Urban Building Energy Modeling (UBEM) plays a critical role in supporting data-driven strategies for the energy transition of cities. However, its application is often hindered by the lack of harmonized, high-quality input data representing the building stock. This paper presents the methodology and outputs of a national research project to construct an Italian library of reference buildings suitable for UBEM applications described with scorecards. The methodological workflow included six key phases: definition of a national data classification framework, acquisition and integration of heterogeneous data sources, data harmonization, statistical analysis and clustering, archetype formalization, and dissemination. The result is a library of 380 scorecards covering residential, educational, office, commercial, and catering buildings across multiple climate zones and construction periods. Each scorecard is based on empirical data from public databases, field surveys, or technical standards, and includes detailed descriptions of geometry, envelope characteristics, HVAC systems, internal gains, and ventilation. The scorecards are shared openly on the project’s website and were built to work with different UBEM platforms. Overall, both the method and the results help bring more consistency to UBEM practice and support better, data-driven urban energy planning.

The recently issued Energy Performance of Building Directive (EU 2024/1275) emphasises the importance of national building renovation plans, achievable by integrating building archetypes with Urban Building Energy Modelling (UBEM). However, UBEMs are often uncalibrated or unvalidated, and building archetypes are typically derived from energy certificates, which are known to have quality limitations. This research aims to assess the representativeness and reliability of data within building archetypes through a validation procedure, enhancing model credibility. Specifically, the proposed methodology introduces two new KPIs—the Validity of Representativeness Hours ( VRH ) and the Percentage of Representativeness Hours ( PRH )—to evaluate how closely simulated energy demand aligns with real-energy consumption data within a defined tolerance range, given a set of inputs derived from the probabilistic building archetype schema. This methodology was applied to a residential case study in the municipality of Turin (Italy), composed by more than 300 apartment blocks and modelled in CitySim Pro. The validation procedure successfully identifies the most representative building archetype data, shaping and capturing the real energy performance of the building stock.

Urban populations are exposed to elevated local temperatures compared to surrounding rural areas due to the urban heat island (UHI) effect, which increases health risks and energy demand. The literature highlights that accurately quantifying UHIs at broader territorial scales remains challenging because of limited microscale climate data availability and, at the same time, the difficulty of increasing the spatial coverage of the outcomes. Within the PRIN2022-PNRR CRiStAll (Climate Resilient Strategies by Archetype-based Urban Energy Modeling) project, this work addresses these limitations by coupling Urban Building Energy Modeling with archetype-based representation of urban form and high-resolution climatic data. Urban archetypes are defined as representative microscale configurations derived from combinations of urban canyon geometries and building typologies, accounting for different climatic zones, use categories, and construction periods. The proposed methodology was applied to the city of Turin (Italy), where representative urban blocks were identified and modeled to evaluate key urban context metrics under short-, medium-, and long-term climate scenarios. The UHI effect was assessed using Urban Weather Generator, while energy simulations were performed with CitySim. The urban archetype approach enables both fine spatial resolution and extensive spatial coverage, supporting urban-scale mapping.

The European building sector significantly contributes to the EU’s greenhouse gas reduction goals, with the 2024 Energy Performance of Buildings Directive (EPBD) aiming to achieve a decarbonised building stock by 2050. By focusing on an existing office building representative of the Italian building stock, this research evaluates various energy efficiency measures and integrates renewable energy systems to transform the building into a Zero-emission Building (ZeB). Moreover, it also utilises future weather data to address the effects of climate change. Results highlight the actions needed for an empirical ZeB transition, offering insights into challenges and key performance indicators across different intervention scenarios. The findings contribute to establishing national ZeB standards, emphasising the importance of the national building renovation plan in compliance with the EPBD recast requirements.