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

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.