There is a significant potential for reducing energy demand in the built environment. In order to make informed decisions regarding demand-side energy management strategies, it is helpful to simulate building energy demand at the urban scale as a function of building standards and operational strategies. Occupancy-related inputs significantly influence urban building energy simulations. It is essential to estimate the impact of occupants and their interaction with building systems on the efficiency of the building’s performance. Most existing urban-scale building energy models use fixed default occupant-related schedules that do not necessarily capture occupancy-related variation. It is primarily due to the lack of data available to model dynamic occupancy schedules that the problem arises. As a result, energy simulation results are often significantly different from the actual data. To reduce the uncertainty, it is essential to develop occupant-centric models connected with urban building energy simulation tools.
Building energy simulations usually require occupant-related schedules for different types of buildings to provide a more robust output. Depending on the simulation purpose, the level of detail of occupant-related data will vary. This research topic aims to develop novel methodologies for occupant-centric modeling for urban building energy simulation to reduce uncertainty. To do so, different approaches, including physics-based, data-driven, and hybrid models, could be exploited. Research objectives also include collecting, processing, and structuring the occupant-related data that could be extracted from various data sources and integrated with energy simulation tools.
To address the limitations and challenges of the occupant-centric UBEM, we encourage articles, reviews, and best practices, but not limited to the following themes:
1. Occupant-centric modeling for different UBEM purposes,
2. The role of occupant-centric digital twins in UBEM enhancement,
3. Automated occupant-centric models integrated with UBEM,
4. Application of AI in occupant-centric UBEM,
5. Archetype modeling for UBEM focusing on occupancy,
6. Impact of occupant-related parameters on the UBEM result.
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.
There is a significant potential for reducing energy demand in the built environment. In order to make informed decisions regarding demand-side energy management strategies, it is helpful to simulate building energy demand at the urban scale as a function of building standards and operational strategies. Occupancy-related inputs significantly influence urban building energy simulations. It is essential to estimate the impact of occupants and their interaction with building systems on the efficiency of the building’s performance. Most existing urban-scale building energy models use fixed default occupant-related schedules that do not necessarily capture occupancy-related variation. It is primarily due to the lack of data available to model dynamic occupancy schedules that the problem arises. As a result, energy simulation results are often significantly different from the actual data. To reduce the uncertainty, it is essential to develop occupant-centric models connected with urban building energy simulation tools.
Building energy simulations usually require occupant-related schedules for different types of buildings to provide a more robust output. Depending on the simulation purpose, the level of detail of occupant-related data will vary. This research topic aims to develop novel methodologies for occupant-centric modeling for urban building energy simulation to reduce uncertainty. To do so, different approaches, including physics-based, data-driven, and hybrid models, could be exploited. Research objectives also include collecting, processing, and structuring the occupant-related data that could be extracted from various data sources and integrated with energy simulation tools.
To address the limitations and challenges of the occupant-centric UBEM, we encourage articles, reviews, and best practices, but not limited to the following themes:
1. Occupant-centric modeling for different UBEM purposes,
2. The role of occupant-centric digital twins in UBEM enhancement,
3. Automated occupant-centric models integrated with UBEM,
4. Application of AI in occupant-centric UBEM,
5. Archetype modeling for UBEM focusing on occupancy,
6. Impact of occupant-related parameters on the UBEM result.
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.