Cross-over analysis of building-stock modelling approaches for bottom-up engineering model

In building stock modelling, several bottom-up methodologies have been developed to assess the energy demand and emission reduction potential of the stock but, often have transitional limitations to shift from aggregated to disaggregated stock boundary conditions. To further understand the limitations of various building-stock modelling approaches, this paper presents a comparison of three major bottom-up building stock-level methodologies, GIS-based, sample-based and sample-free synthetic models, to evaluate the accuracy and added-value of these approaches for use in bottom-up engineering model. The cross-over analysis has been implemented on Tokyo commercial building stock as a case study. The results show that sample-based synthetic approach leads to good agreement when compared to the energy demand estimations due to added-advantage of involving more extensive and wider range of micro-datasets.