A study for clustering method to generate Typical Load Profiles for Smart Grid

Author

Kim, Young-Il ; Kang, Shin-Jae ; Ko, Jong-Min ; Choi, Seung-Hwan

Author_Institution

S/W Center, KEPCO Res. Inst., Daejeon, South Korea

fYear

2011

fDate

May 30 2011-June 3 2011

Firstpage

1102

Lastpage

1109

Abstract

Interests in green growth for environmental protection are recently increased and encourage research on Smart Grid to use power efficiently. Among interesting issues in this research, the methodology of data mining is an emerging issue which stands for utilizing power usage data collected every 15 minutes from customers for the computation of electricity rates. Load analysis method based on VLP (Virtual Load Profile) is used to create virtual 15 minutes power usage data for non-AMR (Automatic Meter Reading) customers with 15 minutes power usage data from AMR customers. In this paper, TLP (Typical Load Profile) generation method, hierarchical clustering, k-means clustering, fuzzy c-means clustering, and two-stage fuzzy clustering are investigated and their performance are also analyzed.

Keywords

data mining; environmental factors; fuzzy set theory; power engineering computing; smart power grids; statistical analysis; TLP generation method; VLP; automatic meter reading; clustering method; data mining; environmental protection; fuzzy c-means clustering; hierarchical clustering; k-means clustering; power usage data; smart grid; typical load profile; virtual load profile; Asia; Conferences; Decision support systems; Power electronics; Clustering; Smart Grid; Typical Load Profile; Virtual Load Profile;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Electronics and ECCE Asia (ICPE & ECCE), 2011 IEEE 8th International Conference on

Conference_Location

Jeju

ISSN

2150-6078

Print_ISBN

978-1-61284-958-4

Electronic_ISBN

2150-6078

Type

conf

DOI

10.1109/ICPE.2011.5944675

Filename

5944675