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Modeling thermostat adjustment behavior in residential communities during eco-feedback energy interventions.

Number: 3577

Author(s) : GO J., KIM H., BILIONIS I., KARAVA P.

Summary

Eco-feedback interventions have been proven to positively impact user behavior toward heating and cooling energy conservation in the residential sector. Understanding human decision-making in thermostat adjustment during interventions enables policy makers (building operators or community managers) to anticipate occupant behaviors
and corresponding outcomes when planning and managing the intervention strategies. This paper presents a modeling methodology for deriving household decisions using MySmartE, an eco-feedback and social gaming platform designed to engage residents in understanding and reducing their home energy use. The proposed model is a utility
function that captures preferred heating setpoints in different smart thermostat modes (i.e., ‘home’, ‘sleep’, ‘away’, and ‘hold’) for different households. In this study, a social game with three levels of rewards was implemented in three different communities over a heating season. The parameters of the utility function were inferred using hierarchical Bayesian calibration with the collected household data. The results show that the developed model effectively captures the behavioral responses of residents for different reward sizes. It is proposed that this model serves as a foundation for decision simulation and energy intervention policy design.

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Pages: 10 p.

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  • Original title: Modeling thermostat adjustment behavior in residential communities during eco-feedback energy interventions.
  • Record ID : 30032907
  • Languages: English
  • Subject: Environment
  • Source: 2024 Purdue Conferences. 8th International High Performance Buildings Conference at Purdue.
  • Publication date: 2024/07/15

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