## 3 Results
### Energy System Modeling  
Energy system models describe current and future energy systems considering scenarios to predict the possibilities of expanding renewable energy production. Therefore, the calculation of scenarios is based on time-dependent information, such as the energy potential of photovoltaic or wind, fluctuating energy demand as a result of day-ahead usage or changes of technologies, or varying energy prices on world markets [37]. A number of different mathematical environments and tools are described in literature for the modeling of energy systems, summarized in the review of [21]. The Open Energy Modelling Framework (Oemof) is one of the tools used for energy modeling [38]. It is based on Python and was developed as an open source tool to construct comprehensive energy system models. As an application, it was used in [39] to investigate the energy storage requirement for different degrees of self-sufficiency while regarding the electrical energy potential of photovoltaic, wind and biogas in a northwestern region of Germany (districts of Muenster, Osnabrueck and the city of Osnabrueck). Biogas, therefore, was considered as a fixed electrical energy potential of this region and included in the simulation either without energy storage or with the possibility of buffering its energy production for eight hours. Further studies [40] also used this approach of biogas integration in energy system modeling and showed that the region could reach a degree of self-sufficiency of 80% without installing any energy storage systems as a result of already installed renewable energies. A comprehensive fictional energy system, including wind turbines, photovoltaic, thermal solar and biogas for electricity and heat, was studied in [41]. Mathematical equations were solved by utilizing the Engineering Equation Solver [42]. Different scenarios were simulated with the use of thermal energy storage to obtain the possibility of heat buffering in times without solar radiation. In the case of biogas production, the energy input into the system simulation is based on a fixed mass-specific energy content of a fixed feedstock mixture consisting of chicken manure and maize silage; the CO2 emission reductions were calculated in comparison to fossil fuel sources. The simulation showed the possibility of producing electricity, hydrogen, cooling effects, hot air and hot water with renewable energies with an overall energetic efficiency of 64.9 to 71.1%. Modeling the potential of degradable wastes using Balmorel as a linear optimization and energy system model [43], Reference [44] developed an energy system model to simulate the waste to energy potential. Accordingly, annual energy potentials of agricultural wastes, forest residues, energy crops and municipal waste were taken from literature for Denmark, Germany, Finland, Norway, and Sweden, as well as their electricity and heat demands. In addition to biomass, the annual electrical energy potential of wind turbines was also included. Considering different technologies of waste conversion (waste incineration, co-combustion with coal, AD, gasification) and their costs (investment, operation, maintenance) led to the incineration of waste as the most economic feasible solution. Reference [14] included biomass as an annual energy potential of Denmark to evaluate the potential of biogas-derived fuels as raw biogas (used without purification), methane from biogas purification and methane from methanation with electrolytic hydrogen. Different sectors were modeled (power, heat, transport) using [45] under varying biomass costs. An hourly simulation achieved the use of raw biogas for electricity and district heat production as a result with the highest efficiency and lowest energy system cost.