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 modeling strategy and extends the concept of Levels of Detail (LoD) used for 3 D models, to UBEM characteristics including occupancy, geometry, context, modeling methodology, and calibration with the proposed model characterization framework. A case study based on a 0.3 km² area of Ahmedabad, India, is presented to demonstrate the framework. The results highlight a need for a higher LoD in occupancy modeling 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.

城市建筑能源模型 (UBEM) 通过将城市数据集与能源模拟相结合，正在推动城市的可持续设计和运营。UBEM 是根据对建筑物的空间和语义细节以及影响其能源性能的系统的一系列输入而开发的。具有更精细时空细节的大地理尺度增加了可靠 UBEM 数据处理的挑战。因此，必须了解提高模型输入分辨率对输出的影响，以平衡在模型开发、填补数据空白和保持结果可靠性方面的努力。本研究引入了适合用途的建模策略，并将用于 3D 模型的细节层次 (LoD) 概念扩展到 UBEM 特征，包括占用、几何、上下文、建模方法、并使用建议的模型表征框架进行校准。基于 0.3 公里的案例研究印度艾哈迈达巴德的²地区展示了该框架。结果表明，住宅和教育建筑的占用建模需要更高的 LoD，而更高的 LoD 对于商业建筑的围护结构特征更为重要。这些见解将为整个城市的 UBEM 提供具有高度针对性的补充数据收集方法。