Rotor angle stability prediction using post-disturbance voltage trajectory patterns

A. D. Rajapakse, F. Gomez, O. M.K.K. Nanayakkara, P. A. Crossley, V. V. Terzija

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

8 Citations (Scopus)

Abstract

A novel method for predicting the rotor angle stability condition of a large power system immediately after a large disturbance is presented. The proposed two stage method involves a) estimation of the proximity of post-fault bus voltage trajectories after the disturbance to some pre-identified templates and b) prediction of the stability status using a classifier, which uses the proximity values calculated at different buses as inputs. The typical bus voltage variation patterns after a disturbance for both stable and unstable situations are identified from a database of simulations using the fuzzy c-means clustering algorithm. The same database is used to train the support vector machine classifier used in the second stage of the prediction process. Development of the transient stability prediction scheme and its performance were demonstrated using a case study carried out on the IEEE-39 bus system.

Original languageEnglish
Title of host publication2009 IEEE Power and Energy Society General Meeting, PES '09
PublisherIEEE Computer Society
Pages6
Number of pages1
ISBN (Print)9781424442416
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 IEEE Power and Energy Society General Meeting, PES '09 - Calgary, AB, Canada
Duration: 26 Jul 200930 Jul 2009

Publication series

Name2009 IEEE Power and Energy Society General Meeting, PES '09

Conference

Conference2009 IEEE Power and Energy Society General Meeting, PES '09
Country/TerritoryCanada
CityCalgary, AB
Period26/07/0930/07/09

Keywords

  • Fuzzy c-means clustering
  • Pattern recognition
  • Stability prediction
  • Support vector machines classifiers
  • Transient stability
  • Wide area protection

Fingerprint

Dive into the research topics of 'Rotor angle stability prediction using post-disturbance voltage trajectory patterns'. Together they form a unique fingerprint.

Cite this