Effective and scalable methods for modelling existing non-domestic buildings and their HVAC systems under uncertainty continue to be instrumental in risk-conscious building performance assessment, recommissioning, and retrofit practice. This study makes such an attempt for large buildings with radiator system with a modelling method that builds upon detailed state space models of radiator-heated spaces, an archetype-based spatial reduction approach to modelling an entire building, a steady-state model of heat distribution subsystem, and explicit quantification of uncertainties in the above models. The capability and efficacy of the method were demonstrated by a case study on a building section on campus. The results show that the proposed method can effectively capture the detailed dynamic building heat transfer phenomena in individual spaces and is scalable to large complex buildings with moderate model complexity and computation cost.

在不确定的情况下，对现有非住宅建筑物及其HVAC系统进行建模的有效且可扩展的方法仍将在注重风险的建筑物性能评估，重新调试和改造实践中发挥作用。这项研究对具有散热器系统的大型建筑物进行了这样的尝试，其建模方法建立在散热器加热空间的详细状态空间模型的基础上，基于原型的空间缩减方法对整个建筑物进行建模，稳态的热量分布模型子系统，并明确量化上述模型中的不确定性。在校园的一个建筑区域进行了案例研究，证明了该方法的功能和有效性。