DocumentCode :
2112020
Title :
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
Link To Document :
بازگشت