The strong integration of volatile, renewable, decentralized production into the electricity grid, can bring the electrical system to its limits. On the one hand, by coupling existing infrastructures (electric-, gas-, district heating-networks), relief on the electrical system can be achieved. On the other hand, a reduction in the primary energy demand for the electricity and heating demand can be realised. In addition, storages provide an effective option to balance energy and power between the volatile, renewable production and consumption. These two approaches are investigated in a region, which is modelled in a way to represent the Austrian building-, living- and energy infrastructure-characteristics. Alternatively this region is called "model region". The goal of this work is the optimal placement and optimal operation of storage and conversion technologies. Therefore in this work the following parts are taken into account or are elaborated: *) The modelling of electric-, gas- and district heating-networks will be designed in a way so that they represent commonly used structures in Austria. For the electricity grid the Direct Current Load Flow (DCLF)-calculation is used, for mass flow networks (gas, district heating), the network representation is carried out in a way so that the (DCLF) method can be applied too. The linear load flow calculation has the disadvantage in that power losses cannot be considered directly; this problem is solved in this work with an additional linearisation of the losses. *) Based on statistical parameters each individual building is assigned to a building type (single-, double-, multi-family houses, apartment buildings and agriculture) and a construction year. The different building types are located within the region in a way that the structure represents an urban and rural area (e.g. line lengths and load densities). *) Realistically load profiles are achieved by an individual, annual, electrical and thermal load profile generation for each building, these profile generations are based on statistical parameters. *) For the production, the maximum roof Photovoltaic (PV)-potential and biomass-potential in the model region is determined and used in the optimisation. The placement and operation of the storage- and conversion-technologies will be optimised for a one year period. As a result, long-term (seasonal balancing) and short-term effects (daily balancing) are considered. For the implementation of a whole year simulation, three representative weeks (summer, winter and transitional period) are generated and used in the optimisation. The investigated scenarios are designed in a way, that three basic cases are considered: *) "technical"-case: only the technical limitations are considered and the storage- and conversion technology-demands are determined according these technical limitations. *) "whole region": in addition to the technical limitations, costs and revenues for the energy import or export at the slack node are considered. *) "ecological region": this case is similar to the "whole region". Only the energy import costs are increased by a factor of 100. The aim is, that the optimisation shall minimise energy imports and maximise the usage of the renewable produce energy within the region. A total of 31 scenarios are examined. These scenario variations are generated by changing various parameters. For example, the modified parameters are: costs of storage- or conversion-technologies, or consideration/variation of technical limitations (e.g. thermal line currents, maximum transformer loads). For those scenarios where the results have an particular influence at the electrical power system, results are up-scaled. Therefore the population ratio (between Austria and the model region) is used and energetic and power characteristics of the model region are scaled to the size of Austria and the impact on the Austrian electrical power system is determined.