Journal Papers

Abstract: Urban building energy models (UBEM) are driving sustainable design and operations of cities by combining urban datasets with energy simulations. UBEMs are developed from a range of inputs on the spatial and semantic details of the buildings, and the

systems affecting their energy performance. Large geographical scales with finer spatio-temporal details increase the challenges of data processing for a reliable UBEM. Thus, it is essential to understand the impact of increasing the resolution of model inputs on the outputs to balance the efforts spent on model development, filling data gaps and maintaining the reliability of the results. This research introduces a Fit-for-Purpose modelling strategy and extends the concept of Levels of Detail (LoD) used for 3D models, to UBEM characteristics including occupancy, geometry, context, modelling methodology, and calibration with the proposed model characterisation framework. A case study based on a 0.3km2 area of Ahmedabad, India, is presented to demonstrate the framework. The results highlight a need for a higher LoD in occupancy modelling for the residential and educational buildings, whereas a higher LoD is more important for the commercial buildings’ envelope characteristics. These insights will enable a highly targeted supplementary data collection approach for the UBEM of the entire city.