WIT Press

Buildings’ Energy Demand Modelling For Sustainable Decision Support


Free (open access)





Page Range

301 - 312




430 kb

Paper DOI



WIT Press


S. Fritz, J. Forster, N. Rab


The City of Vienna (Austria) follows a long-term initiative to be sustainable and affordable. Therefore the interdisciplinary fields of energy, buildings and infrastructure have to be analysed and connected in a virtual planning and decision support tool for stakeholders. In this context, this paper focuses on the development of the buildings energy demand and the interaction to the investments in the extension or expansion of existing district heating networks as district heating represents an energy efficient way to supply the cities heat demand. The extension of these networks and the increase of its share in heat supply allows replacing ecological inefficient heating technologies. Besides the ecological issues, also the economic feasibility is necessary to contribute to a sustainable city. Since the development of the buildings heat demand depends on the building owners investment decision, the methodological approach is divided in two parts: A simulation model, which brings out possible paths for the development of the buildings’ heat demand for various scenarios up to 2030 and an optimization model to determine investment plans for existing district heating networks, considering the development of the heat demand explicitly. The focus of this paper is on demonstrating the developed model. Therefore an analysis of the effects of subsidies regarding renovations and investments for decentralized usage of solar heat on the heating energy system is conducted. The result of the approach displays the optimal investments in the grid and the resulting effects on the whole heat market, i.e. the effects on the CO2-emissions, costs and share of all technologies, for different scenarios. The results can be visualized in a spatial simulation environment to support stakeholders in their decision process (URBEM-platform).


Buildings energy demand, heating energy system, district heating, decentralized solar heat, optimization, simulation