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Knowledge about the demand of renewable thermal energy is essential for the integrated planning of sustainable cities. Planners and decision-makers need high-quality and comprehensive data for rapid and decisive action. However, little to no corresponding information is available for the status quo or possible development scenarios. Thus, new methods for urban building energy modelling and simulation with high resolution and accuracy are needed. In this paper, we present the research we conducted on the thermal energy demand of a city district in Graz, Austria. We developed a novel bottom-up, white box, multi-tool workflow for performing large-scale and high-resolution modelling, simulation and analysis of urban buildings in different development scenarios. We calculated the demand for heating, cooling and hot water in full-year dynamic building simulations and assessed the results quantitatively and spatially. Our results in the Scenario 2050 show that despite massive densification of the building stock by 88%, the calculated heat energy demand rises only by 4%; while the cooling demand soars by 432%. All results are available as hourly mean values and annual totals and in easy-to-understand spatial map representations, thus supporting stakeholders to meet the net-zero CO2-equivalent emission targets of Graz. [ABSTRACT FROM AUTHOR]

In this paper the development and application of an urban building energy simulation model is presented to analyse an existing 5th generation district heating and cooling network (5GDHC) with regard to possible sector coupling potentials. It was evaluated, how the heat energy production through large industrial heat pumps and the total thermal capacities of the 5GDHC network can provide flexibilities for power to heat applications. In a first step a multi model dynamic simulation was set up using the simulation environment IDA ICE. A previously developed urban energy simulation model formed the basis to implement the special requirements of the investigated 5GDHC network. This was followed by the calibration of the multi model simulation utilising the monitoring data of the existing 5GDHC network. In a second step the flexibilities of network sub areas were systematically investigated using step response tests. This was done with respect to key performance indicators like heat-up time or electrical energy consumption as a function of different boundary conditions like indoor comfort or outdoor air temperature. The third step comprised of a cumulative network analysis using different heating setpoint control strategies to optimise the operation of the network regarding heat production costs. • Sector coupling potentials of a 5th generation district heating and cooling network. • Novel district energy system model especially designed for the considered network. • Automated calibration of the simulation model using monitoring data of the existing network. • Systematic investigation of the network flexibilities with regard to specific KPIs. • Cumulative network analysis using a peak shaving control strategy for utilising additional profits. [ABSTRACT FROM AUTHOR]