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iProgram: Inferring Smart Schedules for Dumb Thermostats

Published: 04 November 2015 Publication History

Abstract

Heating, ventilation, and air conditioning (HVAC) accounts for over 50% of a typical home's energy usage. A thermostat generally controls HVAC usage in a home to ensure user comfort. In this paper, we focus on making existing "dumb" programmable thermostats smart by applying energy analytics on smart meter data to infer home occupancy patterns and compute an optimized thermostat schedule. Utilities with smart meter deployments are capable of immediately applying our approach, called iProgram, to homes across their customer base. iProgram addresses new challenges in inferring home occupancy from smart meter data where i) training data is not available and ii) the thermostat schedule may be misaligned with occupancy, frequently resulting in high power usage during unoccupied periods. iProgram translates occupancy patterns inferred from opaque smart meter data into a custom schedule for existing types of programmable thermostats, e.g., 1-day, 7-day, etc. We implement iProgram as a web service and show that it reduces the mismatch time between the occupancy pattern and the thermostat schedule by a median value of 44.28 minutes (out of 100 homes) when compared to a default 8am-6pm weekday schedule, with a median deviation of 30.76 minutes off the optimal schedule. Further, iProgram yields a daily energy saving of 0.42kWh on average across the 100 homes. Utilities may use iProgram to recommend thermostat schedules to customers and provide them estimates of potential energy savings in their energy bills.

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Cited By

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  • (2023)Development of Smart HVAC Thermostat with AI Using Passive Infrared Sensors for Energy SavingProceedings of ASEAN-Australian Engineering Congress (AAEC2022)10.1007/978-981-99-5547-3_17(223-234)Online publication date: 18-Nov-2023
  • (2020)Energy saving impact of occupancy-driven thermostat for residential buildingsEnergy and Buildings10.1016/j.enbuild.2020.109791211(109791)Online publication date: Mar-2020
  • (2018)Do domestic heating controls save energy? A review of the evidenceRenewable and Sustainable Energy Reviews10.1016/j.rser.2018.05.00293(52-75)Online publication date: Oct-2018
  • Show More Cited By

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    cover image ACM Conferences
    BuildSys '15: Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments
    November 2015
    264 pages
    ISBN:9781450339810
    DOI:10.1145/2821650
    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 the author(s) 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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    Publication History

    Published: 04 November 2015

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    Author Tags

    1. electricity
    2. energy
    3. grid
    4. hvac

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    BuildSys '15 Paper Acceptance Rate 20 of 66 submissions, 30%;
    Overall Acceptance Rate 148 of 500 submissions, 30%

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    View all
    • (2023)Development of Smart HVAC Thermostat with AI Using Passive Infrared Sensors for Energy SavingProceedings of ASEAN-Australian Engineering Congress (AAEC2022)10.1007/978-981-99-5547-3_17(223-234)Online publication date: 18-Nov-2023
    • (2020)Energy saving impact of occupancy-driven thermostat for residential buildingsEnergy and Buildings10.1016/j.enbuild.2020.109791211(109791)Online publication date: Mar-2020
    • (2018)Do domestic heating controls save energy? A review of the evidenceRenewable and Sustainable Energy Reviews10.1016/j.rser.2018.05.00293(52-75)Online publication date: Oct-2018
    • (2017)Portable+Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/30900791:2(1-22)Online publication date: 30-Jun-2017
    • (2017)iScheduleProceedings of the Eighth International Conference on Future Energy Systems10.1145/3077839.3077846(132-142)Online publication date: 16-May-2017
    • (2016)SPOCKProceedings of the 3rd ACM International Conference on Systems for Energy-Efficient Built Environments10.1145/2993422.2993584(123-132)Online publication date: 16-Nov-2016
    • (2016)Non-intrusive model derivationProceedings of the Seventh International Conference on Future Energy Systems10.1145/2934328.2934330(1-11)Online publication date: 21-Jun-2016

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