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

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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 languageEnglish
Title of host publicationProceedings IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages3582-3587
Number of pages6
ISBN (Electronic)978-1-5090-6684-1
Publication statusPublished - 2018
EventIECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society - Omni Shoreham Hotel, Washington D.C., United States
Duration: 21 Oct 201823 Oct 2018
Conference number: 44
http://www.iecon2018.org/

Conference

ConferenceIECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
Abbreviated titleIECON
CountryUnited States
CityWashington D.C.
Period21/10/1823/10/18
Internet address

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)

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