Abstract
Physics-based building stock energy models (BSEMs), robust support tools for policymaking, play an important role in modeling time sequence electricity load profiles of the commercial sector. However, the conventional modeling approach, assisted by physics-based BSEM, inadequately considers the occupancy profiles of large populations and the heterogeneity of building systems, which could result in significant errors. To address this issue, this study proposes a novel framework of physics-based BSEM for modeling electricity load profiles in the commercial sector. The proposed framework incorporated both occupancy modeling, using travel survey data on daily travel patterns of the population, and stock modeling, to consider the heterogeneity of building systems within the physics-based BSEM. The methodology provided that (1) the reproducibility of occupancy presence schedules and electricity load profiles can be enhanced by the occupancy modeling; (2) building system stock modeling can improve the estimated electricity load profile. Moreover, the suggested method offers analytical capabilities for forecasting long-term variations in electricity load profiles and estimating the demand response potential of commercial building stocks.
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