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 |
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Pages (from-to) | 4172-4177 |
Number of pages | 6 |
Journal | Energy Procedia |
Volume | 158 |
DOIs | |
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)