A virtual sensing approach to enhancing personalized strategies for indoor environmental quality and residential energy management

This study presents a consumer-centric approach on Demand-Side Management (DSM) for residential energy systems, aiming to align cost-efficient energy strategies with the individual's preferences on operational time-flexibility for residential electric appliances, thermal comfort, and indoor air...

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Bibliographic Details
Published in:Building and environment 2024-08, Vol.261, p.111684, Article 111684
Main Authors: Karatzas, Stylianos, Merino, Jorge, Puchkova, Alena, Mountzouris, Christos, Protopsaltis, Grigoris, Gialelis, John, Parlikad, Ajith Kumar
Format: Article
Language:English
Subjects:
Demand side management
Energy efficiency
Indoor air quality (IAQ)
Indoor environmental quality (IEQ)
Thermal comfort
Virtual sensing
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Summary:This study presents a consumer-centric approach on Demand-Side Management (DSM) for residential energy systems, aiming to align cost-efficient energy strategies with the individual's preferences on operational time-flexibility for residential electric appliances, thermal comfort, and indoor air quality. The optimization framework innovatively incorporates forecasts of the Indoor Air Quality (IAQ) index and thermal comfort levels using virtual sensing technology to predict their day-ahead values, which are furtherly integrated as constraints in the optimization problem. A dual-objective approach is employed, balancing the minimization of electricity costs all whilst increasing consumer's satisfaction. The approach underlines the critical role of consumer participation in DSM and illustrates how the integration of smart home technologies can lead to reductions in energy consumption and cost savings. This paradigm not only promotes consumer engagement in energy management but also showcases the potential of intelligent home systems to optimize energy usage while maintaining personalized comfort standards. [Display omitted] •Enhance user comfort and system efficiency through a consumer-centric DSM approach.•Align energy strategies with individual preferences, thermal comfort, and indoor air quality.•Employ virtual sensors to predict day-ahead values of IAQ and thermal comfort.•Optimize the scheduling of household appliances based on an Integer Linear Programming framework.
ISSN:0360-1323
1873-684X
DOI:10.1016/j.buildenv.2024.111684