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http://dx.doi.org/10.7465/jkdi.2015.26.4.885

Functional clustering for electricity demand data: A case study  

Yoon, Sanghoo (WISE institute, Hankook University of Foreign Studies)
Choi, Youngjean (WISE institute, Hankook University of Foreign Studies)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.4, 2015 , pp. 885-894 More about this Journal
Abstract
It is necessary to forecast the electricity demand for reliable and effective operation of the power system. In this study, we try to categorize a functional data, the mean curve in accordance with the time of daily power demand pattern. The data were collected between January 1, 2009 and December 31, 2011. And it were converted to time series data consisting of seasonal components and error component through log transformation and removing trend. Functional clustering by Ma et al. (2006) are applied and parameters are estimated using EM algorithm and generalized cross validation. The number of clusters is determined by classifying holidays or weekdays. Monday, weekday (Tuesday to Friday), Saturday, Sunday or holiday and season are described the mean curve of daily power demand pattern.
Keywords
Electricity demand; functional clustering; number of cluster; time series data;
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Times Cited By KSCI : 9  (Citation Analysis)
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