DocumentCode :
134046
Title :
Literature review on the applications of data mining in power systems
Author :
Kazerooni, M. ; Hao Zhu ; Overbye, Thomas J.
Author_Institution :
Dept. of ECE, Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
fYear :
2014
fDate :
Feb. 28 2014-March 1 2014
Firstpage :
1
Lastpage :
8
Abstract :
Power system is a highly interconnected network which delivers electric power to the electricity users. Sustaining the secure and reliable delivery of electric power requires continuous monitoring of the system. To process the large volumes of data obtained from the measuring devices, it is essential to investigate effective data enhancement techniques. In this paper, a comprehensive study on the applications of data mining in power systems is presented. Data visualization, clustering, outliers detection and classification are investigated as four major areas of data mining and related works in power systems which utilize each of these methods are presented in an organized and structured fashion.
Keywords :
computerised monitoring; data mining; data visualisation; electric power generation; power consumption; power system interconnection; continuous monitoring; data clustering; data enhancement techniques; data mining; data visualization; electric power; electricity users; interconnected network; outliers detection; power systems; Data mining; Data visualization; Layout; Power cables; Power system stability; Substations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Conference at Illinois (PECI), 2014
Conference_Location :
Champaign, IL
Type :
conf
DOI :
10.1109/PECI.2014.6804567
Filename :
6804567
Link To Document :
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