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  4. A data-driven multivariate estimation of building heat demand: The case of the Canton of Vaud
 
conference paper

A data-driven multivariate estimation of building heat demand: The case of the Canton of Vaud

Romanelli, Giulio  
•
Castello, Roberto  
Waibel, Christoph
2025
International Scientific Conference on the Built Environment in Transition

According to the Horizon 2030 roadmap of the Canton of Vaud's Real Estate Strategy, increasing the energy efficiency of existing buildings is essential to achieve a zero-carbon balance by 2040, with an intermediate target of reducing CO2 emissions by 50-60% by 2030. In this context, precisely assessing and monitoring heat demand and greenhouse gas emissions is crucial. This paper presents an integrated methodology that leverages multiple publicly available datasets to reconstruct buildings' geometric and structural characteristics in the Canton of Vaud. The extracted features are then used to estimate building heat demand based on the SIA 380/1 (2009) standard. Results demonstrate that detailed reconstruction of building characteristics enables accurate heat demand estimations, with relative errors under 20% for buildings with standard geometries.

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Type
conference paper
DOI
10.1088/1742-6596/3140/4/042022
Scopus ID

2-s2.0-105027940109

Author(s)
Romanelli, Giulio  

EPFL

Castello, Roberto  

EPFL

Editors
Waibel, Christoph
Date Issued

2025

Publisher

Institute of Physics

Series title/Series vol.

Journal of Physics: Conference Series; 3140

ISSN (of the series)

1742-6596

1742-6588

Issue

4

Article Number

042022

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
SDSC-GE  
Event nameEvent acronymEvent placeEvent date
International Scientific Conference on the Built Environment in Transition

Hybrid, Lausanne, Switzerland

2025-09-03 - 2025-09-05

FunderFunding(s)Grant NumberGrant URL

Canton of Vaud

Available on Infoscience
January 29, 2026
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/258646
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