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

Takahiro Yoshida; Yoshiki Yamagata; Daisuke Murakami

doi:10.1016/j.egypro.2019.01.813

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

Takahiro Yoshida, Yoshiki Yamagata, Daisuke Murakami

Research output: Contribution to journal › Conference article › peer-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 language	English
Pages (from-to)	4172-4177
Number of pages	6
Journal	Energy Procedia
Volume	158
DOIs	https://doi.org/10.1016/j.egypro.2019.01.813
Publication status	Published - 2019
Externally published	Yes
Event	10th International Conference on Applied Energy, ICAE 2018 - Hong Kong, China Duration: 2018 Aug 22 → 2018 Aug 25

Keywords

Compositional kriging
Energy demand estimation
Populartime
Real time
Sumart community

ASJC Scopus subject areas

Energy(all)

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10.1016/j.egypro.2019.01.813

Cite this

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title = "Energy demand estimation using quasi-real-time people activity data",

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.",

keywords = "Compositional kriging, Energy demand estimation, Populartime, Real time, Sumart community",

author = "Takahiro Yoshida and Yoshiki Yamagata and Daisuke Murakami",

note = "Funding Information: This research was supported by the Join Research Program Numbers 698 and 827 at CSIS, the University of Tokyo and by the Energy Special Accounting of the Ministry of the Environment, Japan. Publisher Copyright: {\textcopyright} 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 - The 10th International Conference on Applied Energy.; 10th International Conference on Applied Energy, ICAE 2018 ; Conference date: 22-08-2018 Through 25-08-2018",

year = "2019",

doi = "10.1016/j.egypro.2019.01.813",

language = "English",

volume = "158",

pages = "4172--4177",

journal = "Energy Procedia",

issn = "1876-6102",

publisher = "Elsevier BV",

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TY - JOUR

T1 - Energy demand estimation using quasi-real-time people activity data

AU - Yoshida, Takahiro

AU - Yamagata, Yoshiki

AU - Murakami, Daisuke

N1 - Funding Information: This research was supported by the Join Research Program Numbers 698 and 827 at CSIS, the University of Tokyo and by the Energy Special Accounting of the Ministry of the Environment, Japan. Publisher Copyright: © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 - The 10th International Conference on Applied Energy.

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Compositional kriging

KW - Energy demand estimation

KW - Populartime

KW - Real time

KW - Sumart community

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DO - 10.1016/j.egypro.2019.01.813

M3 - Conference article

AN - SCOPUS:85063878872

VL - 158

SP - 4172

EP - 4177

JO - Energy Procedia

JF - Energy Procedia

SN - 1876-6102

T2 - 10th International Conference on Applied Energy, ICAE 2018

Y2 - 22 August 2018 through 25 August 2018

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

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