Methodologies for Synthetic Spatial Building Stock Modelling: Data-Availability-Adapted Approaches for the Spatial Analysis of Building Stock Energy Demand

Claudio Nägeli (), Liane Thuvander, Holger Wallbaum, Rebecca Cachia, Sebastian Stortecky and Ali Hainoun
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Claudio Nägeli: Architecture and Civil Engineering Department, Chalmers University of Technology, 412 96 Gothenburg, Sweden
Liane Thuvander: Architecture and Civil Engineering Department, Chalmers University of Technology, 412 96 Gothenburg, Sweden
Holger Wallbaum: Architecture and Civil Engineering Department, Chalmers University of Technology, 412 96 Gothenburg, Sweden
Rebecca Cachia: Codema-Dublin’s Energy Agency, D02 TK74 Dublin, Ireland
Sebastian Stortecky: AIT Austrian Institute of Technology, 1210 Vienna, Austria
Ali Hainoun: AIT Austrian Institute of Technology, 1210 Vienna, Austria

Energies, 2022, vol. 15, issue 18, 1-18

Abstract: Buildings are responsible for around 30 to 40% of the energy demand and greenhouse gas (GHG) emissions in European countries. Building stock energy models (BSEMs) are an established method to assess the energy demand and environmental impact of building stocks. Spatial analysis of building stock energy demand has so far been limited to cases where detailed, building specific data is available. This paper introduces two approaches of using synthetic building stock energy modelling (SBSEM) to model spatially distributed synthetic building stocks based on aggregate data. The two approaches build on different types of data that are implemented and validated for two separate case studies in Ireland and Austria. The results demonstrate the feasibility of both approaches to accurately reproduce the spatial distribution of the building stocks of the two cases. Furthermore, the results demonstrate that by using a SBSEM approach, a spatial analysis for building stock energy demand can be carried out for cases where no building level data is available and how these results may be used in energy planning.

Keywords: building stock modelling; spatial building stock modelling; bottom-up model; synthetic building stock (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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