DocumentCode :
3269017
Title :
Extraction of Basic Patterns of Household Energy Consumption
Author :
Shen, Haoyang ; Hino, Hideitsu ; Murata, Noboru ; Wakao, Shinji
Author_Institution :
Sch. of Sci. & Eng., Waseda Univ. Shinjuku, Tokyo, Japan
Volume :
2
fYear :
2011
fDate :
18-21 Dec. 2011
Firstpage :
275
Lastpage :
280
Abstract :
Solar power, wind power, and co-generation (combined heat and power) systems are possible candidate for household power generation. These systems have their advantages and disadvantages. To propose the optimal combination of the power generation systems, the extraction of basic patterns of energy consumption of the house is required. In this study, energy consumption patterns are modeled by mixtures of Gaussian distributions. Then, using the symmetrized Kullback-Leibler divergence as a distance measure of the distributions, the basic pattern of energy consumption is extracted by means of hierarchical clustering. By an experiment using the Annex 42 dataset, it is shown that the proposed method is able to extract typical energy consumption patterns.
Keywords :
Gaussian distribution; cogeneration; energy consumption; pattern classification; solar power; wind power; Gaussian distribution; basic pattern extraction; combined heat and power system; energy consumption pattern; heat and power cogeneration; hierarchical clustering; household energy consumption; power generation system; solar power; symmetrized Kullback-Leibler divergence; wind power; Approximation methods; Data models; Electricity; Energy consumption; Gaussian distribution; Renewable energy resources; Wind power generation; Gaussian mixture model; KL-divergence; energy consumption pattern; hierarchical clustering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4577-2134-2
Type :
conf
DOI :
10.1109/ICMLA.2011.68
Filename :
6147687
Link To Document :
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