User-centric urban energy modelling: A reduced order model approach based on pre-calibrated archetypes dataset

• A scalable urban energy modelling framework integrating ROMs and user occupancy dynamics. • End-user archetypes derived from detailed white-box models and national TUS data. • Compact RC models pre-calibrated to simulate urban-scale energy demand. • The framework supports multi-domain analysis, and energy planning for building clusters. Significant efforts have been directed by governments and international organizations towards establishing sustainable development programs for cities and communities to facilitate the urban energy transition, encountering challenges in evolving towards a cleaner and more resilient energy system. In support of designing and operating such sustainable energy systems, the development of appropriate modelling frameworks becomes crucial. These frameworks should enable the identification of renovation priorities and the formulation of innovative energy management schemes, business models, and insights for self-sustaining urban districts or communities. The core of implementing sustainable energy hubs in an urban context is undergoing as well as modelling the end-users’ energy demand and their interaction with the hub. This study presents a modelling approach to unlock some of the main challenges encountered in urban energy demand simulation with a perspective to user-centric modelling framework. Specifically, a urban energy demand modelling framework integrating building Reduced Order Models with end-user occupancy dynamics to provide a scalable and comprehensive solution is developed. The method leverages archetype end-user categories derived from detailed white-box building simulations and Time-of-Use Survey data, creating a framework for generating Resistance-Capacitance-based datasets applicable to urban-scale simulations. By capturing complex heat transfer dynamics, the approach facilitates scalability from individual buildings to large clusters. The approach is tested through a proof-of-concept simulation, and it is considered a valid tool to conduct multi-domain analysis and to support the development of building clusters and community energy renovation.

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Publication Details

Journal
Energy and Buildings
Published
2025-04-19
DOI
https://doi.org/10.1016/j.enbuild.2025.115768
Citations
12
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
12.08

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article

User-centric urban energy modelling: A reduced order model approach based on pre-calibrated archetypes dataset

Roberto Stasi, Annamaria Buonomano, G. Russo, Giovanni Francesco Giuzio et al.
12 citations
Energy and Buildings
Building Energy and Comfort Optimization
12.08
article

User-centric urban energy modelling: A reduced order model approach based on pre-calibrated archetypes dataset

Roberto Stasi, Annamaria Buonomano, G. Russo, Giovanni Francesco Giuzio, Giuseppe Cipolla, Laura Pompei
article en
12 citations

Abstract

• A scalable urban energy modelling framework integrating ROMs and user occupancy dynamics. • End-user archetypes derived from detailed white-box models and national TUS data. • Compact RC models pre-calibrated to simulate urban-scale energy demand. • The framework supports multi-domain analysis, and energy planning for building clusters. Significant efforts have been directed by governments and international organizations towards establishing sustainable development programs for cities and communities to facilitate the urban energy transition, encountering challenges in evolving towards a cleaner and more resilient energy system. In support of designing and operating such sustainable energy systems, the development of appropriate modelling frameworks becomes crucial. These frameworks should enable the identification of renovation priorities and the formulation of innovative energy management schemes, business models, and insights for self-sustaining urban districts or communities. The core of implementing sustainable energy hubs in an urban context is undergoing as well as modelling the end-users’ energy demand and their interaction with the hub. This study presents a modelling approach to unlock some of the main challenges encountered in urban energy demand simulation with a perspective to user-centric modelling framework. Specifically, a urban energy demand modelling framework integrating building Reduced Order Models with end-user occupancy dynamics to provide a scalable and comprehensive solution is developed. The method leverages archetype end-user categories derived from detailed white-box building simulations and Time-of-Use Survey data, creating a framework for generating Resistance-Capacitance-based datasets applicable to urban-scale simulations. By capturing complex heat transfer dynamics, the approach facilitates scalability from individual buildings to large clusters. The approach is tested through a proof-of-concept simulation, and it is considered a valid tool to conduct multi-domain analysis and to support the development of building clusters and community energy renovation.

Energy and BuildingsVol. 339
Free University of Bozen-Bolzano (IT), Polytechnic University of Bari (IT), University of Naples Federico II (IT), Sapienza University of Rome (IT)
Ministero dell’Istruzione, dell’Università e della Ricerca, Ministero dell'Università e della Ricerca
Sustainable cities and communities
Openalex Percentile: Top 1%
Building Energy and Comfort Optimization
12.08
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