Actual Consumption Estimation Algorithm for Occupancy Detection using Low Resolution Smart Meter Data

Shunichi Hattori, Yasushi Shinohara

Abstract

This paper proposes an actual consumption estimation algorithm that achieves highly accurate occupancy detection using electricity consumption data derived from smart meters. In Japan, electricity consumption data on households will soon be available because smart meters, which enable electric power companies to monitor how much electric power people are using in each household, have been installed in all households. Occupancy detection is a major technique that leverages electricity consumption data and can be applied to various services such as ambient assisted living, sales promotions, and peak load shifting. However, it is difficult to conduct high-accuracy occupancy detection using electricity consumption data automatically derived from smart meters because of their low resolution: 30-min intervals and 100 Wh increments. An actual consumption estimation algorithm is therefore proposed to generate data that reflects the characteristics of a household’s state from low-resolution smart meter data. Occupancy detection is implemented using the estimated consumption data, which are generated by the proposed algorithm, and the results of experiments show that its performance is improved compared to the result obtained using raw smart meter data.

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Paper Citation


in Harvard Style

Hattori S. and Shinohara Y. (2017). Actual Consumption Estimation Algorithm for Occupancy Detection using Low Resolution Smart Meter Data . In Proceedings of the 6th International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-211-0, pages 39-48. DOI: 10.5220/0006129400390048


in Bibtex Style

@conference{sensornets17,
author={Shunichi Hattori and Yasushi Shinohara},
title={Actual Consumption Estimation Algorithm for Occupancy Detection using Low Resolution Smart Meter Data},
booktitle={Proceedings of the 6th International Conference on Sensor Networks - Volume 1: SENSORNETS,},
year={2017},
pages={39-48},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006129400390048},
isbn={978-989-758-211-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - Actual Consumption Estimation Algorithm for Occupancy Detection using Low Resolution Smart Meter Data
SN - 978-989-758-211-0
AU - Hattori S.
AU - Shinohara Y.
PY - 2017
SP - 39
EP - 48
DO - 10.5220/0006129400390048