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Identification de groupes de pairs dans un immeuble dans lequel résident plusieurs familles pour une conception avec rétroaction écologique.

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

Numéro : pap. 3651

Auteurs : HAM S. H., KARAVA P.

Résumé

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.

Documents disponibles

Format PDF

Pages : 9

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  • Prix public

    20 €

  • Prix membre*

    15 €

* meilleur tarif applicable selon le type d'adhésion (voir le détail des avantages des adhésions individuelles et collectives)

Détails

  • Titre original : Identifying peer groups in a multifamily residential building for eco-feedback design.
  • Identifiant de la fiche : 30025057
  • Langues : Anglais
  • Source : 2018 Purdue Conferences. 5th International High Performance Buildings Conference at Purdue.
  • Date d'édition : 09/07/2018

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