A data-driven heuristic for corrective transmission switching

Xingpeng Li, Pranavamoorthy Balasubramanian, Kory Hedman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


Utilizing flexibility of the transmission network has gained significant attention recently. Prior efforts have shown that various benefits could be achieved by appropriately changing the network topology. This paper focuses on the reliability gains that can be achieved through corrective transmission switching (CTS). A full AC contingency analysis is conducted to identify critical contingencies that would result in violations. CTS is employed on these critical contingencies to test for violation reductions. A data-driven heuristic is proposed in this paper to identify the candidate switching list. This heuristic, also referred to as enhanced data mining (EDM) approach, provides a static lookup table consisting of corrective switching solutions, which is fast and effective. The lookup table can be created through a straightforward data mining technique. Simulations on the TVA system demonstrate the effectiveness and efficiency of the proposed heuristic.

Original languageEnglish (US)
Title of host publicationNAPS 2016 - 48th North American Power Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509032709
StatePublished - Nov 17 2016
Event48th North American Power Symposium, NAPS 2016 - Denver, United States
Duration: Sep 18 2016Sep 20 2016


Other48th North American Power Symposium, NAPS 2016
Country/TerritoryUnited States


  • Contingency analysis
  • corrective transmission switching
  • data mining
  • heuristic
  • large-scale power systems
  • lookup table
  • power system reliability

ASJC Scopus subject areas

  • Strategy and Management
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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