Energy-efficient retrofits have become crucial in building sector as approximately 80% of buildings in developed countries are over 10 years old. Building simulation tools are now being used to provide estimates of energy consumption and implement various models which differ on the basis of enclosed details. Not all of these models are effective in terms of computation and the associated computational costs. This work devises a novel and generalized reduced-order grey-box modelling approach to predict the thermal behaviour of commercial buildings. The generalization approach reduces the order/complexity of model and lays out a general structure to obtain reduced-order models based on easily identifiable building metrics. We also implemented a forward-selection procedure to compare results obtained using a metrics-based approach. The network order obtained using metrics-based approach matches with the network order predicted by the forward selection procedure. The generalized structure would reduce the complexities involved in the dynamic simulation of urban building stock.

节能改造已成为建筑行业的关键，因为发达国家约80％的建筑已使用10年以上。建筑模拟工具现在用于提供能耗估算并实施各种模型，这些模型根据随附的详细信息而有所不同。在计算和相关的计算成本方面，并非所有这些模型都是有效的。这项工作设计了一种新颖的，广义的降阶灰箱建模方法来预测商业建筑的热行为。泛化方法降低了模型的顺序/复杂度，并基于可轻松识别的建筑指标设计了一种通用结构来获得降阶模型。我们还实施了前向选择程序，以比较使用基于指标的方法获得的结果。使用基于度量的方法获得的网络顺序与前向选择过程预测的网络顺序匹配。广义结构将减少城市建筑群动态模拟中涉及的复杂性。