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