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.