The occupancy pattern, number of occupants in a certain space, and their dynamic variation with time are among the largest sources of uncertainty in the simulation results of urban building energy modeling (UBEM). The large size and complexity of cities pose ongoing and essential challenges in obtaining precise data on building occupancy. The current examination of this topic simply looks at the data source and the model, lacking of their scope of application or the influencing factors behind occupancy pattern. Based on the perspective of urban to building-scale, multi data sources and mobility models in all domains, along with potential factors that influence occupancy patterns were systematically reviewed in this study. Currently, there are two main challenges in occupancy pattern generation in UBEM: 1) difficulty in obtaining data with both accuracy and breadth, and 2) difficulty in developing occupancy pattern models through tradeoffs between model complexity, accuracy, and interpretability. Therefore, combination of multisource data should be employed to obtain a more accurate representation of occupancy pattern within a city and future research should establish fit-for-purpose framework to find the best modeling method for UBEM. What's more, the interpretable model considering comprehensive influencing factors should be further established. In conclusion, this study provides a series of suggestions for future advancements in obtaining accurate and interpretable occupancy patterns in UBEM.

A systematic review of occupancy pattern in urban building energy modeling: From urban to building-scale

Causone, Francesco;Ferrando, Martina;
2024-01-01

Abstract

The occupancy pattern, number of occupants in a certain space, and their dynamic variation with time are among the largest sources of uncertainty in the simulation results of urban building energy modeling (UBEM). The large size and complexity of cities pose ongoing and essential challenges in obtaining precise data on building occupancy. The current examination of this topic simply looks at the data source and the model, lacking of their scope of application or the influencing factors behind occupancy pattern. Based on the perspective of urban to building-scale, multi data sources and mobility models in all domains, along with potential factors that influence occupancy patterns were systematically reviewed in this study. Currently, there are two main challenges in occupancy pattern generation in UBEM: 1) difficulty in obtaining data with both accuracy and breadth, and 2) difficulty in developing occupancy pattern models through tradeoffs between model complexity, accuracy, and interpretability. Therefore, combination of multisource data should be employed to obtain a more accurate representation of occupancy pattern within a city and future research should establish fit-for-purpose framework to find the best modeling method for UBEM. What's more, the interpretable model considering comprehensive influencing factors should be further established. In conclusion, this study provides a series of suggestions for future advancements in obtaining accurate and interpretable occupancy patterns in UBEM.
2024
UBEM
Occupancy pattern
Urban data
Mobility
Theoretical models
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1277874
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