ISBN (Electronic)	978-1-5090-6684-1
DOIs	https://doi.org/10.1109/IECON.2018.8592818
Publication status	Published - 2018
Event	IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society - Omni Shoreham Hotel, Washington D.C., United States Duration: 21 Oct 2018 → 23 Oct 2018 Conference number: 44 http://www.iecon2018.org/

Conference

Conference	IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
Abbreviated title	IECON
Country/Territory	United States
City	Washington D.C.
Period	21/10/18 → 23/10/18
Internet address	http://www.iecon2018.org/

Bibliographical note

"Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public."

Keywords

Fault Induced Dynamic Voltage Recovery (FIDVR)
Phasor Measurement Unit (PMU)
Short-Term Voltage Instability (STVI)
Voltage Stability Indices (VSI)
Faster Than Real-Time Digital Replica (FTRTDR)
Transient Voltage Deviation Index (TVDI)

Access to Document

10.1109/IECON.2018.8592818

Prediction_of_Short-Term_Voltage_Instability_Using_a_Digital_Faster_than_Real-Time_ReplicaFinal published version, 557 KB

Cite this

@inproceedings{b1a2a382e32c46cabd4245bd80ef62c1,

title = "Prediction of Short-Term Voltage Instability Using a Digital Faster Than Real-Time Replica",

abstract = "Predictive analysis of post fault system dynamic behavior can be a vital resource for better control and reliability improvement of the overall system. This article presents methods for predictive analysis of Fault Induced Dynamic Voltage Recovery (FIDVR) event using a faster than real-time digital replica of a power system. The methods proposed include use of quick algorithms for detection of FIDVR events and metrics for predicting dynamic behavior of the power system impacted by the detected FIDVR event. We show that, using a digital faster than real-time replica, the FIDVR event can be detected in required time and that the transient voltage deviation index (TVDI) can be quickly calculated. ",

keywords = "Fault Induced Dynamic Voltage Recovery (FIDVR), Phasor Measurement Unit (PMU), Short-Term Voltage Instability (STVI), Voltage Stability Indices (VSI), Faster Than Real-Time Digital Replica (FTRTDR), Transient Voltage Deviation Index (TVDI)",

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

note = "{"}Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.{"} ; IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, IECON ; Conference date: 21-10-2018 Through 23-10-2018",

year = "2018",

doi = "10.1109/IECON.2018.8592818",

language = "English",

pages = "3582--3587",

booktitle = "Proceedings IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society",

publisher = "IEEE",

address = "United States",

url = "http://www.iecon2018.org/",

}

Joseph, A, Cvetkovic, M & Palensky, P 2018, Prediction of Short-Term Voltage Instability Using a Digital Faster Than Real-Time Replica. in Proceedings IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. IEEE, Piscataway, NJ, pp. 3582-3587, IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, Washington D.C., United States, 21/10/18. https://doi.org/10.1109/IECON.2018.8592818

Prediction of Short-Term Voltage Instability Using a Digital Faster Than Real-Time Replica. / Joseph, Arun; Cvetkovic, Milos ; Palensky, Peter.
Proceedings IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. Piscataway, NJ: IEEE, 2018. p. 3582-3587.

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

TY - GEN

T1 - Prediction of Short-Term Voltage Instability Using a Digital Faster Than Real-Time Replica

AU - Joseph, Arun

AU - Cvetkovic, Milos

AU - Palensky, Peter

N1 - Conference code: 44

PY - 2018

Y1 - 2018

N2 - Predictive analysis of post fault system dynamic behavior can be a vital resource for better control and reliability improvement of the overall system. This article presents methods for predictive analysis of Fault Induced Dynamic Voltage Recovery (FIDVR) event using a faster than real-time digital replica of a power system. The methods proposed include use of quick algorithms for detection of FIDVR events and metrics for predicting dynamic behavior of the power system impacted by the detected FIDVR event. We show that, using a digital faster than real-time replica, the FIDVR event can be detected in required time and that the transient voltage deviation index (TVDI) can be quickly calculated.

AB - Predictive analysis of post fault system dynamic behavior can be a vital resource for better control and reliability improvement of the overall system. This article presents methods for predictive analysis of Fault Induced Dynamic Voltage Recovery (FIDVR) event using a faster than real-time digital replica of a power system. The methods proposed include use of quick algorithms for detection of FIDVR events and metrics for predicting dynamic behavior of the power system impacted by the detected FIDVR event. We show that, using a digital faster than real-time replica, the FIDVR event can be detected in required time and that the transient voltage deviation index (TVDI) can be quickly calculated.

KW - Fault Induced Dynamic Voltage Recovery (FIDVR)

KW - Phasor Measurement Unit (PMU)

KW - Short-Term Voltage Instability (STVI)

KW - Voltage Stability Indices (VSI)

KW - Faster Than Real-Time Digital Replica (FTRTDR)

KW - Transient Voltage Deviation Index (TVDI)

U2 - 10.1109/IECON.2018.8592818

DO - 10.1109/IECON.2018.8592818

M3 - Conference contribution

SP - 3582

EP - 3587

BT - Proceedings IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE

CY - Piscataway, NJ

T2 - IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

Y2 - 21 October 2018 through 23 October 2018

ER -

Prediction of Short-Term Voltage Instability Using a Digital Faster Than Real-Time Replica

Abstract

Conference

Bibliographical note

Keywords

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Cite this