Feature extraction and classification using power demand information

Tomoya Imanishi, Rajitha Tennekoon, Hiroaki Nishi

研究成果: Conference contribution

5 被引用数 (Scopus)

抄録

Electrical load monitoring, by means of a smart meter, is getting more and more popular these days. Power demand information from smart meters is drawing attention among researchers, since it could be applied for power demand control. Providing attractive services with smart meters encourage electricity retailers to utilize demand side management, which could be a solution for energy-related problems in our society. In this paper, a novel service is proposed by classifying private information from the household electricity usage. The private information is estimated using feature vectors extracted from time series analysis of power demand information. In order to extract feature vectors effectively, two extraction methods were proposed: simple statistical method, and Discrete Fourier Transform (DFT) based extraction method. Then, Support Vector Machines (SVMs) classifier is carried out after the optimization of hyper-parameters. As the estimated information, both family structure and floor space were selected. The classification result is evaluated using F-measure and accuracy. As a result, the accuracy of DFT-based classification was superior to the statistical method for detecting the floor space in a house.

本文言語English
ホスト出版物のタイトル2016 IEEE International Conference on Smart Grid Communications, SmartGridComm 2016
出版社Institute of Electrical and Electronics Engineers Inc.
ページ92-97
ページ数6
ISBN(電子版)9781509040759
DOI
出版ステータスPublished - 2016 12 8
イベント7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016 - Sydney, Australia
継続期間: 2016 11 62016 11 9

出版物シリーズ

名前2016 IEEE International Conference on Smart Grid Communications, SmartGridComm 2016

Other

Other7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016
国/地域Australia
CitySydney
Period16/11/616/11/9

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • エネルギー工学および電力技術
  • 制御と最適化
  • 信号処理

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