A versatile clustering method for electricity consumption pattern analysis in households

Hideitsu Hino, Haoyang Shen, Noboru Murata, Shinji Wakao, Yasuhiro Hayashi

研究成果: Article査読

46 被引用数 (Scopus)

抄録

Analysis and modeling of electric energy demand is indispensable for power planning, operation, facility investment, and urban planning. Because of recent development of renewable energy generation systems oriented for households, there is also a great demand for analysing the electricity usage and optimizing the way to install electricity generation systems for each household. In this study, employing statistical techniques, a method to model daily consumption patterns in households and a method to extract a small number of their typical patterns are presented. The electricity consumption patterns in a household is modeled by a mixture of Gaussian distributions. Then, using the symmetrized generalized Kullback-Leibler divergence as a distance measure of the distributions, typical patterns of the consumption are extracted by means of hierarchical clustering. The statistical modeling of daily consumption patterns allows us to capture essential similarities of the patterns. By experiments using a large-scale dataset including about 500 houses' consumption records in a suburban area in Japan, it is shown that the proposed method is able to extract typical consumption patterns.

本文言語English
論文番号6484217
ページ(範囲)1048-1057
ページ数10
ジャーナルIEEE Transactions on Smart Grid
4
2
DOI
出版ステータスPublished - 2013 3 26

ASJC Scopus subject areas

  • Computer Science(all)

フィンガープリント 「A versatile clustering method for electricity consumption pattern analysis in households」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル