Energy demand estimation using quasi-real-time people activity data

Takahiro Yoshida, Yoshiki Yamagata, Daisuke Murakami

Research output: Contribution to journalConference articlepeer-review

6 Citations (Scopus)

Abstract

This study proposes an approach to estimate quasi-real-time electricity/energy demand in each commercial building using Google's Populartime data. The Populartime data records real-time human locations/activities that are collected from users of Google's maps on smartphones. The proposed approach considering changes by hour and by day of the week is applied to Sumida-ward, Tokyo, Japan. The result suggests the usefulness of our approach for energy demand monitoring considering quasi-real-time human activities.

Original languageEnglish
Pages (from-to)4172-4177
Number of pages6
JournalEnergy Procedia
Volume158
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event10th International Conference on Applied Energy, ICAE 2018 - Hong Kong, China
Duration: 2018 Aug 222018 Aug 25

Keywords

  • Compositional kriging
  • Energy demand estimation
  • Populartime
  • Real time
  • Sumart community

ASJC Scopus subject areas

  • Energy(all)

Fingerprint

Dive into the research topics of 'Energy demand estimation using quasi-real-time people activity data'. Together they form a unique fingerprint.

Cite this