Classification of power system stability using support vector machines

Christian Andersson, J E Solem, B Eliasson

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingResearchpeer-review

12 Citations (SciVal)

Abstract

The last years' blackouts have indicated that even when a lot of data is available, the operators at different centers do not take the proper actions in time. This depends partly on the reorganization of the centers after the deregulation and partly on the lack of reliable supportive applications when the system is close to instability. This paper uses a novel technique based on support vector machines, SVM, in order to classify, if the power system can withstand a (n-1)-fault during a variety of operational conditions. The support vectors can be used on-line in order to determine if the system is moving into dangerous conditions and support the operators on an early stage, so proper actions can be made. This paper also shows that the scaling of the variables is important for good results. A new technique for finding the most important variables to measure or supervise is also presented.
Original languageEnglish
Title of host publicationIEEE Power Engineering Society General Meeting, 2005
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Pages650-655
Volume1
DOIs
Publication statusPublished - 2005
EventIEEE Power Engineering Society General Meeting, 2005 - San Francisco, California, United States
Duration: 2005 Jun 122005 Jun 16

Publication series

Name
Volume1

Conference

ConferenceIEEE Power Engineering Society General Meeting, 2005
Country/TerritoryUnited States
CitySan Francisco, California
Period2005/06/122005/06/16

Subject classification (UKÄ)

  • Other Electrical Engineering, Electronic Engineering, Information Engineering

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