スマートメータデータからの実需要推定による在・不在判定の精度改善手法

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2017/09/01

タイトル(英語): Improving Accuracy of Occupancy Detection by Estimating Actual Demand from Smart Meter Data

著者名: 服部　俊一（(一財) 電力中央研究所），篠原　靖志（(一財) 電力中央研究所）

著者名(英語): Shunichi Hattori (Central Research Institute of Electric Power Industry), Yasushi Shinohara (Central Research Institute of Electric Power Industry)

キーワード: 在・不在判定，スマートメータ，電力需要，非侵入型モニタリング　　Occupancy detection，Smart meter，Electricity demand，Non-intrusive load monitoring

要約(英語): In this paper, we propose high-accuracy occupancy detection using low-resolution electricity consumption data. In Japan, residential smart meters, which automatically read and transmit energy consumption data at each household to electric power companies, have started to be installed and will be set up in 80 percent of households by 2020. Occupancy detection is one of the major techniques leveraging electricity consumption data and is applicable various services such as ambient assisted living and peak load shifting. However, it is difficult to conduct high-accurate occupancy detection using the transmitted smart meter data because they are in 30-minute interval and truncated to 100Wh units. Especially, truncation makes difficult to analyze the change of demand by absence. Therefore, we propose a machine-learning based occupancy detection method combined with the estimation of the actual consumption from the truncated data using total variation regularization. In experiments, our method shows the performance is comparable to the result using the raw demand data in 1W unit.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.137 No.9 （2017） 特集：知能メカトロニクス分野と連携する知覚情報技術

本誌掲載ページ: 1296-1303 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/137/9/137_1296/_article/-char/ja/