An overview of decision tree applied to power systems

Leo Liu, Zakir Hussain Rather, Zhe Chen, Claus Leth Bak

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

The corrosive volume of available data in electric power systems motivate the adoption of data mining techniques in the emerging field of power system data analytics. The mainstream of data mining algorithm applied to power system, Decision Tree (DT), also named as Classification And Regression Tree (CART), has gained increasing interests because of its high performance in terms of computational efficiency, uncertainty manageability, and interpretability.
This paper presents an overview of a variety of DT applications to power systems for better interfacing of power systems with data analytics. The fundamental knowledge of CART algorithm is also introduced which is then followed by examples of both classification tree and regression tree with the help of case study for security assessment of Danish power system.
Original languageEnglish
JournalInternational Journal of Smart Grid and Clean Energy
Volume2
Issue number3
Pages (from-to)413-419
Number of pages7
ISSN2315-4462
Publication statusPublished - 2013

Keywords

  • Classification and regression tree
  • Data mining
  • Decision tree
  • Power system data analytics

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