Urban building energy model: Database development, validation, and application for commercial building stock

Abstract

Achieving citywide building energy reduction goals require extensive understanding of energy use at scale, which is challenging due to scarce and disparate data. Despite attention to urban building energy models (UBEM), unexplored aspects and missing details in this emerging field have remained, including further exploring non-homogenous commercial buildings, providing a detailed structure to create UBEMs for replication purposes, and developing methods to mitigate data scarcity and dependency. In this study, a structure is proposed using commercial buildings in Pittsburgh, Pennsylvania. We provide a description of an archetype library with relevant sources to improve reproducibility and describe a novel framework to create a database focusing on façade reconstruction through photogrammetry and image processing. For our UBEM, twenty archetypes that comprised eight commercial use types were identified. The average annual energy use intensity was estimated between 74 and 1302 kWh/m2 for different use types. The simulation results also showed discrepancy in energy use of the buildings with similar use types. Validating the results utilizing actual data revealed an overall 7% error. Employing the model to evaluate energy conservation strategies showed energy use reduction of 2–5% for the entire stock. Outcomes of this research can aid policy makers in instituting energy goals and efficiency regulations.