Developing a regionalized representative building stock model for Germany

According to statistics, the German building sector is directly responsible for 16 % of the GHG emissions in the country (Fed eral Climate Protection Act), as well as roughly 40 % of the total final energy consumption. More than 70 % of heating rely on fossil fuels. The building sector is a key pillar of the green en ergy transition in Germany. To model the decarbonization of
the sector and support policymaking, a reliable and consistent representation of the heterogeneous buildings and technologies in the stock is needed. In this study, we develop a regionalized representative building stock model for Germany by making use of different sources, incl. (1) Census survey data at various geographic levels, (2) findings from the TABULA project about residential buildings, (3) non-residential building stock dataset (dataNWG) developed by the Institute for Housing and Envi ronment (IWU), (4) built environment data from the Global Human Settlement Layer (GHSL) varying from 10 m to 1 km geographic resolution, and (5) data from research papers and the public reports by IWU and the German Energy Agency (dena). As a result, the building stock model includes a popu lation of “representative buildings” (RBs), each of which has detailed information on its sector, type, construction period, geometry (surface area and orientation) and thermal efficiency (U-value) of components, heating system and technology, and location in terms of the NUTS 3 region and settlement types (e.g., urban center, sub-urban, rural cluster, etc.). The number of buildings that each RB represents is also estimated for aggre gating the results to different regional levels. Finally, the energy demand of the building stock model is calculated according to the simple hourly method of the DIN EN ISO 13790. The en ergy demand is then updated with user behavior parameters such as internal set temperatures, occupancy profiles etc. and heating system conversion efficiencies to obtain the final en ergy consumption. The final energy consumption is compared with the statistics in a base year at the national level. This rep resentative building stock model can serve as the foundation for developing agent-based energy demand projection models for the German building sector. Based on the high geographic resolution, such models have the potential to analyze the effects of the development of infrastructure, e.g., district heating net work and gas grid, on the transformation of the building stock.