Energy disaggregation based on semi-binary NMF

Masako Matsumoto, Yu Fujimoto, Yasuhiro Hayashi

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

The large-scale introduction of renewable energy resources will cause instability in the power supply. Residential energy management systems will be even more important in the near future. An important function of such systems is visualization of appliance-wise energy consumption; residents will be able to consciously avoid unnecessary consumption behavior. However, visualization requires sensors to measure appliance-wise energy consumption and is generally a costly task. In this paper, an unsupervised method for nonintrusive appliance load monitoring based on a semi-binary non-negative matrix factorization model is proposed. This framework utilizes the total power consumption patterns measured at the circuit breaker panel in a house, and derives disaggregated appliance-wise energy consumption. In the proposed approach, the energy consumption of individual appliances is estimated by considering the appliance-specific variances based on an aggregated energy consumption data set. The authors implement the proposed method and evaluate disaggregation accuracy using real world data sets.

本文言語English
ホスト出版物のタイトルMachine Learning and Data Mining in Pattern Recognition - 12th International Conference, MLDM 2016, Proceedings
出版社Springer Verlag
ページ401-414
ページ数14
9729
ISBN(印刷版)9783319419190
DOI
出版ステータスPublished - 2016
イベント12th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2016 - New York, United States
継続期間: 2016 7 162016 7 21

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9729
ISSN(印刷版)03029743
ISSN(電子版)16113349

Other

Other12th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2016
国/地域United States
CityNew York
Period16/7/1616/7/21

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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