Methods for optimisation, simulation and modeling of combined grid systems
The increasing shortage of fossil fuels as well as the continuing climate change leads to an increasing relevance of renewable energy. The control and structural expansion of decentralized energy systems are rather complex. Due to the fact that the heat demands as well as the yield of renewable energies such as photovoltaic are charac-terized by seasonal fluctuations, long-term studies at least over one year are re-quired. Beside such low-frequency alterations, dynamic fluctuations e.g. due to cloud movements occur which requires a high temporal resolution of the problem. The conceptual synthesis of such systems incorporates an optimization of the structure, design and operation. Due to the fact that a variation of the structure influences the design and operation of the system, a holistic investigation considering these three levels is required. Furthermore, the stochastic behavior of the renewable energies includes an additional uncertainty regarding the design and operation of these sys-tems. Summing up, it becomes obvious that such long-term investigations with a high temporal resolution require a high computational effort.
Therefore, novel methods for investigating such optimization problems are developed in this thesis also considering the computational effort. In order to achieve a simple adaption to different problems and various structures, a generic applicability of the methods is intended.