An overview of decision tree applied to power systems

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

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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.
TidsskriftInternational Journal of Smart Grid and Clean Energy
Udgave nummer3
Sider (fra-til)413-419
Antal sider7
StatusUdgivet - 2013

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