Automated modelling of residential buildings and heating systems based on smart grid monitoring data

More than 60% of the energy is consumed in European households for space heating. Combined with the currently low renovation rate, the realization of the 2000Wsociety will be challenging. A fast and remote detection of optimal retrofitting targets may help to address this problem. In this contribution, a novel procedure to characterise a building and its heating systems from smart grid monitoring data is presented. The parameters of a simplified physical simulation model for the building and heating system are adjusted to match the simulated and the actual power consumption of the heat pump. The method is validated on three reference buildings with almost perfect reproduction of the heat consumption over the course of one year and good recovery of relevant building/heating system parameters. The application on five real-world buildings shows the possibility to reproduce the annual heat consumption within a maximal deviation of 5% in four out of five cases. These convincing results enable also the application of the developed procedure as a load prediction tool