Application of sequential testing problem to online detection of transient stability status for power systems

Jhonny Gonzalez, Yerkin Kitapbayev, Tingyan Guo, Jovica V. Milanović, Goran Peskir, John Moriarty

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

We address the problem of predicting the transient stability status of a power system as quickly as possible in real time subject to probabilistic risk constraints. The goal is to minimise the average time taken after a fault to make the prediction, and the method is based on ideas from statistical sequential analysis. The proposed approach combines probabilistic neural networks with dynamic programming. Simulation results show an approximately three-fold increase in prediction speed when compared to the use of pre-committed (fixed) prediction times.

Original languageBritish English
Title of host publication2016 IEEE 55th Conference on Decision and Control, CDC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1536-1541
Number of pages6
ISBN (Electronic)9781509018376
DOIs
StatePublished - 27 Dec 2016
Event55th IEEE Conference on Decision and Control, CDC 2016 - Las Vegas, United States
Duration: 12 Dec 201614 Dec 2016

Publication series

Name2016 IEEE 55th Conference on Decision and Control, CDC 2016

Conference

Conference55th IEEE Conference on Decision and Control, CDC 2016
Country/TerritoryUnited States
CityLas Vegas
Period12/12/1614/12/16

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