Establishing a reliable heating energy benchmark for urban buildings is essential for effective energy management, yet benchmark accuracy is often constrained by multiple building characteristics and uncertainty in energy prediction. This study investigated the influence of scale heterogeneity on the heating energy use intensity (EUI) of office buildings. A Bayesian surrogate model was developed, trained, and validated, yielding acceptable accuracy, with a CVRMSE of 12.37% and an NMBE of −1.02%, both within the limits recommended by ASHRAE Guideline 14-2023. The validated model was then used to simulate the heating EUI of office buildings with floor areas from 100 to 100,000 m2 under climatic conditions ranging from 3250 to 9698 HDD65. The results showed a clear inverse relationship between building scale and heating EUI. Smaller buildings were more sensitive to scale variation, with pronounced declines around 1000 and 3000 m2, while the decline rate weakened beyond 5000 m2. Climatic severity remained the dominant factor controlling the absolute level of heating demand, but the climatic differences in heating EUI gradually narrowed as building scale increased. Moreover, the scale effect persisted longer under colder climatic conditions. These findings provide a reference for establishing scale-sensitive heating energy benchmarks in urban public buildings.
Na et al. (2026) studied this question.