Title :
A method for classification of electricity demands using load profile data
Author :
Yu, In Hyeob ; Lee, Jin Ki ; Ko, Jong Min ; Kim, Sun Ic
Author_Institution :
Korea Electr. Power Res. Inst., South Korea
Abstract :
The multiple participants of the electricity market need new business strategies for providing value added services to customer. Therefore they need the accurate customer information about the electricity demand. Demand characteristic is the most important one for analyzing customer information. In this study, load profile data, which can be collected through the automatic meter reading system, are analyzed for getting demand patterns of customer. The load profile data include electricity demand in 15 minutes interval. An algorithm for clustering similar patterns is developed using the load profile data. As results of classification, representative curves for the same groups are generated. The demand characteristics of the groups are discussed. Also, the compositions of demand contract and industrial classification in each group are presented.
Keywords :
customer profiles; load distribution; metering; pattern clustering; power markets; power system economics; automatic meter reading system; business strategy; customer information; demand contract; electricity demand; electricity market; industrial classification; load profile data; pattern clustering; value added services; Information science;
Conference_Titel :
Computer and Information Science, 2005. Fourth Annual ACIS International Conference on
Print_ISBN :
0-7695-2296-3
DOI :
10.1109/ICIS.2005.11