Abstract

Increasing energy consumption of commercial buildings has motivated numerous energy tracking and monitoring systems in the recent years. A particular area that is less explored in this domain is that of energy apportionment whereby total energy usage of a shared space such as a building is disaggregated to attribute it to an individual occupant. This particular scenario of individual apportionment is important for increased transparency in the actual energy consumption of shared living spaces in commercial buildings e.g. hotels, student dormitories and hospitals amongst others. Accurate energy accounting is a difficult problem to solve using only a single smart meter. In this paper, we present a novel, scalable and a low cost energy apportionment system called WattShare that builds upon our EnergyLens architecture, where data from a common electricity meter and smartphones (carried by the occupants) is fused, and then used for detailed energy disaggregation. This information is then used to measure the room-level energy consumption. We evaluate WattShare using a week long deployment conducted in a student dormitory in a campus in India. We show that WattShare is able to disaggregate the total energy usage from a single smart meter to individual rooms with an average precision of 96.42{\%} and average recall of 94.96{\%}. WattShare achieves 86.42{\%} energy apportionment accuracy which increases to 94.57{\%} when an outlier room is removed.

Bibtex

@inproceedings{Thakur:2014:WDE:2674061.2674069,
    author = "Thakur, Shailja and Saha, Manaswi and Singh, Amarjeet and Agarwal, Yuvraj",
    title = "WattShare: Detailed Energy Apportionment in Shared Living Spaces Within Commercial Buildings",
    pages = "30--39",
    year = "2014",
    booktitle = "Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings",
    doi = "10.1145/2674061.2674069"
}

Plain Text

Shailja Thakur, Manaswi Saha, Amarjeet Singh, and Yuvraj Agarwal. Wattshare: detailed energy apportionment in shared living spaces within commercial buildings. In Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings, 30–39. 2014. doi:10.1145/2674061.2674069.