Spatial models as a basis of decision making for the utilisation of regionally available energy potentials for a CO2 neutral satisfaction of the local heat demand

Analytical GIS-methods to model regionally available renewable energy potentials for the evaluation of measures to achieve a CO2-neutral heating and cooling supply.

Short Description




More than the half of the energetic final consumption in Austria - as well as in Styria - is used for space heating, cooling, hot water preparation and process heating. The satisfaction of this energy demand is still dominated by fossil fuels. Bearing in mind the challenges of climate change or questions of security of supply, it is obvious that in the long term a rise of the use of renewable, regionally available energy sources will be necessary.

This project aims at the development of a model framework that is able to optimise and visualise the satisfaction of an existing energy demand for heating, cooling and hot water preparation within a defined region on a spatially and temporally highly disaggregated level. The developed model framework is applied to two testing regions (Murau and Steirisches Vulkanland). The influence of different parameters on the optimisation of the whole system and especially on the employed heating technologies is identified and analysed within five scenarios. Also the energy supply for cooling is considered, although in a more generic way. Furthermore effects of the resulting optimised setups of the regional energy system (regarding heating and cooling) on costs and greenhouse gas emissions are outlined.

The spatially explicit approach is based on methods of geographic information systems (GIS). The model concept developed consists of three modules, the potential model, the demand model and the dynamic demand satisfaction model. All three models operate on a spatial level of 250 m raster cells and have a temporal resolution of one calender month. With the potential model the regionally available renewable energy potentials from biomass, solar and the ambient are computed. The demand model provides the monthly energy demand for space heating, cooling and hot water preparation. With the dynamic demand satisfaction model, optimised scenarios for the satisfaction of this demand using different technologies are evaluated. The developed model framework serves as a basis for decision-making regarding the future development of a regional energy system, with an enhanced use of renewable energy sources. It thereby focuses on site-specific characteristics and their influence on an optimised regional energy system. An essential requirement in the development of the model concept was to make it easily transferable to other regions.

The data used for the visualisation of the current situation of the energy system in the testing regions is geographically explicit as well as spatially aggregated. Lack of statistic data due to availability in general and data privacy has been a substantial problem. While the energetic potentials can be modelled on the spatial level quite good, the computation and spatial assignment of the heating and cooling demand was a great challenge. Reference buildings were developed that show an individual heating and cooling demand dependent on building type and use, quality of building envelope and location. The actual demand was then assigned by spatial identification of the building stock (on basis of the statistical data) and allocation of the particular buildings to the reference buildings. The technologies for the satisfaction of the enery demand for space heating, cooling and hot water preparation considered in the project are included in the model using predefined reference technologies. The visualisation of currently used technologies on a spatially explicit level is also carried out by interpretation of statistical data.

The spatially explicit energy potentials, the demand and the current structure of the heating and cooling demand satisfaction are finally brought together in the dynamic demand satisfaction model. In five scenarios, based on different assumptions, an optimised adaptation of the energy system is computed under the aspect of system costs. On basis of the outcomes of the scenarios, a qualitative and quantitative assessment of measures (e.g. subsidies or costs for greenhouse gas emissions) can be performed and potential courses of action are outlined.

Project Partners

Project management

Dr. Markus Biberacher
Company: Research Studios Austria Forschungsgesellschaft mbH

Project or cooperation partner

  • Mag. Sabine Gadocha, Mag. Ingrid Schardinger, Mag. Daniela Zocher
    Research Studios Austria Forschungsgesellschaft mbH
  • DI Angela Dröscher, DI Dr. Richard Heimrath, DI Dr. Hermann Schranzhofer
    TU Graz, Institut für Wärmetechnik
  • DI Josef Bärnthaler
    Energieagentur Obersteiermark
  • Ing. Karl Puchas, DI Alois Niederl Lokale Energieagentur - LEA GmbH

In cooperation with

  • DI Wolfgang Jilek, Wolfgang Kleindienst
    Land Steiermark
  • DI Egon Dorner, DI Andreas Gößler
    Energie Steiermark AG

Contact Address

Research Studios - Studio iSPACE
Leopoldskronstraße 30
5020 Salzburg
Tel.: +43 (662) 834602-0

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