Our analyses were utilized, for instance, in the scientific study accompanying the Hydrogen Roadmap NRW, and can also be used to generate extensive scenario analyses in collaboration with the Integrated Transformation Strategies [BG1] team. A successful example is reported in the study, “Pathways for the Energy Transition.” Our clients and project partners are diverse – in addition to the public sector and scientific institutions, these include, in particular, grid operators, energy suppliers, industrial concerns, component developers, and also engineering firms. Through intensive cooperation between the teams of the Integrated Modeling and Strategies [BG2] and Energy Potential and Supply Paths groups [BG3], as well as Transportation Technologies and Future Mobility from our Technology Assessment and Networked Infrastructures [BG4] department, we are superbly positioned in terms of both depth and breadth. Feel free to contact us.

Cross-Sectoral Network Planning

Our model suite ETHOS enables us to consider the respective energy infrastructures for electricity, gas, hydrogen, and heat not only at high levels of individual detail but also across sectors and in an integrative manner. For this purpose, FINE.Infrastructure permits the model-based design of infrastructure components across several hundred regions and all relevant energy carriers at simultaneously high temporal resolutions. For this purpose, the model covers regionally-specified demand for electricity, gas, hydrogen, and district heating through the cost-optimized design and operation of the energy infrastructure and plants for power generation. The model is based on the open model generator. FINE. In addition, acceleration methods developed at the institute [BG1], e.g. for complexity reduction, as well as our extensive computing capacities, are used to gain especially detailed insights into integrated network planning via high-resolution modeling.

Power Grids

The EUROPOWER model enables the detailed load flow calculation of the European power transmission grid for studies spanning the present to the scenario-based view of the year 2050 and beyond, as required. In addition to the network load, the results also include the temporally- and spatially-highly-resolved balancing demand of renewable energy sources due to network bottlenecks, the plant deployment of generation and storage facilities, as well as possibilities for load-shifting. Zone and node prices can also be determined.

In addition to transmission grids, load flows in distribution grids at low and medium voltage levels can also be investigated. For this purpose, the dgnetz model maps the power flow in technical detail and provides results such as voltage stability, the utilization of the installed network components, any necessary regenerations, as well as network losses. For parameterization, the model can be combined with the OsmBuildTag tool, which can generate synthetic distribution grid data using publicly-available geo-information and an AI algorithm. In this way, we are even able to investigate realistic synthetic networks without real data available, which will be helpful in illuminating the future situation of the distribution network.

Gas and Hydrogen Networks

We also have a detailed model for gaseous energy transport, namely GFopt, which offers the capacity to realistically-calculate the load flow in the German gas transport network under explicit consideration of the pressure loss. For this purpose, the model includes not only the pipelines of the gas network, which are stored with strand-level accuracy but also compressor and pressure control stations. The investigations provide far-reaching results on network utilization, gas flows, operating pressures, and flow velocities for flexibly-generated network use cases; this is not only the case for natural gas but also for hydrogen as an energy carrier. In this manner, statements can be made regarding the consequences of a conversion of the gas networks from natural gas to the accommodation of hydrogen and in-depth knowledge about changes in network operation can be obtained. Our modeling approach is flexible enough to investigate in detail (inter)national, (supra)regional, and even local gas transport systems on a multiscale basis.