A decision tree-based on-line preventive control strategy for power system transient instability prevention

Yan Xu, Zhao Yang Dong*, Rui Zhang, Kit Po Wong

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

31 Citations (Scopus)

Abstract

Maintaining transient stability is a basic requirement for secure power system operations. Preventive control deals with modifying the system operating point to withstand probable contingencies. In this article, a decision tree (DT)-based on-line preventive control strategy is proposed for transient instability prevention of power systems. Given a stability database, a distance-based feature estimation algorithm is first applied to identify the critical generators, which are then used as features to develop a DT. By interpreting the splitting rules of DT, preventive control is realised by formulating the rules in a standard optimal power flow model and solving it. The proposed method is transparent in control mechanism, on-line computation compatible and convenient to deal with multi-contingency. The effectiveness and efficiency of the method has been verified on New England 10-machine 39-bus test system. © 2014 Taylor and Francis.
Original languageEnglish
Pages (from-to)176-186
JournalInternational Journal of Systems Science
Volume45
Issue number2
DOIs
Publication statusPublished - 1 Feb 2014
Externally publishedYes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • decision tree
  • intelligent system
  • optimal power flow
  • preventive control
  • RELIEF
  • transient stability

RGC Funding Information

  • RGC-funded

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