## 4 Discussion  
The literature review shows that substantial research and development of models for biogas production was carried out in the last 18 years. Regarding biogas modeling on a process level (anaerobic digestion), these models differ substantially from modeling biogas for potential analysis, GHG emissions and in an energy system. This is reflected in Tables 1 and 2: Table 2 (top-down) contains biogas model on process level that are not reflected in Table 1 (bottom-up) with models of potential analysis, GHG emissions and energy systems. This different modeling approach of the energy system and the AD perspective can broadly be regarded as top-down and bottom-up approaches, respectively.  
Dynamic biogas models contain detailed information about AD processes, technical systems and time-dependent conditions and, thus, generate a complexity that is not to be disregarded. This bottom-up modeling approach differs from the top-down modeling approach used in energy systems, LCA and GIS models. In these models, holistic effects are modeled on a national or regional level [37].  
Figure 5 shows the complexity of the mathematical mapping of biogas production within the discipline or view on the biogas system that the different studies represent.  
Many studies are available in the field of dynamic AD process modeling which deal with ADM1 at a high level of detail. These studies also published programs and source code, allowing great transparency of their results. In addition to complex AD process modeling, simplified AD models have been developed and applied many times. These are based partly on the well-known ADM1, but studies also developed simplified models without relying on ADM1 findings. They led to an easier use of AD models with less parameter input compared to ADM1. On a low-detail level (black box), ANNs were used for different types of problem description: Modeling the behavior of a specific plant, different feedstock conditions, or generating a black box model of the deeply detailed ADM1. Both detailed ADM1 and simplified AD models and black box models are applied for energy conversion and biogas control of full-scale biogas plants. Research in the area of dynamic process modeling is well penetrated in terms of both highly detailed and highly abstracted models, including the thermal behavior of digesters. Energy production models with a detailed and simplified AD process description were focused on studies including additional components, such as micro gas turbines with power electronics or CHP units.  
The field of top-down models that regard the biogas plant as part of a greater energy system, on the other hand, contains a very high proportion of black box assumptions regarding anaerobic biogas production. No publications that model the behavior of biogas production dynamically have been found within this literature study at the regional level or in energy system modeling. The top-down approaches are used to determine, capture and further process biogas potentials via simple linear equations. The picture is similar  
Figure 5: Classification of the references regarding their respective level of detail and field of application.  
in the area of GHG emissions. The prediction of GHG emissions was modeled mostly by including simple dependencies of biogas production. Only one publication was found that used a dynamic AD model (AMOCO) and is backed by LCA data to be able to reduce GHG emissions within a dynamic model.