Evaluates comfort under blackout scenarios in residential buildings, suggesting improved resilience strategies.
Residential buildings are increasingly required to maintain suitable indoor conditions under both occupant-related activities and external disruptions such as blackouts. However, simplified building representations often fail to capture room-level thermodynamics, occupant behaviors, and their interactions with building energy systems in a unified and physically interpretable manner. This paper proposes a modular multi-zone white-box modeling approach for residential buildings that couples room-level building physics with configurable energy system components via a Python-to-Modelica workflow and explicitly incorporates occupant-related disturbances as model inputs. Its feasibility is demonstrated through a simplified three-zone residential case study under blackout conditions, comparing passive, buffer-supported, and PV/BESS/HP-supported configurations, highlighting the potential of the model as a flexible basis for occupant-aware comfort and resilience analysis in residential buildings.
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昊鎮 et al. (2026) studied this question.
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