Investigating the sustainable design of a shipping container building using advanced building energy modeling and Bayesian inference

Modular buildings demonstrate environmental benefits in raw material usage but vary in energy performance by climate. Our research evaluates the energy performance of a modular educational building by calibrating a Building Energy Model (BEM) with operational data and Bayesian inference. As expected, this case study reveals that energy model calibration is not required when sufficient knowledge about the building is available.

Furthermore, our CMV schedule is essential information, and its omission leads to an uncalibrated model. Although calibrating the degraded model meets ASHRAE standards, the original model remains more accurate. Finally, implementing seasonal modeling that aligns with the building’s annual dynamics is a promising enhancement, though it requires more data.