DocumentCode :
3399179
Title :
Data mining techniques application in power distribution utilities
Author :
Ramos, Sérgio ; Vale, Zita
Author_Institution :
Polytech. Inst. of Porto, Lisbon
fYear :
2008
fDate :
21-24 April 2008
Firstpage :
1
Lastpage :
8
Abstract :
This paper presents an electricity medium voltage (MV) consumer characterization framework supported on the data base knowledge discovery process (KDD). Data Mining (DM) techniques are used to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge concerning to the electric energy consumption patterns. In order to form the different customers´ classes a hierarchical clustering algorithm is used. The framework includes several steps, starting from the pre-processing data, application of DM algorithms, classification model, and finally, the interpretation of the discovered knowledge. To validate the proposed framework, a case study which includes real databases of MV consumers is used.
Keywords :
data mining; power distribution economics; power system analysis computing; data base knowledge discovery process; data mining techniques; electric energy consumption; hierarchical clustering algorithm; medium voltage consumer; power distribution utilities; Classification algorithms; Clustering algorithms; Contracts; Data mining; Databases; Delta modulation; Electricity supply industry; Energy consumption; Medium voltage; Power distribution; Classification; clustering; data mining; electricity markets; load profiles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transmission and Distribution Conference and Exposition, 2008. T&D. IEEE/PES
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-1903-6
Electronic_ISBN :
978-1-4244-1904-3
Type :
conf
DOI :
10.1109/TDC.2008.4517229
Filename :
4517229
Link To Document :
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