Comparison of building modelling assumptions and methods for urban scale heat demand forecasting

Building energy evaluation tools available today are only able to effectively analyse individual buildings and usually either they require a high amount of input data or they are too imprecise in energy predictions at a city (district) scale because of too many assumptions made. In this paper, two tools based on 3D models are compared to see whether there is an approach that would probably be able to fit both – the amount of data available and the number of assumptions made. A case study in the German town of Essen was chosen in the framework of the research project WeBest, where six building types representing the most important building periods were analysed. The urban simulation tool SimStadt, an in-house development of HFT Stuttgart, based on 3D urban geometry, is used to calculate the heat demand for both single building scale and city district scale. The individual building typology results are compared with the commercial dynamic building simulation software TRNSYS. The influence of the availability and quality of data input regarding the geometrical building parameters on the accuracy of simulation models are analysed. Different Levels of Details (LoDs) of the 3D building models are tested to prove the scalability of SimStadt from single buildings to city districts without loss of quality and accuracy in larger areas with a short computational time