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A simulation-based framework for parametric energy renovation strategies in European buildings
Journal article   Open access   Peer reviewed

A simulation-based framework for parametric energy renovation strategies in European buildings

Maryam Fakhari, Ulrich Filippi Oberegger, Francesco Turrin and Roberto Lollini
Energy and Buildings, Vol.355, 116976
355
2026
Handle:
https://hdl.handle.net/10863/52392

Abstract

This study presents a simulation-based framework for evaluating energy renovation strategies across European building typologies and climate zones. A factorial parametric approach was used to simulate over 800,000 combinations of envelope assemblies, HVAC systems, and shading controls for three archetypes (single-family, multi-family, office) across five European climate zones under both current and projected (2050, RCP 8.5) weather conditions. A Rhinoceros/Grasshopper workflow generated an extensive, public simulation results framework, enabling evidence-driven renovation scenario exploration. The framework enables detailed assessment of both staged and deep renovation pathways by simulating envelopes and system upgrades in both isolated and combined configurations. Baseline models were calibrated using European building stock datasets, ensuring realistic energy performance with deviations within ± 10 % for residential cases. Results showed that retrofit solutions reduce space-heating demand higher than cooling demand. All outputs are compiled in an open-access platform that allows users to filter scenarios by building characteristics or performance targets. By integrating large-scale parametric simulation, empirical calibration, and climate change projections, this study offers a screening-level evidence base for comparing retrofit strategies across climates and building typologies. The framework provides a reproducible basis for prioritizing such strategies to support early-stage decision process through a performance-based transparent comparison among technology choices.
url
https://www.sciencedirect.com/science/article/pii/S0378778826000368View

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