In the paper, a method was developed to automatically dimensionalize and calculate central energy generation and supply scenarios with a district heating system for cities based on 3D building models in the CityGML format and their simulated heat demand. In addition, the roof geometry of every individual building is used to model photovoltaic energy generation potential. Two types of supply systems, namely a central heat pump (HP) system and a large co-generation (combined heat and power-CHP) system (both with a central storage and district distribution system), are modeled to supply the heat demand of the area under investigation. Both energy generation models are applied to a case study town of 1610 buildings. For the HP scenario, it can be shown that the case study town’s heat demand can be covered by a monovalent, low-temperature system with storage, but that the PV only contributes 15% to the HP electricity requirement. For the CHP scenario, only 61% of the heat demand can be covered by the CHP, as it was designed for a minimum of 4000 operating hours. Both the PV and the CHP excess electricity are fully injected into the grid. As a result, the primary energy comparison of both systems strongly depends on the chosen primary energy factors (PEF): with given German regulations the CHP system performs better than the HP system, as the grid-injected electricity has a PEF of 2.8. In the future, with increasingly lower PEFs for electricity, the situation reverses, and HPs perform better, especially if the CHP continues to use natural gas. Even when renewable gas from a power to gas (P2G) process is used for the CHP, the primary energy balance of the HP system is better, because of high conversion losses in the P2G process.

The importance of climate protection and sustainability is steadily increasing all over the world. However, there is a large potential for reducing emissions in the heating demand reduction and renewable heat supply of buildings that needs to be addressed. Therefore, a method was developed within the scope of this work that allows local decision-makers such as energy supply companies, project developers and the public sector to calculate, evaluate and compare different scenarios to make buildings and city districts more sustainable based on few and widely available input data. It includes both the determination of the heat demand and measures for its reduction as well as the selection and simulation of centralised and decentralised supply systems. A combination of different methods from the fields of geoinformatics, heuristic decision-making and object-oriented modelling is used. The latter forms a focal point in the work with the development of a data model for energy system components to enable automatic simulation. The applicability as well as the transferability of the method is shown in several case studies. Based on the simulations results, which can be related to CO₂emissions as well as costs, recommendations for the implementation of measures can be given and implemented.The paper is a summary of the dissertation with the title “Automatische Simulation von Wärmebedarf und -versorgung auf Quartiersebene” by the first author at Karlsruhe Institute for Technology.