Assessing data uncertainty in large-scale energy model

National building renovation plans are a central element of the newly approved Energy Performance of Buildings Directive (European Commission, 2024). This plan will offer a comprehensive overview of the energy and environmental performance of both residential and non-residential buildings. To effectively map the energy status of the urban building stocks, it is useful to analyse building typologies that represent various climatic zones, building uses, and construction periods.

Urban Building Energy Models (UBEMs) require vast amounts of data, which are often limited and inaccurate. Privacy policies significantly restrict data availability, impacting access to building information on a city-wide scale (HosseiniHaghighi et al., 2022; Johari et al., 2023). To address data uncertainty in large-scale energy analysis, collected data are used to create building archetypes (BAs). The BA approach strikes a balance between reducing complexity and enhancing the model’s accuracy in energy analysis. The energy performance certificates (EPCs) represent a core source of information to bridge the data uncertainty in large-scale analyses.

Given the significant data uncertainty associated with generating BAs, deeper analysis of the effects of key input data deviations on energy performance assessment is necessary. This study begins with the classification of data in UBEMs, aiming to identify the essential inputs required for large-scale urban energy analysis. It then reviews and categorises existing Italian databases that can be used to reduce the high uncertainty of input data.

The study involves generating probabilistic BAs based on EPCs from the Aosta Valley Region (Italy), which serves as a case study. A local large-scale sensitivity analysis was conducted, varying the thermo-physical parameters of the building fabric and the window-to-wall ratio of residential buildings in Aosta one-at-a-time. This analysis demonstrates how changes in the statistical ranges of inputs, in particular the performance of opaque building envelope components, affect the assessment of building energy needs.