Ammon, Mathias

The Tessif project, in the context of which this thesis was written, provides a software interface that enables an automated and standardized comparison of software for the modelling and optimization of energy supply systems. So far, Oemof and PyPSA are included and to which an energy system formulated in Tessif can be passed for optimization. The approach is based on two functions individually developed for the software model, to perform pre- and post-processing of all relevant components, parameters and data to realistically describe the energy system. Tessif is designed to compare the respective results, optimized with the same basis and to work out distinctive differences. The aim of this thesis is to integrate the software model FINE and to examine first results concerning an example energy system. The main task is to develop the individual functions for the automated transformation (es2es) as well as the standardized presentation of the results (es2mapping). Software for the optimization of energy systems usually makes use of five basic components (source, sink, energy conversion, storage and transmission). That serve to formulate and investigate a wide range of research topics. The intention of the translation is to automatically transform all components available in Tessif into the FINE specific interface and make them available for optimization. The second function to be developed enables the standardized presentation of the results. Relevant is detailed information about generation and load profiles, installed capacities as well as energy flow related emissions and costs. Finally, the total costs and emissions calculated during the optimization can be used as a basis for testing results of the respective software and making them initially comparable. In addition, a scenario analysis was carried out in this thesis, using an energy system specially developed for the comparison, in order to verify the function and results of FINE. Overall, it could be shown that the integration of FINE achieves approximately the same results as the integrations of Oemof and PyPSA and therefore is correctly integrated. Minor differences could be identified, analyzed and, if possible, adjusted to make the software models behave identically. In summary, initial results demonstrated that the capabilities of Tessif have been improved and, based on this, a recommendation can be formulated in the future to determine which software achieves the highest benefit in which scientific energy sector.

The present scientific work was created in context of the project Tessif which provides a comparison of different "Free Open Source Energy System Modelling Software" (FOSESMS). The thesis develops a statistical method to differ the in Tessif implemented FOSESMS based on their results. This uses various statistical analysis methods such as Pearson correlation and cross-correlation in combination with model errors such as mean absolute error, mean bias error and root mean square error. Within two scenario an exemplary application of the method is then tested using the software tools oemof and PyPSA.

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