Extraction of basic patterns of household energy consumption

Haoyang Shen*, Hideitsu Hino, Noboru Murata, Shinji Wakao

*この研究の対応する著者

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルProceedings - 10th International Conference on Machine Learning and Applications, ICMLA 2011
ページ275-280
ページ数6
DOI
出版ステータスPublished - 2011
イベント10th International Conference on Machine Learning and Applications, ICMLA 2011 - Honolulu, HI, United States
継続期間: 2011 12 182011 12 21

出版物シリーズ

名前Proceedings - 10th International Conference on Machine Learning and Applications, ICMLA 2011
2

Conference

Conference10th International Conference on Machine Learning and Applications, ICMLA 2011
国/地域United States
CityHonolulu, HI
Period11/12/1811/12/21

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 人間とコンピュータの相互作用

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