About this Research Topic
Urbanization continues to demand innovative approaches to energy management, especially within the building sector, which is a substantial consumer of energy in cities. Current urban building energy models often deploy standard occupant schedules that fail to reflect the complex, dynamic nature of human behavior and its direct impact on energy use. This can lead to significant discrepancies between simulated outputs and actual energy consumption patterns. Furthermore, the gap in capturing dynamic occupant interactions contributes to increased uncertainty in simulations, prompting a need for models that can meticulously simulate these human factors.
This research topic aims to pioneer new methodologies for occupant-centric urban building energy modeling (UBEM) to enhance the precision and reliability of simulations. By developing models that accurately reflect the variability in occupant behavior, the project seeks not only to reduce the discrepancies in energy consumption data but also to provide a more credible foundation for developing energy efficiency strategies tailored to actual usage patterns.
To effectively refine occupant-centric UBEM, the scope of this research will focus on creating models that better integrate and process occupant-related data. We seek contributions that explore the following areas:
- Occupant-centric modeling approaches tailored to various UBEM objectives.
- The impact of occupant behavior on the accuracy of UBEM outcomes.
- Development of digital twins that incorporate dynamic occupant data.
- Leveraging AI to automate and enhance occupant-centric modeling.
- Architectural modeling that prioritizes occupancy data in UBEM.
- Exploration of the implications of occupant parameters in real-world UBEM applications.
By addressing these themes, the research will advance the field by decreasing the gap between modeled and actual building performance, ultimately leading to more effective energy management in urban environments.
This research topic aims to pioneer new methodologies for occupant-centric urban building energy modeling (UBEM) to enhance the precision and reliability of simulations. By developing models that accurately reflect the variability in occupant behavior, the project seeks not only to reduce the discrepancies in energy consumption data but also to provide a more credible foundation for developing energy efficiency strategies tailored to actual usage patterns.
To effectively refine occupant-centric UBEM, the scope of this research will focus on creating models that better integrate and process occupant-related data. We seek contributions that explore the following areas:
- Occupant-centric modeling approaches tailored to various UBEM objectives.
- The impact of occupant behavior on the accuracy of UBEM outcomes.
- Development of digital twins that incorporate dynamic occupant data.
- Leveraging AI to automate and enhance occupant-centric modeling.
- Architectural modeling that prioritizes occupancy data in UBEM.
- Exploration of the implications of occupant parameters in real-world UBEM applications.
By addressing these themes, the research will advance the field by decreasing the gap between modeled and actual building performance, ultimately leading to more effective energy management in urban environments.
Keywords: Occupancy modeling, Urban building energy modeling, Decarbonized cities, Data mining, Energy demand calculation, Energy management, Building control, Archetypes, Data modeling, Microclimate modeling, Thermal comfort, Pollutant dispersion
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
