Title :
Clustering analysis of electric power user based on the similarity degree of load curve
Author :
Zhang, Cai-qing ; Wang, Ting
Author_Institution :
Dept. of Economic Manage., North China Electr. Power Univ., Baoding, China
Abstract :
The form of power load curve is important to demands side managing. The paper studies on the similarity of load curve, and set up the estimating concept on similarity of load curve - similar degree. And it designs clustering analysis method according to similar degree. Using this method the cluster analysis can be carried on the main electric power user in the electric power grid, finding out the users with important influence of regional load curve. So that, it can be directed against user load´s different influence with the peak valley disparity of regional load, determine to take different demands side managing measures to it, thus improve the form of regional load curve, optimize the purpose that the power system runs.
Keywords :
pattern clustering; power grids; clustering analysis; electric power; power load curve; Design methodology; Energy management; Pattern analysis; Power generation economics; Power measurement; Power system analysis computing; Power system management; Power system measurements; Power systems; Shape; Power system; clustering analysis; degree of similarity; load curve;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527184