2017Unpublished venueRequires access

Communicating thermostats as a tool for home energy performance assessment

Michael Zeifman, Kurt Roth, Bryan Urban

Open publisher page 5 citations

Abstract

Communicating thermostats (CTs) can provide a stream of home data, e.g., room temperature and status of heating, ventilation and air conditioning (HVAC) system to participating utility companies. We show how these data can be used to estimate physical home parameters that represent such major categories of home energy performance as wall insulation, air infiltration and HVAC efficiency. The estimation is based on a coarse-grained physics based modeling technology that connects weather data and household thermal comfort preferences with CT data through these parameters. The proposed method is scalable and can be automatically applied to numerous households to identify home improvement opportunities.

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What this paper is about

Communicating thermostats (CTs) can provide a stream of home data, e.g., room temperature and status of heating, ventilation and air conditioning (HVAC) system to participating utility companies. We show how these data can be used to estimate physical home parameters that represent such major categories of home energy performance as wall insulation, air infiltration and HVAC efficiency. The estimation is based on a coarse-grained physics based modeling technology that connects weather data and household thermal comfort preferences with CT data through these parameters. The proposed method is scalable and can be automatically applied to numerous households to identify home improvement opportunities.

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OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Communicating thermostats (CTs) can provide a stream of home data, e.g., room temperature and status of heating, ventilation and air conditioning (HVAC) system to participating utility companies. We show how these data can be used to estimate physical home parameters that represent such major categories of home energy performance as wall insulation, air infiltration and HVAC efficiency. The estimation is based on a coarse-grained physics based modeling technology that connects weather data and household thermal comfort preferences with CT data through these parameters. The proposed method is scalable and can be automatically applied to numerous households to identify home improvement opportunities.

Key concepts: Thermostat, HVAC, Air conditioning, Thermal comfort, Scalability, Computer science, Efficient energy use, Architectural engineering

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