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Heterogeneity and stochasticity, two main aspects of uncertainty in occupant behavior (OB), at the urban scale are not featured in most current urban building energy modeling (UBEM) platforms, and their respective impacts on urban-scale building energy consumption remain unclear. We aimed to introduce OB uncertainty into the UBEM workflow and assess the differences in the impacts of heterogeneity and stochasticity on cooling demand. Different OB models were integrated into the cooling demand simulation of residential building stocks, considering the heterogeneity and stochasticity in both occupancy and energy-use behavior. The impacts of heterogeneity and stochasticity on urban-scale cooling demand and its applications for different purposes in UBEM are discussed. We found that stochasticity in occupancy decreased the peak cooling demand by 54%, whereas the uncertainty in air-conditioning (AC) behavior had little effect. Heterogeneity is the main reason for the diversity in cooling demand, whereas stochasticity better reflects the dynamics of cooling demand., which Occupancy and AC behavior models with higher fidelity are required to obtain results with higher spatial or temporal resolution should be selected according to the UBEM applications. The proposed approach will contribute to the development of appropriate urban-scale occupant behavior models and bridge urban mobility with occupant-centric UBEMs. • Heterogeneity and stochasticity in both occupancy and AC behavior were considered. • Different impacts of heterogeneity and stochasticity in OB on UBEM was assessed. • The sufficient fidelities for OB models for different UBEM use cases were discussed. • Insights on developing appropriate OB models in occupant-centric UBEM were provided. [ABSTRACT FROM AUTHOR]

Urban building energy modeling (UBEM) is a promising tool to evaluate building energy consumption at high temporal-spatial resolution at urban scale. However, state-of-the-art UBEMs use identical building envelope thermal transmittance according to design specifications in model characterization, which neglects the uncertainty in U-values of the building stock. To evaluate the impacts of uncertainty in U-values on heating/cooling demand at the urban scale, this study proposes a physics-based model of building envelope thermal transmittance to generate the U-value distributions of building stocks. Diversified U-values were assigned to buildings according to the building age, while identical initial U-values in the design served as a baseline. The impact of uncertainty in building envelope U-values was assessed by comparing the heating/cooling demand simulated under different U-value distributions, taking 33,222 residential buildings in Beijing as a case study. The results showed that, considering uncertain physical factors, thermal transmittance followed a right-skewed distribution, which led to an increase in the heating/cooling demand of the building stock. The annual total heating/cooling demand increased by 26% and 13%, respectively. The diversity in the heating/cooling demand intensity of the building stock was enhanced when more causes of uncertainty were considered, which was more evident in the building stock with a small range of building age or heating demand intensity. Therefore, it is advisable to consider the uncertainty in the building envelope thermal transmittance in UBEM simulations for energy evaluation and planning at the district or urban scale. [ABSTRACT FROM AUTHOR]