The City of Vienna (Austria) follows a long-term initiative to become a Smart City. Efficient, affordable and low-carbon energy systems, as well as environmentfriendly transport systems are obligatory to provide a sustainable development of a city. URSETA (Urban Strategic Energy and Transportation Analyses) is a decision support tool which is able to communicate the dynamics of a city system and shows the potentials of implementing sustainable energy and transport techniques. Based on the Geographic Information System (GIS) data of two representative areas, the energy system including different types of energy carriers (natural gas, electrical, thermal) is analysed by an energy hub model. The transport behaviour of the city system is examined by implementing an integrated, dynamic transport and land-use model. The optimal energy and heat supply of the future city is computed by a mixed integer linear optimization problem. Various sustainable strategies with a time horizon of 10 and 20 years are evaluated in the URSETA model. The obtained results are implemented in a spatial 3D model. This model features dynamic information visualisation in a virtual reality environment and enables access for different types of stakeholders.
The city of Vienna (Austria) follows a long-term initiative to be sustainable and affordable. This initiative is getting increasingly difficult due to a changing energy landscape and the aim to increase the usage of renewable energies. Additionally Vienna is a growing city. Current population forecasts predict a growth of the population which will pass the two million mark within 2029. Thus the requirements on space, infrastructure and support systems and therefore planners and decision makers are increasing. Concerning these issues, the paper focuses on the city's internal development potential as a basis for gaining new living and working areas. A model calculating the floor-area potential considering city development areas will be presented. This model establishes a basis for a simulation environment which is expandable via heating system models. The simulation environment is needed to test and visualize future scenarios. Thus it acts as an interactive, multi-scalar decision and planning support tool for interdisciplinary stakeholders. This generic approach aims to describe a process tool with the ability to be used in other cities and other disciplines.
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 CO 2-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).
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