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The continuously increasing installed power of renewable energies causes strong changes in energy and especially electricity supply systems. With increasing share of intermittent renewable energy, it is becoming more and more difficult to compensate the areal and temporal mismatches of energy production and consumption. To increase the areal balancing, transmission and distribution system extension will be needed. The temporal balancing is a more complex issue to address because there are various technical options including demand side integration, import/export of energy, excess installation of renewable energy producing units, using excess energy for other sectors like the heating and transport sector and last but not least storing the energy during times of surpluses and providing it during times of shortages.

All these options will have a share in the final solution, but the particular share will still have to be defined. The question that has to be answered in the upcoming years is how much of each measure will be needed to fulfill the political goals of renewable energy integration and CO2 emissions on the one side and to maintain the system stability and the security of supply on the other side. The achievement of these goals has to be investigated against the background of economic considerations like minimum electricity generation costs. This can only be done by modeling the supply system under certain scenario assumptions.

This thesis presents the Energy System Optimization Studio (ESOS), a new tool for energy system modeling including technical as well as non-technical considerations and closing the gap between physics based system-dynamic models and projection models. With ESOS it is now possible to study the influence of different framework conditions (technical, economic and political) on the power plant dispatch, energy storage needs and operation strategies, load flows, CO2 emission and costs. In general, a transparent and reproducible approach to model energy supply systems is carried out, which up to date is still missing in research and literature. The simulation period can range from few hours to multiple years with a timely resolution of 15 minutes to one hour. Even when calculating periods of multiple years, ESOS allows the modelling of the integrated technologies with much details by using a rolling optimization approach.

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