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WattShare: detailed energy apportionment in shared living spaces within commercial buildings

Published: 03 November 2014 Publication History

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.

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  • (2022)Real-Time Cooling Power Attribution for Co-Located Data Center Rooms with Distinct Temperatures and HumiditiesACM Transactions on Cyber-Physical Systems10.1145/34945786:1(1-28)Online publication date: 6-Jan-2022
  • (2021)AutoShare: Virtual community solar and storage for energy sharingEnergy Informatics10.1186/s42162-021-00144-w4:1Online publication date: 12-Jul-2021
  • (2021)A Data-driven System for City-wide Energy Footprinting and ApportionmentACM Transactions on Sensor Networks10.1145/343363917:2(1-24)Online publication date: 23-Jan-2021
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    cover image ACM Conferences
    BuildSys '14: Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings
    November 2014
    241 pages
    ISBN:9781450331449
    DOI:10.1145/2674061
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 03 November 2014

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    Author Tags

    1. energy disaggregation
    2. personal energy apportionment
    3. smart meters
    4. smartphones

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    View all
    • (2022)Real-Time Cooling Power Attribution for Co-Located Data Center Rooms with Distinct Temperatures and HumiditiesACM Transactions on Cyber-Physical Systems10.1145/34945786:1(1-28)Online publication date: 6-Jan-2022
    • (2021)AutoShare: Virtual community solar and storage for energy sharingEnergy Informatics10.1186/s42162-021-00144-w4:1Online publication date: 12-Jul-2021
    • (2021)A Data-driven System for City-wide Energy Footprinting and ApportionmentACM Transactions on Sensor Networks10.1145/343363917:2(1-24)Online publication date: 23-Jan-2021
    • (2020)Lessons from large scale campus deploymentProceedings of the Third Workshop on Data: Acquisition To Analysis10.1145/3419016.3431490(9-13)Online publication date: 16-Nov-2020
    • (2020)Real-Time Cooling Power Attribution for Co-Located Data Center Rooms with Distinct TemperaturesProceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3408308.3427607(190-199)Online publication date: 18-Nov-2020
    • (2019)Data-Driven Energy and Population Estimation for Real-Time City-Wide Energy FootprintingProceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3360322.3360847(267-276)Online publication date: 13-Nov-2019
    • (2018)A Scalable System for Apportionment and Tracking of Energy Footprints in Commercial BuildingsACM Transactions on Sensor Networks10.1145/321858214:3-4(1-25)Online publication date: 27-Nov-2018
    • (2017)ePrintsProceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments10.1145/3137133.3137150(1-10)Online publication date: 8-Nov-2017
    • (2017)Categorization framework and survey of occupancy sensing systemsPervasive and Mobile Computing10.1016/j.pmcj.2016.09.01938(1-13)Online publication date: Jul-2017
    • (2016)MotionSyncProceedings of the 3rd ACM International Conference on Systems for Energy-Efficient Built Environments10.1145/2993422.2993572(65-74)Online publication date: 16-Nov-2016
    • Show More Cited By

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