Evaluation of district heating potential at the territorial scale: validation of the BRUSA model

The study presents the BRUSA model, a scalable and replicable tool for estimating the annual heat demand of larger residential buildings stock using national census data. Unlike traditional bottom-up models, it calculates energy demand at the individual building level without relying on archetypes. The model incorporates specific details about building geometry, wall construction, heating systems and energy performance assumptions based on building construction periods and applicable regulations. This methodology ensures a simple yet efficient representation of energy demand, making large-scale energy planning more practical. The paper details the model's construction and validation using 170 buildings' annual thermal consumption data from eight heating seasons in Turin. The model has been validated at individual building, census section, and building aggregate levels, with a Mode of Percentage Error ranging from -1% to 14% at building level and a Mean Absolute Percentage Value of approximately 15% at aggregate level. By overcoming common limitations of archetype-based and high-data-requirement models, BRUSA offers a versatile tool for spatial energy planning. The paper presents a case study that uses the BRUSA model to assess the feasibility of developing a district heating system in an urban area, highlighting district heating systems' potential to support the energy transition. • Engineering-based models support effective and efficient energy planning. • Large datasets improve accuracy, overcoming archetype-based modelling limits. • BRUSA estimates residential thermal demand using detailed national census data. • Validated on real thermal data, BRUSA performs well across multiple spatial scales. • A case study tests BRUSA’s application in identifying areas for district heating.