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Identifying peer groups in a multifamily residential building for eco-feedback design.

Number: pap. 3651

Author(s) : HAM S. H., KARAVA P.

Summary

Heating and cooling energy consumption in residential buildings is the result of complex interactions of occupant behavior, weather, and building characteristics. Energy saving strategies require residents’ participation because they control energy consuming devices and pay the utilities. An effective way to increase this participation is to provide information on their household energy use, potential benefits, and incentives associated with the acceptance of energy-conserving behaviors. Energy comparison in a peer group, often called normative feedback, has been utilized in eco-feedback research to motivate people to reduce their energy use. Due to the variation of building characteristics, even among units in a multifamily residential building that are exposed to the same weather, it is difficult to make a fair comparison of the energy use attributed to behavior. In this paper, we present a Bayesian mixture model that is used to identify building groups with similar thermal characteristics. The model is developed using disaggregated energy use and temperature data from Wi-Fi-enabled power meters and smart thermostats collected in 31 apartments of a multi-unit residential building.

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Pages: 9

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Details

  • Original title: Identifying peer groups in a multifamily residential building for eco-feedback design.
  • Record ID : 30025057
  • Languages: English
  • Source: 2018 Purdue Conferences. 5th International High Performance Buildings Conference at Purdue.
  • Publication date: 2018/07/09

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